From 79109f311c55756c3a515e734addef7a3f0335a4 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Mon, 5 Aug 2024 17:55:49 +0530 Subject: [PATCH 01/46] Added new option "RLparallel" to ImageDeconvolution.deconvolution_algorithm_classes --- cosipy/image_deconvolution/RLparallel.py | 334 +++++++++++++++ .../image_deconvolution.py | 3 +- ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 387 +++++++++++++++--- .../511keV/GalacticCDS/inputs_511keV_DC2.yaml | 2 +- 4 files changed, 663 insertions(+), 63 deletions(-) create mode 100644 cosipy/image_deconvolution/RLparallel.py diff --git a/cosipy/image_deconvolution/RLparallel.py b/cosipy/image_deconvolution/RLparallel.py new file mode 100644 index 00000000..8b2510be --- /dev/null +++ b/cosipy/image_deconvolution/RLparallel.py @@ -0,0 +1,334 @@ +import os +from pathlib import Path +import copy +import logging +logger = logging.getLogger(__name__) + +# Import third party libraries +import numpy as np +from mpi4py import MPI +import h5py +from histpy import Histogram + +from .deconvolution_algorithm_base import DeconvolutionAlgorithmBase + +class RLparallel(DeconvolutionAlgorithmBase): + """ + A class for a parallel implementation of the Richardson- + Lucy algorithm. + + An example of parameter is as follows. + + iteration_max: 100 + minimum_flux: + value: 0.0 + unit: "cm-2 s-1 sr-1" + background_normalization_optimization: True + """ + + def __init__(self, initial_model, dataset, mask, parameter): + + DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) + + # TODO: these RL algorithm improvements are yet to be implemented in RLparallel + # self.do_acceleration = parameter.get('acceleration', False) + + # self.alpha_max = parameter.get('alpha_max', 1.0) + + # self.do_response_weighting = parameter.get('response_weighting', False) + # if self.do_response_weighting: + # self.response_weighting_index = parameter.get('response_weighting_index', 0.5) + + # self.do_smoothing = parameter.get('smoothing', False) + # if self.do_smoothing: + # self.smoothing_fwhm = parameter['smoothing_FWHM']['value'] * u.Unit(parameter['smoothing_FWHM']['unit']) + # logger.info(f"Gaussian filter with FWHM of {self.smoothing_fwhm} will be applied to delta images ...") + + self.do_bkg_norm_optimization = parameter.get('background_normalization_optimization', False) + if self.do_bkg_norm_optimization: + self.dict_bkg_norm_range = parameter.get('background_normalization_range', {key: [0.0, 100.0] for key in self.dict_bkg_norm.keys()}) + + self.save_results = parameter.get('save_results', False) + self.save_results_directory = parameter.get('save_results_directory', './results') + + if self.save_results is True: + if os.path.isdir(self.save_results_directory): + logger.warning(f"A directory {self.save_results_directory} already exists. Files in {self.save_results_directory} may be overwritten. Make sure that is not a problem.") + else: + os.makedirs(self.save_results_directory) + +# Define the number of rows and columns +NUMROWS = 184320 # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS +NUMCOLS = 3072 + +# Define MPI and iteration misc variables +MASTER = 0 # Indicates master process +MAXITER = 50 # Maximum number of iterations + +FILE_DIR = Path(os.path.dirname(os.path.abspath(__file__))) +BASE_DIR = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/44Ti/') +DATA_DIR = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/') + +''' +Response matrix +''' +def load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: + # Assuming the dataset name is "response_matrix" + dataset = f1["response_matrix"] + R = dataset[start_row:end_row, :] + return R + +''' +Response matrix transpose +''' +def load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: + # Assuming the dataset name is "response_matrix" + dataset = f1["response_matrix"] + RT = dataset[:, start_col:end_col] + return RT + +''' +Response matrix summed along axis=i +''' +def load_axis0_summed_response_matrix(filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r") as f1: + # Assuming the dataset name is "response_vector" + dataset = f1["response_vector"] + Rj = dataset[:] + return Rj + +''' +Sky model +''' +def initial_sky_model(): + M0 = np.ones(NUMCOLS, dtype=np.float64) * 1e-4 # Initial guess according to image_deconvolution.py + return M0 + +''' +Background model +''' +def load_bg_model(filename='data/total_bg_dense.hdf5'): + with h5py.File(BASE_DIR / filename) as hf_bkg: + bkg = hf_bkg['contents'][:] + return bkg + +''' +Observed data +''' +def load_signal_counts(filename='data/Ti44_CasA_x50_dense.hdf5'): + with h5py.File(BASE_DIR / filename) as hf_signal: + signal = hf_signal['contents'][:] + return signal + +def main(): + # Set up MPI + comm = MPI.COMM_WORLD + numtasks = comm.Get_size() + taskid = comm.Get_rank() + + # Initialise vectors required by all processes + M = np.empty(NUMCOLS, dtype=np.float64) # Loaded and broadcasted by master. + d = np.empty(NUMROWS, dtype=np.float64) # Loaded and broadcasted by master. + epsilon = np.zeros(NUMROWS) # All gatherv-ed. + epsilon_fudge = 1e-12 # To prevent divide-by-zero error + bkg = np.zeros(NUMROWS) # Loaded and broadcasted by master. + + # Calculate the indices in Rij that the process has to parse. My hunch is that calculating these scalars individually will be faster than the MPI send broadcast overhead. + averow = NUMROWS // numtasks + extra_rows = NUMROWS % numtasks + start_row = taskid * averow + end_row = (taskid + 1) * averow if taskid < (numtasks - 1) else NUMROWS + + # Calculate the indices in Rji, i.e., Rij transpose, that the process has to parse. + avecol = NUMCOLS // numtasks + extra_cols = NUMCOLS % numtasks + start_col = taskid * avecol + end_col = (taskid + 1) * avecol if taskid < (numtasks - 1) else NUMCOLS + + # Load R and RT into memory (single time if response matrix doesn't + # change with time) + R = load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_511_DC2.h5') + RT = load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_511_DC2.h5') + + # Initialise epsilon_slice and C_slice + epsilon_slice = np.zeros(end_row - start_row) + C_slice = np.zeros(end_col - start_col) + +# ****************************** MPI ****************************** + +# **************************** Part I ***************************** + + '''*************** Master ***************''' + + if taskid == MASTER: + # Pretty print definitions + linebreak_stars = '**********************' + linebreak_dashes = '----------------------' + + # Load Rj vector (response matrix summed along axis=i) + Rj = load_axis0_summed_response_matrix(filename='psr_gal_flattened_511_DC2.h5') + + # Load sky model input + M = initial_sky_model() + + # Load observed data counts + # XXX: Only simulations give access to signal. Eventually, + # we will only have observed counts d and a simulated background model. + # signal1 = load_signal_counts(filename='data/Ti44_CasA_dense.hdf5') + # signal2 = load_signal_counts(filename='data/Ti44_G1903_dense.hdf5') + # signal3 = load_signal_counts(filename='data/Ti44_SN1987A_dense.hdf5') + # bkg = load_bg_model() + # d = signal1 + signal2 + signal3 + bkg + signal = load_signal_counts(filename='data/511_thin_disk_dense.h5') + bkg = load_bg_model(filename='data/albedo_bg_dense.h5') + d = signal + bkg + + # Sanity check: print d + print() + print('Observed data-space d vector:') + print(d) + # print(d.min(), d.max()) + ## Pretty print + print() + print(linebreak_stars) + + # Initialise C vector. Only master requires full length. + C = np.empty(NUMCOLS, dtype=np.float64) + + # Initialise update delta vector + delta = np.empty(NUMCOLS, dtype=np.float64) + + '''*************** Worker ***************''' + + if taskid > MASTER: + # Only separate if... clause for NON-MASTER processes. + # Initialise C vector to None. Only master requires full length. + C = None + + # Broadcast d vector + comm.Bcast([d, MPI.DOUBLE], root=MASTER) + + # Scatter bkg vector to epsilon_BG + comm.Bcast([bkg, MPI.DOUBLE], root=MASTER) + # comm.Scatter(bkg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) + + # print(f"TaskID {taskid}, gathered broadcast") + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon_BG') + # print(bkg) + # print() + +# **************************** Part IIa ***************************** + + '''***************** Begin Iterative Segment *****************''' + # Set up initial values for iterating variables. + # Exit if: + ## 1. Max iterations are reached + ## 2. M vector converges + for iter in range(MAXITER): + + '''*************** Master ***************''' + if taskid == MASTER: + # Pretty print - starting + print(f"Starting iteration {iter + 1}") + + + # Calculate epsilon vector and all gatherv + + '''**************** All *****************''' + + '''Synchronization Barrier 1''' + # Broadcast M vector + comm.Bcast([M, MPI.DOUBLE], root=MASTER) + + # Calculate epsilon slice + epsilon_BG = bkg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` + epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge + + '''Synchronization Barrier 2''' + # All vector gather epsilon slices + recvcounts = [averow] * (numtasks-1) + [averow + extra_rows] + displacements = np.arange(numtasks) * averow + comm.Allgatherv(epsilon_slice, [epsilon, recvcounts, displacements, MPI.DOUBLE]) + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon') + # print(epsilon) + # print(epsilon.min(), epsilon.max()) + # print() + +# **************************** Part IIb ***************************** + + # Calculate C vector and gatherv + + '''**************** All *****************''' + + # Calculate C slice + C_slice = np.dot(RT.T, d/epsilon) + + '''Synchronization Barrier 3''' + # All vector gather C slices + recvcounts = [avecol] * (numtasks-1) + [avecol + extra_cols] + displacements = np.arange(numtasks) * avecol + comm.Gatherv(C_slice, [C, recvcounts, displacements, MPI.DOUBLE], root=MASTER) + +# **************************** Part IIb ***************************** + + # Iterative update of model-space M vector + + if taskid == MASTER: + + # Sanity check: print C + # print('C') + # print(C) + # print(C.min(), C.max()) + # print() + + delta = C / Rj - 1 + M = M + delta * M # Allows for optimization features presented in Siegert et al. 2020 + + # Sanity check: print M + # print('M') + # print(np.round(M, 5)) + # print(np.round(M.max(), 5)) + + # Sanity check: print delta + # print('delta') + # print(delta) + + # Pretty print - completion + print(f"Done") + print(linebreak_dashes) + + # Save iteration + # np.savetxt(FILE_DIR / f'outputs/Mstep{iter+1}.csv', M) + + # MAXITER + if iter == (MAXITER - 1): + print(f'Reached maximum iterations = {MAXITER}') + print(linebreak_stars) + print() + + '''****************** End Iterative Segment ******************''' + + # Print converged M + if taskid == MASTER: + print('Converged M vector:') + print(np.round(M, 5)) + print(np.round(M.max(), 5)) + print(np.sum(M)) + print() + + # Save final output + # np.savetxt(FILE_DIR / f'outputs/ConvergedM.csv', M) + + # MPI Shutdown + MPI.Finalize() + +if __name__ == "__main__": + main() diff --git a/cosipy/image_deconvolution/image_deconvolution.py b/cosipy/image_deconvolution/image_deconvolution.py index 362108ac..8367a41c 100644 --- a/cosipy/image_deconvolution/image_deconvolution.py +++ b/cosipy/image_deconvolution/image_deconvolution.py @@ -9,13 +9,14 @@ from .RichardsonLucy import RichardsonLucy from .RichardsonLucySimple import RichardsonLucySimple +from .RLparallel import RLparallel class ImageDeconvolution: """ A class to reconstruct all-sky images from COSI data based on image deconvolution methods. """ model_classes = {"AllSkyImage": AllSkyImageModel} - deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple} + deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple, "RLparallel": RLparallel} def __init__(self): self._dataset = None diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index 36216b21..dc71bee7 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -33,12 +33,268 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "e751bbd5", "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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         WARNING   Could not import plugin HAWCLike.py. Do you have the relative instrument         __init__.py:144\n",
+       "                  software installed and configured?                                                               \n",
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         WARNING   Could not import plugin FermiLATLike.py. Do you have the relative instrument     __init__.py:144\n",
+       "                  software installed and configured?                                                               \n",
+       "
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17:24:36 WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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17:24:36 WARNING   Env. variable OMP_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
+       "
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         WARNING   Env. variable MKL_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
+       "
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+       "                  performances in 3ML                                                                              \n",
+       "
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For navy, set #002060\n", + "defaultcolor = '#002060'\n", + "plt.rcParams.update({'text.color': defaultcolor, 'axes.labelcolor': defaultcolor, \n", + " 'xtick.color': defaultcolor, 'ytick.color': defaultcolor,\n", + " 'axes.prop_cycle': cycler(color=['b', 'r', 'limegreen']),\n", + " 'font.family':'serif', 'font.serif': 'Times New Roman',\n", + " 'font.size': 22, 'lines.linewidth': 3,\n", + " 'figure.figsize': (9.6, 5.4), 'figure.dpi': 100})" ] }, { @@ -109,7 +373,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "cafd42c7-7f7f-4e6e-acd7-8e76eb5160dc", "metadata": {}, "outputs": [], @@ -117,13 +381,13 @@ "# Response file:\n", "# wasabi path: COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_511_DC2.h5.gz\n", "# File size: 3.82 GB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_511_DC2.h5.gz')\n", - "os.system('gunzip psr_gal_511_DC2.h5.gz')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_511_DC2.h5.gz')\n", + "# os.system('gunzip psr_gal_511_DC2.h5.gz')" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "ae368f5f-2d30-4ba6-a152-c5bbb4187471", "metadata": {}, "outputs": [], @@ -131,12 +395,12 @@ "# Source file (511 keV thin disk model):\n", "# wasabi path: COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz\n", "# File size: 202.45 MB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz')" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "dddb7361-a523-42b4-93fe-da0b3ce75deb", "metadata": {}, "outputs": [], @@ -144,7 +408,7 @@ "# Background file (albedo gamma):\n", "# wasabi path: COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz\n", "# File size: 2.69 GB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz')" ] }, { @@ -157,16 +421,6 @@ " please modify \"path_data\" corresponding to your environment." ] }, - { - "cell_type": "code", - "execution_count": 4, - "id": "fada24bc", - "metadata": {}, - "outputs": [], - "source": [ - "path_data = \"path/to/data/\"" - ] - }, { "cell_type": "markdown", "id": "90fec91e-8209-4f03-bbe3-b9acb78682b8", @@ -177,7 +431,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "id": "9cae1835-e54b-4720-b3a6-196c42cbd1ce", "metadata": {}, "outputs": [ @@ -190,19 +444,19 @@ "Em unit: keV\n", "Phi unit: deg\n", "PsiChi unit: None\n", - "CPU times: user 7.75 s, sys: 255 ms, total: 8 s\n", - "Wall time: 8.06 s\n" + "CPU times: user 6.47 s, sys: 184 ms, total: 6.66 s\n", + "Wall time: 6.72 s\n" ] } ], "source": [ - "%%time\n", + "# %%time\n", "\n", - "signal_filepath = path_data + \"511_thin_disk_3months_unbinned_data.fits.gz\"\n", + "# signal_filepath = path_data + \"511_thin_disk_3months_unbinned_data.fits.gz\"\n", "\n", - "binned_signal = BinnedData(input_yaml = \"inputs_511keV_DC2.yaml\")\n", + "# binned_signal = BinnedData(input_yaml = \"inputs_511keV_DC2.yaml\")\n", "\n", - "binned_signal.get_binned_data(unbinned_data = signal_filepath, psichi_binning=\"galactic\")" + "# binned_signal.get_binned_data(unbinned_data = signal_filepath, psichi_binning=\"galactic\")" ] }, { @@ -215,7 +469,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 13, "id": "801ba251-96e0-4243-8f55-1678823f1d58", "metadata": {}, "outputs": [ @@ -228,19 +482,19 @@ "Em unit: keV\n", "Phi unit: deg\n", "PsiChi unit: None\n", - "CPU times: user 1min 51s, sys: 3.96 s, total: 1min 55s\n", - "Wall time: 1min 55s\n" + "CPU times: user 1min 32s, sys: 2.64 s, total: 1min 35s\n", + "Wall time: 1min 36s\n" ] } ], "source": [ - "%%time\n", + "# %%time\n", "\n", - "bkg_filepath = path_data + \"albedo_photons_3months_unbinned_data.fits.gz\"\n", + "# bkg_filepath = path_data + \"albedo_photons_3months_unbinned_data.fits.gz\"\n", "\n", - "binned_bkg = BinnedData(input_yaml = \"inputs_511keV_DC2.yaml\")\n", + "# binned_bkg = BinnedData(input_yaml = \"inputs_511keV_DC2.yaml\")\n", "\n", - "binned_bkg.get_binned_data(unbinned_data = bkg_filepath, psichi_binning=\"galactic\")" + "# binned_bkg.get_binned_data(unbinned_data = bkg_filepath, psichi_binning=\"galactic\")" ] }, { @@ -253,14 +507,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 14, "id": "f224b957-d0df-4b4b-98dd-90d3a5bda3fb", "metadata": {}, "outputs": [], "source": [ - "signal = binned_signal.binned_data.to_dense()\n", - "bkg = binned_bkg.binned_data.to_dense()\n", - "event = signal + bkg" + "# signal = binned_signal.binned_data.to_dense()\n", + "# bkg = binned_bkg.binned_data.to_dense()\n", + "# event = signal + bkg" ] }, { @@ -278,9 +532,9 @@ "metadata": {}, "outputs": [], "source": [ - "signal.write(\"511keV_dc2_galactic_signal.hdf5\", overwrite = True)\n", - "bkg.write(\"511keV_dc2_galactic_bkg.hdf5\", overwrite = True)\n", - "event.write(\"511keV_dc2_galactic_event.hdf5\", overwrite = True)" + "# signal.write(\"511keV_dc2_galactic_signal.hdf5\", overwrite = False)\n", + "# bkg.write(\"511keV_dc2_galactic_bkg.hdf5\", overwrite = False)\n", + "# event.write(\"511keV_dc2_galactic_event.hdf5\", overwrite = False)" ] }, { @@ -293,14 +547,25 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 15, + "id": "41371ac9", + "metadata": {}, + "outputs": [], + "source": [ + "path_data = \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/\"\n", + "path_511_data = \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/\"" + ] + }, + { + "cell_type": "code", + "execution_count": 16, "id": "e0f3dcae-5d3c-45af-931d-057d5681859c", "metadata": {}, "outputs": [], "source": [ - "signal = Histogram.open(\"511keV_dc2_galactic_signal.hdf5\")\n", - "bkg = Histogram.open(\"511keV_dc2_galactic_bkg.hdf5\")\n", - "event = Histogram.open(\"511keV_dc2_galactic_event.hdf5\")" + "signal = Histogram.open(path_511_data + \"511keV_dc2_galactic_signal.hdf5\")\n", + "bkg = Histogram.open(path_511_data + \"511keV_dc2_galactic_bkg.hdf5\")\n", + "event = Histogram.open(path_511_data + \"511keV_dc2_galactic_event.hdf5\")" ] }, { @@ -315,7 +580,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 17, "id": "88efdbfa-aa5e-40b3-bdd6-2635946318e4", "metadata": {}, "outputs": [ @@ -328,7 +593,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -347,7 +612,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 18, "id": "b5b295cf-0a96-4501-aa4e-4182a21dfe63", "metadata": {}, "outputs": [ @@ -355,8 +620,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.3 s, sys: 23.2 s, total: 26.5 s\n", - "Wall time: 38 s\n" + "CPU times: user 3.14 s, sys: 13.7 s, total: 16.9 s\n", + "Wall time: 31.3 s\n" ] } ], @@ -370,7 +635,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 19, "id": "fbdbd818-8a58-4d25-a657-d43fc7f88ea4", "metadata": {}, "outputs": [ @@ -380,7 +645,7 @@ "array(['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi'], dtype='" ] @@ -2568,7 +2833,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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\n", + "image/png": 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", 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\n", + "image/png": 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", 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\n", 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", 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\n", + "image/png": 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" ] @@ -2818,7 +3083,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.13" } }, "nbformat": 4, diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/inputs_511keV_DC2.yaml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/inputs_511keV_DC2.yaml index 5a71e89e..d8820d0d 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/inputs_511keV_DC2.yaml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/inputs_511keV_DC2.yaml @@ -2,7 +2,7 @@ # Data I/O: data_file: -ori_file: "/Users/yoneda/Work/Exp/COSI/cosipy-2/data_challenge/DC2/prework/data/orientation/20280301_3_month.ori" +ori_file: "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/orientation/20280301_3_month.ori" unbinned_output: 'fits' # 'fits' or 'hdf5' time_bins: 7979955 # time bin size in seconds. Takes int or list of bin edges. tmin: 1835487300.0 From c918ab55b2c12f53d4b54f23e43c1e7db3b7450f Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Mon, 5 Aug 2024 19:00:27 +0530 Subject: [PATCH 02/46] Renamed RLparallel.py to RichardsonLucyParallel.py and adapted code skeleton from RichardsonLucy.py --- ...Lparallel.py => RichardsonLucyParallel.py} | 91 ++++++++++++++++++- .../image_deconvolution.py | 4 +- .../imagedeconvolution_parfile_gal_511keV.yml | 7 +- 3 files changed, 96 insertions(+), 6 deletions(-) rename cosipy/image_deconvolution/{RLparallel.py => RichardsonLucyParallel.py} (81%) diff --git a/cosipy/image_deconvolution/RLparallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py similarity index 81% rename from cosipy/image_deconvolution/RLparallel.py rename to cosipy/image_deconvolution/RichardsonLucyParallel.py index 8b2510be..67f946a9 100644 --- a/cosipy/image_deconvolution/RLparallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -6,14 +6,15 @@ # Import third party libraries import numpy as np -from mpi4py import MPI +# from mpi4py import MPI import h5py from histpy import Histogram from .deconvolution_algorithm_base import DeconvolutionAlgorithmBase -class RLparallel(DeconvolutionAlgorithmBase): +class RichardsonLucyParallel(DeconvolutionAlgorithmBase): """ + NOTE: Comments copied from RichardsonLucy.py A class for a parallel implementation of the Richardson- Lucy algorithm. @@ -27,10 +28,13 @@ class RLparallel(DeconvolutionAlgorithmBase): """ def __init__(self, initial_model, dataset, mask, parameter): + """ + NOTE: Copied from RichardsonLucy.py + """ DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) - # TODO: these RL algorithm improvements are yet to be implemented in RLparallel + # TODO: these RL algorithm improvements are yet to be implemented/utilized in this file # self.do_acceleration = parameter.get('acceleration', False) # self.alpha_max = parameter.get('alpha_max', 1.0) @@ -57,6 +61,86 @@ def __init__(self, initial_model, dataset, mask, parameter): else: os.makedirs(self.save_results_directory) + def initialization(self): + """ + initialization before running the image deconvolution + """ + # clear counter + self.iteration_count = 0 + + # clear results + self.results.clear() + + # copy model + self.model = copy.deepcopy(self.initial_model) + + def pre_processing(self): + """ + pre-processing for each iteration + """ + pass + + def Estep(self): + pass + + def Mstep(self): + pass + + def post_processing(self): + """ + pre-processing for each iteration + """ + pass + + def check_stopping_criteria(self): + """ + NOTE: Copied from RichardsonLucy.py + If iteration_count is smaller than iteration_max, the iterative process will continue. + + Returns + ------- + bool + """ + if self.iteration_count < self.iteration_max: + return False + return True + + def register_result(self): + """ + NOTE: Copied from RichardsonLucy.py + The values below are stored at the end of each iteration. + - iteration: iteration number + - model: updated image + - delta_model: delta map after M-step + - processed_delta_model: delta map after post-processing + - alpha: acceleration parameter in RL algirithm + - background_normalization: optimized background normalization + - loglikelihood: log-likelihood + """ + + this_result = {"iteration": self.iteration_count, + "model": copy.deepcopy(self.model), + # "delta_model": copy.deepcopy(self.delta_model), + # "processed_delta_model": copy.deepcopy(self.processed_delta_model), + "background_normalization": copy.deepcopy(self.dict_bkg_norm), + # "alpha": self.alpha, + # "loglikelihood": copy.deepcopy(self.loglikelihood_list) + } + + # show intermediate results + # logger.info(f' alpha: {this_result["alpha"]}') + logger.info(f' background_normalization: {this_result["background_normalization"]}') + # logger.info(f' loglikelihood: {this_result["loglikelihood"]}') + + # register this_result in self.results + self.results.append(this_result) + + def finalization(self): + """ + finalization after running the image deconvolution + """ + +""" # Define the number of rows and columns NUMROWS = 184320 # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS NUMCOLS = 3072 @@ -332,3 +416,4 @@ def main(): if __name__ == "__main__": main() +""" \ No newline at end of file diff --git a/cosipy/image_deconvolution/image_deconvolution.py b/cosipy/image_deconvolution/image_deconvolution.py index 8367a41c..e07c4d85 100644 --- a/cosipy/image_deconvolution/image_deconvolution.py +++ b/cosipy/image_deconvolution/image_deconvolution.py @@ -9,14 +9,14 @@ from .RichardsonLucy import RichardsonLucy from .RichardsonLucySimple import RichardsonLucySimple -from .RLparallel import RLparallel +from .RichardsonLucyParallel import RichardsonLucyParallel class ImageDeconvolution: """ A class to reconstruct all-sky images from COSI data based on image deconvolution methods. """ model_classes = {"AllSkyImage": AllSkyImageModel} - deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple, "RLparallel": RLparallel} + deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple, "RLparallel": RichardsonLucyParallel} def __init__(self): self._dataset = None diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 53e53ae7..0c0a5198 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -1,7 +1,9 @@ author: Hiroki Yoneda date: 2024-06-12 + model_definition: class: "AllSkyImage" + property: coordinate: "galactic" nside: 16 @@ -10,13 +12,16 @@ model_definition: value: [509.0, 513.0] unit: "keV" unit: "cm-2 s-1 sr-1" # do not change it as for now + initialization: algorithm: "flat" # more methods, e.g., simple-backprojection, user-defined, would be implemented. parameter: value: [1e-4] #the number of these values should be the same as "the number of energy_edges - 1". unit: "cm-2 s-1 sr-1" # do not change it as for now + deconvolution: - algorithm: "RL" + algorithm: "RLparallel" + parameter: iteration_max: 10 acceleration: True From 015f64883b67fec99c1e4a425540cef3fc0922a6 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Mon, 5 Aug 2024 19:35:19 +0530 Subject: [PATCH 03/46] Installed mpi4py to cosipy venv and added it to skeleton --- cosipy/image_deconvolution/RichardsonLucyParallel.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 67f946a9..7e0d3bf8 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -6,7 +6,7 @@ # Import third party libraries import numpy as np -# from mpi4py import MPI +from mpi4py import MPI import h5py from histpy import Histogram From f259d3605ab49d4f94bebe2ce38f3ead85b50304 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Mon, 12 Aug 2024 20:49:45 +0530 Subject: [PATCH 04/46] Created subprocess call. Ported MPI to separate script RLparallelscript.py --- .../image_deconvolution/RLparallelscript.py | 292 +++++++++++++++ .../RichardsonLucyParallel.py | 352 ++---------------- .../imagedeconvolution_parfile_gal_511keV.yml | 4 +- 3 files changed, 335 insertions(+), 313 deletions(-) create mode 100644 cosipy/image_deconvolution/RLparallelscript.py diff --git a/cosipy/image_deconvolution/RLparallelscript.py b/cosipy/image_deconvolution/RLparallelscript.py new file mode 100644 index 00000000..3bc89001 --- /dev/null +++ b/cosipy/image_deconvolution/RLparallelscript.py @@ -0,0 +1,292 @@ +import os +from pathlib import Path +# import logging +# logger = logging.getLogger(__name__) +import argparse +parser = argparse.ArgumentParser() +parser.add_argument("--numrows", type=int, dest='numrows', help="Number of rows in the response matrix") +parser.add_argument("--numcols", type=int, dest='numcols', help="Number of columns in the response matrix") +parser.add_argument("--iteration_max", type=int, dest='iteration_max', help="Maximum number of iterations in RL deconvolution") +parser.add_argument("--data_dir", type=str, dest='data_dir', help="Directory where data lies") +parser.add_argument("--save_results", type=bool, dest='save_results', help="Should the results be saved?") +parser.add_argument("--results_dir", type=str, dest='results_dir', help="Directory to save results (only enabled if --save_results is set to True)") +args = parser.parse_args() + +# Import third party libraries +import numpy as np +from mpi4py import MPI +import h5py + +# Define the number of rows and columns +NUMROWS = args.numrows # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS +NUMCOLS = args.numcols + +# Define MPI and iteration misc variables +MASTER = 0 # Indicates master process +MAXITER = args.iteration_max # Maximum number of iterations + +# FILE_DIR = Path(os.path.dirname(os.path.abspath(__file__))) +DATA_DIR = Path(args.data_dir) +RESULTS_DIR = Path(args.result_dir) + +''' +Response matrix +''' +def load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: + # Assuming the dataset name is "response_matrix" + dataset = f1["response_matrix"] + R = dataset[start_row:end_row, :] + return R + +''' +Response matrix transpose +''' +def load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: + # Assuming the dataset name is "response_matrix" + dataset = f1["response_matrix"] + RT = dataset[:, start_col:end_col] + return RT + +''' +Response matrix summed along axis=i +''' +def load_axis0_summed_response_matrix(filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): + with h5py.File(DATA_DIR / filename, "r") as f1: + # Assuming the dataset name is "response_vector" + dataset = f1["response_vector"] + Rj = dataset[:] + return Rj + +''' +Sky model +''' +def initial_sky_model(): + M0 = np.ones(NUMCOLS, dtype=np.float64) * 1e-4 # Initial guess according to image_deconvolution.py + return M0 + +''' +Background model +''' +def load_bg_model(filename='data/total_bg_dense.hdf5'): + with h5py.File(DATA_DIR / filename) as hf_bkg: + bkg = hf_bkg['contents'][:] + return bkg + +''' +Observed data +''' +def load_signal_counts(filename='data/Ti44_CasA_x50_dense.hdf5'): + with h5py.File(DATA_DIR / filename) as hf_signal: + signal = hf_signal['contents'][:] + return signal + +def main(): + # Set up MPI + comm = MPI.COMM_WORLD + numtasks = comm.Get_size() + taskid = comm.Get_rank() + + # Initialise vectors required by all processes + epsilon = np.zeros(NUMROWS) # All gatherv-ed. Explicit variable declaration. + epsilon_fudge = 1e-12 # To prevent divide-by-zero and underflow errors + + # Initialise epsilon_slice and C_slice. Explicit variable declarations. + epsilon_slice = np.zeros(end_row - start_row) + C_slice = np.zeros(end_col - start_col) + + # Calculate the indices in Rij that the process has to parse. My hunch is that calculating these scalars individually will be faster than the MPI send broadcast overhead. + averow = NUMROWS // numtasks + extra_rows = NUMROWS % numtasks + start_row = taskid * averow + end_row = (taskid + 1) * averow if taskid < (numtasks - 1) else NUMROWS + + # Calculate the indices in Rji, i.e., Rij transpose, that the process has to parse. + avecol = NUMCOLS // numtasks + extra_cols = NUMCOLS % numtasks + start_col = taskid * avecol + end_col = (taskid + 1) * avecol if taskid < (numtasks - 1) else NUMCOLS + + # Load R and RT into memory (single time if response matrix doesn't + # change with time) + R = load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_511_DC2.h5') + RT = load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_511_DC2.h5') + + M = np.empty(NUMCOLS, dtype=np.float64) # Loaded and broadcasted by master. TODO: Correctly link variables to relevant object inputs + d = np.empty(NUMROWS, dtype=np.float64) # Loaded and broadcasted by master. + bkg = np.zeros(NUMROWS) # Loaded and broadcasted by master. + +# ****************************** MPI ****************************** + +# **************************** Part I ***************************** + + '''*************** Master ***************''' + + if taskid == MASTER: + # Pretty print definitions + linebreak_stars = '**********************' + linebreak_dashes = '----------------------' + + # Load Rj vector (response matrix summed along axis=i) + Rj = load_axis0_summed_response_matrix(filename='psr_gal_flattened_511_DC2.h5') + + # Load sky model input + M = initial_sky_model() # TODO: Correctly link variables to relevant object inputs + + # Load observed data counts + signal = load_signal_counts(filename='511_thin_disk_dense.h5') + bkg = load_bg_model(filename='albedo_bg_dense.h5') # TODO: Correctly link variables to relevant object inputs + d = signal + bkg # TODO: Correctly link variables to relevant object inputs + + # Sanity check: print d + print() + print('Observed data-space d vector:') + print(d) + ## Pretty print + print() + print(linebreak_stars) + + # Initialise C vector. Only master requires full length. Explicit variable declaration. + C = np.empty(NUMCOLS, dtype=np.float64) + + # Initialise update delta vector. Explicit variable declaration. + delta = np.empty(NUMCOLS, dtype=np.float64) + + '''*************** Worker ***************''' + + if taskid > MASTER: + # Only separate if... clause for NON-MASTER processes. + # Initialise C vector to None. Only master requires full length. + C = None + + # Broadcast d vector + comm.Bcast([d, MPI.DOUBLE], root=MASTER) + + # Scatter bkg vector to epsilon_BG + comm.Bcast([bkg, MPI.DOUBLE], root=MASTER) + # comm.Scatter(bkg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) + + # print(f"TaskID {taskid}, gathered broadcast") + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon_BG') + # print(bkg) + # print() + +# **************************** Part IIa ***************************** + + '''***************** Begin Iterative Segment *****************''' + # Set up initial values for iterating variables. + # Exit if: + ## 1. Max iterations are reached + ## 2. M vector converges + for iter in range(MAXITER): + + '''*************** Master ***************''' + if taskid == MASTER: + # Pretty print - starting + print(f"Starting iteration {iter + 1}") + # logger.info(f"## Iteration {self.iteration_count}/{self.iteration_max} ##") + # logger.info("<< E-step >>") + + + # Calculate epsilon vector and all gatherv + + '''**************** All *****************''' + + '''Synchronization Barrier 1''' + # Broadcast M vector + comm.Bcast([M, MPI.DOUBLE], root=MASTER) + + # Calculate epsilon slice + epsilon_BG = bkg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` + epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge + + '''Synchronization Barrier 2''' + # All vector gather epsilon slices + recvcounts = [averow] * (numtasks-1) + [averow + extra_rows] + displacements = np.arange(numtasks) * averow + comm.Allgatherv(epsilon_slice, [epsilon, recvcounts, displacements, MPI.DOUBLE]) + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon') + # print(epsilon) + # print(epsilon.min(), epsilon.max()) + # print() + +# **************************** Part IIb ***************************** + + # Calculate C vector and gatherv + + '''**************** All *****************''' + + # Calculate C slice + C_slice = np.dot(RT.T, d/epsilon) + + '''Synchronization Barrier 3''' + # All vector gather C slices + recvcounts = [avecol] * (numtasks-1) + [avecol + extra_cols] + displacements = np.arange(numtasks) * avecol + comm.Gatherv(C_slice, [C, recvcounts, displacements, MPI.DOUBLE], root=MASTER) + +# **************************** Part IIc ***************************** + + # Iterative update of model-space M vector + + if taskid == MASTER: + + # logger.info("<< M-step >>") + + # Sanity check: print C + # print('C') + # print(C) + # print(C.min(), C.max()) + # print() + + delta = C / Rj - 1 + M = M + delta * M # Allows for optimization features presented in Siegert et al. 2020 + + # Sanity check: print M + # print('M') + # print(np.round(M, 5)) + # print(np.round(M.max(), 5)) + + # Sanity check: print delta + # print('delta') + # print(delta) + + # Pretty print - completion + print(f"Done") + print(linebreak_dashes) + + # Save iteration + # np.savetxt(RESULTS_DIR / f'Mstep{iter+1}.csv', M) + + # MAXITER + if iter == (MAXITER - 1): + print(f'Reached maximum iterations = {MAXITER}') + print(linebreak_stars) + print() + + '''****************** End Iterative Segment ******************''' + + # Print converged M + if taskid == MASTER: + # logger.info("<< Registering Result >>") + print('Converged M vector:') + print(np.round(M, 5)) + print(np.round(M.max(), 5)) + print(np.sum(M)) + print() + + # Save final output + # np.savetxt(RESULTS_DIR / f'ConvergedM.csv', M) + + # MPI Shutdown + MPI.Finalize() + +if __name__ == "__main__": + main() diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 7e0d3bf8..5b532a16 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -1,12 +1,12 @@ import os from pathlib import Path import copy +import subprocess import logging logger = logging.getLogger(__name__) # Import third party libraries import numpy as np -from mpi4py import MPI import h5py from histpy import Histogram @@ -61,52 +61,46 @@ def __init__(self, initial_model, dataset, mask, parameter): else: os.makedirs(self.save_results_directory) - def initialization(self): - """ - initialization before running the image deconvolution - """ - # clear counter - self.iteration_count = 0 - - # clear results - self.results.clear() + # Specific to parallel implementation + self.numproc = parameter.get('numproc', 1) + self.iteration_max = parameter.get('iteration_max', 10) + self.base_dir = os.getcwd() + self.data_dir = parameter.get('data_dir', './data') # NOTE: Data should ideally be present in disk scratch space. - # copy model - self.model = copy.deepcopy(self.initial_model) + image_response = self.dataset[0]._image_response + self.numrows = np.product(image_response.contents.shape[1:]) + self.numcols = np.product(image_response.contents.shape[:1]) - def pre_processing(self): + def iteration(self): """ - pre-processing for each iteration - """ - pass + Performs all iterations of image deconvolution. - def Estep(self): - pass + NOTE: Overriding implementation in deconvolution_algorithm_base.py and invoking external script + """ - def Mstep(self): - pass + # All arguments must be passed as type=str. Explicitly type cast boolean and number to string. + subprocess.run(args=["mpiexec", "-n", str(self.numproc), "python", "mpitest.py", + "--numrows", str(self.numrows), + "--numcols", str(self.numcols), + "--iteration_max", str(self.iteration_max), + "--data_dir", self.data_dir, + "--save_results", str(self.save_results), + "--results_dir", self.save_results_directory]) + + # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. + # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. + return True - def post_processing(self): + def initialization(self): """ - pre-processing for each iteration + initialization before running the image deconvolution """ + # TODO: Write bkg and data to scratch space pass - def check_stopping_criteria(self): - """ - NOTE: Copied from RichardsonLucy.py - If iteration_count is smaller than iteration_max, the iterative process will continue. - - Returns - ------- - bool - """ - if self.iteration_count < self.iteration_max: - return False - return True - def register_result(self): """ + TODO: Port this to RLparallelscript.py NOTE: Copied from RichardsonLucy.py The values below are stored at the end of each iteration. - iteration: iteration number @@ -139,281 +133,15 @@ def finalization(self): """ finalization after running the image deconvolution """ + pass -""" -# Define the number of rows and columns -NUMROWS = 184320 # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS -NUMCOLS = 3072 - -# Define MPI and iteration misc variables -MASTER = 0 # Indicates master process -MAXITER = 50 # Maximum number of iterations - -FILE_DIR = Path(os.path.dirname(os.path.abspath(__file__))) -BASE_DIR = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/44Ti/') -DATA_DIR = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/') - -''' -Response matrix -''' -def load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: - # Assuming the dataset name is "response_matrix" - dataset = f1["response_matrix"] - R = dataset[start_row:end_row, :] - return R - -''' -Response matrix transpose -''' -def load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: - # Assuming the dataset name is "response_matrix" - dataset = f1["response_matrix"] - RT = dataset[:, start_col:end_col] - return RT - -''' -Response matrix summed along axis=i -''' -def load_axis0_summed_response_matrix(filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r") as f1: - # Assuming the dataset name is "response_vector" - dataset = f1["response_vector"] - Rj = dataset[:] - return Rj - -''' -Sky model -''' -def initial_sky_model(): - M0 = np.ones(NUMCOLS, dtype=np.float64) * 1e-4 # Initial guess according to image_deconvolution.py - return M0 - -''' -Background model -''' -def load_bg_model(filename='data/total_bg_dense.hdf5'): - with h5py.File(BASE_DIR / filename) as hf_bkg: - bkg = hf_bkg['contents'][:] - return bkg - -''' -Observed data -''' -def load_signal_counts(filename='data/Ti44_CasA_x50_dense.hdf5'): - with h5py.File(BASE_DIR / filename) as hf_signal: - signal = hf_signal['contents'][:] - return signal - -def main(): - # Set up MPI - comm = MPI.COMM_WORLD - numtasks = comm.Get_size() - taskid = comm.Get_rank() - - # Initialise vectors required by all processes - M = np.empty(NUMCOLS, dtype=np.float64) # Loaded and broadcasted by master. - d = np.empty(NUMROWS, dtype=np.float64) # Loaded and broadcasted by master. - epsilon = np.zeros(NUMROWS) # All gatherv-ed. - epsilon_fudge = 1e-12 # To prevent divide-by-zero error - bkg = np.zeros(NUMROWS) # Loaded and broadcasted by master. - - # Calculate the indices in Rij that the process has to parse. My hunch is that calculating these scalars individually will be faster than the MPI send broadcast overhead. - averow = NUMROWS // numtasks - extra_rows = NUMROWS % numtasks - start_row = taskid * averow - end_row = (taskid + 1) * averow if taskid < (numtasks - 1) else NUMROWS - - # Calculate the indices in Rji, i.e., Rij transpose, that the process has to parse. - avecol = NUMCOLS // numtasks - extra_cols = NUMCOLS % numtasks - start_col = taskid * avecol - end_col = (taskid + 1) * avecol if taskid < (numtasks - 1) else NUMCOLS - - # Load R and RT into memory (single time if response matrix doesn't - # change with time) - R = load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_511_DC2.h5') - RT = load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_511_DC2.h5') - - # Initialise epsilon_slice and C_slice - epsilon_slice = np.zeros(end_row - start_row) - C_slice = np.zeros(end_col - start_col) - -# ****************************** MPI ****************************** - -# **************************** Part I ***************************** - - '''*************** Master ***************''' - - if taskid == MASTER: - # Pretty print definitions - linebreak_stars = '**********************' - linebreak_dashes = '----------------------' - - # Load Rj vector (response matrix summed along axis=i) - Rj = load_axis0_summed_response_matrix(filename='psr_gal_flattened_511_DC2.h5') - - # Load sky model input - M = initial_sky_model() - - # Load observed data counts - # XXX: Only simulations give access to signal. Eventually, - # we will only have observed counts d and a simulated background model. - # signal1 = load_signal_counts(filename='data/Ti44_CasA_dense.hdf5') - # signal2 = load_signal_counts(filename='data/Ti44_G1903_dense.hdf5') - # signal3 = load_signal_counts(filename='data/Ti44_SN1987A_dense.hdf5') - # bkg = load_bg_model() - # d = signal1 + signal2 + signal3 + bkg - signal = load_signal_counts(filename='data/511_thin_disk_dense.h5') - bkg = load_bg_model(filename='data/albedo_bg_dense.h5') - d = signal + bkg - - # Sanity check: print d - print() - print('Observed data-space d vector:') - print(d) - # print(d.min(), d.max()) - ## Pretty print - print() - print(linebreak_stars) - - # Initialise C vector. Only master requires full length. - C = np.empty(NUMCOLS, dtype=np.float64) - - # Initialise update delta vector - delta = np.empty(NUMCOLS, dtype=np.float64) - - '''*************** Worker ***************''' - - if taskid > MASTER: - # Only separate if... clause for NON-MASTER processes. - # Initialise C vector to None. Only master requires full length. - C = None - - # Broadcast d vector - comm.Bcast([d, MPI.DOUBLE], root=MASTER) - - # Scatter bkg vector to epsilon_BG - comm.Bcast([bkg, MPI.DOUBLE], root=MASTER) - # comm.Scatter(bkg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) - - # print(f"TaskID {taskid}, gathered broadcast") - - # Sanity check: print epsilon - # if taskid == MASTER: - # print('epsilon_BG') - # print(bkg) - # print() - -# **************************** Part IIa ***************************** - - '''***************** Begin Iterative Segment *****************''' - # Set up initial values for iterating variables. - # Exit if: - ## 1. Max iterations are reached - ## 2. M vector converges - for iter in range(MAXITER): - - '''*************** Master ***************''' - if taskid == MASTER: - # Pretty print - starting - print(f"Starting iteration {iter + 1}") - - - # Calculate epsilon vector and all gatherv - - '''**************** All *****************''' - - '''Synchronization Barrier 1''' - # Broadcast M vector - comm.Bcast([M, MPI.DOUBLE], root=MASTER) - - # Calculate epsilon slice - epsilon_BG = bkg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` - epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge - - '''Synchronization Barrier 2''' - # All vector gather epsilon slices - recvcounts = [averow] * (numtasks-1) + [averow + extra_rows] - displacements = np.arange(numtasks) * averow - comm.Allgatherv(epsilon_slice, [epsilon, recvcounts, displacements, MPI.DOUBLE]) - - # Sanity check: print epsilon - # if taskid == MASTER: - # print('epsilon') - # print(epsilon) - # print(epsilon.min(), epsilon.max()) - # print() - -# **************************** Part IIb ***************************** - - # Calculate C vector and gatherv - - '''**************** All *****************''' - - # Calculate C slice - C_slice = np.dot(RT.T, d/epsilon) - - '''Synchronization Barrier 3''' - # All vector gather C slices - recvcounts = [avecol] * (numtasks-1) + [avecol + extra_cols] - displacements = np.arange(numtasks) * avecol - comm.Gatherv(C_slice, [C, recvcounts, displacements, MPI.DOUBLE], root=MASTER) - -# **************************** Part IIb ***************************** - - # Iterative update of model-space M vector - - if taskid == MASTER: - - # Sanity check: print C - # print('C') - # print(C) - # print(C.min(), C.max()) - # print() - - delta = C / Rj - 1 - M = M + delta * M # Allows for optimization features presented in Siegert et al. 2020 - - # Sanity check: print M - # print('M') - # print(np.round(M, 5)) - # print(np.round(M.max(), 5)) - - # Sanity check: print delta - # print('delta') - # print(delta) - - # Pretty print - completion - print(f"Done") - print(linebreak_dashes) - - # Save iteration - # np.savetxt(FILE_DIR / f'outputs/Mstep{iter+1}.csv', M) - - # MAXITER - if iter == (MAXITER - 1): - print(f'Reached maximum iterations = {MAXITER}') - print(linebreak_stars) - print() - - '''****************** End Iterative Segment ******************''' - - # Print converged M - if taskid == MASTER: - print('Converged M vector:') - print(np.round(M, 5)) - print(np.round(M.max(), 5)) - print(np.sum(M)) - print() - - # Save final output - # np.savetxt(FILE_DIR / f'outputs/ConvergedM.csv', M) - - # MPI Shutdown - MPI.Finalize() - -if __name__ == "__main__": - main() -""" \ No newline at end of file + def pre_processing(self): + pass + def Estep(self): + pass + def Mstep(self): + pass + def post_processing(self): + pass + def check_stopping_criteria(self): + pass \ No newline at end of file diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 0c0a5198..5264b916 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -35,4 +35,6 @@ deconvolution: background_normalization_optimization: True background_normalization_range: {"albedo": [0.01, 10.0]} save_results: False - save_results_directory: "./results" \ No newline at end of file + save_results_directory: "./results" + data_directory: "" # Absolute file path to directory where data lies + numproc: 6 # Number of MPI threads to spawn. Limited by number of nodes available. Only applicable for algorithm: "RLparallel" \ No newline at end of file From 4cde4dd283f6eb7a61a9e8833510f360b63682d6 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Tue, 13 Aug 2024 22:56:30 +0530 Subject: [PATCH 05/46] Added code to register results if save_results_flag is set to True --- .../image_deconvolution/RLparallelscript.py | 106 +- .../RichardsonLucyParallel.py | 36 +- ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 1848 ++--------------- 3 files changed, 220 insertions(+), 1770 deletions(-) diff --git a/cosipy/image_deconvolution/RLparallelscript.py b/cosipy/image_deconvolution/RLparallelscript.py index 3bc89001..5ca2141f 100644 --- a/cosipy/image_deconvolution/RLparallelscript.py +++ b/cosipy/image_deconvolution/RLparallelscript.py @@ -1,21 +1,32 @@ import os from pathlib import Path -# import logging -# logger = logging.getLogger(__name__) +import logging import argparse + +# logging +logger = logging.getLogger(__name__) + +# argparse parser = argparse.ArgumentParser() parser.add_argument("--numrows", type=int, dest='numrows', help="Number of rows in the response matrix") parser.add_argument("--numcols", type=int, dest='numcols', help="Number of columns in the response matrix") parser.add_argument("--iteration_max", type=int, dest='iteration_max', help="Maximum number of iterations in RL deconvolution") parser.add_argument("--data_dir", type=str, dest='data_dir', help="Directory where data lies") -parser.add_argument("--save_results", type=bool, dest='save_results', help="Should the results be saved?") -parser.add_argument("--results_dir", type=str, dest='results_dir', help="Directory to save results (only enabled if --save_results is set to True)") +parser.add_argument("--save_results", type=bool, dest='save_results_flag', help="Should the results be saved?") +parser.add_argument("--results_dir", type=str, dest='results_dir', help="Directory to save results (only enabled if --save_results_flag is set to True)") args = parser.parse_args() +logger.info(args.numrows) +logger.info(args.numcols) +logger.info(args.iteration_max) +logger.info(args.data_dir) +logger.info(args.save_results_flag) +logger.info(args.results_dir) # Import third party libraries import numpy as np from mpi4py import MPI import h5py +from tqdm.autonotebook import tqdm # Define the number of rows and columns NUMROWS = args.numrows # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS @@ -82,6 +93,69 @@ def load_signal_counts(filename='data/Ti44_CasA_x50_dense.hdf5'): signal = hf_signal['contents'][:] return signal +def register_result(iter, M, delta, ): + """ + The values below are stored at the end of each iteration. + - iteration: iteration number + - model: updated image + - delta_model: delta map after M-step + - processed_delta_model: delta map after post-processing + - alpha: acceleration parameter in RL algirithm + - background_normalization: optimized background normalization + - loglikelihood: log-likelihood + """ + + this_result = {"iteration": iter, + "model": M, + "delta_model": delta, + # "processed_delta_model": copy.deepcopy(self.processed_delta_model), TODO: The RL parallel implementation does not currently support smooth convergence through weighting, background normalization, or likelihood calculation + # "background_normalization": copy.deepcopy(self.dict_bkg_norm), + # "alpha": self.alpha, + # "loglikelihood": copy.deepcopy(self.loglikelihood_list) + } + + # # show intermediate results + # logger.info(f' alpha: {this_result["alpha"]}') + # logger.info(f' background_normalization: {this_result["background_normalization"]}') + # logger.info(f' loglikelihood: {this_result["loglikelihood"]}') + + return this_result + +def save_results(): + ''' + NOTE: Copied from RichardsonLucy.py + ''' + logger.info('Saving results in {RESULTS_DIR}') + # model + for this_result in results: + iteration_count = this_result["iteration"] + # this_result["model"].write(f"{RESULTS_DIR}/model_itr{iteration_count}.hdf5", overwrite = True) TODO: numpy arrays do not support write_to_hdf5 as a method. Need to ensure rest of code is modified to support cosipy.image_deconvolution.allskyimage.AllSkyImageModel + # this_result["delta_model"].write(f"{RESULTS_DIR}/delta_model_itr{iteration_count}.hdf5", overwrite = True) + # this_result["processed_delta_model"].write(f"{RESULTS_DIR}/processed_delta_model_itr{iteration_count}.hdf5", overwrite = True) TODO: processed_delta_model here is not different from delta_model + + # TODO: The following will be enabled once the respective calculations are incorporated + # #fits + # primary_hdu = fits.PrimaryHDU() + + # col_iteration = fits.Column(name='iteration', array=[float(result['iteration']) for result in self.results], format='K') + # col_alpha = fits.Column(name='alpha', array=[float(result['alpha']) for result in self.results], format='D') + # cols_bkg_norm = [fits.Column(name=key, array=[float(result['background_normalization'][key]) for result in self.results], format='D') + # for key in self.dict_bkg_norm.keys()] + # cols_loglikelihood = [fits.Column(name=f"{self.dataset[i].name}", array=[float(result['loglikelihood'][i]) for result in self.results], format='D') + # for i in range(len(self.dataset))] + + # table_alpha = fits.BinTableHDU.from_columns([col_iteration, col_alpha]) + # table_alpha.name = "alpha" + + # table_bkg_norm = fits.BinTableHDU.from_columns([col_iteration] + cols_bkg_norm) + # table_bkg_norm.name = "bkg_norm" + + # table_loglikelihood = fits.BinTableHDU.from_columns([col_iteration] + cols_loglikelihood) + # table_loglikelihood.name = "loglikelihood" + + # hdul = fits.HDUList([primary_hdu, table_alpha, table_bkg_norm, table_loglikelihood]) + # hdul.writeto(f'{RESULTS_DIR}/results.fits', overwrite=True) + def main(): # Set up MPI comm = MPI.COMM_WORLD @@ -153,6 +227,9 @@ def main(): # Initialise update delta vector. Explicit variable declaration. delta = np.empty(NUMCOLS, dtype=np.float64) + # Initialise list for results. See function register_result() for list elements. + results = [] + '''*************** Worker ***************''' if taskid > MASTER: @@ -182,7 +259,7 @@ def main(): # Exit if: ## 1. Max iterations are reached ## 2. M vector converges - for iter in range(MAXITER): + for iter in tqdm(range(MAXITER)): '''*************** Master ***************''' if taskid == MASTER: @@ -263,13 +340,8 @@ def main(): print(linebreak_dashes) # Save iteration - # np.savetxt(RESULTS_DIR / f'Mstep{iter+1}.csv', M) - - # MAXITER - if iter == (MAXITER - 1): - print(f'Reached maximum iterations = {MAXITER}') - print(linebreak_stars) - print() + if args.save_results_flag == True: + results.append(register_result()) '''****************** End Iterative Segment ******************''' @@ -282,8 +354,14 @@ def main(): print(np.sum(M)) print() - # Save final output - # np.savetxt(RESULTS_DIR / f'ConvergedM.csv', M) + if args.save_results_flag == True: + save_results(results) + + # MAXITER + if iter == (MAXITER - 1): + print(f'Reached maximum iterations = {MAXITER}') + print(linebreak_stars) + print() # MPI Shutdown MPI.Finalize() diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 5b532a16..6c5dcf96 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -85,7 +85,8 @@ def iteration(self): "--iteration_max", str(self.iteration_max), "--data_dir", self.data_dir, "--save_results", str(self.save_results), - "--results_dir", self.save_results_directory]) + "--results_dir", self.save_results_directory], + text=True) # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. @@ -98,37 +99,6 @@ def initialization(self): # TODO: Write bkg and data to scratch space pass - def register_result(self): - """ - TODO: Port this to RLparallelscript.py - NOTE: Copied from RichardsonLucy.py - The values below are stored at the end of each iteration. - - iteration: iteration number - - model: updated image - - delta_model: delta map after M-step - - processed_delta_model: delta map after post-processing - - alpha: acceleration parameter in RL algirithm - - background_normalization: optimized background normalization - - loglikelihood: log-likelihood - """ - - this_result = {"iteration": self.iteration_count, - "model": copy.deepcopy(self.model), - # "delta_model": copy.deepcopy(self.delta_model), - # "processed_delta_model": copy.deepcopy(self.processed_delta_model), - "background_normalization": copy.deepcopy(self.dict_bkg_norm), - # "alpha": self.alpha, - # "loglikelihood": copy.deepcopy(self.loglikelihood_list) - } - - # show intermediate results - # logger.info(f' alpha: {this_result["alpha"]}') - logger.info(f' background_normalization: {this_result["background_normalization"]}') - # logger.info(f' loglikelihood: {this_result["loglikelihood"]}') - - # register this_result in self.results - self.results.append(this_result) - def finalization(self): """ finalization after running the image deconvolution @@ -144,4 +114,6 @@ def Mstep(self): def post_processing(self): pass def check_stopping_criteria(self): + pass + def register_result(self): pass \ No newline at end of file diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index dc71bee7..9acbb2b4 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "e751bbd5", "metadata": { "scrolled": true @@ -42,12 +42,12 @@ { "data": { "text/html": [ - "
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        "                  performances in 3ML                                                                              \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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Now they are consistent with those of the response file.\n", - "Calculating an exposure map...\n", - "Finished...\n", - "CPU times: user 245 ms, sys: 337 ms, total: 582 ms\n", - "Wall time: 601 ms\n" + "CPU times: user 200 ms, sys: 197 ms, total: 397 ms\n", + "Wall time: 429 ms\n" ] } ], @@ -821,7 +820,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "id": "5fa73486", "metadata": {}, "outputs": [], @@ -831,7 +830,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "id": "a4b47308-3e13-400d-bebc-b5d1e093201d", "metadata": {}, "outputs": [], @@ -892,61 +891,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "id": "879053e3-ac7b-4a0a-ad58-24e3fb137065", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#### Initialization Starts ####\n", - "<< Instantiating the model class AllSkyImage >>\n", - "---- parameters ----\n", - "coordinate: galactic\n", - "energy_edges:\n", - " unit: keV\n", - " value:\n", - " - 509.0\n", - " - 513.0\n", - "nside: 16\n", - "scheme: ring\n", - "unit: cm-2 s-1 sr-1\n", - "\n", - "<< Setting initial values of the created model object >>\n", - "---- parameters ----\n", - "algorithm: flat\n", - "parameter:\n", - " unit: cm-2 s-1 sr-1\n", - " value:\n", - " - 1e-4\n", - "\n", - "<< Registering the deconvolution algorithm >>\n", - "Gaussian filter with FWHM of 2.0 deg will be applied to delta images ...\n", - "---- parameters ----\n", - "algorithm: RL\n", - "parameter:\n", - " acceleration: true\n", - " alpha_max: 10.0\n", - " background_normalization_optimization: true\n", - " background_normalization_range:\n", - " albedo:\n", - " - 0.01\n", - " - 10.0\n", - " iteration_max: 10\n", - " response_weighting: true\n", - " response_weighting_index: 0.5\n", - " save_results: false\n", - " save_results_directory: ./results\n", - " smoothing: true\n", - " smoothing_FWHM:\n", - " unit: deg\n", - " value: 2.0\n", - "\n", - "#### Initialization Finished ####\n" - ] - } - ], + "outputs": [], "source": [ "image_deconvolution.initialize()" ] @@ -963,60 +911,10 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 17, "id": "1a658d2a-4dee-4d05-83ae-d7ac06317c73", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#### Initialization Starts ####\n", - "<< Instantiating the model class AllSkyImage >>\n", - "---- parameters ----\n", - "coordinate: galactic\n", - "energy_edges:\n", - " unit: keV\n", - " value:\n", - " - 509.0\n", - " - 513.0\n", - "nside: 16\n", - "scheme: ring\n", - "unit: cm-2 s-1 sr-1\n", - "\n", - "<< Setting initial values of the created model object >>\n", - "---- parameters ----\n", - "algorithm: flat\n", - "parameter:\n", - " unit: cm-2 s-1 sr-1\n", - " value:\n", - " - 1e-4\n", - "\n", - "<< Registering the deconvolution algorithm >>\n", - "---- parameters ----\n", - "algorithm: RL\n", - "parameter:\n", - " acceleration: true\n", - " alpha_max: 2.0\n", - " background_normalization_optimization: true\n", - " background_normalization_range:\n", - " albedo:\n", - " - 0.01\n", - " - 10.0\n", - " iteration_max: 50\n", - " response_weighting: false\n", - " response_weighting_index: 0.5\n", - " save_results: false\n", - " save_results_directory: ./results\n", - " smoothing: false\n", - " smoothing_FWHM:\n", - " unit: deg\n", - " value: 2.0\n", - "\n", - "#### Initialization Finished ####\n" - ] - } - ], + "outputs": [], "source": [ "image_deconvolution.override_parameter(\"deconvolution:parameter:iteration_max = 50\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:background_normalization_optimization = True\")\n", @@ -1039,7 +937,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 18, "id": "a57fbf71-2fcc-48c4-9ac7-4c545dca67c9", "metadata": { "collapsed": true, @@ -1049,19 +947,10 @@ "scrolled": true }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#### Image Deconvolution Starts ####\n", - "<< Initialization >>\n", - "The expected count histograms were calculated with the initial model map.\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "89d1cd50288a4cc8b53a981ef6ad2c91", + "model_id": "c566470367ef4498bf41a9f4f1217d3e", "version_major": 2, "version_minor": 0 }, @@ -1072,1295 +961,157 @@ "metadata": {}, "output_type": "display_data" }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "## Iteration 1/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.190086058358472}\n", - " loglikelihood: [389620.43700901093]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 2/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.1025288937649729}\n", - " loglikelihood: [397966.1184134454]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 3/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0758137427893717}\n", - " loglikelihood: [404486.16370658483]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 4/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0350780054934294}\n", - " loglikelihood: [409379.8773129297]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 5/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0067984138659716}\n", - " loglikelihood: [412636.6223042265]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 6/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.985156644640505}\n", - " loglikelihood: [414652.8432038162]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 7/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - 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}, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9811445475083196}\n", - " loglikelihood: [419297.3156418806]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 28/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9814501457708779}\n", - " loglikelihood: [419329.29936073]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 29/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9817278823799748}\n", - " loglikelihood: [419358.7592438542]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 30/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9819833894554746}\n", - " loglikelihood: [419385.9721169963]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 31/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9822211437837377}\n", - " loglikelihood: [419411.1781302572]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 32/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9824446724033365}\n", - " loglikelihood: [419434.58626423194]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 33/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9826567290384426}\n", - " loglikelihood: [419456.37887861417]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 34/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9828594435217093}\n", - " loglikelihood: [419476.7155086895]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 35/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Post-processing >>\n", - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9830544469470661}\n", - " loglikelihood: [419495.73606062576]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 36/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9832429754605946}\n", - " loglikelihood: [419513.56351841916]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 37/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9834259555500988}\n", - " loglikelihood: [419530.3062484892]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 38/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9836040735157432}\n", - " loglikelihood: [419546.0599689196]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 39/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9837778315636565}\n", - " loglikelihood: [419560.909436545]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 40/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9839475926980296}\n", - " loglikelihood: [419574.9298950087]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 41/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9841136163173547}\n", - " loglikelihood: [419588.1883192825]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 42/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9842760861622056}\n", - " loglikelihood: [419600.74448627164]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 43/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9844351320221638}\n", - " loglikelihood: [419612.6518964899]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 44/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.984590846391934}\n", - " loglikelihood: [419623.9585680197]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 45/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9847432970746457}\n", - " loglikelihood: [419634.70772087073]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 46/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9848925365610207}\n", - " loglikelihood: [419644.93836726644]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 47/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9850386088673744}\n", - " loglikelihood: [419654.68582116824]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 48/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9851815543913989}\n", - " loglikelihood: [419663.9821384823]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 49/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9853214132384271}\n", - " loglikelihood: [419672.85649777134]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 50/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "\n", "\n", "WARNING RuntimeWarning: invalid value encountered in divide\n", "\n" @@ -2370,16 +1121,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9854582273832847}\n", - " loglikelihood: [419681.33552991366]\n", - "<< Checking Stopping Criteria >>\n", - "--> Stop\n", - "<< Finalization >>\n", - "#### Image Deconvolution Finished ####\n", - "CPU times: user 1min 59s, sys: 3min 16s, total: 5min 16s\n", - "Wall time: 1min 14s\n" + "CPU times: user 1min 33s, sys: 4min 22s, total: 5min 56s\n", + "Wall time: 46.4 s\n" ] } ], @@ -2391,7 +1134,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 34, "id": "cc64ea8d", "metadata": { "collapsed": true, @@ -2404,365 +1147,22 @@ { "data": { "text/plain": [ - "[{'iteration': 1,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 1.190086058358472},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [389620.43700901093]},\n", - " {'iteration': 2,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - 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" {'iteration': 45,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9847432970746457},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419634.70772087073]},\n", - " {'iteration': 46,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9848925365610207},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419644.93836726644]},\n", - " {'iteration': 47,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9850386088673744},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419654.68582116824]},\n", - " {'iteration': 48,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9851815543913989},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419663.9821384823]},\n", - " {'iteration': 49,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9853214132384271},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419672.85649777134]},\n", - " {'iteration': 50,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 0.9854582273832847},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [419681.33552991366]}]" + "{'iteration': 1,\n", + " 'model': ,\n", + " 'delta_model': ,\n", + " 'processed_delta_model': ,\n", + " 'background_normalization': {'albedo': 1.190086058358472},\n", + " 'alpha': 2.0,\n", + " 'loglikelihood': [389620.43700901093]}" ] }, - "execution_count": 60, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "image_deconvolution.results" + "image_deconvolution.results[0]" ] }, { From e98fb79ecc2b765b8db4817282fcb15df9b44208 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Wed, 14 Aug 2024 14:58:17 +0530 Subject: [PATCH 06/46] End-to-end working script version commit --- .../image_deconvolution/RLparallelscript.py | 146 +++-- cosipy/image_deconvolution/RichardsonLucy.py | 2 +- .../RichardsonLucyParallel.py | 69 +- .../RichardsonLucySimple.py | 2 +- .../image_deconvolution.py | 11 +- ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 618 ++++++++++-------- .../imagedeconvolution_parfile_gal_511keV.yml | 5 +- 7 files changed, 486 insertions(+), 367 deletions(-) diff --git a/cosipy/image_deconvolution/RLparallelscript.py b/cosipy/image_deconvolution/RLparallelscript.py index 5ca2141f..32493fec 100644 --- a/cosipy/image_deconvolution/RLparallelscript.py +++ b/cosipy/image_deconvolution/RLparallelscript.py @@ -3,49 +3,44 @@ import logging import argparse -# logging +# logging setup logger = logging.getLogger(__name__) -# argparse +# argparse setup parser = argparse.ArgumentParser() parser.add_argument("--numrows", type=int, dest='numrows', help="Number of rows in the response matrix") parser.add_argument("--numcols", type=int, dest='numcols', help="Number of columns in the response matrix") -parser.add_argument("--iteration_max", type=int, dest='iteration_max', help="Maximum number of iterations in RL deconvolution") -parser.add_argument("--data_dir", type=str, dest='data_dir', help="Directory where data lies") -parser.add_argument("--save_results", type=bool, dest='save_results_flag', help="Should the results be saved?") -parser.add_argument("--results_dir", type=str, dest='results_dir', help="Directory to save results (only enabled if --save_results_flag is set to True)") +parser.add_argument("--base_dir", type=str, dest='base_dir', help="Current working directory and where configuration file is assumed to lie") +parser.add_argument("--config_file", type=str, dest='config_file', help="Name of configuration file (assumed to lie in CWD)") args = parser.parse_args() -logger.info(args.numrows) -logger.info(args.numcols) -logger.info(args.iteration_max) -logger.info(args.data_dir) -logger.info(args.save_results_flag) -logger.info(args.results_dir) # Import third party libraries import numpy as np from mpi4py import MPI import h5py -from tqdm.autonotebook import tqdm +# from tqdm.autonotebook import tqdm +from yayc import Configurator -# Define the number of rows and columns +# Load configuration file +config = Configurator.open(f'{args.base_dir}/{args.config_file}') + +# Number of elements in data space (ROWS) and model space (COLS) NUMROWS = args.numrows # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS NUMCOLS = args.numcols # Define MPI and iteration misc variables MASTER = 0 # Indicates master process -MAXITER = args.iteration_max # Maximum number of iterations +MAXITER = config.get('deconvolution:parameter:iteration_max', 10) # FILE_DIR = Path(os.path.dirname(os.path.abspath(__file__))) -DATA_DIR = Path(args.data_dir) -RESULTS_DIR = Path(args.result_dir) +BASE_DIR = Path(args.base_dir) +RESULTS_DIR = BASE_DIR / config.get('deconvolution:parameter:save_results_directory', './results') ''' Response matrix ''' -def load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: - # Assuming the dataset name is "response_matrix" +def load_response_matrix(comm, start_row, end_row, filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r", driver="mpio", comm=comm) as f1: dataset = f1["response_matrix"] R = dataset[start_row:end_row, :] return R @@ -53,9 +48,8 @@ def load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_T ''' Response matrix transpose ''' -def load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r", driver="mpio", comm=comm) as f1: - # Assuming the dataset name is "response_matrix" +def load_response_matrix_transpose(comm, start_col, end_col, filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r", driver="mpio", comm=comm) as f1: dataset = f1["response_matrix"] RT = dataset[:, start_col:end_col] return RT @@ -63,9 +57,8 @@ def load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_f ''' Response matrix summed along axis=i ''' -def load_axis0_summed_response_matrix(filename='psr_gal_flattened_Ti44_E_1150_1164keV_DC2.h5'): - with h5py.File(DATA_DIR / filename, "r") as f1: - # Assuming the dataset name is "response_vector" +def load_axis0_summed_response_matrix(filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r") as f1: dataset = f1["response_vector"] Rj = dataset[:] return Rj @@ -73,27 +66,25 @@ def load_axis0_summed_response_matrix(filename='psr_gal_flattened_Ti44_E_1150_11 ''' Sky model ''' -def initial_sky_model(): - M0 = np.ones(NUMCOLS, dtype=np.float64) * 1e-4 # Initial guess according to image_deconvolution.py +def initial_sky_model(model_init_val=[1e-4]): + M0 = np.ones(NUMCOLS, dtype=np.float64) * float(model_init_val[0]) # Initial guess according to image_deconvolution.py. TODO: Make this more general than element 0 return M0 ''' Background model ''' -def load_bg_model(filename='data/total_bg_dense.hdf5'): - with h5py.File(DATA_DIR / filename) as hf_bkg: - bkg = hf_bkg['contents'][:] - return bkg +def load_bg_model(filename='bg.csv'): + bg = np.loadtxt(filename) + return bg ''' Observed data ''' -def load_signal_counts(filename='data/Ti44_CasA_x50_dense.hdf5'): - with h5py.File(DATA_DIR / filename) as hf_signal: - signal = hf_signal['contents'][:] - return signal +def load_event_data(filename='event.csv'): + event = np.loadtxt(filename) + return event -def register_result(iter, M, delta, ): +def register_result(iter, M, delta): """ The values below are stored at the end of each iteration. - iteration: iteration number @@ -121,7 +112,7 @@ def register_result(iter, M, delta, ): return this_result -def save_results(): +def save_results(results): ''' NOTE: Copied from RichardsonLucy.py ''' @@ -129,9 +120,11 @@ def save_results(): # model for this_result in results: iteration_count = this_result["iteration"] - # this_result["model"].write(f"{RESULTS_DIR}/model_itr{iteration_count}.hdf5", overwrite = True) TODO: numpy arrays do not support write_to_hdf5 as a method. Need to ensure rest of code is modified to support cosipy.image_deconvolution.allskyimage.AllSkyImageModel + # this_result["model"].write(f"{RESULTS_DIR}/model_itr{iteration_count}.hdf5", overwrite = True) # TODO: numpy arrays do not support write_to_hdf5 as a method. Need to ensure rest of code is modified to support cosipy.image_deconvolution.allskyimage.AllSkyImageModel # this_result["delta_model"].write(f"{RESULTS_DIR}/delta_model_itr{iteration_count}.hdf5", overwrite = True) # this_result["processed_delta_model"].write(f"{RESULTS_DIR}/processed_delta_model_itr{iteration_count}.hdf5", overwrite = True) TODO: processed_delta_model here is not different from delta_model + np.savetxt(f'{RESULTS_DIR}/model_itr{iteration_count}.csv', this_result['model'], delimiter=',') + np.savetxt(f'{RESULTS_DIR}/delta_model_itr{iteration_count}.csv', this_result['delta_model'], delimiter=',') # TODO: The following will be enabled once the respective calculations are incorporated # #fits @@ -162,14 +155,6 @@ def main(): numtasks = comm.Get_size() taskid = comm.Get_rank() - # Initialise vectors required by all processes - epsilon = np.zeros(NUMROWS) # All gatherv-ed. Explicit variable declaration. - epsilon_fudge = 1e-12 # To prevent divide-by-zero and underflow errors - - # Initialise epsilon_slice and C_slice. Explicit variable declarations. - epsilon_slice = np.zeros(end_row - start_row) - C_slice = np.zeros(end_col - start_col) - # Calculate the indices in Rij that the process has to parse. My hunch is that calculating these scalars individually will be faster than the MPI send broadcast overhead. averow = NUMROWS // numtasks extra_rows = NUMROWS % numtasks @@ -182,14 +167,23 @@ def main(): start_col = taskid * avecol end_col = (taskid + 1) * avecol if taskid < (numtasks - 1) else NUMCOLS + # Initialise vectors required by all processes + epsilon = np.zeros(NUMROWS) # All gatherv-ed. Explicit variable declaration. + epsilon_fudge = 1e-12 # To prevent divide-by-zero and underflow errors. Value taken from `almost_zero = 1e-12` in dataIF_COSI_DC2.py + + # Initialise epsilon_slice and C_slice. Explicit variable declarations. + epsilon_slice = np.zeros(end_row - start_row) + C_slice = np.zeros(end_col - start_col) + # Load R and RT into memory (single time if response matrix doesn't # change with time) - R = load_response_matrix(comm, start_row, end_row, filename='psr_gal_flattened_511_DC2.h5') - RT = load_response_matrix_transpose(comm, start_col, end_col, filename='psr_gal_flattened_511_DC2.h5') + R = load_response_matrix(comm, start_row, end_row) + RT = load_response_matrix_transpose(comm, start_col, end_col) - M = np.empty(NUMCOLS, dtype=np.float64) # Loaded and broadcasted by master. TODO: Correctly link variables to relevant object inputs - d = np.empty(NUMROWS, dtype=np.float64) # Loaded and broadcasted by master. - bkg = np.zeros(NUMROWS) # Loaded and broadcasted by master. + # Loaded and broadcasted by master. + M = np.empty(NUMCOLS, dtype=np.float64) + d = np.empty(NUMROWS, dtype=np.float64) + bg = np.zeros(NUMROWS) # ****************************** MPI ****************************** @@ -198,20 +192,32 @@ def main(): '''*************** Master ***************''' if taskid == MASTER: + # Pretty print definitions linebreak_stars = '**********************' linebreak_dashes = '----------------------' + # Log input information (Only master node does this) + save_results_flag = config.get('deconvolution:parameter:save_results', False) # Extract from config file + logger.info(linebreak_stars) + logger.info(f'Number of elements in data space: {NUMROWS}') + logger.info(f'Number of elements in model space: {NUMCOLS}') + logger.info(f'Base directory: {BASE_DIR}') + if save_results_flag == True: + logger.info(f'Results directory (if save_results flag is set to True): {RESULTS_DIR}') + logger.info(f'Configuration filename: {args.config_file}') + logger.info(f'Master node: {MASTER}') + logger.info(f'Maximum number of RL iterations: {MAXITER}') + # Load Rj vector (response matrix summed along axis=i) - Rj = load_axis0_summed_response_matrix(filename='psr_gal_flattened_511_DC2.h5') + Rj = load_axis0_summed_response_matrix() - # Load sky model input - M = initial_sky_model() # TODO: Correctly link variables to relevant object inputs + # Generate initial sky model from configuration file + M = initial_sky_model(model_init_val=config.get('model_definition:initialization:parameter:value', [1e-4])) - # Load observed data counts - signal = load_signal_counts(filename='511_thin_disk_dense.h5') - bkg = load_bg_model(filename='albedo_bg_dense.h5') # TODO: Correctly link variables to relevant object inputs - d = signal + bkg # TODO: Correctly link variables to relevant object inputs + # Load event data and background model (intermediate files created in RichardsonLucyParallel.py) + bg = load_bg_model() + d = load_event_data() # Sanity check: print d print() @@ -240,16 +246,16 @@ def main(): # Broadcast d vector comm.Bcast([d, MPI.DOUBLE], root=MASTER) - # Scatter bkg vector to epsilon_BG - comm.Bcast([bkg, MPI.DOUBLE], root=MASTER) - # comm.Scatter(bkg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) + # Scatter bg vector to epsilon_BG + comm.Bcast([bg, MPI.DOUBLE], root=MASTER) + # comm.Scatter(bg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) # print(f"TaskID {taskid}, gathered broadcast") # Sanity check: print epsilon # if taskid == MASTER: # print('epsilon_BG') - # print(bkg) + # print(bg) # print() # **************************** Part IIa ***************************** @@ -258,8 +264,8 @@ def main(): # Set up initial values for iterating variables. # Exit if: ## 1. Max iterations are reached - ## 2. M vector converges - for iter in tqdm(range(MAXITER)): + # for iter in tqdm(range(MAXITER)): + for iter in range(MAXITER): '''*************** Master ***************''' if taskid == MASTER: @@ -278,8 +284,8 @@ def main(): comm.Bcast([M, MPI.DOUBLE], root=MASTER) # Calculate epsilon slice - epsilon_BG = bkg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` - epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge + epsilon_BG = bg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` + epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge # TODO: For a more general implementation, see calc_expectation() in dataIF_COSI_DC2.py '''Synchronization Barrier 2''' # All vector gather epsilon slices @@ -340,8 +346,8 @@ def main(): print(linebreak_dashes) # Save iteration - if args.save_results_flag == True: - results.append(register_result()) + if save_results_flag == True: + results.append(register_result(iter, M, delta)) '''****************** End Iterative Segment ******************''' @@ -354,7 +360,7 @@ def main(): print(np.sum(M)) print() - if args.save_results_flag == True: + if save_results_flag == True: save_results(results) # MAXITER diff --git a/cosipy/image_deconvolution/RichardsonLucy.py b/cosipy/image_deconvolution/RichardsonLucy.py index 99e038d2..46eedc57 100644 --- a/cosipy/image_deconvolution/RichardsonLucy.py +++ b/cosipy/image_deconvolution/RichardsonLucy.py @@ -36,7 +36,7 @@ class RichardsonLucy(DeconvolutionAlgorithmBase): """ - def __init__(self, initial_model, dataset, mask, parameter): + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath = None): DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 6c5dcf96..53ee827f 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -1,6 +1,4 @@ import os -from pathlib import Path -import copy import subprocess import logging logger = logging.getLogger(__name__) @@ -8,7 +6,7 @@ # Import third party libraries import numpy as np import h5py -from histpy import Histogram +# from histpy import Histogram from .deconvolution_algorithm_base import DeconvolutionAlgorithmBase @@ -27,7 +25,7 @@ class RichardsonLucyParallel(DeconvolutionAlgorithmBase): background_normalization_optimization: True """ - def __init__(self, initial_model, dataset, mask, parameter): + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath): """ NOTE: Copied from RichardsonLucy.py """ @@ -62,48 +60,75 @@ def __init__(self, initial_model, dataset, mask, parameter): os.makedirs(self.save_results_directory) # Specific to parallel implementation + image_response = self.dataset[0]._image_response self.numproc = parameter.get('numproc', 1) self.iteration_max = parameter.get('iteration_max', 10) self.base_dir = os.getcwd() self.data_dir = parameter.get('data_dir', './data') # NOTE: Data should ideally be present in disk scratch space. + self.numrows = np.product(image_response.contents.shape[-3:]) # Em, Phi, PsiChi. NOTE: Change the "-3" if more general model space definitions are expected + self.numcols = np.product(image_response.contents.shape[:-3]) # Remaining columns + self.config_file = parameter_filepath + def initialization(self): + """ + initialization before running the image deconvolution + """ + # Flatten and write dense bkg and events to scratch space. + self.write_intermediate_files_to_disk() + + def write_intermediate_files_to_disk(self): + # Event + event = self.dataset[0].event.contents.flatten() + np.savetxt(self.base_dir + '/event.csv', event) + + # Background + bg = np.zeros(len(event)) + bg_models = self.dataset[0]._bkg_models + for key in bg_models: + bg += bg_models[key].contents.flatten() + np.savetxt(self.base_dir + '/bg.csv', bg) + + # Response matrix image_response = self.dataset[0]._image_response - self.numrows = np.product(image_response.contents.shape[1:]) - self.numcols = np.product(image_response.contents.shape[:1]) + new_shape = (self.numrows, self.numcols) + ndim = image_response.contents.ndim + with h5py.File(self.base_dir + '/response_matrix.h5', 'w') as output_file: + dset1 = output_file.create_dataset('response_matrix', data=np.transpose(image_response.contents, np.take(np.arange(ndim), range(ndim-3, 2*ndim-3), mode='wrap')).reshape((184320, 3072))) # NOTE: Change the "ndim-3" if more general model space definitions are expected + print(dset1.shape) + dset2 = output_file.create_dataset('response_vector', data=np.sum(dset1, axis=0)) + print(dset2.shape) def iteration(self): """ Performs all iterations of image deconvolution. - - NOTE: Overriding implementation in deconvolution_algorithm_base.py and invoking external script + NOTE: Overrides implementation in deconvolution_algorithm_base.py and invokes an external script """ - + # All arguments must be passed as type=str. Explicitly type cast boolean and number to string. subprocess.run(args=["mpiexec", "-n", str(self.numproc), "python", "mpitest.py", "--numrows", str(self.numrows), "--numcols", str(self.numcols), - "--iteration_max", str(self.iteration_max), - "--data_dir", self.data_dir, - "--save_results", str(self.save_results), - "--results_dir", self.save_results_directory], - text=True) + "--base_dir", str(self.base_dir), + "--config_file", str(self.config_file) + ], text=True) # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. return True - def initialization(self): - """ - initialization before running the image deconvolution - """ - # TODO: Write bkg and data to scratch space - pass - def finalization(self): """ finalization after running the image deconvolution """ - pass + # Delete intermediate files + self.remove_intermediate_files_from_disk() + + def remove_intermediate_files_from_disk(self): + # Ensure that the number of deletions corresponds to the + # number of file creations in write_... function + os.remove(self.base_dir + '/event.csv') + os.remove(self.base_dir + '/bg.csv') + os.remove(self.base_dir + '/response_matrix.h5') def pre_processing(self): pass diff --git a/cosipy/image_deconvolution/RichardsonLucySimple.py b/cosipy/image_deconvolution/RichardsonLucySimple.py index 65fde9d6..c9eea0c1 100644 --- a/cosipy/image_deconvolution/RichardsonLucySimple.py +++ b/cosipy/image_deconvolution/RichardsonLucySimple.py @@ -22,7 +22,7 @@ class RichardsonLucySimple(DeconvolutionAlgorithmBase): background_normalization_optimization: True """ - def __init__(self, initial_model, dataset, mask, parameter): + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath = None): DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) diff --git a/cosipy/image_deconvolution/image_deconvolution.py b/cosipy/image_deconvolution/image_deconvolution.py index e07c4d85..9720875f 100644 --- a/cosipy/image_deconvolution/image_deconvolution.py +++ b/cosipy/image_deconvolution/image_deconvolution.py @@ -62,6 +62,7 @@ def read_parameterfile(self, parameter_filepath): Path of parameter file. """ + self._parameter_filepath = parameter_filepath self._parameter = Configurator.open(parameter_filepath) logger.debug(f"parameter file for image deconvolution was set -> {parameter_filepath}") @@ -80,6 +81,13 @@ def parameter(self): """ return self._parameter + @property + def parameter_filepath(self): + """ + Return the registered parameter filepath. + """ + return self._parameter_filepath + def override_parameter(self, *args): """ Override parameter @@ -199,7 +207,8 @@ def register_deconvolution_algorithm(self): self._deconvolution = self._deconvolution_class(initial_model = self.initial_model, dataset = self.dataset, mask = self.mask, - parameter = algorithm_parameter) + parameter = algorithm_parameter, + parameter_filepath = self.parameter_filepath) logger.info("---- parameters ----") logger.info(parameter_deconvolution.dump()) diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index 9acbb2b4..5aa59b02 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "e751bbd5", "metadata": { "scrolled": true @@ -42,12 +42,12 @@ { "data": { "text/html": [ - "
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"[penguin:04495] shmem: mmap: an error occurred while determining whether or not /var/folders/5w/bxqs6l5j65vfrl397w9mj1kc0000gn/T//ompi.penguin.501/jf.0/1943732224/sm_segment.penguin.501.73db0000.0 could be created.\n" + "[penguin:50890] shmem: mmap: an error occurred while determining whether or not /var/folders/5w/bxqs6l5j65vfrl397w9mj1kc0000gn/T//ompi.penguin.501/jf.0/92012544/sm_segment.penguin.501.57c0000.0 could be created.\n" ] }, { "data": { "text/html": [ - "
20:31:14 WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
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09:37:36 WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
        "                  require the C/C++ interface (currently HAWC)                                                     \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mrequire the C/C++ interface \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mcurrently HAWC\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m                                      \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m              \u001b[0m\n"
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20:31:14 WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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        "
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+       "\u001b[38;5;46m09:37:36\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed                                             \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=280182;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=274921;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n"
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Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=956922;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=141419;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=340645;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=921794;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -294,23 +294,12 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=397152;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=171896;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=960904;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=376459;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" - }, - { - "ename": "NameError", - "evalue": "name 'cycler' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 39\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# Matplotlib style template\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m## For black, set #000000. For navy, set #002060\u001b[39;00m\n\u001b[1;32m 36\u001b[0m defaultcolor \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m#002060\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 37\u001b[0m plt\u001b[38;5;241m.\u001b[39mrcParams\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtext.color\u001b[39m\u001b[38;5;124m'\u001b[39m: defaultcolor, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124maxes.labelcolor\u001b[39m\u001b[38;5;124m'\u001b[39m: defaultcolor, \n\u001b[1;32m 38\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mxtick.color\u001b[39m\u001b[38;5;124m'\u001b[39m: defaultcolor, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mytick.color\u001b[39m\u001b[38;5;124m'\u001b[39m: defaultcolor,\n\u001b[0;32m---> 39\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124maxes.prop_cycle\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[43mcycler\u001b[49m(color\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlimegreen\u001b[39m\u001b[38;5;124m'\u001b[39m]),\n\u001b[1;32m 40\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfont.family\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mserif\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfont.serif\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mTimes New Roman\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 41\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfont.size\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m22\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlines.linewidth\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m3\u001b[39m,\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfigure.figsize\u001b[39m\u001b[38;5;124m'\u001b[39m: (\u001b[38;5;241m9.6\u001b[39m, \u001b[38;5;241m5.4\u001b[39m), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfigure.dpi\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m100\u001b[39m})\n", - "\u001b[0;31mNameError\u001b[0m: name 'cycler' is not defined" - ] } ], "source": [ @@ -343,6 +332,7 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from matplotlib.gridspec import GridSpec \n", + "from matplotlib import cycler\n", "\n", "import healpy as hp\n", "from tqdm.autonotebook import tqdm\n", @@ -358,6 +348,87 @@ " 'figure.figsize': (9.6, 5.4), 'figure.dpi': 100})" ] }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a89ac003", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Observed data-space d vector:\n", + "[0. 0. 0. ... 0. 1. 0.]\n", + "\n", + "**********************\n", + "Starting iteration 1\n", + "Done\n", + "----------------------\n", + "Starting iteration 2\n", + "Done\n", + "----------------------\n", + "Starting iteration 3\n", + "Done\n", + "----------------------\n", + "Starting iteration 4\n", + "Done\n", + "----------------------\n", + "Starting iteration 5\n", + "Done\n", + "----------------------\n", + "Starting iteration 6\n", + "Done\n", + "----------------------\n", + "Starting iteration 7\n", + "Done\n", + "----------------------\n", + "Starting iteration 8\n", + "Done\n", + "----------------------\n", + "Starting iteration 9\n", + "Done\n", + "----------------------\n", + "Starting iteration 10\n", + "Done\n", + "----------------------\n", + "Converged M vector:\n", + "[0. 0. 0. ... 0. 0. 0.]\n", + "2e-05\n", + "0.0027317294547643117\n", + "\n", + "Reached maximum iterations = 10\n", + "**********************\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "CompletedProcess(args=['mpiexec', '-n', '1', 'python', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numcols', '3072', '--numrows', '184320', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml'], returncode=0)" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "import subprocess\n", + "\n", + "numproc = 1\n", + "filepath = \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\"\n", + "config_file = 'imagedeconvolution_parfile_gal_511keV.yml'\n", + "subprocess.run(args=[\"mpiexec\", \"-n\", str(numproc), \"python\", f\"{filepath}/RLparallelscript.py\", \n", + " \"--numcols\", str(3072),\n", + " \"--numrows\", str(184320),\n", + " \"--base_dir\", os.getcwd(),\n", + " \"--config_file\", config_file\n", + " ])" + ] + }, { "cell_type": "markdown", "id": "00f20cda-81f8-4685-b9c4-f9423e5ebcf7", @@ -449,24 +520,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 6, "id": "9cae1835-e54b-4720-b3a6-196c42cbd1ce", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "binning data...\n", - "Time unit: s\n", - "Em unit: keV\n", - "Phi unit: deg\n", - "PsiChi unit: None\n", - "CPU times: user 6.47 s, sys: 184 ms, total: 6.66 s\n", - "Wall time: 6.72 s\n" - ] - } - ], + "outputs": [], "source": [ "# %%time\n", "\n", @@ -487,24 +544,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "id": "801ba251-96e0-4243-8f55-1678823f1d58", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "binning data...\n", - "Time unit: s\n", - "Em unit: keV\n", - "Phi unit: deg\n", - "PsiChi unit: None\n", - "CPU times: user 1min 32s, sys: 2.64 s, total: 1min 35s\n", - "Wall time: 1min 36s\n" - ] - } - ], + "outputs": [], "source": [ "# %%time\n", "\n", @@ -525,7 +568,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 8, "id": "f224b957-d0df-4b4b-98dd-90d3a5bda3fb", "metadata": {}, "outputs": [], @@ -545,7 +588,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "24289425-380b-4d26-a7c0-cbbd5c58e7b2", "metadata": {}, "outputs": [], @@ -565,7 +608,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 10, "id": "41371ac9", "metadata": {}, "outputs": [], @@ -576,7 +619,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 11, "id": "e0f3dcae-5d3c-45af-931d-057d5681859c", "metadata": {}, "outputs": [], @@ -598,7 +641,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "id": "88efdbfa-aa5e-40b3-bdd6-2635946318e4", "metadata": {}, "outputs": [ @@ -611,7 +654,7 @@ "" ] }, - "execution_count": 4, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -630,7 +673,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 13, "id": "b5b295cf-0a96-4501-aa4e-4182a21dfe63", "metadata": {}, "outputs": [ @@ -638,8 +681,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.07 s, sys: 12.5 s, total: 15.6 s\n", - "Wall time: 29.8 s\n" + "CPU times: user 3.03 s, sys: 12.4 s, total: 15.4 s\n", + "Wall time: 28.7 s\n" ] } ], @@ -653,7 +696,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "id": "fbdbd818-8a58-4d25-a657-d43fc7f88ea4", "metadata": {}, "outputs": [ @@ -663,7 +706,7 @@ "array(['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi'], dtype=' pass (edges)\n", + "... checking the axis Phi of the event and background files...\n", + " --> pass (edges)\n", + "... checking the axis PsiChi of the event and background files...\n", + " --> pass (edges)\n", + "...checking the axis Em of the event and response files...\n", + " --> pass (edges)\n", + "...checking the axis Phi of the event and response files...\n", + " --> pass (edges)\n", + "...checking the axis PsiChi of the event and response files...\n", + " --> pass (edges)\n", + "The axes in the event and background files are redefined. Now they are consistent with those of the response file.\n", + "Calculating an exposure map...\n", + "Finished...\n", + "CPU times: user 203 ms, sys: 197 ms, total: 400 ms\n", + "Wall time: 435 ms\n" ] } ], @@ -820,7 +878,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 17, "id": "5fa73486", "metadata": {}, "outputs": [], @@ -830,7 +888,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 18, "id": "a4b47308-3e13-400d-bebc-b5d1e093201d", "metadata": {}, "outputs": [], @@ -891,10 +949,62 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 19, "id": "879053e3-ac7b-4a0a-ad58-24e3fb137065", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "#### Initialization Starts ####\n", + "<< Instantiating the model class AllSkyImage >>\n", + "---- parameters ----\n", + "coordinate: galactic\n", + "energy_edges:\n", + " unit: keV\n", + " value:\n", + " - 509.0\n", + " - 513.0\n", + "nside: 16\n", + "scheme: ring\n", + "unit: cm-2 s-1 sr-1\n", + "\n", + "<< Setting initial values of the created model object >>\n", + "---- parameters ----\n", + "algorithm: flat\n", + "parameter:\n", + " unit: cm-2 s-1 sr-1\n", + " value:\n", + " - 1e-4\n", + "\n", + "<< Registering the deconvolution algorithm >>\n", + "---- parameters ----\n", + "algorithm: RLparallel\n", + "parameter:\n", + " acceleration: true\n", + " alpha_max: 10.0\n", + " background_normalization_optimization: true\n", + " background_normalization_range:\n", + " albedo:\n", + " - 0.01\n", + " - 10.0\n", + " data_directory: ''\n", + " iteration_max: 10\n", + " numproc: 6\n", + " response_weighting: true\n", + " response_weighting_index: 0.5\n", + " save_results: false\n", + " save_results_directory: ./results\n", + " smoothing: true\n", + " smoothing_FWHM:\n", + " unit: deg\n", + " value: 2.0\n", + "\n", + "#### Initialization Finished ####\n" + ] + } + ], "source": [ "image_deconvolution.initialize()" ] @@ -911,12 +1021,64 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 20, "id": "1a658d2a-4dee-4d05-83ae-d7ac06317c73", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "#### Initialization Starts ####\n", + "<< Instantiating the model class AllSkyImage >>\n", + "---- parameters ----\n", + "coordinate: galactic\n", + "energy_edges:\n", + " unit: keV\n", + " value:\n", + " - 509.0\n", + " - 513.0\n", + "nside: 16\n", + "scheme: ring\n", + "unit: cm-2 s-1 sr-1\n", + "\n", + "<< Setting initial values of the created model object >>\n", + "---- parameters ----\n", + "algorithm: flat\n", + "parameter:\n", + " unit: cm-2 s-1 sr-1\n", + " value:\n", + " - 1e-4\n", + "\n", + "<< Registering the deconvolution algorithm >>\n", + "---- parameters ----\n", + "algorithm: RLparallel\n", + "parameter:\n", + " acceleration: true\n", + " alpha_max: 2.0\n", + " background_normalization_optimization: true\n", + " background_normalization_range:\n", + " albedo:\n", + " - 0.01\n", + " - 10.0\n", + " data_directory: ''\n", + " iteration_max: 10\n", + " numproc: 6\n", + " response_weighting: false\n", + " response_weighting_index: 0.5\n", + " save_results: false\n", + " save_results_directory: ./results\n", + " smoothing: false\n", + " smoothing_FWHM:\n", + " unit: deg\n", + " value: 2.0\n", + "\n", + "#### Initialization Finished ####\n" + ] + } + ], "source": [ - "image_deconvolution.override_parameter(\"deconvolution:parameter:iteration_max = 50\")\n", + "# image_deconvolution.override_parameter(\"deconvolution:parameter:iteration_max = 50\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:background_normalization_optimization = True\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:alpha_max = 2.0\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:smoothing = False\")\n", @@ -937,7 +1099,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "id": "a57fbf71-2fcc-48c4-9ac7-4c545dca67c9", "metadata": { "collapsed": true, @@ -947,182 +1109,95 @@ "scrolled": true }, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "#### Image Deconvolution Starts ####\n", + "<< Initialization >>\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c566470367ef4498bf41a9f4f1217d3e", + "model_id": "41a85f73c3214e109c26912f22b18449", "version_major": 2, "version_minor": 0 }, "text/plain": [ - " 0%| | 0/50 [00:00>\n", + "#### Image Deconvolution Finished ####\n", + "CPU times: user 8.56 ms, sys: 44.2 ms, total: 52.7 ms\n", + "Wall time: 325 ms\n" ] }, { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "CPU times: user 1min 33s, sys: 4min 22s, total: 5min 56s\n", - "Wall time: 46.4 s\n" + "100%|██████████| 10/10 [00:00<00:00, 101067.57it/s]\n" ] } ], @@ -1134,7 +1209,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 22, "id": "cc64ea8d", "metadata": { "collapsed": true, @@ -1145,26 +1220,31 @@ }, "outputs": [ { - "data": { - "text/plain": [ - "{'iteration': 1,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 1.190086058358472},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [389620.43700901093]}" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" + "ename": "IndexError", + "evalue": "list index out of range", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mimage_deconvolution\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresults\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n", + "\u001b[0;31mIndexError\u001b[0m: list index out of range" + ] } ], "source": [ "image_deconvolution.results[0]" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "b0e2c89a", + "metadata": {}, + "outputs": [], + "source": [ + "raise" + ] + }, { "cell_type": "markdown", "id": "9d32d0a8", @@ -1186,7 +1266,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": null, "id": "445ee3d5", "metadata": {}, "outputs": [ @@ -1227,7 +1307,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "id": "1695af05", "metadata": {}, "outputs": [ @@ -1268,7 +1348,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": null, "id": "71ad8d7a", "metadata": {}, "outputs": [ @@ -1307,7 +1387,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "id": "94ab604d-12d9-4f81-b8d1-7dcbe793b6e8", "metadata": { "scrolled": true @@ -1341,7 +1421,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": null, "id": "2769b6e5", "metadata": {}, "outputs": [ @@ -1372,7 +1452,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": null, "id": "79bde8df-6fa3-430f-895e-06d7e6f91a9f", "metadata": {}, "outputs": [ @@ -1435,7 +1515,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": null, "id": "2e91030b-0ae0-4d77-8bf8-e51bb636536c", "metadata": {}, "outputs": [ @@ -1483,7 +1563,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.12.2" } }, "nbformat": 4, diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 5264b916..29939b49 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -34,7 +34,6 @@ deconvolution: unit: "deg" background_normalization_optimization: True background_normalization_range: {"albedo": [0.01, 10.0]} - save_results: False - save_results_directory: "./results" - data_directory: "" # Absolute file path to directory where data lies + save_results: True + save_results_directory: "./results" # Relative file path numproc: 6 # Number of MPI threads to spawn. Limited by number of nodes available. Only applicable for algorithm: "RLparallel" \ No newline at end of file From cd45e445b0eca6d76358e78e823d92853d8145e7 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Wed, 14 Aug 2024 18:58:41 +0530 Subject: [PATCH 07/46] Unclear what files are causing conflicts --- .../image_deconvolution/RLparallelscript.py | 1 - .../RichardsonLucyParallel.py | 29 +- ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 1731 +++++++++++++++-- 3 files changed, 1575 insertions(+), 186 deletions(-) diff --git a/cosipy/image_deconvolution/RLparallelscript.py b/cosipy/image_deconvolution/RLparallelscript.py index 32493fec..1277dbb4 100644 --- a/cosipy/image_deconvolution/RLparallelscript.py +++ b/cosipy/image_deconvolution/RLparallelscript.py @@ -18,7 +18,6 @@ import numpy as np from mpi4py import MPI import h5py -# from tqdm.autonotebook import tqdm from yayc import Configurator # Load configuration file diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 53ee827f..745dd995 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -93,10 +93,14 @@ def write_intermediate_files_to_disk(self): new_shape = (self.numrows, self.numcols) ndim = image_response.contents.ndim with h5py.File(self.base_dir + '/response_matrix.h5', 'w') as output_file: - dset1 = output_file.create_dataset('response_matrix', data=np.transpose(image_response.contents, np.take(np.arange(ndim), range(ndim-3, 2*ndim-3), mode='wrap')).reshape((184320, 3072))) # NOTE: Change the "ndim-3" if more general model space definitions are expected - print(dset1.shape) + dset1 = output_file.create_dataset('response_matrix', data=np.transpose(image_response.contents, + np.take(np.arange(ndim), + range(ndim-3, 2*ndim-3), + mode='wrap') + ).reshape(new_shape)) # NOTE: Change the "ndim-3" if more general model space definitions are expected + logger.info(f'Shape of response matrix {dset1.shape}') dset2 = output_file.create_dataset('response_vector', data=np.sum(dset1, axis=0)) - print(dset2.shape) + logger.info(f'Shape of response vector summed along axis=0 {dset2.shape}') def iteration(self): """ @@ -105,12 +109,19 @@ def iteration(self): """ # All arguments must be passed as type=str. Explicitly type cast boolean and number to string. - subprocess.run(args=["mpiexec", "-n", str(self.numproc), "python", "mpitest.py", - "--numrows", str(self.numrows), - "--numcols", str(self.numcols), - "--base_dir", str(self.base_dir), - "--config_file", str(self.config_file) - ], text=True) + # FILE_DIR = os.path.dirname(os.path.abspath(__file__)) # Path to directory containing RichardsonLucyParallel.py + # logger.info(f'Subprocess call to run RLparallelscript.py at {FILE_DIR}') + + # stdout = subprocess.check_output(args=["mpiexec", "-n", str(self.numproc), + # "python", "mpitest.py", # RLparallelscript.py will be installed in the same directory as RichardsonLucyParallel.py + # "--numrows", str(self.numrows), + # "--numcols", str(self.numcols), + # "--base_dir", str(self.base_dir), + # "--config_file", str(self.config_file) + # ], text=True) + # print(stdout) + + subprocess.run() # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index 5aa59b02..e74a1799 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -42,12 +42,12 @@ { "data": { "text/html": [ - "
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09:37:36 WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
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        "                  require the C/C++ interface (currently HAWC)                                                     \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mrequire the C/C++ interface \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mcurrently HAWC\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m                                      \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m              \u001b[0m\n"
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        "                  performances in 3ML                                                                              \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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@@ -294,7 +287,7 @@
        "
\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=960904;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=376459;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=47220;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=527768;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -350,9 +343,155 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, + "id": "d6b01b44", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hello, World! I am process 0 of 4.\n", + "\n", + "Hello, World! I am process 1 of 4.\n", + "\n", + "Hello, World! I am process 2 of 4.\n", + "\n", + "Hello, World! I am process 3 of 4.\n", + "\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", + "184320\n", + "3072\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", + "imagedeconvolution_parfile_gal_511keV.yml\n", + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [00:00<00:00, 19231.10it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "CompletedProcess(args=['mpiexec', '-n', '4', 'python', 'mpitest.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml'], returncode=0)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subprocess.run(args=[\"mpiexec\", \"-n\", str(4), \"python\", \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py\", \n", + " \"--numrows\", str(184320),\n", + " \"--numcols\", str(3072),\n", + " \"--base_dir\", str('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS'),\n", + " \"--config_file\", str('imagedeconvolution_parfile_gal_511keV.yml')\n", + " ], text=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, "id": "a89ac003", "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "python: can't open file '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py': [Errno 2] No such file or directory\n", + "--------------------------------------------------------------------------\n", + "Primary job terminated normally, but 1 process returned\n", + "a non-zero exit code. Per user-direction, the job has been aborted.\n", + "--------------------------------------------------------------------------\n", + "--------------------------------------------------------------------------\n", + "mpiexec detected that one or more processes exited with non-zero status, thus causing\n", + "the job to be terminated. The first process to do so was:\n", + "\n", + " Process name: [[64571,1],0]\n", + " Exit code: 2\n", + "--------------------------------------------------------------------------\n" + ] + }, + { + "ename": "CalledProcessError", + "evalue": "Command '['mpiexec', '-n', '1', 'python', '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml']' returned non-zero exit status 2.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mCalledProcessError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[17], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msubprocess\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m stdout \u001b[38;5;241m=\u001b[39m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheck_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmpiexec\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m-n\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpython\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/RLparallelscript.py\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--numrows\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m184320\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--numcols\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3072\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--base_dir\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--config_file\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mimagedeconvolution_parfile_gal_511keV.yml\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;66;03m# print(stdout)\u001b[39;00m\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/subprocess.py:421\u001b[0m, in \u001b[0;36mcheck_output\u001b[0;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 418\u001b[0m empty \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 419\u001b[0m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minput\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m empty\n\u001b[0;32m--> 421\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpopenargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheck\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 422\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mstdout\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/subprocess.py:526\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 524\u001b[0m retcode \u001b[38;5;241m=\u001b[39m process\u001b[38;5;241m.\u001b[39mpoll()\n\u001b[1;32m 525\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check \u001b[38;5;129;01mand\u001b[39;00m retcode:\n\u001b[0;32m--> 526\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CalledProcessError(retcode, process\u001b[38;5;241m.\u001b[39margs,\n\u001b[1;32m 527\u001b[0m output\u001b[38;5;241m=\u001b[39mstdout, stderr\u001b[38;5;241m=\u001b[39mstderr)\n\u001b[1;32m 528\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m CompletedProcess(process\u001b[38;5;241m.\u001b[39margs, retcode, stdout, stderr)\n", + "\u001b[0;31mCalledProcessError\u001b[0m: Command '['mpiexec', '-n', '1', 'python', '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml']' returned non-zero exit status 2." + ] + } + ], + "source": [ + "import subprocess\n", + "stdout = subprocess.check_output(args=[\"mpiexec\", \"-n\", str(1), \"python\", \"/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\"+\"/RLparallelscript.py\", \n", + " \"--numrows\", str(184320),\n", + " \"--numcols\", str(3072),\n", + " \"--base_dir\", str('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS'),\n", + " \"--config_file\", str('imagedeconvolution_parfile_gal_511keV.yml')\n", + " ], text=True)\n", + "# print(stdout)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "cb594af4", + "metadata": {}, "outputs": [ { "name": "stdout", @@ -400,33 +539,13 @@ "\n", "Reached maximum iterations = 10\n", "**********************\n", + "\n", "\n" ] - }, - { - "data": { - "text/plain": [ - "CompletedProcess(args=['mpiexec', '-n', '1', 'python', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numcols', '3072', '--numrows', '184320', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml'], returncode=0)" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ - "import os\n", - "import subprocess\n", - "\n", - "numproc = 1\n", - "filepath = \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\"\n", - "config_file = 'imagedeconvolution_parfile_gal_511keV.yml'\n", - "subprocess.run(args=[\"mpiexec\", \"-n\", str(numproc), \"python\", f\"{filepath}/RLparallelscript.py\", \n", - " \"--numcols\", str(3072),\n", - " \"--numrows\", str(184320),\n", - " \"--base_dir\", os.getcwd(),\n", - " \"--config_file\", config_file\n", - " ])" + "print(stdout)" ] }, { @@ -462,7 +581,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "cafd42c7-7f7f-4e6e-acd7-8e76eb5160dc", "metadata": {}, "outputs": [], @@ -476,7 +595,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "ae368f5f-2d30-4ba6-a152-c5bbb4187471", "metadata": {}, "outputs": [], @@ -489,7 +608,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "dddb7361-a523-42b4-93fe-da0b3ce75deb", "metadata": {}, "outputs": [], @@ -520,7 +639,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "9cae1835-e54b-4720-b3a6-196c42cbd1ce", "metadata": {}, "outputs": [], @@ -544,7 +663,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "801ba251-96e0-4243-8f55-1678823f1d58", "metadata": {}, "outputs": [], @@ -568,7 +687,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "f224b957-d0df-4b4b-98dd-90d3a5bda3fb", "metadata": {}, "outputs": [], @@ -588,7 +707,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "24289425-380b-4d26-a7c0-cbbd5c58e7b2", "metadata": {}, "outputs": [], @@ -608,7 +727,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "41371ac9", "metadata": {}, "outputs": [], @@ -619,7 +738,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "e0f3dcae-5d3c-45af-931d-057d5681859c", "metadata": {}, "outputs": [], @@ -641,7 +760,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "88efdbfa-aa5e-40b3-bdd6-2635946318e4", "metadata": {}, "outputs": [ @@ -654,7 +773,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -673,7 +792,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "b5b295cf-0a96-4501-aa4e-4182a21dfe63", "metadata": {}, "outputs": [ @@ -681,8 +800,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.03 s, sys: 12.4 s, total: 15.4 s\n", - "Wall time: 28.7 s\n" + "CPU times: user 3.62 s, sys: 20.5 s, total: 24.1 s\n", + "Wall time: 52.6 s\n" ] } ], @@ -696,7 +815,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "fbdbd818-8a58-4d25-a657-d43fc7f88ea4", "metadata": {}, "outputs": [ @@ -706,7 +825,7 @@ "array(['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi'], dtype='>\n", + "A directory ./results already exists. Files in ./results may be overwritten. Make sure that is not a problem.\n", "---- parameters ----\n", "algorithm: RLparallel\n", "parameter:\n", @@ -989,12 +1109,11 @@ " albedo:\n", " - 0.01\n", " - 10.0\n", - " data_directory: ''\n", - " iteration_max: 10\n", + " iteration_max: 50\n", " numproc: 6\n", " response_weighting: true\n", " response_weighting_index: 0.5\n", - " save_results: false\n", + " save_results: true\n", " save_results_directory: ./results\n", " smoothing: true\n", " smoothing_FWHM:\n", @@ -1021,7 +1140,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "1a658d2a-4dee-4d05-83ae-d7ac06317c73", "metadata": {}, "outputs": [ @@ -1052,7 +1171,7 @@ "\n", "<< Registering the deconvolution algorithm >>\n", "---- parameters ----\n", - "algorithm: RLparallel\n", + "algorithm: RL\n", "parameter:\n", " acceleration: true\n", " alpha_max: 2.0\n", @@ -1061,8 +1180,7 @@ " albedo:\n", " - 0.01\n", " - 10.0\n", - " data_directory: ''\n", - " iteration_max: 10\n", + " iteration_max: 50\n", " numproc: 6\n", " response_weighting: false\n", " response_weighting_index: 0.5\n", @@ -1078,11 +1196,13 @@ } ], "source": [ - "# image_deconvolution.override_parameter(\"deconvolution:parameter:iteration_max = 50\")\n", + "image_deconvolution.override_parameter(\"deconvolution:parameter:iteration_max = 50\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:background_normalization_optimization = True\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:alpha_max = 2.0\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:smoothing = False\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:response_weighting = False\")\n", + "image_deconvolution.override_parameter(\"deconvolution:parameter:save_results = False\")\n", + "image_deconvolution.override_parameter(\"deconvolution:algorithm = RL\")\n", "\n", "image_deconvolution.initialize()" ] @@ -1099,7 +1219,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "id": "a57fbf71-2fcc-48c4-9ac7-4c545dca67c9", "metadata": { "collapsed": true, @@ -1114,18 +1234,19 @@ "output_type": "stream", "text": [ "#### Image Deconvolution Starts ####\n", - "<< Initialization >>\n" + "<< Initialization >>\n", + "The expected count histograms were calculated with the initial model map.\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "41a85f73c3214e109c26912f22b18449", + "model_id": "0a5572e469264dd283ae5bdcb0d32774", "version_major": 2, "version_minor": 0 }, "text/plain": [ - " 0%| | 0/10 [00:00>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "\n", - "Hello, World! I am process 5 of 6.\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 1.190086058358472}\n", + " loglikelihood: [389620.43700901093]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 2/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "\n", - " 0%| | 0/10 [00:00>\n", - "#### Image Deconvolution Finished ####\n", - "CPU times: user 8.56 ms, sys: 44.2 ms, total: 52.7 ms\n", - "Wall time: 325 ms\n" + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 1.1025288937649729}\n", + " loglikelihood: [397966.1184134454]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 3/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:00<00:00, 101067.57it/s]\n" + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" ] - } - ], - "source": [ - "%%time\n", - "\n", - "image_deconvolution.run_deconvolution()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "cc64ea8d", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true }, - "scrolled": true - }, - "outputs": [ { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mimage_deconvolution\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresults\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n", - "\u001b[0;31mIndexError\u001b[0m: list index out of range" + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 1.0758137427893717}\n", + " loglikelihood: [404486.16370658483]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 4/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" ] - } + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 1.0350780054934294}\n", + " loglikelihood: [409379.8773129297]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 5/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 1.0067984138659716}\n", + " loglikelihood: [412636.6223042265]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 6/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.985156644640505}\n", + " loglikelihood: [414652.8432038162]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 7/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9720022993182517}\n", + " loglikelihood: [415871.5890431596]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 8/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9647331909406436}\n", + " loglikelihood: [416634.49362002616]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 9/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9618007024814392}\n", + " loglikelihood: [417146.494831466]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 10/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9614669811731035}\n", + " loglikelihood: [417517.0766809179]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 11/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9626309655788825}\n", + " loglikelihood: [417802.0571046409]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 12/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9645047367641191}\n", + " loglikelihood: [418030.60138296254]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 13/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9666322970227704}\n", + " loglikelihood: [418219.05430964916]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 14/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9687449645442027}\n", + " loglikelihood: [418377.4557194025]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 15/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.970708567948022}\n", + " loglikelihood: [418512.5036855284]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 16/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9724635379800978}\n", + " loglikelihood: [418628.95036220574]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 17/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9739955171908575}\n", + " loglikelihood: [418730.3084008504]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 18/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9753132429889781}\n", + " loglikelihood: [418819.247143395]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 19/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9764369687276027}\n", + " loglikelihood: [418897.8365083168]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 20/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9773911433114139}\n", + " loglikelihood: [418967.70833261264]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 21/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.978200663714772}\n", + " loglikelihood: [419030.1679826325]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 22/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9788888402984666}\n", + " loglikelihood: [419086.2736994118]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 23/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9794765199076383}\n", + " loglikelihood: [419136.89394879853]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 24/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.979981789196119}\n", + " loglikelihood: [419182.7493856037]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 25/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9804200184058396}\n", + " loglikelihood: [419224.4438976394]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 26/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9808040644678145}\n", + " loglikelihood: [419262.48783887096]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 27/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9811445475083197}\n", + " loglikelihood: [419297.3156418806]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 28/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.981450145770878}\n", + " loglikelihood: [419329.29936073]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 29/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9817278823799749}\n", + " loglikelihood: [419358.7592438542]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 30/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9819833894554747}\n", + " loglikelihood: [419385.9721169963]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 31/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.982221143783738}\n", + " loglikelihood: [419411.1781302573]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 32/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9824446724033364}\n", + " loglikelihood: [419434.5862642322]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 33/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9826567290384427}\n", + " loglikelihood: [419456.37887861405]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 34/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9828594435217094}\n", + " loglikelihood: [419476.7155086893]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 35/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.983054446947066}\n", + " loglikelihood: [419495.73606062576]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 36/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9832429754605947}\n", + " loglikelihood: [419513.56351841916]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 37/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9834259555500987}\n", + " loglikelihood: [419530.3062484893]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 38/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9836040735157431}\n", + " loglikelihood: [419546.0599689197]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 39/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9837778315636562}\n", + " loglikelihood: [419560.9094365451]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 40/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9839475926980294}\n", + " loglikelihood: [419574.9298950087]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 41/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9841136163173546}\n", + " loglikelihood: [419588.1883192825]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 42/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9842760861622055}\n", + " loglikelihood: [419600.74448627164]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 43/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9844351320221637}\n", + " loglikelihood: [419612.65189649]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 44/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9845908463919338}\n", + " loglikelihood: [419623.9585680199]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 45/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9847432970746456}\n", + " loglikelihood: [419634.7077208706]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 46/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9848925365610206}\n", + " loglikelihood: [419644.9383672667]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 47/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.985038608867374}\n", + " loglikelihood: [419654.68582116824]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 48/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9851815543913988}\n", + " loglikelihood: [419663.98213848204]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 49/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.985321413238427}\n", + " loglikelihood: [419672.85649777134]\n", + "<< Checking Stopping Criteria >>\n", + "--> Continue\n", + "## Iteration 50/50 ##\n", + "<< Pre-processing >>\n", + "<< E-step >>\n", + "<< M-step >>\n", + "<< Post-processing >>\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "WARNING RuntimeWarning: invalid value encountered in divide\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<< Registering Result >>\n", + " alpha: 2.0\n", + " background_normalization: {'albedo': 0.9854582273832846}\n", + " loglikelihood: [419681.33552991366]\n", + "<< Checking Stopping Criteria >>\n", + "--> Stop\n", + "<< Finalization >>\n", + "#### Image Deconvolution Finished ####\n", + "CPU times: user 3min 15s, sys: 2min 48s, total: 6min 3s\n", + "Wall time: 48.5 s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "image_deconvolution.run_deconvolution()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "cc64ea8d", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'iteration': 1,\n", + " 'model': ,\n", + " 'delta_model': ,\n", + " 'processed_delta_model': ,\n", + " 'background_normalization': {'albedo': 1.190086058358472},\n", + " 'alpha': 2.0,\n", + " 'loglikelihood': [389620.43700901093]}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } ], "source": [ "image_deconvolution.results[0]" @@ -1237,10 +2604,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "b0e2c89a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "RuntimeError", + "evalue": "No active exception to reraise", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[24], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n", + "\u001b[0;31mRuntimeError\u001b[0m: No active exception to reraise" + ] + } + ], "source": [ "raise" ] @@ -1452,13 +2831,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "79bde8df-6fa3-430f-895e-06d7e6f91a9f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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XcWAYEIYch8uXL0/9d6fTwUte8hL8yq/8Ct7ylrfgH/2jf4TNzU381m/9FjqdDv7BP/gHc9sHlxNRrVajv0kQCwB/8zd/g6c+9ak4d+4cvuEbvgHf/M3fjJWVFVQqFXzxi1/Em9/85qnB5+KC+Krouf4ux9Is+OCSfSxd+vCHP4znPOc52N/fx3Of+1z83b/7d7G8vIw8z/Hnf/7nePvb3+4cLD9P3XzzzXjBC16A//Af/sO4+iEwOeZyjGzJ301XTyvfMtVq1VkoY14qex8AcM5DBgyvv+c85zn4yEc+gsc//vH4vu/7Ppw8eRK1Wg0A8NrXvnYu51COt6+Ay+nTp3Hvvffi/PnzU/dL6FgDQL/fP3DfkpKSrnwlIEpKSorq5MmTAIZfgo+jfv3Xfx2/8Au/gNe+9rUYDAb42Z/92anfJUD6iZ/4CfziL/4ite6Xv/zl+JVf+RX82q/9Gv7RP/pH+K3f+i1cunQJL33pSxdaKa+MfvEXfxFnzpzBm970ppnKa29961vx5je/eepv0v+HHnrIuT7X3+VYfvzjH8cTnvCEA/X353/+57G9vY33vOc9M4UHXve61+Htb3/7gdavlev6vuuuuwBgxiET/fVf/zUAONMKj6sOch+4UuIA4O1vfzs+8pGP4Ad/8Afxpje9aeq3Bx54IFqGXyvp+4MPPuhMC33ggQem2iUlJSUxSmOIkpKSovrwhz8MYDhW4DhqdXUVf/iHf4hv+IZvwM/93M/NjI946lOfijzP8cd//Mf0up/85Cfja7/2a/GJT3wCH/nIR6i5hw5bn/vc5wAA3/M93zPzm2uuJ5lM9k/+5E9mfhsMBvjgBz848/ev+7qvA4BSx9LW5z73Oayvr8/AEODuLwBUKpW5f9X/0z/9UwDT1/djHvMY3HLLLfjsZz+LL3zhCzPLSFlwO4Urz/MjdR0kFc/Vh4PcBz7JNffd3/3dM7+FzqGvjz7JteoqAf+5z30O9913H26//fZSjl1SUlJSAqKkpCQAw3EDLgfoi1/8Iv7X//V/BQB8//d//2F3S62lpSX8wR/8AZ773OfiX/yLf4Ef//EfH/926tQp/IN/8A/wZ3/2Z/i5n/s5ZyD2+c9/3hn4ApOxQq985Svx4Q9/GE94whPwtKc9bTE7cgBJCWM7aHz3u9/tHHD+jGc8A495zGPwnve8Z2ben3/7b/+t0x35oR/6IayuruK1r32tswDAYDBwBq2+/p49exaf+MQnpv7+67/+696B+BsbG3jkkUdmxkbF9Gd/9mfOvr7uda/Dhz70IZw4cQLf+q3fOv4tyzL86I/+KADgp37qp6ZS2d7+9rfjj//4j/HYxz52alyS9O/LX/4y1bd5amNjA8BwLJmtg94HLvmuub/5m79xlquP9dEnKXrx8z//83jkkUfGf+/3+3jlK1+JwWCA/+l/+p/U60tKSkoylVLmkpKSAAC//du/jTe84Q245557cOutt2JpaQmf//zn8fu///vY2dnBC17wArzyla+cWe4XfuEX8JnPfAbAcI4XAHjTm940dh2e+cxnjueSEZnpXLLsT//0T2NpaQkA8MM//MPOgf4xtdttvOMd78D3fM/34F/9q3+FnZ0dvPGNb0SWZfjX//pf46//+q/xT//pP8Vv/uZv4pnPfCauu+463H///fj0pz+Nj370o3jrW9/qnHPmJS95CV75yleOv6zPs5jCPPW//C//C970pjfhe7/3e/HCF74QN9xwAz71qU/hD/7gD/CiF70Iv/3bvz3VXipzfeu3fiv+7t/9u/ie7/kePOYxj8EnPvEJ/OEf/iGe//zn413vetfUpKQbGxt429vehr/39/4evu7rvg7Pfe5z8bjHPQ5ZluHLX/4yPvShD+HMmTMzxRFcesUrXoF3v/vdeOYzn4kXvehFWFlZwZ/92Z/hT/7kT/DCF74Qb3vb22aWee5zn4uPfvSj+NZv/Vbcc889aDQaeOITn4jv+I7vCG7r7/ydv4PHP/7xeOITn4gbb7wRFy5cwAc+8AF86lOfQrvdxn/4D/9hJgXyf/vf/je84x3vwNve9jY87WlPw3Of+1zce++9+N3f/V202238u3/376aOjfTvt37rt/Ad3/EdePKTn4xarYZ77rkH99xzT/R4zEPPfvazkec5/vf//X/Hpz71qfGYOqlqd5D7wCWZh+oXf/EX8clPfhJPetKTcO+99+Id73gHvu3bvs0JPbE+uvT0pz8dP/VTP4V//s//OR7/+MfjhS98ITqdDt71rnfhU5/6FJ75zGfiJ3/yJ9nDlZSUlDTU0Vb9TkpKOi5673vfW7z4xS8u7rrrrmJlZaWoVqvFiRMniuc973nFm9/8Zuc8I0UxmUfH988P/MAPzCwTag+geNOb3qTqs28+k93d3eLv/b2/N95+v98f//2Xf/mXi6//+q8vlpeXi3q9Xtx8883Fc57znOL/+r/+r+LRRx/1buuHf/iHCwBFq9Wami9Iq9g8RC655mMR+fb9Ax/4QPHsZz+7WF1dLbrdbvGMZzyj+L3f+z3v9ouiKD784Q8Xz3ve84put1t0u93iuc99bvHBD36w+LEf+7ECwMz8TEUxnFPnx37sx4o777yzaDQaxdLSUnHXXXcV3//931/83u/9nu6gFEXxX/7Lfyme9rSnFd1ut1hZWSm+6Zu+qXjf+943njfIvhYuX75c/OiP/mhx4403FpVKxXuN2XrlK19Z3HPPPcXp06eLRqNRtFqt4q677ip+7Md+rPj85z/vXW5zc7P4J//knxR33nlnUa/XixMnThQvfOELZ+ZgEj300EPF3//7f784depUkef51DGXeYh8/Q1dCy7BM+fRb/7mbxZPfOITi2azOb6nTDH3Qei6Ed17773FS17ykuKGG24oms1m8djHPrZ4/etfX/R6vVJ9DF33b33rW4tnPOMZRbfbLRqNRvHYxz62+Pmf//mZeaSKIjxnVWwupKSkpGtLWVEYtTGTkpKSkpJGesYznoE//dM/xYULF9DpdI66O0lJSUlJSQtRGkOUlJSUdA1ra2vLObnob/zGb+CDH/wgvvmbvznBUFJSUlLSVa3kECUlJSVdw/rMZz6DJz3pSfimb/om3Hnnndjf38fHPvYx/Mmf/AlWV1fxwQ9+EH/7b//to+5mUlJSUlLSwpSAKCkpKeka1rlz5/CTP/mTeN/73ocHH3wQu7u7uP766/G85z0P/8f/8X8453xJSkpKSkq6mpSAKCkpKSkpKSkpKSnpmlUaQ5SUlJSUlJSUlJSUdM0qAVFSUlJSUlJSUlJS0jWrBERJSUlJSUlJSUlJSdesEhAlJSUlJSUlJSUlJV2zSkCUlJSUlJSUlJSUlHTNKgFRUlJSUlJSUlJSUtI1q+pRdyApKSkpaXHKsvSYn4eKYv+ou5CUlJSUtCCleYiSkpKSjrES0FwdSkCVlJSUdHyVgCgpKSnpkJTgJolRgqikpKSkw1ECoqSkpKQDKEFO0nFQgqekpKSk8kpAlJSUlORRgp2kq0kJmpKSkpLcSkCUlJR0zerKA57M+u/0+E6anxIwJSUlXatKQJSUlHRV6sqHHZ/SIzvp6JSgKSkp6WpUAqKkpKQrVlcO9Ghhx6X0iE66MpRgKSkp6UpVAqKkpKRjrSsDeg4CPC6lx3LS1aUES0lJScdZCYiSkpKOha4M8DF1UAjKrf/uH3B9SUlXnhIoJSUlHQclIEpKSjpUXXngY0sLQjbwuJQgKCnJpQRKSUlJh6kERElJSQvTlQ8/Ih8EaaDHVoKgpKQySpCUlJS0KCUgSkpKOrCuHvCxJSBUBnxMJQhKSlqUEiglJSUdVAmIkpKSKF298GOqcoBlE/wkJR21EiQlJSUxSkCUlJTk1bUBPyIWghL4JCVdSUqQlJSU5FMCoqSkJADXGvyYioFQAp+kpKtVCZKSkpKABERJSdesrl0AEtkglMAnKelaVwKkpKRrUwmIkpKuASX4EQkEJfhJSkrSKUFSUtLVrwRESUlXmRL8XO0yna0yYGeXEE+vgKQkVgmSkpKuLiUgSkq6wpUA6FqQb5wTA0ShCWXTayAp6SBKgJSUdGUrAVFS0hWmBEDXkjSV70JQFIIgU+k1kJQ0TyVASkq6spSAKCnpmCsB0LWmMnMgmVCkhSBT6TWQlLRIJUBKSjreSkCUlHTMlADoWtVBJ4MtA0Km0qsgKemwlAApKel4KQFRUtIRKwHQta0sqwMAioIvkJDnjfG/DwbbJXuQj/7/KCvvCcxdia+jgxW5yDC8/wukAPlaVgKkpKSjVYrEkpIOWQmAkoAJCE3+u6KGIhOEeOXxJkcm0+W6kuFIdx4z4xWcwOjalv1eSICUlHS4Sg5RUtIhKEFQksgGIVshKIqBUNgl0oDQUblEsXS/4/qaiqU5+o9nFvkemcAoSZTgKClp8UpRWlLSApQAKMlWDIRCunodIa2uVOeo/ETAyTFKEiX3KClp8UoOUVLSnJQgKMmlMiBUFP3SEDR0icpC0HF1iFw66ldX2SIY/ag75FICoySXEhwlJc1HV8Onw6SkI1OWVcf/JC1KZaunHbTq2sHWkWXNUjBUrSyXhqHhdXiQx/pBKt2VVYZyfc4wn3N82KoAGb+/GarI83bprZaBsKTjr/QOSkqaj5JDlJREKL10DkNl06Ps4Pggj7by68qypvFfA/Vy1cry1H/3B1vENifXZb+/qV7OrcNwiezjawOC/rgdnVNUDh6zzFqu0O9rlk8Ae8BcHxYMJbfp2lByj5KS9EpAlJQUUYKgRcv3lT/2aCq7XJl1xtc7DUKmwgGvDUIiDRD5rs2DQdEigch3fH2OSQwWriwYAhxAJIqAkQlDpmJgFHKGEhhdO0pwlJQUVgKipCSHEgQtUmUrii26Elm59ftByNRssOsDIVM+KIpdn8cLiDRpbZoUMhcwXFlA5IUhUw4w8sGQKR8YpWp2SbYSHCUlzSoBUVLSSAmCFiVmnIf5OCq7HKty29GBkGgS5GpASGQDEXONHj0UMceVGVNjAsNRvL4W4A65ZICRBohEJhgx44YSGF2bSnCUlDRUKqqQlJSUlJSUlJSUlHTNKjlESde0kiu0CJUtoXzYpZfLVigrSHdINKDcIVF/sFXqOj06h6jMcS3zbW6AK8khotwhUTGg3CHRYLBVuqpccoquXSW3KOlaVooGk645JQhalNhAWILgAbVsJgHpqHRxUeyR252kuxXFLrlcuXLY1Uq35HJNDErsX1llo/NQHjO4ayCz4KKgtpzjKOZNypCR/RypGPDltrMcRTFARi4n5bmLAXntZFVkqKIodrjlkq4Kme/GBEdJ15qSQ5R0TShB0KKlDYTLlVe2A2c7sNRAkcvV0QLRUYCQqb39i6XWo3WJMuv8lXcJdNfBzPm0pAeOwwWi2fLVun7ax1cPRtPtWDASqcHI8ZxMcJSU4CjpWlCKEpOuWiUIOiyFguBy5ZS9AXPJgNCX4pZljSgUlYGheYHQIjUTpE/9Vl1I6lQMhCbtxKk63t/rSvdTCiYEr+fZ34rRciwYZXk9DkWe52WWNRMUXeNKzlHStaDkECVdNUoAdBRyBdWxYM1RVlgTKEeCQJdLpB3r44Kiw3SFNCBUxiVyOUQhEDJVDohm162FoJjc0HG0DpEtVx9Vx9t5bYev97m6RcpnZwKjJFsJkJKuFiUgSrrilUDoKGQGeeVKJqsDZSLwM6GILXwgUHTcQEh00LQ5LQiJDpo2Ny8QsjWBjuMFQ6ZMMKKO+/ha11/zBwYj8vmZoCjJpQRGSVe6UiSZdEUqQdBRKkOZqmDDwJAMktnUoKyOg8wmcDWmx7EgdPDtLQaEJus/aOGHxetAqXTkNb/QNDrXcuOCJAmMkiZKaXVJV7pSVJl0xShB0FGqZKnhMsH46DxX8ubMxKQx5fkwWBvQgd4AWVYjlyl3TdYqHQBAQToc9eoy5RJlB5lmLqsCZFBTqsyzBPGFrrjGkapEX8fXFHUsD296QCnpXZQ4/mlsUZJPCY6SrkSlCDPp2CuB0FGJh6DSboRxjit50/j3thqK8rys4zKw/j0ekJrXZH+wM9VnnwSEDkOlYcjYL23AeyAQuhKV5TzAyXFdUHBYNm3OXD5BUdIiJM/KBEZJx11pDFHSsVSCoKPSIUGQ5/z6wCIERT4QirtEvgDQH1z6rssYELlgiHWIRCGXyAdC/f7l8Eo9+xUKducKQiWC8cOcQHSYiunqRKDfvmdYLDAs8ew7KBCZKgNGw+USGCXplOAo6TgqRZ1Jx0oJhI5CRwtB414EoMLnFIVcoTyvB6AoFPS5XaLQtelziUKuUIZKaSiaXVeJgLjkvXbNOUIhlUn5C7lFRwxDsr7kFiUtUsk1SjqOStFn0pErQdBR6HhAkEiTcmZDUbkUuTKBXvlxQotWAqFjonmD0RErQVHSYSiNNUo6Tkopc0lHpgRCh63jBUGADoRM9QdbNAgNXaIyaUA5fY1W8iYNQ2Vcor39ixQM9fuXS4FQUewcDghdqSlzLhUD/lgX+8fCHfKpDBwlMEoqowRGSUela+TzXdJxUZZVx/8kLVZ53sYQguQf7XItZKP/qZRVp//RLJJVS5WrrpQqcV22ghm3XK3SpWEoz8tAyoB2hsoctyyr0jCU5fVSrlC51MEyBTz4ZSgYAoCMB2lk1ZJwcziv8DLPa3YesCRTh1sq/zgpxQhJR6XkECUditLD7XA0hKChBoNdYrnW+N+LgeLLbqkAyV1JTv1F0AgYNcsMNPsR26QyGK4ZwFHJdXMZmTDUV5wr8yv9fp8rRz7chv54TKWyKJaT8s1AuS+8RdGbrEsJ79MQpXmNmUGm/rVHA5G1jOZ4ZFPXtg7Ep5+piy5bzt17ppJTVEblrtWrVck1SjoMpSg1aaFKILR4mRAk0sCQCUGiYPB7QAgS2WlyWVYNv/BKfDmfBwwBQFHsBQPiWgnnpawrZKpaaZeCopjY+9UEoXlJQIeb4FUCSG3wyLYnemJdL9Hre2b54fXOpanJPbIIMJq+//j9SRO58iowuUYTHKUiDEmHoRStJs1dCYIWLxcEiUIw5IIgkROG5gRBIt+YIW+Q5YGhUFA2LxiKyQdD/cGu0yWaBwgtSqVSohYAQ6bKgxETNC4OjKa2UiKgC4GR/3zlmB8UhcvPs8FpKrjAyoQi0bUNR6kIQ9IilVLmkuamBEKLVQiCRDYMhQDI1BQMzRmCRLECCjMvOIUzZC+zKBgyv/prXCEbiDQwZKbNaUDooGlz2vvVBmUNCPFpVb1oGxOMdGOO7FebdlzGZLmDpst5t2AcH83YIft60J27g4IRf/9plKCIVey6vbZDuARGSfNSimCTDqwEQouVBoSACQxpIUg0DnjZdKk5V5Ob+upMpskdtStkS1yi4+oKHUdHKCbeMSrr/rAuE6+DpNHpz91B3CLd/VfO+UpO0XyVXCMggVHSwZUcoqTSSiC0OGkhyFii1Hb4tBe+DDWrggzi+v3L9DbKqF5dp9rXqlzFuf3+NtV+uAznEg1KBQ1lSi7P3yE6CmVZjWxfBhrZ48ve6+VKzrNKxRYWqTJV545jaLf4jw0JjJLKKgFREq0EQosRD0FAvboKYDgvjVbVynA7PeUyZc93GRjKsyr6xZ5+gZGbYk7YGtJ09S/ddqqV5XHftKpWWlQZ5cFg+BIfKMGgGO+3Mqgc9WU4J5NeeV6n3DeZI0oLqeOvu6N+actvi0vElevmHRMWiAQk9PfM4cAKty1+/XJvcJUMcwyU9+1oidH/Xx0hizyLtM8heT8MBroPJ3neGbXX3otcf8bLjRKN9POCHc55TGCUxCoBUZJaCYQWIxaEBIJEGhgSCBLFYOig55qFIRs2VFBkpJZpgMj19T728hcYEsWgqFqZTleMQZGA0Pi/FUBUTO23pkT6pA9aIMqt9LgYFNmT5caAyL6+CqtfMdCx0+biYGSfB21p63JANFx2EeN8DjrvUGx75dZv3heaa9K+L+JgZDskV37YYj+PNCAyPa1CHIwEiibLxO5Lvk/2XGVxMDrcc5nAKEmrBERJQSUIWowOCkGiEAzZECQKwdA8zvdBYUjkhSLPGJsQFPlSmUIvfBuGgDAQ2TA03K4/wLRhCAgDkW9skTcA9Ww7BEU2CE2WcW/DBqFxnwJA5LrGbCACwpDjG0fkX8Z3HvyAcBAYml5P6J46bCCKbbO8O2TLd1367gk/FPnSxa780IV9LvneGz44soFo0j50f/IfjlwTOIfByHVOF38+ExwlhZSAKMmpBEKL0bxACHDDkA+CRC4Ymue5nhcMiWagKFJwwIYiXcWv6W24QMiU3WcXCE33YTYAdMHQ+DcHFIUKLTgDzyCI+YIt/7FyAZEPhgA3EIWuMxcQjX9zQE6osIIbikKBvvvYzguIhuty7ftRwFBo+/ODIZF9bcYdUxcUhcbPXPnhS+gZ5QKR8JQLs2Dkg6Jhe9d9yvUHcAPReBknGB3tOU1glORSAqKkKSUQmr/mCUEiE4ZiECQyYWgR53neMARYQKSovmYCkXaAu/mSj8EQMN3vGAwN+2GmrMVfxCYQaSrOTQWdinFLNhCFQGiyzGQbIRAa98kAIs21FgKicRsDdDSV5qbBSBPs26Wt5wdEk3Wax+Kogcjuw/yBCLBLvWuuTxOKNMUErvwQhv1wo5uCYQJHISiatDfvWf7ZGYKicfspODr6c5vAKMlUin6TACQQWoQWAULABIa0IARMYGhR53kRMAQAlaw+hCJlKepK3kZ/sEVV+8qyOopiTwVDwLBSW55VVTA0tZwChkzR5beJIg4aCJpdhjvH877W2EIKfOEF8/gtpvR5Uewfs2etFJpYDAwBw2dDf7CjLjKS5+0RFGkrqy2+ctlxEF+EYfh80hdh6I7a66t2sn06bgUYUsnuJFPJIbrGlWdN4uGUFFO1sooBUaWnVb9uakLOmGrVDnZ7F9Tty0zeyapW6VLlnGuVDrXPTOUqoFxpaQboGrUVClZYsGGODTD86r5/SPMwacXOC6VxiA6iokRAlWXa+Y4Eqvl5hfTtq9R1lGX5wuezYqouAqCei0COwWBT3TpD5Yp/j7El24ftmXPMXXNstbnhQtw1x1SJzLIGWaqdA+UMVQxSKfhrWgmIrlHl2SQAvNJfJIsR92WqWlkFoH/pt+rXAdAHvzKnjQaGzEBFW45bHAO2Clll9BLXQkitMtwP7X6LC7PbO6dqX6+uAAB2emdU7Ru11fG/7/fjL8NGbbh+bbB5GDAEQAVEVQP6tAAl51dbCl3a9/rlSroPlACfjfalIMuOF4XSXZpKl4ufw8mXct19UAaIhuvXVsebTOS6CI0dRu36x2XftQGntNdB0cQNJOdVox0LE5KZku/K/pSCIkALRuLyap7z5keifeX9PF4/eR+rz3PWAMDMYaV/j5spfwmMrk0lILoGlWAoJK4kqICQKAREAkGiWPBrT+wZgyH7i60GhmbLK+srkFWsl3cMigSGRLH9t1PSQlAkICTSAJEJQ0AciASGRLFgkwlGy4KQKAY4VcsB0wCRfX5DUGS3jQFRLG0sFlBl1v4Ewcg6Vhoomh0/FD6Xs+WKw/cCA0QzJcoj15W97kVA0UzKZWgbMyW2Y9ee3T4cLM+WYCecOrpkNICZ8WvzBSM23Xda4XNtp73GwMh2zjVgNLONwL1s38fRcz0CIlEcjLj3eYKia1sJiK4hmSAkSkAk0pcBtSFI5IMhG4REviDYBiHAD0O+tJUQDPlLK+urj9kB8HgdnkDQhiGR7xi4xuf4gMiGIVEIimwYEvmgyIYhwB9oHpYrZMoHODYIxdoD/nPrAyJXex8QseNnfMGUHUgBASjywEcIjPwFFXwV6Vylit33Qll3aHb9vr7Mrn+eUOQdf+bbhrPKou/685XkdgfK/vLr5aFItw5fOuXB4ai8S2TLfT5cYwF9z35fKnEIjHxjDZl72Xu+LSAS+cGIK9nuuhYSGF07SkB0DcgFQqIERPrynz4QAtww5AMhYDYIdkGQKRuIQvn7PhgKl1XWVx7zBczjdVmBoA+GADcMhIoV2FDkgyHADUQ+EBLZQOQCIVN2oLlIGIoF0jbk+GDI1VYUOrc2EIXauoCobDEBVyDlCqJEM2AUOG4+KApXmLOr0YXvBxuM5gVEw3XbfQmvex5gFCzIYa8/WP7ddQ2G2k8HybFKg/OAovB6Qts/GBjND4oA+3oNFUdxgVFsfKULjoLbsO7n0L3sAiMfFAEuMIoV5ph+x4eugwRGV78SEF3FCoGQ6NoEIq7cZwiERAJEIQgSmUFwDISAaRiKDWQ2YUhbScx8CcaWicEQMA1EIRgSmccjVrnNBKIQDIlMKIrBkEigKAZDwHSAeZgpci6ZkBOCIbstoDuvJhDF2ptANK+qamYgFQqiAAuKFMfOBqN4ye3JudaVTJ7cEwdJl3Ov2+yLZl/LQ5HqmWKuPzrvkHkdakpyTwJkXen1+UCRf52xPpQHo4Olzrk0OS+aipHyXtAWnDHBSLV+4n6eOu8BIBJNg5EeijTXQAKjq1fHqf5n0pykASHgWoQhbRnXoTQgBAxhSANCpjQgBAxhiK3mxJRUHgz2SpVgDm4/q2JQ7KtgyJSmjHWjtobd3jkVDE0vt0q259Z/1DAkioGQSxoYKtMWmG/p7bzSXljRhSyrqAsujHoz+n9tkYPqwkr7shXlFl6BLsuHUKS4bvO8SVUkzPMOBoNNFQyxKrCvCoi5QgyLLcIgKoo9BRRx16y8F/qDHRUUybQF6gIMo2kjNPe0zKOkL74wuv9V8DIpvKC5BiS+SmB09Sk5RFeRKpVVfdUlXDtAlGVNFIUuCK3XTqorrQHDAF2rWpUrN93b15edrVU72N7TVVYro1qlTc2j06itqKq2iZigv1btYK93SdW2Wmmi19cfRwCo5PEvkKI8q1L7yZz/St6YmqR1nsqynJ4XiVGeV9UVDlnVKl1q3Wz54Eqliz5Rrp6BvmqljX1j0tp5rjvP6lRpaxaKmA8n1bxJlYJnnrl5Vp2a+DfavtJGXxmkA3qnaLJAFQV1nzKlpptgSmuzqXbac5qTZd8Brsx6ntWp6RXYEvfauZgAnfM4aVyl5m1KOt5KQHQVqGI4GQmIJpp8JYoHofXaSQD6F3OzvjFad/wlIW6QutT0aEK97b1H1evWwlC9sgQA2OvrgKI2+oqXj1KI9vvxF4u4K1pQqNeGfdIAoOyvBoiqleH5Z4BIXC1NGXFx7rT7OS6RrTiGAmUaIBJnTbNesx9aIGLXn+fD46KqcjgK4MbHchAHkVqlq14/MEn50X65rozWr4WiWlW+jMfby2TKGiiqjCZ21gaWciw17TMpa00EliwQAbpqhpP7SHe8pb0GinJr8motGEl2gBq8xmXR5w9G2TjjQwMk+WiZ+WcV5GTpd+aeHrafOFLRtuJeaR3j8TMv/gxjgWi43gRFV4MSEF3BqlgpXQwMAVcnEGWuSnoBIBIQEsWASEBouN7wi8FOiwsBkUCQKAZD5ro1MCQgJAoBUc0KInJrPEUoMLZTzWKwIDAExIHIPp4hKBIYGq9bAUVmil8sULTTGEP7OVMiOwIWpkMVAyI7zTC0brsfGiAy1x/rt4CQKFjp0PqSPXM8A0GUAJFmOwA/n0rFWn8o6BIYmqw/HKBVjXsrBkUCRKIQ6NjHMwZFmTFeRwX/JWBIFIMi89zHjp99nYSAxYYhWyE4stOlVWBk9I0DIyAER7PvtBiQTM7tPMHIlbodewdOndsIGNnXcAiM7H7GwMh89sWgiE7HtOdSS3B0xSoB0RUoG4RE1zIQuUAI8MOQDUKAH4ZMCJpet/tl4Bof5C0vnc+Om/HBkGu9IRiyIUjkgyEbhIBZGAL8gbFv3I0PFkwYEvmgyLXvPiCyYQgIA5FvrJMvUHQFBr59dJbI9hw/X6qeD4pcY65863b1IwREzLqBWRgCAtUOHWk9zmPqCaBsIAptC3APCg+BkQ1EgD/gsoFouG5326onQPeBkQ1EgB90XMfU1zbzlbYOgNFBgAjwQ5H7XnIfP99YSh+sxIBosrz7WvCNIQ3CkRMaDu4aud9vPhhxn18q/dJzvn3nwPcuZO7rYfvZ7frAyNVH333qfv55npUHBKLJ+hMYXWlKQHQFyQdComsxXc4HQiIbiFwgJLKByAdCw/XOvgB8hRKcpaUdIAS4YShUgMEGIh8EiWwYckGQyAVDIjs4DhUhcMGCC4YANxCF9t+GIhcMjdftgKJQ4QdXgOgLCFz7GBoXZR+/0LglG4hCxSdc0OLrhw+ImPW7QEhkQ4or2Jn85l+PHUC5gMi3zdBgcB8UuYAIcAdbLiCarH+6vQ+Ihm2ngycXDIlcoOM7tq62PiAatndc8weEIZELivz30+yxDl0jNqRoYWh2PdPXRKywzgwcBUukHwyM/O86F4z4z/FBwChW4Mf1XvSeYwcYhZ4RNhiFrkv7Xg09i11gVCZtzr/+BEZXirgJEZKOTDEYutaUZU0Khuq1k2oYatY31DBUq3bG/2hUzVteGLIVW68JQ/XKEgVDtUq7NAwBuopwk7bT58kHQ8As/GiPq2s7McWq4Jkv8jyrBoMBe9tMkQimiANz3LMs5yrUVVrU+kMwNNOWHOxtqhqAA1v1AKDMrLeyPK6MpVGl0kaFCLRDADTb1g95tmbTDUOgWZ/6PQRDw/aLKzxrw1L4frLTdolrrSQMAUClsoyKcU3s989H2nenATrgsmVZTVHOfbxmxEt6i3LjH5E/la0o9tVFCQaDval3Yyy9knnmVPM2dW9X8qa6BLh9r4ZS+/K8hVz5Ti6jPNff20lHq+QQHXMxIHQtOEQxCDJVFLtBCDI1GOwFIWh6vQN1oN4f7KoBSNwhzboFhmIQJBIYCkGQqRgQARO3QFOiWhyUEAyZ6u1vqo/xXu+SGobEJdKWBB8U++pgbL+/ow4G5NhpYEgcIg2syHoZEBoM9tUgtN/fVoPQ3v5FNQipj/FgK+gQ2dtn5lDxOUMuyRfokEM0WfewrQaQxCkKOUSmBsWe+hgPir0oEE3a7tPl+LUl3/cHO8Q9NTx2mvbi1hwEiGbXOXSMtFMwjB0j1fxR/Dgj/ftvAO33btYxYuBUQESzjDhGmutZ3CLtNdrvb6mfiYPB9lwdoul1J7foOCsB0TFVtbpOl7m8moGIASFAF6iI6lVdkA6QX+gJA3afKAvarK5ic/dhdXsAKIhSrxoYElWIoCnP9etlNBgspjQ1qz5ROpi5t6uVJlUNjJ3niDnfTBlwphw5E2QxsEedE6K8McD1uVXfoMriL2qeIGouJOI4A9wcWMz1zJTkZs+hVsyzXPpB9Zu4r/QuEye2fDy1buL4MdcGc76Z+a4K4twxQDRc+X6aw+iYKgHRMRQDQ1mWqycrHC4gpTM1N6R8JdEE0/q2zKRp1er6cK2KfTQnR9UARrtxathWUU5YoEnzsG6MS1vHK5u1qqsAgEt7D0TbNkdtNTBUqw5fWHv7uvLasn/iWOz2LkSXmZTXVpTiHgFqT3FeaiNHTdN2UrJX0dYAMg1ESeCtuRdl3ZrS4eNy4PuaMs0yCWD8uhM41Zxz0yHTQINcHzu9s+p1q6ofjq+7Yd81112rcWLYl714X2T9mr60DId4a++RaPtu84ZhW8X9KOvW9EOOn+Y8yvWhgU85xkx5cEBXOlucZ829Ih+VNPsnfe7tx7+s16r6cuzN2vB8COBrS7hLipemNLQE6yowGt3fBeLhmKR3aeCWeYZNlokH+FPpxHMu2S0OtOaankytoCnXPzx3u4pnmKSw9hRtASQoukqUxhAdI1Wr62MAiIkdH4CsSsCQmb8cAxx9W3PcT6wP5rGIwVCrft0YhvYH21EYajdOqWGoXl1Sw1CjsqSGoVZ1VQ1DzeqqGoZq1TYFQ+b+MWNZNGly47aEW1cjcrmpcQWkO8XcW8y6mXFOTFvGqdOmC4oYB5VZt2u9zHXVrOuelcA07GjUrutSbYHJh5V594Nzrpnrivu6zzg/zH1DXVdVfTojM45M3NF6dVm1nKR1acaziCuS5/U4NIyeZdnofyFJEYAsq0bhRQCEiRc0Y4wGxf74fWiPM/K11/ZDir1UK83odS3QFBsTC0ygqVFbR6MWfnZI6mqtto5apG1Z5VkTOZn5krRYJSA6JtKCEMC9dIYLaANHZiCnvq2mAIKIgUIThDQyQSgmExRiMkEoJhOEYjJBCAjDkAlCQByG7P2zYSgUmNq/hdIIbRgKAY/9W6itDUOhPriAJQQx9v0Vut8SDPHrjt1bjdqKGowSFE0UumbsayQERa7fQlBkB6Kh+8W+T0P7Z/c5BEX2byG4EXdIZKaMasDIrI4WAyMzVUwFRuPl4mA0bqsAo0nb+YKRKQ0YlemHBoxEGjASacBovN4FQRGABEXHSAmIjliH5QrFxdTe17c9KAi53CEfCPmcIR8IudwhX7Dmcod8IORyh3wg5HKHbBAKyQahmCjQcwSlyRkKr9tXCML1QvedN1db1z5X8roahmqVDu3eaK8TZt1MgM9AkRaMWvUNCkja9ZNqMPI9Z1zb8/XBdRx9x8x1nSSnyFzv7PPHhqHQsozTxFRA84KR4x73gZGzVLQHjFxpavMCI9d70QdGrrYsGGmlhSIAFBQlt+jqVgKiI9TxAaF5uELT6XIhV8hOl2PcsePuCNkwFHKEbBgKgZDtDoVAyHSHZL9C+8ekyvlkf/kNwRDjBNm/hUv1Wm2vsDQ55ktoCITs83wcXCF2vaLjmkIn44ecbZXPHAbOjmv6XCjwtO+nkItr71/o+rahiIEkn3yFRQSMbEDyTS7qAiNfQQEnGHmeby4w8k4seowcI63sPvjnSJt9RvrGGi3SLVokGCUdnVJRhSOQBgDM3N+YpooqRHOK5eGhgSCBHH1bjSMkfdAcB3GIYiAk7pA2GBF3SBNoyJctTVqcAJEmLU6AKOYGCQxpnCCBIW0ApYEhGeiuK689KsUd+boqBRM0zpC0VZVuHW1fCyxSXEFzn41LyEbWLYUVNIGpFFbQtJXrUOMKyXWgBRYprBC7bqSogma949LwimtRs09yHUpRhZCk4EJs29JHLZhIsYUQEI3bju5bzbqlH5rjKudWO75Cc2yZ0uDApNCCJuCU+0ZToVP2LdZnKbKggSEpmKBxh7RVFGWdmnl0pABDrCLaGCAU0CHFFzTz5xTG+J14W65Kn4BX7Nks4Kd5hk+es5rn/SiW0DxrpVS+4pqVwgux+cHGRRdKFFWIKRVdOHwlIDpkMW6IVlx5zx3oHaG+ui1TClQ7uWG/v6V2hPYH21QeP5N2pU3n2utvqscHXdp7QJ0Wt2fPhj4naZ2h3d4F9Zf6/f62OlWuN9hWH9u+MlAZzpNDlJEe9IgvpAP1uotCV+a8t7+l/qI/KPbVKXJ7+5co90Z7Lez0zqrXu713hgBz3X7t9i6ogAgYQlEZVyqmrb1HVEAEDKFIC1vbe2eI+bG098OO+tju97cox2h/sKP+Aq+9vvb2L6n729u/rHaH9vYvqtPlmNLyPifDJZ+rNLvOPVXADAzBSD+pqB522Kp02vcpM48RPVZaoV5/S33N7vbOqidM7imrFI6lnRg3QdGhKqXMHZKYsULMrO4MDA2/0ugAp1LpqNvWlS+aVv06NQx1GvqCCd3G9WoY6lavUz+Q25UNdcDeytfUMNQbbKtgqJEvq2GoUdHnuwNxV8rUSvNmddului5QBIBOVTc2gxlfxOwXwKULamGoSty/bSJ1Sz1eKG9RMMQcs2XltdCoLqthpFM/ha7yXm/UVtBUTpK52rpD1Q4Alus3qdu26yexXNVd58xHmtXW7eq2jdqqqh2TPtdu6NORAa7ohHb+NiaVUTuRNgB0GqfVbZm55vK8qh8Dk7dV7/Y8r6snlx2m0WnhJYd+stZcnXZXFPvq+YAGgz313GBFMVBPkKo9Z7VKG01lulujto6V1q269VaXqbkPtcqzJnLlJM1JBxfp8yWV0SJAaPKw0j1ctNVtKsyYgBEIab6OaOGmQ7yUu43rAQB7g/jcL8AQhjRqV/Qv2la+NuxDEQeXVjZs20O41Hcj1z9YBYR2+7ovVBL8VrIaKpUadrTLVZajbVuVNdW6AKCe6768CQxptl/NuLFQ2skCzfEFsRc/A0Na0DMdtxggLwoe68RzgSmm0alPgKFbvw6X9x5SLdesrGKnfz7arl0bBu1bvfi8QgJFF/fuU/VhuXoDLu7fH2xjQv/l3oPRdXbqp7C5p5t0uVFbxW7vfLCNGShq5siqV5fUc5cBwxS/XmSKAYG3aqWlnvNN24dK3ohORMx8HLCLomj6awKRap6d0TNiUITf3dloLFJswvVisIds/H7XPNOkTbyvWVZVjRsaDPbGMYbmuSpQpPnIk6ESnVh8v789vtY150ygSDOv2krrVlzY/lK0HTAp0KCZ64hRnrcxUDqMSeWVHKIFqqwrFHpQMgMmAa7UpwlD/cBLrl7boFyhMjAUmrSy27h+DEMadavXjWFoq++fGLFd2ZiCoV7h70MrXxvDUEytbG0MQxf7/gCqkS9PwdClXqBtZZlyhcyCDRUjwG9G1hH7XWTCUAx2zN+1YBSTCUP1PB4AlYGheB8m91kMTMrAUEzmOmMAc9Qw1KmfmoIhUbd+ndot0jpFwASMNIq5Rav1yVdjrVMEAN2a7pnlOi6mzKBd6xTZy4WkcfbMNmzRDp/M4DjWB9PZ1bq8seDbPD6yzmqlRTlGsSIFUxOaZvXgR1BZT5Y3x3AU1wDzc4xkHDMXcxQYBD8cmYCldYsyVCi3KHTOTAjSukUrrVvVbhGgKNLAjjnCEIqSW7RYJSBakBgQ0jpDzEMJ4FwhrTN0EBDa67u/+nUa16mcIRcIhdwhE4Ri0rpCLhDyuUMmCIVkgxDghyEXCLncIQEgu3JdhQjwbRjSwhHgBx0GgGxo8G2fcYYy5DMw5IOesjAUk71fPuBYRNlypqQ7oIehRnWZgqGYGCjSghELRdo0unlAkX1Pa47ReNk5QJENIOzYKx8U2X1j4GIeVTHtfjFzdpnbkSDbF2y75i7zgZGdsq2NAUJgVMyABQtGccXAyE7fj4GRqB9Io7PHc7FgpFGztk6BESNt5TpGCYoWpwREc9aixgrNwxVyuT4MCLlgyJUuxzhCLhByuUNaR0ggiAEhFwzZ7lBZR8iU7Q65QMgnnyNkwxAb8AJu0PDBh+vv2lQ5BpK0Ab4PhlwukdYVAvww5FrHotPk5rVO9rpgYEgrJtDXQhGgd4sYKAL0Y4uOwiky5YIiX0DIOEUuKPGBitYpcvXLByoHqZbp649rW9pjInKBkQuAmLLWLjByrnMhjhEzvqhKuUYuKHKl4YXAaKYPDihypcoxDp8Lii7vzs4TWMYtmreSW7QYJSCao5gKcowrxMKQRoflCrmkdYQAfXqcBoLMdDkfCNmKgZDpDh3EETJlukPa1DgNCIXcIcb9MRWCobLpcKEA3+wn6wyFZALQvJwhcz9qeWsuMFQ3qh4x64xdG3a63TxgqF2fVIPzpcjFZKfQhYCGgSJzPTHoYaDIBKNQ0RAGiszjFgrcyzpFMegoOy9VqD+MU2Qq5A6VnU8tdExj69QG3DYYhQr7lHWMZl0iU2XBKLyMNj7RukWAHoyuJLeImeeIUYKi+SoB0Zx0lCly4gjNq3CCOEnasUIaEJJ0uXmCkKTLad0gQAdC4g4d1BEyJe5QzBESGNKA0G7/otoROkiqnO/3eRZRkN+ZogDxbQ6v83k4Qy5pnSFmn7Ruy5VUPKEMCNk67uOKptoq3SItFAH6Y7iIMUXABIrmWcZcgtRYGhuzTQGYmFtVNnXOJwGjmBtkglF07p7R8yW6Ttox0kjvGAGTWCVW9ZYFIyBeBl0LRia8xoopLHJs0byVoGh+SvMQHVCLcIXUD4z+lhqCGNkzbYdUVQZmmklFgWG6nDY9bl4D8m1pnYcKdMHzxf796tS4vYGuzDY7RwMDRKrtq+ey0itWScjUfqSylKjnmc3dpUHRUwNRpcSg2JiyTHdMtXMc7fU3KRjSXlMDYrZ6LYxWlV/3B+TEkaptE07jxb37pooqhNSHbj6bHlE9SltRM1Z5bbzt/c2FzNXEzAWmvZ616VSAfp45bT+1x1Okqeg3XK9unwbFHjE30HzHDrHSPkcy6Et7a9MxKxV9PKSNXbTPJgC4sP0l9bW3q6wmCeJdnyrRHUzJITqAGso5V7TzD1TyuvrLVZ5V9Y4QATg15URkjdqK+oGinWtlqXaDCobWK7divaL/KrMB3dfdNdygDo5WCuUcOmioYUgLLVpnRtL9tE5XPdOde01aoKitbNtQbhsAapkOrmvEl7NGZRmtqu46bSvbVfO2aiZ7YDoVLiTtuQQ4V4M6VsrrWVuoZKVyIzqZbrLVpnLbdeU1AnDX3g2NJ6rbdjLd/ncrOvennnf1YyNruuO51LyRGgPW0s7hUtFDlhbaGXDTgo42eK1VOuN/NNKmaKnBLaur3+P6FPuBfg4lYsJebRYM4xZp+9nv7+njEuVzfH+wi05F975fad2qnnusUl1GRXPvFQNUtHEZMQ9g0qwSEJVUo34D+pH5ASQgin1RNUFoP7LOfDQrdGzbw/U21Q/RWqWLWqUb7WujtoJGbUW1znZ9A+36RvQr/VLtBizVdDeygNDlwl8+W7SBmygY0milOEnBkEaVrLYQGGLEwlAziz/IWRhqZuHrqpa1FwZDWjEwpBULQ+1KPNhtEumMcqyqWfxZoT3+AkNMWmVMco3OE4o6+bCfDBS1s9VoG7k/5g1FADGfmhKKAK4wBgNFMTCS3+cJRQIj84Yi0SKgSNsHBoq0YMRAkQaMJDZhMmJiYLS3f4kqUFHNW1Ewurh3H9rVDfUzvVM5qQKjSlZDu3EqCkbV0bnUgFF//yIqlW4UjHr75xMUHUAJiEg16jdEYYj5Mmw6QiEYYh6aw/VOHpyhvgoIacSCkEYMCC3KFWJgSKMaGhQMadSqrC0EhupZd+7OUDtbm7szpA3EgWkYir3sysJQo+K/F8rCUGhcEHNOm8ScUIzMc8BMHhzSSuXG8b9rXaKYTBBinKKYugbcaKBIFIIi8/qfFxSZEDJPKDJBSAtFdn9CYqBI6xYxUMS8XxkomrdbxHzoZKDoKN0iQD9UgAUjjWJgdKE3maxZ6xYBiIJR1TiPKrcIiIKRQFECI14JiAjFLjAXCPkcF216nOtBHQIc7cOSBSEbhvr92dxnFoRsGPKNn9GCkDhCNgydgXvm+avRFWJhSCsGhrQ6CAz5jslBnSEfIB3EGfIBktYZcvbH4xKxzpB9vHwukesc+KDITpXznSsThkQ+KLKvVZ9L5AIgHxSJOyRqZN25OEUa99QnHxS5wPagTpELQObhFLn+Pm8oAvQpdMx4JhaKrhW3aL8/PTZF3CItHPmgyC6/zabRufq727sw3VeFWyTSOkYxt8h+t2scIyDsFvWtKU40jlGCIk4JiJQyLywbSFhHyAVCtjvEPhjZ9DiXbHhj0+NcstPl2PQ4Boa0mocrdDk7P/Xfi3CFgOORIndQGHL9fdHOUEzzSJOzXaJ5pMm5XCLtufXBkHueJ39fbShizoFv3NBBUud816o2dW64jul9sGHIlOva7HpcHq1T5HKJfPfAQZwiH3gcdfoccDAo8lV6Y6DoSkmhY/rgeu/7ii8swi0C9I4R6xbZYLS3757Y/SBpdBf33B9L551GN16vA4yqjrhNPb4IbjDq7Z8f/3uCIr0SECnku6BiIGQCBlswQSMNBJnwpnWFyowT0mheIGSOH2LGCQFH6woBxz9FzvxtUcUTDhuGplPddPM6uZY9iMznBOMMhc6t6RKVGTM0D5kukbaIAuB2h0RM6pwJRfNMjyvrFIXcIe14ImAaiuaV9ngQKAqBz6KgaNHFFkKAciWl0AFHO7YImB1fFMpiOQ5pdBrHyHaLzLQ5WwJGWjgqW3jBdomm2gYcowRFOiUgCsiVh9kf7MzFEXJJ8xDuD3YoNwiY/zihfn/vwOlxPrHpcVodh7FCV2OKHDDfSnJSWGERzpAWhKQdA0PzrCYnLhHr+gW3O57nSddPcYmY8xCTXNchGBIJFDHXbEwCTCF3yJRcrz53qIwEijT3gtYpouZhG0GRBjYa1WW1W1QGijRwdJQV6IArL4XuKMcWAfrCC8B8iy6IpL922pxL806jEwkYxd732jQ6oJxjZLpEgDueTZpWmofII9+Fo51Xg3mIMPN6MGo3TmFnLzwBmYiZpE/7la9TPYV+ZFI1ERN0NApu8s6B8mHaLNrYy+LV+wBgN9PPb7MN/1cdUw10sQvlPEQL/JahnV+phgb60F272jlZmLYNdLGpqDYIQH0dipi0Ru26cyawgP6Dx0A5f1M9a2O30F1fAHeNMcerDuWcZNDdiwD3DK1l+udHt1hV3+va5wwA7EM/r81eoZtbpKdsB/DvHG1Q3sxXsDOIB6OstPOJVbOGeq4mNjWOkS+9y9UHTfAOcOdsUOjmN6pVuuj1dc8E5iMs4E/dc7ZV3juVrK6GSQaStcCzkl2PLeiv74v79+vbbt+rbquV7xrf3dP361pScogccsFQrdJRBQj12hLqNd2NWMkbqlmwAS6NDdDDUKt+Aq26LpWiVV1HSzkRLQNDWudmabCGpQHhiBRN1AvdQ5yBoRrmPxluA4R7A33KVw1N1JTBdR1tdbBKpQlCH3g0lceBOV6NrIs24bYwbbUD6Jv5strt6GQn1ClbTLUzRo2sq05Ba2Ur6uumA+I8QPe8q6FJHS/m2mWk/VBTRU19nVdQQytSjl7UyfUpcUx6YyNfppzCZq7rr7YdwI1Bq+dKlyZrqOeda1aW0SRSbSnHTPler1aaqFaUz3Klm9DrX1ZnjzDZLgDXXy2c9os97Pf1HyO1qqCm+hB4oXhQ/VwChi6v1untNK5Dp6Fze+uVJdQVH6YHxb7TtUxOkVsJiCzZFwpjg5cBoV4//DXLBCHNlyTGhl0UCHWquu0zaWwMCAGgQKhZaCGgfmxgKBZQMSAE6L/aD9fNw1Ad4WCxie54n2JBMwtDjASGdOl9o7lmIilYzOB/ZvyMwJDGXRW4YY9HDIq0wTowOa+a60faMMFHbN9YeOwWw/Ya0KkVDXVbkRaKgPhxnqQDKuaoGoEIA0UAlz4Zgx35vZmvRNtK+uYioGi4fv3zTANG4pYuAooAUFCkBSMmrZ6BIkDfXyY9cL+/vTAw0qiNFdWzSfZHA0YSE7JgpJErjk1QNKsERElJSUlJSUlJSUlJ16wSEBkyidkm6tDXCDtNrrfvd30WkSInrhDjDDHukKlBIA1uUc6Q1h2SFDnGHdJqUc6Q1u1oYVmdKudyhkJu0SLcoQqq6lQ55ku5fby0k15qtKhUOVOhtDnbHQr133Y7Qi4RW32NPW7j7QSuI9v1C11H9m+hL7GMC6rdvksh50fcIU3bqvUFOnTt21+rjzp1Dgi7RLbTw6TEadsy1Tfn5RK5HCFt+lyrtq52iph3vtZ1AfTpc4B/Sg5bkj6ndYvY9DnGKfJJO47LljZ9DtA7RSI2hc6nvf5k32Lpc7v7k8wiO65NLtG0EhCNJBcGmyK3qPFCGoUgyDV+yAdC+44Bq4tMk9OKHS+k1ZWaJqcRGyC6gljXy4CqqLeAMUPAwVPlQsDj+s0HBi4YcqXNLTpVTiMXDIWAx/WbD6hcAfpB4ZoBFde17ts31zELbUvS5abWTaTDHWbqnOv8+KDIBR4+KGrky87Jdxcxnohty0CRC4xcf2NS5wA9FAHHY0zRItLnAC6FjgG5w0yfu7T/4MzffGB0oZhtK2CkhaOjHFcETMe5CYomuuaBSEoRHgUI2eOHQl+I7PFDWjdIpHWEgFlXyKdFjhdiXSGtjtoVAhYDQ2XGDM2jgIINPyEYsscRHSYMhXQYzpAp2yUKwZC9LyEYsl2ikDPkOkbMcSszduggmudYIlOua9sFQ+N1W6Bju0OhtrY7ZMq+F0JfqI+7U2TrIFBkTxJsyoaiENAsotACwBVbOOoxRcBi3CKAK7iwSLfoKMcViexnla//LrfIFysuGoxSSe6hrmkg0oKQ3GQaEJJ0uUVVkGNS44DFVpHT6ji4QoAehhbpCh1WilxIiy6goFEMhswgOnbMzLS56MD6fG0KgGIwZK4vBkPa+W2mljlEZyik2HEz1xcd4G9cXzEYMq+v2LVmBhqxa97cn9hxm2f63EHaMh8IRLHzbEJRDExMKHI5Q7ZMKNIWUWDbxnQcCi0AxyOFblFuEaOjdouAcBpdWTFpdACXSle2Ep2ZNueSCUZm2pxLJhhdy7pm5yESGNIoz/U342CgnyuAWa8WrkTMHCI15QRlAPcCWlZOcApwzs0iVWS6+RAuZ/q5CLZxUQ1Cu7isBqEdXKZgqIcdNQz10VMHin3sq2FoD9vqwG8T59THbbM4QzkDW4Nzamdot7isdoY2B2fUqXLMuWNgcw/zDwgm/dAHBYsqb90j5vBhjtui5jcDgH6mfy9o92+7uKAG383Bo2rQ2OqfUQGRqFdsqde9M7hAtQ05RKa2++fUELM32FTD0X6xS6XG7fQvqufk2u6dVQf6u70L6nhhv7+jhg1mriBmbkVW/YFu3iSAi22Yj8dL1evVbdnJmi8r58sDgAu9L6vb9vb1c49pz1+vv3nNzlN0TTpEK53HqWGImbCUgRZmvcv1m9RtAW7m8pZyJnCAS6tgYGi50H8RzMlLlmlfJ4K9LtFn5lhsFPpzvVRwD2UmdalBuEixktqmlgp92ghzLNbB3SPr+c0LWfdGfqu6bbPQPwOY6y3peImByEqhB7iVTB/AncjvULddrnBfiZfz0wtpu5LfqF9vVd9npi2bSkgF1XX9sWg19E5yp6nvAwMMTSLlD4B6AlUAqBIfZbWTuALhIlAHETsxOgNQnZo+XlhEamWt0sFK53Hq9V5NuuYcopXO41RfIwRY+oP417rxnEKB6nJl1isgtLn/SLQtMAEhTXsBoX1FP8yXQuxhVBaE9hB+cJlgo/kyy7Q3QWg30399jrlE5viC2Gz35riFreyier07Wfias2El9vXZHOcwQD/Y1gz0+pHzZ35972Xh+88EhcvZefV6NyNtgem0pB3EZ2jvjM5L7JyY697EuWhbgdnY+QOAlVFbjSspx+NSFp+UuWNcc5pjJ/e2pq2sey9y3QOT8605FtKW2b+dLH6ezVRdzQTN4mhvKdYt94nmWAgQaY6F3NvbiF+b4jpfRvxLdXXk7O0W8X0DplMo9xD+Ym061LG2pju8GfnCXssmz4Gtfrit6VDtDML3VD2fdp0HkeecmUYY60fFcLS2euF3dp4b76je+WDbRm1V3dZMp9/afVjddqcXv/9MIIqlsWWoTNo6ijz5lwuDSbM+ua9zhXPHAO1SNnweMoAG6NyifQyfQZuR6wKY7JdmnspadXh97vfjz7hKXseFzb+ItruadE05RBrqrVU7aveGGSfErHe5fpPaFepWrxv/o1Gruqp2hdqVjUOBoZgYlycf/U8rxhViFBpsbSs0iPsg62WcGyA86NsW89WbGkdBuCbs+Ax2jEaHOC/mumNOnOnsxfZ3xWgbc4nM4xFz4ux9i+2reW/H2pq/1yPnyNz/2LEwf2f2r1mEz7s9bjE2NtFM721H1m3eJ7FjYbpDsWNh3ttMFcou9F+qG1l3/I9WzPhEpm2ovL4txtVhxisBQM6MIyH60aZcgdWFtGXdIsYxOiq3aGdv8nFqUPQW4hhlyMf/aNTNNtSOUad2Uu0YLWLM2bXmFF0zQBQ7sYsCIVm3Vkx6HJMaByw2PU4LQ8vFihqGGLgpA0IJhiY6KAz5AMkFLbXCPfDWFQT6jo9rvb5A3QdCIUCy19Uu/EEnA1pMmuMK0ZaBQwb0APeHDt86XH/3gYDrfPtAwPV3HxS5+hCDIltMwZYYFE2vdzEfB0JQZP8WgqKqZ9yXD4qY0uuuv/vausYO+qDIdIdECYqm22rbs0WbGDCqVlpqMKrmLTUYFRgcizQ6gEulW2Qa3TzB6FqComsCiMwT6kqXW+Q4oUW6QlodxBUKiQGhYfvFuUKMFglCWmjpFqtqGGLWC4RhyDXQ3QdDuZHGILoSnSFGnWK1tDM0tR6HS+SDIde++2DI5RL5jocLGEL75vqNub+p4xY438y1wIxJc0FRqKqlC4p8xV9cUOS7V1xQ5Bs75DoWvvubdYoYtwjgypkfV6fIBz+uv9vpcqZYKNK+U9u1k2owYkBH2mvFTutxXNwiLRgtyi0CcCzcIuDg44vMWPlagaKrHohCJzIGLOY4n+OUHsfouBRNOA6uEHBlpMiZbkRsvWbAVEfrqkyTM49XbL1TqVIKGJpKdSPOi3b9oqNyhkxg0ACL2SZ2jzMAxDgjthhAivXJhCJNiX8TimKVMI+jUxSDJBOKfO6QKROKmPLrMei5UtPnTDCKzc1k9qUSqYh3paXQAcfDLQKOR9EF4HiAke0WharSxdyiawGKrmog8p3ARaTH9fY3qfUCi0+PS67QREedIieB63FKkdPCkHYOBmmjgSFJmztOzpBGAkWa9YtLpIEhOQ4aGBKXaJFpcux6NesXCNCcc2mjaSvQt6h9LJM+p7lf5HhoKsvJcdDc5wJBWsfouDlFmlL7AkWudDlbzPutma8cuxQ6s6CCT8clhQ5IbpGtRabRdWonVX2fVxrd1Q5FV22VOdeJq+QNuiLIItSp6oGina1hu9DPeVPP2tih2i/mKzcDQhVUsAv9PASsqo7UL5+YKnNZkWMn080D0C666GX6hy4z18pAOXeSqFG0VFWsgGEgFquQZ6pKlA1mHCfmeNTQUO8fMNzHRR3vvNC/DFeKNewoj3WjaOByFp6YzxQzZw7Az86u1XKxhMvKc9MtOuq2ALePtYLbP/ZjzbbyPNaKmvoZAvD3ulaNooULma6aKTD8ILCo+a6YADJWqc5UGyvq+WAaWZd67wJQzz8EALsDXQU/AMizHFv78apuwHDy2b2B/p5hJjxl5iwCuGpx1bylqpIGAJVKXd0WAFp1wp2v6adjkCpzWjHvXQA4X3xF3XZ7/7y6LQN/WVbBYDDb/mqtPndVOkQ+GNKqnnfUE7flWVX9UOlUT9IwxIiZnb6ZraAZSXkYtyUrdLEwpNVg9D+tqqhQMAQMA02NMiLQZVJpKkUFlULf5xw5BSGLGtfTKtpoEZPr1oumej9rRU19DNnJQJl9HLZvoz3Q9aU7WFb3e6Ug5oginEMAWCpWqPVvFBtYDRSRMLVaLKvbLhdL6j6Iusrzs1osYV353FkultAiJsXtoIUWeV21qPtMd9/U0FDfv+z9CAArhPMP6F3pyuhJrFENDSqNt4M1an415gt8LCXQVCPrqlIORUv5KSzleuelXdW7LtrYpVlZDY6TssXGL63qOlpEv5kxL0zbohioYS7L8oVOQEu9U7M1tJQxIJMRxBYFczmUV6tTdNUBkX2izJMfc4cWBUIA7wppYaietcf/aKUFIYBLPWLGClVG/9OK/cLNghCjRcKQKBYklRk/VRaGYsuZgVcN7gpyonrRpFKQmC/5JgwxaVn2sv72+nusO9APcDdhpRk51iYMdRWAsURO6LphuMAx0DF/10IRoIMcLQgNtz05DjEoMqGMgaJh+/g1Yt6TMSgyr23m2mLuYw0UmevTQJH5TmBSdbVQBOhSes17NgZFbUyui0VBETAchxUDIzON8KihaNi2GwUjM9WPiWUA0FCkhR2mLcA5XIuGIhaM1G3nDEZFMZyLMM9rM2B0NULRVQVE5gliKJgBIYCzmZmvKgwIAZwjBCRX6KDKivxAMBQK7llXSKtG0Rr/Y2peVb5YV8hWaL/t4xWCy8Nwhqb6EnCJbBgK9ZtxbpzbCkCRDUOxbW0QKbEuAApBke0OhYDH/i3UdtWx/1qnCIhDUccK+ENQxH6gsBWCIvv6DkGRfU8epVNkQ1AIipgKmC7Nyymyx0i1spXxP1qxbpFPuRWYs1DEgpFWyS06uBgwYtwigCumxcTKNhhdbVB01QCRnBjWDmRB6Dikx7GOEDAfV6jnGF/DuEIAD0Pavy8ShAC/K+QKYtpFt7QzFJMv6HKlzTFfkkXzgCGXS8S4QkB5Z8iUb54b3z7613NwZ8h1PfgAxecSMalyPmfIt00fDDHOj0++VDkX6Pjgh3GM2H74oMiGoUl7/XnwuUS+69t1rfmuy3k4Rb51+KDI925YlFMEuKHId0wWlT4nckGRr8jEvKDIVru67gQjXyyzKCgC/HFOzVMAYZFQ5GrfrLmvh+PiFgHHI40O4IaVmGB0NUHRVQFEJgxpFft6Yg9MPA7pccCV7QppYaiMKzRP2YHnUY0XsoMj1hliFPtaZa/voM6QT7WiFoShGdeNCDo0Lx57fSEYsl2ismlyLtlQFIIh2yU6SJqcSzYUhSDJ/q3MuCGfbChyuUMi2yWK9eOg6XOhe9OGohjsHyR9LnRf2r/FnhErxUnKLbKhKAQ+zLgi4GBOkZkuZ4spdyw6iFMUqrp3mOOKmpXVQNt4Cp2tRblFbFrcteAWAXwananQPpcdX3S1QNEVD0QrncctPD3uSnSFGBACFjdWCNC5Qo2Rq3Bc0uOAg6fIuSTBEOsKLQKGmNLGpjQwJC6RBobkWLCVv3Tjfsrt43CZ+H4KFGlgSK4PNk1O4wwJFGlg6CBpehrHSNpoYMiEHGZsUQiGREzqnC2fO2RKoEhzbzJFFoDJtae5xuV+19yXbPocMHGLNO8Itvy/QJFmPwWKNG0ZpwiYuEXakuIsFJVxi+x0OZeOSwodUC6NDtCV056HW+QT6xZd7UUXgHJpdFcDFF3RZbfXlu6mSnT6bFyX9gt9GV4AaFX0D2C2elwfi6uRX0WDCrY3BvovWEx6HABsY0fdlp1TqIIK+uir2+8Rx5wdO8BA316mPybA4solA0C7aKvLQgOcs8YeQ6aEeRktakzXMtrYJq4tZpoA5lkIANUFfw8bYDGvFrbf+2RBlhwZ1X6XOJ/72Fe3baFJlR1n+l3m3DDl99l3Vk68K5jrvD3oYjO/qG7PlN8HgAHxTgG4/dwsHqXWvT/Q9z0nSoQv5afoEuR7RFnxHlGeG+DKeTPXymr9Vgp26Pm7yI8iTBn87eIcte6dvv6eGBT6ZxYAnLv051T746Qr2iHSXuyNyjIaFX06C3NTVLMGqpFZp001M30/WBuVTXljvlo1i+7ULO8x1VClAwutGuQAehbMmGChjprapWqgPnbCNCqyQbRqm6g2mnqWUatooqVMZ2uTX5aZ8S7MMQSAGgF9jaJBl6lm9rWFpvqcLhOTVA7XXUNbea230UCLOC5reQtLeQNLyq+Aq5UmVgOzmNvqZPprcS1vYY34WLVc0Z/PTl7HSq7rdzdroJs10Cb6XkGuPkc1VOnUPO3YqXbRjlYoNLVMPMuB4X20PFhVt2feFRXUuA+b5P3cUaayNovOeJJfrZh3bhNdykHrZCfQyU6o2uaoUY4OE7MAfLW9boVJ/dtAu6qDi0ZlGZ2afpL6RnUZjao+5mLnWmKUI6NiojYxfpPNCGI+4LMVla9kXZFAtLZ0N9aW7la1ZUFIC0NlQEgLQ4cBQiwMaVUbFUxdhBqj/wF6GOaKOBRjGKoq9oFxqcygWRMUFcQEjCYIaR+4WhACysOQ5viwTp/AkKZPZUBI1quBbia4NWFIAy4M3JgBuWY5Bj4ATIGQBooEhpYUz0ezL5p+rY9mttdAUSef3BdaKBJpoKhiPIO0UATorhuzDVNQQgNFsr7lokuDkQaKBFiY9wage6bXR/u3KCgCoIYiE26Y9y+bVqiFIkCX5iZt2BhGC0WS2t+tnKLBSKtO7ToajLRixhaVEQNG7WJ5YWDUqqzRYKQRE58fN11xQMSAkBaG2LzQRYEQwOWQsiAELN4VWpTKuEIsDGlVH/kxWrGuUFkY0ohxhYBZ8AgFXKwbYx/DkEtUG/1PK7sfsX6x0GcHtaFzXMYZMhUKtplAHHBDR8glYlwhYNYZCkGRqy8hKBIYEjFOERCGoq6jn4xTBITPhf1snKdTxNyjLsWgyL53WKco9A6xU3xZpygERnbRExaKyrhFWtXRot0i9brJoggsFB0XtwjAFesWAVyKaxkw0ooBI8YtuhKh6IoCIs0BvpbS45jf5uUKbWZbM3+blyvkCxIYGAqBkO/vLAy55AvmWRhyyQc9ZWCI+TsDCT7g8B0vBih9IOTrn68vvr971+O57vzX6ez58MGQz8nx/Z1zINzrCMGGNnUO8EOSL01O4xTFZMOQyAdFpjsUkwuGRD4oqjCBu+fZ6LuOfH93QZHv2vVBkQ+sXFAU+sDhgyIfoDAf1nxQVPeWMCdSKD1Q5Hv3zguK5lGu3AdFue8ZOwco8lW9Y8HIB0W13H39zsMtanqKCMzDLWLHD/l0tafRXWlQdMUAkRaGtDpKV8geiHmcXKFhf46PK8TCECMzRc4lO22OdYVCMGQHPYwrBIRhyPWAZVwhIAxDTElol0LH0QbLmCtk93Pe44Xs64/9sh+SDS5MmhwQhiR7XWyaHBB2h+zfYmOGbCgK9cf+zQdDIhuKQjDEps4Bs1AUgiHWsbOvp3leX/Z9Gku9O2j6XAxM7PdKqAAMWyDE3nZo4mTGKQLcUBQCGfb9vKhxRcAsFIUgif3gC3BjixaZQgfwbhGjw3aLQsU9jotbBOjS6K4kKLoigCh2QBfhCklFuivFFXKpjCs0bxgqW1hBA0Ly0mTT4wC+ypIGhiSYZ1whQAdDAkBs8QRtipy0McfRaKQBEPPYMceRSZHT9sX86n3QNDnn+o1zw6TKaWDIDLY1gbesUwtDpkukSZWTNkwBBW1/WIATKNI4QyYUhdwhUwJFGmfIPDeaZyQDQSbUaK7fsulz2g8LTPrcsD/D9WuqYZpQ5HOHTLFOkYCR5h3MptCZHy4XUa5coMjnDk2tmyyfXQaKBIw0U4OUTaHTxHiLTqE7LmOLgPJuUaaIlebtFl0pUHRFlN32HczQ5GIuFWSJTObiX6pcT62buZj7GVf2EAD2ybKnTH/Y2esZ+GBBpQxw9YjSt+z6GTDLkVFldVmxbgn7VZYpCc2K7QtTUh3g3UT2Omgs0Dll1Mz5flQybl97A2LuMHIOD6YrffJVxrYHgF2iBG2PvCYZsc9JtlQ5U0ocALaJktwA0Mv0JaLZAgrsfGb9jDtPTPlxVo2ihUvZWXV7thw2I3asEMCXW98t9OW5+wW37j4xdUor56ZCWcr08y2Nt0F8gNslpiABgM3svH7dxDEHgO0+V9LbV6b7SijHfewdIhcMNSurFAw18i4axFeSDBUVRYsYmu4Wq+gWq+r2zaJNW/yM68Tar8vFkvpl3Bh5VIyYwJN9ycdS5GwNi0HrrwMmXYYOsMmCBUxlKgBYylrqr+UAsJwRhRnQoI4NW0KaucakL8wyLdSo9sxxbOc1tHOiohzRfr3WQLvCgd9qvYqlGnHNE+tfb9SwXGfaV7FW1x/3U039cVyuVbFW5wLnVqWC1aqyxHZWoYoyrORNKp2PKlOeNam+tLM61jLu+cFMgltFhQoO2YmpGcdtCW3VJL+mGFesPegG0/ecfSKcKGqCWDLbpTKa+pwR66KtZPoPyZ18A51cl0bXzJfRqeihpZa1UMv4tGKt2AmRG2iiQVzHLehjuE62gU6mT0dsVzbQrujbV7M6qo7nzZXgEh1rILIPIAtCACgQAnR2osjMt9xXTOjGglCTvInYFDwWhDQzz4sW+YW8inwMQ1qwYL+oMmOjzIBfs99lYEirbtEZw5B2H5bIF4HA0IoiPYJN82LHYMjxLrNuzblix/UIDNWy+HPEBBsN5DDgNLWcElpWDfjQQJGsd6UW79d6Y9JGA0XrjUlfNFC0MWqvgaLlmrlu3TFtkWAp0oCICUIaKJI2bFqhpi9mm7WsowKj1ihNlIEiQBckmpNZaqBI3lHsWCwtFMmzeHmwSoMRIxaKWDBipIWi9ugYsumFDBQBUEMRAHQqJ2kwOk7SQNFglHLfwjINRow0UGTeoy4wOu5QdGyByAVDjK50V4iRC4RC2yvjCjGyA002qAyJdYWAWRgKuT5sxTw2gLdhKOTkLNoVAmZhKORuLGfNGWcoBEXssbHbx64b+zqbZ3lq1/ZjAGUfuxAUsXBjt48tv16zBplHAvpVwolxrU8DRaZCUGTCkEYbVnvGKQLiUGTDUMwlss87W747BEX2bzEosu9Xti8AglDUssYzxqDILprCfjkPQZH9nmqhGQSjJWuMH+sUAfN1ixrWOCm2wt083aKuFSyzThHA9X8luz4IRvbYbAaKAMzVLSqTLncQXcluEYArCoqOLRCJFu0KlQEhFoZc8j3YGRhiHSGAc4UADobKpMi55HNQDiNFziUfQPmCbN8xYJwhtnS0D4ZCgMc4Q0yKHOA/NuzfXWKvs9C6fevxwZivPZsmt8i/2zAUkw+GfC6RD658UGS6Q6ZcUOSDIZ9LZMOQyAdFpjs0vX4OonxQ5INgH4j44Gce6XO+e9bXlxAsMSl068UK5Rb5oMgGBBGTPgdwbpEPisqUIPfBD+MWzQuKfPBzVCl0vkITi0qhA/xQtFy5wfn3K9EtEpVxi1gwYuRLoztuOpZAtLZ0d2kQCsFQM59+WDAgBCzeFWJhiNU8U+Rs0DisFDmXXKARAyEbctjy4ex4oRAM2TDDFkMoM14oBEN2cB+DIdslOqgzZIp1aex1afpyUEczBEMzbkHE2WGdIFshGLJBZrVejTpDNhTFnCYbinwwVEY2FPlgSGRDkQ+GJuuvzYBRKFVOO55IZANHDHrs30PtD5o+p3GObCiy3SFbNhSFJl4+qFMU+3BnQ5HtDplaLZYWOq4ImIUiH/wBfAoaWwzBhiLbHbLlgqJ24HgddgpdM/fHOVdDCt2i3CJgNo0uVNyorFtUzerH1iU6dkAkMMTqSnCFfNKAkFkitIwrdJgpci6VTZtbtCsE6GBIAIotELCI8UJmGy0MyT6WHS+kFTuWhykfzUL3PNLkXDL7oXGGBIoOmiYXa6NxhtgiC8AEithlNTBkukSaVDmmyAIwgaIYDLmkGTdkQpFq3FjJ9DmNY2RCkea+nXf6nEsCRSEYEplQFAIE0SKdImDiFpUpQa5xgQ5rXJHGBSozrmiRBRfMFDrNVCZHmUIXEwv7Gl3JbhGAYwtFx6rs9unVb6SXYYsm7A64koPM+lcLfQ18AKiTk2Wy5UEBYECURu4UbaqqGgs522RJThYm9sky0IsupcyW3WXKgZeZELeZceeLPT69Qr+/nUoNm3399cBCbhmx+6sJgCdtF/vtqVnh1l+vcPvaJyusk91BlSz1nZPV9nf63PWzQ+7wZp+bGmGR10OZcuKsdsgSyBcz/Xu3UTSwnenLDrMOOfuRbRt7VHsA2Cee5ex7nSnLDQA9soQzO9+hBl5N9TLueO5ii2rPlP7uYA070F+b7LEBFgNEprYz/fEJTfjq0lbBldzeIUt0A8AjFz9CL7MoHSuHiP1KwXwVyEaJS1qxRRlYGFohXSTNhJamakWNmo+hQ9603ayBCvFSz4iAhx0jwk5oJtuoEfDXzRpUAMy4Ac2sRsHKUtai4WYlb6JB9L9TqVKVtZi2nQrX93pWQVMxI7aokVXRINoDQDOrok4dH+J8VasUsDQrOdV+vVFFu0q0b1bQrXGP/pUGs/4cK3V9+9PtCk629O2vb+c4RbRfJfoCAO1qThV2qOU5Vmt6t2W1Vkenql//RqOGDSL1cJUocNGqVOgKes28opq4V1TPqjiBVWobmsmkRcxzfC1vTU1ArFn3MjlpagM1dIhlzMqgGp0YnFa3bRYdLBXEOBusqSbNNdUuumgTE7qvDNaxMiDcokLv5rSLZWp/AQ5yakWDnheLzlgp9M+SrMgpp5HNFlrDDViDe4yVS52qftJdAGgSmVeHoWMDRDevfYuqnQykExiqKtJi2EkeWRBiYGilWB3DkMbCr6M2hiHtS4KdmK4MDGmVZdkYhjQpGiYIaV50ZSZmZZ2esvPKaNJcTLDRpLOZbTRQxM5vAgxhSCszoFquxs+vCRIaqDAhRQNFLAhp12tK+l3P48+VJSPw1UCO2UbTnq3Itt7kU+YEnjRQtN6ctNFA0en2pD8aKLq+PWmjgSKBoetb/H6zx1YDRWYbDRSZIKSBIrneGCgCypUV10BR3bi3NFBkpqdp3ndro+CuhgoFRgwUARglHcWfzw0DJjRQZMYAGiiS43NicJoCIxYSWCgCoIIis40GimR4wEpxkgKjRUIRoJ8sWNwzbSq/wFCtqFNgxM53xRbX0kBRZRSPdKqnxv9opI39D0PHAogYGGLkcoVCA+6udFcImIWhUP5zp2jPwFA/kObVzRo0DDE66CSudcUL0d5G6CXq2t95llJmXR52/I8LhGIukQ1DoUDJ9VsIiso4Q4xsGNLAkQ1DsW3a+xCCoiVHwBuCHDbtzQ7YYy6RDUPdWh51iuzfGacICEORCUOiEBSZMKSR7QzFoKhdzWeOYQyKatb5Z5wiIAxFLgAKQZF9vcWgyL5/NVDUzK3CHIRTBOigyFQIitYcQV3oeW4XnohBkWtdrFvEOEUAn/4XgiJ7rPFSsREEhQ6mv9ZroGhtMA0pjFME6KBoqj0JRcz+NtENgpG9LtYpAhbrFgHcuLSYW2SnQrJuEaB3jI4LFB0LIIqJLa8ILNYVAjgYMl0hjUxXSCNJj1t0ipxLvrQ5Hwz5XKLDSJFjtsGAH+CHIZ8744MhH/T4/u5bTxlXiHWGuPW7++n7uw9MfG6OD35CUORbl2/bbJocIx8M+f7uC9R9UBRyhnxQ5Pu7D4pMd2iqPZmy5pIPhnwukS9NzgdFIZj0HWsbhsbb9kCR7+9M+hygc4om23S39d2/ofvahqHxNjxQVPfcXz4o8n28Y9LnAC6FbilvlHKLXGp43tk+KPJliPigyHd8GKcI4NyTysh7Y1Qmhc4lX/EoHxT5gvvjmEJHTQficYuywv388UGRr5+LcItMMW7RUevIgShEhmVBaNFjhVgYCsl+KMZAyH45sOlxwOGlyGkUAxX75RYDoToqM05RDITsbcT2ly2lbGuRzpAmRc52iWIgxH5Jtl2iGEjMuC4Rl8YGmcNMk3PJdoliMGRDTswZsn+PuRYzLociTc6Gn5hzZEORD4Z8crlDImY8ETALRbExQzYUacZf2cfcB0PjPljwE3OObCiKQY/9e+iaO4r0OR8MiWwoilVys997LnfIlP1Mj5Ult6EoBlXaFDrRYTtFsUq0NiTYboktG4rWBidn3CFbNhSFIKnMuKLjlkJnA0es2IQNRTE3aNEpdIscWwTEweg4uERHCkSuAyCFFVgQAo6XKwRwKXJlXSGN5GXjSpFzSdLmtCly4hIddorcIrYxL2fIlACKtniCAFBsviCRrJNxhQSKtK6QBEnzcoZ8OmiaXKxNM6uqYMjsh2qs0yhA1jpDAjnaNDlppx3XIkE+M2ZIIIgtuKCBIdMlCsGQyIQiTaocU2QBmEARVYxidOxjMCQSCNKm0QkUaR0gaae55kwo0tzDdhufOzS1jSNMn3NJoEY7R5NAEeMwCRT53CFTHbTGYKQZP2wWW9CU/l6kUwQsblyRqbIpdJpg3kyhiwEgMJ1Cpz1WrGNUxi1ixJZ2X7RbBEzS6FwFFY4aio607LZv5xsZfxIvZWfU7ZvoYhsX1e3XihtQECWU2bFCoXE7Lu2T7QHdPBCm7Mk2Y2JzY/sFV9a2T5bUbmY17Bb60qdLlTr2BvptLFWrVGneTrWCsz2+fKtWTAU5UZWtXUyKLf/bI44/ALoQN7u33WoVu8w1Uatgjyjv3K7m2NrXr3+lXkFvoF9/s7rY8wsAZPVutMk+sevfIx+NF3v86+9Sj7nvM2zu67ex0cip9t1ahrM7+v7UKxku9biDxEYIWwOuBPmlYptq34xMCGurm3Ptd8j+A8AuUWYb4N6X3ayBc8Wmuv0yWrg/e0i//mIZF/Pz6vYbgxPUFBFltJtx5aHZctKDjHvXlBkvxM6TxU7IzpR2b6CBy0Tp+27RxYVMX0K7ghrOZfer2wNA31O6/8vn3k2tZ546MofIBUPtbA3tjCvDxxIta4WuFRwBnyg2qC9MDVSpCSQrqKBBvhBqqFHu2VLWUj+wa1lOzanRyCpU8G5WbdOILWENDGGIak/m/HeqrKvCjedZrdXRIrfRrVWoQfyuAeex9jKhp0bNSgVLRGpPmzxGS9UqusR5Y9oCoPYV4JwJYAhDjE62cizVOJpYq2dYq+uXOdXMsNHQt7+lk+EE8c4/3SpwqqkPHE80CtzQ1rfv1IDTbe4YtaoZTpEV6zokBLLt2XRF7bVay3PU8hx14jlRyzOsVPX3cY6M+vjWRZOaR2i92lRVgxQ1K1wJdWCYIcFMctvJ6lgiMxHYCXFvILNZzEllNaqhSs2Fx05ovlGsYGM0qa9Ga8U61pQTvzaLNuWctIo2/UG5UTSo4Qy1okbNGVlDlZ5ouMu6dQUXi7Oxsjl5sKmjdImOxCHywZAoNrGWC4JiDpENQjGHyD65MYfohGWpxibltFO5tiJfOOwJU3cVk8XVLIu7iNxwdnpWLEXNBqHdyMScNghtDSLn2QKhS4PwMXKBUMwlsmEo5hLZMBRziWwYirlEdpAfm/DRfnlv78e//natgCi2D2bwrnE0zPaar9FNIz3nUi8+qV7bOEax42Ofr8v78a9qNgzFXCI7wIy5RDYMxY6pDUMxl8geg3NJ4YLYIHRuL7zMqeZ0+zO74fa3dKbbPxr5oHu6Nb2+h3fCz6ITjen292+F23esR8UDW/Fj1LJA5eHt8LVtg03M+dmwxmXF2nct4I05RfZkvLF705UauBd5VtQM1/nCfvxeNt8xF4r4BJNdIwjUTMS9Xp20jz3b7Q9E5xWOvl1UaKuIPN8tcLpUhG8EO4U75hTZ45piTlHXiqViTtHG4MTM32JukQ1CsVinawX6Z7IL4fbWeKlzkYlrm9awga087JzYE6tqMnRst6eXhe8FG55i7pINo9uRyXcb1jmIuUU2PMXcIlc6ZcwxqmNyXLeL2XN8FE7RkRdVcLlCoVzVMpVEXK5QC35nyUW6WeALgQ1DQDgPmR3XYsOQRjYMxcSWdGZnWmdTuhZdqAA4ns4QI/ZLJjALQzHZwXvM2bB/j32NblpjFUIuUbtSnYIhIHzMXOerG3GKXL81QqW1HftnB56mXMcvdExdzlAtkOroKkgQc4pcrlDIKbJhCEDQKbJhCEDQKbJhaLhNPxzYMAQg6BTZMATEnSIbhgAEnSKXyxNyfmwYirW3YQgIO0WuazJ0b/rGSYXcIvu6XKnWgm6R/cEt5hTZgXLMKTJhCNDNG2aqzPOVcYoAXPFOETAbnMfEOEUAKKcIgNopErHjbFi3COCLX4XcItfxDrlFNgwBYbfI9VvILfLF6yHHyIQhwO8WHbYO3SEy3aFQepzLJYqlx7lcolCKnMslCp1El0vkgiGRyyUKwZDry0kIhnwuUQiGXC5RCIZcLlEIhlwuUQiGXC5RCIZcLlEMhmyXKAZC9pfEGAjZDksMhGyXKAZCtgsSe1G7XKIYCNn7EAMf29WItbe/RtsgNNt++rqwQciWfYw08Gq7RbE0OdspisGe7RSxxzSWJmc7RbHqbLZTpEmPs50iFwyZsp0iFwyZsp0iFwyZsp0iFwyZsp0iFwzZst0iFwxN9clyimIpb7bz44KhUHsXDJmynaIQoAOz96amaITtFIUgHZh1i2LZB7ZbZMOQLdstsmHIlv2Mj6UPu9wi35QTItstst0hW7ZbFCvwY7tFsap3tltku0O2bLfI5Q6ZcjlFIfhxxTuh8+xyikLV+FxOke0OTfXH4RTZ7pApn1MUGgvkcopCsORyikIA6nKKXEAkcjlFIVhyOUWxYhsup8gGIlOmW3TYLtGROETsWCG2JCAQn2TL1lpxA5UDeaLYCMKQLXYenMrof4xqo/9ppa1iNl5/Gi8U1XFzhbq1yoFdoXm3j8HQzPrJY8SeM+DKHDNkBqGaUtWmU6QdK2S2i8EQMO0UxWAImHaKYjA07MOkTQyGgGmnSANDwLRbFIMhYNop0oz/uVLHFJlixhUBoMYVAXxRH2ZcEVDOLWKfvdeaW3QljysC+FLVVVRot4idL3Iw+p9WLTSpsUXdokuNLVop1kqNLWJi66N0iw4ViG5e+xY1CAl1MiAkaXNaEJK0Oe3JkrQ5LQhJ2pwWhOThoAUhKa7AgJAUV9CCkBRX0IKQAJAWhASAtCAkpVEZEJKyy1oYKltCWQtD66MXqxaGpJ32hSwFFhgQkn3QBu7STttegi4tDEnqnBaG5BgxMCQQpIUhSZ3TBpDyZZ49pmUKKDBiCidcq2KLLZQttBBzh+z2MXdIJFAUc4dEck1rS4oP152PltFtQ6BIO32CQFHMHRIJFMXcIZE855niMvIMjrlDIoGimDskEijSTv8gUKSdE0mgKOYOiQSKYu6QKYEiLexIO+15FijSztUkUBRyh6b6M4KikDtkyoQibaU4gSItHAkUaYFToCjkDpkSKNLCkUARU4pd4uyQO2Sqla0ceoGFQ02Zu2v9xeq2y8UadiMDxWw10MTlyAA8U0uDtehgN1MbZDntdl6jS3gusnyniJ1rp0xJ50WqR5bsBvgvgsu1KnaJstrL9Qo2iXK83VqOM7v6c71cq2CbKOm8Ws+p8sAAsNGs4NwuUV6+nuPCHrfP53aZMtY5zhP9YfsvfbpMHKfleoUqt96t5dghyigv1bn2ALBKVHoDgDLVuMmpidAhTbpazu0zUX0cAHChx+/0ebJKPnP/A8CJZo7LRNnvlXpGlQmvZBl1f2YA9YwBgGYlwzZROr6aZzi3p3/ntioVXFYUZxCt1RvoExdHt8aVvgfK7cNOX/9c6laruKQo/iLqVKq4uK+/WLvVGu7f1087AvDjhIbLcHEDO88gGyvFCg/YKsjS3ABQKfjjxIitMNxCDZuKAlyT9Vep41pFjvMZdy1VUcEFYpqcz579HWr9B9GhOUSPX/8Bddtl0pIDhjDEaGnAbaMMDAFAM9fdILWsglpWUcOKpOC1CELXTrQqauYVNPMKtPOtNiv5+B+tWtUKVTK6U63QM6+v1mpoE2layzXuobZMftFnJ75cJlNaVuv8bb1BTOAJTE+0qZHs85ryi/jSqP1qQ9cv6f+asr3ZJ+35kPOsvb5lvdr5gJbqXHsAONXKwJyKjQawQo4VP9kssFrXB5l3dvs43dQHgHd293BrWx9g3tDcx00t/Ut7pVbgljYZ9Gbhwg+2mhVgg0hVO9GUa0/ploxcvWVl+8rooa29T2WtLWLip+aobUvpgMq8Z2t13fNbJoftkul2FXJ+NTadFdDvg4hNE2bTfper3E19Q1WfeXMi71KTfgPDyXCZ+Z9Wqw1qH5YqdZyotHGionR9sjo2smVsZLr9bqGJdtFGW+kSNYsWmkWLytYZGP/TiIUhUYdcji36tUoOZwGAFWK4CcMOB9WhpszVIvbdcrE2BUNayDHbdRU5piYMaSzLsjCkVY10YNgLFuBdIc3M5FPtyZzyMiBkpqRpoGi1VptqF4Oi5Vp1CoYain0yYaijCKzN4HujET+PJgxpghUThpaUgb4JQxqgMIMsTcDFAqC23yIW5oASUGpBb+x6t9fPTpKqaX+qNWmjiXs3jEeAFopOGmN2NFB0Z3cCQhoourM7+XqpgaIbmhMQ0kDRSm3SZy0UmYdeA0Xm5aeBohPkGJ8VK8UxBkUV6wsW+/GCgaLxMiRUsEChgaK1+uRkaaDIvEe1UGROZq3Zh5bxztFAkZm+q4EiM+1aAxTmcbyhuhwFoxP5JIVqJW+qwGgtn6TvdfM6BUbL1ToNd1ooEmmhSKSFIlNslV9mnJBW5sdyDRSZcaUmxjTH7WmhyEwvXCk2omBUV6aCzkuHAkQawivrCjHO0NJgjXKGNopVCobYogCAG4ZC8OK6UFuoBZ2iecBQyCVyBYehgNEFQiE4YgsVADpgMlXGFWKcoW4tn4szFApWXM7QUi0PAoYLJkJQ5AquQgGXa59DLpGrryGXiO2/7zyEzs2iHUBg4g6ZCkGRCUOiUNy74XgErNTDYHTSUeo6BEUmDIlCUGTCkCgERSYMiUJQZMKQKARF1cydThiCIheLh6DIBUNal8iU1ikShe5R15piUNR0/B6CoqoDUEJA0XLAQwiKTBgShaDIdY+GoKiaZ3PZhzJOEeMWlQEKxi0CQLtFAIJQtFqdPXehfXCNBQ5Bkau4RQiKXEUJQlDULNxBewiKXAC0CCgy1UGdcovYQmCrxfLC3KLDcokWDkQHhSEX8MRAyOUShUDI5RLN0xVypc1JipxW7MUJ8ClywOE4Q8xvIRhyQY/tCtlyuUQhGHK5RKEA2eUShQJkl0u0XKtccWlyrt9C++2CohC4uaAo1H8XFMVAxfV76Fy7rv3QNnyA44KhkFwwFJILhky5oMgFQyIXFLlgSOSCIhcMiVxQ5IIhkQuKXDAkckFRzJBj0ucALn0O8EOR7Q6ZckGR7Q5Nr2u2T6HdblUyJxi5YGi8jAMqXCAhcgGFCyRELihywZDouKbPucAoVNzFBUWhojwuoAgBpQuKTHfIls8tMt2hme07oMgFQ6Lj6BSxbhFb+deXQldm7JBPLigKxZau30JVHX1gFKrId1yg6NDLbptpc3aKXEysIyQ6rPFCWmlAyAQZLQiZN0EZEIrBkPmu1YwVsn9nUuQA3hliXSFA5wyZUKRxC0wo0rgFJhRpQMgMUlbruQqGbNiIwZANFGXHDGmlSZMzoUgDc+Y+aPtjttOca/Ma12zDhqIYDNntYzBkry4GQy6FYEhkQlEIhkQmFIVgSGRCUQiGRCYUhWBIxI4pAmahKHYJ2lAUS5WzoSgEQyITikIwNFnnpA9aVDCfNyEYGrc3oCIEQ6JFpM+ZsqEodp/aUKTdB3M/QlAnMqFIU+nShCJNhVITKDTHjHWKAN4tYtLngFkoilWKtccVxUqf2+OKNCWrTSjyuUO2TCjSOEGH4RYxKjNMg3WM7BS6w06XAw6hypyL6nrYpUBoFzulQCgryBQlcHX9WRDaGexTrtDlYpe+ELfRW6grVBS8K5RpqzKMxFL6+V6PhqGtfp9Kk9vtD6jUqc3egIKCM7v7tCvUKJHrry3DKzq326dg6MIet9/ndgfUmKHzu33K2Tq32y+VwpaT1yz7YXlnv6CcoZ39gnKG9gY8DF3Y08GQ6PxepoIhU50q17434M7DfdtVFRCJ7t3K6ap7j+7GYcjUmZ0BNW7ocq9QwZCpTa7gFi4S1edE2/1CBUTj9vsDFUyIzu31VCAhurzfC7pDtvqDgn4W7LHlDDE7yXW8fZ+aB+3S/j41f93F/T0KIu/fvxh0h1y6MNgJukMuMdcGMIw9GD3a36LmgjpTXKTm8NnKttRAJOqhR8FOjnyu7pBL9qTGMfVLwNr57CI1Z9OF7IwTiD519s30thkt1CHyWVwnB9dT6zlVnKS3ra1RL1rHEtU+ZPW61K5wKXKtSgUnq/xgvuuq3H4vVcgJ8+ocoLGDbdlJCLu1HDe1+c/gp5rcfq+T6WU3dLj2t3XJynnKam2mTigm1rR1+xK3H7d2F9v+jmXu+rt1qcSXLdoNy6hAEeDnDrpJMcmpKc0kp7ZYuHny2uxM8yE9prtJtQeA27tbVPsnrGxT7b+6S5IEgJvIx/IdS4s917UcWCULUJV5fmgrRIqua3P3Hvscv7XDBaNMBUpRmVTkdUWxHFPXt7iTd12Ta39Tm/uY/PjOOtUeAG5tdumxluyEwOwE4zfVOai7pcrt9wmsUu2BYeobA10DDNAjy4tr58gSNTPuemXLqQN8JbrVgTvmX3Ta3KGmzK0O1rBKpK+tFEtYKThQAcrDkHa2a4Eh7dw2Mm5FOziS+UoGTAZSsjm3LAyJo6KpvgZMYEgbLAoMaWaHB8oNXi9T3KBDD2AelchVfuVdGq1/XRlwSDCjPU7ABIaWlad8tV4iyKrLZJO6fi2P91s52WRDSgkr1y/9Ib7OSwCkHbReZkC8nG8tY0uqljY222gUo/Z6KDpZH8LQSlX39e+OzjDtbbmme1kLDF3f1M8FclN7CDdaKFqvD9Psbm3rttHMh/t6R0cfcMg5044pWhndb8x9BwBLfPav+n6VD/MMFDXJZ/Py6GLVurmd0btCU3nTbLdMPstreaaeSLY92lcGiiTdTgtFq3WZRFsZS4zWz77DVklYub5Vp0EN0BegWRsdHy0UdcjJxiWLZV05mbmI/QhdZpw2oEvNA4DqKENIC0XSFy0UVUftDgOKukWHis3bg+54ktzD0sKAyCY5G4RiM/raIKQBI/uAdyI5iOtYOhRnyFQMimwYikGO6/eYnb5UqU3BUC1y89jlqDU6qDMUe/HaLwTNC2KmFHIE1Dq1bAqGNLvEprosWQF1DIrsICZ2nE40sxlnKBac2YGVBlhWyf1mq2TZfYgdZxtGNVBkBz6xPtowpAF/+3zHZAfesdhMYGjSPg5FAkOiGBQJDIm0UCTSQJHAkFYCQ6IYFAkMiTRQZMf2MShase4zLRSJNFBkP/ZiUGSzgAaK7HFssWfOsnWRssVbtFA03p7i2W+3iUFR29pHzVhNe+xRDIpsSGEhR9PePBer9UoUjOw+a6Bo1coaiUHRmrWNRTtF67V6FIzMmOlktR0FIzsVTwNG9sSzMSiqWsMlDsMpioGRuQ81VEqDUUj2UBcbihbpEi3cIWJdIUAHP7bmlSLnc4lWqw0nDPlconalQk0GCpRzhlj5XCEfFPlAyOcStaq5E4ZCwWKZNDlWvmV8/fK5Qj4oWqlnziA95BKxwTGb5hJKkfMFZ76AygdFq/XMCUMhl8gFGiHo0jpI4/V7jnkIinzBjg+KfM5Q6Dp3ne9QrEhXNmu44ccHRSfr/RkYEvmgyIYhUQiKXKlyIShywVDIJbJhSOSDIhuGRHd09r1g5DtP7DkKQZHr3gtBke8x6LuHfQzge640q5m3MiLjTgNhKOo4HqohKHJX5sy9YOT7uw+KbBgyxabQselzoXebqwJeKOPBBlORD4p8fV2kUyQKQZGruFK3VvGCkW+Msw+KfB+QywxZYN0iJn0OGEKRD4xc265kuReMqp6/H5ZbxOiw3KKFAJEQXAyEbJcoliLn+y10cF0u0WG7QrZsl6hVqQRhyAU+MRhy3eRlU+S0irlCdrDYqWZBGHK9dEMvDN9v806Rs3eTdSuAMAy5XKIQDLmOU5nxQrGvyzaYxFwhFxSFXBcX+IRgiAVQn2JBjt3nWJqcC4pC59sVK4YCbVd3fTDkkw+ETNlQ5IMhkQuKQuOGXFAUcoZcUOSDIZENRT4YMsWk0AHuc2W7Q6ZcUBS691xQFHuk2euLZYmVGVPkeu74gnDADUUuGBq3dwToMffIhp+Ye6RNnzPlel6EynW7QCPk1LBzJLmWCZ2H2PZd8kGR7Q5N98E1R1ygtHitMgNGsUqzZdwiRi4oihVqcIGJ7Q6ZaqE5A0a2O2TrKMYVhfZhXil0sUJoAkWLcokW5hAdliukIU2BIm2K3NQMvAoYMl2iw3CFtM6QCUUaGDJdIrYc9aKKJ8hLVzv2x26nKoVsBLBlxwtptVTLVM6QCUWaYMUMTrQwZAZmZccLxWRCkSZNzgQgjTNkHn8NDG008ymnqEwBBY3Ma0pzvs1YUeM6mN3WwJDpEmlgSKQdUyQyoUhTRMGEIk2anAlFMRiypYEhkQlFmowv85yFYEjE3nsmFGm/7xyk0EJoUmBT5nMnFoQD01AUgqFxeyOA1qbSlRlXJAq5Q6bM54Zm7iITijQwUmas60HGFWmcLBOKVuvVIAyJzAnMQzBk6iApdJoKuCYUaar1mVCkrVpXZmxRGbfI3F5MJhT53CFTZgpdCIZEi0qhs7VIp2juZbefufoKepkmWVawTNk/elJTcq4DAKiSpXr3F1vxHIDuQjbVKwa0M8R+ZGOrRWvm17B1mSx7DQBkNXE61Y893Wd3B/SX2w5fVI0+f2wl2t5ip1QAAJS5k8jquKVmhmCzO7vk+VsiSkwDPOAAwIX9POoO2TrZ4CrQVYkCEABwYY97Pn9pq0kBkej+He6EsNc6e+/tcIUAAQAXOW7ETp+/m1inZWd/8e8+ViUyscFWLz+7u0+7M+zzlr2m2CkGHtzeU8GQLfY9zu73PrnA2d4eVb4cADb7fFXKrYJ7drLuz1rGAQWgn4NMtFfwD54euGU2wY0bBYCPnP839DIhzd0hqhCEuJK1sZJxeZrs3D8AsFppokVc+CcaDWqunU61Qk8iys6IXWYbq/WK6qvduH2jgpNkOWrWUelUuRLF3VpO5au3qhla1QwnW+QksOx4nnpGvUDX6sA68cFopQ7cTpbrPV1iHrONRoG1uv5FslYvqPSs1XpBzW0DcMcJGH5t13yVt5dZI7az1uDn9Vkjv9CfbhUU4FzXHKBd0be/obmPTgkgYktZf9XKRaw29UB04+olXLd8Wd1+tbWNW1cuUn16LLF+UaNS4PaOniZWagOcaOiP72q9wDIJtGxqZC3nrttWBVgjXe+NRkYXjDjdJouLOIrDBPvUzLBBtF9rZKUqRrLjG2/r1ihXerWeq6uPAsOJnjsk2bH7cMdSA+uNCtaJMuZrDS4W6dYyOv2ZWT8A3NJuUgU8lmoVXN/kXgKNrELPz9Qg5xHqFX30CGBp5hU0iLknAaBOTBkjYk2IJbSxBD0PsI6aRgsvquCTCUINxSCudl4bw9BS3sBSrrswVyvcQTvR4C54E1I05ajb1XwMQ9qJOFkQAvgc4dWGuR/xB5FZgU0LLAcpnqDZht1G3a9xGWRtugS3H2ZgrAn2V4z22qBaYIgJTNjgygQnzbKrRnstFMnx0UIRG4gt16aX0UCR2UYbXMp50zo+7LxB1zUngbcGim5oTr46MlB0a2cINl3lhKpfZYCKBopuXL00/ncNFK22JnCmhaJOdbjvdxBzGjWMY6qBopXa5JgyUARADUWd6rCd9r4142LNdWt+Q2KhCNDfi3JvaKHIBCENFJkgxEARwJXRl7ZaoDBThjVQZLZhoAiAGopkwmDtPtgphRooMud/YqFFC0XSr+V6rtqGGVuwVQ1ZKAKghiLJ6GmgpgKjrgEFDBQBWBgU5ciM/aiqwMjMZGKgaN6aKxA9a/X/ByDuEh2WK2TDUMwlsmEo5hLNwxUKQZHLFdJs04ah6ABLcsI6l5sSgw8bhmLwwaa7+bYf6pddVlvTLxuGYt1kXYIVR/vQOk63Zp0hTWBiB1Uxl4hxkYBpGBLFoMiGoBgU2fsZc4l8xyUERa7fYsGlfb5iUGTDUMwlMmFIFIIiE4ZEGigSGBLFoOirSNfGhCER4xQBcSgSGBJpoKjhOJYhKDJhSBSDIvv+iEGRwJAoBkWu51LounUZ6mv1LApGduGU2LPHvjdiUOQCILZgTAyK1qx90ECR3Wa9kQWhwjV+kq9YF26/ZK0vBkUnrKqbsX3wja9inCIgHo/YxzYGRa5+seAVgyJ7XJMGihoWQKzlrSAYuYY3lHGLQmpaEFQGig7LLQpJ3CFhjnlpYQ6RD4p8MORziUIw5HOJyrhCPmfIB0U+MPG5RGVS5Mr85nOGvCU4PQ8zn0tUJkXO5wz54MMHQ2Wgx9uvEukRPmfI997xgYwv0HfBUEihFLlQYOILpnzQ4/u7bz0uGIrJd0x8f/ftnw+KWCcJCIOSL7j0nXMfFPmcIR8UuWCorDrVgReMbBgS+aDIB0M+l8gFQyIfFJnukCkfFNkwJPJBUaNSOGGorHxQ5Ls/fFBkw5DId/+F4mA27RPwu0W+0vreDw+ee4NNnwP8UOSDH9/fbRgShaAo9BubfuaDIt/ffVBkw5CITZ8bbqNM6qA7jljz/N0Xj/iO7XJ9fil0vvjCB0W+Ig8hKLJhyNS8Uui6npQxHxTZMDRe/xxT6EJj1n1Q5FvGB0WLSJWb9OWQtKjxQjYUxWDIdonKpMjFXBobimIwZLtEZcYKaSZdm1ku8mXHhqIYRNhgwqbIAXFnqExa3Ey/yLLJvrl2TNndjjlDdqAfg6GZL6slxgsB8S/LNvzEnCF7fTEYsl2i9UbcCbJ/j8FNmQkxbfhhxheNl4mcQxuKYmlyNhTFYMjlErncIVs2FPlgSGRDUcwZsqEoBEMiG4p8MCSyocgHQyIbijQg5HKJXO6QKRuKYveHDUU+GBKxaa/DZab/WzPc0oai0DxjwOw9F7s3TrezGTCKOUH27zEnyP7dB0OiMmOKgFmgiFXXtOEn5hzZUOSDIVGnNjuuyHaHZrcx3WdN9T0binwwJGJdnOEyXL/sbcTiizLpc/NIoYsVv7KhyAdDInZcEXDwFDpNAa9Fjys6qOYGRC7rSlwiLQiJS2SOF2KkdYYEirQwJC5RmbE8WmdIoEi7DWnHQJA8HFYblbmkybkk8KGFIYGPMmVG2WILgH4/pF/seCFAnyYngb7WGRrn3ithyA5KtMGTQJA2TU7Wq3WGBIrY4gmA3ukRKGKcIYEgLQyZgaX2nAsUaccMCRRpnSETijQwJBIoisGQSKBImybHFFmYWTYCQyKBohgMiQSKGFfIhKIYDIkEirT3h0BRDIZE5n2tfYTKtcvUnhEoisGQqIwrK1CkTYuTdtqxQtIuBkMiG4q0kCRAoZlqAJhAkDaNjh1TBEzcohgMTbYx7Lu2FPlwGT59TuIS7bEVKNL2q0z6nICRtgS4CUYhd8iUQJG2EjCbPgdM3CKfOzSzjUMqtiBgpN13gSKXOzTPtLkjK6qQlJSUlJSUlJSUlJR01JrbPEQ+SmMnp1qqVrHV56y+Msuwbs9yPcdmT3+olusZ1R4A2OkfysybsNbIcWGP2xA5/Imm7E4tw26J+TVYsfMznGgAl4kpAU40Cuz0uY2w5/y65gAXevojfGI0CeeF/cV++1ivDfDInn4bJ+sDPLjL3YP75PCZ65oDPLhDfh2sD3CG2A+Any/jhtYAl/b118kNzX2c75HpsDX+hjrR4CasuXPjHDZ3uIFvnSY3J8cuud/tRg/3nl2hlvnKNp9/enaPPx+P7unTRVaqfZwl9/1ij3v2tCoFzuxyy6w3Cpzf45Zh553baBR4cFu/0M3tAe7dWuw9K272WcLoXG8AD/NTq1BargNniD5d1ywzLxXXHuDnhTvRAB7e4ZZi3wfsOd9oZnhgix+zeW6Xm0fowmAn3sjQUt7AzkC/jeVqnZ4DcXfAnfRqllN9kmW2C+5i3PfMBvi+82+g1uPTwqIkqahRU8yIK1qq8pN9yTLtitKmrFexVq+iTkTHZUtFatOzpNoZM2hwuZ7RxQTWRjb7inI73dpwbgZm3qB2hWvPFjdoVyf/MFqqcZOWniDTuU6M0laaRPrNen2Ak0SJXnZAvcAQwE3IuV4bYF2ZDiTtGZ2sD9tf39A/dNdqiz1WwBCGzP/XLsP064YW1y9Je2MA57b2LlZr3Mvp9u4Wlmr6l9OdG+cAcIBz8+3nsX5aX/r6xC2buPEx+sp17RHQ3bJ+Qb1Mo9LHHV2usl0zH+CGpv5Yybk7UefOyTpxzht5QV2HrQpXwtsUUzTldKvAKWIeMunP9WQZ+lvaxD3b4OZGM1N72TTfUwRrn2gO/9FqefQtgi2UwU3NANxIDuFYrQ9TiNkKq6eI6oHLtXBFvJn29QyrjeE/Gklq5ek2Wwwrw00d/QGu5hk2qi1sVHUXioyZb+ZcAMTMidus5Fip1bBS0+1HdRTjs30CgFamP1b1rIp2Vkc7Iy8sQnMBItsdsgeMaaDIhCEt3LAAtWbNrqyBIhOGNME7WwnFXqdmebONForWyJxjO59XAzlto42mvbnvmtRjG4K0ULRk3HMaKDJhSDOPzAkrqNBA0boRdGsCGTPA14xdMGFovJwCiky40YCO2eakAiTsNhooWquVP1bXK8HIhiANFG2Q59CEoSXF+BB7DJAGim5rTz4Xa6HodqPAgAaKBIZEGii6+fbz43/XQNGJWzbH/66BorblbmmgqFGZHE8tFDXzyTnUQJF9zjRQtGIUrdBAUSM35vtSXIct6/mkhaJ1o50GisxxchoosvuhgaKbDRDSQJG5DQ0UuQBIA0VmGw0UmSCkgaJlKybUQNF1xnp1UzNM/l0LRatWvzRQZL5vNVBkjsvSQJEdU2mhSKSBIruargaKqlb8qYUikQZAlquTE6CBIruqshaKmD4BE4gCdFBUt6pQ21A0r3FEc3eI2JKCS9UqDTa+ZUIgZcNQTL4JvkJQ5IKZUHvWHfGVnmxVw26RC4ZCLhFbXaddyaZgSBSCIte+h6CIdYRES457LQRFLmcoBEU2DGm07gi2Q4GMy+0IQZELhlT9cqwzBEWu30JQpAEmW2uubZDHKgZFjCMUWibUL5czFIIiX0GEEBSZMDRp7w/Ab+9uTcHQuF8BKLJhSBSCIhOGRCEoMmFIFIIiG4ZEISgyYUh0R/dyEIxMGBKFoMh3rkJQtOIoax6CIhOGRIxTJIpB0brj9xAUuYqGME6RKARFNzsAKARFrn1knCJTIShy/RaCIhcAMU6RKARF1znWF56aYfZvrFMkCkGR630bgiJXkYrY/EkuhaDIVaAjBEW+AlI3dWqUWwSEocg1zUwIQEwYEmUZ5xYBYSiqOsyOZl6l3aJWVqPcImAWiuahuQJRCIZcLlEIhFxwo4En13IhGHK5RPMoB2nKFfyzYMU6T6KQM+SCohAMuQDHBUIxhfbdBUUhGPL9tlRzw1BIoTQ5FxSFYMjlEq3XB04YCimU+uWcEDICQz6XiAWfUHsX+IRgyOcSuWBovD5H0Bc6Vj4oCsGQ77fQMq5+hdLkXFDEVIcTuWBI5IIiFwhN9csBRT4YCskFQyIXFLlgSMSkz4lcUOSCIVMuKHLBkIhJnxO5oMgFQyIXFLlgSOSDItsdMuWDIhcMiVxQFKqg6IOiEJC5oMgFQyIXFIXW74MidjqA2DJM+hzgT6Gz3SFTLpBxwdB4XeQ78sa2H4xsd8iUC4pC71smfU7kgqJQ3OSColC1QjZ9TuSCItsdmuqDA4p8c24C5VLVXFDkm3MTcEORC4bsfrn6FlrOBUW2O2Rq3lB0YCASq6qMMxSTCTdlxhcBOmfIhCINDJkBfZkJw9jUO+36TZdorZEfOE3OJROKNDBkQ1SZMUNMGy0I2S6RZsyQCUUaZ8iEIg0I2UGMZhyMCUVaZ8iEIna8kCwTkwlAGmfIhqIQDLmkOVY2FLFpcdplzPOoGTNkQpEGhmznIQRDk2Um643B0LhfBhRpYMh2iUIwJDKhKARDIhuKfO6QKROKYjAkMqEoBEMiG4o06Y0mFIVgSGRCUQiGRPbzJARDIhMc1htFEIZE7ETMNhRpUvZMKArBkIgZUwQMocgEI+1YIXZ8kQ1FGifIbBOCIZEJRSEYGq9zZnqG+DI2GIVgSHTQMUWaEuYmFGnipjLpcyYYaacXMaEoBEOiMulzJny43CFbJhSFYEjEps+ZfRPFIArgxhUBEyiaR9rcgavMfdf6q6j2vWJAwc1Wv18KhuxJRWPaGxS0M8SaI5u9ggKCi3tFKWeIKWoAABf2CipNbqdf0M6Q4n6b0m6fT5MrYVZhc58roHB5n0+Tc02YGdIjuzlVFOBCLy+VJscer7O9nIYnVg/uVigYYo+VqEcucmYvp1LrHtnN6QIKS4qg2NT5XkUFQ6bWGlyVNwC41KtR7tDmTl0FQ6byGnePfOXzyyoYEt17dkUNQ6bu3+LyhO7fqdEV/noD7kY826uogEj0yG6ugiFTZYKC83uZen4tAHh4J6OLOtQyrv29Wzm9jX7Bv0jO7nIFFx7e5tPi9thn1q4OiEQXe3yBBmD4DmV0bo8vWsRWuju7y8VO53cL9VxWootktV4AuG+zpwIi0Zn97aA75FI954KtotABkanNff5ZujPYVwGRaLvoBd0hl9517nVst6Z06PMQLZOUuVbnqbRby1EjayyfYmaoA58qtlTLcD1pubLtgXITid7c4ZbRTswn6ta4CQCH2+DaMxXkRKeaBW7vcg+1x3S5t9LpZl89gaPoby+T5Y+7fJC7Xu9jhQzc7upywfdJsowzADx+mStB+vgVrk8n6vs4Ud/HaTIt7bHL3DF+wgrX/uYWXxnua1a46mi3LF/CUoOfIPVvX/8I1f72J56n2rfv7qD5uC61zK1PvkS1v/P0Gao9ANQrfdy2RG6nS5bQrfaxTlafu6nF3Ve3trn7/ER9UGq83+OWuf14/Ar/fGDv2yevcdvYqA9wiqh+KbpriXyWLnPHd7U2wClybNjjV7j2X7OyXypdV1u4RvS3yX3faBS4sc29p+9Y4mKU28n2wGQSYUZ3aCw+Q1/VWcL1LW6ZNjlPykaTC56qeYYVckw+oHOtTK1WSgykO6AODERaGm1VK2iN5v7JlKO6GiNqZYi6S07Os9rIsTpKLdM6KwJDDWW/lsg0MWAyCzMzS7TAUFMJH8u1iV2utbMFPFrK+6FbwmWV1DQtREmftPsNTKdtLCm/TosTsaJsf7pZZi6Y4TLrSsfnZGNUlplwiMx1a6FI4EYLOWx7YDIPzo0tHUxc1+S2wZY9nmxnf+r/Y5KgTbu9m1t8Zbib28MJTrSlsm9Z5gJ70U0b5wEANWW/Tt01TIGrLuvW3767M/53LRRVV4bPuZOP08FHfXSP3HzqvK5TlrRQ1B45fNr5nExHUAtF7VG6q9z30fYjZ4gNpoFhqqsWjG4cPeu0pcJPjfrPAM4tIxDULiPP0lvbuvamA8xA0cnR8/Sk8hksDniZYi7a83i6KdeJrr15jBgoWhpdj1ooup7slyktFEn6ntaFktjHjIdikpiDgaL6KG68pURQpIWi1RGoaKFovTFs36nl6JCxMwNFwgntim6ZRj4M5tp5FW3lGKmlSrmUPlMHAqIXnfinAOJQ1CInQQUmMCTSQJENQzGXaJUcYwPMOkMxKLJhSANHNgTFoGi1ns04QzE4YAdTArMuTAyK7PteAzh28YLYMnafmpX4vpepdmSnZcWgyIYhVals6yUcgyI7KNJAkRa0prfTC/73QdufaPRmgsgYFF3XJLfhCDg1gZUNQTEostcZgyIThkQxKBIYEsWgyIYhrUskMCSKQZHAkCgGRSYMiWJQJDAkikFR3bpHtFBUt9LrYlDUttIdY1DkSo+MQVHbKogSgyI7VVcTTJ8gC6IAExgSxaDolNXv0824Y3uL5YrF2tvPUi0UmdJAkQ1BMSiy04E1ULRqLRM7j6eb9nXCw0cMipaqgzEMiWJQZP+u6Zed7hiDInssE5uaB8RjIzvm0EBR3YobNVAksCKKQdGqBSisUwQgCkV2HK6BIpsPtFA0tUwEigSGhEnKam4pcz4o8sGQzyVqVPIZGNLI5wz5oMgHQyGXyJcm54MiH/z4/t6uZpQjBIRT5Hxg4LvhQy6RLyXNB0W++90HON2qbs4fTZ8A/777YCjkEvnGqPigyOcM+aDoRKM/8wKPyRcMhaDIB0Mhl8gHGvP6u/ZruikbhqLbCASaocDKBz++v/vW5du+C4ZismFI5IMinzMUgyIbhkQ+KLJhSKR1ijSyYUjkgyIbhkQxKLJhSOSDIhuGRGWubR8U2TAk8j0HfOMWQ8G0C4bG2/H8ZsOQiJlUVuS7f2wYirX3PUtDUOQDkxAU+eBH6xSZ2/Zt34ahSb/cf7dhaNynwHn3HRcfFNkgZIpNnzvZ8E9s7Rv75YMiX2GHEBT5Yh5fjOSLOU63MzqF7pZuzQtGNgyJfFBkw5AoBEW+bfigyGdKlEmfa1eqXjASd2hmGQ8UzcMZEi10DFHMGbKhKAZCvhNSJk0uJBuKfPPshBRzguzfYyDk+l0zXsgGg9jXD9cDgh2fE/v4YUNRDIRcEKXpk73vMWfIBUXsgP1YmpwNRTEQckFM7MuwC4pizpALitgxQKxzFAsYXS6RD4a821CkIrkCq5gTZP8e/WJNpuu5XCIfDIlsKIqlyS01dp1g5IMhkQ1FPhgSuaDI5Q6JXC6RD4ZENhT5YEjkgqJ6pe+FIZENRT4YErmucbZ4hg+GRPbzIFbExRVMh2BovB2rjQ+GRC4ost0hW/Z95IMhX/uYXMF/zKVxQVEMely/x4rF2P3wwdCkXzx82Io5ZzYUhWBI5IKiGCjZfYsVwmDHFLmgKDZMwI6VNDGHC4psd8iWDUU+UBGVGVNkg1FsG/NKn4tlj9lQ5IOhcfsSJcYZzRWIzJ1n0+S0rpAJRd1aroIh0yXSpskJFGlByHSJ2DFDWlfIbFemeII2TU4eFJ2q7iFgukTa9FiBHK0rZEJR2QIKGplQpCt7PWmvHTMkUKR1hUyY0Y4dEChar/fVaXImFGlgyGzDji3Sfj03oSgGQzPbICDEDKy0Y4Vcy4Zk9kfjDplQFIMhkUARM2bIhKIYDIkEimIwJDKhKARDIhOKYjAkEiiKwZDIhKIYCJkSKIrBkMi81jUwZLpEMRgSaZ8LIjOY1sDQeDujtjEYEplQFIMhkdxPMRiy2wO6Z6oJAdpxPKca/TEYaR0gs522cqb0JwZDk35N2vncoak+Ge21aYQHLbSgdY2kb9qqgCYUacp+n2hMwEg7ZrrM0AITimIwJGLHFZlQ5HOHbAkUxWBIZEKRZsjKSr06BUba+gJsCp0JRfN0h4ADlN0O5epVyApvrslRQxIwGJA9Z+fAKUOLdXK4VJ/ch2aF328AYOeabVcLnN8jS2uTjFamTDZ5qQAAlsmSvifqfWz1uQPWrpBz+dR7uLTPPQgqZMnZsl876op5Vw6ik80dPLzDVZDZJ0vhXtfcwYPb5EyIANg9L3OMW2T5Z23hBNEt6xdwaZtPnl/p6qBLtHYHX92wfkcchkzt3xefm8jWhc9x99VDZ5bobVTyAg9scvuySz5Tdgb81bW5z72AyrxLrmvu4dweF4hUiTLhAHBdYxdn97gv4T3yGXF5v9wTko2Y2GdXtzrAhd5ipwA53ezhQo+7Vi6VPF6sBuB2ZnOfa79SG+DsHrcvbJwGDOf9um+LvCZ73IZ2+vy7mi2xvUvuvEx5c36Xe8/1yRurEijO9juP/iy1LtFcr/BWNUeLHMhVy4GCmPWAHWMjWqpl1M42KzzcdGrD/dGqlnOV0aQtCwWr9QLtKnOM+bt/qcbNG7ReL9TV2kQrtWJqEkuNrm8OqHmAZD4fBnBO1Pep9ut1fmzBycYu1uv6APREfY9qLzrV3MEqsdzJ5g5ONvWlhqXtKWKZjcYuriPaM21N3dLdxG1dfQB+a2cTN3e4gP3G9hbWidLXN3Y3sUzMHSSTkC6R45NOnbiMBlEVceNv7SEnJ1psfOOtyG45oW6f3XEKtXtup7aR1XOsPlZ/L1aqBW647mK8obnMKLg/TZz7VmWfuq+61X2cIO/fRj6gni2rtX265LdojdjOicYeVgmov250fzDPr5PNXdzQ0t/3S9V9nG7yz8cT9X3KjVuv99XOmClmqoaTDe48nh457cy0Cyu1Pl3uvczY2NPNfdyozAQAhg7kzS3++GomShct1wqskZMPy7xfNxGpfUs1rmrdiWaGmzpckHqqWVFNcCvq1jJsNMthwmpD37dmNaPT9OqVTO3AaTU3IDJBSOv4mPuvgSIbhrRgYKawaXbYhBQNFHVqw38YmfuugSIGnEyZs4hrQMdso52BfMnYdw0UrRvr1UDRSm0anrRQZFr1GigqM7mpmQalgSIzYFmq6h7kJ40AWhMkmIHUOgFGJqRogjcThDRQxICTaMPYdw3omG2ub+kdj1sMENJA0a1GMKyFohvbk/QyDRTdaPRDA0UCQ6xOnZjMZ6SBoo2/NemLFooa33jr+N81UJTdcWr871ooygwbXANFFeM5wkKRSANFrcrkPtfcV13juaCFoobh6mqgyEzHZILp6wyI0EDRCeO6ZaBIpHl2nWxO7iUNFJnPXS0Uyfxl420qIMdMVdZCUddIkdRAkdmPMnCrgSKzjRaKTBDSgpGZ+qiBIjMdUwtF5jHVQJGZXcJCkUgDRWYMxRZnuKlTUYHRKSOI1EBR12ijhaKGBSgaKGoacb0WiqZ4Y45QNBcgcrlCMSgiYdDrDIU2s1TL6PE8LvAIQZELhGL75vo9BDyu3zQw6AKaEBS5fotB0RIJguuO9YWgiHWRRK685RAUuWAoBjiuMSqhZVyBSgyKTjoC51CQ4AugYoEF49gAbrgJAY/rt9g2Nxz7HoIi128aKLrFAUAhKLrVEQTHoMiEIVEIim50bD8ERS4YirlEp05cnoIhUQiKTBgSxaDIhCFRCIpMGBLFoChz5ASHoKjieNbdcN3FKBhVHKlfISgyYWjcr8C92HU8D2JQ1HCkuIagyFWwQxNMX+eAhxAUnXBcrzEouo583pkwJGKcIiAORb6xiCEoco3bjEFR1zFeLARFru3HzuNpB2iEoMj1G+sUiUJQ5BqHyThFQByKXMcyBEWuVHsNFLUccUYIilwxVAyKTjRnfw9B0SlHEMk4RcAQikJgZMOQiHGKgDgUOXljTlB0YCAKpci5oKiW+4HB5xLF0uRccBACIV+PQ1DigqKQK+Tbx9C5dm0/1KcQFGndHVEIlFzrWqr5YcjnErlgSOQCnxAM+Vyi65uD4CBOFxSFnCEf4IQG7LuWCQUoPihywVBIscDJF1j4wMQXuLHgE2rv27YLhkQu8AmBUgiKXDAkckGRC4ZEPihywVBILhgSMelzgB+KXCBkygVFLhgS+aDIBUMiFxS5YEjkgyIXDIlcUOSCIVM+KHLBUEguGBr3i0yH893bLhgSuZ45oTmuQsG0C4ZELihywdCkD+5noQuGJn2bXZ8LhkQ+KPI9a31QFCvMwhezcLd3wZDIFciHYcy3j/53kAt8QqB0U6vnBaMQ+Lh+CxWl8UGRr6z7za19JxiFwJJJnwPCUOSCIZELikIflH1Q5IKh8TYcUOSCIZEPirqB+NkFRT4YEvmgqOmJ7X0TxQZ5Yw5QdCAg0owXMqFI4wrZUKQdM2TCgcYVsrvCpqRpUuTs/WVdMU2fXFAUgyEbfjSpdOY6Na6QDUUhGBKZAKRxhmwo0lazMaFIkyZnAw5bQlmTwmK/qGMwZAcI2tQac7lTzZ2oS2MHbmxqnKa93YcQDIlMANKk0rmgKARDLoVgSGRDUQyGbJcoBEMiG4piqXI2FMVgSGRCUQiGRDYUhWBIZEJRCIZENhSFYEhkQlEMhkQ2FMVgyHaJQjA07pd1b7ncIVP2PR6CIRE7XtEVTIdgSGRCUQiGRDYUhWBo0rfJekMwJLKhKObGn27uTYGR9jlvw0msqqcNRSEYEjFjioZ9sKcFiF8HJgBpxxfZUKRJjTPbaCp02lCkmePKhCLNsbOhKFaIyYaiVqUIwpCIGVMEzEJRCIbG2yDHFdlQFIIhkQlFMRgS2VDkgyFTJhSpeOOAUFSqytyLTvxTqnjC3qCgYSADP0npoOBLXg/AwdBenx8v1BtwMLTTLzdmiK2mtrWf0QUU+mTFnK19HQyJLvQyOk3u0n5GTwi31c/oMUNb/ZyCoa1+Tgckl/arlDN0dq9OD74GgCpZSe78Xr3UGCBGD+80VTAkeminSRdQkMpzDAx98XJHBUOmvrzZoZyhs7sNFQyZurhbp8YNXdpuqGHI1O5ORQVEosGeDoamRBbj6b3/CyoYEp3/y1wNQ6buf2iZcoYe2OyoYMjU+b16FIZMPbpXV8GQqbN7taA7NNu+qgIhW+f2aiogEp3v1VQwZIp16u7fbqrHa4p6JSr8PbJbVU9xAAAP71ZVMGTqQi+nXKmze1UVDE1vo0IVXACA+7ZrdAGFR3cr1DxSX9mp0RP+XiQr453dy+k4aocfeoz7tjJquMEDW4UKhqa2sdkPukO2LvYKFQyZOrMzUAOR6PxuXwVDpjZ7A445+kWpSnOlHCI2J5Atqw3MTo6q0XKJuXlck36GxMIQwMMN2ycpOsDuPQMqAN8vALi5zT3wb27zT5fblPMpmCqTB30dOVHpTWQuOwDcTKZXMVXRRCvNXXRIULtliQuku2RqFwDcscINbP/qVb6IwBNOPYonnHqUWuZrr3+E3s5jN85S7W8vsS+3njhPtT99Y7nCAet3ktXOnnED1X7wtCdh8LVPpJapPedOqv3KV5eIWgCcPsUds5usiVs1uqHD3fM3EMVCRLcq57ES3d7htwEAt5PPozu6PKB3yOIM7DaWavtYL/H8+qol7jze5Jh4OqZb2twyt3f4d9ANZIVKALijwy9zZ5fr22NK7MsGmc1xA1FpEwBqGV/5FgBu73LL3LVCbwJ/a4UL2NhiDgBwskQFuo0SX/vXSOZgGUVUOmWOpcKMCNdbozrpzBwJQraB0uQzkmOmXYR1uSoZPz9AZv1/TGWLDsh1rL2eJxOp6rcnk8x1lMssj6ztZSI9YGP0Ra5JfDGVdIImUSpbJlTUzgUk6R1tYs4ZSaFpKpdZHkFNl4CbFUWqycx2RsFBS/mFWWCIgSJpq+2ftGP259TSJFhbVQaIG91hkHOCCHaWpG9KIJZ2deIr9tqoP5nya3l3fdinCjm7feem4bVYKLtW+zsjGOqVG3it0mjS7+oz71A1L/aHx6h7B7fvkjtx6oQOciqjZ9AGAR/t0T2lHRsmE8gyTqq4IytKkJB27Uq/1PNLO2+WpIsygCPHSbtMc+TWlXG3GSiSfdeeF5nrjXHtVkZtW8r3lrTXvk8AoDO6VjrEs0j2ZZlYRlImtduRfWDKvdfkflRCUXP0LO2ScwoCw/R9LRhJHHlCOQGtaKNRqCetlQnv15XT0cmHfsa1ktCRKc4g8XCHcHvEUNGaJG0y28DU4cy0NZIGilrkpFHAbM5jDIoalQkMaVUGhkL/7ZLdJLaIC4Y0l4wNQTEosp0hDRTZM4DHoMiGIA0UbVjpCRoosnOrNVBkzy4fgyJ7fI8mqGAHWS9bLwYNFNnwoHGJ7EAtBkU2BGmgyG4Tgxz7dw0UmTAkikGRwJBIA0VLdt8iUGT/roGiNasfMSgSGBJpoUhgSBSDojEMiRRQNHjakyb/rnGJqtMPoxgUCQyJtFBkJ5LHoKhiPXs0UNS27qUYFNWt54gm+LZTxWJQ5Pq9zPMrBkX22DkN4NjHJ7ZM00pd1EDRknVONFBk7zsDq4AOilasNjEosttroMiGEw2s2JN4a6DIHj8W247ddw0U1ez7MQJFTesZqoGimiMOiEGRHUdqoMhO4YtBUdcev03O0R0qmCWyQ0a2Yh2ggyI7u6xM5hijAwER6xIBfihqVXInDMVcIl/Oow+KfCAU2pODwlDs76Ht+/4ecoZC++KDH9/ffWlyISiyYUjkgyIf/ISgyIYhjXzVd0JQZMNQfBvuF2goqHDBUOgFZsOQKARFPmgIQZEvQPNBkQ9+QlDk+83XX/bvgBuGRD4osmFIFIIiG4bGffNAke/vISiyYUjkgyIbhkQxKLJhKKYZGBIFoMiEofHfQlBUdT+MtE6RKAZFvlG1PiiyYUgUgiIbhkS+e86GofE2AsG3b9yMD4pCsMQ+vwA/FPnKzYcAx3dcfMvYMCQKQZENQ6IQFPn2PXRebIgAwlBkw41I6xSJQu8UH5QwTpEoBEW+CoO+7fj6HIIiG4ZEPiiyYUgUgiIXDIl8UOSLI0NQ5BvP5IMiG4ZEISjyDQPxQZEvHI5BkSv+7VRzLxj5htqEoOgg7hAwB4doHlAUc4V8UBQbAGZDUcwVcq1tXjAU+j12BO3fNWlyrnWy6Z6xMUMuKPLBkE8xJ8j1ewiGmvnA6RTF5mdwQVEIhlwuUWyuH1dQEXKGXC8DHwyJbChaae5GHRQXFMW+VttQFHOCXL/HlmGdINfvIRgS2VDkgyGRC4p8MDTumwU/MefIBUU+GPLJB0OiSmPgBKMQDLlcIi8MiRxQ5IKh8W8uKPLA0PhnBxTZ7pApFxQVhR+GRNr0OZELinwwJLLvPR8MjbfhCL5jRQRs+NGk07HPL2AWimITErsAJ/YsspfxwZDIBUU+GBKtN/ZmwCi2767z4oKh8focffDBkMgFRaFlXO+UGPS4fq/ng+C+uKAoNgcVC18uKPLBkIgdU+SCohAMiWwoisWRLiiKFXewocgHQyIXFMXGxNtQFAshfVAUi4ttKIrVHXBB0UFhCJhTytxBoEibImdCUbeWqathCBRpU+TMtc4bhlzt2CPHjBky162BIbONtoCCCUUaGDJdIu1YIbOd1hlqTs3crs1TniyjcYZMKNLMqA5MBxWaNDnzBRaDIREzpkhkQpF2PINAkXaskNlOuww7Vshsp4EhkUBRDIZEJhTFYMiWdmyRCUUaGDJdohgMmTKhSOMMmVAUhSGRAUUhGBq3MaEoAkPjZgYUhWBIZEIRU2vVhCKfO2TKhKIYDInY+abM4FtbUU0gSDu2COCfX8AEimIwJDIBR3scZJkYDIlMKIrBkEvafTfPSwggxus1+hKDIZEJRZplzHeKFkLMdpr9AKahKAZDru1o0vxMKIrBkMiEIp87ZMqEIg0MidhiCyYUaSvdaccUiUwo0hYIEyjShsPLtWwKjLRxsUCRtgibCUXzgCGgZNntl9/4Wuffd/vcqg6rkhxRnXUs9viWSW1kikYAfFltUYMteV5iXxpkKVRtcQJTzMNI1CbLmpbZDhNQiGJffWfb8/uhCdZmliH3vVbpY0CWYj8MNUoEOWw5XwDY7ZWrZsOoQ1aj6qzy1asAoHmS2//613PV5ABg8MynUu3zj3+K3kbvvZ+n2l/6fLmX6ZmzHar9do8vUbqzz11fe/3FX48A//wC9AGriL0fq/kAu+Tx2ulHPqs7xL63AeASee7LvOm1oCIq8w4uU448L7EddnqPy+R5B4BNcpndQbn33A653B7/2sZun9vGboltbJaok7Op+DBlq0feYLknYP23X3k1ve25FVUYFNxcQ5WM3/FmNaMvlkoGkJwGANgnt8Nug32o1nNgh7zoAR6GKlmBnHwcdysDCiI6lYHqy4ypRl44J6EN9qs6oC/wRj6gHuDtah+9gtsKG0x0aj3Uchag+vQLr17pl4IoRpV8QG2jVhmgRsJgu9Gjg6lmo4caCVGVfIA2UYq9WhmgSu5Lo9bHPvHibnV6GPT450StO0B/W3/Mard1UDzAlQofPP0pwIDY/04Hg6c/jdpG8cA5VO9aV7ffvzBA6wQPz3u7FSwRZYAHRYZGifEYTWIMY55x7YHhPc8+j5rVPv0sblb71D3ZqPbpudJYZRnQIs9JLR+gQd7DlaygiuY0KgOqAioAtMjnfSMfoEq+H/pFRsNNLR/Q76FKVlBw1xvk9AfZAhn9sZTdBjC8J9uKCVtFlYyf3qSZ89WG2biwNwDqZL96BT9RapZxy9TyrJQZ4dNcgGhgmEwaKDJ3QAtF5kROewMdRZvbOU5QVAaGRAwUlYEhkRaKWDu5Y7TXQpH5INK+iM0J77SHwZzsUPPgbxvBhxaKysCQSAtFZb7emstogaU2Wkb7kjTXq9mGCUJaKDIBRRuANY1ltFBk9l8DRSYIaaGoYUxCqIGiVsdISyOgqNad9EcDRbXbJs6IFooGT3+K8R+K/e9MtqGFouKBc+N/10DR/oVJPxgo2tudnAsNFJkO6qKgyHwuaqHIvOe1zwxz3dpnsbmM5p5sGO21UCTtGsp9Nz8qs1AEQA1F5juVrSSqhaKW+exWPIvN95wWikzHRvu8Nx1BLRSZ7TRQZDpWWmAxZ2xcJBSZ94cGisx4VQtF5jCHRUFRzzhEGijqFcN/Jstww1u0y9SMAzwvKDowEA0cGXchKHJ1PAZFvlltQ1Dk2s5xgKKDwJBIA0UHgSFRDIrYAYcdR/sYFLFfZbrVgXP279jhYGd+bztevDEoOggMiWJQZG+jkhXRl5GrXzFgqVnLxF6SrvWxblQMilxgEgvAmo5lYlDk6ncIilwAFIOihmNG9hAUmTAkikFRrTuYgiFRCIpMGBLFoGgKhsZ/DOx/Z3YbMSgyYUgUgiIThkStE/tRMDJhSBSCIlc66byhyAUmMShy3fOx55NrnTEoYh0rF9DEoMj+PQZFrgybGBTV8sFMyl8MilzP3RgU2euMQVHL9ewmHZkYFLnS1/KsoN2iWL9cv4egyJW+F4sXXNPXLwKKXPdFCIpc8WoMilzjwucNRT3HoQlBUc+z+RjguO7J0DI1xwGeBxQdCIhcMCRyQVGowz4o8sGQyAVFoe0cJRTNA4ZEISiaBwyJfFDETl7mgiGRD4p8Dx7fS9gFQlPLef7ugyHfA98FQyIfFM0DhkQ+KAptw3eOg8t4josNQyLf8QqBj38b3N9DQFJmbJAPikL74upDCHx8v7lgSOSCIhcMiXxQ5AIhUy4ocsGQyAdFThga/+jogwOGJutyQ5ELhkQuKHLBkCkfFLlgSOSCotDYunlBUQhIfDBSxkFmgSy0jO9+DIGMD4p8f/etKzQ+1gdFobFPPigKvVN9UORblw+KXDAU277vXeeDothYHt8z33fMfP0KHS92bJQvbnDBkGieUBS6J11QFIpXfVAUKpI1LyhywZDIBUU+GJosw02R41vGBUOig0JRaSAKwZDIhCJNR20oisGQyIQizXbKQBErexvzhCGRC4rmCUMiG4piMGS7RCEYEtlQFPsKY98TMRgaL2f9d8wZsh/4IRgS2VA0TxgS2VCk2YZ9rlXLWMfHB0Mi+3hpXKDZbcTcqenfNSlrriDM5Q5NbceCIs2+MGOKgFkoCsGQyISiEAyJbCiKwZDIhKIQDIlsKArC0LiR0ZcADE3WOQ1FIRgSmVAUgyGRDUUhGBKZUKQpNFIGikxpUtZsKInd867f2ZQ9zTL2/ahJdbPhJ+Yc2evUFAuyoUhTCMIGGc071YaimNtkQ1EIhnz9iL3rbCjSFjawn/mxY2b3S3O8bCiKFXew44cQDInmAUWae5IZUwTMQpGmYvBBoSgEQyITimIwNFlm+gBp7klzmRAMiQ4CRaWASANDolrOdVCgSAtDppjtsFDEukTmNhYBQyITihYBQyKBIq0zJFCkgSGRQJE2TU7uDS0MjZcb/b82TU4e+BoYEgkULQKGRAJFzDbknFPLjI5TDIZEcryYlLjJNrTjl4btGAAxg7AYDI23M4IiZl+kT9qxQtJOA0MiptACMIEiLQyJmEILwASKVDAkGgxUMDRuPoIiDQyZ0sKQSKBIA0OmmKqLLBQJaDBFDWQZ7T0v7ZrVPl3UwdxeTHI/asf9ABMI0o4tknUzlVMFipiqeAI0zDtVoEg7HkmgSANDIumP9l0nUMRWeZNnvvaYSb+Y4yVQpK10J3GEBoZEZaEoz7h7UqBIG7MKFDFzSZaFIg0MidhCC8NlhjvN3JP1SqaCIVFZKJpblbl5iq0+B5QrVcguUwaKdvjsBFoF+DKdZVwythz1YZTWLnvhs9spUzp0t0SJUlZl+lVGbHH+MuV/9/uLP16DQY4BeV74iQm4l+NwG/yFXJDlXAcln0UZW5m4FZgWfV7qciWvsxIf2AB+CgK2imAZlSlzz1ZsK5NWB/DX/WEcrzLbqGT8Muy+A0CXBeJS+8I9wLZLlm7nIYrfxg7ZN7ZPAMAe4bJvYPZtp5x6c3oZciO7JW773RLxepnS9Yehkg6Rvu1Ov8Beib2/VIJwtomTKUCwSCgS0ma3wbRvGPbrjnK5yb7zxK2txS9dYWrws46arHmbDKTlBcEGFjvEdmQf2PknNon2/ZELtU8E+PKCYIBFQGVP6Urs7A8jaGbeld3eaJk9XfTdG/Vpa1e/jZ7R/61tXdC+N+oPA2s7e8M+acFL+rWj3HegxBxToy+Zuxe4e6W6RJZNvePUcHMf+6R6meLESRSNprp9/onh3ETZV91E9a22Qc5Rc2Z4PhpNspQ14Xjs7nO0uTW6T/aJ56q0ZZ93g6Jc4KJ9tmQl3Ah51mmfebJu5n7ZG93rzL6La8G4EbIPNRK+mG2Mt6U8xpdG1+Me+dFI9l8LLLIPzL5cHL1PtNfLVonzeHl/tIyyvcQ3/YL7yCyZPdqPbRJ3MtvYGm1DC0UXR0kTzPG6pM2VM7QzmpuoT1z2/QHXL3ZOVNEBxhDF2+wYnTpOUGQfq0VAkW07LgKKGo5c1BgUze47n5MZgyK7CxooYsdc2WvUQpH9tWwRUGT3fRFQ1LfGKWkCBPtFoglcbBCIQdGOFeBpoEhgaLxMBAx6Vp80UNRz9DsGRXtWPzRQJDCkld0vDRSZwd3WpXp8I1YKqhaKTBjav28z2l5gaLxZBRQVJ05O/l0BRQJD420qoKj/+UlqnRaKBIZEGija3pmcCw0UsTBkSwNFdpsy7tIioCgrMV7FfsbFnnn2OjVQtGfd45p9t1O4NEG+3ffjAEWXrOtRC0X2/segyO67Zl8uWu+R2PWyVeI8CgyNl4m0d8U1mjicnU/Sjjc129git3HRyiDXHC8ThrTDaHasiVo1UGS20fSrLAwBB64y5/9tx9Gp4wBFvmM1Tyjy5WDOE4pcMCTSOkWT7fBVO9hZm0NQxFbl860pBkW+1IF5QpGvz/OEIhuGRKEAwfcCCQUuPgDwQZENQ6IQFNkwNF7GAwY2DIlCUOSCoZhsGBKFoMgFQyGXyNevEBS5grogFHnG48WgyOUMhaDIhqHx5gNQZMLQ+G8BKLJhaLztABSZMCSKQZENQ6IQFJkwJApBURkY2nLcKyEo8v121FBkw5AoFOT6nm2+v/vWFYIiG4ZEoX33jWcJBfm+Ph8lFNkwJIpBkW//fVDk63NoX2wYismGIVHoPNowFFOZeAZww1CIJXxxZmgbLhgKuUQ2DIlCx8vlDMWgyIYhUQiKXL+F+nUQGALmMg/R7N9cMCQ6SiiKHat5QFFsQNo8oCgEQyIXFIX23wVFsfE5LigK7V6ZLyrs5bLdz51gFMujngcUxfo6DyjywZDIftn2iyz6Nc0VuMTcEBuKfDAkckGRD4Z88sGQyAVFMRhyuUQ+GBK5jk3IGXJBUaxfLigKBXNOKIoUJ9m9kDvBKJQm54IiHwyNu+GAIhcMjX9zQJEPhsZ9cECRC4ZELijaOVP1wpDIBUUuGBK5oGheMCRygU/MPTpqKPLJ9ayKOUGuZ15IrvvIB0MiV/pgbHC/K8iP7cthQJEtHwyJXFDUG+Tq4gaiWF9dv4dgyHWefTAkcl3DIRhynY0yGS9A2BlysUQsE8m1jZAz5IIiHwyJXMcrlCbngyIfDIlc4BMCJVe/DgpDwJyKKpidC8GQ6CigSHusDgJF2uocB4EiDQyJTCjS7L8JRdpiBSYUaXbLfJhoz4l5uWgf/yYUaQeVHgSKtJf0QaAoBkMiZkyRyAxctONlBIpiMCQyoUgDQ6ZLFIMhkQlFWmfIhKIYDInMY6RJkzOhSNsvE4o06T5TUETMvWRCkWbMkAlFMRgad8eAohAMjdsYUBSDoXFfDCgKwZDIhKIYCJkyoSgEQyITiuYNQyITgLTji44CinzukCkz0NU+y6SddnyJeT/FYMglLQyYQX6Z5zK7DY1MlygGQyITirT7brpE2j6a7TTOkHm+YzAkMq9hjTNkPnnLjIkGdGlyJktox6qb29CkyZlQFIMhkXm8NGOGBkUxBUYxGBKZAKRJpTP7NQ8YAuZYZW5Q6GBIdJhQxB6rMlDElCoss429AQdDop0Bt/97g4yu3LY7yKjKLDuDjD4ng0IPQ6Ltfk5X2CkDReylXAaKtDAk2h/kdIWdvX5l4ZXetns1yhna3quqYUi0tVuj0+S2thtqGBLt93NqzNBgkNP92tmrUgPCty7VKRgS7V7IqQIK+/dtqmFIlH/skyoYEhWNphqGRNlX3aSCIVFto0LBkKjR7KtgSFSv9hcGQ6L9QUYVWwAOF4o0MCTqF9nCAEJUyQc0DA0KPRCICnD7wrpEsg1G+0WmhiHRXglXaKdfoftWIKPS5PpFpoYh0aDg0uQG4GBI1C+4MUNFwVcz7hfcmKFaroch0aDgCygMikINQ6L+gCu2MCjmB0PAHIHocm+APbJjF/a46j17gwJnStSxvrhHnpSCq1i32wfIXUFvAGyS8/Jd8sw6H95ORt0svQK4uM+PD7pEPFy2+jkukIHh3iDDNjlQsABwiQ2M+zkuE8tc3q/gLDmQfm+Q48yuvjTx1n4VZ3e4UsYXd+u4QC5zea+Oi3vcMg9c5sofX9hp4NyOvqIYAJzdblHtL+02cHaLWwYAzm626fYXiWN8ebdOVd4Dhu7bmcv6fu33c1w8y+87Bhk279Xfw3mniv5//zK3jfVVVP77/9Bv4+MfR1HnjtfgA59BvqRf5tJny6UcnT/PHeOzmy0a7M/uNKgyw9v9Krb7XJDLljEGhs+jy2y6KxlIb/eq2CGf3dtkny7v1ekPTef36rhEbudSr4ot4jhf2q9SFU0BYGu/gk0CcM7u1ejqrBd7VVxgz3uRUe9TAHh4p0717VyvQgPR2b0KBSrnezldqAAALu1n1JjuS/tcvCbLMB/YH97hTYKLJarJXdwrKJMEALYZGgKwuT8oZa74NBcgutwz7Wdd57ZHGKyFInOnz+z01WAkhKqFIrP7DBQBeigy3aRFQlFvYNrJ8eXMa14LReZXEw0UmQ8uLRSZqXxaKDLPthaKzL5pHuJmGy0UmakHGijaMl5yWii6uKv/ci26vDdZRgtFZ0Zgc07ZLxPQtFAkfdFC0SXjmDJQJGCjhSKzHQNFgL4cuZmKqIEi092joMi4vzRQlHcm/VJD0frq+F81UJR//OPjf9dC0eADn5ksr4Ciw4QhkRaK2A8gJghpoUhgaIsIpM22WigSGDKfMSGZYKOFIjmu2qkBzL6wUARADUVmOw0Uma6NFoq2jH3WQJH5rtKCx0VjP7RQ1DPcRy0UPWy4rpq+nesZUylo7609I1VWEU+c703Wy8DKJfLDstleux12Gw/vTP5dyyoCQ+r2e8VUvK2FIoEhLRRtGlbavKDowEB02ZErFoOibcsTjEGRb2djUGTbdTEocnU7BkX2RFYxKHKl1i0CinoOe5cuxRi52VwWMuMUAXEochV7CEFRAfdEaTEocj1MQw9x128xKHINTg1BkStQiQVKNgxd2GlEnSJXoBKDojMW0MSgyNWHGBTZfYhB0SXHsdRAkQ00MShy/R6DosvWeYlBkWtcFuMUAQooGmRTMCQKQZEJQ6IoFBkwJApBkQlDohgUmTA0Xk8Aio4ChkQxKLLv8ZiL4wKgGBTZ69RAkatNDIpsZygGRS6XJwZF9vGMQZGrDzEoOr9Xx3lruRgUuX4PQZErhS0GRVuOfQ1BkesdFQOPi479uBBxi3qOVMwYFD1MpKAC0zAkikGRCUMamTA02Ub82WGDSswlcoFNbDv2MjGXyIQhUYxVbGco2t4TY8egyIagGBRtOvIK5wFFBwIiFwyJfFBkw5Dowl7fCUaxnfRBkS930XfCQufLB0W+WX19UBQaZzRPKHLBkMh3k/kcUR8UhfJpfVDke1j5oChUDpxNnxv2y72d0EOUtft9UBQqX+qColCA4oOikDPkg6JQgOKDIhuGRD4oCgGZD4p82/ZBkQuGxssEoMgHMj4oCsGSb102DIl8UBQqUuGDIt/YLy8URfLhmfQ5IABFDhgSuaDIBUMiHxS5YCiko4QhkQ+KfPe2D4pC4OP7zbeu0DMn9JsPinxpcr5nTijlzQdFvuPog6LQ884HRTYImfJBUQiWXFAUGs/jgyIXDIUU+mDngyIXDMXkgiGR733qgyFfv1wwJPK9z30w5HOJXDA02UYo/vHFTFz70HZ8y/igyAVDIl/s60uT87aPGA4uKNruD7zw4/u7C4ZEB4WihY5atKHIB0Om2HFFwCwUxQZy2ZaeRjYU+WBIZO+GpujCPKAoBEMi+yaLpYfaUKQZXGhDUezLjQ1FmgljbSjSnFEbijQ2u/0Qj0GS/eLRTHDHjCkCZgMnTZqcDSaaFBYbTHwwJLKhSDOOyYaimDtlQ1EIhsbLOKAo5urY8KNJp7PX6YMhkQ1Fmop9NhTFCmHMQJFycLANRS53yNQMFAVgSGRCUQiGRDYUxWDIdomOAwyJ7GA+5v7aIKNJjbPbxNwmF/ho3CMbimJjhuxnj2b8jw1FMafNhiLN886GohAMiWz4occYKY6vDUUxGLJdIk1Ktw0fGhiyXaIQDIns92fMGbL7FYIhkf1ejzlDNhSFYGiyDVeGTCyrhmvv2k5sGRuKQjDk0sVeER0zZLMNG08DutQ4u00Ihuah0kAUcodMCRRpYEgkUMTQnkARU9VCTqI2N1KgKAZDor0SxRYOo9ACMLnJtGPlBIqYSisCRdrcXoEiDQyJBIqY21GgiBmIKQ9xrWMkLyDtbN/ABIq0Of0SQDFjhthCC8AEUGIwJBIoYrYlUKQdvyRQpIGh8TIGFGnH/QgEMQUXZN0xGBIJFGnLlwMTKNJWBRxDEVkpSaAoBkOiMRQpYKisBIq0zpBA0XGCIZEE9doxQwI0TPEEaastoCDPn639KjW+SKBIW0BBAIUphiBQpB2LJVCkHb9kSgNDIoEgLQyJS8RUehMo0jpDAkVM0R+BD8YZEijSwJBI3qPaNDnplwaGRPJ+16bJCRRpYMjWpf1MPZ5HoKjMGCPtMgJFWhiSGJgpnjBehoAhcYmY4gnSVgtDB3GJSgHRQzt7VPsHdrfobdy/TWItgK9skrUEAZxhSoCgXLWN8yQ9n+MOLy71MlzqZSp3yNQju/MdU+TSV7Y5W/8rO7xF/wiZFwwA921z1auGy3Av1S9sctXUAOBvyKptnz6/TG/jwk6DDhA+c2GFaq8ttHCQbXzizBq9jU89uo5PPbpOLfOXj2zQ2/ncOW5fvniBP49fOrtKtb//fq696NIXyMk1P34f1b7y3/+Hyh2a2sb7/pJqXxaGHnpkiWp//8UuvY37yeqG92/zz5VHSAeadaxFZ8mCLg+XqAbJVus7Qx6vfpFTMCRiz8t9Jc7jQ+Q4my9t8dtg33MAcD/ZL4B/P35pi39ns2OG7ifjla2+HlJMfWWbW+beTX4bD21z7R8lY2EAOFtimQe2yQAXwFe2dqn2LKOISgHR75/7P7HZ56yM83094Gz2h2Dz6C53EADgzK6+X70RSZ7f1Z1Uab9LEOjWiIg3lc6VkD0DRVJIYLuvr4wnTtT5Pf2Ntrmf4RzR/uLIvWKWATjAuTx6OT5aAoqYh+X50Zep88ovVBdG7b5CvFzkS9uDSph4aNTuK+SL9aHdBvXylrZMUPXQTgMPEFD00GjdbFDxBaLQwP1G8HWvEjwfHC3zIBG4PTzaB+0yD8k2iMBYgPYrSpC6PDoX9z/IgdqAHatXHbbvv0c/f1DxV/cCf/EFfZ/+cAhPxYLTJwSGtPNmCQwxpawfGTmj2mXka/85Ys4s+RqvdSO2xy5UZfzvGjFuODBxOph52fb6FWwTroqse5eAqEfIcufA5Nhqj7GcR6aMtbTVVk19dI9rDwBnyLnYAGBzdGwf2dWfR6YtADy8O9yHi4R788huhSrydHZPHDjdM+/MboYzuxkVQ8lygH4uoEdHofM5IhyWtoUyVD03ioGZqXMuKOPmqe3sDXf6/J4+Tj+7yxkd5/Z6+P1z/ye1jOhAY4g0UHRmf4KpGigSGBJpoWjHsOA0UNSzoEYLRSINFG1ZF5cWikQaKHKtMQZFdlqe5obeNB4SGsC5aKXyaZa5bGxDA0WXrZecFoouGA9VDRTZEKSFIpEGiuwXYwyKHrJ+10LRQwbU3L/djAKI/bsGisy+aaDoIWudGii6z/jyqYGi+x1wooUikQZwHrb6HlvmIet3DRTZ7l4Mii5b50ALRSYMXfiU4tlVnb7HNVBU/NW9k/9QQJHA0Hh5zbjU/07mIWPWGYpBke0MaQLqR6wU1NgyduqTBorYojAuANJAkQlDmrQxO+1LA0V7Rj80UGSvMwZFj+w08Ihxr2ihyIagGBTZ51EDRez8P4/u2X2K74sJQxeVILFpHVMN6Jht7OVdEhga900BRY8Yy2igSGBIFIOiM1Z2zfk9HRjZy8X0qBUya6CIAadh++lnqAaKTBjaVxoEAkMiDRSZMHR+Lw5G9jZYHbioQgiKTBgSne/veMHIhiFRDIp2HPmIISiyYWjctwAUuZYJQZENQ6IQFLkqhISgKHQZsnMohW7mTcfD4dye3y2yYchcxqfLjm2EoMiGIdGje5UgGF1wPExDUOSDnxAUXXD8FoIi38tO6xRNthEGCRs8RD4A8f09BEU2qAFhKGL7BEzDkCgERS4YEoWgyAUzIcCxYUizjLN9AIrYVEcbhkQxKHI5Q0Eoqrrv7RAUTcGQKABFNgyN1xOAonnAkEjrFIlCAbUNQzH5xoGEoMgFQ6FgPQQ+od9czlCwyponOA9B0Z4L1AL74luXD4oe8dwnMShixgAB/vMYAh7XbyHAsWFIs4zLGQpB0WY/98JMCIpcv4WgyIahcd88UPTIbmUKhkQhKLJhKKYQ1ITiKNdyIZfIhiFRCHhcv4VcIhuGRCEocjlDMSjygYoPis7u9pzOUAiKDgpDwJyqzLmgyAVDppgUOsAPRS4YGvdhd59KoQPcUOQDKMANRT4YErmgKFRD3gVFGiZ3QVGoaIPrZnbBkCk2Hc7V3gVDojLjgwC3W+SCIZELimJOkOt3FwyJXFAU+/LngiIXdEy24Q60fOAhYlPVXFAU6pcLisr0yQVDIhcUhWBI5IKiEMS4fvPBUGgZ2x2aau+AohAMuVwiHwyJ7n9wxQlGoTQ5JxR5YEjkgiInDIkcUOSDofH6HFDEwtBDjyxFxwy5oCg0bsgVUIdgyNU+NijeBUUhZ8gVxGtcIFebUJqccx6eiFPhAhkXDI375NgXJgUP8MOQyAdFIRhy/RY7j653Qej94AIcHwyFlgmlybmgSOPquBQCJdc6fTDkX38MXl0fQwOltR1xicbhccVRoeVcUOSDIZELfEKg5IIiHwz5dGF3EEyT80ERCyqxFDkXFM0DhoA5lt02oSgGQyITinzukCkbikIwZMqEohDcjPtlnHRN+91BQY0rAqahKDahFsAXWhCZUKSpYGfezDEYEpmQ43OHfO1DMCR6ZK8yBUY+d8iWCUUhGBKxAzCBaSgKwZDIhCJtGoQJRSHomGxjEnA9tNuIgofIBBANIJlQpOkXM6bI1Y8QDIlMKNLAkMiEIo2jY7aJwZBrmRAMjdsbUKRxhrTjiWyZUKQZMzQFRREYEplQFIQhkQFFMRgar9eAojIwVEaaIgpmQK1xhsz22gphJhRp0uTMgJ0ZJ2S21YwZMqGInTcHCMPQuE/GvmhgyHSJYjAk2ulXps6Lxhky22jPo/lO0LwfTMCJwZBLmjFDJhRpYciEn0d2a6pUOnPdGhgyXaIYDIlMKNI4QyYUseluzHImFMVgyNa5XV2anAlFGhgyXSLteCEbijSgYrpE2vFCJhTNC4YAICsK7bCraX3b2s94f9spuA7WwD0oTzSGDzEtEImWa9x2OjX+BiDGpAEAajm3jbU6V2JaxFYiXK0XaiASVcjDVSuB460Kv/e1jFtmvd6nxwmxV8qNrT06L5zdRjU/+MzNGrHX1unmrhrSym7j9u4WBUSies49U3Ly2gL489itccH9jSsXo+6QS9efvEi1X7mbv4HzGzhoG9zP9QkALn6cO4dlYKhR26cryrHOBTMtgKhG3vPVEtdvq9KnCyhUyO0s1XoqGDK1T5R9BoCL5PkQMeWlAd3cgKZWavv0u2GX3MZStU8XUGDf72XFxh38vg/oNDl2CAIwjKFYiCoxDSet85ov8Ia2ybHv1VyKaXEcMCBRJNS6bFGF0kAEuKHokeICAGAJuopJmxji8Cr0A5x7GF41a1V9mo+Q63pD/xDoF8BynZgTZ3Th1JVPDpnLaa1BVPIZEdeplr5f50fu0jLx/L/YAzaImEq2wSxTdhunW/pLVtyoUw39Q+DM6GF5UrnMo7tcewA418txc0sf6N63PbxumWUe3K3gJqI9ADwwKnt+uqlb7qFR+5MN/XYe2a3iOuX6AeD+0b5fTyxzdq+i3geROHwnG7oH+YM7wxvqhpbevn1kVJb4VEO3zPlRYHRTW//Z8FKvipu6m+r2ALA/CnBvuu68epneXgUnnqq/F3sPDve58eQTqva7/+NRAEDtev24qUf+NEOjqY8qvnj/sHR7i4TOey910anqlxEHtV3RPSPki3qnqt+Xi6Prd0N5L14atV+rc/u+1a9gidh3caxWiGO8N8ipbYhzVVN+0HiQPB+ic70KulXiOT/KOmCWudDLsVLTtxd3ZFm5jLRntiEZFut1/TLnR9kiqzX9M+LBnRxLVX37s6P3u3KaNADDuXnWiKGYj47cF2YbZ3aH+7BKxI+P7gyXWVZ+iJcso47SpQeG08Yw4CHbYPDxkb3hu6qZ6w/Y2cHwfbWa6bjhQjHcxnI2ywBlYQiYY8ocMIEhALgEbu6h89C9wAWGAODc/g7O7ccDBdPGO6scU8ROOmVSNFO6EADOKWd6Ndf78DbPsdoyj9LuzO7wn5jOG7Gdpr29DY3MbTxA1vAHgId3dZf6mT3Tho8v8+gu1x4YwhAAfHlb98C4z2inXebB0Uvvvu3q1PIhPWDMAfWAYj6oh4w2j+zqtiHtHlLON3W/0fcHlctI6qNmH0RmuiNbEvZ+ZWn1R4w5Wh5WzNdy3vhKrEkXBCYpSvcRFfT2ja/99z20qlqmNzrGj35Edy8KDAET0AnJbGMuG9Ijfzrsy+6O7gOTwBDATQ5676WhM7SpHFBvppNqXJ+pKlzKNLOLpKN9yWjPlPBmJxQ10/e0roe4T2yZcEA3KeyD5PkAhiAkk4JeVlZgO2emeSuXEfDQpHgD06libPU17Ta07UydN1Lnzysnj39wR867rv3ZqfT+ePuHdyYTlWqHIDxKVmwDJjAE6OegFBjSyhxyoa1eLHNo5hkHXACgweBH9nbGMAQAOwNdrC0wpJXAEABcLMj8wojmCkS2YlAk7pAoBkUmDJnSQJGpGBTZPHNxr6Bm4wXiUCTukCgGRa71aaDovHXjx6DI9bsWWrTt7W3E2tv7AOigyC7gEIOiMw4bXQs52vbnrJdLDHBcMBNb5kFHPnUMilzwwAAFEIci+/cYFN3v6HMMiuxxYJp9cI39ikGRuEOiGBQ9Qk5Yed4RPMagyB7EHoOi/UE+BUPj5SJQ1LOOcQyKXEATgiLXbzEoEhgaryMCRSYMibZ71SgYCQyJYlDkGlvHpsLFoMiGoTOR+/CS43rXQNGWlcIWAxbXWKYYFNmpeLFtMOOfAHeRmtj5OOc4XjHAOecYjxpbxgaPGIhox82E2se2Yf+uSTVzAVAMigSGRDEoOksWc3rYESLGoMiGIQ10mTAkikGRDUMCLj6x07dc7BUz64xBEbsNE4RMxaDIhqHzRZgZLswZgGzNDYhMd8iUD4psGBKdx6baLTLlgyJf5QsfFIU4xgdFvhxLHxTZMCQ6t9tXu0WiEBS5QALwQ1EIlnzQ4tuGr71vG1o3ylQIinzV73xQ5IIhkQ9yHvX83dfehiHRl7eraufHXMYlFwyJfFAUggbfbz6Y8UGR7+9ap8iUD4p8RTFC+xcqhOGDIhuGRD4o8sGQxiWy9f9v782jpbvKOv/vOVV3fOe8mYA3CQSUmWUwDCKJhKRJJAxJELCVabUsgZ8ZRCYVNGCDNNIMQRbTSgekYwCFXglokDnEoAToJKIEaDXJm/Gd7lxzneH3R91dtWvXHp7n3Kp76977fFx0v7m165xT0zn7c77P3tslRa5pjl1SZBOhvuc5pMiUIYVLiqjpDgXXtkwZUrikyCZDOi4pMmVI4ZIiykQjJq7vnEuKXMmQS4psMqTwSZEpQ93tOV47d/0jwD1Jg2sfLhlypUS+ZQxcUmSTIYVLcGwy5GOpHTvFxPV3lwz5pqP27Z/zd58UUdMgxaFGPCBDCpcUuWTIJSw2GVK4pMiVDLn2MdfMrTLk41gjdyZDLilyiYrr7z65ckmRa1uulMglQz7ms6ozGXJJkUuGhpkSrUmIVK2eS4YU3PI5YDAtcqVDOqYUheZGp5bP6ZhSFBpwZkqRS4Z0TCkKpU1H6vmAGLlERUEtn9MxhSW0D7M9ZZ/cfZhS5FsfSUEtn9MxJcclQ672LhnSMSUnlOqY7X0yRN2mDVMoQhJjyk8oOTrcKA9s05YO6ZhSFJoh0CZFlFkBzQ6qS4YUphSFkiGbFNnSIR1TikILYZpSFJKh7vMMKXLJkMKUopAM2ZKgUDmduU2XDHW3Z0hRSIYUphS5ZEhhSlFIhmwd8FAqaUpRqEzOlCKfDClsUuSSoe52jdcekiEzJWplcXCSBnMfoWTIlCLumm6AX4YUphSFZMhsTylHM9uEkiFTirhJEuW45lvxgBiFZMh83CVCOqYUhZIhU1h8MuQiVCZn7oMiQmZKRCmRM2UmlNqYj4eSJso2TMzeK0WGzJSIWyIHhJMhJUVrGT8EDCEhCsmQYgW1rhi50iETJUUUGVIUKZ9TYkQd+qOkiDr7BndMEdCTIs5zlRSFJEKx3O5JClWQlLBQ98FNfYrsQ0kRZ00kXYp86ZCOkpyQDJntOSjJoYqLak+RIYW+bWpZnGpHTXSUBFHHFunbDsmQQkkRdbp0bgmgQnVUQzKkUFJELZPTpSgkQwolRSEZ6rZnjCnqe96qFIVkSKGkiJoM6QJEGVukbzskQ93trkoRVYZMQjKkUFJETYZ0KaKOW1NSRB0zpKSIIkMmtbQUlCGFEhZqMqSkiDNbndoHtUxOSRFVhvTPgyJDCiU51GRItS8yNocqN0qKqO31Y+Ecl5IiajKk2lFkaHBf1LEvnf+fKkMqJTrWpI8ZUvvgpEJKirjjhTr7oz1HtaPKkEqJqkk+tDI5G0qKqDKkUqKlvEEukxtGUrSmWeYA4Ol7f4/VfiVewJ5sP7l9GiXYnfOmNwWAXTHvjlCSZ9g/xSth4U4bvdhKMVumP6mWZDhhmt+Jo85yp1hsZtg7xbgwtXjtAf57dbSe4eRZ3pOmC6zherSR42TGjH0LTeA45s1GxkcOADhSB05izBj9UB04dQf/Z8ydRnWhFWH/5Gin8j7ajHAcYx9HmxEeMcObKQoAZpnTtx9rxdjHmJXpcLOEAzO88lfulN/zrRIetYN3x+HkWdoacTq1dhmPOnGB3H6lOoUDj+dPl83hvjv3YNcO+gXw/x3ej10T/Ficsm6QzrHmBKaZM5dRJ05QLLZj7GLMWraSxNg/yfsuThVY3mClHWP3BH0/9bSE4yZ5nwl3mvBDjUn2VOTcaZyBzmeyg/GecT9DAGgxj+tQI2LNprbc5s1Eq+AuPTDfjDDL7NYQCmv6ONbIMcOYfe1YI8M+Zp+mUeBG93wjxe5J+u99uZWyZiEG+Eu/zDcTTMS81z5XoEzuaLSAHTltFjkAqEQr2JUPLhzu4x8XP8g9rD7WnBC1ogZaEe3NWYk7F9WleI61j+WowmqfIcdS1sBSxvvQ5pr0evd6kmGZMZ/74uoE8zXLiuo+jjZ4ZX3VJGONQ1KL0C4yVy3mtF9sZjha7/yPgmp3qEbfx5F6hnsr3Pe2c+Y4xJyxb57RBz3cAB5gVIweWe2vHmb2W++tcgeZRqzZ+lT6NsdI4eZaEav90dU1G6h3AlX7B+qcu8wxVpIYhxmJ2rHVu6CUsked++v0fcy3YvIsep32nW3fXaXbeS0t4S5i2tF9DnM9lJXV47n/p/T1hubvmsH8XfQ7APfduWd1XzxZ4a4DdLC6g5yQAB0ZAoAGY9KEuVYZDUZHd5H5HVQLUc4xxrU0sphUTtq3n9XjoiZXKuWhLlgKAM0sRpXxeRxqdGyAsw7QsVapb/FOCtzPRLXn7Ge+FZMWMVccanDXZOr//6kstjqCQ0W1rRG7NWpsMee4uAnMsUan30BZrFTxUC1ltQc6MsRhebXPyOnP1ZIcTYYRcYeNHGnVcKRVQ0qad67H0Yh+Qw3oyBAArETECrRoidzWx5qF6I6F/wUAZClSUKQojXofFleKuvshSFGS9z5cihTVNalZbvHECKBJkd6GKkVV7TlFJmigSM6K9lop7c02VClSUKToiLbNeys0MTpqnDQpUqSvBk2RosPaV48iRUcMCaJI0UNaG6oUHdEulg/VeWIE0KRIb0Npf9S4qHJnEaJIkdkBoUjRMaOckiJF+nYpUqTX4lOkyCwRpEiR3rGnSpEuQ3cfCZebrRjHQZEiXYQoUqRkqLfPsBT9v8O9igSqFB2s9koMKVJ0zCh5o0iRvjAmRYr0jjelM222oUhRQythW2qXSGK0whQCs+SNIkVN7bgoUqRkiMqxVgnHtPeHKiv6Z1JNeZ8hdT/6+YEiRboMUaaXNmWDIh+Lrf6SdooUccQJKDYGWZchypAGJUNUHqqleKimLf1ClCJdhpYJq69S2ujUkhw17fVSpEiXoXZG6Ge1+HMBAP0yVI3C21AyREWJkHKRtTDUabd9UqTSIR2fFOkypFiOKkExyizr1/qkSJchBScp6h6bR4oWLV9unxTZHuMmRQqfFNmExic5K5bXyE2WAL8U2R7zSdERx7aoYtS3H48ULVgEyCdFhy1fuQdqvLQI8EvRQ5bHQlJ0xHHnkDtjn09ybI/52psypPBJke05PilydTx8UmTKkMInRbbt+aTINmMTJylS+KTI1qEPSZEtGaJIkYlPimwC5JMiU4Yo6DKkCEmRLkMKnxSZMkRhzjJ5gU+KbCmErzPteswnRQ3HeB6fFNlkyJcSucb/+KSoaTkunxTZZMiXEh1zvCchWbF9Jj4p4iZJtokLAL8U2ZIhnxQVSYRcY3t9wmN7zJcSFRl7bEuGfFJkkyGf4OgixMGWDPmEx/aYrx9XY479AezJkE+KbDIUSomORgvWZMgnRTYZ8iU/w0iFdIYqRECxpKhICZ1NjGwy1N1PgfI5mxjVPSJjkyKbDCmKlM/ZxKiaZH3pkIntx+QTmSLlc1y5somPT5Q45XM6Niky06G+/VikyCZDCk75nMImRWY6pGOTIpsMKbjlc71t2i6mwxMfTvmcwiZFLoEC7FIU6thwyucUNinybccmRb7pa7lTiwN2KfJ15O9a2WkVI1+ZnEuKzHRIxyZFPvGxPeaTIVdKZJOh7nMsUnSwusMqQwrbe+mTIVdKZJOh7nMsHXdfR9r23eaWfHX2G1qPZvC1+5IhmxRx1wwC7DKksEmRLxmySZFLhkL4PhObFHE/Q8p6Pya+MjmbFPlkyPYYdZIjE58o2aTIJ0O24/JNX+3ClwzZpMgnQy6Jmm+khcvk7Pux3Vh3v25bSqRPIkbFlwzZpMglQj4q0UrhZGiYDEWIzKjKlCJbOmSiS5EtHbLBLaMzpciWDpnoUuSToe4xrbF8jiJJuhT5REhnreVztnTI9xyKVOkCRCmlM6XIlQ6Z6FLkk6HufjQp8smQwpQiWzpkokuRT4a629Ta+GRIYZMiVzqko0sRZdY+bmmc2cYnNwpdiijtdSmidg5NmXGlQzq6FFGkSpciSoeHO7U40C9F1PEvuhRRxgyZUuSTIYUuRZTSOL0NJRkypcgnQ93naFLkEyEd/T2lJEOmFPlkqPscreNOSRX07zjl+26mRCEZUuhSRCmT06WIIkNmSuSTIYUuRZQyOV2KKDJkez8pn4kuRdzPkHJuMFMiypghXYooyZDehipDpvxQyuR0KaIkQ/pxUUTITImKlMmFWGhmfWJEESFTfoqUyYXQpYgiQmZKxC2To4qQnhJRRMiUH/O/h1EuBwxhljnFL+37HevfmxFvdPiebD9ZiBS7853edMjGjohXY7x/apIkRN1jmoy96dAw4MxYp9g3VWInQNzZyLicMBOzxxbFBY6JM+sMAJw8E5GESHHcFE2GdCaYr+OkGZoQKdTscxQZ0uHO2Ld/MmclQPsnc5Lc6HBnz3nETMa+W37SVEqSIR3u7E8HZlLWHeCTpxPy1OKKk6b5JbYnT/O+vI86cYEkQzqzU7wanSpzLMiuHQ2SDOnMt/gL5NaY36vpUkaSoW77OGeXWHHZP5mSZUixZyJljxnizjB63GSbJEOKHaWUPWZoifn5qRnhOJ/JjhL/M+TOpraznLMmUNg3yS+TCyznOBRmy/wyOe5yJtxppfdNxYXK5IbUpXayb6rEKpObKkXsVIi7fE0JMTsV2pHPslMhF8MSotGecQGkYH4Q8VH2PpajCioRb7En6tzmisMNXvv7aw1UEt6Zp57yfnxzTf40sgdXeLl3NUmx3GbGvsz2/7HEex3Hmm0cafBf+2Hmye3/LfGuTj9b4k9kwT3h3rnIO6Y7Fzv/45YUcC9Od1d4UvCfzPYLLf6F/O4q//T27xWeeBxuRKSByzr/usTbx78u8cao1NIId1f541ruqdKnRAWAf3ngRFb7+doM7l+gzz53/8JuLNR5M8nd8cBJrPb31Rjz269yuFFmi/aDxDWsuvtglnFWkog1CxkAPFhgrBp1jTDFSmIfB+Pj/jpPbu6r86Sc+94utiLcVyvhvhrvefczZr8EaBMg6BxrAvcwy6PvrfKuAwuMdXa6z2nlWGjxnnf3Cu+6NsdMeRaaGVug/mOZXw+/0OI951ib16+sJAnuq/L28WCN1/5wwutLH46P4MH4EOs5AHAkfpDVvh0VrNlkMHIhEgRBEARBEARBGFeGJkS2yKq2GodRU6JsdYDWcrSAZWb8BoCcEiWr+6GmRGqs0XLCN1RqSqTSIWpKpNpxUiJVo7rUSrDU4iV31NRHtaO2X+oeU9r9NxVOSqTGdlFTouXVO1xHmXeiAPp4rWP1TjtqSjTX5K2XUGmbtdPU1a7V/kjNsdzq//9DqHp0buLDeY4a8kZdeVzfNmXsFNBJhxTUu7uq3QPEqc65ay3VtLELnJRIjXWhpkTLq+Nv7lqkzfw2XyCJUVBTov9cPZZaQksxVDrEWRj1sJaqUFOi+dWxNNQFP5dWy6yo7fVkiJoSqW1z0pvq6rapr7vI5A7q+3u0SfsM51fLENs58Te7mg41CFNkA510SGelTXueOodUiJdZdV6gtuec1xQrq9eDRWJ6o9KhJUbaw02GDtczHF4tl6eOv1bp0Eqb+jqY6VOz3e1XVRPaB7LQanbTocU27WKg0iFqSlQhHouOGgPfIPYrVTrUArF9fIR9TNVoEdVoEUDPEUKodMiWEg2rXA5Yx4QoRcIunxuFFCXGrBjc0rnlpBUUI/PxkBSZElSkdE7/EVMJSVE1MQb9BSTHfJxbOtc5Jv9zjhmvkSJF5ok2JEXLxkn9aCMLitERYxBlSIqUDClCUjRnnNS5J/nufgNSVDW+EiEpMiUoJEXm4NzldlhyTNkItTevq5TOg7lNqhT1P4f3eEiKzDFWISmqWTp5FCkyB/6HpGjZmKEtJEWmDFHK5sw2ISn6T+MYQlJklspRpOiwpcQs1OmfN2ZbC0nOkjHmJNSeWyZn2yZFiqrGfkKv23w8tI9aGg18f0NSNG+MyQpJkVkqF5IiU4aomOeOkOSY54VQe/N8Fhq/v9LOB+QhJEVmqRxFikwZCsnRYea4YWCwVC4kReZ1MlQ2x+1D6SLEwZSgkBSZMhRaGsY1S7IPs1QuJEWmDLWj8PugRIhKO2qtS6mcYmRC5DI/lxRljjnNR5kUKZbyhlOMXDPRuaTI9fdhjifyPeb6QbtmMHFJkSlD3e0UGE/keo5Lflx/N2VIsR7jiQB3WmTKkMIlRaYMKbjjiXxSZKZDfft3SJEpQwqXFLnkh5oU9T3H8RG6JMPV3nWTscgdVZ8UHXYMZHYdr+vvLilyTThBTYooNNLYOTW0S4pMGVK4pMiVDPmkyPWYS4pMGVK4pMg1bqialFhpUQhThhQuyTFlKNTeJUM+SaKmTjqmDClcUuT6u0uKbCIfwpQhhUuKXOOGXFLkkyFfSsS9keI6L7ikyHUec0kRNUXpO6aC44Y4f3fJkCslmmtkhcYN2XBJkavv5EqJfCLkS4mKjBuy4RIe199dKdHhpFpo3JANnxS5ZMjlCi4RGqUgDVWIVHQVisHWKykyxchMh0xMKQpNy80tobNJUUh8iqRH5g87NJ3jMMrnuOlRKAkaVvmcL4Y/XEsHxMhMh0xMKXLJkGIYkyyY6VD/9rOBE79PhhSmFLlkqHcMwU32YZOi0NStgykNr32o4sLVmfAlTrYOjkuGes/x/7eJKUWh2fdsUuTrVNpSIpcI6ZhS5JIhBbV8TmETH86kC4BbhhSmFFEmUbBJkS0dUljXkfEsTgoMiolLhlztQ8mQ7XGfDNlkpZpEThlSmK89mJgZ+wnJkC0lcsmQi9AkCqYUUZIhU4oWWpFXhmyCU2QSBR/mpSgkQ2ZKtNDMvTLkSomKlMn5MK/ZIRGyvc4iZXI+TCmipEKmFB1rN7wyZHuMWyYXSoVMKQqJkJkSHY6PFC6T4xCSHvX4MMvlgA2cVEGXIlc6pDPqcUWKIiV0tn87jydpd8WIO16Iw1rK51zpkI6e/HDHF9GPqdfelQ7pmFJErUlWUhSSIQV3XJEuRa50SEeXIp8M9e+j044iQ91jWcPMc5QUSG9DXceiN46H157KsWZ/x4LyfL2jE5Kh3nP6//8Q1DFFvfa9UzflDrsuRRQZUigpCsmQQpciyrghXYAoMqSnRCEZUigp4swop0uRT4YUfevIBGTIJCRDCiU01DI5vR0lGdJlJSRCNshjqlb3Q02GdCmiyJCeEhWZUY6KkiJqKqRLEeW8oLfnJtzUZEhJETUVMqWIIkN6G26ZHDUVUq/XdoPQhp4SFSmT40JNhVS7SpKQZEgXoLWWyAXbE0WoHTW7SZE+XsiHHqKsZ4mcydDWIVL84nEv4x8E08t25/bV0n1M57xBvTvAX5uCSykavY9OMPdRyVrYW+ZNY8qF+41rExbQNVnKGjipTFtsUTHDXNcpZ659lTJfxkqSYP8Ub7reiQILNHHXZ+KunVRktBN3zSHuukkAMMn8+THXXC4E95j2TfLeqIdN82+uVJIYp87yOgF7J0d7UZtv8s5Rd1WnsGeC/wFyx+hQB/crqIP7u9sv8B3krgM0FY9+4ZnpEn8f3PXwuNN9E9bSHIC5tA3mGjl2T3K/I7x9tJkLB3Gvx8vtDDu5Xyrw1w3iftcT5utebLdRinifRSvjf0lClUkm0xF/Onwu3Bv/C/Ecex8t8NYgnQC/3/mT+f/Nfo6PoffI/9/837DaZ0iRgm7oMWJUoiVUjJVqQ5gr24ZYRBWLoBt0BQ1UQP+SVdHCMuNLuZw3WO0VC1kdCxnvi7mY0Ds/euJFYTlpYSVlroWUFetcce6A1NKEdYdlqZWwVpaea7ax2OaPdeLOIjjX4EXstSTDHOOKu9LKMM8sR6i0c1ZyVWnnA6uL+2gkORaZde+1JCfPtgR07qBWmfX4i03eca20c8wx2i+3gYOMdUjqaYS7qsUutvfW6Ber+dYE7qrQb0Ycqs/gUJ1+w+pgdRYrjLE+dzEXj1UcbsaoMoRlsR2zkpWVdsTq9FUTvpQ3M/rMZUCn871EnElNsZJEWOG87iTC0Sa968HdPgAcbsSs93axxReP5TZQY7y3c8xEXj2Hc95ZaGasc+1ya3DCBW/7IkYOYJ755s41Eyy36W/uXLOFJcb1lXstns+qmM94iQoAzEVLWGIsPlpDE/M5fT++8e82juUrOJbzFkOdZ64NWsEcKphDCzXyc1K00UCF3L6N5tBlCBijdYg4UqSgilEbnY7uSrREEqO2diwUKdJFiCNFANiSwxGjSt4TG4oUVTTxoEiRLkLcSSOoUrSYdl5rNWuRxGgpa2Ap670/FCmqpb0TLzd25kgR0DkRU07GK4l+TJSZ9LQyO6IU1ZLexY0jRQDIUrSsXWwpF2q9DUWKGlobinzUkrxvlW+OFAEgd070Y6Ecl94poUiRXupHkaK61rHnSFGFOXXyfKuXaFKkSBchihQd1MY1caQIoJemAR0ZUlCkaLHNKzfTx6BQ+pj6GD+qFHEnotRPAVQp0kWFIi16G4oU6e0Xicd0uMH7zurlvNTToP77o0iRLkOU0uy5Rs4WKO64Gf04KFKky1ClnaFC+OLON9KuDFHaAx0Z4qBfsylSpF9/U0I8posQtX83Fy1hjnkTvgZeCq+LEEWKdBFqE/rb8/HRrgzlhJRLiRAXbt+/zXyfOIxEiKgpUWYM2ErR9r45seNwfVKkZEinSFrEIfSjqRrHFJIc22MhKdJlSDHKpAgIS5E5xmol9adFSoZ0fFKki5AOt1Y2JEXmJBQhKbIJjU+KViy1wz4psu2fmxR1nuN/HStGTywkRcuWi6xPimyP+aSoYXmMmxQB/CloQ1JkOwbfcdk6Iz4pso174iRFAE2KTBkKpUS6DHX345EimwD5pOigZea7kBSZ6RBFig4z0gugX4YUPimyzVLm6yvaJjwJSZH50wylREXKxWwC5JMi22M+KbK1D0mRKUOhPjh1bKOO7ffnkyKb2PikyNY+dM7hTqxDHS/bbe94I32SY0uFfO3nmsmADIVSIu4NzCLJkEmof2cTIV9KVENzQIZCKRG35G0YqZBPilwi5EuJbP39UEqkZIhbiUZlbBIinaJpEQeXFLnM2VVC5/pxcEvogGJpEReXFFUcouGSIpf8uErofBNOrEcJnUuK9HRIx3Widc3It9xK7WLiERnuyZk7+NMnRXo61P8ce8/IlCHFfNNeQmeTIYXtYu27gHPK5wC3fNQ823FJkWuwsauD4hMf22O+O7Oc8jnALUV1R8JxV7XsFCNXMuSSIpsMdfdjkSKf+Nges8mQwiVFrlI5lxQdbsZOGXKlRDYZ8uGbstnWV/TN/uiSItd9CpcUuWRoqR05kyJuCZuvvU2KfO1tUnS4ETuTIVcf3CVDPjnkTuLCTXl87W3nHN8kAq5zqkuGXOeiImVyRUrkXNikyLfOjislcl1vXSlR0RI5DkVSIZcM2f7uK5Fz9XWLlMhxKZIKjTIZUoxMiEIGZ6ZDJuYb5kqHdMwSOls6pEMtodNZa1pkpkMmpuSEpMf2uC0d0jHHFblkSLGYNIeeFpmYUmRLh3RMKXKlQzqmFLlkSGGedCnTkxcpodOxpUP9x8SbUn2ukQyIkUuGes/p36ZLhnSKjCviYEqRLR3SMeXDJ0Pd51imofVhdlAo6RQ3wTKlKNQhM6XIJUM6phSFyuRMKfLJkA1KaRxnTBEwKEWhcUOmFFFSIVOKQjI0sJgpc2xOaCp8YFCKQj9DU4oo/VZTikIyZD4+THmyQSmRM/v0oWTIfF8oC0ibKVFIhkwxGUWJnH6eXW7lwWTIlCKKDJmpT0iGzPZrKZGjQClT16WIMl7I7NdRSuTMlCgkQ2ZKtB6pUEiG9JSIWiJnpkQhGTJTIlOERpUOAWOaEClCJXQuiqZFlLpKoCdF1ARItQvJkKLouCLu84qW0FFlR7WjrtekpCgkQ4qiSdGwS+hMlKRQEx11sg7JUO942n37IT1nVYpCMtRrnxYeV+RLh3TUxZoqR0qKQjKkUPJBkaHuc5jT0HInWtCPizqYWUkR9e60kiKKDCmUFFHHDCkposqQSok4oqPa+tIhHSVF1EkUlBRxSuSUFFGTISVFVBlSfUWKDJlQ70koKeL8vJUUUWVFtaO2VykRtb1KiYqMF6KWyan3h5MKKSmiyo0SFGp7db5Zy3ghUvt2NtJkSEkRVYZUSkS9FquUaBglcj6KjBUC6MmQkiKqDKl2VBlSfd71SoU4/fn1SoV0hj7ttoltGu42GiiBOZ1wgSn5pphTbU/ntAuvogzeoN5KtIJdOW3tjE77CnbmO5n7qGB3vovRvop9OX0xxBqa2A3e+5pxp6dmTlO5HFUwy/zsmmjh+Ij+PtXzNnbF9O/gQlbHzojevpI3sSeeDjfU4E6pDvCnFq8nGfZM0r/nlXaGvVP09sutFLsZ219upazjqSYZ9k3x3yf21PDMvkOlnWEP47iWmhmOn6G/7nqS47SdvDvttQR45A76C1lsxzgww+u5z5Z4bxRl/Rydg7UJzDKmdH6wHuG4KW5qF2E34/K12AKrfSXhT7/OvYgzZ9oHANRTYAdjksJaAswy23M+i/lmxDqehdb6TLXPLfGda2bYzZjGeqmVss7j1XbGar/cTrBrgte3mW+2sbPMm8GymfHe3Daz/WJew56I3i84mi9hktEvXYwXMMPsdyxHC9ifnURuX4sqrD4jQL+xr1iJF1ntq1hgtQeAPM9QZvSHUrQxicH3dpTpELChC7OOdmaJDBnqURV14sKszaiOpXgOS8T51htRDZVoBRXilIqqHbdErxLRpyJULDOmeQSAhWiZt33G/PJVtFBHG3Xi572MGqpooEpM35ZX359aRJ/isbma1HEj5ZWMWTYYKF00oZT9KVpZimrK+w3VsgRzrRbmWrS7bPXVNGmJmESpu36LTVp7lXBxywypx6MocjeVOxVtnbHIlHqflojHpdpRFvUFeh2ygxX6a1B3tu+p8i4J99fpnaBjrRLurdM7HEeaZSwxFjk9WOPdZHtwdTHc+SbdDuZW21JTA5VGUNur9IbTEa+nvLSnnXWew4HbnjMdtd6e+lmodtQkTS2ESn1fF1o5Flo5qky5OdbIWM+hLryt4J77qsw7NSqJWWEsoj6/WrFAWUgU6Cw+eqzdII8dXk6bWE6bqOeMabVzen8A6MgQh8WYLwXLEe85tdW+DbXPuBDPYSGeQyWm9eeOxQ/iWPwgmsTpsWtYQg1L7HVDc+Y6kkWqwobFugtRW+vorleERpUiBVWKFFQpUlC+4LoIUaVIb0eRoor2vixEy0Ex0mPeZdSDYmSWCFKlqPd8XgkgR4oUFCnST8QUKeobn0WQIr0NRYr0xeGqaZskRrWs/2IVkqK6UVrHvRBTpUhBkSK9DeV4qtproErRWqaipUiRWT8fkiLz8ZAUmXenOVKkoEiRXjJGkaJjrZ7YUKToSLO3TYoU6TJUI5QKKhniMGd01kOSY5Zmhdqb43sonXf960CRIv3rR5UcvR1FQHQZoogRV544Agv0ZEgRel8XjPIyiuAca2Q41uhtmPIcXYYo5Wn6Oc88P9vQZYjSnrPuj2KeOdHPsTZzOEDaf/0MSdFiXuuToaWAGB3Nl/pkqEXoo+gyVCf2OXQZmosPB9vXmDfCuQunHosfZLWvgV8WmOcZS4ZMH+CsYzQsRi5ElIhr2DNOZJaSK58UNaPBjr1PihqWH4FPimyPcSd0qEQVdlq0HK2MVVoE+KVo2fID8EnRsuX9qEU1rxg1LeO4fFJkOwH7pMg2LssnRbbHzLWUKHDTIiAsRSY+CbFNp+qTIpsA+aTI9pjveKqWDkBIimx19j4psnVifFLkmnKWmhQpqEmRIiRFtg6pT4ps42d8UqTLkMInRboMKXxSZEuGfFJkk6FQJ9uUoRDc6ZxdM8D5Ou+2r4FPimxfP99XqZ7aH/dJke275BMe22O+z8L2mO94TBkKYcoQBV2EKMw1M2sy5JMi27nOJzm2ZMjX3iZDvpRovtm2ypAvJbLJkC8lMmUoxHqkQtxkaDlaYCVDtahilSFfX9EmQ76UyCZDvpTIJkO+lMglQomnH0RxgFGXywHrlBCNQooAfmLEKaEDwCqhA8AqoVPYvug+8bE9FpIlmxRVPO+DTYp8gwBtUuSbQMImRTYZ6m2LP704Ny0qUj7HKaGr5M2hlNDp6ZCJTYpqWTKQDunYpMh34bRdmH1rS9ikiCs+vva247HJkMI1Ta1v0DGnfA6gJUUmNinyiZJNinxjF2xSVEv8nVWbFPkmE7BJkU2GFDYpssmQwiZFvjI5mxT5kqH5ZmTtcPtkyJb6+GTI1j60RpANbgmbL4CwbSu0fZuEcMXH1972OfhEyXY8PhmyiaZPhqqJvXzOJ0O29kVK5DjpfLWdFS6To8JNhQB/MmSTIp8M2W5S+mTIlhL5ZMiWEvlEyJUS+UTIlhIVSYU4yZAqkaOiSuSocBMhxbjIELDOJXPtQMe26KxyuhTZ0iETXYps6ZCJLkW2dMhkFCV0/dvf3OOKALDGFQEYGFdkS4dMzLTIlg7pmHP2U2qWdSmizNqnSxFFkHQp8smQQpcinwjp6FJEKa3QL9CU1cdHUT7nOh4q3HFF3OloTSmirtKuoKRGuhRRBnLrUkQtU9KliDKzmi5FPhlS6FLkkyGFLkWUMUO6FFHL5PSONyUZ0iWHkgxx17IxO+8hWTFTIu6EH1zZAoqPGaJCKZPTpYiSDOnvKzUZ0iWHkgzp7SkypJ9XKOc1/XxNESG9/XI7CcqQnhK5UiETPSVS44WoqPFCHLbSeCEqFBHSUyKKCOkpEUWE9JSIKkJ6SkTp76932dzIZ5nTedRxLyK35c5CB3RmoqMIkWIm30ESIsWebD9JiBQ7811sOYqYM9cVgbKmk85Uzpvhr8R8DdxZUdKIf0u1lPNmwDk+2sUaxLkrnmJNY74zmmIlRnviaZIQKXaUJshCpNg/OUkSou4xTZZYHf29UyWW7Oye5LXfM1nypkM29k3FrClpd01ErOloZ0ox6z3aMxWzS+h2MGaoAoATpvnjZ/ZO8tpPM2Z6A4DpmLn4LnNBVG4JG8CfuS1jPmH3BC8dmox5sjJd4snQTIkvQzvKPLmZZbY/bipnjRnaUeaVyU3G/DK5HeWIVSa3oxyxkqHdEzHrJs9MOWalQjPlmJ0KcWd4A4BGzttHAVOMvQAAd1NJREFUzvzFNZn9Bsr4IJ1azL/xzB3jPpMPLlrtY1e+h5UK7cx2s1KhKczyUiHwU6FyNMUKPu6Z/zvW9tfCuiZEvhpCkxRttHNe6tBGk2WU9ag6sAiUj6V4DivRPLl9JVphT+jQYggaANSYSQ4AVKJFVvtl5rSMDeZr4ApOs1AJHe/kxi2hm8t4dzLmmNs/ljGPP+XfWXmgyfuuPljnfQ731XjtH6jxLi73M9sDwIPMBV8O1XntjzR4F+F7K7zXUEt5Pdhmyr//VU2ABxhfp+U2cKRB78QutyMcYawFdKgRs2ZVe6BWbF0f7tot3MWG768xJZApdSvMJGquwJIf3LSL2/6+Kk/eH2S+p4fr/I7+fcwax3urvA+Oex471OC1P9LktecmNgB/EdEGcY1GBaVCRIc76cBigXV5uGvzJEx5qkSLrNdRwRxLhtp5nSVDWZ6wZShDypKhlHFTehisqxDdt/A1shRlq3cXOFKk3miqFKl2VClqrZaFUaVIyRBVitpR56RAlSIlQ7VomSxGqh1VilSCRpUi9RqoUqTaUaVIiQ1HilRbrhRRxy610OmdUddbUqV7oRI+RRud94ZalqhKEWs5/SLTWD3xzKe0fajSPPqiu532S8RFfdUitdTFalW7hRb9BKrSsApxitlq0mlHXdxWlZtQpUUtJrjEXEzwKFO67q8WWFxlm7HEXciSvfBlp/0i8XkqVaFWn6rAgCqOavuc9Ea5NXWW6YTZXkksVWbVZ0ZdB0iVzbYYNwnUwqPUJF0tol0lnseWmYt0q/PpCnFSHdWuQaw2UDLEqZZQMtQE7TU0utdD4tIcqg8Q0fqSSiKqxOmolQy1iNdbXYSaxL6kkiFqX1L116h9VXVMVOlS/eyMmOpR2/U9Z7WfRJWcNG/jvoWvsfezFjZkHaIkb7LSonZeZ6dFLdRYaVEDFVZatBLNs9Ii7oQOraheKC3iJEaVaJGVFi3Hi6y0qBHVWWlRGiWstKiJBjstGpUUKbiL0FKlSMEdq1XLWywxAuhSpKBKkYIqRQpq50DBkSIFVYoUVCnqtmcmORQp0rdJkSI9HaJKkd4ZpaREegJASYmW2702lJToUKPXhtLZ14+Z27EGaKKjt6GkRMvMJIk73oY7Zoi7faAnQ1SYy/mwEz2uwHLHEM430q4MUZljTj6wzLwRwj6PMmci5SZDS3mDlQw10GIlQ8tRhZUMcScdWIyPspKhoqkQJxni9tG4x8TtW2d5wpahDGlXhiikeXvdkyHFuo4hUpyy7/zuv12r17re9IloxrldVxRnW/EWcCdJ09jpaG//4uzKj7P+3SVAtrpRlazYmMwHX3NIfGbz3azn7Mz3DvzNN75qdzbY3vcapi2vwSdLtjE/PpmZwrT17z5hms3tn7OLHZZ9tDw/9BiDHUKfAE1hcKBG23OXbTcG39PQRBWz0eA+Gp6Tz3GlwX34pvjeXR7cvu9CvKc8OFbQJUC7HCuhu9rvm3SPQ3Td4d3pWKFdpUMms44V4F1T1s6W7Nt3CdCeCftrcAnWCdP29r5SuQM77K/B1Sl9hGNxdlc51InT9n3rMtTXfsr+2egypDPtGLLoErgdjuGEvk717kn7sbqEaeeEo71DhvY6tu+SlSnHa3bJkOs9cm1/1jPk0vVVKjv81yVDtvY+EbJ9br7PbMayA58ITZYsM9sFJGjG8vv3idAOyznMJ0K2c55PhHaVLOdTz/l3Oh78YvhEaCayn198IjSFwdfgE6Epy/hxnwjZxjj7RGhHNtg38onQpOU6G5KOKUsf0idCtj6kS4Rc/VPXMZVh72O7RCiO7D/+taRCJiXH90gXofVOh4ANSoh0bGmR7413fYi+ukSb+PjSI1tS5ItPbUmRLw0a9bgigD+2SMYVhdnsaRHAK6MDBtOi0HpHZloUuitpXtx9adBKkgw87mtvS4rqSeYtd7ElRS4ZAuxJkW/9DpvI+NIg22O+tMmWFIXGDdnSIl/H1CYavrEhtqTIJUOAPSlyyRBgT4p8aZbttYUSBpv4+NIjW1LkS4ZspXO+5MZWOudLhmzvEXeabMCfDJnik+T+ZMh8LJQKmY+HPjOzdK5IKsRlu6VCwPYcL8SlyHghF7b+qe+YbPv2pUK2/vcwZQgYLJvbyFRIZ0OEyGZ+RUroOFGflNCFKVJCp/ClQwpdiiiCpEsRRV5MKaJI0lqkyJcOKXQpogiP3saXDil0KaJOY65LkS8dUmzmErqFVptdQqdLkU+GFLoU+WSo214TGkppnN6GUnqnSxF1EgVdiijlSrpwUAbK61Lkk6Fue02KfDKk0PuulNI+/TVSy62WmaV0uhRRyuR0KaKUselSRCmT098jbplcmvPK5DZjiZw+logqQ/rNFYoM6WOJKDKkn+so50ldgCgypI8losiQOZaIIkP6WCKKDOljiSgypI8lkhI5P6MukVPlcdwSOZONSIeADSqZU+ilczoxc9rmiWiGNXPFJGZZcjSNneQBdoA7onS3500xnhRYq4nLBPM1zOSOOpohwU2ApjDNek6R8jmKECliRKwEiDs1+oSlLCG8D94MTrbSBx9RxNs+93i42MpDfOycKJGESDFbjklC1G1fKrEmUNgzMcEai7R7gv+d2DfF+97tYq6O4CrdcsGdypo7U1rC3QGTnRMRa8zQ3smIJStTzKm1p0t8GXKV5w0L5jJl7M+swRzwxF0zDOCPEUwZ3a5d5TLrptGu0gQrGZqOS6xkaCaaYKdCOWM5FIA+YYKCe2OTOz12kfVwuEvHRMxrPke0yphiiVAclQuNFRoGGyVDwBiUzNloMRfaauTLrA+7kS+zPuxavshKsJqokGcb6bTnvd4ii9fWct5CYVXw2nPkI+vMXk9uX4mW0GaeILnPqcTLfQuZhaiiwVo/iZL26PAvCPwTdpVZcjfHWEB4GXXrCuEuVnJe+6W8xmrfyNtYTHkX8SPNJqop/XM7wpz+9lCL95k92OKV2haZXOIoYyGaWpLjcJ3+O15o5niIMS3yQhNYYoSND9VztBid5SVzxVMCVWb0wZ3W+QizvblgsI9WmrNmw0vzHGmeo8Z4ze2MJ2jLrZw1FXylnbEEh7NmGAAsFljkeb7N+91z1qsDgAfa9L5ELW/hcEI/TyzlNRxO6UtALEYreAj0Shigc22qR4zFWaMlVn9iKeKlNpzKHwCoMxdyBYAmc5mMUU4y1s5rqDP6f9wlb5r5CprMZUTazD7+erGhQuQrneNKEcCbohvg10VyvrQAfQrGTtsaS4woq/wqlAzV8gWSGKm7IVUskMQozjtfI26Kwx1jw5WiIs/hSBFAW1Q2Xb1zEq/+X3CbUWebzahJEiNVrsiRovrqZ0WVospqeSdHigCwpGVU7fWywMW0QRIjfVFbihRVVu/g1okCxZ3Otrpa5kiVOnUHmiNF6s47R4oAkKRoodlrQ5GiBe1rT5Gihxhi1tlmp6PMERzVlvoc1Y46DbQq2aImFEr+KIKgl4NREhYzwaBIETdY4a/zxNuBkiGqJCsZShjpjZKhBmER7IWs3pWhZULCspw3uu0oi3hzx4dyz7WLzEXmAf6NumXu9WVVhiiJjz4MgtJ3qudLXRmijm9pZhWWDBWZcZkDVzy4N9u5IgT0jsl2bBuZDgFjkBD53oBWXmOL0ahrJLlf4JAUmV/AkBSZj49bWsSdCjuUFlWME2RIcNpRc6BN6DlZ1H+hHYUU6XDL4ThpUS2qBS9CdePzCUlRxRjrFpIic7KH0IV3Jee1Nx/nXtgBulgofFJUMcpZQlJklqeEpKhqdHRCx252ZilSZHaSQ1JkdpA5SRHgl6IF5n0PU4ZCHWAzGaIIjtkm9Bzz8ZAUmWvhhDr/5mv0SRFnnR2AV86lMA835C6mDIVSIvP9CEmgmQyFvhNmMhSSovl2k5UMcVMhijDpmDIUkiPznFkPlHObMkS5zpiP+1Ki5WiJJUNL0RwrGRp1KmQToVrm7zeZ/chQv5WbCnFkiHODHSieCvmOaaNlCBgDIaJQVIw4uKTI9XeXFNm+VEVK6IqkRZwv9LCkSKVDJi4pcskPJy2ySc+wnzMsKUoddbUuKVLpkIlLilyTWXDvzFVRZ5XQDSspMmUo1J77d9+kES6xqDnu9nLK56hJUbe94zhNGVK4jt3VmfVJkSsxcEmRKy1wSZGeDhXFlRK5kiFXB9hVJucTHNdj3L+7pIgrLJyyQNe2XZ+5T4Zcn7tLflx/dyVDLikqmgxRWGyl7DI5lwi5UiKXDLmkx/V3V0o0ymRoMVphJ0MUWdJxiZCrD+ESIVdKNEoZ4iZCwPDW4cxz+/fcJR2J4/0cdSrElbONZCyEiGqGw0iLfGlQkbSIA0eKOu35XyLzy+0TH1sJnW/wILWETrHeJXQU4THbmOmQDndc0TglRYBdisx0yMSUIjMd0rFJkW8q8PUun6PMoGeKhUuGFKYUmemQjk2KfIOXOavBA4PHHrqzb0pRkuXB8ilTijjjSQC/DNlSIl86xBlPBAyKQ2jMUDXJ15wEcccY+WTIJgI+GTJTk5BomZ89JRkyP/+NLJOzpUQ+GTLfu5AI2VKiUY8XWmsy5HssNO7STIkoImReY9arRI5CaKZgs6+kl8hZ2xvnZ64IAfw+4yhL5EI30Qeql0Y4Vmgc0iFgTIQI4EmRnhhR7HaUY4uKlNA1GXWselpEFSSu8a9XCR1FePQ2ZrmcjXEbV9Re/T/AnQ7p6FLkSod0dCmiTHXOvVsH8CZbmIuWumJEWRdJvyC70iFXe4ogrWf5nE+GFLoUcae1daVDOtxjX8tECxQZ0lMiSjKkSxGlVE6XIsq4IdUJXo8JFCjt9ZSIkgzpQkBJhpQkbESZXKgNRYb0lIiSDKnXu9zO2MkQB2qJnJ4SUWRIFyCKDKmUqJa3WMnQuIwX0svmKDKk+g7jWCJHQZXNUfuJqq9aZOIErgxxoIiQPjaIczzjIkPABk+7bfKwvc9hP8e14q2zPXMqRA5RxPNL7vTcRWjm9BPDbLSPNb3krnw/61i4U3lzF5flwv0u7LSscO1jlAlQkSmqI0d5o4vck57ZmMgnyW33RLMkISqKbbXzEJOOFbpdcE6dbeaUpNy0dFfM+23tKvNe644J3ndnknmrbbrE+z7XmB1+6sQG6wXz5WKS8QTuXU7m7PgAgImY9yTO+z9VilhlcpwSQsC+mLIP7rpqAH1NuCJwz/2jnuGUC3fK6wZzIXtOZ7+ECZYMcRMeAJiMRrskiasUzkbEXNImYSaWRTi0+I8j3weVsUmIAOChxZvQYsaQ7ayGdkbvxHMiv0a2hEY2unpS7qJd3Ln86/kCMsbJYSl7APXAQECdRlRlnaxYY5yYMpQiQco88XMX3+UkRWWUWBeuBAlKOf1k1UYLbeaK35QESlGLK6gzkqVaVMFSTJ+O9b7oQSzG9O9ahXHHshrVMM8sxaijxbqLWsmbqDLe/xXGjYYV1FgpXRsJ5jP67zDLc9b6RwAw36T/tqrtjLQQpmKlneNog97+aCNDlTHdNOdYgE7qwJnamdu+leYsQeB0+JMM4IRhGXgLrqp9cI5/kfH+L7cy1iyHlXbGSsNW2ikrDVtIeB1CPTEnHU+0hBVG+0pUwTLjXLjAWCx+Lj6MufgwuT3AX/x9JZpn9RmqjEVK22igzZCDJG+ybhgXkaGMUQadoMGSG+648SRrsvrKnL54K62ilfLEtZ3Vx0qGgDETIgCYW/4RW4oAsKVo1GLEgSJFSoby1XnZOGRos8SII0UA7Q6OSku4P2IuRcWICndcEfduHkWK9PePKkXJakLBkSIALCkCQJKi5Xix+2+KFCkZ4kgRALYUAbTSEn1wM0WK5tE5bo4UdbYdliL97i9FirICBQHNrHO+4UgRQBMRfR0dihRxxEk/Bu7inNTn6G24019TUDJESUz04IMiRfwiwv59UFAyRFlraFk7aIpwcSdb4CyaDPRkKCW+U7oIUcrHOCIEdGSIykI035WhCkFYRi1CQEeGqFSjxa4MkYZFMMcrc+SGOywC6IiQkiFK35EjQgDv5nKSNZFk9ONvZRW2DHFpZ3XMLf+I/bxRM3ZCBPSkaNhpkRn/cQeIbea0CABbinxiNIHpvv8eZawd3tZgRy0kRWZsz6055kqRT4wS41g5SRFAl6Ju+6jtFaNa3P9ehKTIXCWckxQBfikyJSgkRVXjWClSZA4m5tbb+6RIyZAiJEXm49zFc31SZMrQUrsdTIqUDHW3H5CiqtFJ5aYzPkwZCqVE5r5DwmJLenzP4UqWKUPBqbiNZMgnAFxRMZtTXoq5j9Dxm8mQT4qWmWO8zPciJJqmDPlSooWkUSgZ4mDKkE+OKlGFLUMcTBmqBFIZmwj55GglmmfLEAdThjJPeTJXbrZCKsTB7HP7xtMXTYXGVYaAMRUinaJiRGUzpkWKommRDdcAuI0ooRvW2CFuWjQsKSo76nQ5aZFLilzvmUuKktV3wfocRlo0rKRIT4d0uOVznLTIJ0Wu9TdcUuSa+nYY5XOuv7ukyDU2gFM+B8ApRaYMdbfvkCJThhQuKVqxCI0rAXL93SVFrn26JIYrN9ztuDrszqm4mWVy9m3Y/+66YvjeAo5wLTYzdpmcDdd7M8pkyCVCKTJnUuSSIVdKxC2Rs+Eqm3PJkCsl4iRDw0yFXP2EUZfI2Ygd12uODKlEiCtDnL9v5lRIidC4M7ZCZBrkeowt4ooRedsF0iIONjGqe2aOW+8SOt/kAqMuoevso78D5xvUOcpxRcCgFJnpkE4pL7HHFXExpchMh3TqUW1AjMx0SGetSVFIeszHzXRIZxjlc6HV4k0pMtMhnbWWz4UGSptSFCqVW+uYIpcMubDJkIJbFmdKUZExQ5zHue2Huc6QKQMhUTFdY9hlcqa0hETITInWmgzpmO/zSjv1ytDAAsbMVAjgJUOh8ULmY5xUCBjueCEzJSpyk7JoiZwNs48wTiVyHAnq7mNMUqEiIlREhnTGNR0CxliIALsU6R8e5YvIkSKg+KQLlDWSRllCB/ATo2GW0JmsVwkdNQFar3FFrnRIZxTjihT6ZAuuZGjgOQXHFflkSKFLkSsd0uEkRUBPinwypDClKLQ6O1C8fM4nQwpdiiiCxC2fU1DHDelS5EqHdJQUUWRIlxSfDCl0KaIIkpIiigxxx/1w2plQZKhvKm5CMqSkYK1lcjb0w00y2j7U8XNSIYAmQ/p7Q0mG1PtddLxQCJUSFZk8gQNFhlRKpI8XolBkvBCn3XqXyPkYZYkcNxECipXIhVAzxxVJhThQREhvY0uFxlmGgDGbdtvF/t1nWv9ejnhTzXKnxXatBGwjZk7/PRXvJLctMlV4gzmvvrnomI/d8cNY257Nd5HbNiNep48rOoC/xthkGvTPCQD2ZvsYx5F7EyKTVsS7K8adYpO7PhO3XDNi3H8p57xpobmvdSafYbUvMbffZN7M4DDJOB/sLTDl63SJ91qnYsbnypyumQN3+uVRw73bWGI8YZrTGECZeTDcXgFl0oSi7blrJFFkXoeyPpgOd40ezs2+XfkeVjLEXk+GcX3lLhsB8K/HnOPnXLcB3nqSlBva/dvm38AtM5ZGYF+7GTf+uddt7jgkVz973GUIGPOEKEQzXUYzpUe53LivkSyS21bbh1Ft0++8cEruis1ywljHIa0gZXzpq/kxVPNj5PY1xgWEO+6HG52naLNOCFUssBai5c6EVga9458xjrsdtdBiyiWHFuqs9SSaqLFSN84dxpVoHsvRUXJ7gFfOV4/qrE7KSrREltdaXPGWKZo0ohprdff5nJvU5t2FZykkDAlpZhmqCb1TU01SVvtWSv99NNIUjZTXwaomjPGIaYoaY/uNNCOXHbYzYIVRophkORqcab6ZcrPcyliCs8RYFLWapGgwPtelpI1GRt8+V4bmonlWJ36JcV5aiebxYHw3uT0nWVmJ5rDCWNi0xTxfA0Ad9L5YPV8a2fo/3EqZFG3WepYJs+qImyRxbk4neYO1VhDnfWylFbRSRlVTVkeyCcYJ+dgUQhQyyyJiFKLe7nSYGskiW4yocCdoKCJFHDFKsyZbjKjUohW2GIVQJ2zu4EqAf5eEIkUq1RiFFDVWS8Ky1f+j0orqJDHipkPd5xGkqKmVg1EusurCypEiACQp0t8P7hgnihTppTGcRI8iRQ2tLJAiRWpxV6oUpdpisBQpUjLEkRZqe+42K6slUhQp0kWIKkVKhihSpG+TIkWcDr/uQRQp4ggr0JOhNvF53DFASoYor1n/DlDaLyX0juRy2mTJ0Fw0jznG+WgpOtqVodCsbQD/XKdkiFKazhEhAKzF2YHO+VqdsynP5YqQ6vdQEh+uCPHG5tQKyRD5ePI2W4bobXvvI2UfwxahzZAOAZtEiADaG7pZ0qLciH7HKS0CMDIpAsYrLQrdSTJPltykyCdGGfo7HJykqPN893G3o8GxMcNMi1oDA/yZK497pMi8yxjqKJiPDzspqhvvG3egsw9TgjhJEeCXIvP7xU2KAL8UmR3tkMCYZUy+9uZjoW1XjPEiPinipkKd/Sfe/17L9s2OPndyCh/mZxRKiYokQzqhlMhMhnySwxViU4Z8KVGRVMjE15HmpEIA7xwWmnxgcNv9MuQTlhZqhWSI3HaEqRDAlyEO650K+WRn3FKhEJtFhoBNJEQAXYqGnRYpNktaVLNMflAkLbJhi5aHVULn+jtXilxi5DoJckvobLjGvHDSIpcUNRwTBnCSIsAtRUXTob5tOKSo6bjADqN8zvV3V4fC9fpdUmTKkMIlRbaB066UyCU/rr+7vgM2TBlS+KQodTzHhit1cHViuWM6ONs2ZUjBLZ9z79cxxTijfM6VErmEwCVFtj+7UiLXZ+SSIpsMtbPcmRS5kiGXFHHL5Gy43i9uMsSBkwoBbhlypUTDmHzAlRJxS+Ss23acp/VUiIJLhFxjd4ZRIucayzKMVMgnO+OYClEYRXncZpIhYJMJEUB/gzliJGOL7Gy2EjodbhnduIwrKq/+H5UiUrSWtMhMh3TaaLLSIvNi67vAcmcuMqUo9JrXWj7nm0WKOxmGKUU+GeKMJwLsUuSTIc54ImCwM+uTIVvHl5McuWTIhU98bI9xpCe0fVOKOGVygF2GFKYUFS2Tc++7+FTZS63UK0MDCRkjGVpK2l4ZMlOiUZbIAfzxQqOaia3IeCEqXBECipfIURh1iRyVIusQbcaxQpxxQptNhoBNKERA543miBEVjhgVSYuoYlQkLeJNFzmctMjGek24QE0YuFKkTrCUE2dRKXLdwdcpKkW2cjkbo5xwQUmRKx3S4Q7cVZ0ISmeiSPmcEiNXOqTDKZ/TpYhSGscpn9OliPLd4pbP6VJE6WyrTi0lGdI7wJyxRRQZ0lOiUUygoLfhbJ80fkaTHE4VHeXzUSlRK83XXCZnQ6VEnFQIoH3+6r3jpEIAX4Yo6NcIrgyF0M9daymRs6EEiFsiRxUhtc1xmziBfBzMsULcGec4qVAREaK+j6MojwN4/fNxY1NMu+1i/+4zWZ11ztTYnO0CvDsVsxPHs7Y9FdGnrQZ4U0jGUcz6UUyW6NNQ74h4r5MDd7zQBKZHNsXnnvwE1rHM5vT30LXCuIs04t3V5kyFDfgTIhPOe8id5IIDd+p0AJhkTMttjgn0b3eaJTtxTv98dua7yW0BYA9zSu6piDcV7Kim2OZesSiSqMOd5rkU0V8nZw2yHRMxS4ZmSozjKPDRmIuw+uAmYJz3vJkzlk2ISyORIQVlwgQdznmOu9wG95pIZRo72akQJ/2ImVNMc5ZP4UhWmrfZY4U4lBjTbnMx1/sJwenfcqYvnyjt2LQyBGzShEgxt/wjtBJ6wtBs0+9WtNMq2owyulabfhzV1hFUW0fI7TlpEcDroNWSeSQ5LVUAgAYjcVvJjmAlo7/OWk5PXLilgs28MrIF2hajw1iM6GWRlAVNi9CIquwJDjjtOTIEgLWwMEfiG/kSa52t5Zz+HQQ6qRUnXaozFiFejOnbbaDCWiH+WPwQuW07auEYFnEMi6T2aZ6hltE7OW1GAs2dApu17SxFiziGaSVtYSVtsV5nI6N3FuppgmrKGO/CSFhSRplckufsNZs4C9NyZajJmCab835X8iaOpfTzirlwc4il6CjrJlsjp/+WbeOAnW3zBda1kyNl7byOlZyXtHMWoOcsDp8hZd1kazOuKc10iSVDKUMSuO2zPGFJCEdukrSOJKVfxzl95iStb2oZAja5EAFArXEPWskKWYya7aWRiVGrvcIWIyrcMrocKUuMuFLEFaMQ6oTOlSKuGHGliCtGVEYlRQBdcpLVixFXoiiosgmKFDXzznvBXRyPIkVqm1wpAmgld0pYKFKkykO5YkmRIjWwmiJF1LJK67EQZEEJS5005TRvCmwlNxQp4qxHY0J5napzTpGcOnMslkpM6oQyMiVDFco03AUKQpQMUYKwojKUkD7PzntIKWqpMK8LSoaoC2JySuQa+XIhGeJcNylwy8zaOe881cwqhWQoISRbXBHiyhCVNE9YcsNtzxUhqgwVESFqP1ltu9a4h7z9cWXTCxGA7gfBTYt8H/j0xHF9/72Z0yKqGCV5ayzSIu4dryJS5HuO2TEfpRT5xIhbLqdTJCnyPYfbidfhJkU+MTIlaNhJkTmmySdFpqhwkqLQ+2keh0+KzFmmOEkRgGBKlBqdVZ8smKJCkSIqZtLjkyJThkIp0UrKk0QzqfBJkSlDIYHilI+ZyZBPikwZCqVEjTQfWTLUzNKRJkM6Lc/1bz5aKpQMUTFFSN38sVHLFtjJEBVThHxi1M7rhWSISoY2ORkadSpElSGu2KjnUBl1KqTjKznkBgZq21tBhoAtIkRAvxSNQxndOKVFAK+MziVFthnNRpEWKVwnfNtAzfVIi2zYLiwbUUJnm3q1SPIzjLTINlCXI0UAv4SOuo3l/IhTjFwTPAyjfM42eYhLilzHMYzyOVc65JIiU4aK4JIiWyLkSomoZW8+XNtwyZBL/LhlcjZcUmSTIVdKxC2Ts+GSIpcIuVIirgxxsL3frpSIkwxxRQiwy5CrbG69S+RcErMRqZDresktkaPiSoVc/R5uKsRhM6dCVPRtbxUZAraQEAH9H8yoy+iocMRoO6VFVIqkRaMaK7QZS+hU8mOKTuK5MI2ihK6zz8Ht+u6YmkLjS4M4SRHAL6EzpcgnJ6YU+WZSXEvyBvhXqjelKFQqRx1PBNhlwZfYmFLEmQLbJ0O2fXJK5ULJkPk6fTLEGR9kw5cMmVLkkyEzJeKWyXFSoU774ciQrWxuLcmQD58MmWVzS9HR7v+oDEuGzGvluJTIFSmPG6UMUdmsqRB3CZRRl8cptpIMAVtMiIDBD0gXo4myf1YlzhdjXCZdUGkRd3wRlVGNLRrlhAtAv+iETjqjlKiiUrSWcjkXHNHR23I67aFpXBM0RzrZAud5uhRRpv8e1UQL+vsbOg5dxHwypFhL+VwoHdJlgTuJwjDa2PYdkiFdrtZaJmdDl6LQuCG97VrK5HxQZEhPiSgypKdEo0qGGlkSfL/1lCgkQ3rZHCcZ4kgQQBsvpN8EWq8SOR+UEjn9mscRIWB0EyeMeqwQpy1HnsZl0gRKf3eivMO53a0mQ8Amn3bbx+z0Iwf+NlnehXZC/wFxxCFj3MlSXzIKOyZPRM7obEzHe9DMGSWDKb1tHNHXxpku7SavdbQrPpF1sudOFc2Z1pNzZ6ocTZEvPHvzk8jb7RwHo4PJ6HwDwASmvAmR2XaYQqTDmZqVc1GdjvawRGp3dCJrPaQy6NOncjomk5ghH8dsvpv1ue/J95PbAsA+xhTeE4zpuGdKJbLsTJdKrFI53tTNvDu/rOmySxPkSRR2lCZYxz0Z089902X6MU/GESsZyvPRyRBlggVFFXSpnUSJLEM5UrYMcRIWzrmPc32ciGZY5xzutNQcYsb02GVMk6+9pWiCJUKcZUU4IlSKyqz2k6UdLBHKGdPLU9fPBHhj7SfKO6yCtRVlCNiCCZHC9oG1khVWqtNmTNnJ+aK3kyraCe04qq0jqCf0tREa2RLrx8H50XFi2E5atEhqu5IdQTWhX3xqKX0VboCXMrQYd7+q6VHysSxGh7EA+t16TmeXIyEAUMnp718FvPeac4HlXNQSxl2ylfQQuS0AzGf3sdpXGOV2nM9mKacf9wIeJLflrk+SIMXRiLHoMOMzn0vo55DFhL5dzlTZlbyJNuPGBwBUGO/hUUYHbDGlb5e7nhIHygx1OpRFd3ttOeuR0akzbpIAvDWGuOsLcc57nKQiyWqsm4WjkjLOdbGzbUaqkTXJMtRIF1jXjRqj78TpNyVZnZciZU1yH7GVVkYmQ6xxQlljW8kQsIWFCHB/cJxyt3ZaI4lRuTTNjkKpUgSAJUVA50dC/aHkeUr+AVIjWfU+UKUIwMiliCpGrazCugBQjkWlfOMiRZypYKkrmqsLN6VzoEo8RyVFzYxXckgtXVFleRQpaq6mPZT3Tk0U4htT1d3uahvOKvDHogfIbTk00fmdU6Sotlp+WyWU4TZWzx8U0VFtuKkPlRqjxFO1pQiUkrIVwvdayRBnfFSDuJBqa4PGDJmooygRkgUlQ5TkbiVawgoxGVqJ5rASje4mEFeGuM+hkOZtsgxxr4Wd7fNkiEoj7ZyjKYlPLZknyxCnr5RkdSQjXASVk2Zxjps1TihrIMns56+tLEPAFhciwP8BhsRosrRLa0sTI4BXI8pJi+rJfCExojK6tGiRLEbV5ChZjGrp3NikRZzjCEmRPgg/JEX6uBaquOhwBv9ytj3MpEj/HEIXUH3FbooU6ccZkiJz4oZRJUUUKVKEpEhPhyhSlGh3akMpkZIhCjXGWMSB5zLSn5AU6eJGSYl0GQpJDkecOAnVWpKhkBTpMpQQxibpMhRal2gckiGqCHXa8kVIP3+ESrl1sQktAspZJJTDqFMhqgwlWZMsQ410oStDFEaZCnHgTITQSitkGVqLCPmm3PaJELD1ZQjYBkIE9H+Q5dL0wOOjLKMbBzHa6LRIMU5pEbktU4qox7KAh8hpUSOqDi0tsnW2XVLUtIxn2Sgp6tvuiJMizkBnlxRx3jub1LikyPZ3lxTZSuV8UpRYOumjKp3zpUQNRtLDLZUz8YmJTXBcUsRpa9unKyWyydBaFpxVtNJ87JIhCmuVIde4YJsMlTDh3DY3FaKmPElW27QyRKVIKkRhXFKhcRAhgF8eZzJR6k1Cth1kCNgmQgSEP9BRlNEpxqmMjgo3LTLFyDUBw7ikRRtdQqcYpxK6tWzbVedu6zi4ZkS0SZHrfbddVNuOi5ZLinydGlOKfNN6b4akSIdbPmeTIlc6ZJMOVzpkkyKXDNnExyVDtpSII2tAsTI5CuuVDOmYKZFPhFwpkUuGbCnRMGTIVjbnkiFb2dyokyEqRUrkhs0oS+Q2IhWaLO3s+2+OCAGjT4Xox8Erj6MyrPI4xXaRIWAbCRFA+2BHJUajTouocrSWtCiO3XfMAH4ZHRVuWsQVI3JbkaJC2x6XpGhU44qAfimypUM6+nsXEhldikKCpG8rNJGCKUW2dEhHl6JQqZwuH6FSOV2KQsmQLkChZEiXopAMmZISEhw9+eG0DcmQnhKFZKhoSsRJhRpp1v0flXFNhtxtt74MURmVCAGjTYV8lKPJ7r9HlQqpRGijU6FhixCwvWQI2MLTbvuYnX4kEuLsPhOlHWgRp6aeKM2St8uZwnqivMNb+2kyUz7OebfcZLK0A41kkdQ2ikrIiCUq5dIMWQCnS3vJgrSjfALqjBPmbGk/+SI2Gc2S13OajHeSO9izpf3kqdP34WHehTx1pvMdrLVxJjFLTh2mo93Bjr2+XepMSOVoivweT0Sz5It0OZ4if+cBYCreTf5ezMb7yAu/7oxOZL1v1GRnKtpJ/uzKEX1acADYm59Mbrs73xVutApnqurSiO7NcRKZNmNMFEB/fTsxTT6OXfEUORmajunTnU+XI7IMleOIJUF5PhoRSvOMLEIZcrIIRSiRRShFmyVBOTKyCJXjWbIITZX2kI+hHE2RRShHRj7HlqIplgRNxDNkEZqMd5JFaLK0k5wIlaNJslCU4imyBJXjGVYaNFXeTZagiXhmJKVxURSTJAjo9GW3mwwB21SIAGCifDwiopRw5vXnrJHDkaLJCXpHBOj8YKlkjLtInDWRQolSUTjvG9A52VKhvhe19jHMTBxHattKK9gzcQqpbTNfwe74YaS2y9lDmI7pF8pGtoSpiPY9amRLmCntI7WtpXPk97iWzGGyRFuHq53VyZ37JG+iFNG/b2neJh9zK6tgukRblyfJmuT3jbuuBxURoh7jIEQAMOUZj2KyI54MN0JnQdpdJdp2G1mK2RJNoGppylrviLOILqez0cjbSIjX3uVohbxuYC1aIU/zzBWiVlYhX0OSvNWXYPjIkJHPK0newETkX4RewU3NOXD6Qpw+CGexeOoNXGB0/TzAP5nBwHEw+liccUIp9X3LM7STY+TtbiW2VcmcTjs5hpyYYOR5Mpq2yMg/Qk4ZHcCMT9MGOdlilRQyjpnTlvPaAPq4pUa6iFbGGMPVptctL7Xpa90sZ4wSOmLaouAs2stJ4jjlFqwa7hEuHMg55kZK7zhQ3rd2XiMvNstZkb2d11AnlvqpMt553E9q34gqOBLTvpu1qIYKsbyzjiYqxMV/a2iSx+wsRSuoRbT3bTlaQT2qox4RjyOqoEJMcptRE8sR7buWISdNw91mdJo45XU1htwAo5UhKsvEzwEAOX0HOjLEgXM+YXXqWQut0te1aqQLpLHCnLE/3PaNZJFcodJIltBIaNe7evMY6k1ap77WOopai1Zpwe178PpLNbQT2vmKcxxp1kBKTIa2swwB21iIgJ4UhQQmXr2LQ5Kd1TsB20GMqHCOl/vaOFDL8lpZlSxG9fY8WYyW2veRxWg5e4gsRltRivTyt5AU6Y+HpMgcYBw6Zv3xkBRxOg0KqhQBvPFVVClShKSooXXoQ1KkS0hIiup901r7ZUQXoZAULWkd35AUcTrUne3Rv+fNiP6dKDKJwkrq//7oMhSSHf3xFmHhVZGhHtRzX5K3yDKUrf4fbbsNsgxxprHmntNYY4WIItRpS7/GiQh16BOhUEKVZ9tehoBtLkRAR4qoYqQYVlszGvWJkdmWIw4AcwrGLZ4WUdlMaVEjW2KJUTNfIYuRT4rMySN8HYNaYrTdwkmR7z0zxcYnRWZbnxSZj/mkyDa+j5oUAWEp0qEmRT44M7ktMTq+tg61LyUyZciXEpky5EuJTBnypUTUdGgrJENlTxfF/OwiuEsCqTKUos2SIc6sbOOSCpG3u8VTISrcG69mn2iybC8ztomQbVkYdQyjSoSUCG13GQJEiLqoL8NGiNFA2yGkRaXSYG2y60dl+8GOsoyOyqjSIs7U36NMi6isdwmdbRv1dIGcFo1r+ZxPlGzH7HodNimydQY46dp6JkW+yU5sUtRwdORtUkQtUQP60yEFtXQOsEuSS4Zsx+VLF2xSNA7JkE2GbCmRS4Zs4uOSoVaWWZOizZQM1aIVqwzFFnnabCVyo0yFuDJEZRSp0DDK42Ym9w/8zdVfmp4YHMul+kCcVIjCqEWocywiQgoRIkEQBEEQBEEQti0iRBq6KZuJTuyZDWYg/fHUa45yXNEoyszMlMgV/wL0cUWjLp+jvraNLp9bzzFFvuRoFGOKOKUka0mJfKnROJbO+dIdMyXilMf52g57PJELXzpkls3Z0qFuWyMl8pXLcUrpdIY5bsgsm/OlQ2bZnC8dMsvmtlOpnIvlaIWVDlHxpUO2WRvHYcwQlVGUyakUaRzK5FxMTfTPwDqK8UKcVAjgjxeiEEyG9P6olgx1jkfSIR0RIgPzC8Iti6O2U21DUyzqYkSZjpErEBTGZRY6DhwpGlX5HJUi5XMhOSoypohKkYkWzPFDA+20BehC6wmtx3giSodHSVGoUzDq0jlKCZ2SIuraYApXuZyiyFginwx1265K0TDHDnHK+YBe2RylVE5J0XqWyumosjmKDCkJGgcZauTtoAypcUTjMIEC5UZPvDr9/0aPGRpVmRx3ooVxGC/EkSEK1H6OuoFMESE1fohbJkfCEKHOMYkMmWzbdYhCTJSPt/6dmtqw1iMirjsB8Bd0TVPaSZkzTz51zYCJ0g6kGf2iMComyrR1bzgLxCYpfaxDifj57pk4hSUmo4K6DsJMad/ApAouOBdR6nexHE2x5GhUUNf9Kcf09YFGsUbRTLyPJUSz0V5y2505fT2sUk47h8WMc2g7op9nEsbaRDP5DHns0ATo5/GdOe2cBADTxPW1JhjncC4Zo5vAkSEq88RFV3OkZBlqg56yUM9zCuqNs3I0SZahCcbagtRFQ6OoVGh2zGEeA0C/UVMuzZBFiLzuDuj9qumJfaxEyDfRhwnn/SKLkAORITuSEDlwfWE4i7lS5SnLWuQTAmfRrnZSRSulXRzyPEMrobXlpEVNxnSZVMngyAgANFq0tKaRLpKTKOp7BQC1Ju3u1FL7PlSah2jbbPNOaJz21Iv5YusgefVtzsme+vk202Xydjn757RPsyaaxPK5UPKlQ/2dt7M6ebuVhPbdUsynB0ntavkijoDYljExQSWiva8L8VFUiB3mhegIef8AcCSmlQ/WohUsRbROcxv0jlqTmF408jZp/SIAaGTMlJDYvpEnaBCvY7wJFGjfmZVoDpVokdS2mdO/h1wZop4P8jxlJUNUqH2JDBlZhrjnT071CfV4G+0Fsgy1iKlUmiyTZSjNGiwZot4MbiVL5Pe3nVZEhkaICJEH61SEeYYoKo9GjFYXSgxuL89YYtRKV8hiROnoT5Z3scromskSWYw4UsQRo0ZrnixGHCmiilGteZQsRhwp4ojOKKQIwFClSLXhfLbDliLVjtMJGKYUqU4K5zceQr2WWkr7DqhyS6oUUVAytBIvkttSpYiCkqEVoriodtRONgUlQwtRuJSJI0NUlNxQJKeRJSwZIh/DiGSIyqhkqJkus2Ro2FD6D922xD5JmjV558E1jE920WgvoNEmjl1NFtFKFlEqzQbbpgnts2LN3oaOCKVZC+VAotdKltAi9ovaaQVt4nXWuQ2ZWjuICBEBX1o0KjEibZMgRuW4N689VYw4HX2uGNG26ZedcmmG3NaEI0UbmRZVmodGkhaFJKqpfT9GJUXUC+ywpEh/jHuB594ZdaH/9oeVFOnb4WyTKkWkbeWL3X9TUyLAL0WcFGkh7v2eqCkRBU4HWy/R8qVERZOhJcY06z44yZDZtuXpwI9ChpajyshlyHedraVzbBmikOfpyGSI1I4xccNaRMi1ng7A6zNwRYhCmiyTZMgUocnybk/bVvd/FIqKEGfIRN92RIRIiBAR6ftCGZ2UoYiRsU3O3R4lRtQ7yi4pmij117Vzxci+zf47Ndy0aBRldMNIi2anTuz7b25aRGWjS+g4E0m4pKhpufistxSNoq35d2qnCHALjK2EhVM+Z8N2/D4pMifj4KRELiniSI6JKyXSZSiEWSrn60TbHnOlRPTxKoMdJVdKRE2GgEHBcJXNrUWG/PsfjQyZlB1jMagy1Mwr5GRolCVyw8bWT3DtZ5SpEAWuCJkyVHLM9LsWEZqYOM7elpgIcSQIsKdCpXhQHoeRCHW3JTJERoSIQeiLNYrEyHrC8zyPKkbcMjqzs7/WxVxtYqQnP/3b5ZXRme1LjsHsG5kWbdUSOmpSBKxNiqiSwt3/Wrdr6xy5fq+cVIf6XG5SZIqRa2ZCmxTp6ZCOKUUuGbKlRK62phS5ZMiWErnGDZmd6ZVornAypEMdS2TDJUO2lIgqGC7Bsf19GDLUtPx9LTLkgiNDVDZbiRyp3RBSIfMayl3iwtUviOP+/lKR8riBYzVuwlITIYBeHhcSIbNcjloe5xOhIumQyBAPESIm3TpMj3Rwxaj3H+5tchIjoP+uctlyB0Ix7PFFwMaU0dnaUxiHsUUUNqqETocjRcOebKFoUhTaflGB8j2vaFLkG+DMmkxF2+awSv6AfilyyRAXXYrWkiLp6FLEnUTBv93F7r850zr7SuX0lGgtyZCOnhINMxnSy+bWKxmywRFXTiq0WUrkNnqsEFWCgPEojyO1C4iQXi631kRIR0+HhpUIATJeqCgiRAUJSRFAF6O+tCiwTXUypKRL3DK6VroyUDY30K7A+CKzbM6kyKQLrjTJbMsRIwqbKS3iwJUiSoeAK0WhCzLn81zv8jmTYZTPmajfMqV9kTFFlHWrqOVzKiUaluQAvZSIWipHkSHVsR5GMqSjUiLquKFhyVBfuw0uk6OsMaQY5nihbHVa9a1aIkdqN4KxQtRESI0fGuakCaVocujjhCYmjmNNmEAtjyvHM6RESMkQpTyOkw6JCBVH1iFaIxMTJ4YbrUJduJWcLuUJynF4NhUFdV5+zhpKVDhTkE+Udg59/5x1llwldibUKTiTtIIS8XOylSLaMEsNhgX1tXMu9sOcLU3B+TyptJMaJsr03xOFScZ3mfq7o669lOcZSowLaUxc72Y6pq85tDPaT2pHXZuozVj4tM1Y1JVKNZvDrph2zp/Nab/l2Zz+HZkCcU0i4vonFTSwE+4KAhPqYrI5Y9FZqgxx0r52TrwRRly8mnODgwP1fAsAJeLvk7qGGa/iYm1TPdugVqYAQJoSJxZhJJcxYSY6wD7Gx0WSVhA7xjqZUOVWZGj9kIRojbTbR9Bu007U1I5hlrWQEe5ERFEZSUafgSjPE5KUJWkFCfHuPrVdmtZIJ7U4niRHx5y7O3meISG2paZgE6UdpM+pXNqJNKshJXxW1LQsyxI0WrQSAyqN1gKqDVoCxUkJqSUG1AtEmrXIF+iRXMgZKaltQgkb7axOLknkCGbK6CBQ919Jj6CS0s55lbz4eBoTaoqznB/Cck77Hlcyeie7mg1/aud21MJSTEyniYvPNtFGhbHoKBXqNmtook5Mxg7HtPf/aHQfEqLgrqTEzz49MvSFnam/zTiaIN+AAGgylGRNkgy10yr5Zl6zvcRad5C6XaoMpWkFKbE/kOfE73wUd/4XaoaYfpNqtc9EkSHOawLxRrKUyA0HEaIhwZEijhhRSLJa93+0Y/B3ktSgRKoYUdqVV++UU+/0UGJkdeeGs0ZAkjWCYlSKOyc1aqeXIrDd1x/4jNQJmCJGk+VdaLQWhi5GISlqthcB8KYbD0mRkiHOOLkQ6kLOkaJ2Qr/BMGwpAuhSstFSBGBdpYgjQ1TGQYaocGSICkeaVNvaEFM3JUP1yP+bOxrdR96mkqFQ8kP97gK0dEhd10PJtS5C1JQ7JENJ1iQvsKqEJdTR50yYoG83WHLPGLPckwb/seZ5gyZDmgjFgdSHK0JUeCJElyFhOIgQDRGqFAHDT4sUHCmilvBx0iJKW2paBNCnn6SkRfq0nRQxAsJpwNTEvu6/qZ9VKC3ST8bUxGitYlT0ub73pmg645MiXaw42w+11UVoWFKk/8abyTJZjHxSoo8N4txcCUlRopXTcqZa50hRETEyB9A34D4XcFIhXYZCYkSVIXNq5wU85GxLFZx21OprW4ncn0tRGQqJEUecdGHypUTUZMjElxJRk6GBbXpSopAMUX+DZiI0jJJfU4R826SmN6YIhUr6qNvlihBFHMgiBJASIYCfClEZRSoEiAwNGxGiITOKEjqAnhYBcKZFtvFGHCmynQDKljESay2ji+PB2JlbRkdNjVxiVDKOgVMm5RIj872iltEBbjEyxxwVESNbe1dKpNIhHer74kqJbAJETYpcomP7+zCSIttr5SRlw5Aik2FJUdFj4Nxt50gRZ6KDUZTIATwZosKRISo2GXKJDFVwKmhY27pSImp6ZJMhV0pETYdsMuRKiWzfV27pnE2EbELCLY0zsaVD3ETIFBZbh5+TCKltjlt5XATLWBtieVzn+ZbPz9IXGV0qBEiJ3MYiQjQiNrKETjFuaZFNngB6YmRLi3wDHrliRMEmRnpKpLOWxMh1l8omRraJGJQYrSU5MqXIJkMuXPLBmbLUlCLXc7lJkdneJT+jKJ8DBqXINSPcqKRoM4wrGofxQuspQ+Y4orXKkAuqJHHHILlkyEyJOMmQS4aoY4mAQSkqWiqnL35u+62ZMuQToaLpkE+EzG1yxwlRCG1zYGF3YirkF6H+17WZUiFASuQ2GyJEI6RoWuQ7YRYpoSsytshc3Kxvm8xJFziJkcJ2Z0bBXcVZFyPXatfAYFpkpkQ6RRMjlxR2jrNfjHwnac5U5YA7OQrJUpFJFkKCoovNsMYM6fukCBJ5oHBBKQoJyqiTotD+x2FckU2MOGvMbNR4oRVtWxuRDOllc6MYM0RppwvQsMYV6SlRKBnSpYgziYJ3m1pKpGSIc8MSCCdCrNlOV7ez1kSob/96OXYgFVLlchy5AoqOE/LDFiHP+6yPHxrlWCHfa4v6buRKKjQuyLTb68TExIlkkYmimHwS5pxgy/EsWY6iqEwe51Mu7SSdLKjtgI6QUd+vidJOchJUiqfJ04+X42lyojFZ3oUmcWG5jLj/UjxLnq58qryHlVJMT+4jJ0c7pk8mp0OT5V1k2SjFkyQhiqMy+XMol6ZZiVG5NE2Wnhy0qcYny7vIv9+p8m7ymkHUizfn/AEApajcN4bIx2S8g1RetLNEX45gZ7QfpbxMFqFp7CTJ0Ey0jyxCO+MTWRMn7IpPJMsQderxPdlxZGname9gyRBpm5hmJUOzmCLL0AwmSenQTD5LLpMrY4osQ9PxHrKsp1mT9fuJophcFse5XnP6AFRhiRCTE6FSPEXe7kRpB3MabapcxCQRilAmJ0JxPE0+l8bxJEuEcmofL54GVYTiaFJEaJ0QIVpnSqW9Q98m5ySbpTXy/PtZWgMYc+APnTwx7qR4mmYNlDjrFzHeM85dJOqaBWlaQeRJoHRCM+LojGINqSRZxPTUyaS2rWQZ0xO0DmCS1jFR9s9KpKB2DprJEqbK9HVy6q2j5ONtJgt9K5b7CM22pGinVUxN7CW1bbVXMDVBe23ttEo+BoCzTlibtCgy0LnDPRPby0lNqGttNLJlxMTfbiNdxkRMO9aIuG4PAKR5k/y6EjSwN3oEqW0bTezJad/FiZx27liK57EnO47UdiE+in3ZCaS23G0vx4u0Y8jvw0REuz6tJIdQjmjr+DSSRfL3lrM+D2cdIep1utleIq9HV28dI59DW226sHCS+zSrka9RnZustHNNTrxJAwARce0fICZfo5N0BTF1XT7mcAbqtT8d0fpXgh0pmVtn0nSR1C7LKsgyaqnZSvd/pG1TFzkDyAudcSJt+jSZZeRZAzl1JWnGnRxO6WGWt0ipTnk1qaKkVaXSTuRZi3QiTZIlJMTyuHYyh3YyvLVfFI0mvTyp0Q7vn7coYJ28mjoAVikhQDteRYtQ6tZOa6i1jpK3yRmbVWQqXApp1iS/x5zPrp4Nb0r4RkbvHDSIHYl2VicndEBHhqgkjLSFs4hsLaqQ1i6irm8EdGSIA2fbR+L7vbMDmrTz8PVpJWGcj5JFclvqdzvLE7I0cGd4o8hQvXWMLEO15mHUmodJx9pKFtFivF/USYF644TDMpTnbeTExWWBaPV/FOjd3YTal8pqyDhrQSJBDuJ6eyJD644kRBuILy3SZSiO/clHZtT4l0r+E6ouRKG0qE+ePHdxTcGJIvddGE5bU8h8iZEpTqHESL+g+cYsAf3jq3yLr5nxunfSB6Ot765RZnRWy54UJEl6ndCJMu2Os3tbi33/7UuKdFkIpS56xyN0Udfbhu7I6jIUSorqhrT4jrmZ9HfsfUlR27jhMDvpvuuud5RCSZF+hzeUFOnbDSVFiSEEvvc4y/o7Kr677uYMWb5UxZcQmSLkS4hMEfIlRKYITQbOs7oMhRIiXYZCCZEuQ76EqBb1ny986YwpLL62pgyFUiJ926GE6Eh8f/ff0/C/vwt5r1QulBLpQuRLiUwZ8n1fKTKkXzN8vytTgHySY97k8LWtt/pLp3znTl2CbDPM6ugS5BvnCgxKkC8dGiy7dwvRoAT5uqb9EhR5SxZ754tQOqSLUCgdyvrG+4YTbl2EYs/nISK0cUhCtIGMIi3qbJeXFpETozxxJkam1PhSIFtbKtS0COBN4zmsxGhwam13YmQKmy8xMk/OvtSoXO511lRiNKrkSGEmJ77Uxex4tBP33VOzrS/FMJOhjU6KFNS0qNleJKdFvqTI7IxxkiLA/x6bjDotGkUqBLhn9nNhJkO+10JNhtpokpMhU4Z8rGcy5NuXLkOAfw0pXYYAf0pkpkPcKbNtuL7HKgkyEyGXDNnSIJfg2CY1cLVViZCOS4ZGlQhxlokA6IuwAxwZGkyE3DIUg9rFTdIVSYUEEaKNJk0Xx0aMyDDqi9dcRme5c+wqo3OlRy4xst2VdolRZGvrECPbHTaXGNlSLGopHcArpwN4JXVmOgQMv3RO4ZMik3EunzPTIYVNilyiYl3ryVL/X2TtECrcEjqqGHGkiCpDjXR5pCVy1DK5BA2rDC3mDwweh0OEliwTS7hkyCYj41QmRz6OnDaJArD2UrlRlMQB/Gmubb9bmwzZRAiwy5BLhGzpkEuE7NcutwjZ0iH3MhqD6RC/PI7K5iuPExnaeESIxgSqFAFgSVFn2+ubFg00HcX4IrjFyMVGJEYDx8BYG8kUI1+Eb4qRnhLZCImRTYYUphT50hJTMHwdElOKfG3NzrpPfGyPmeVyOuYxm+VyOqNIioDxGFcEjCYtqmcLXjFqZMssGaKy1lTIxyjHC1HxCYv5mE+GbI9xtu2TITMl8smQmRL5ZMhMiXzjhszvqf7fFBHS06GQCOmSw7mB4RIhG+OUCFFTodGOExpNKsSBKkKApELjhAjRGLFeaRFl3JASo+CMdJoYeccCoV92OG1DM93pYhTF08GZ6XQxCs1upYuRLSXqa6uJUbgOW1sbKdBWF6NQXbMuRiEpAopPwiBJUQ+Roh5rLaEb1xI5H+MuQybbMRlyob6v1ERIyRAlEVIyRBEh1ZYiQiodooiQSocoIqSuWRQRiuPpbjpEE6FOOkQTIVUuFxahXrlcWITU+CGKCKnrrKRC2wuZVGFMKZX2spMgTqTMmWaWA+fOCAfKoMXC2+ZMa82Z4pwzFSejPCOKJwcmWSAcDX37jO8GdQp3IDywt+8YGO9zwkgJWZ8J8zhCwqwzwXjfpib2sqbMjWPeb4X1Ghn30KaIU5QDQIk4fTIAtNjnReox0NaSUVCn9AY6EytwZGgC9PeDQ0ZcSwsAYuY1ogl6x7GeM0onGZ1GjpAPa1FoG5116eg3KTg3HTiLknPOd6NYI6nXfjiL95pEjPMGPZECwPidcInjWRGhMUUSojElTRf7ZjajQXdbjriMSnI4cO686M8htcsaZPnM8wwZsQMex5P0C0FUJr/GTlqUgnfSzkH9flAXIM2RkE/sWdZAK6HfaeZc9DmDd/nJKqMz5imtM+FMoFBtHCKnOlneZnUKAV4qx1n0tsX4DKk0GZ8Hp8PL7eAlWRN1aulR3sZcdg+pbS1fQI0hC5WcnmQuERazLbJdwD5OysVy+iC5bbV9lCwLzfYSeQFn6neDMz5OHQO1NK7RnkOjPUd/fa0j5PNimi6TZSjPG2QZyrIa67fCKYHnXKN4bXkTN41ShvKcfs0U1h9JiDYJnLvPq88IPN772EPpi95J504vOSq4x8F5jaFpzvUF4ygL0uljuEJ3tPQTN+eYQbqbq5/oA6UIhO3p+y+V/GmALpGTZf9UvYlWojARKCdstnuSVQqkLokhZKHPGeiN1wu9PqD/cw6VK+qdldB027qEhKbQzrS7oKGFKM2OHmVNkzTtHXe55P/u652sycDnGEqIdBEKdd76ptMnnDfNDl45VJaqdWBnynu9bVPt89gdP8zbVhehPZF/IWRdWHZG4an1lQztisILr5oytDs60dtel6GZyP+912UolLBV273SvuB0+5qAlAiLXoaESP9tUBZ01fcfWkdIL8cNnt9aR7r/pqTxad/vJFyW3t12IL3vm2I6sF1z25y+CK3KJS94HKFr2mhFSBh/JCHaJBRLi6iJgD+Z0DvmRZKaUUA5Ds5x621DKYK+KnaWNbr/o5DnTXJqxDlmWmKkXxD8349QSsT5DpjvjS8pSox67VElRZ3j8m9bfzxU721OXMJNi6hwxv9w7263k+pYpkWjTIU4d7uTrNknQyFSRonOWlIhX5qzlB/qS4ZWcv/4ofVMhnzjunQZAnglZaGUyPcdMX8zIRky0yCfDKlEiEKzdaRPhnyocxNVhszUxidD5hga1tjfILyUh9WnGTgOnwxxqy14iAxtHiQh2oQMLy2yf/S2ZMLVAea0HSWuNGUYx+1KEnLHzHL2qUjtY0BsiZFz/Sb2e+26CLhO/oPfE1tS5NqnK0VxyaItKTKFSGG7k6qnQ/3HMXiBN9MhHdfn6xIm2+t0fb62pMhVyuJKilziYUuLMkcn3Nax88mSLS3S06HB7Q9+511Jji0tsiVELhGybdfXybWlRD4RsiVELhGyJUQuEXIlRC4ZsqVELmGxpUSuEjlXSuSTIVtK5JIhW0rkKpOzpUSmDClcKZGrPM2WFNm+J67fgUuGfOVwNiFySZD1nOaQIFs65LpB45IW13XFJkSuiQS427b3PegLrvra247FfRy2a+HoJAgQEdqMiBBtYtYuRv6P3kxYqG0p7UcFVxq4x613nl1C1Gvbf8L2TX9uilHoLhvns+lgXhB8FwNj4Tvjub79mbIQSs50KXLJkMLsQLiEqHMc/Rd5nxAp9M82lB6Zr9P32ZpSFKrt18UolMKYUuQSImCwg0dJj3Qx8glRZ/v933dfaZspRaYQ+VIhc7uhVEgXIkoiZAqRLxUyhSiUCulSFEqFTCHyCYspRKHxQroUUVIhU4h8yZApRKExQ7oUuWRIYUqRT05MITK/J77vv/lboYwJ0mUolAQNnMs8aZApQ6ExKLoohK4jpgz5ZlTjCUj3WXprRlt/e/7i7vo1TERIsCNCtAUoLkbhj151vKmCw20/SjjHwj1u1XkOSVGnrZqelDZTmJIjSukB//1WFwbqRSFa/X9L5P0oWaCWESopCgkR0OtI+GSodxydiz1FhhTqc6VMvKBeJ/VzVWJEGeyspIhSlqakyCdDfcex2tmjltMpKQoJUW/7ne87ZaC2EiMlRJTyOLVdanmcEiJqeZwSImp5nJIiSomcEiJKiZwSImoZm5IiyuQJSog4JXJKiihlckqKKBMoKCEKyZBCSRFFUpQUqe8K9TuvfiPUmeKUDFFK4rrnMGJJnBIiymB8JQrUsjUlRJSppbnb5vQzuO35x8K97vEQCdoaiBBtIfhixNg2ymMhOUXgHDv3derjiULE8TS589yB/tMc/ecTgXM8pdJushABtMkpFBOlnSQh6hzHLEuIuJRKu1mfaRyHJy5QTE3sZY3ToQwmV5RLM+zZ6GLGtNTl0jRrGl/OtqMoZo0V4kwVDnSEiDNWaDIw0YXO7vhhrPFCJdDfl53RftZMctz3ZXd0InnM0Ey0jzWbHGeMWSmeYk1pHUUx67tOnalOMVnexVq3jLz4OToyNKpZyeJ4lrzGThRNM2dq48K7vvAoQcYICRREiLYgoxQjwQ5HjDqpEnXNqM3786S+Jyplo8zkBnTulFJmGOpse5QXcR36Suoxcf0alWxQf89xVGZJCJc8z4KzfXXbrnZAQjNuKahClKwOxKceR5o1USa+33rCRj2eLG9jOjDTnEItGLpzwj+DnKKeLmBnyT/Dm6KSdtKGmVJ4MWYAqCVz2FEOzzjXbZ92OvzTxN9otX00OLNgd9urC5GGZi1UNNtLrM+fCleE0ow+XTUApGkVEfE8sVlvPm4nRIS2HjLL3BYkzxP5sa4zed4ilc9pzwBNduiL7Y4bvPeDVhKi2qyf6FChi2vmmV3LuuURzpzGJc2arE5mK+Ekon4SxvvGPU5quaHenvOcBnHNIkU9Zcw6l9JKrxS1hDeTnJIhKqr0jZL6KBmiopIhzmfrI81a3f/Rn9NASky/07Ta/R9FhsZlFlfBjfSvti6SEG0DJDHaGHwJyaAscNZq2Fzw3gd/UmRKU2h62fXH9zkO3n/ypUXm7Gih3/Fg++He7zJFy3eX3jZtuy8t8iUyNhHy7dvsLPsSIpfU+I7HfE4oITJlyJcQ2UTIlxKZMhRKiEwZ8qVELhHypUTmOCBfSmSTIV9KZJbJhVIinzRxBciG7/eVGtPjh2RIJGj8EQna+khCtA2QOxobgy81GpSEHPTUaHMxrKTI9vfNnBQBvLTI9zvmTi09DNYjLRqnVMj1HFf600gWWckQJxUC7MmQaxu1ZI6VDHFTIcA+KYIrJSqaDOn4hWfwMW4a5EuCXDKk0iAKKg0SGRpvpP+0fRAh2kbID3tjGE453eYtnQPsUuR7TzgDiW1StLGixBNbmxTZBKe79TEqoQN45UutZIUkRklWZ8sQFW65W5Hn+ESo0h6c+IBbIscpk/OJUDUZlJiQDDUsv03qDHGAX4Zsk4j4JlCwi0/T+G++BPlK4kwZ0svirO2Nc7dI0OZA+kvbDymZ26ZIGd3GohIiuihxpzAdT7ivuze1NU2Q+NOxjhr1udHuPakSOp8Q9W19tR2l/VpK6KhSpcqYbCVzNlQZnSpRo0qQ2g9VhFTZHFVq9JI5ynNU2Rw1EVJlc1QRUmVzVBFSpXOUVEgvm6MmQ6psjipCqnSOmgyp0jnqbHLm96HIBAkU9N8QJQlSMiQCtLkQEdqeiBBtc0SMNpYommSmR6OcnnR94L/mzU4EThgfxzNkIQI6v2Fee74YcVOmOOadV8yFMIcN5/0pwnR5L6s8bufEyaxUaGfpRFYqNFPaxyqRK/Kd4E5swJlCvlyaZk2tXYqn2CWZVAnS4ZS4RohEhDYZIkLbGxEiAYCIkSCMnlK4CYBoNZ0oEddm4qREnfb8zm+WJ6x1a7I8IU+jDPCEqNVeweQEbTpvoLMYJ3X6795zGuTjbyedtVwmyrOk9qrjPjN5PKs99TU020us19tOq+z3p51WWZLZSlZYa01xt09NhFSHl7qOlWqfs0osR7fmjTAaRIQEQMYQCatIvawgjBpeR4l7B5uzWGkRcmTIQU+KkrTBSgVCtNoraLXpKUCS1lkLcqrj5RyzkiEq3BSD216lKtTntVfLvjj7Uc+hft/UtqnlitztU2RIv75Rtqu3p8tQCpGhzYX0ewQdiQWEPtTJQRIjQRgFqsNES4uUFFHTItXZG2WJmJIiamKkBIOTGOlwJKizP946T0WkbdxECKCPt1G0ibOhreU53Ndhbj/LE+932SdDto6uT4Zs7cMyJAK0GREJEmxIyZzgRcRIEEbFoBRFnrIilxS5fqOujmTRkjnrthxS5Ot42sTIVjLnEyFXyZxLhlwlYT4ZcgmcS4ZcJXM+KbCVzfna216HT4Rs7X1S43qffM9xfc9cr8NVOufah2v7NhnydXRt30lfe7cMiQRtVkSEBB/S2xW86CcQkSNBGCYpqEkRYE+LfL9JW1o09MVamWkRQBufMw6pkHmcoVSondT6pKhIylO0RI7KKFIhM8UJvYYsbw9IkW8ftpRIlyFKJ9eUodBzBmVIJGizIhIkUJGESGAjYiQIw6YjRr6EqK/1qhRRf4uqQznMdMiGEiPqc5RwqISIKkIqIeKI0GR5F7s8Th0ftUROCRFVbFRCxBGhyfIulgip1IcqQ9z2QO/7xXkdcTRRaB9Khqgd3aw7Fog6kYKSIZGgzYyIkMBFhEgojIiRIAwPtYYSh/Lq+i5USvEkex9FJmtgT9PNPJdwp/Xu7IM+y5mC+zqo6y/pqDV0yPtgHlMRCS7yHG5Kx10rCACyEa0vpBif9cuEoogICUWRWeaEwsgMLYIwPPK8weqQ5Xkb7YS+lg0AtJJltBLaIreKNGuwO5Zpxpt0gEM7rbDaF5ntjjtDHdBJVFgz1KU1tFPe+1RrHma1b7TnUG/RFk8FgHZSRTvhl9U120sswWkly6zvVJa1yDKUZrXV/9G2r353IkObG+mPCGtFbvELa0ZmphOE4ZHnDVZapKRooryP/JxWsozJ8m7WcXFnvFNSVIpp6/OEKCJCRSgiQlzWIkL11lHMTJ4QfE6jTV+YFUCfCFHXeuKOYQLQJ+Rp1gh+nygiNCjg4Xu9IkBbA5EgYVhIyZwwdESMBGE4+MTINQuWS4x8d8x9cuQSEVdHNnG2d4uRr2TOtf+pib2O/dtfp2/xUZ8EuUraXCLkmzDCJULTE26ZtaVCPiFyiZDvObZUKCRELhnylWXa0kmfEPlkyJ1CumVIJGjrICIkDBvpuQpDR2amE4ThoDpw3MSIkxYBvY4qJzWi3N3vb89LjLiJEMBPhbhpkIKbCnETIcBfHudKidaSCpmoCS5sYuRLhtKsZZUiV6mm63tkk6FwKeagDIkEbR1EgoRRIr1VYaRIOZ0grB2zjC60YGSRMjqAL0bcMrrOc/xitNlFaGC67hGPEwJoImRKFHWskFk+xy2To4xZM6VIlyH6eLSeDIkEbS1EhIT1QErmhHVFxEgQ1kYUTQeFyGSivI89McJkeTdbTkrxtLNkzv2cWcRRmb2vqYm9bBHqTL3Nk6FSPMVOhMqlabYITU/sY8vQzOQJrFRoZvKEQpMmTE7wpvoGOqVz3Ak8SvE0sqxVYFKOWCRoCyIiJKwnIkTChiFyJAhrgb6oK5AijnlTdANAllVQKjEnX0hXEMczzD3xJjzNswbK5b2s56RZAxPMacqBTmLFS8AaiJnTmyfJEvs9K/bZVDE1EZ6QwaSVLGKCOQlHqz2HUmkH6zkZQ9rznD9ttzD+iAQJG4UIkbDhiBgJQlGoUtRbH4cjRlnWS22one807S3OSe/k04Qo1zrMVCHSkzGOEOmJFX1mvd6+qFKUJL3khfp+FftceskQRYpayeLA3yhS1NISK6oQUUVIJGjrIiIkbDTSExU2HJmEQRCKokSHnhapzjQ3MUrTTvkTJ5XIsvrqvriJUT85s9wP4C/KqSgyhqnIvnQRoqKLEJW0wLTgNhkiPc8o30vTalCKQjIkErR1EQkSxglJiISxRMRIEIrgEqPU8fcOLjnydcBdYqQnRIP7cYmRPSHyiZArIfLJiSshCkmQKyHy7cuVEIVEyPYehUTI/Vm4ZciVEoVkyJUSmTKk45IilwyJBG1tRISEcUR6ncJYIqmRIBTBlhj5ZQgolhqNMjFar0SImgaZs6BR9pVlrQEp2gqpUDtZ7pMinwjpx2NKkS5DIkBbH5EgYdyRhEjYNIgYCQIHJUVhITKJ453sjrgSI19CNLgfJUadhIgjQioh4orQRGlnobI4JUSc/Skh4oiQek+KvP9cEVIpEbdETgkRRYZ0SqUdXRESCdoeiAgJmwURImFTInIkCONKVOAZnBnzVp/DmPlNkWX1NY9n4u6PD19gO/DfQyBlLfqrw536Xe1P2PqIBAmbEelVCpsSKakThHFF3WPjixFt6wl768XEZHV/q4kGR8CK728twpCCOxV7EfrX+xn9/oTNgUiQsNmRhEjYMogYCcI4ElYXSkKkREgnNObJJibUhMhWvheSoo0RIZPQezm4L2pKZF/8lL8/YesgIiRsFaQHKWwZzBOzCJIgjAP6PTdeamSTIArDSITWZ3/rKQvufeV5wytFdhHSt1tsdkNh8yECJGxVpMcobFmkrE4Qxg1aOd0oRcg2jqiIBFH3Z2eUomATlPD+XFLklyHfMQhbBZEgYTsgvURhWyByJAjjhF2M1jsR4opQnjUQxdNjKkLmfkqF98eXIF3CRIa2AiJBwnZDxhAJ2xqRI0HYzBScWa3gvcCOsBXbpyCMOyJBwnZGeoPCtkaSI0HYLhSXkqLJlYiQMO6IBAlCh3ijD0AQBEEQBEEQBGGjkJI5QbAgaZEgbAYo5Wv2lIZSNudOhmSqaWHzIqmQIAwivT5BsCCldIKw2ZESOUFQiAQJgh9JiASBgciRIIwbelpDFxIzIeJLULH9CsJ6IRIkCHSkdycIDGTxV0EYRwpOL104CVrbfgVhFIgACUJxJCEShCEhciQIgiCsJyJBgjAcRIgEYQSIHAmCIAijQCRIEIaPCJEgrAMiSIIgCEIRRIAEYfSIEAnCOiNyJAiCIPgQCRKE9UWESBA2GBEkQRCE7Y0IkCBsLCJEgjBmiCAJgiBsbUSABGG8ECEShDFHBEkQBGFzIwIkCOONCJEgbDJEkARBEMYbESBB2FyIEAnCJkcESRAEYWMRARKEzY0IkSBsMUSQBEEQRosIkCBsLUSIBGEbIJIkCIJQDJEfQdj6iBAJwjZFJEkQBKEfkR9B2J6IEAmCAEAESRCE7YcIkCAIgAiRIAgeRJIEQdgqiPwIguBChEgQBBYiSYIgjDsiP4IgcBAhEgRhzYgkCYKwUYj8CIKwVkSIBEEYGSJKgiAMCxEfQRBGhQiRIAjrikiSIAghRH4EQVhPRIgEQRgLRJQEYfsh4iMIwjggQiQIwlgjoiQImx8RH0EQxhkRIkEQNi0iS4IwPoj0CIKwWREhEgRhSyKyJAjDR6RHEIStiAiRIAjbFpEmQeghsiMIwnZFhEgQBMGBCJOwlRDhEQRBsCNCJAiCsAZEmoRxQGRHEAShOCJEgiAI64TIk8BBJEcQBGF9ECESBEEYY0SitgYiN4IgCOOLCJEgCMIWRoRqOIjQCIIgbF1EiARBEARBEARB2LbEG30AgiAIgiAIgiAIG4UIkSAIgiAIgiAI2xYRIkEQBEEQBEEQti0iRIIgCIIgCIIgbFtEiARBEARBEARB2LaIEAmCIAiCIAiCsG0RIRIEQRAEQRAEYdsiQiQIgiAIgiAIwrZFhEgQBEEQBEEQhG2LCJEgCIIgCIIgCNsWESJBEARBEARBELYtIkSCIAiCIAiCIGxbRIgEQRAEQRAEQdi2iBAJgiAIgiAIgrBtESESBEEQBEEQBGHbIkIkCIIgCIIgCMK2RYRIEARBEARBEIRtiwiRIAiCIAiCIAjbFhEiQRAEQRAEQRC2LSJEgiAIgiAIgiBsW0SIBEEQBEEQBEHYtogQCYIgCIIgCIKwbREhEgRBEARBEARh2yJCJAiCIAiCIAjCtkWESBAEQRAEQRCEbUt5ow9AELYihw8fxuLi4kYfhiAIgrDF2Lt3L0466aSNPgxB2FKIEAnCkDl8+DAuueQSlEqljT4UQRAEYYsxPT2N//2//7dIkSAMEREiQRgyi4uLKJVK+NnP/h31Wh2IotVHYkRY/bf+tyi2/Dta/X/j3r+j3uO97cSIol7baLUKNor0f0eWv+nbLa3uXTs+lBAbj0eIes+Hua3O32L1t7y3rRiDz48RI8r116jenWhgW7H2evvborvd7rHqf4t6f1Nvt2qHqPfvOOo9s/vuR9o+I9VG236ktdW2r97rWGsc9+2/fxu9/ff+re9Xbab/uPK+5/W/vv7ndZ9vbZtr74XlWCyvr7P93LKv3jH19ptr2+s93q3T7ttvru1Xf33ma8373je1X3VMkfb8KMr7jtv8W+f4tLZam8H9a8+L8+7ze597/78H/hb3Xp/+t17b3kH2/633b+2U0X3/9L/ppw7jNIKo/4PpvaHaFyvSv2TqWPo+LP2Nj/ofj+yP9+9fe7z7gdqeYzze3W7c22b38XjwhxRFvbax9iL7jk/7W2QeS2zfltYu1/8WG9vvOybj+Fb3m/c9rj3fsi8Y+zp48Cj+/D1fwuLiogiRIAwRESJBGBG1Wh21aq2v16KLTPdv3X+X+uQCULKhSY7lcf1vXXmJcq1jqNrqne18oOPd6eAqiYh6cmMTHpR6ctIVprgrP3HeE6YcpYHnAzHivPfvTjvt/cl7rxuGKPWOTx1/79/6M5QQxYgGhCgyhKhPZIzH+4Wo9xxdMnr9p952bJKiC0F/x17/d28f5vZ1CbA+bmzX+zh6nW1diHrHkjue3xMiXVQG35dc+zy052Dw8e6xaPuNjef1nmN7XH8tgxKjS1Lvs+oXIl2aes93C5H+eJ98xXYh6hMd829av1j/W58Q9f9c+vrdfUIU29rqH+zqf+tvbKwJkfYhOoWn+7hFcizCE7ke12XCKjShtrHjcV14TCGK7W2jwONau1z/mylEfZJj31ZufTy27sv6uCAIQ0d+XYIgCIIgCIIgbFtEiARBEARBEARB2LaIEAmCIAiCIAiCsG0RIRIEQRAEQRAEYdsiQiQIgiAIgiAIwrZFhEgQBEEQBEEQhG2LCJEgCIIgCIIgCNsWESJBEARBEARBELYtIkSCIAiCIAiCIGxbRIgEQRAEQRAEQdi2iBAJgiAIgiAIgrBtESESBEEQBEEQBGHbUt7oAxCErcrs7AwiAIii1b/EiLD6b/1vUWz5d7T6/8a9f0e9x3vbiRFFvbbR6j2OKNL/rT2/uy21/96hdPaUr/41R4ys//nIu493/q22n3X3HyPt/Dvv7StGqXvM6jkxYkS5/hrVa+q9L/r9mrzv753/zrrvVO95ufa3fPW4s77XqN633r/jCN3nd9/9CNp7pdr0ji6KtLba9tV7FWuNY5jvcW8bvf33/q3vV22m/7jyvufp+4+N53Wfb22ba++F5Vgsr6+z/dyyr94x9faba9vrPd79VPv2qz653nHF+vO0berfBP37CABR3nu+2db8W5Tn3f1Gkfb3SH9/1b/z3mvNte1Hvefo/x74W9x7ffrfem17B9n/t96/o8EX0/c3/dRhnEYQ9X8wvQ9a+2JF+pdMHUvfh6V9YdU5oe85g4/37197vPuFtD3HeLy73bi3ze7j8eAPKYp6bWPtRfYdn/a3yDyW2L4trV2u/y02tt93TMbxre4373tce75lXzD2dfDgUQiCMHxEiARhyGRZhnK5jMc97hc2+lAKoDpuifa39kYcSB+58f9nroaCoMjR+8IIwhaiXC4jy+QsKAjDRIRIEIZMHMdIkgTveMc7cNppp2304QiCIAhbhIMHD+Ld73434jgONxYEgYwIkSCMiNNOOw2PfexjN/owBEEQBEEQBA9yi0EQBEEQBEEQhG2LCJEgCIIgCIIgCNsWESJBGDL79+/Ha17zGuzfv3+jD0UQBEHYQsj1RRBGQ5TnuczDIwiCIAiCIAjCtkQSIkEQBEEQBEEQti0iRIIgCAIA4Prrr0cURfinf/qnjT6ULck3v/lNRFGEG2+8caMPRRAEQdAQIRIEQRgDrr32Wrzuda/DmWeeiampKURRhM985jNr2uall16KiYkJLC4uBtu222289a1vxfnnn49nPetZa9rvMLjlllvwpje9Cb/8y7+M/fv3Y3p6Go973OPwtre9jfR6xpHzzjsPz372s/HWt74VaZpu9OEIgiAIq8gYIkEQhDHgkY98JA4ePIjjjz8eO3bswMGDB/HpT38ar3nNawpv89RTT8Uv/uIv4pvf/Gaw7TXXXIPf+Z3fwbe+9S0897nPLbzPYXHyySfj2LFjePazn40zzjgDURThpptuwu23347TTz8d//RP/4STTjppow+TzVe+8hW86EUvwrXXXovf/u3f3ujDEQRBECAJkSAIwlhw9dVX45577sHRo0fx+te/fs3bu+2223DffffhxS9+Man9xz/+cZxyyik455xz1rzvYfDGN74R9957L2666SZ86EMfwgc/+EH83//7f/GGN7wBd911F/7sz/5sow+xEBdccAGOP/54fOITn9joQxEEQRBWESEStjW1Wg3XXHMN3vzmN+PCCy/E2Wefja9+9asj2dfRo0dx5ZVX4vnPfz4uuOAC/NEf/REefPDBgXZnn3229X/XXnvtSI5LGA/OO+88nHbaaUPb3g033AAAeNGLXhRs+2//9m/40Y9+hJe85CWIosja5uabb8ZFF12Ek046CVNTUzjllFNwySWX4JZbbum2eec739lNcj796U/jyU9+MmZmZvCoRz0KH/nIRwAAeZ7jAx/4AB772Mdienoav/ALv4DPfvazA/t729vehoc//OF9f4uiCH/yJ38CAPjud79LeyPQkcPf+I3fwKmnnoqpqSmccMIJeNrTnob3vOc9pOcvLS3hT//0T/GEJzwBO3fuxO7du/GYxzwGr371q3Hw4EHr6//MZz6Dpz71qZidncVznvOcbpuJiQlcdNFFuOWWW/Af//Ef5NcgjJZWq4WPf/zjuPjii3Heeefhda97HX74wx+Snks5tx8+fBif/vSn8bu/+7t4/vOfjxe+8IW4/PLL8aMf/ci6zZ///Od429vehosuugjnn38+XvOa1+CLX/ziQKllrVbDRz7yEbzkJS/Bueeei1e84hW4/vrrB7Z37NgxfOITn8AVV1yB888/H2effTZuv/12674vv/xy6zXozW9+s/d9+OxnP4uzzz4br371q73tBGEcKW/0AQjCRrK0tITPfOYzOOmkk/CYxzzGeYFYK7VaDVdccQWq1Spe8YpXoFwu42/+5m9w2WWX4ZprrsGePXv62p955pm44IIL+v72C7/wCyM5NmFrcv311+OXfumXSJL1rW99CwDwzGc+0/r4VVddhTe+8Y2YmZnBxRdfjFNPPRUPPPAAbrnlFnzxi1/Es5/97L72H/7wh3HTTTfhxS9+MZ773OfiS1/6Eq644grMzs7i9ttvx5e+9CW84AUvwLnnnovPf/7zePWrX41HPvKROPvss4PHOjExAQAol2mXrzvuuAPPetazUCqV8OIXvxinnXYaFhcXceedd+JTn/oU3v72t3ufn+c5zj//fNx666341V/9VVxwwQWI4xgHDx7El7/8Zbzyla8ceI/f//734zvf+Q5e/OIX43nPex5KpVLf47/yK7+Cq6++Gt/+9rfxmMc8hvQ6hNHy3ve+FzfddBNe+tKX4sCBA/jqV7+Kt771rbjqqqvwlKc8xfk86rn9lltuwXXXXYezzjoLF1xwAdI0xde+9jX8wR/8Af7wD/8Qz3/+87vb/PnPf47/7//7/3DgwAH81m/9FqampnDrrbfiIx/5CB544AFcccUVAIA0TfHmN78ZP//5z3HxxRfjwIED+MEPfoAPfvCDWFlZwStf+cruNu+77z5cd911OHDgAE4//XT85Cc/8b4fJ5xwAl73utf1/c239tGRI0dw7bXXYmZmxrtdQRhbckHYxjSbzfzYsWN5nuf5T3/60/yss87Kb7zxxqHv56//+q/zs846K7/zzju7f7vnnnvy5zznOfknP/nJvrZnnXVW/sEPfnDoxyBsHt773vfmAPJPf/rThZ5/99135wDyd77znaT2L33pS3MA+b//+78PPHbHHXfkcRznD3/4w/O7776777Esy/IHHnig+99XXnllDiA/7rjj8v/8z//s/v3ee+/NJycn8z179uS/+Iu/mB85cqT72Pe///0cQP7CF76QdKzve9/7cgD5W97yFlL7P/iDP8gB5Ndff/3AY+q37+PHP/5xDiC/6KKLBh5rNBr5yspK97/V69+xY0f+4x//2LnNf/mXf8kB5K961atIr0EYLT/5yU/ys846K7/uuuu6f2s0Gvlv/uZv5q9//eu9z6We2++66658YWGh77nNZjP/7d/+7fySSy7p+/tf/MVf5M997nPzpaWlvr9feuml+QUXXND9729/+9v5WWedlf/d3/1dX7t3vOMd+bnnnpvPz893/1atVrvb+853vpOfddZZ+W233WZ9TZdddhn7u3nllVfmV1xxRaHnCsI4ICVzwrZmcnKSvOL397//fVx66aV43vOeh/PPPx9vfetbcffdd5Oee9NNN+Fxj3scHv/4x3f/dtppp+GpT30qvvOd71if02w20Ww2SdsXBB1VLkcdP3T//fcDgHWSgk9+8pPIsgzvfve78chHPrLvsSiKBsraAOCKK67A6aef3v3vU045Bc9+9rOxtLSEt7/97TjhhBO6jz3jGc/A6aefjn/5l38JHucdd9yBd73rXTjxxBPx1re+lfTaFLY719Tfvuv5U1NT2Llz58Dff/d3fxdPfvKTndtS77N634WN5bvf/S5KpVJfeenU1BQuvPBC/OQnP8Hhw4edz6We2x/1qEdh7969fc+dnJzEM5/5TBw9ehS1Wq3792q1isnJyYHv1v79+zE1NdX97x//+McAgHPPPbev3bnnnotWq9VXzjo7O4vdu3f73oYBkiTpOy4Xd9xxB7773e/isssuY21fEMYJESJBIPC1r30Nb3vb2zAzM4PXve51ePWrX4177rkHv/d7v4eHHnrI+9wsy3DXXXfhcY973MBjj3/84/HAAw8MXHT+4R/+Ac973vPwX/7Lf8ErX/lKfOMb3xjq6xG2NjfccANOPfVU/NIv/RKp/dzcHEqlEnbt2jXw2A9+8AMAwPOe9zzy/m37fdjDHuZ9zDaeTueuu+7ChRdeiDRN8fnPfx7HH3886Vhe9rKXIY5jXHzxxfhv/+2/4XOf+xweeOAB0nOBzm/0KU95Cj73uc/h7LPPxgc/+EHcdtttyLLM+ZynP/3p3m0ed9xxADrjOoSN59///d9x4MAB7Nixo+/vSnJcY72KnNtN5ufnMT093Sc6Z5xxBqrVKv7n//yfuOeee3Do0CHccMMNuPnmm/tmJmy1WiiVSgPlo2pbP//5z7379nHffffh/PPPxwUXXICLLroIV199NZIkGWiXpimuuuoqXHjhhXj0ox9deH+CsNHIGCJBCFCr1XDVVVfhBS94Ad7ylrd0/37BBRfgFa94Ba699tq+v5ssLy+j1WpZ70arvx07dgynnnoqAOBJT3oSzjnnHDzsYQ/D3Nwc/s//+T/47//9v6NareKiiy4a7osTthzz8/P4x3/8R7zhDW8gP2dmZgZpmqLdbnfH6CiWlpYQRVFXaCjY7kSrTpvrMVtnS3H33XfjnHPOwbFjx/ClL32JNRPeM57xDNx000348z//c1x33XX49Kc/DQB42tOehve9733BbZXLZXz729/GO9/5TnzpS1/Cm970JgCdMRaXXnop3v72tw+MEQpNB16v1wF07toLG8/c3Fzw/GyDe243uf/++3HzzTfjnHPO6fsOveAFL8Ddd9+NL3/5y/i7v/s7AECpVMLv//7v96W+p556KtI0xZ133tk3zkklR0WF++EPfzjOOOMMnH766Wg0Grjpppvw2c9+Fvfddx/e9a539bW94YYbcPjwYXzoQx8qtC9BGBdEiAQhwI9+9CNUKhWce+65fQtCxnGMxz/+8bjtttu8z1dlb2ZHE+iUTOhtAOBjH/tYX5vnP//5eO1rX4tPfepT+PVf//W+O4mCYPL3f//3SJKEJc+qhG1+fn6gM793717keY6HHnoIj3jEI4Z5qCTuuusunHPOOXjooYfwt3/7t3jBC17A3sZZZ52Fr371q6jX67j11lvxla98BR/72Mdw4YUX4t/+7d/6yvts7N+/H3/5l3+Jj3zkI/jZz36Gb3/72/jLv/xLXHnllZiYmMAf/dEf9bV3zdSnmJ+fB4C+0kFh42g2m+Tzs/k8gH5u12k0GrjyyisxNTU1MHlBqVTCwx/+cDz96U/Hc57zHExOTuJb3/oWPvzhD+O4447DWWedBaAzM+Vf/dVf4X/8j/+BN77xjThw4AB++MMfdmeZK1py/Yd/+Id9/33++efj/e9/P77yla/gZS97GZ74xCcC6Nwsueaaa/CqV71qoBxQEDYbUjInCAFUnf/v//7v40UvelHf/374wx92JanZbGJubq7vf0CvfKHdbg9su9Vq9bWxMTExgUsuuQSVSmVNJRDC9uCGG27Avn37SDO2KdR4F9v3S5V/ff3rXx/OATLQZegLX/gCeUyUi5mZGTznOc/BBz7wAfzxH/8x6vU6qxw1iiI8/vGPx+/93u91n/flL3+ZfRzqffaNMxLWj6mpqULn56Ln9jRN8c53vhP33HMP/uzP/myg/PPaa6/Fddddhz/90z/FBRdcgOc+97l4z3veg6c85Sn40Ic+1E1T9+/fjz//8z9Hu93Gm970Jrz85S/Hxz/+8e4sdMOc8e3lL385APRNE3711Vdj165deMlLXjK0/QjCRiEJkSAEUGMF3vGOd3Rr/3VUqcO3v/1tvPe97+177Oabb8bu3bsxOTnZFSQd9bfQeIgTTzwRQKdEQxBcNJtNfO1rX8OLX/xi8rTUAPBrv/Zr+NCHPoRbb711QKRe//rX45Of/CTe8Y534LnPfW7fFNMqObJNrLBWVJncgw8+iC984Qu4+OKLC23nn//5n3HGGWdgenq67+9qoLz5d5N77rkHAAYmlKA+38att94KoPO+CxvP/v37cfTo0YG/h87PRc/t73//+/HP//zP+JM/+RP88i//8sDj119/fXcNK51f/dVfxUc/+lEcOnQIBw4cANAZk/f5z38ed911FxqNBh796Ed3933KKaf4XjYLdQ1aWVkB0Blj9JWvfAWXXXZZX2leq9VCkiR46KGHsGPHDvZEDoKwUYgQCUIAVSa0d+9enHnmmc52T3va0/DBD35w4O9xHOP000/Hz372s4HH7rzzTjz84Q8PjiVQA86lLGHrcvXVV3dnhfrXf/3X7t9uuukmAMCzn/1svPa1r/Vu45vf/CYqlQo7STn33HOxa9cufOMb3xgYD/fkJz8ZH/7wh3H55ZfjiU98Ii666CKcdtppOHToEG6++WZceOGF+PCHP8zaH4VzzjkH9957L575zGfixz/+cXdchM473/nO4Hbe97734Tvf+Q7OPvtsPOpRj8L09DRuu+02fOtb38Lpp58eFK077rgDl1xyCZ7+9KfjCU94Ak4++WQ88MADuP766xHHMd74xjeyX9s3vvENdoonjA61Bl21Wu2bWOHOO+/sPm6jyLn9Yx/7GG688UZcdtllOO+886zbXVhYsE7aoZIhc3HWUqnUt07d1772NQCwylZRzGvQsWPHkGUZrrrqKlx11VUD7V/+8pfjN37jN3D55ZcP7RgEYZSIEAlCgKc//enYsWMHrr32Wjz1qU8duPO+uLiIvXv34vjjj3feSfy1X/s1fPKTn8TPfvaz7oxE9957L26//fZuKYK+LZ1arYYvfvGL2LNnDx772McO98UJY8Mtt9yCv/qrv+r72/e+9z1873vf6/53SIhuuOEGTE1N4dd//ddZ+965cyde8YpX4FOf+hQeeuihgQkULr30UjzpSU/CBz7wAXz1q19FpVLBiSeeiGc84xl42ctextoXlYMHDwLoTHf//e9/39qGIkRveMMbsGfPHtx666347ne/izzPceqpp+KP//iP8cY3vjF4B/vMM8/E2972Ntx00034+7//eywuLuLkk0/Geeedh7e85S3OxWxd3HPPPfje976HK664olC6JAyf5zznOfj85z+PL3/5y/iv//W/AugkHTfeeCOe8IQndMfVHT58GI1Goy8lpZ7bAeBzn/scPv/5z+OVr3wlXvrSlzqP58CBA/jRj36EpaWl7sKuaZriO9/5DmZnZ71j+RYXF3Hdddfh0Y9+tPcGnotqtYqJiYnuGCigkwR/9rOfBdC58Qd0phF/z3veM/D8q6++GrVaDZdffvlIkmNBGBVRnuf5Rh+EIGwkX/rSl1CpVDA3N4frr78eZ599dvdu20te8hLs3LkT3/jGN/Ce97wHp512Gs4991zs3bsXhw8fxve//3086UlPCt4lrtVq+J3f+R3UajX85m/+JkqlEv7mb/4GWZbhmmuu6UrQNddcg1tuuQXPetazcNJJJ2Fubg433ngjDh8+jLe//e2sqY+F7UWe593ZoW688Ub283/+85/jSU96Et75znfi7W9/+wiOUAA6pbd/8Rd/gZ/+9KcyTfEYceWVV+Lmm2/Gy172MjziEY/AP/zDP+CnP/0pPvShD3Wnir/88stxxx134Oabb+4+j3puv/nmm/GOd7wDBw4cwGte85qB/Z955pndkuyvf/3rePe7341HPOIReOELX4ipqSl885vfxE9+8hO89rWvxate9aru8y677DI88YlPxIEDBzA3N4evfOUrqNfr+MhHPjLw/VI3XO655x5861vfwvOf//zuzY9Xv/rVAIDbb78d73rXu3DeeefhEY94BJrNJv7xH/8R//qv/4oXvvCF3hlV1Xu0tLQ0cHNHEMYdESJh2/Oyl70Mhw4dsj72hS98oXvBuP322/HXf/3XuPPOO9FqtXDCCSfgKU95Ci655BJScnPkyBF89KMfxQ9/+ENkWYYzzjgDl156abcWHAB++MMf4nOf+xzuuusuLC8vY3p6Go9//OPxW7/1W0MtfxC2Ht///vfxK7/yK/jEJz4xMGsVlTe84Q3427/9W9x9993WNYmEtbGwsIBHPvKReM1rXmMtMxI2jmazif/1v/4Xvv71r6NSqeD000/Ha1/72r41pWxCBNDO7ddccw0+85nPOPd/1VVX4Ywzzuj+9w9+8ANce+21uPvuu1Gr1XDKKafg4osvHiiH/ehHP4pbbrkFx44dw+zsLM4880y89rWvtaYzvhJN9ZoefPBBfPKTn8RPf/pTzM/PI45jnHbaaXjBC16AF73oRcEZFEWIhM2KCJEgCIIAoNOx+9jHPoaXvOQlMgPaCLjtttvw5S9/GZdddpl17RpBEARhYxAhEgRBEARBEARh2yLrEAmCIAiCIAiCsG0RIRIEQRAEQRAEYdsiQiQIgiAIgiAIwrZFhEgQBEEQBEEQhG2LCJEgCIIgCIIgCNsWESJBEARBEARBELYtIkSCIAiCIAiCIGxbRIgEQRAEQRAEQdi2iBAJgiAIgiAIgrBtESESBEEQBEEQBGHbIkIkCIIgCIIgCMK25f8HxSbSIgwUWf8AAAAASUVORK5CYII=", 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" ] @@ -1563,7 +2942,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.2" + "version": "3.10.13" } }, "nbformat": 4, From ef279f4c1bc67bec378a8395d9a67e2bede3ed32 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Tue, 27 Aug 2024 05:45:49 -0700 Subject: [PATCH 08/46] Add modified files and new RL parallel script New files: RichardsonLucyParallel.py and RLparallelscript.py Potentially modified files: dataIF_COSI_DC2.py deconvolution_algorithm_base.py image_deconvolution_data_interface_base.py image_deconvolution.py model_base.py --- .../image_deconvolution/RLparallelscript.py | 375 ++++++++++++++++++ cosipy/image_deconvolution/RichardsonLucy.py | 2 +- .../RichardsonLucyParallel.py | 154 +++++++ .../image_deconvolution.py | 14 +- 4 files changed, 542 insertions(+), 3 deletions(-) create mode 100644 cosipy/image_deconvolution/RLparallelscript.py create mode 100644 cosipy/image_deconvolution/RichardsonLucyParallel.py diff --git a/cosipy/image_deconvolution/RLparallelscript.py b/cosipy/image_deconvolution/RLparallelscript.py new file mode 100644 index 00000000..1277dbb4 --- /dev/null +++ b/cosipy/image_deconvolution/RLparallelscript.py @@ -0,0 +1,375 @@ +import os +from pathlib import Path +import logging +import argparse + +# logging setup +logger = logging.getLogger(__name__) + +# argparse setup +parser = argparse.ArgumentParser() +parser.add_argument("--numrows", type=int, dest='numrows', help="Number of rows in the response matrix") +parser.add_argument("--numcols", type=int, dest='numcols', help="Number of columns in the response matrix") +parser.add_argument("--base_dir", type=str, dest='base_dir', help="Current working directory and where configuration file is assumed to lie") +parser.add_argument("--config_file", type=str, dest='config_file', help="Name of configuration file (assumed to lie in CWD)") +args = parser.parse_args() + +# Import third party libraries +import numpy as np +from mpi4py import MPI +import h5py +from yayc import Configurator + +# Load configuration file +config = Configurator.open(f'{args.base_dir}/{args.config_file}') + +# Number of elements in data space (ROWS) and model space (COLS) +NUMROWS = args.numrows # TODO: Ideally, for row-major form to exploit caching, NUMROWS must be smaller than NUMCOLS +NUMCOLS = args.numcols + +# Define MPI and iteration misc variables +MASTER = 0 # Indicates master process +MAXITER = config.get('deconvolution:parameter:iteration_max', 10) + +# FILE_DIR = Path(os.path.dirname(os.path.abspath(__file__))) +BASE_DIR = Path(args.base_dir) +RESULTS_DIR = BASE_DIR / config.get('deconvolution:parameter:save_results_directory', './results') + +''' +Response matrix +''' +def load_response_matrix(comm, start_row, end_row, filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r", driver="mpio", comm=comm) as f1: + dataset = f1["response_matrix"] + R = dataset[start_row:end_row, :] + return R + +''' +Response matrix transpose +''' +def load_response_matrix_transpose(comm, start_col, end_col, filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r", driver="mpio", comm=comm) as f1: + dataset = f1["response_matrix"] + RT = dataset[:, start_col:end_col] + return RT + +''' +Response matrix summed along axis=i +''' +def load_axis0_summed_response_matrix(filename='response_matrix.h5'): + with h5py.File(BASE_DIR / filename, "r") as f1: + dataset = f1["response_vector"] + Rj = dataset[:] + return Rj + +''' +Sky model +''' +def initial_sky_model(model_init_val=[1e-4]): + M0 = np.ones(NUMCOLS, dtype=np.float64) * float(model_init_val[0]) # Initial guess according to image_deconvolution.py. TODO: Make this more general than element 0 + return M0 + +''' +Background model +''' +def load_bg_model(filename='bg.csv'): + bg = np.loadtxt(filename) + return bg + +''' +Observed data +''' +def load_event_data(filename='event.csv'): + event = np.loadtxt(filename) + return event + +def register_result(iter, M, delta): + """ + The values below are stored at the end of each iteration. + - iteration: iteration number + - model: updated image + - delta_model: delta map after M-step + - processed_delta_model: delta map after post-processing + - alpha: acceleration parameter in RL algirithm + - background_normalization: optimized background normalization + - loglikelihood: log-likelihood + """ + + this_result = {"iteration": iter, + "model": M, + "delta_model": delta, + # "processed_delta_model": copy.deepcopy(self.processed_delta_model), TODO: The RL parallel implementation does not currently support smooth convergence through weighting, background normalization, or likelihood calculation + # "background_normalization": copy.deepcopy(self.dict_bkg_norm), + # "alpha": self.alpha, + # "loglikelihood": copy.deepcopy(self.loglikelihood_list) + } + + # # show intermediate results + # logger.info(f' alpha: {this_result["alpha"]}') + # logger.info(f' background_normalization: {this_result["background_normalization"]}') + # logger.info(f' loglikelihood: {this_result["loglikelihood"]}') + + return this_result + +def save_results(results): + ''' + NOTE: Copied from RichardsonLucy.py + ''' + logger.info('Saving results in {RESULTS_DIR}') + # model + for this_result in results: + iteration_count = this_result["iteration"] + # this_result["model"].write(f"{RESULTS_DIR}/model_itr{iteration_count}.hdf5", overwrite = True) # TODO: numpy arrays do not support write_to_hdf5 as a method. Need to ensure rest of code is modified to support cosipy.image_deconvolution.allskyimage.AllSkyImageModel + # this_result["delta_model"].write(f"{RESULTS_DIR}/delta_model_itr{iteration_count}.hdf5", overwrite = True) + # this_result["processed_delta_model"].write(f"{RESULTS_DIR}/processed_delta_model_itr{iteration_count}.hdf5", overwrite = True) TODO: processed_delta_model here is not different from delta_model + np.savetxt(f'{RESULTS_DIR}/model_itr{iteration_count}.csv', this_result['model'], delimiter=',') + np.savetxt(f'{RESULTS_DIR}/delta_model_itr{iteration_count}.csv', this_result['delta_model'], delimiter=',') + + # TODO: The following will be enabled once the respective calculations are incorporated + # #fits + # primary_hdu = fits.PrimaryHDU() + + # col_iteration = fits.Column(name='iteration', array=[float(result['iteration']) for result in self.results], format='K') + # col_alpha = fits.Column(name='alpha', array=[float(result['alpha']) for result in self.results], format='D') + # cols_bkg_norm = [fits.Column(name=key, array=[float(result['background_normalization'][key]) for result in self.results], format='D') + # for key in self.dict_bkg_norm.keys()] + # cols_loglikelihood = [fits.Column(name=f"{self.dataset[i].name}", array=[float(result['loglikelihood'][i]) for result in self.results], format='D') + # for i in range(len(self.dataset))] + + # table_alpha = fits.BinTableHDU.from_columns([col_iteration, col_alpha]) + # table_alpha.name = "alpha" + + # table_bkg_norm = fits.BinTableHDU.from_columns([col_iteration] + cols_bkg_norm) + # table_bkg_norm.name = "bkg_norm" + + # table_loglikelihood = fits.BinTableHDU.from_columns([col_iteration] + cols_loglikelihood) + # table_loglikelihood.name = "loglikelihood" + + # hdul = fits.HDUList([primary_hdu, table_alpha, table_bkg_norm, table_loglikelihood]) + # hdul.writeto(f'{RESULTS_DIR}/results.fits', overwrite=True) + +def main(): + # Set up MPI + comm = MPI.COMM_WORLD + numtasks = comm.Get_size() + taskid = comm.Get_rank() + + # Calculate the indices in Rij that the process has to parse. My hunch is that calculating these scalars individually will be faster than the MPI send broadcast overhead. + averow = NUMROWS // numtasks + extra_rows = NUMROWS % numtasks + start_row = taskid * averow + end_row = (taskid + 1) * averow if taskid < (numtasks - 1) else NUMROWS + + # Calculate the indices in Rji, i.e., Rij transpose, that the process has to parse. + avecol = NUMCOLS // numtasks + extra_cols = NUMCOLS % numtasks + start_col = taskid * avecol + end_col = (taskid + 1) * avecol if taskid < (numtasks - 1) else NUMCOLS + + # Initialise vectors required by all processes + epsilon = np.zeros(NUMROWS) # All gatherv-ed. Explicit variable declaration. + epsilon_fudge = 1e-12 # To prevent divide-by-zero and underflow errors. Value taken from `almost_zero = 1e-12` in dataIF_COSI_DC2.py + + # Initialise epsilon_slice and C_slice. Explicit variable declarations. + epsilon_slice = np.zeros(end_row - start_row) + C_slice = np.zeros(end_col - start_col) + + # Load R and RT into memory (single time if response matrix doesn't + # change with time) + R = load_response_matrix(comm, start_row, end_row) + RT = load_response_matrix_transpose(comm, start_col, end_col) + + # Loaded and broadcasted by master. + M = np.empty(NUMCOLS, dtype=np.float64) + d = np.empty(NUMROWS, dtype=np.float64) + bg = np.zeros(NUMROWS) + +# ****************************** MPI ****************************** + +# **************************** Part I ***************************** + + '''*************** Master ***************''' + + if taskid == MASTER: + + # Pretty print definitions + linebreak_stars = '**********************' + linebreak_dashes = '----------------------' + + # Log input information (Only master node does this) + save_results_flag = config.get('deconvolution:parameter:save_results', False) # Extract from config file + logger.info(linebreak_stars) + logger.info(f'Number of elements in data space: {NUMROWS}') + logger.info(f'Number of elements in model space: {NUMCOLS}') + logger.info(f'Base directory: {BASE_DIR}') + if save_results_flag == True: + logger.info(f'Results directory (if save_results flag is set to True): {RESULTS_DIR}') + logger.info(f'Configuration filename: {args.config_file}') + logger.info(f'Master node: {MASTER}') + logger.info(f'Maximum number of RL iterations: {MAXITER}') + + # Load Rj vector (response matrix summed along axis=i) + Rj = load_axis0_summed_response_matrix() + + # Generate initial sky model from configuration file + M = initial_sky_model(model_init_val=config.get('model_definition:initialization:parameter:value', [1e-4])) + + # Load event data and background model (intermediate files created in RichardsonLucyParallel.py) + bg = load_bg_model() + d = load_event_data() + + # Sanity check: print d + print() + print('Observed data-space d vector:') + print(d) + ## Pretty print + print() + print(linebreak_stars) + + # Initialise C vector. Only master requires full length. Explicit variable declaration. + C = np.empty(NUMCOLS, dtype=np.float64) + + # Initialise update delta vector. Explicit variable declaration. + delta = np.empty(NUMCOLS, dtype=np.float64) + + # Initialise list for results. See function register_result() for list elements. + results = [] + + '''*************** Worker ***************''' + + if taskid > MASTER: + # Only separate if... clause for NON-MASTER processes. + # Initialise C vector to None. Only master requires full length. + C = None + + # Broadcast d vector + comm.Bcast([d, MPI.DOUBLE], root=MASTER) + + # Scatter bg vector to epsilon_BG + comm.Bcast([bg, MPI.DOUBLE], root=MASTER) + # comm.Scatter(bg, [epsilon_BG, recvcounts, displacements, MPI.DOUBLE]) + + # print(f"TaskID {taskid}, gathered broadcast") + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon_BG') + # print(bg) + # print() + +# **************************** Part IIa ***************************** + + '''***************** Begin Iterative Segment *****************''' + # Set up initial values for iterating variables. + # Exit if: + ## 1. Max iterations are reached + # for iter in tqdm(range(MAXITER)): + for iter in range(MAXITER): + + '''*************** Master ***************''' + if taskid == MASTER: + # Pretty print - starting + print(f"Starting iteration {iter + 1}") + # logger.info(f"## Iteration {self.iteration_count}/{self.iteration_max} ##") + # logger.info("<< E-step >>") + + + # Calculate epsilon vector and all gatherv + + '''**************** All *****************''' + + '''Synchronization Barrier 1''' + # Broadcast M vector + comm.Bcast([M, MPI.DOUBLE], root=MASTER) + + # Calculate epsilon slice + epsilon_BG = bg[start_row:end_row] # TODO: Change the way epsilon_BG is loaded. Make it taskID dependent through MPI.Scatter for example. Use `recvcounts` + epsilon_slice = np.dot(R, M) + epsilon_BG + epsilon_fudge # TODO: For a more general implementation, see calc_expectation() in dataIF_COSI_DC2.py + + '''Synchronization Barrier 2''' + # All vector gather epsilon slices + recvcounts = [averow] * (numtasks-1) + [averow + extra_rows] + displacements = np.arange(numtasks) * averow + comm.Allgatherv(epsilon_slice, [epsilon, recvcounts, displacements, MPI.DOUBLE]) + + # Sanity check: print epsilon + # if taskid == MASTER: + # print('epsilon') + # print(epsilon) + # print(epsilon.min(), epsilon.max()) + # print() + +# **************************** Part IIb ***************************** + + # Calculate C vector and gatherv + + '''**************** All *****************''' + + # Calculate C slice + C_slice = np.dot(RT.T, d/epsilon) + + '''Synchronization Barrier 3''' + # All vector gather C slices + recvcounts = [avecol] * (numtasks-1) + [avecol + extra_cols] + displacements = np.arange(numtasks) * avecol + comm.Gatherv(C_slice, [C, recvcounts, displacements, MPI.DOUBLE], root=MASTER) + +# **************************** Part IIc ***************************** + + # Iterative update of model-space M vector + + if taskid == MASTER: + + # logger.info("<< M-step >>") + + # Sanity check: print C + # print('C') + # print(C) + # print(C.min(), C.max()) + # print() + + delta = C / Rj - 1 + M = M + delta * M # Allows for optimization features presented in Siegert et al. 2020 + + # Sanity check: print M + # print('M') + # print(np.round(M, 5)) + # print(np.round(M.max(), 5)) + + # Sanity check: print delta + # print('delta') + # print(delta) + + # Pretty print - completion + print(f"Done") + print(linebreak_dashes) + + # Save iteration + if save_results_flag == True: + results.append(register_result(iter, M, delta)) + + '''****************** End Iterative Segment ******************''' + + # Print converged M + if taskid == MASTER: + # logger.info("<< Registering Result >>") + print('Converged M vector:') + print(np.round(M, 5)) + print(np.round(M.max(), 5)) + print(np.sum(M)) + print() + + if save_results_flag == True: + save_results(results) + + # MAXITER + if iter == (MAXITER - 1): + print(f'Reached maximum iterations = {MAXITER}') + print(linebreak_stars) + print() + + # MPI Shutdown + MPI.Finalize() + +if __name__ == "__main__": + main() diff --git a/cosipy/image_deconvolution/RichardsonLucy.py b/cosipy/image_deconvolution/RichardsonLucy.py index 99e038d2..46eedc57 100644 --- a/cosipy/image_deconvolution/RichardsonLucy.py +++ b/cosipy/image_deconvolution/RichardsonLucy.py @@ -36,7 +36,7 @@ class RichardsonLucy(DeconvolutionAlgorithmBase): """ - def __init__(self, initial_model, dataset, mask, parameter): + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath = None): DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py new file mode 100644 index 00000000..031266d2 --- /dev/null +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -0,0 +1,154 @@ +import os +import subprocess +import logging +logger = logging.getLogger(__name__) + +# Import third party libraries +import numpy as np +import h5py +# from histpy import Histogram + +from .deconvolution_algorithm_base import DeconvolutionAlgorithmBase + +class RichardsonLucyParallel(DeconvolutionAlgorithmBase): + """ + NOTE: Comments copied from RichardsonLucy.py + A class for a parallel implementation of the Richardson- + Lucy algorithm. + + An example of parameter is as follows. + + iteration_max: 100 + minimum_flux: + value: 0.0 + unit: "cm-2 s-1 sr-1" + background_normalization_optimization: True + """ + + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath): + """ + NOTE: Copied from RichardsonLucy.py + """ + + DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) + + # TODO: these RL algorithm improvements are yet to be implemented/utilized in this file + # self.do_acceleration = parameter.get('acceleration', False) + + # self.alpha_max = parameter.get('alpha_max', 1.0) + + # self.do_response_weighting = parameter.get('response_weighting', False) + # if self.do_response_weighting: + # self.response_weighting_index = parameter.get('response_weighting_index', 0.5) + + # self.do_smoothing = parameter.get('smoothing', False) + # if self.do_smoothing: + # self.smoothing_fwhm = parameter['smoothing_FWHM']['value'] * u.Unit(parameter['smoothing_FWHM']['unit']) + # logger.info(f"Gaussian filter with FWHM of {self.smoothing_fwhm} will be applied to delta images ...") + + self.do_bkg_norm_optimization = parameter.get('background_normalization_optimization', False) + if self.do_bkg_norm_optimization: + self.dict_bkg_norm_range = parameter.get('background_normalization_range', {key: [0.0, 100.0] for key in self.dict_bkg_norm.keys()}) + + self.save_results = parameter.get('save_results', False) + self.save_results_directory = parameter.get('save_results_directory', './results') + + if self.save_results is True: + if os.path.isdir(self.save_results_directory): + logger.warning(f"A directory {self.save_results_directory} already exists. Files in {self.save_results_directory} may be overwritten. Make sure that is not a problem.") + else: + os.makedirs(self.save_results_directory) + + # Specific to parallel implementation + image_response = self.dataset[0]._image_response + self.numproc = parameter.get('numproc', 1) + self.iteration_max = parameter.get('iteration_max', 10) + self.base_dir = os.getcwd() + self.data_dir = parameter.get('data_dir', './data') # NOTE: Data should ideally be present in disk scratch space. + self.numrows = np.product(image_response.contents.shape[-3:]) # Em, Phi, PsiChi. NOTE: Change the "-3" if more general model space definitions are expected + self.numcols = np.product(image_response.contents.shape[:-3]) # Remaining columns + self.config_file = parameter_filepath + + def initialization(self): + """ + initialization before running the image deconvolution + """ + # Flatten and write dense bkg and events to scratch space. + self.write_intermediate_files_to_disk() + + def write_intermediate_files_to_disk(self): + # Event + event = self.dataset[0].event.contents.flatten() + np.savetxt(self.base_dir + '/event.csv', event) + + # Background + bg = np.zeros(len(event)) + bg_models = self.dataset[0]._bkg_models + for key in bg_models: + bg += bg_models[key].contents.flatten() + np.savetxt(self.base_dir + '/bg.csv', bg) + + # Response matrix + image_response = self.dataset[0]._image_response + new_shape = (self.numrows, self.numcols) + ndim = image_response.contents.ndim + with h5py.File(self.base_dir + '/response_matrix.h5', 'w') as output_file: + dset1 = output_file.create_dataset('response_matrix', data=np.transpose(image_response.contents, + np.take(np.arange(ndim), + range(ndim-3, 2*ndim-3), + mode='wrap') + ).reshape(new_shape)) # NOTE: Change the "ndim-3" if more general model space definitions are expected + logger.info(f'Shape of response matrix {dset1.shape}') + dset2 = output_file.create_dataset('response_vector', data=np.sum(dset1, axis=0)) + logger.info(f'Shape of response vector summed along axis=0 {dset2.shape}') + + def iteration(self): + """ + Performs all iterations of image deconvolution. + NOTE: Overrides implementation in deconvolution_algorithm_base.py and invokes an external script + """ + + # All arguments must be passed as type=str. Explicitly type cast boolean and number to string. + FILE_DIR = os.path.dirname(os.path.abspath(__file__)) # Path to directory containing RichardsonLucyParallel.py + logger.info(f"Subprocess call to run RLparallelscript.py at '{FILE_DIR}'") + + # RLparallelscript.py will be installed in the same directory as RichardsonLucyParallel.py + stdout = subprocess.run(args=["mpiexec", "-n", str(self.numproc), + "python", FILE_DIR + "/RLparallelscript.py", + "--numrows", str(self.numrows), + "--numcols", str(self.numcols), + "--base_dir", str(self.base_dir), + "--config_file", str(self.config_file) + ], env=os.environ) + logger.info(stdout) + + # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. + # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. + return True + + def finalization(self): + """ + finalization after running the image deconvolution + """ + # Delete intermediate files + self.remove_intermediate_files_from_disk() + + def remove_intermediate_files_from_disk(self): + # Ensure that the number of deletions corresponds to the + # number of file creations in write_... function + os.remove(self.base_dir + '/event.csv') + os.remove(self.base_dir + '/bg.csv') + os.remove(self.base_dir + '/response_matrix.h5') + + def pre_processing(self): + pass + def Estep(self): + pass + def Mstep(self): + pass + def post_processing(self): + pass + def check_stopping_criteria(self): + pass + def register_result(self): + pass \ No newline at end of file diff --git a/cosipy/image_deconvolution/image_deconvolution.py b/cosipy/image_deconvolution/image_deconvolution.py index 362108ac..9720875f 100644 --- a/cosipy/image_deconvolution/image_deconvolution.py +++ b/cosipy/image_deconvolution/image_deconvolution.py @@ -9,13 +9,14 @@ from .RichardsonLucy import RichardsonLucy from .RichardsonLucySimple import RichardsonLucySimple +from .RichardsonLucyParallel import RichardsonLucyParallel class ImageDeconvolution: """ A class to reconstruct all-sky images from COSI data based on image deconvolution methods. """ model_classes = {"AllSkyImage": AllSkyImageModel} - deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple} + deconvolution_algorithm_classes = {"RL": RichardsonLucy, "RLsimple": RichardsonLucySimple, "RLparallel": RichardsonLucyParallel} def __init__(self): self._dataset = None @@ -61,6 +62,7 @@ def read_parameterfile(self, parameter_filepath): Path of parameter file. """ + self._parameter_filepath = parameter_filepath self._parameter = Configurator.open(parameter_filepath) logger.debug(f"parameter file for image deconvolution was set -> {parameter_filepath}") @@ -79,6 +81,13 @@ def parameter(self): """ return self._parameter + @property + def parameter_filepath(self): + """ + Return the registered parameter filepath. + """ + return self._parameter_filepath + def override_parameter(self, *args): """ Override parameter @@ -198,7 +207,8 @@ def register_deconvolution_algorithm(self): self._deconvolution = self._deconvolution_class(initial_model = self.initial_model, dataset = self.dataset, mask = self.mask, - parameter = algorithm_parameter) + parameter = algorithm_parameter, + parameter_filepath = self.parameter_filepath) logger.info("---- parameters ----") logger.info(parameter_deconvolution.dump()) From 871c9a87b70f8b8c8fbc693f855a1ca57fe9a9b2 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Tue, 27 Aug 2024 05:48:53 -0700 Subject: [PATCH 09/46] Another tiny change RichardsonLucySimple.py and RichardsonLucy.py were modified to include the propagation of the config file from the user facing image_deconvolution object to the respective deconvolution algorithms --- cosipy/image_deconvolution/RichardsonLucySimple.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cosipy/image_deconvolution/RichardsonLucySimple.py b/cosipy/image_deconvolution/RichardsonLucySimple.py index 65fde9d6..c9eea0c1 100644 --- a/cosipy/image_deconvolution/RichardsonLucySimple.py +++ b/cosipy/image_deconvolution/RichardsonLucySimple.py @@ -22,7 +22,7 @@ class RichardsonLucySimple(DeconvolutionAlgorithmBase): background_normalization_optimization: True """ - def __init__(self, initial_model, dataset, mask, parameter): + def __init__(self, initial_model, dataset, mask, parameter, parameter_filepath = None): DeconvolutionAlgorithmBase.__init__(self, initial_model, dataset, mask, parameter) From 27c8afe199b6e16dfb0fd37a7f12ccc049c21906 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Thu, 29 Aug 2024 09:35:52 -0700 Subject: [PATCH 10/46] Modified configuration file for RLparallel --- .../imagedeconvolution_parfile_gal_511keV.yml | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 53e53ae7..1577573d 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -1,7 +1,9 @@ author: Hiroki Yoneda -date: 2024-06-12 +date: 2024-06-12 # Modified by Anaya to include deconvolution:parameter:numproc on 2024-08-23 + model_definition: class: "AllSkyImage" + property: coordinate: "galactic" nside: 16 @@ -10,15 +12,18 @@ model_definition: value: [509.0, 513.0] unit: "keV" unit: "cm-2 s-1 sr-1" # do not change it as for now + initialization: algorithm: "flat" # more methods, e.g., simple-backprojection, user-defined, would be implemented. parameter: value: [1e-4] #the number of these values should be the same as "the number of energy_edges - 1". unit: "cm-2 s-1 sr-1" # do not change it as for now + deconvolution: - algorithm: "RL" + algorithm: "RL" # Choose from RL, RLsimple and RLparallel + parameter: - iteration_max: 10 + iteration_max: 50 acceleration: True alpha_max: 10.0 response_weighting: True @@ -29,5 +34,6 @@ deconvolution: unit: "deg" background_normalization_optimization: True background_normalization_range: {"albedo": [0.01, 10.0]} - save_results: False - save_results_directory: "./results" \ No newline at end of file + save_results: True + save_results_directory: "./results" # Relative file path + numproc: 6 # Number of MPI threads to spawn. Limited by number of nodes available. Only applicable for algorithm: "RLparallel" \ No newline at end of file From f044589d5e4d83a0847636f38880472389c6e230 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Fri, 18 Oct 2024 09:26:47 -0700 Subject: [PATCH 11/46] git fetch changes unclear. Performing a commit to avoid data loss. --- .../RichardsonLucyParallel.py | 25 +- ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 1823 +++-------------- .../imagedeconvolution_parfile_gal_511keV.yml | 6 +- .../511keV-DC2-ScAtt-DataReduction.ipynb | 126 +- .../tutorials/response/DetectorResponse.ipynb | 1314 +++++++++++- 5 files changed, 1585 insertions(+), 1709 deletions(-) diff --git a/cosipy/image_deconvolution/RichardsonLucyParallel.py b/cosipy/image_deconvolution/RichardsonLucyParallel.py index 745dd995..031266d2 100644 --- a/cosipy/image_deconvolution/RichardsonLucyParallel.py +++ b/cosipy/image_deconvolution/RichardsonLucyParallel.py @@ -109,19 +109,18 @@ def iteration(self): """ # All arguments must be passed as type=str. Explicitly type cast boolean and number to string. - # FILE_DIR = os.path.dirname(os.path.abspath(__file__)) # Path to directory containing RichardsonLucyParallel.py - # logger.info(f'Subprocess call to run RLparallelscript.py at {FILE_DIR}') - - # stdout = subprocess.check_output(args=["mpiexec", "-n", str(self.numproc), - # "python", "mpitest.py", # RLparallelscript.py will be installed in the same directory as RichardsonLucyParallel.py - # "--numrows", str(self.numrows), - # "--numcols", str(self.numcols), - # "--base_dir", str(self.base_dir), - # "--config_file", str(self.config_file) - # ], text=True) - # print(stdout) - - subprocess.run() + FILE_DIR = os.path.dirname(os.path.abspath(__file__)) # Path to directory containing RichardsonLucyParallel.py + logger.info(f"Subprocess call to run RLparallelscript.py at '{FILE_DIR}'") + + # RLparallelscript.py will be installed in the same directory as RichardsonLucyParallel.py + stdout = subprocess.run(args=["mpiexec", "-n", str(self.numproc), + "python", FILE_DIR + "/RLparallelscript.py", + "--numrows", str(self.numrows), + "--numcols", str(self.numcols), + "--base_dir", str(self.base_dir), + "--config_file", str(self.config_file) + ], env=os.environ) + logger.info(stdout) # RLparallelscript already contains check_stopping_criteria and iteration_max break condition. # NOTE: RichardsonLucy.py currently does not support a sophisticated break condition. diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index e74a1799..f8f62c51 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -42,12 +42,12 @@ { "data": { "text/html": [ - "
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        "                  require the C/C++ interface (currently HAWC)                                                     \n",
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        "                  performances in 3ML                                                                              \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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@@ -287,7 +287,7 @@
        "
\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=47220;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=527768;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=470712;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=726622;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -341,213 +341,6 @@ " 'figure.figsize': (9.6, 5.4), 'figure.dpi': 100})" ] }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d6b01b44", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hello, World! I am process 0 of 4.\n", - "\n", - "Hello, World! I am process 1 of 4.\n", - "\n", - "Hello, World! I am process 2 of 4.\n", - "\n", - "Hello, World! I am process 3 of 4.\n", - "\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n", - "184320\n", - "3072\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\n", - "imagedeconvolution_parfile_gal_511keV.yml\n", - "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS/mpitest.py\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 10/10 [00:00<00:00, 19231.10it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "CompletedProcess(args=['mpiexec', '-n', '4', 'python', 'mpitest.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml'], returncode=0)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "subprocess.run(args=[\"mpiexec\", \"-n\", str(4), \"python\", \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py\", \n", - " \"--numrows\", str(184320),\n", - " \"--numcols\", str(3072),\n", - " \"--base_dir\", str('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS'),\n", - " \"--config_file\", str('imagedeconvolution_parfile_gal_511keV.yml')\n", - " ], text=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "a89ac003", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "python: can't open file '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py': [Errno 2] No such file or directory\n", - "--------------------------------------------------------------------------\n", - "Primary job terminated normally, but 1 process returned\n", - "a non-zero exit code. Per user-direction, the job has been aborted.\n", - "--------------------------------------------------------------------------\n", - "--------------------------------------------------------------------------\n", - "mpiexec detected that one or more processes exited with non-zero status, thus causing\n", - "the job to be terminated. The first process to do so was:\n", - "\n", - " Process name: [[64571,1],0]\n", - " Exit code: 2\n", - "--------------------------------------------------------------------------\n" - ] - }, - { - "ename": "CalledProcessError", - "evalue": "Command '['mpiexec', '-n', '1', 'python', '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml']' returned non-zero exit status 2.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mCalledProcessError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[17], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msubprocess\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m stdout \u001b[38;5;241m=\u001b[39m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheck_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmpiexec\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m-n\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpython\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/RLparallelscript.py\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--numrows\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m184320\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--numcols\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3072\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--base_dir\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--config_file\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mimagedeconvolution_parfile_gal_511keV.yml\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;66;03m# print(stdout)\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/subprocess.py:421\u001b[0m, in \u001b[0;36mcheck_output\u001b[0;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 418\u001b[0m empty \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 419\u001b[0m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minput\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m empty\n\u001b[0;32m--> 421\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpopenargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheck\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 422\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mstdout\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/subprocess.py:526\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 524\u001b[0m retcode \u001b[38;5;241m=\u001b[39m process\u001b[38;5;241m.\u001b[39mpoll()\n\u001b[1;32m 525\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check \u001b[38;5;129;01mand\u001b[39;00m retcode:\n\u001b[0;32m--> 526\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CalledProcessError(retcode, process\u001b[38;5;241m.\u001b[39margs,\n\u001b[1;32m 527\u001b[0m output\u001b[38;5;241m=\u001b[39mstdout, stderr\u001b[38;5;241m=\u001b[39mstderr)\n\u001b[1;32m 528\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m CompletedProcess(process\u001b[38;5;241m.\u001b[39margs, retcode, stdout, stderr)\n", - "\u001b[0;31mCalledProcessError\u001b[0m: Command '['mpiexec', '-n', '1', 'python', '/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml']' returned non-zero exit status 2." - ] - } - ], - "source": [ - "import subprocess\n", - "stdout = subprocess.check_output(args=[\"mpiexec\", \"-n\", str(1), \"python\", \"/Users/pengun/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution\"+\"/RLparallelscript.py\", \n", - " \"--numrows\", str(184320),\n", - " \"--numcols\", str(3072),\n", - " \"--base_dir\", str('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS'),\n", - " \"--config_file\", str('imagedeconvolution_parfile_gal_511keV.yml')\n", - " ], text=True)\n", - "# print(stdout)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "cb594af4", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Observed data-space d vector:\n", - "[0. 0. 0. ... 0. 1. 0.]\n", - "\n", - "**********************\n", - "Starting iteration 1\n", - "Done\n", - "----------------------\n", - "Starting iteration 2\n", - "Done\n", - "----------------------\n", - "Starting iteration 3\n", - "Done\n", - "----------------------\n", - "Starting iteration 4\n", - "Done\n", - "----------------------\n", - "Starting iteration 5\n", - "Done\n", - "----------------------\n", - "Starting iteration 6\n", - "Done\n", - "----------------------\n", - "Starting iteration 7\n", - "Done\n", - "----------------------\n", - "Starting iteration 8\n", - "Done\n", - "----------------------\n", - "Starting iteration 9\n", - "Done\n", - "----------------------\n", - "Starting iteration 10\n", - "Done\n", - "----------------------\n", - "Converged M vector:\n", - "[0. 0. 0. ... 0. 0. 0.]\n", - "2e-05\n", - "0.0027317294547643117\n", - "\n", - "Reached maximum iterations = 10\n", - "**********************\n", - "\n", - "\n" - ] - } - ], - "source": [ - "print(stdout)" - ] - }, { "cell_type": "markdown", "id": "00f20cda-81f8-4685-b9c4-f9423e5ebcf7", @@ -581,7 +374,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "cafd42c7-7f7f-4e6e-acd7-8e76eb5160dc", "metadata": {}, "outputs": [], @@ -595,7 +388,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "ae368f5f-2d30-4ba6-a152-c5bbb4187471", "metadata": {}, "outputs": [], @@ -608,7 +401,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "dddb7361-a523-42b4-93fe-da0b3ce75deb", "metadata": {}, "outputs": [], @@ -639,7 +432,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "9cae1835-e54b-4720-b3a6-196c42cbd1ce", "metadata": {}, "outputs": [], @@ -663,7 +456,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "801ba251-96e0-4243-8f55-1678823f1d58", "metadata": {}, "outputs": [], @@ -687,7 +480,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "f224b957-d0df-4b4b-98dd-90d3a5bda3fb", "metadata": {}, "outputs": [], @@ -707,7 +500,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "24289425-380b-4d26-a7c0-cbbd5c58e7b2", "metadata": {}, "outputs": [], @@ -727,7 +520,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "41371ac9", "metadata": {}, "outputs": [], @@ -738,7 +531,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "e0f3dcae-5d3c-45af-931d-057d5681859c", "metadata": {}, "outputs": [], @@ -760,7 +553,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "88efdbfa-aa5e-40b3-bdd6-2635946318e4", "metadata": {}, "outputs": [ @@ -773,7 +566,7 @@ "" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -792,7 +585,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "b5b295cf-0a96-4501-aa4e-4182a21dfe63", "metadata": {}, "outputs": [ @@ -800,8 +593,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.62 s, sys: 20.5 s, total: 24.1 s\n", - "Wall time: 52.6 s\n" + "CPU times: user 3.08 s, sys: 12.7 s, total: 15.8 s\n", + "Wall time: 29.3 s\n" ] } ], @@ -815,7 +608,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "id": "fbdbd818-8a58-4d25-a657-d43fc7f88ea4", "metadata": {}, "outputs": [ @@ -825,7 +618,7 @@ "array(['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi'], dtype='>\n", + "A directory ./results already exists. Files in ./results may be overwritten. Make sure that is not a problem.\n", "---- parameters ----\n", - "algorithm: RL\n", + "algorithm: RLparallel\n", "parameter:\n", " acceleration: true\n", " alpha_max: 2.0\n", @@ -1184,7 +978,7 @@ " numproc: 6\n", " response_weighting: false\n", " response_weighting_index: 0.5\n", - " save_results: false\n", + " save_results: true\n", " save_results_directory: ./results\n", " smoothing: false\n", " smoothing_FWHM:\n", @@ -1201,8 +995,8 @@ "image_deconvolution.override_parameter(\"deconvolution:parameter:alpha_max = 2.0\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:smoothing = False\")\n", "image_deconvolution.override_parameter(\"deconvolution:parameter:response_weighting = False\")\n", - "image_deconvolution.override_parameter(\"deconvolution:parameter:save_results = False\")\n", - "image_deconvolution.override_parameter(\"deconvolution:algorithm = RL\")\n", + "# image_deconvolution.override_parameter(\"deconvolution:parameter:save_results = False\")\n", + "# image_deconvolution.override_parameter(\"deconvolution:algorithm = RL\")\n", "\n", "image_deconvolution.initialize()" ] @@ -1219,7 +1013,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "a57fbf71-2fcc-48c4-9ac7-4c545dca67c9", "metadata": { "collapsed": true, @@ -1235,13 +1029,14 @@ "text": [ "#### Image Deconvolution Starts ####\n", "<< Initialization >>\n", - "The expected count histograms were calculated with the initial model map.\n" + "Shape of response matrix (184320, 3072)\n", + "Shape of response vector summed along axis=0 (3072,)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0a5572e469264dd283ae5bdcb0d32774", + "model_id": "19f46d373b214182a465a877ecfd9be2", "version_major": 2, "version_minor": 0 }, @@ -1256,1310 +1051,175 @@ "name": "stdout", "output_type": "stream", "text": [ - "## Iteration 1/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.190086058358472}\n", - " loglikelihood: [389620.43700901093]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 2/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.1025288937649729}\n", - " loglikelihood: [397966.1184134454]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 3/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0758137427893717}\n", - " loglikelihood: [404486.16370658483]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 4/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0350780054934294}\n", - " loglikelihood: [409379.8773129297]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 5/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 1.0067984138659716}\n", - " loglikelihood: [412636.6223042265]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 6/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.985156644640505}\n", - " loglikelihood: [414652.8432038162]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 7/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "Subprocess call to run RLparallelscript.py at '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution'\n", "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9720022993182517}\n", - " loglikelihood: [415871.5890431596]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 8/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "Observed data-space d vector:\n", + "[0. 0. 0. ... 0. 1. 0.]\n", "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9647331909406436}\n", - " loglikelihood: [416634.49362002616]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 9/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9618007024814392}\n", - " loglikelihood: [417146.494831466]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 10/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9614669811731035}\n", - " loglikelihood: [417517.0766809179]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 11/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - 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[418377.4557194025]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 15/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.970708567948022}\n", - " loglikelihood: [418512.5036855284]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 16/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9724635379800978}\n", - " loglikelihood: [418628.95036220574]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 17/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9739955171908575}\n", - " loglikelihood: [418730.3084008504]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 18/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - 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"<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9773911433114139}\n", - " loglikelihood: [418967.70833261264]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 21/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.978200663714772}\n", - " loglikelihood: [419030.1679826325]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 22/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9788888402984666}\n", - " loglikelihood: [419086.2736994118]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 23/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9794765199076383}\n", - " loglikelihood: [419136.89394879853]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 24/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.979981789196119}\n", - " loglikelihood: [419182.7493856037]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 25/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9804200184058396}\n", - " loglikelihood: [419224.4438976394]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 26/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9808040644678145}\n", - " loglikelihood: [419262.48783887096]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 27/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9811445475083197}\n", - " loglikelihood: [419297.3156418806]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 28/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.981450145770878}\n", - " loglikelihood: [419329.29936073]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 29/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9817278823799749}\n", - " loglikelihood: [419358.7592438542]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 30/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9819833894554747}\n", - " loglikelihood: [419385.9721169963]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 31/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.982221143783738}\n", - " loglikelihood: [419411.1781302573]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 32/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9824446724033364}\n", - " loglikelihood: [419434.5862642322]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 33/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9826567290384427}\n", - " loglikelihood: [419456.37887861405]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 34/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9828594435217094}\n", - " loglikelihood: [419476.7155086893]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 35/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.983054446947066}\n", - " loglikelihood: [419495.73606062576]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 36/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9832429754605947}\n", - " loglikelihood: [419513.56351841916]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 37/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9834259555500987}\n", - " loglikelihood: [419530.3062484893]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 38/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9836040735157431}\n", - " loglikelihood: [419546.0599689197]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 39/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9837778315636562}\n", - " loglikelihood: [419560.9094365451]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 40/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9839475926980294}\n", - " loglikelihood: [419574.9298950087]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 41/50 ##\n", - "<< Pre-processing >>\n", - 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"text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9845908463919338}\n", - " loglikelihood: [419623.9585680199]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 45/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9847432970746456}\n", - " loglikelihood: [419634.7077208706]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 46/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9848925365610206}\n", - " loglikelihood: [419644.9383672667]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 47/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.985038608867374}\n", - " loglikelihood: [419654.68582116824]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 48/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9851815543913988}\n", - " loglikelihood: [419663.98213848204]\n", - "<< Checking Stopping Criteria >>\n", - "--> Continue\n", - "## Iteration 49/50 ##\n", - "<< Pre-processing >>\n", - "<< E-step >>\n", - "<< M-step >>\n", - "<< Post-processing >>\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "**********************\n", + "Starting iteration 1\n", + "Done\n", + "----------------------\n", + "Starting iteration 2\n", + "Done\n", + "----------------------\n", + "Starting iteration 3\n", + "Done\n", + "----------------------\n", + "Starting iteration 4\n", + "Done\n", + 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iterations = 50\n", + "**********************\n", "\n", - "WARNING RuntimeWarning: invalid value encountered in divide\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "<< Registering Result >>\n", - " alpha: 2.0\n", - " background_normalization: {'albedo': 0.9854582273832846}\n", - " loglikelihood: [419681.33552991366]\n", - "<< Checking Stopping Criteria >>\n", - "--> Stop\n", + "CompletedProcess(args=['mpiexec', '-n', '6', 'python', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/cosipy/image_deconvolution/RLparallelscript.py', '--numrows', '184320', '--numcols', '3072', '--base_dir', '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/image_deconvolution/511keV/GalacticCDS', '--config_file', 'imagedeconvolution_parfile_gal_511keV.yml'], returncode=0)\n", "<< Finalization >>\n", "#### Image Deconvolution Finished ####\n", - "CPU times: user 3min 15s, sys: 2min 48s, total: 6min 3s\n", - "Wall time: 48.5 s\n" + "CPU times: user 2.35 s, sys: 1.23 s, total: 3.57 s\n", + "Wall time: 42.6 s\n" ] } ], @@ -2571,7 +1231,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "id": "cc64ea8d", "metadata": { "collapsed": true, @@ -2582,20 +1242,15 @@ }, "outputs": [ { - "data": { - "text/plain": [ - "{'iteration': 1,\n", - " 'model': ,\n", - " 'delta_model': ,\n", - " 'processed_delta_model': ,\n", - " 'background_normalization': {'albedo': 1.190086058358472},\n", - " 'alpha': 2.0,\n", - " 'loglikelihood': [389620.43700901093]}" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" + "ename": "IndexError", + "evalue": "list index out of range", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mimage_deconvolution\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresults\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n", + "\u001b[0;31mIndexError\u001b[0m: list index out of range" + ] } ], "source": [ @@ -2604,7 +1259,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "id": "b0e2c89a", "metadata": {}, "outputs": [ @@ -2615,7 +1270,7 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[24], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n", + "Cell \u001b[0;32mIn[23], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n", "\u001b[0;31mRuntimeError\u001b[0m: No active exception to reraise" ] } @@ -2651,9 +1306,9 @@ "outputs": [ { "data": { - "image/png": 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", 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" + "
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", + "image/png": 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", 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", 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" + "
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", + "image/png": 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" ] @@ -2831,7 +1486,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "id": "79bde8df-6fa3-430f-895e-06d7e6f91a9f", "metadata": {}, "outputs": [ diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 29939b49..1577573d 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -1,5 +1,5 @@ author: Hiroki Yoneda -date: 2024-06-12 +date: 2024-06-12 # Modified by Anaya to include deconvolution:parameter:numproc on 2024-08-23 model_definition: class: "AllSkyImage" @@ -20,10 +20,10 @@ model_definition: unit: "cm-2 s-1 sr-1" # do not change it as for now deconvolution: - algorithm: "RLparallel" + algorithm: "RL" # Choose from RL, RLsimple and RLparallel parameter: - iteration_max: 10 + iteration_max: 50 acceleration: True alpha_max: 10.0 response_weighting: True diff --git a/docs/tutorials/image_deconvolution/511keV/ScAttBinning/511keV-DC2-ScAtt-DataReduction.ipynb b/docs/tutorials/image_deconvolution/511keV/ScAttBinning/511keV-DC2-ScAtt-DataReduction.ipynb index aecc131a..c2dce513 100644 --- a/docs/tutorials/image_deconvolution/511keV/ScAttBinning/511keV-DC2-ScAtt-DataReduction.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/ScAttBinning/511keV-DC2-ScAtt-DataReduction.ipynb @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 7, "id": "e3bb550f", "metadata": { "scrolled": true @@ -72,6 +72,7 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import os\n", + "from pathlib import Path\n", "\n", "import healpy as hp\n", "from tqdm.autonotebook import tqdm\n", @@ -121,7 +122,7 @@ "# Response file:\n", "# wasabi path: COSI-SMEX/DC2/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\n", "# File size: 350.43 MB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5')" ] }, { @@ -134,7 +135,7 @@ "# Source file (511 keV thin disk model):\n", "# wasabi path: COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz\n", "# File size: 202.45 MB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Data/Sources/511_thin_disk_3months_unbinned_data.fits.gz')" ] }, { @@ -147,7 +148,7 @@ "# Background file (albedo gamma):\n", "# wasabi path: COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz\n", "# File size: 2.69 GB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Data/Backgrounds/albedo_photons_3months_unbinned_data.fits.gz')" ] }, { @@ -160,7 +161,7 @@ "# Orientation file:\n", "# wasabi path: COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori\n", "# File size: 684.38 MB\n", - "fetch_wasabi_file('COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori')" + "# fetch_wasabi_file('COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori')" ] }, { @@ -180,7 +181,7 @@ "metadata": {}, "outputs": [], "source": [ - "path_data = \"path/to/data/\"" + "path_data = \"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/\"" ] }, { @@ -193,8 +194,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 16 s, sys: 1.16 s, total: 17.2 s\n", - "Wall time: 16.9 s\n" + "CPU times: user 6.95 s, sys: 368 ms, total: 7.32 s\n", + "Wall time: 7.38 s\n" ] } ], @@ -207,7 +208,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "id": "4709061c", "metadata": {}, "outputs": [ @@ -217,31 +218,33 @@ "(16, 3072)" ] }, - "execution_count": 4, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "full_detector_response_filename = path_data + \"SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\"\n", + "full_detector_response_filename = path_data + \"SMEXv12.44Ti.HEALPix04.E_1150_1164keV.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\"\n", "full_detector_response = FullDetectorResponse.open(full_detector_response_filename)\n", "\n", "nside_local = full_detector_response.nside\n", "npix_local = hp.nside2npix(nside_local)\n", "\n", - "nside_local, npix_local" + "nside_local, npix_local\n", + "\n", + "# image_response = Histogram.open(full_detector_response_filename)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 11, "id": "328808b4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "FILENAME: '/Users/yoneda/Work/Exp/COSI/cosipy-2/data_challenge/DC2/prework/data/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5'\n", + "FILENAME: '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.44Ti.HEALPix04.E_1150_1164keV.binnedimaging.imagingresponse.nonsparse_nside16.area.h5'\n", "AXES:\n", " NuLambda:\n", " DESCRIPTION: 'Location of the simulated source in the spacecraft coordinates'\n", @@ -254,13 +257,13 @@ " TYPE: 'log'\n", " UNIT: 'keV'\n", " NBINS: 1\n", - " EDGES: [509.0 keV, 513.0 keV]\n", + " EDGES: [1150.0 keV, 1164.0 keV]\n", " Em:\n", " DESCRIPTION: 'Measured energy'\n", " TYPE: 'log'\n", " UNIT: 'keV'\n", " NBINS: 1\n", - " EDGES: [509.0 keV, 513.0 keV]\n", + " EDGES: [1150.0 keV, 1164.0 keV]\n", " Phi:\n", " DESCRIPTION: 'Compton angle'\n", " TYPE: 'linear'\n", @@ -275,7 +278,7 @@ " SCHEME: 'RING'\n" ] }, - "execution_count": 5, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -296,46 +299,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 12, "id": "6c61a321", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angular resolution: 3.6645188392718997 deg.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING ErfaWarning: ERFA function \"utctai\" yielded 1 of \"dubious year (Note 3)\"\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "duration: 92.36059027777777 d\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "WARNING ErfaWarning: ERFA function \"utctai\" yielded 7979955 of \"dubious year (Note 3)\"\n", - "\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "182c9f53f9ac483e8244d24e2a887e58", + "model_id": "bcde623f7aa64b9da764a04b3dc4c1bb", "version_major": 2, "version_minor": 0 }, @@ -350,8 +321,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 44.7 s, sys: 1.88 s, total: 46.6 s\n", - "Wall time: 46.5 s\n" + "CPU times: user 44.6 s, sys: 1.38 s, total: 46 s\n", + "Wall time: 46.9 s\n" ] }, { @@ -631,7 +602,7 @@ "[278 rows x 10 columns]" ] }, - "execution_count": 6, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -660,7 +631,7 @@ "metadata": {}, "outputs": [], "source": [ - "exposure_table.save_as_fits(\"exposure_table.fits\", overwrite = True)" + "# exposure_table.save_as_fits(\"exposure_table.fits\", overwrite = True)" ] }, { @@ -689,8 +660,8 @@ } ], "source": [ - "exposure_table_from_fits = SpacecraftAttitudeExposureTable.from_fits(\"exposure_table.fits\")\n", - "exposure_table == exposure_table_from_fits" + "# exposure_table_from_fits = SpacecraftAttitudeExposureTable.from_fits(\"exposure_table.fits\")\n", + "# exposure_table == exposure_table_from_fits" ] }, { @@ -703,7 +674,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 13, "id": "0f073766", "metadata": {}, "outputs": [ @@ -716,7 +687,7 @@ "" ] }, - "execution_count": 9, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -735,7 +706,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 15, "id": "b24d8dc3", "metadata": {}, "outputs": [], @@ -746,7 +717,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 16, "id": "b75a6097", "metadata": { "collapsed": true, @@ -757,7 +728,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", + "image/png": 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", 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" ] @@ -788,7 +759,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 17, "id": "cd627fef", "metadata": { "collapsed": true, @@ -799,7 +770,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", 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10:44:05 WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
+       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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+       "                  software installed and configured?                                                               \n",
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         WARNING   Could not import plugin FermiLATLike.py. Do you have the relative instrument     __init__.py:144\n",
+       "                  software installed and configured?                                                               \n",
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10:44:05 WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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         WARNING   Env. variable OMP_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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         WARNING   Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to 1 for optimal     __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
+       "
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Modify if you can want a different path\n", + "data_dir = Path(\"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data\") # Current directory by default. Modify if you can want a different path\n", "\n", "ori_path = data_dir/\"20280301_3_month.ori\"\n", "response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\"\n", @@ -97,15 +353,15 @@ "\n", "# download response file ~839.62 MB\n", "if not response_path.exists():\n", + " print('Response file does not exist')\n", + " # response_path_zip = str(response_path) + '.zip'\n", + " # fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5.zip\",response_path_zip)\n", " \n", - " response_path_zip = str(response_path) + '.zip'\n", - " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5.zip\",response_path_zip)\n", + " # # unzip the response file\n", + " # shutil.unpack_archive(response_path_zip)\n", " \n", - " # unzip the response file\n", - " shutil.unpack_archive(response_path_zip)\n", - " \n", - " # delete the zipped response to save space\n", - " os.remove(response_path_zip)" + " # # delete the zipped response to save space\n", + " # os.remove(response_path_zip)" ] }, { @@ -266,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 3, "id": "d4972c53-f653-4694-8190-8524362b6ef7", "metadata": {}, "outputs": [ @@ -286,6 +542,197 @@ " drm = response[0]" ] }, + { + "cell_type": "code", + "execution_count": 25, + "id": "5d4c8849", + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$\\mathrm{cm^{2}}$" + ], + "text/plain": [ + "Unit(\"cm2\")" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drm.contents.unit" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6acc1e23", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['DRM']" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import h5py\n", + "\n", + "hf = h5py.File(response_path, 'r')\n", + "list(hf.keys())" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e8adf052", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['AXES', 'CONTENTS']" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(hf['DRM'].keys())" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "6f45fb1d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(hf['DRM/AXES'].keys())" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "54a9ba60", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,\n", + " 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,\n", + " 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,\n", + " 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n", + " 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,\n", + " 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,\n", + " 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,\n", + " 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103,\n", + " 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116,\n", + " 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129,\n", + " 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142,\n", + " 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155,\n", + " 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168,\n", + " 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,\n", + " 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194,\n", + " 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207,\n", + " 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220,\n", + " 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233,\n", + " 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246,\n", + " 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259,\n", + " 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272,\n", + " 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285,\n", + " 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298,\n", + " 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311,\n", + " 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324,\n", + " 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337,\n", + " 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,\n", + " 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363,\n", + " 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376,\n", + " 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389,\n", + " 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402,\n", + " 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415,\n", + " 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428,\n", + " 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441,\n", + " 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454,\n", + " 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467,\n", + " 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480,\n", + " 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493,\n", + " 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506,\n", + " 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519,\n", + " 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532,\n", + " 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545,\n", + " 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558,\n", + " 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571,\n", + " 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584,\n", + " 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597,\n", + " 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610,\n", + " 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623,\n", + " 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636,\n", + " 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649,\n", + " 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662,\n", + " 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675,\n", + " 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688,\n", + " 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701,\n", + " 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714,\n", + " 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727,\n", + " 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740,\n", + " 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753,\n", + " 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766,\n", + " 767, 768])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hf['DRM/AXES/NuLambda'][:]" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "5fa04060", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(768, 10, 10, 36, 768)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hf['DRM/CONTENTS'].shape" + ] + }, { "cell_type": "markdown", "id": "9bf2f221-0300-4dd1-8dc7-eb4e0e694997", @@ -296,7 +743,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 26, "id": "5a621225-5619-4d43-9670-b4bd03b1d801", "metadata": {}, "outputs": [], @@ -316,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 27, "id": "6680c76c-3483-462e-bb40-5a00b282cdba", "metadata": {}, "outputs": [ @@ -326,7 +773,7 @@ "array(['Ei', 'Em', 'Phi', 'PsiChi'], dtype='" ] @@ -380,7 +827,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] @@ -443,7 +890,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", "text/plain": [ "
" ] @@ -478,19 +925,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 29, "id": "cd6dd9bd-02c3-4116-b291-b8eaba8a05cc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now converting to the Spacecraft frame...\n", - "Conversion completed!\n" - ] - } - ], + "outputs": [], "source": [ "# read the full oritation\n", "ori = SpacecraftFile.parse_from_file(ori_path)\n", @@ -505,6 +943,227 @@ "dwell_time_map = ori.get_dwell_map(response = response_path, src_path = target_in_sc_frame)" ] }, + { + "cell_type": "code", + "execution_count": 34, + "id": "c9dc63eb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_pix_rangesets': None,\n", + " '_pix_rangesets_argsort': None,\n", + " '_uniq': None,\n", + " '_scheme': 'RING',\n", + " '_order': 3,\n", + " '_coordsys': ,\n", + " '_npix_ratio_max': 4503599627370496,\n", + " '_data': array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 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"metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dwell_time_map.__dict__" + ] + }, { "cell_type": "markdown", "id": "17277018-0380-4daf-bf41-fe1fac44d0ab", @@ -515,7 +1174,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 35, "id": "f6edcf60-c017-40d9-92b5-e85f612d7eeb", "metadata": {}, "outputs": [], @@ -534,7 +1193,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 36, "id": "62b557b0-c988-4859-b5c7-f3709e47a9ae", "metadata": {}, "outputs": [ @@ -547,7 +1206,7 @@ "Unit(\"cm2 s\")" ] }, - "execution_count": 15, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -556,6 +1215,577 @@ "psr.unit" ] }, + { + "cell_type": "code", + "execution_count": 37, + "id": "5800cf50", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_axes': ,\n", + " '_sparse': False,\n", + " '_contents': array([[[[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n", + " 0.00000000e+00, 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}" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "psr.__dict__" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "e1ca2c89", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "psr.bin_error" + ] + }, { "cell_type": "markdown", "id": "5b014e8e-21ca-4d97-8436-2292b2a5c132", @@ -603,7 +1833,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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", 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\n", + "image/png": 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", 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\n", + "image/png": 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UcKkekZsJ6gnd0ShzVP90JEzstMkcI8NSxzByp3nlBTYRt06a8YWIUuk5D918GU7/GE68aDGeeuqpur+tW7cOF110ES688EKTwTNIY6TOIMzw8DB+/etf484778Tjjz9e9y3WmuxGbmwO7LEBWE5ebgeEeA833QJCqb6JUJl06J5MmLpNmQsOAOA4SlM8NOBS/XLM0Cl1rIwspm5xgGbBa9JkxtrFziLNkVCrFtPVeA+w86lxjjzYttL17+YqcPrHcPLrlmHTpk11X4jPOussXHTRRbjgggvQ29urq8SGowAjdQYuyuUyHnjgAdx+++144IEHUA3IkTXVjdzoAOzxAamMHIAZkQuiU2x0CF1YNHQIXfCh0ESZq9ul6i3fTJljaFr3NjGmkTs9NEPurFA8HYIXPpeqghc+ZoV7guaqqPaPYe3Fi+q6rhQKBbz0pS/FRRddhJe97GVmsmNDKkbqDLFQSvHkk0/i9ttvx5133onR0VH/b9Z0CbnxebDH58CalqzQwyLHKl2R6Ut4kBW6JLFQEbqoyr8ZQpcQT+q2b4XMBZEVu7gyxsUzcqdOK8QuiKzkxZ1HWcGLO2aVDF434PQdwfKN3di5c6f/ek9PDy644AK89rWvxemnn97ceRUNHYuROkMDL774Im677TbcfvvtdSO3SDWP3Pg85MbmwaqUvBdFBSxO5BjtFro0kZCRubQKvsVCBwhKXatljiEqdWllTIt3FMpd5sUOSJY7QFzw0s6hqOClHbPovZP3Wju8ufCmUO0bxtx1BAcPHvTfsnz5crz2ta/Fa1/7WjPAwlCHkToDAGB6ehp33303brrpJjz22GMzf3At5CbmeCI31Vc/apVXwNJETjQeL7xCxysPIkLHU5G3QeaCpN767ZI5Bs/nIlI+EUnM8qCKo1Hu0sSOwSt4vOePV/B4j5f3es3Xd2OhoHBLE6j2H0Fx2TQmJiYAeNfVxo0bcemll+LlL385CgXJ7i+GWYORuqOcHTt24Je//CVuv/12jIyMAPAqCmuiF7mxebAn5oDQuCaGBAnjFTmeWDKkCZ1MFihJ6ETlp81CB6RIXbuFDkhv/tYZLw6NcmfETjWmYLw0wRM9f2mCJ3q8SddwPl7OKHHh9A3j5NctxO9//3v/9f7+frzmNa/BpZdeijVr1oiVxTBrMFJ3FDI5OYm77roLv/zlL+s65ZJqHrnRBciNzYflpHzji5wQWFDk0uLJEid0Kn20ooROVnp0C51CrIbbPwsyx4j6vFTKpjL4wsidOFkQO0ac4MmeuyjBUznWqOs6QewYbn4a1f4jmHsS6ppn161bh8svvxwXXnghurq65Mtl6DiM1B1F7NixAz/72c/wq1/9CuPj4wDgLTo90ovc2ALYk/3ckwLXSVhQ5mQqyWZm6VRHUYaFTlV4MiR0DL8KyJLQMYJTx+iKpUIW5c6InRhBwdNx3oKCp3qsweucQ+r8zUDhdo/hvPccj3vuuQeVilem3t5eXHrppXjTm96EY445Rq1sho7ASN0sx3Ec3Hfffbjxxhvr+sqRSgG5MZaVE5xPjlLAdeWzcuFYuoVO17xxTOh0CEUGmlvjaMpkzLoglr6y6Zr7Lqv97TTLXaabY1XFjuE6eoW4XNF3nNQVEjt/M7uK6sAQFpxmYe/evf7rGzZswOWXX45zzz0XuZzmiaMNmcFI3SxleHgYN998M37+859j3759ALx1B8loP/KjCxoHPfBiWzOZKx2Voe5mV11C5zr6yqVT6GqrQuha25JWqlpXg6Au1RKP1paQ0lU2v1w6JzXWdd5c+RUKwvgT2Op6aFOqLRalFKQgOSF5FLrEDvA+S133KLEAXZOcA4Dk+ffWoB3DS962HA888IB/bSxcuBBvfOMb8cY3vhFz587VV05DJjBSN8vYvn07brzxRvzqV79CuVz2XnRs5EcXIDe6ML2vXBzBh07cwtyi6BC6wOWrLHQsI6SjXG6wXHqFjqEidkzoAD3iRAPHqxKPhq4t1bLFlktHszyLo3r+gmVUlLu6NUpVZUxjrLpyZVnsGKr3bPD6UhU8DVLt5sqozhlE7/FVHDlyBIA3sfHFF1+MK664AqtXr1behyEbGKmbBVBK8eCDD+JHP/pR3Wgoa7qE3Ogi5MbnglCJh0XUAyYLQhdxyUoLXbhpT6VcEeemWULHEBW7oMz5MTRKmGy8qDiyseLiRcbSNcGxitxFlVVS7qKqcykh0xUHMWXqBLFjyN7DUdeWrODpyrzmCJzeYRz3yh5s3rzZf/mcc87B2972NmzYsMFMatzhGKnrYCqVCu644w78+Mc/xo4dOwCwgQ99yI8sgjXdI9/EGke7pC7hMhUWurg+WjJCl3A+tAhdjMwxRCrgKKHz42gUMZF4STFE4iiXSddEx6Jyl1ReQbFLqsqFhUxjrLhydZTYMYQmWk/4/ETlTmMfOJKzvabZ4gTOfucy3HPPPf5ntHr1arz97W/HRRddZOa861CM1HUg4+Pj+OUvf4mf/OQnM8PYXQu50QWezOloYo2iHUKXcnlyC11aZ3uRMnGch1YIHYNH7JKEDhCTpzQR442nK47WWCITUSfF4D2fPOXmlLu0qpxbxjgeCbyxUsvUiWIH8NcVPNcTr+BpEjuSqz9Pbm4alYFDyC8dx+TkJABg3rx5+IM/+AO8+c1vRl9fn5b9GlqDkboO4tChQ7jhhhvwX//1XxgbGwMAkGoOuZFFyI8tAHElbnqRbIAOqeORJ4FLMlXqeEZO8pSJ89ib3dwaRZLUpclcXRxNIpYWizcGTyxdZQq9MfnvvKNxeeSOt+wp96lINZ4qZJyx0uIIlUmX3OkSO5Fsa9p9yvtFIU3uNGfrwlDLQaX/MOasq/rJgp6eHrz5zW/GFVdcYQZVdAhG6jqA/fv34wc/+AFuvvlmf/4hUi4iP7IYubF5IBBsOiJEvP9PK7J0gpdirNCJTIGRVB7BY26H0DGixE5E6IDWiJhoHJ2xhJuY4x7GokuTJe1X9Bhi5E60Go8VMk1xZB4rHS12QMLqOhL9I+MEr0nZuiAUFE7vESx7qe136ykUCnjDG96AP/zDPzRrzWYcI3UZZu/evbj++utx6623olq7ya2pHuSHF8OeHBDvLycjc4xmZekkL78GoZOZyyyqPJLH2U6hAxqlTlTo/DgR14eMiIVjycaIKpOO8ghuWP+77BJl4f3LHkdI7GSr8Eghk5GxiDjSZep0sWM0rLYjOSAnLHctkDoGBYXTPYLVr+rCM888A8Drs33JJZfgyiuvxIoVK7SUxaAXI3UZZM+ePfj+97+P2267DU6tcrAme1EYXgp7SqJ/g4rMAc0ROoXLjupY4SFcHoVjbGX/uSQIIdIy58fQJGIslmoMFkdXeRQDoFYQtRisHKrHU5M71SrclzJNcZTLM1vEDqivY1Sm0QnKXQvFDqjNd1caw0mXDfgT2DO5e/e7341ly5ZpKY9BD0bqMsTevXvxve99D7fffntA5vpQOLIU9nSveEBVmWPokjoNE3JSXXPbOY6W48qK0PmhFIQO0CdQOtEth4pB1KSOxbCIluuP2JayRAE1IdPxKNC0mkKmxE7jJNPKVKstl7ogTnEcp79lPh566CEAntxdeumlePe7322aZTOCkboMcPjwYVx//fX4xS9+4Tez2hP9yA8vkZM52/KWDHJVMgq1ikx1Ql/28KpELIAtUR6qGocRtSC3AJQtlaZKLY6W29BxsiNj1FWf4FdnHGiSOt2oHpumYyKEeHWGeiAtcQghQF6DvGQhWxdGl8wr1s0yUsdwiuNYf/kc/Pa3vwUA5PN5vP71r8eVV16JhQsXKpXLoIaRujYyOjqKH/3oR7jhhhswNTUFALCm+lAYXAa73CMWzLZmviWrCAchM0JHqbzUWaReDGVkLPiAcF01oQs2nSkInX+7aBS6htgy1DJ9mZC6YCZLRVqCqzZoIJNSB6gdn06pA9SELNivUyFOXf9Q21Y/xiyKHaAkd8F+lSpypyJ2AOB0jeGk1/f7zbKFQgFvectbcOWVV5qpUNqEkbo2MDU1hRtuuAE//OEP/alJrOkeFIaXw54QzMwFZY4hI3VBmWMxZCoLKxRHRujC3/ZVhC74wJQUuoZbpAlCF7kfXkJNt20Vu6iVFtoRI4LMSh0gf4wajqlh5LSskGmIEzk9T7B+kz3erIodoG/AjER9rSp1DKd7HCde0o1NmzYBAPr6+nDllVfiD/7gD1AsFrXsw8CHkboW4roubrvtNnz729/25wEilZInc1NzQCjERCpK6AAxqQvLXDAGb1nCIscQFbq4phtRqYt6QEoIXeytoSp1CZ+P0O0Y0w+vLVKXtMJCO+JEhsiw1DFEjlN3lq4hvkBZNMSILUdUHSdz7FnqXxeHwL0bO72NwDNEl9TBsrzRsqURLHsZ9adCWbRoEf7kT/4EF198sbfakaHpGKlrEY8++ii+/vWvY9u2bQAAUi2gMLwC9uS8malJeEUqTuZYDB7piJM5kXLEyRyDR+rS+uCICF3SvGKcQpd6OzRR6LjLAKQOFmmp2KWtrqAaQyROYogOkDqA/1ibkaVr2AdHWXTESCtLkhCInIdOEDtAy6TUvHKnRewCnzEFRbV3EAMnT/rJi+OOOw5/+qd/irPPPlt9X4ZEjNQ1meeffx7f+MY3cP/993svuDbyI0uRH1vcOGlwmkwlyVwwRpI0JMkcbznSZA5IFzqeDtU8QsfzAOSQOq7boAVCx1UWjpGyLZE6kZUVVOMcTVLHSDvmVkgdkH6faojBVY60uo/nfGS5GTaKtLWROVYESpM73VLn75e4qPQfRHHliN/N6Nxzz8WHPvQhHHPMMer7NERipK5JjI6O4jvf+Q5+/vOfw3Ec2LYNMjwfhZFlIG7EcP0kkeKRuWCcKHHgkbm0svDIHCNO6kRGxyVJnUgGKEbohC79FgndzNtjyiYw9UlTxU50VYVmxRCg46QOiD/uVgmdv7+YcmiIIVQO3now6fx0SrYuSMy9zLsuMBAvdzqbYCP3a1Vx2SfX4ac//Skcx0Eul8MVV1yBd7/73ejpERwQaEjFSJ1mWL+5f/mXf8HQ0BAAwJ6cg8LwCljVUvyGUSIlInMsRlgcRGQurhwiMgdEC53oVAdxQifycI8ROuFLvsVC520SUUbBueyaJnWi87TF9XFUjSFIR0odEH3srZY6IPr+1RBDuBwidWLceepEsQMi5U5E7IBouWtWti6Im5/CaW/p9+e4mzt3Lt73vvfhda97nelvpxEjdRrZsmUL/uEf/gFPPfUUAIBUulA8shL29ED6xkGZEpW5YAwmD6IyF1UOUZljBKVOZt6qKKGT6XAfEjqpS70NQjezaaC8kpMTaxc72SWyVLYPx5CkY6UOaDx+xWMRFil/v4FyaIghXQ7R+jHqfHWq2AF1cicqdYyg3LVC6hjV0jAWbaxg9+7dAIB169bhE5/4BNauXateBoOROh2MjIzgW9/6Fv7rv/6rNimthcLIMuSi+s3FwT4GlW8slHr/ZCtKJnSyMgfMCJ3KJKRM6lTnOCtX1OZ+a6PQeZvXyq6w2oQ2qVNdGktXDAU6WuoYUWvIyoSRvb+BmftaQwylcsjWlez8dbLUMWr3t6zYAZ7ctVLqAIDCRbX/EPIrj2B8fByWZeHyyy/HVVddhd5eiQn3DT5G6hSglOKOO+7A//t//w9HjhwBANgT81A4cgwstyAWTDazVl8gte11xKAUqCoseeW6oCrbA4DrgCquGMHKIo2GFSd0LImmRepUl8XSgZG6GTQ0VSnJlK4yqMZQ3d4is0PsoOHz9IKobS/xJd61Kzjv/7cEd9xxBwBg3rx5+MhHPoILL7xQzzEdhRipk2Tv3r34P//n//j9A0ilC8WhY2GX+8UC6ZA5hspHqesykF17lJ0H11UTMgWhY5WIL1MqGU8dQudSZaFSlrosCB2gReq8MGr3GnVp++UwC9k6QE2qdGTqLDJTBtnrXIPYsSyZyqOUEKK8VKCWz1O1dcK2pZ4lTtcIFmycxgsvvAAA2LBhAz7+8Y9jxYoVauU5CjFSJ0i1WsUNN9yA73znO97SXpQgP7oM+ZEl/E2tAEAIaK0yIAoPXlqr3IlL2yd1rDJxXfEsXVBq2yR0wcqwITsmWlEG1nKVrWR9ofNfUGjCVZE6VaFj15SuLy2axM4LJV6m4Llsq9ix89DJYqfary547MEyyFzvGsUOkJM7ws4HpdJyp/WzlJW7YAzB46DERWXuQZCFh1Aul1EsFnHVVVfhrW99qxlIIYCROgG2b9+Ov/3bv8WWLVsAANZ0H4pHVsOqdoldwAGhA+SkjgYqNWWhA+S2Dy8rJpKlC2coVYUOEJa6cCUY2dwpIXU0EEO0om0QOqA92TpdQgdkUuq8cIKfTdTIw1bLneYBE0CbxE6n1EWVQeSa19QM27Bsl2CdSoLNlxJyp6W5suE8CtYDUUtWipCz4eamcPLri/jd734HADj55JPx6U9/GqtWrRKLdZRipI6DarWKH/zgB/je974Hx3EA10ZhZCVyEwu9pb14T2FI5vyXBSogGlGJtzxLF1V58Gbp4pqbW5ili6r8EvuviczvV8vSJe0rfvMIofP/2KJsnY7m1vD1lFGpmwnLV76489hSsWvSvHUtFTvVaU3ijjWqDLzXvuZsXRDeRyyJ6pMmKHdN+xx55S5ppSNecra3KkXPIeSPOYTx8XHk83m8973vxTve8Q7kcjn+WEchRupS2LlzJ6699lo888wzAAB7ci4Kw6tmBkJQDqGKkTn/z5wVT5TQ+du3QuqSlhVLy9Il9R1skdAlVXipgxJ4VuEICR3Pfuv2n3QdtELqmiF0DC0duZsjdV5ojs8o4Ty2TOySzkGniJ3KJMRJx5i0f557oIliB/DJXaTYeRvzbd/Mz5BH7HhWPEojMBLXtcs44y09eOCBBwAAa9aswWc+8xkcf/zx6XGOUozUxeA4Dn7yk5/g29/+NsrlMuDaKA6vgj05f2atViBd6jQIXZzM+ds3u+k1raJIytLxDARpotRxC1XaKNOkOAlCx1OGVKHz39hEsdPZ3BpFxqXOC5/yOXF8Rk2XuyYvHdZ0sVNdLizt+HjEMu5zbLLUMZIeubFSN7Nx8vbNaIINkyZ3qmIXml6FgsLpHkRx9WGMjIwgn8/j/e9/P6644gpYstNmzWKM1EWwd+9efPnLX8amTZsAAPbUAApHjouepiRO6lJkzn9bwoMiSebqtm9Wlo6ngojL0vGO6m2S0PFWbkLThkTFTBG6tPJwCx3QPKlrttABHSF1M7uJ+ax4F1lvltjxHn+WxY7jIRy7f97j4s0YRn2eLRI7IF7uUsXO21j6S2Qq3OcvbllLgSUto4iZM49aFZxxRY+/jvpZZ52Fz3zmM1i0aBHf/o4SjNSF+J//+R/8/d//vbcAsWuhMHKs13cOMTdKlNRxCh0QL3U8Qudv3wyp460Ywlk60SlaNEudcB820XngwoNDOIQurmxCQgc0R+paIXRAR0mdt6uIfpcCn1VTxE7k+LModgJZlYb9ix6PSB+/4OfaQqljhOsPLqnzNpTu7pGI0LmLqD9El7YMkzARMutrZy3bj6mpKfT29uITn/gEXv3qV/Pvc5ZjpK7G5OQkvva1r+GWW24BAFjlXhSHjofldCVvGJQ6AZljhKWOV+bqtpf9CGMyjELbB7N0bRQ6mYpMh9RRge0bpk5p8ajUBilpldABHSd13u5CEi74eWkXO9Hjz5LYCTaTtVTqGOzz7SSx8zZu3L7VK3UE5U52iUsGx+oWbm4Kqy50sHnzZgDAxRdfjI9//OPo7u4W3/cswzRIA9i6dSve97734ZZbbgEh3rxzXYdOThe6IBJCF6alQtcQTFDIgPp5yCxL3yhHHmpCRwhpndB5G878LzjcP1Pfn1opdDLvzwDUpUrz/Gldd1dGaBX3387rtW7fMnIqc29bxPvnUsBVXNVGENl6rLYxiGXpW4FB6twpqoRg2a1qF56/vYT3vve9sCwLt99+O973vvfh2WefVSvHLOCoztRRSvHTn/4U//zP/4xKpQLi5FEcOkF4VQhRGQtCXCq9vVapE4VSr9lVtiLRkKWTXb1Cx/JbIs2uQfyZ49swKbAvGa0WOobqQ6fFmbr6XRMlSVPO2qkcezszdrat9MAnhKiVX2nVi9Zm64JQSsWydY0B5LcF1M6b66ptL3jenMIo+tYP4uDBgygUCvizP/szvP71rz9qlxk7aqVucnISX/3qV/015+zJuSgeWQ1C80JxpIWOXXAKp7+tUgfIr/FKKWilIi82CkIHwGsyVTlvkkI3s33rhc7blLZP6ICOljodKImd6rGrfPFU/dzyYnVqw/4VW0DaJnaWQvYNUF+2S+VeVV3BQbnpXrD52qrgtLeU8OCDDwIALrroInzyk588Kptjj0qp27VrFz73uc9hx44dACUojByD3PiS+MEQIahVa27kmaMuCtbUqbA9cVzpbantlZ04khUGK7uM1FEKVKty2SrqAo7r/S8pRn4fONnLvlbJSt827RQ61qSkWuG2Q+zaLXTs3CuUQ3lpMh0L2EsiLScs26RY9raJHTtumc+dLeEoe+78dW0l73t27mVbJVQ+sxZLHeANoqj07YM7fx8cx8ExxxyDL3/5y0fdShRHndTddddd+Ju/+RtMTEzUmlvXwC73cW3ryxwh3o0msxJDMEMnK4SAuNSF+/zJSF145KeI1NVkzvtRUegAKTmqG9Qgc+4DlavwbaPav0qX0AGdJ3VZETpGC8Uu3OTbcWIXbkJUKH9bxC54zApi54VSHOwhKnfhcy8qdx2WrWMEm2NLpRL+6q/+Cueff75aWTqIo0bqHMfBN7/5TfzoRz8CAFjlPhQHT4ieey5EncwxRKQuahCCqNSFtheSuqhBHKJSp0novF8lpvIICh0gtH3kCFWRcx9RmQrdNlkSOkYnid0skjpvc84WgbhlyTpJ7KL6hXVS1i58vIojkFsqdlHnXkTsOlTqAK85du3rLTz22GMAgPe+973+oIrZzlEhdRMTE/jSl77kT1qYG1+KwvAxqc2tkTIH8Atd3IhSEaGL2Z5LyOJG5IoIXVz5eaQuJHMzL3NKHZM59nMQ3qXV4iox3vMfU4ly3zZZFDqgc6Qua0LHaIHYJS5L1iliF/cQ7RSxiztWxYmguc+h6lqsceefR+7YrAYqtFPs4OJ1H1uNG2+8EQBw3nnn4a/+6q/Q09OjVqaMM+ulbu/evfj0pz8d6D93AnKT89NXckiaoiNN6tKmB+GVupgYXFm6pClWBKQwbvtUqYsROu9PHFIXlZ0LwrO8WlLFxXP+EypOrtsmq0LHyLrYZVXoGE0UO64lyTpB7JKkoBPELuk4eT7/pCUeec6h6lqsSeefR+w6OFsHALSQR7XrALBwN8rlMlauXIm//du/xfLly9XKlWFmdS5y06ZNuPrqqz2hc/IoDp7CJ3S2rdChW2K+N50xCAHN2Wpz5qnsn1KgUokVuvTtXW/bJKFLC+E4QpMCR5JSYaZWyFkXuqzTbqHjQXEkseo8durXuMIcfDxCn5blUSw/lR3oFdy/ShmofB0FeOdQKadiWWqZNNtWl7aMQ8oV5KYWgexdi4ULF2LXrl34wAc+gCeffLLdRWsaHVBzynH77bfjYx/7GI4cOQJS6UHX4Kmwq/EDIqjlyRDXYsZxKzHwTMCblKVrt8yxMsiSkJ3j2z6QnVMQOi6SsrAq0wgAR4/QqV4rWUZ16hfu3TSeBxHZy7zYpaFB7LTInVIhFOVe9TyqNpE2U+5Uj031s61hV3sx9vRKrF27FsPDw/jYxz6GX//611piZ41Z1/xKKcUPf/hDXHfddQAAe2oeCsMngMBmb6jL1KU2tYYJS52oiEVJneD2DU2noqtZxMQQ2b6u+VVQ5iKbX9OaW6MIL7EmWjmHPwfVFSJ0rCDQaqHLYhNsu7N0op+BhvIGm2JlMniZbIoVlY2sNcfqGNAjukpQeJ+i5yRch4l+BuE6tMP71QFeE6z/Mxyc9Qd53HfffQCAq6++Gu985ztn1UTFs0rqHMfBP/3TP/kdI3PjS5EfO3ZmQERA6IRljsGkTjarFpY6wRh1/elklyYLSp3sMTCpk8jO1Uld0mCINIJyrrLkFyCVnau7dTpR6AD1ChfQK3btFjpA7nPQ1L9OadWKLImdrAhkSex0zKkocU7rzqXs+WD1meznEKxPO7xfHRAWO4rLPrQCN9xwAwDgjW98I/78z/8c9ixpip41Ujc9PY0vf/nLuOuuuwAA+dFVyE8srX8TO1TZdUpVhY6VgcWQwJc6WaGrlYE4rmK/uap0U6svdTLZuSAuVWt+YteDQnOr8pJfgJ6+WSpNru3M1gX336lCx9Agdqr97NopdkBASFT7eqmUQYMEKPWrBmauBVVRVl2uS+VzYHVru6UO0JqtY1RKe+HM2QXXdfGqV70Kn/3sZ1EopE9xlnVmhdSNj4/jL//yL/H73//eG+E6fAJy0wvq32RZ3oWh0kav61S185SHmp+lcBxguixfBMedEUKV7JTCUmEA1PvSQENn7XYLHZCNbF2nCx0jA8eRCbHT0c9LEWW5y+WUy6AsqDrK0G7Y6ksqqEpdbzcQsdZ4tXgYdOEOVCoVbNy4Eddccw1KpZLSvtpN+2sgRUZHR/Hxj3/cEzrXRnHopOYInaVhVCsgf3ETAuTUFsfW0j+CxVHBIt7nofIQVc6OUeVzofx9SIfQ6RAR5ePQ0PyqvCZtRoSsRQMs4iAWUS+Djq4EqoONFNGSrVP9wqajOU91hK4OVGd0UGiZ8kPkc6B5ecEl45NARLYuNz0f1oETUCqV8Mgjj+DjH/84RkZGVIradjpa6o4cOYKPfexj2Lx5M+Dm0DV0MuzKwMwbLAu0WFC6GLw4ihe16k1BiNo3FSaEOvomKH6LVxYhV0dzp+JUEsGpCGTPh06ha2cnX51ZZ9lzwrbLithlgU4WO7YMYxZwXG0jMGXw65p2ix2g1l2Hba9B7mTLQAnxxC4kd3Z5DtwXjkdfXx+eeuopfOQjH8Hhw4eVytlOOrYGO3z4MD760Y9i27ZtIE4eXYOnwKr2en/UKXNM6BTXapVCh4ypCmEAFaFTnpMJ0DQYQV3o1MuQkQxdXVCJ49LVl06F8HnIgti1KVvXMJlxG8SuYcCEipzpmF5IF20UOwDZEjsd87CKbjI1091HJWtHCYmUO7vah8qO4zB//nzs2LEDH/vYxzpW7DpS6g4cOICPfvSj2LlzJ4hTQHHoFFhOd3Nkjl2AohXcLMrOAepCp0zE+RfqOyQr5XUhMix0rc7WNUvotDQnZ0AEslAGoLMzdrq2lyFK7LMidlmRO9Xt29gkGyV3ltON8S0rsWjRIjz//PP42Mc+hsHBQaUytoOOk7rBwUH8+Z//OXbv3g3iFGtCV/KELuYDJi5nCj1K5kTRIXPNzM7ZljfJMifUIu0VumY3t3L2q0s8Dt7zk8UMXd0OOM9zszN0vMfYzHPRYf3rEteS7SSxS5oUnBMt/eniMM2xM7R79aQavHJnjU00bhuUOwCW04WRp5dj4cKFeP755/Fnf/ZnHSd2HSV1w8PD9UI3eAos2g0U8vr6zakKmQqzLDs3G5pbvRDtn4OOOk56jFYM5MlCkyuQfi6y0AyrqxwpJAqdrnJwfLlKXzqvAzN2cZis3Qw67mkNMVIdIKHuCmbtLKcLo5tnxK7TMnYdI3VjY2P45Cc/iR07doA4eRSPnAIr1+tZusoFEczOyZL17Jwgqdk5ywKK8fP5cEmQbSdPGcApdIlNsFkQOtX1IZudnROhlUKXdMytzOR1iNhxoaMcql+0VPvJtULseD/zJLFrwUS2JmvXiK4mWcvu98Vu586d+OQnP4nR0VGlsrWKjpC6iYkJfOpTn8KWLVsAN4/i2Okgdp8+mev0ptYWZ+dojARry87paG4VKUdEE6zwsUSdt3Y0tzYrW9eODF3UsYuej1kudlxZOt3liOrfKrMyT2MQ+W1ZiGY2vUbR5uZYIINZu1kid5bdj9HtqzBv3jxs374df/mXf4np6WmlcrWCzEtdtVrF//pf/wtPPvkk4OZQHDsNhPaoBZ0NTa26YtRoe985wDS31m1+lGboEsvRxvORYbETJgsZO2D2jIwFMiF2mcnaAZ3TJJu0LSEgtBsTO1ehp6cHmzZtwuc//3lUJVdSahWZljpKKf7u7/4ODz/8MEAtFMdPheX2ygecLU2tLE4G+s4Bs0Toatk6pWNh57HdQqczW9fuBWdmy2jYJiCcpQuiUeyUFkNnYiYbIyB2Lc/ShWmz2AEZmvoEmBVZOwAgbh+q+45HoVDA/fffj//9v/833Cx9oQiRaan77ne/i1tuuQWgQGH8ZFhOv1wgoqGpVceKEjpEzNLUZFtDWugIAXI5NQli/epUhU7HMjSuazJ0YdotdAzFfol+jCyQlXIAsyNjp2P7IMpzFNKW9KdLLkKGmmOBWZG1s5y5wOAa2LaN//7v/8a3vvUt5fI0i8xK3U033YTvfe97AID85BrY1fnCMdzuPMqLeuD0FZX6zVHLUltSimUIFTNiWrAs0GIOtKsgLXTE0dD04dYqnizMHaeLrFSiWTknOr6p64IqynKWZKwG1ZLdVjwui6jfgzq+lAHq6zAD3pdllS/MrE+wjs9GBzqEV8c9rPr8swhodxG0uygfgxAMnzIHw6fMkdrcri6ANXICAOAHP/gBbr31VvmyNJFMSt0jjzyCv//7vwcA5KZWIldeJrQ9k7lqXwHUgvyACkJAbaJ2lrIgckBtHj/bOx4FtAmdhodk3cNEpfmmdjxKzUgahE7PQzojDxNCvKxHFpbdCjYlt1vOsnA+wui+F+WDyG0X+MJNHVde7oKj8VXEjmWW2y12/sT5CnU2O7e6vqCpPA9rZVARO2p5/2TlLldZgne/+90AgK9+9avemvMZI3M1zJ49e/CFL3wBjuMA9nLkplYJbe925wMyJ1mIWnZOSYCykpkDPKHTIHOkUtUvdIQAEmnxhoeITCZVV7ONbqGTffBnTej839tYzYTPiYzY6RLBJpwHLV8EvEDi24TqNymxC9+3mq5hbVk7lW2yIHZBZkvWjqhn7YJyJ8p//uNOvOpVr0K1WsVf/dVf4YUXXpAuRzPIlNRNTEzgM5/5DEZHR+EW5oIUTgUB34dfl51TlTkyS7JzgDahi6wQbAskn298PQq/uTUjWYGYCk4oW6ep30rkg1lUALIqdP7rGapqRM5VhoWO0VaxC4fQlbHjjZPwZa5tYldXCHd2NseK1JNx51BT1k5V7kSzdgQEt27vxrp16zAyMoJPf/rTGBsbky6DbjJT01JKce2112LHjh2gdhHlhRtBCF+HU23ZOSZzsmcla9m5hOZWmrPqFjSOI2vNrYkPDQ3zXHGjqf/crGxyzQpJ54Xnemx3U60ALRe7hHqOW+zSsuut7GeXNBG6aj+7FjfHcq3sMYuydjqbZLmxcvj96LFYuHAhdu3aha985SuZ6d+dmRr43//933H33XcDxEJ54dlAroTJBTlML4mfk85k52LQ1dxadVojdBxNsFw3DE8TLMfxpFaKrRI6HkHKSEXCJXStFD6e5c50rFrBQ4uOu2VixzNBua7rUse6zbqmGkkTu7S/t7I5lke42pG1i0P1+dnCrN3w+trfc114wT4J+Xwe99xzD3784x9L71snmZC6Rx99FN/5zncAAJW5p4EW5wGoZd0iPuzGgRCSOxbIzlE2v1yYDsrO8eJn57iW+4ppgm1Xc2tSBdOJGbokIegkofPf24Iqh/e8tGLgRIszlx3TFCvSB7bZGbukLF2Y2dgcG1cvinxGzczaWQTuAMeCAy0aSOEGNIAW5+IjH/kIAOCb3/xmJgZOtF3qhoaG8Nd//deglKLauxJO37GJ79c6EEIkOxf1vqzIHCCVnYtqgm1bcyshkfM7CX/jj6qIJJobIrN1mvrPHfVNrs0UHdHzEiV2HdCPLommip1gnadl6UAvUKgc4udWaWRskCixE5G9JjbHSo/gz0pzLBB9jYnEbvFAimtv2I7XvOY1cBwHX/jCF3D48GHp/eqgrVLnui6uvfZaHD58GG6+F9W5p8a/t7eg3tQK6Ok7B3S80IVpaXNrHDpG0wH1FUBWR7iKEJaDTha6ZiJ7XoJi10H96JJoitjpWkZQds7PZoyMFcnSBdGxekWzmmPbLXbB/cueJw3NsapZO4CzSZYQ/PKZAlavXo3BwUF8+ctfbuuKE22tkf/zP/8TDz30ECixUFmwEbCibzC3t4BqT146O+d051AdKOnrO5cVoWtHc2sUrAlWx/JWtq3+7Z49NBRvLP9bbxbmoGPyNFuELksyCOhvis3A8WWpKRbQODJWZSJ4FkbnRMWqgyiy0hQLzLRqqJ7jLAyiqJWDZe2Gz1wkFYIra2fl8Mz0ahSLRfz2t7/FjTfeKFdeDbSt5tm6dSuuu+46AEB17qmghcYlwI6caGHfxprQKXy2bo54TY2K2TlPCDVc7BlZNkVbLJcC1ap65a/rwappdJeudRS1PVx1kZVVHgzJ6OjXlrVrTwdZWblFF1kTOyBTzbHlY8RXk2ooByE4eIZaeZjYHfenW6L/nu/Dn/7pnwIArrvuOuzYsUNpf7K0ReoqlQq+8pWvwHEcOKWlcHob+9EdOdGCvX4YNCffd47aBG7RAs0pZufc2j9Vghe5ygWv4WYhDgWZqgBVxQrSpV4FQAiIbFMG4AmdropNsdKnlIJWq9kSOm39vDR9oVBeIzODzZw6s6C61qrNktgpxvEz36rCQIi+aTmqVfUYqhBLX+uPri9sOs6vrmOyCar9Xaj2dymFoTZw+DSCw6cqdCOwgQXFsVix+8qNz+Kcc85BuVzGNddcg3K5LL0vWdoidd///vfx7LPPgloFVOafXnchHllLcORN47DXD8O25S8qahNP5lTR9ezR9jANxKEUxBGvaIlDgUoVQpN8RsGETvXmDwodsUBkmzMcB6hUFIuiJzsHNEnodH0ZUFg6L7NCp+Mey4LYNWHghtK1GPy8tQmi5DGFP2PJOHV1TLWaDbnLGqxub2P/MJ9aK5uy2Fk1uVMQO2BG7BrkjhD8Zs8cDAwMYNu2bfjud7+rtB8ZWi5127Ztw/e//30AQGXeaYA905HxyFoC+5QRFApVX+jIqSPYfzZ/Z8e67FyASq/Xr44bndm5DDW31gldDWpbkSNPE4kSOtFsHaWAE9H0ICN2lYpy5ZN5oWPIXAtR24jGybLQMWaL2DUhjtQ1GfV5S8SJHJWpSxZ0xWmH2GnM0imtXR1HlsQO8MVOVO6eu2JO3e9M7ITkjgCrPzQjcQuKY9FZO7sLBwtrAQA//vGPsW3bNqGyqtJSqatWq/ibv/kbr9m1eync7mUAPJkbeuME7FNGGrJzuZwDl3MlqtTsHO/RJs1JKtKvLu0m470JdTa3hoROGJd6TbaqN7rO5lbF7BzQQULHEBzir0wnCB2jk8WuyRMiC12bSZ+3QJxE2RCpQzTFSfzC2MkZu2b2lRWt7zWJamR/Opa16+NP9kQ5BLXFs3YLio3LgUVl7dzupXjlK18Jx3Hw1a9+1VvLvkW0VOp++tOfYtu2bV6z67zTAEL87FyxWGl/c2sWs3NpcTiaYHmaW7mydcHsXNwNzpOt4xE63mzd0Sh0Iuj4YtFJQsfoRLFr0dJlWeljNxPnKM3YZT1LF6YdWbukmR1YXzsBuYtCV3NsOGv339sK6OnpwTPPPIOf//znSvFFaJnUHTp0yF81ojrnZBw5uRSbnQuT1AQb19wqTJb6zmmME9XcKkUz+s+pcrQLXSsywZ0odIxOEjtd2TzuEBqWqANS72Vu2UirVzTF4e7W0WkZu1aNaM9gcyxsok3sYuUu1PQaR13WLlfC1VdfDcBbbeLAgQNKZeSlZVJ33XXXYWJiAm5hDg6/5Fih7FxcE6xodq7SE9OvTvD6jG2CbVdfp5hsnajQxWbrRIUuLlsnKnRJ2bqjXegYcdeKTH+5qNc6VegYnSB2MueomWIn+pnHxBHOHiVk/3XEEe6n20yx67QsXZjE5cXaMJVJgtg999Y5XCHSmmOjml7j3regOIZVf7oV196wHaeccgomJyfxz//8z1zbq9ISqdu0aRNuu+02UACDl58Ie/2oWlNrzpLLzhHUH3EnNrfyhMli/7moAREyaBrhqnPKEj3Lfrl6BEjXtQhkYgJdQ3PRdv3qWs9UVxZI55QnWc/atWveyWZn7UQn1Y9pjnULYmGkBlFEsKg4ilUf2oZ9F02AEII777wTTz75pFJMHppea7uui6997WsAgKn1y2Ct7JYSOtYES3MWqOBAzSB+tk61FZFl67Iic7Vsnep0JX62jqf/XBIsW6fa3BrM1h1NI1xFYNeO6jWkax5FRruzdIwsZ+tUzpHG8+tfy6oiX4ujnD1i97mmONLTJDF0il2nZ+mChJ8Rmo6rskJywuFQcyxvli5MXdaOAMd+aKtUnEXFUSxfXcGll14KAPj617+uZ2WVBJoudb/+9a+xbds2uAUbU69YJR2nv3sK5QGqJHQAGrN1swnX1dN/jurpP0d19p/T1pla0/qRWRE6hs6+nLOh2TVMFsVOxznK2nkG9N3zuvoV67o3dH3+Wpeja7PUMXRm7IiGQY+1rJ1oli4MtYHD6wn+Ytl/K8V57uxHUSqV8NRTT+HOO+9UK1QKTdWbarWKb3/72wCAqY3HgHbLneHuQgUDxSlPyBQgDmBPuSBltYuPUAqislZqM9GQ8dO1viIA9YWvqatnnUZAX5ysLemTNXQ+tFQnyA6iM5OZJTScb8IyLLrWedV0r2lD25cwDXGIpaU8hJDsPYMc1/ungDvQA3ukDHtEcTUGC3CWTMNZMq0UhtpAN6niPfPvk46RH7Dxzne+E4A3vqCZK000Vepuvvlm7NmzB939Lk69TC6GL3QAlp6+D3vPlVuKijiAVXEBCjilHNxeOcEkOh8yulF56FAKUqmCVB0tx0f95hOFBa+DQmdJTJAcDBWsaBSyUNqFLqv91lRXQ9BxnwS3b7fYZVXoGFpFOgNip3Cv1xH8cqpy7wbLo3ItNmN1jqw8k4L3iMpnT4iXOKFUSey2X5kDsSmITZXE7l/e+k0A6mLXd/bfYcGCBdi3bx9uueUW6ThpNO2JMj09jX/7t38DAJz/hnEUS2IXXXehgsV9Y77QAUApV+GeiJjBsnNM6BhUopLOtNAxLIHJkRmUzsgcOz6LABJruVLXnRE6FkeGZmfoJGSqaRm6rIqdKEGh81+TPGdR27VL7LIudAxJGSNR92g7xU6j0DU0vWYpYwdIDzCJbFJu57Mp6pmjof5WETurNNMPkomdjNwts0f9n5nYychdX1cF73rXuwAA119/PSoaZnCIomlPk5tuugmHDh3CwHwHZ71qUmhblp2z0HiRimTrgtm5cCiRbF2mm1vDyEyHEpedExQ7GtenQiRbR13QajX6YSCRreuYJtcsip3M3Gk67pGkGK0Wu04ROoagjEUKnWSs2DAi96AuoUNCXzrRezmuTKJf8luxQke7nlFxZRKsf905vY2ha2InInfbr2x8bslk7b7+lm83vNZNqtJZu+71n8X8+fNx4MAB3HrrrcLb89CUJ0m1WsV//Md/AADOvWwCuTxw2dzfY+OS3anbBptbo+DN1tUJXQw82bqOyM6F4c3WJQmdCJTGCx0rD1ccjuycgNilxuIUqaO6D53IKgdx15HI9dXKe63ThI0XThlLFDrBWKlhWt3HLq3+472neeoanVk7HbT6eZV2rjn72blzemPvSdHm2GCWriGWgNgdkxuO/ZuI2F0y5wkAQK4Av2/d9ddfj2oTpstpitT95je/wb59+9Dd5+L0l3tZui5SQdGOP4Co5lYZ4ppbo3C77MRsXUcKHeDdGGlixyt0adk6SvmGaKdl63Q2t1LKHytF7FoqdFnM1gHJD3beDB3PNcJ7r+m8J9NW0+hUUmSMS+g4Y3GHSbsnm9nsGoWuufWA9Guy1St0ZPHLUeqXbL4kS5rYbX9XeuuSSnNsEN7m2C4y09Tac9rnMG/ePOzbtw+/+tWvlPYfhfanCKUUP/zhDwEAGy+aQD4wD2Bcti6puTWKuCbYpObWyLISEpmt66jm1jjibhCZARFxYscrdCxGnNiJCl1Cto7qmuQYbcrQdZLYiTa56mxWbbbYdbLQMTpp8EQrml3jiLvPRcsUd022a4WOViQlRPtvx3z+7kAPd4i05lirmy/7ldYcG9X0GkVacyzL0jHyBeCKK64AANxwww3a563T/gR59NFHsW3bNuQLFBsuqu9LF5WtS2tujSKqCZanuTWKcLauY7NzUYSzdVEDImQREbpgeRriSGboIsROOtMXUem2tck1q2IXRLYPnc4BEM26T2eD0DEiZEwoS5cSSypMM5tiZadiCt/vspKZtaZYoLnPM5l7Ja6/tMhuY5pjebJ0DbFixC6p6TWKOLELZukYfaddg2KxiG3btuHxxx8X2k8a2p8eP/vZzwAAp58/ie7exovpsrm/xzlLdyk3twazdbJCB9Rn62aV0AH1N5xq/zmWrav1n5P+dhHM1qk2uQbETvlBURMpbcsmqZJFsfNFTnFQhM6pSnQPnJhNQscIyJi00EXEUgoTvF9b3ewaB7vvVcsTvCZV7uNA87DyBMrNeK6pzGUa6GcnkqULExY73ixdQ5yQ2P2/t3xHKk64OTacpWOUeikuvvhiAF62TidanxyHDh3Cffd5B/OSC6NHvHaRChYXR4SaW6Mo5SpY8JL92L8xLy10DLfLhtudz5bQ6RLMWiWubUCEagzWDGuRzE0qbOBA5yhXXbR7DrtOgLrqQheIpSWM4+oTOkr1rByhs4+dri9mWRxAoWuJTMdVnuieUAp7rCyVpauLUxO7T7/xZzg2NyQdJ9gcG5WlYyx76fcAAPfeey8OHTokvb8wWqXulltugeM4WHFCGYtWRK+v6VALG3p24LS5e5T25YKgYDtwClRJ6OxpB7kj07DKDqjqKgqUehepjuyDrhvZcUEcV8MailTP+oeOA1TKgONoWR+SVqt61hvU2P9I28OTWPoeDLq+JOiI0wx5ypJkZhRdGWjqUlBd6ydrHP2nJZZF9KwNbWnsI6i6Ko8fSPN9p+Oey+dAxsSmPIti+zv6AIfAHRWcyDYEsSmW54ewuzqgXKY/3/p2fH7bm2L/vmiFg1NPPRWu6+K//1ttGbIg2qSOUoqbb74ZAHDWqxqbVB1qoUJzcGF5fess+RvQBUHVtUApwZzTD+HF84vpG0VgTzuwx8t6BkUERcxVePDpilN1QKbKejJ0AaFTEjHH8eLoGHXGhI6hIlIam6fY9trEzgumtr0u4dERJ3z96HzQGLFLhrrKYhfcXovYuVRdxgKfu1Ks4D2rSVpV0SZ0Ogn105Ymz7pPucpi53TPDJBUEbvPb/glAMCFpSx24+U8Jis5fH7bm2LlbtXZXsvmrbfeqm3AhLYr5qmnnsLevXuRL1KcvLFe6hxqwQ3tSiZb54Kg7Nq+0AFAd74Cpyh+MpjQ1V2UNhHP1rHsnI5vwVEZOhmxqzrRAyJkMpFM6AJxpMQuKHQBpGKFhU4FjR3JtYpcY3C57cLXTjsHJcR91kbsWoeC2EVt13axi/i8tdUNssemKUunVeh03WNRzxAN9xwTOxm52/aukHwpiN2i3MzqEUzsZOTu6i3v8n+erOR8uQtz0sZplEol7N69G08++aRUmcNou2r+53/+BwCw7iXTddOYRAkdAOFsXTA7x4SOIZqtixQ6GZKaSUVlTFeTa1DoohARuwihYwjJWIzQScVKEjpRqUpochUVtKj3a5c8EbFLaiZtx/QhaZ+xEbvWQV1QxxGSu6T3tk3sEj5n4Vhx96rosWlsdtVGK/qKit5z+agpyVyprJ3TE/EZSYgdy9IFcWFJZe3Gy437jhK7YoniggsuADDjUKpokbpqtYo777wTAHDKS2eydHFCx+DN1gWFLorufAV9Zx/kErtUoePN1vFIGK/YpcXijZMmdAye2dbLlVihEyJF6BipYue6oOVyemUtsHpFGjxSRiyS+L62iF3WJvptx5JcRuzS4czacb1Ho9hxCRnH58stdmn3qOPwyd1s70eX9tzgvecihC6IiNg1ZOnqygO4Y3xi97kNN9dl6cKIiN0Ht74z9m9RYjfn5B8D8BZtcJNWZuJEy5XzxBNPYGhoCKVeF8edUq7rP5dEF6ngvL5tiWKXJnSMtGZYe9pBfmiKL0OXJna6smoiTbdpYscrdDz7YTKXEitVxDiFLr1Mgs2taZW0pkERvMLW1GbZMKLZYV2xdDGbR6BmEQ397PxQmsROSz+7Gtq+BAIt62eX+X50SWgakMUjdtveNRCdpQviehm7NLlbwjEnHY/YfXDrOzE6nbymfLif3XGnlNHb24vDhw9raYLVcvXcf//9AIA1Z0wDdnJ2LkxSMyyv0DHimmGbNiCChzgZ0znCVUboom7ShObWOGLFTkLoImPJ9p+Lq6w1LXiuo3lWmrhsncy1rauJNg4ZSdMldiZbx0eC2IkKn65RsYliJ/i5auuuAcSL3WzuRydD3GeUkqULkiZ2qULnlwWe3MWI3ec23MxdpjSxSxM6RrCfnZ0DzjvvPADAXXfdxV2WOLRcQQ888AAA4PjTK0JCxwg3w0YNiOAhqhlWuv9cOFunMiAiLHayQhcliCoZuuDxSQgdo0HGFDJ0dbF0DogApDN0YSHLxECKsNipCIyuwRRhVB4qRuxaS4TYSQ+oaKbYSX6eWuuR8PHN9n50slN9hT8rAaFjxA2gSGx2jSNC7D634WauLF19mOgBFEnNrnFMVnL44vY3ov/E/wAAPPTQQ8IxwihL3e7du7Fr1y5YNsWq9XI3TrAZNmlABA/d+QqcLu9iUh4QwcROZ1ZNNRYTO11TlliWktA1oKHJlRCiR+iCEqXY5NqUqUpUYWKna/45XbEAPQ8VI3atJSB2ylOfNEPsFD9HbVMgATNid7T3o0tDV1NsIGvH1ewaR0jsRIVuJkz9AAqeZtc4xst5/EfXRbBtG7t378aLL74oFYehfBX97ne/AwCsOLGKYkk+ThepwCJUODsXxZzTDmHfOUU9I1wBPULnKmT6wsRNWSJVLleL0HkiRrX0oaNUX58aL2Br+9A1O0bTmM3yM5uPTSca+9jpnNBbV3+2pmbsFOjofnRpUCqVpQtDHBdkfEpe6Bg1sRNpdo0P5YmdrNAxxq0STjnlFADAI488ohRL+VN77LHHAADHrotfDoOHLlLBZQO/x9kLnleK88KhORh8egGqPRRDp/QrxSJVF2S67ImPKq4LUqmqx3JrK0RokVXXG+WqCHVc0OmylhUnKKVARb1MdWRsHVXtyzWpfjMnZOafKrriAHpFLIsDMHSt8qEb6uoVMlVcb3lCLdk/29Y2ySuIBbg6Vp8g3vG1cqR5K7EsPc9QQjC0YRHm/V49O3rNq27EcYUD6Lam09+cwtV3vQeDu+coxzn77LMBtFnqKKV4/PHHAQC/m3+qdJwuUkG3NY0eUsZlA7/HOQt3SsV54dAckF0l2GUABHAK8hc4qdaEh1W8shdlTeZIbX1S4rhqsXQKXTVQIUlWBtRhmT71B0FQ6LSs4xhktold+FzLni+dKzxkdUqSLD7own1sdcTTLYgK9zNhazzrIHCvKIldYJ1Z5fWi2bG5VI/Y1VASuyw1uwbjsM/PVXj2EYKhs5fAKRDY01AWu2Pyh/2fVcTug7/5I5AJG6RKMPjCHKUyffm5zQCAJ598Uuk6UPrkdu/ejcHBQVDLwjPD6/DPe14ltH0XqWCePYZuaxp2bQHXHlJGt1UWLgsTOitwf40dSzC0XrxDZZ3QMWTEjkmYDpohdOHjEawU6oQuiISwRGXo1NeGDZ2r2SJ2urIoOld4MELHT9xoeB3xMiB2zRI6hpTY2Y0SIC124WNTEbuo45P5DLModED0s0D0OVoTumpxJpaK2F3z6hsbXpMVOzI+UwZS8cRORu6Gds5FpW8ucrkcBgcHsXfvXqnyAIpS98wzzwAAynPmgDg5PPnEsdxix7JzNqgvdIxX9T2Ncxc+x12OKKEDADdPMbzGwtCp/GIXKXQMEbFLEDrhbF0rhE6QWKFjCAhLUpOrtNjp6hfUZITFLukhK3KudK7wYISOn6Tj0zUlTRvFrtlCx9A1EIM6rpjcxR2bjNglHV+7muW1Cl1CLN7nT4TQMWTE7ppX31iXpQsiKnYf/M0fNbxGKsSXO16Gds4FqRBQ28aJJ54IAErz1Sl9glu3bgUAlOd60kTKBOOV9A6DQaGLooeU8dqBTVxiFyd0DDdPMXyClZqxI1UXZGI6XuhE4MjQcYudLqFj/efShI7jQZgqdAwOYeHpQye2jFjK6OKMZesAAbHjebjynCudKzwYoeNH50ofae9tg9i1Suh8eMUgIksXhkvs0o5NROx460Yemrmuq0qstGPk/PyihI7BxI5H7r544U9jhY7BK3Yf/M0f1WXpwoiIHanMHB8bLLF582aubaPQI3Vz5viv7XhmaWK2Lk3oGDxilyZ0DDdPE/vXNfSfSyItWyfQ5JoqdjqFjskcz42UUElwCx0j7dso56AILrHjzc5lUOxSEWkGSzpXog8AnbGSMEIn9l7dgshD2jXYSqED+AZPcAidH09HVxkesRNtxUgii9c6j9AxUhIMQ2cvSQ1hT/Nl7VYVDnEVKU3s0oSOwSN2Qzvn1v3+L89tBwA89xx/S2UY6buQUort270CVAZmsmCkTGKbYXmFjsHELmrgxAsH53IJHSOuf11ic2sccWIn0YcuVuyaIXRCBYvqyyIodIy4fiM6R7mKNrdmTOwSs3UyfeiiKntdgylUYjWbrJZLFF1ZuBaJnbYR3TJx4uo2AaFjxIqdSH2RJHay/Y0jy5TBfnQiQseI+vwSml3jSBK7L174U6EixYndB+/mEzpGktixZtcglX5vxo7nnntOugle+pMcGhrC2NgYKIBKX2/d36LETlToGFEDJ144OBdkdxe30AGB/nUBsZMSOkZY7FQGRYT3326hYwQqDWmhYwRHsEkKXWy2Trb/XCeIncqgiOD50jHtia5YYbI04XEzkD0+Xf3lmix22ppdJcWQRn3JlhA6P164Hpc5tiixUxDfhgd8FoUOkD/G4OcnIXSMKLH74oU/5c7SBYkSOzImfl1FiV2U0AFAtb8PlmVheHgYhw8nNxXHIf1p7t69GwDgdHdH3kDB/nWyQsd4Vd/TOGfhTrxwaA5e2LREWOgYwYETSkLHYJWJ4ihX4gYqpawInV84oi50AVQzdA1ipzogIstip2OUq85543TGYhih499e51JwqtSuTa396BSoEzsFofPjsfpc5diaNd1JZoVOMZbrKgkdw54G5j3uXQOyQsfotqZ9ufvg3Y0DI3gJi12U0AEAtW0sXboUAPDCCy9I7Uv6U2A7rPb2xL5nxzNL8e295ysJHeBl69448CiOXTQIe5pICR3DzVNUugncQk7b/FA6pi0h5QrIxJQeoas6gKZJk6mrT+gAaGly9cVO1wjXDDyUgmhfdSJjx+eTRaHTKT+6YmV1kmKg5f3oktA+YlTXSkKuo+X4gDaOik2DED3H6LpKQsewp4DXbdykJHRB/uKJt0hl6YIwsQv3owvDpE52WhPpO5KtT1btiZc6a5rg0d8fj//9wutkdwMAsEExx5rG51bfhAUv2a8Uq/tFgoHnynB68nD7upViEZfqWSXCqUlYpaK+wkPVAZ2a9obqq05b4rrA9LQ2oaOOk41Uf3B79k/Hw0m3POksU9bELstCp3Mt3dmMjnqBTVquQaD8L3sapjvRGQsu1bJyD0O1Xq9D00oPALxlMBWhPSXMe3pMOc5x79+ChYVRPDC+RjnWhze9A1OTBZB54vPnhll8n4VFDybXWUuWeIND9u3bJ7UP6ZqetfdWS12RfycUgEtgTVl49PfH4ysvXCq1HxsUeeJdLAvtcXx5zc+lxa77RYK5W6ZhV1zAJkpjf4lLZ254lRUnmNAxqlWgIrncVtUBLQdiuVS6AvCFThMzzRlEi9j5la6s2DUrG6ZBnurW3lSJF942K2KXZaGL+10lVhZoUvO00nxxQSnUJHZ+PaxQroYuHrrWeJ2NYtdwruRj0d5uUJuATFeUxW5tr+cIE25BSew+vOkdmJwoAgAsiyqJ3aKHCXKTFLkpioWPxr/v+toI2JZL3eDgIADA7aqXOkIB4gJwZz5sWbELCh1DVuzqhK6GU8qD9paE4gAhoWPIiF1Y6BgyYseETkPF2BShC3WEbavYRb1fJVunUZ4iF1OXiRe3TbvFrhOELu11mVjtpJn9DakrJ3ZRWT4FsasTMQWxix2MZcSukdhzJR6LCZ0fWkHsjnv/lrrfZcUuKHQMWbFjQsfITXpiFyV3zKmYY4miLHVOceagWXYOtPHDZmL3t3v4mmKjhI6x0B7HQHGKu6xRQufthKDaWxASu0ihY4iIneMk3+DVav3arEkkCZ1gtq7pQsdol9glvU9G7DTKU6TQycRLe2+7xC6LwpPFPnQ6acUAElGxS2q2lRC7SBGTELvUuTCN2M2Qeq4EnjkhofN3MV3B3M1iYrfqfVv9LF0QGbELCx3DsijIXH6xW/iIVSd0jNwk9eUuiFPwBpiOjIzwFzZYPqmtAjt0i14BfKFL2tmUhd8+dkJqxi5J6BifWvnfWMiRrYsVOn9nntjx9K9LFDoGj9gxoUt7CFQq6Rk7ngwdp9i1TOgYrRY7HvETETuN8pQodCLx2p2JiyOLkwvrnMA3i0LXSnjFjqcfnoDYJYqYgNhxr1pjxI7//uMQuzihY1hT/GK36n1bcVJffJOliNh9ZNM7Ev9u2Xxit/ARC/mJ5PMQFjvmVMPDw+kFjSqb1FYAJicnvQLkclxC5+9wysJwOT4zxiN0gJetuyalGTZV6PydEjg9yU2xXELHSBI7XqHjQaTJNUXsWi50DN1iF4dIEy2P2OkSP3AKHU88ndk8nXSq0PG+N6tC1+ppXtLETmRgBYfY8a0yo97HrgEjdvwkiF2a0DF4xG7lVdsShY7BI3Yf2fQOTMRk6erKxSF2aULHCIqd265MHZM62DluoWM8+/SyyGwdr9AxkvrXcQudv/P4plghoWNEiZ2M0MX1r5PpQxcjdm0TOoYmsQMQ319OJo6uptWE9wsJXVI8nf3udNLpQpe2jRG6euLETmakbILYia0HnSx2QrEYR6vYSZ2riGcOp9AxksRu5VXbcEo///QfSWLHK3R+uRLEbuEjYvUrEztam2exXJYblCFVqzuO4++Qkpz4TiMGTogKHSNK7ISFzi9Eo9hJCR0jKHYqGbqw2KkMigiJXduFjqFB7CKbYVVGuUaJna7BFJAUuqh4OkfI6mS2CF3ctkboogmLncrUJxFiJyVhMWInFYtxtImd0rkKPHMEhY4RJXaiQseIEjtRofPLFSF2PM2uUeQmKeY96dXJlUpFal5CaaljUMkHcXDghKzQMRba4/jSml9gwUv2ywsdIyB2SkLHoLU5ilSbXNnACR2jXGtilxmhY+gWOx3TlgTFTlWAAtsrCV0wXhbn1wNmn9CFYxihS4aJna657Gr3i5KEhcROKRbjaBE7LefKlRY6RlDsZIWOERQ7WaHzyxUQO1mhY+SmvGudUjrTIipSFpmdWnUPXvnKzZqy8NT+Jfjd1LHSMRhL7DFsXLgL5X7ICx3DJqA5C1TnXGY6HgKVirZpS+A4nijqIrjUWZshhPj/tKBzKaSsDmTQSRaFTidZFboMQmr9g7TEyom3CjVQq6O01Q060djvT6vYaURF6BjWVAVT84mS0DEm3AJ2V+YrCR2D2BRL7idKQhdGpglWw0ypCtsun8RJi/bj4dHVeERR7H42cibu3nM8pk+dwL6N4nPPBbEmq7Amyt4agqrrCDIB01CJ+KlYVdkMfnvWuMwP0bDmopZzDngZP8vSK3Y6CK6ZmRV0LQEHZFfojhYR03CcxLbV72ViweryHpTKMkYskELeu6dVy6UjRhgdMsbqg6yJHUvgaLp/rOFx5Rj7zp8HagM/vukVyrGWF4ZQoTb+eP0DSnEogAW3dCE/7sKq6luPPCdx7yhn6npkZXn5JM445gX05adRdnN4YOR4abH72ciZ+OnO0zFdyaFYrGDyLHmxsyarsMem/T4ANJ+TrwTcwJqNtq30kGpoW5eVAvYADwpiVsSOXVeqFW8wk5wlsQvJUybEzgjd7EPheIP3r/S9HBA6AN49KCt2QaGrxZKuG2rbNiVLpyJjFqm/3rMiduGuMDruI8dVErt9589DtTb7WOEIURK75YUhFIjXWrWsMCQtdkzoisO1L+wulMQuNznz+ZdK4h4jLXWFWlq9f+c0el4UvEkCQseQFbug0DFkxS4sdAwpsQsKHUNS7GI7S4pKQVjognHaLXbhCkS28o7qk5cFsYuRp7aKnRG62YvEcUfdt8L3cljoGDJiFxa6QCzhuqGZQseQkbGw0KnEikFK7OL6NrdR7IJCx5AVu6DQMWTELix0DFmxy026gOuVq1gswpZ4Bko/yXt6erwA0xUMPFcVErtczqkTOoao2P1s5Ez87PnT6oSOISp2cULHoDmBZsEooWMoZuwa4JWCOKELxmmX2MVVIDqbStopdiny1BaxM0I3+xE4/qT7lfteJhasQj7+7yJiFyd0gVjcdUMrhI4hImNxQicTKwUhsdM1vVQSgmIXJXQMUbGLEjqGiNjFCR1DdOxnbtL1tqHe597dnb4gQhTSn97MDquwpym/2C2fxPql8W22TOwenFydGIYJ3VQ5vhLhFbs0oQMAEMIndklCxxAQO64hzWlSkCZ0wTitFru0CqTTxY5TnjLRFCuDEbqOh+c+TX0Py9Bx3M+pYpcmdIFYqXVDK4WOwSNjaUInEosTLrHjETpd9xan2CUJHYNX7JKEjsEjdmlCx7CqFN2V9CVNc5Muusss0eWVr+VS19vb6/1AvaHYXGIX0ewaRdnNpQ6eGK6WEoWOkSZ2XELHSBM7HqFjcIid0Bw1cVLAK3TBOK0SO95vhLxixxOvlWInmA1rmdjpytIZocs+KedCJKMe+960DF2YJLHjFbpArNi6oR1Cx0iSMV6h44klSKLYiWToWiR2+16eLnSMwhGCH90cL3Y8QsdYVhiK/RsFMP/WUqrQAcDSsUF8//b/g3ds/U3se3KTLt7+7N347r3/F0smBgHqjXjt6+vjKmsY6af3/PnzvR/ojIUysVvykNsod5xCx0hqiv3ZyJm4cw//4rxxYickdIw4sRMROkaC2MlMOhgvdoKxWiF2oin+NLETidcKsZMUp6aLnRG6o4+YcyLT97VhGyZ0Evdzg9iJCl0gVkPd0E6hY0TJmKjQJcXSiUyTa5PFbt/L56HaIxaqOBQtdiJCx3jP+gcbXmNC13Uk/fNYMjGIf7zvOiydHMJHNt3UIHa5SdcXug89czOWTg7hHx7+JvqnBwEACxYsECovQ/rJvXDhQu8Htz61aE9T5Mfc+qydoNAxosSOp9k1imKxgskzJ+vEzptcWG71gzqxkxE6RoTYSQkdIygFKg/wZoqdbJ+NOLGTiddMsVMUp6aJnRG6o5fQuVEZpe5vKyt0jKDYyQpdTNy2Cx0jKGOyQhcVS4GGbJ3KOW+S2MkIHaN4pP4cywgdAKwoDNaJnYjQlapTvtAxgmLH+s8xoWMsnRzCa/Z4+/QTZ4JIf5q+RdLo9mKWtSMUUkLHCIqdrNAxil1lX+z8uehkCYqd6oUdEDsloWNYRLzZNS6ObrFTrbTDYqcSrxlip3MAgk6yWC4jdK2ldo50zCfpx9BwP5NCQV3oWL2QJaFjOI660GnGFzsdEq1T7EYmlITOKw/8bJ2s0DGY2IkIHQBM5rpw4+pzG17/yKab8K6n7gJxgbftqBc6f9uXbgAgL3XSs0IuXrzY+4FOxL5nesBGfpRg055lOG/VDtldoezmYMG7CGWFjlHsKqPSVwK1LbksXRBCQK3aygU6xA4AcRw9k0YSC3A1TYrpWupSoGMVjCCtGKElA9FwrnSTxZGuRujagpYJwoFalk7HEnUzWXzlL7SWBWJb+uoa29Y3sbBLAQ2rKcBxtA0co64LoqsepVTPBPvdXWpCV6N4hODErn2oUPVztaIwCGe4wC10jP844QIAwIefrhe3D22+GW977h4snB5p2Obr6y7Di/PmAbt2YenSpVLllf5EV65c6f3gjsW+x80BxAGsLb24//nk0axJnNP/HF7TvRPvnvNb/PtZ38VrV22WjlXe1o8FmxxU+/Jw5sqNLvFxXRDHBWxL/YImtW9ytq3nRrMIYOkaNaoxY6cLHVLQrCWDFM+VlnVhZ4JpjGWEri1oyybrEzpiW+pfrIimVWhYOLu2FrKulW0somEFiyZk8HX2r9MZS/FepP09oJaFpffHJ4q4IMBr//AB5EkV3Zba2uZfeuj1+NJDrwepEuw9T/xa+I8TLsA/nXxZw+txQvefq1+BXbt2AQCOOeYY8QJDQer8HdJpUNq4GPHEohwmF3oXtD0NkGfkxa7PnsKAVcACq4CT8sCfLbxbSuzK2/qx+BEX+XEX1CKo9Bfkxc51QapOYMUIDWIHzE6xC0iKskAFs5g6Fvf2Q6mWK1ShSZ4rI3QCHE1Cp3reLFtPX80mCp3KPegLHUNFxpjQAWpiFz7fqi1DdbE09a+jtPmDMHjKURM6ALCHp+TFriZ0G3uf81+SFbsvPfR6YDTv/SNAtUfu8/uPEy7A19c1il0QJnSUVjA46A2U8BNngkjfmX19fZg3b573SyhbN7Eoh4klBMHMp6zYndP/HC4sPV/32gKrICx25e39WPxbT+gYvtgNCC7FERY6xmwXO0BcViIkRbryjmqWlokV07wtX64YuRA8V0boBDiahC7ud146QOhm/iRezgahY8jIWFDoGDJiF3W+qTv7xU7ivqR93b7QMaTELkLoGKJi96WHa0IXQiZbZ1Uo/nPV+ThY7I/8+8FiP/5zdW3Ebs2l5s2bNzNtnOj+pLaqcdxxx9UKMpNKZELnRvTWY2J3304+sTun/zm8qXcLBqxCw99Exc6eIsiPNd5Q1CKozCnyZ+zihM7fkYTYRb0/i2LHKipeWUmQFK1NniKxUvorCpcrTcTa0WydRaHTSRbLpJu461D0+uwgoZt5C395Y4WOISJjUULHEDmHSe/NstjpQiAW7esGjfmMhMQuQehE+dLDrwdGIvru17J1ImJnVbyZMd624+7IJlfAa4p92467vV9qLnXCCScIl9vfp/SWANatW+f94BzxX3NziBQ6hj3N18duQ//OWKFj8IpdeXs/FjwRf/GzjN308oF0uaM8K0YIiF3S+3SLXS6nLne8YseRdRISqLTBIzyxOAegcJeLN7PGIXbasnRZFTpdEn80Cx3v3xkdKHQzb00vd6rQMXjOQZLQBd+jY18ZFbtW969LEjqGPZyyGgMBLv7DB3Hx2x9MFTqebF2s0AX2V+1xsffc9GshKHQf2nJL4ns/9MzNeNuOu3HZRV6T69q1a1Pjx+5XeksAJ510kveDewSAl6WbWpB+Uac1xZ7T/xz+oHdzotAx0sTO70cXkaULQi0Ct2Al97NjAyN44BE7nspZp9gBerJ2aWInIChcAsU7GpgNNtFAarlEJSzh4WOEjhMjdPzv62Chm9kkvvzcQgekZ/J4hA5Ib4YVOd+6xU4D2vvXJdyvPELHWPJATLaOABe//UGc0/cszul7litWktilCl1gv9XeZLFLE7qoptgPPXMzttxzD4BAwkwCPZk6dwwTCxDb7BoFE7t771rf0BzLBkbwEid25W21fnQpQhckdgBFWrNrFEliJ/Kg6ySxkxCURIGSmd4lKp5EnNhyyUpYxMNFaz86XRihaw86um0As0LoZjZtPA4hoWNEnQ8mc6JNq5EToEucb51il8X+dXH7EBA6AMgdiWiGDQidKFFixy10gf1Xexs/O6tCU4Xu62svxVtf9Rl8fe2lda9P2DZ2DA8DaGOmbuHChViyZAkAikppkFvoGPY0UBghsLb2+GIXNTCChyixs6ej+9Gl0SB2MkLnF8ICcunrvKbSSWInQaRAqczXF4ynEKehXKoSFjhXmRwYkUWhOxqQPVfh7WaR0M2EmDkeKaEDvG2C54U3OxdFWOxUzncGpzpp1sAJ2tctLHQMe3hqJmOnIHRR/PUjl4kJXYBgto7JHChFqTqNP3j+/ob3f33tpf6giP9c/Yo6sdvU3w+HECxbtgyLFi2SKg+gKHUAcNZZZwEAcqMHpWPYU57YvTg+kNqPLgkmdt8963sgBIn96NJgYuf2l+SFLohtef8AtQr8aBE7LRMwt6gpVjigZYROhNmepdM1x2XWhA5ozjx00gEssebWJJjY6TjfGexfp3vgBJM5GaFj5I5MYcmDk1qErotU8NePXIa/fuQy0GE53wg2w/pCV2MyV8THzn4/9nbN8V8LCh0jKHaPDQwAAM444wy58tTQJnWFIXmpAzyxOzTRjQnFa2mBVcD9E2swOV7A6DFqFQq1CNy85a0+oQohXiWZU6zksip2bB47xUrOFyhdx8fOuw409n3Ttr6rzm/6ukTMCB0fOvuA2pqEDqjdzxqELpfTIz0slo6R5MEv1zpi6cAi2bzOdWXrCAGZVJsEmDG+rKgsdDYoXtfzIr573nflhS4Ybyr689vXPc8XuyihYzCxe6yWnWNOJYs2qbPHj8Ael//gyusncPUJ92J3tR97HYU1WQEcKPeDOhZG1lYxeJL8smK58SrskWkgn/PWeVXFXzVC4bSz0be1xbBV5Y4QonfKE0Wxq/uGmBGx0/qtNYC2h7BOdGSNDOloPE86s2F+s6Jiplyn0CGfE+/7FkWw3tWSHbW8GQWUyhT47HTVM4pfPgkhM1+uVcWOPfM0ZCNHTp4Dp0jwxe+9SzqGDYqLuvdjwCrhFV2KBaJA8ZANqwIMnhwth/u65+GPX/7nsULH+M7LzsOWLq9AbZe6BQsWYM2aNSAAug7sgyXhY+X1E/iLM2/HqvxBlKmN3dV+bCrbUnL3zeET8dNtpwMASJcjLXa58SpyQ5Mg7KLO50CLBTm5C1YgKmIXNZ2KZUmLHbtxsyJ2kfLUZrHzy9SkEarKYteMefB09e9SJYvZCx1kXehQu+4lxa5B6FSu8XxImmRj6cqqATNCB6iJnc7PLgh1peuryK4msmIXykRbY3KrRIycNICRk+eg2uXF6n2B4gv/Ji52QaFjfO/S68QLVJO54mFP6ACgWooXu8lcMTHc6Io8yPR+UEqxdu1aLFiwQLxMAbRc6S9/+csBAPnhvchNQVjsenumsCo/03xbpjZG3C7hrN03h0/Evzx1PsoTMydXVuyIS2eEjmER8axd1DI/OjJ2deUSF7vwzdtusUvMhrVJ7JotdIxZIXZG6PjoAKFjyIhdbIZO5hoPC51srLh6VuazCAqd/5qE2MV9drquewmx0z4hfDie4wqL3cjJc1AtWb7QMXpfEDu2KKEDgFd0CYodhSdz5UbPqQouTAV4QucUCS5e1QMAOO+888SDhNAqdbnRA0C1itwUkB/lk7vKqeP44Il3R/6NZe14xW5veU6d0DGY2O26xOaSu9x4NXnSQ1mxC79GiNfHjkfu0iY9VsjYzRQpGxm76Hhtyti1aA65WSF2upitQqeRZgsdQ6TrQWqTq8g1Hid0oqTVraJTS2np15fy2ekUO05ShY43W8eea3HxBJphg9m5ht1QcGXrbFBc0r0vUugY3M2wAaGLIy5bF2Z0Rd4XOrhV/Pa3vwWQIak74YQTsGTJEhDqID+yD3AB4iA1a1deP4GPn35HXZau4T2cYvfN4RPxi22nxv6ddDmgcyupWbuGZtc4eMSOZ/JhnqwdzyoWALfYJU7qycRO1+oTHGLH/eCw9IzI4xE7vaO/OFey6FSxMwMj+NA4KEIbPLE4snXcfejS3pPP8Qkd1yoRvJMT89bTCfF4s3W892gL+9dxZ+jSnolpQleDJ1s3ctJArNAx+nYnN8MGs3NxQsf4zuu+lVwgDqEDkpthGUzmnKJ3fPnhvZiamsLSpUuVlgdjaHkKEELwmte8BgCQH9o98wc3Wex6e6ZwXOFAavw0sYtqdo0ta0pzbGSzaxxJYhfV7BpbKI3NsSlix7X8Dusoq2tkbILYSclTk8VOa7Or4OjUjhM7I3R8ZE3o2NQeHKQ1wwoPioh7r2h2LmmfonVp0iTxhHMqlTSx09lywUtKM6y2JleRkdwpzbAjJw2gWuL7/OKaYeOaW+N4ZcmNFztOoWMkNcP62bkAr17huchrXvMaLZ+HticAk7rc6H6QamAUbIzYlddP4Oo193DHTxpAEdfsGkec2KU2u0aRNIBCOLUfIXa8WbogMWInesE0W+yUsmFNEjvt/egk0CJ2uuUurguBLozQpYfRKXSCxImdtlGuss2tkStFaOyqIXofxYmdjNA1uX+dlEBEJTxkpuaJaIYdOWlASOiAWjPsv9dn60SFjvHKUqhMwQERguMEorJ1UUJHqtN4+OGHAcw4lCraav5Vq1Zh7dq1IKDIH3mh/o81sQv2s+PN0gWJGkCR1uwaR5TYCWXpgoQHUKiMHgyKnYzQ+WXK2JQnuvvYAdrFrlUDI3jQNYmsVsKDfXRhhC49TBuFjhEWOyWhC26n2n+ubqUIlcmJQ9e3rvtHpd5rQv+6uilLZAg+IxXmWgxm65jMiQgdo3f3zDmSFTqGn61LGBDBQzBbV9d/LkT+yAtwHAcnnngijj32WKkyh9Fa67/2ta8FABQO72i8GAP97CZPnBbK0oUJNseKZumC+AMoLrYxvConnqULk8+BsgpKl9ipUsvaqdzE2sVO10zsgP6MXQaEjpFZsTNCx8csEjoGEzstGbral2Ft6JokXlXoWLaOZcxVz5PG/nVNH+EqguPCGp8Uzs41FIMCX/j+u/Ca0l4loQNq2TrB5tY4Bk8qNPSfq4NSrMsPAwBe//rXq+0sgNYa/5JLLkFXVxfs6VHY44ej3+QCxHbRZ6sJVJnauG9yFabdHOYvGJWOQ7ocFEYs9O+qghY1TjCsI4ampXpgq68964udKoEY2pffyhLN6NsmC3u4ZKlMgBE6rjgas0W6vrDo+lKm83rU1uSq6T4htZUrMjbBONUwCTB1XNBqVcs1Tm257FxdDAJMLXLwuiferSR0AHD3FPBHr7hXWegAYOTEarTM1bDHD+P5559HqVTS1vQKaJa63t5ev3CFw89FvufI+iouPHErXijPw9PTy3HQ6Zfa1+7KfDw1uQIuJThtwYtKYmdPArkJB053AW63wrIhrvyEnXWwZlcdYsduPEWx8xd5VpVWl9b18dAidqriy7IPfkYyOw9kXatO+HGyInZG6Dji1LoFqMpY8DNXXW0gl/PuNx1lUu47yjfaUqhMOiGWvrKp3i+ajs2XQpeCluXNhxbzoMU8QAjmPjUiH4cAhza4QH8FBw7KuQTj7ingiNONl3TvwGvf8qB0nIkVVUysqAJFF8Pr4rtzvXGV1/XroosuQk9Pj/T+wmiv4S+//HIAQH74RZBy4wgX0lPFsaXDqFAbY04XXijPkxK7KZrHpOOdlJ7ctLTYFXcWMf+pKgCA2kRN7CgFaUYH+wxl7HxUxa4uVBvFLtxPKDjyVwcZEDu2fWbEzggdRxyNmacwsqsNMKEDa4aV/Bx1CZ1OmnVPtPteiyiDbLauYTvJz5/JHPsMrVG5Vrug0DFe9vhbpGLdN+XiiNPt/35B/zNScZjMoeidK9oTLXWkPI7f/OY3AGacSRfar7g1a9bgzDPPBAFF8dD2ur8dWV/Fq9dtqXutQm1hsdtdmY9d0/PrXpMVO3sSyI9V/d+Z2FXn9YjJne4sXUNBJcQuquJjUxkIVIp+lo4nfhIsSxdBJjJ2AWaL2IW3a7vYGaHjiNP42Uhl6zR+xkGhY0iJ3dEkdH78NmXrNHa5iBNB0WydL3R1L1LMfZr/uU0JcHCj2yB0ALD/wIBQeQBP6A47vQ2vv+YtDwvF8YUuRFS27o9P6YPjONiwYQPWrFkjtJ80mnI1v+td3hDjwuDOuulNWJYuTIXaeLEyh7s5NpilC8LE7qzjn+eSu+LOIuY/XW14ndoEbt4Sy9o1K0sXxLa8FShU5YUQbrGLFbpgLB5Cza7RoVosdmnzb80SsYuN02qxM0LHESf+MxESu7TPViBWlND5ZRIRu6wJXav6mbajGTbluHizddRxk98rcB1FCl0Na2SSL0YwOxcSOgZvtu6+KTdW6ADgwv6nueIEm1sjyxzK1pHqNG666SYAwDvf+U6ufYjQlCt648aN3vQmroPCoWcBAMOnOA1ZuiDTbh5jThderMyR7mcHeGK3rDTMlbWzJ4H8aKPUMbibY5udpQvC08+Ot5+JruZYEbFLDaVJ7NLkjnNdy04Wu6T3tlzsjNBxxEn/LLjEjvcz5bkfE4TOLxPPZ5tFoWslrdwf577SxI5b/FKydcH+c0mkZeuimluj4MnWMZmLEzpews2tcQSzdR89exGmp6exdu1avOQlL1HafxRNudIIIX62rnj4OcCpAL2VyCxdmGk3nyh2UU2vUaQ1x8Zl6cL4zbFzu6PlzvUyWU3P0oVpQT+71CxdkKQbNqHZNTqU4jxKDE3NsZ0odkLvyUK/n06lDX3oEsVO9LNMypxzCB1PnKNe6Pz9tiBb1+Tm1kgSPvtw/7n4N1JYI5ORYkcJcHCDi0MvSRc6xnmb/iD2b0nZuTCv/oNHYv+WlJ0L42frnApuvPFGAF6LZjNmgGja1f2KV7wCK1euBHEqKB7cnr5BACZ2Uc2xcU2vUSQ1x6Zl6YJQm8At2NFZO13NrjITDTdR7ISEjpF080qco6aJHWeWrqEsHSJ2Utm8Zj7oZmuWrhMGRfAQtdqAiNAhoRnWCF1z9h11T0nEj5I3mYEUUdk6nuxc/Qa0oRmWEngyN1Dx/nGyd/+chtfSmlujuGjgqYbX0ppbk/jwWXMxOjqKlStX4vzzzxfenoemXeGWZeGqq64CABQGt+GCZY0nJ4mo5ljeLF2QqOZY3ixdGOXRsc0g3M9OtgKUGEARSzCGYJauMZRmsZMQurqyZFzsZPrdNVXsjNClxJE75w3ZuiYPiuChQeyM0EWUoQnz1mnqG5jafy6J0PUoLHRR5QkKnQTBbJ1Kc2swW8fb3BrF6LHj+MlPfgIAeP/73w9b16TiIZp6lV9wwQU46aSTYFUdVO7cJxUj2BwrkqULE8zaVXpd7ixdmLrm2K5C6/rSJaFrouLgAAqZ5dLCsYDUwRF8oUxTbHyIDA+eMEKXEkdx0lV2X+n4zNi8kZJC55eJBspkhK4RnYMmWDxFlGQuGKdc5u4/l8TczWMzza2SQgd42TqZ7FwYlq2bXO5IyRzjw3Y3pqamcMoppzQtSwc0WeoIIfjgBz8IANhzXxnj++VEgYndULUHFpF/ULCsndPjwi0oVFy15ljYTfjWpYLOpbfa3SQUDpOh1SeyKHbsX6bI0GemDcvWc01rlWcNXyzBrmsN5dKxhJhOdJ1rXV+gcpqWRsuKqAZRnQyaJTgEm1ujWLdyn5bBEKcUDmByuQPaJZ/oyI2M45e//CUA4Oqrr27q86zpV8UZZ5yBl73sZaAusOsXY9JxxpwujDpdyBNHSexu2bIeCx+y4RQsJbGzp6qwxqcBQkBVbnbVLF0wjoZvW/7qCrYmsbOIljUnAUWxC2ZUFR9cfjYiQ2KnCg03m+kiK2KnY+WB4NrHqmuDaqBO4hXFjrBMv2KGnhQLerJRGcmG+lh6JiUnbDkzVbFTXYdbN2yC8wm15T/d/hJozsKyX8q1yDFOPGY/FnSN4c6Rk5XinFI4gD6L4NqL/lMpztv2VeA4Ds455xycccYZSrHS0Liacjwf+MAH8PDDD2PP7x2csXU/+k7uxqFqn1AMh1pwqXfh5IkDFwQOZl7jjjOSR+mwAxB4YpcjsKoUVlmw47xDgWqtAiQE1CatmauuFdSkhdgWKCVy/eKComoRALVKSPWhUavsuaZRSCxTrXJVbT5nlbyupZw0ZV2UIVZ2yqJKUBAImRXNwtqa3ZlkKH7RIcVaP2N2HRMLoBL3egZlDpipdwghoJAY9MXOM4sDSERBZmWOQaty3Zrcfm/NVmpbgEvR88IkZPTkxGP2AwAWlbz+84Pl7qS3x3JK4QAAoK92fBd2vyAV570b7sehJ8q4775x2LaND33oQ1JxRGhJimD16tW44oorAAD3/iCPBXQYC3Lya7UCgEWocNaOZel8SK2PnGDWzp6qwhqL+EYimrXLaJYuCCFET9aOranajqxdkrgJPsxiZbKDs3bKa4umkZVsnQpRD1OZz6qpo4wFv5iy7Fz4HhD84jWTnQvFEf3cMyh0kdMrCd7rXv0ZkSkWzdZlXOgYotk6t78Ealue0AVYepNYtu7EY/ZjUWnUFzqGaLaOZef6FOv09264H6fnn8OhX3gDPd/2trdh1apVSjF5aNkT5L3vfS8WLlyI4YM2fndLDkvywzihuJ9L7irURoVGX9B54nDLnZ+lC8OydpxiV5ela/ijYnNsu4mRFiGxSxLVVosdE7rEMnFO1pkm4B0odlrnPEuiXWIXtV/RsiQ9TEXOUTOaXcNwih1JG1jFKXa+0EX+UaAZNqNCF7kLgbL6QtcYROyLaYcIHSCQrSPEF7oGXIre3XyrTAAzQhcFb7bulMIBX+ii+MrLb+SK894N9+O9G+7Hhp7ncOT+P8fevXuxcOFCvOc97+HaXpWWPT26u7vxkY98BADw8M1dGN3vos+exJJ8etYu2PQahUzWroGa2FW7baW+dl4s4n3zaIXcNTFLF6Zj+9nxZEN1rRvbQWKndXUCHlotdkn74y0Lz8OU5xy1QugYKWKXKnS8ZUkSOv9NPOcmY/dMgtAF35NanDihC8KTrcuS0LEWFxVqMuf2dUULnQAnHrM/Ueh44cnO8TTBMpnb0PMcBvdZ+OEPfwgA+PCHP4zubrmmYFFa2tZzwQUX4Oyzz4ZTJfjv73TDdYE8qQpl7ZLQIXZpzbGxTa+R8RKydrqaXnXCUR5iW7VpT2IuHd5jaoXYifaXS3jQCfXh6yCx46ITxY5nP6kPboHrM+kctVLo0mKICF1Cto5L6Pw3a5Dr1H20UOiQ/mWSS+jSsnWWnT2h4yS2CZYQX+Z4hC6pCTauuVWUpOwcL+/e8ADeveEBbOh5DoD36Hnw++eiXC5j48aNeOUrX6kUX4SWPjUIIfjEJz6BUqmEPVvz+N1tRQCe2MVl7ZKaXqOIa469ZespWPAwZ5yErF1i02tkrBZm7WQRnJBXaz87NumxIrGVo6g4HyUZO+F+dJ0kdiLx494r8zCNOkftErqIbJ1Uhi5C7ISEDohvhu1QoQu+v6EotsUndEGisnVZkjlAuD5raIKVyc7FNMHKZOei+tWlNbdGcc3Lf9bw2rs3PICze57F2T3P+q/99rYinnrqKfT09OBTn/pUS6fkankqYOnSpX4z7D0/LeHQnpkiRGXt0ppeo4hqjnWGC+g+JCJjcoMo4uM1oa+drqZXFkuQBrGTyTxqHEBR16lZZVRr6MEnNdIWyKzYSQ+M6ASxk4nb0BFe0wO13Rm6gNgpNbkGxE5Y6PwNFQdR8MaVoVYHiT54w1OcxA6ISA4SMRAjQ0Knq7lVIDuXhGx2LtyvTnYwxGu6d/k/s+xcUOYA4PCLFh742RwAXrPr4sWLhfahSlvady677DKcc845cCoEt367B27AtZKydqKIDKKIRXdfO4tks+lVkkz3s1M5x7VRgdJC58fJ0MNLB1kWO5V4bFvVB2pwSg8NtLzJNSmOrND5AUj9/0qF0VfvRI5w5S0Gm6JENDsXhmXrsiZ0CpCJqTqhU2HNigPa+s7pam4NZ+cAwHWAB77/UpTLZZxzzjm49NJLlfYjQ1ueFIQQ/H//3/+Hvr4+7NuRw/2/6Gp4D8va5YmDkWrj33lhWTuofIa1rJ1Vdr0Jh1WoNcdmapoHxbnaZvrZKR6TRrHThZ4lyozYNR0topCtz0nLXHQW0SN0Or68ZfC60XF/Kwsdk0odQqdtVSENcRxHi9AtuaWAxd0jLRkMkcZdk8sis3OMA3d9FJs3b0Zvb2/Lm10ZbbvLFixYgI9//OMAgAd+2YWdTzX2K8iTKmziYrhSUhK7m55djzmbcqiWLDgF+ZPs96fTMTu9juVUdMQBasuC6fr2rBCHTXKsI+UP6Dkmy1K+MbO0rJi2Oem0LSOXkc85Y2gROvYFSfVLm65lrair/lmxVg4dE2NnpZ9zYLJ3JSSakGPRVE+oCh1cit5d/FObNG5u4bF9K/DYvhV4/7Z3KhXlrsll2F+ZEyt0O57M4frrrwcAfPKTn8TChQuV9idLW786vfrVr8Yb3vAGgBLcfF0Pxo5EX5BV18JwpYS9UwNScjc1UkTXkAvXBtw8URK7OmRT9m5IyFRuRH8hdk1iJxsnuLi4ropFstKlwc7dbRa74Ez07RY77ZMMZ0HsdAtdBlbR0Cp0qPUJlRQ7ElzHVXK1AK8QmqZdivpZKWSbu8Ho2L9kn8BmwsqSOzDctjK41MLj+5dhcrKAyckCnj8wTyrOXZPLfKGLY+wIwf/860pQSvGmN70JF154oWSp1Wl7PvyjH/0ojjvuOEyMWLj5up7YuqfqWphycspZO0o8sVPN2vmI3kjhm7jdYhdeOktH1k5G7OKEQ1fGToP0amuK1XJMbb91Pdopds16iLVR7HQLHUNGXuqEDvDOi6jYUVe/0AVjq6DzS47qsoWyRPUJbGMGsqEsU4rdlSRg2TkmdCowmUsSOtcFHvr3CzE0NITjjz8eH/7wh5X2qUrbnwzFYhFf+tKXUCqVsGtzHvf/PFnYVLN2QE3sBLN2uXEHuaGYNHCrm2OjKoOg2LW4OTbygUEsr4+ISFniKmmBSoomzYTfYrELv5dVeNqydgJC1dSlwLKQsZsFNEvofESmLQoLHUNEpHTJcZz8dGq2LmGgnFATbEx2rl1NsM3KFBJK8fS3T+F6bzg7JwtPdo5x8K4/w6OPPopSqYQvfOELKBaL0vvVQdulDgBWrlyJT3ziEwCAB/6rhC2PeBMObptegmcnGtulg1k7ZbnjzNpZFRekXEkOqEvsZOMEs0CtbI5NW2oqLQZP5aGt6TIjGTugZWLX9LVdOcvBF4fznDRbAFucrWu60IG/GTZW6Bg82bpmC52u/bQ6WzfLm1ubgksx/6nxlLfoyc4FZS5O6PYFXt/ycB7//u//DgD4xCc+gWOPPVZ637rIhNQBwMUXX4wrrrgCAHDrt3qw/3kbY04XRivx1qujSVYma5eIaqZMd3NsUpzUtUxb2BzLUzmnNF0mZunqytN8seP+u2mKldhPix5mLRK7VggdIy0rlSp0QHozbKuEjvc9XLtqwRefZjW3xryvFahMB6MLndm5tKZWAJhwPSfZ/7yN27+zAADw9re/HRdffLH0vnWSkaeBxwc/+EFs2LABlTLBz/+xB+VRvspBW5NsC/raEd5vhlnM2kXAXRnKNMfGlqcNfSEbymCB2LZShdYKsWtJlo6jHGIxEs5Hqx8gTRa7VgqdT0y2jkvoGHHnRVf/OREBylK2LgrB44ltghXIzrVCtHj3kTs40pT9NyM7x8vECMHt3zgRU1NT2LhxIz7wgQ9I7183mZK6XC6HL37xi1ixYgVGDtvY9M0J0Cq/2OnM2mmRu7CUiX5Ta/cgiro4Mc2xMstNBWPIVqhZEDsgMmsn1e/OZOxCMSLOR7syAk0Su7YIHaK/iAkJHSOcrWvWgIhmbNMswmWZhc2twtm5Sc610jkJy1wrsnNBnArFvf96Afbt24fly5fjC1/4AuwMza+akafADH19ffjKV76C3t5eHHnWwdgNLwplG9o1kCIRnX3tZJfiCsaRpVnNsbIPg8BDiLvptaEsegaWZDFj1/IsXUw55GNk4yHWDLQInQqBbJ2U0AH19227hE7j/rU3wbayubVZhOqQdotlOwZCBKEuxejPXoHHH38c3d3d+MpXvoK+vj7pcjSDzEkdABx77LG+/U4/PoyJ/94vtH0wa7d/ug+oSM7rFWiSdfPqS4S1ta9duD+a6hJaOsTOsgENE25qQZPYqc5np0vs2ip0gXKox9CQrdaBxmydNqFTyA6wQRPSQseoVtsvdDq21z1gQqPQqWyviyz0nfv9/uXYdGBp0wdCJPHETx38z//8D2zbxjXXXINVq1ZJl6VZZFLqAODss8/Gpz/9aQDA5D2HMXnvIeEYVdfCRLUAa9JCflKu4mFZOxDoqXh03OwubW+zpc54lOp5+GtYCklLE7XS7vWJXdszQVlDda1QYoFYROm8qm5fh47mHsvKxqoKOupE5XuX1IqShS9DBMTWtJKNluIoxtFwrZJpBxMTRUxMSE4XQgn67u2WljkA2HaHg22/8jziL//yL7Fhwwa5sjSZzEodAFxyySW4+uqrAQDjN+/HM7+SW66GOEB+1EHXkCMtdwACS9SoNBPUphXQJXdZQPXBYBFlsfPmfsuA2OlC5ZzWMidtF5AMrM4AoP7a0vAFQum86FiIXsdDsrZWM3UUPiN2HKr1oSqahC4TsGPJSj2kAiHKa4JbZQdW2QGRXequJnN995XQu0+yiw6Ab113Gjb9xNv+Ax/4QGZGukaRaakDgHe+8514y1veAgCY/+sn8PRvSlJxiENhTznIj2ZA7IJxVGmz2GnLLs0GsVNcY7OBDGTsTMYPfpZOLQQJvyAXSKPQAZC/ZoPll62DdAudzJeILF3fs0HkGLatXBdbZce7PlWE7r4Sevc66N0rL3Tf/NezsPDxxwAAb3nLW/COd7xDOlYr0LRSc/MghODDH/4wBgcH8etf/xoLb3sUWw69FBMv6ceZq3aLx3Mo8qMO7CkKp4ugUpK88IIVkuzNyMROtc8Qq1TbVEERQrxmC7Z/paZh29teMstDat8OVda7rAXy/m9hc0xk049FxM5nxHkjFhHqYxcWENHt48rRFqLkiVj85YsROpFz4m+foQxdEOq4YisZRB0Hq8d4Ub2vZmN2bjag4Visck3AVGTu/hJAoSRz/3jzpSgeOICljz2CiuPgoosuwoc//OG29y1MI/NSBwC2beNzn/scyuUy7rvvPsz73UPITZyLJ3auQeXYaZy1epdQPOJQ2I4Dq0LU5C5qHVcZdMpdKyqriOZjdqH7csfzwHNjbjiLAC7ngzdmP4QQUMtSz57xjjjWnaULIip2EUiJmez2WRa64N/SypmSoeM5J4lCJyKXTRI6AN61yyt1cefUpYDNUfc0u7mVuuny3ClCJzvbQTvwW2zkv7hkSeYAYO6mQ5i793eYrlRw/vnn4zOf+Uympi6JI/PNrww2h90555wDQh30P3M/+rceRs8TXXjirjV4dMdK4ZizsklWZRCFBuqaY1Uqz9nQHCtAagdtnvOZIgg8TYhpEtMx8Fw7KdKnrck1TS7TaKbQ1UjtW8fTFzB1Sa/O6D/XksESWRjRrQtWz6oKnY6m1hflm1r/8eZL8Y83X4r+Z4E5Twxi/v7fYXp6Gi996UvxhS98AblcR+TAOkfqAKBQKOCaa67Bhg0bQFwH3c8/gK59h9H7AtDzRBce23lM5HZz1w1i3znxc9axJtlZNZAiTuxcTX35Eqgb/q5D7BTkrpPEjosm9pFTlT4A2cnSqSAgdHHvy3qTawNJD1PeY0j6MtkhQtcSWlmXNPOYmZgqypwvdDJQgr77utF3fylZ5ggw/SeDsX/+2i2ezPU/C9gTh7HowO8wOTmJl7zkJfjrv/5r5PN5ufK1gY6SOgAoFou49tprccYZZ4C4VXQ/fx/ssYMojFB0byrhid80Zu2OHRjE1MKULEYga6ckd0GxU5W7ZmTtWpjO1yZ2cVk73j5NhHgPNlW5i6uMm9n0GkXU+RSQqVk/eEJEpJowGlZY6OLe1yqhqxGZrdMx3VCrhS58L6i2GuikxV8Om9b/SzE7VydzMvVnUOZedND7Ynp27o9WPdzw2tduuRRfu+VSDGz3frfHDmLe3kcwPj6OM844A9deey2KRclpVNpEZ+QTQ3R1deFv//Zv8dnPfha//e1vUdr1ACaPORsFLEFhBCgPd+GJ3WtQXTklPJgirr/d9Jwc7Ml+5A5wrmOXtYEUs2EQBW8/u6SyqPaza0I/F6nmHsV+duH+YKKiFtmfLAtZOhkJCfZtU2x27bgMXZBw3zqZYwgPmGh3hk7ys6SU6hWirGT6VdHVd06kDiYEz10xB8CkJ3MP1PrNcYhcHF+79XUAJb7MAYA9ug9z9j2KqXIZZ599Nq655hp0dcmtStVOOlLqAKBUKuErX/kKvvjFL+Lee+9FaddDmFqxAdWB5SiMUE/ujpTwxK41qBwzLZySDModAFRKFpxSTvyE6ajUWAwdI2TbgNQgiiiY2AFKo2O1iB3Q/k7M7FzKngudgyc6VehC28oKXd25UBXLdghdDX8krOy5DA6YMCNcPWaT0LVpIIRz3KQ/EEK3zAFAbngPevc+irLj4Pzzz8fnP/95FAryK1e0E0IzMYW2PNVqFddeey3uuOMOAARTy05HZe6quveU+wkmlrvoftHC4ofFFxemNoGbt5AfLiN3kDNTFwUhII5CZ1Cg1ueu3c268n3+KCt/3MhX7jJQQHa9V78ciiKiIYby7acgdbqgGSgDAPWBNdqWnFMoh465CRUnfCWqDzMtS90pxiDqq2VoydSpxtDweFaaYBoAydW+ZEgKnTu/39tWek5Egn3nzwUA9O6RqPMJMPHHQxjeMg8D2xo/j/zgTnTv3wTXdXHRRRfhM5/5TMcMioiic0teI5fL4bOf/Sy6urpw0003oevF34NUplBeuNa/oQojFICFrsMU9lQVTpfYYc9k7RyQmlBRqQWwM+DPmrJMss0TXqYMAFUsh0W8GJKC62fsAKXKRqmyYuVQWodXvVlaFS9LpVgGkek94rZXQIvQqTa56hA61a4alsU3LUgz0SF0swHLUvriCqgLnV8O1e0l60gyMQ1AUuZqdL84ib1RQkcpCgefQfHgFrgALrvsMnzyk5/siGlLkpgVV79t2/iLv/gLXHnllQCA4sFnUHzxsbqHRGGEovugA2usjPyRKdhTVeH9OF05uL1dAKW+3B3NUErlhYRVvCoVuG3XZi6XbDJjo3R1VFoK2yotlq3S5MfQNVhANo5/Lchv3/bBG1kROkDhi1JtvVGV7hGqx2GETnl6kMyhIHSk6mB65Typ7bv3TqJ77yTs0ekIoXPR9eJjKB7cAgB4z3veg0996lMdL3TALJE6wKvQ3v/+9+PjH/84LMtC4cgulHY9CDgV/z2T82yUF/WATFek5I7mLNBCLctXEzsjdwpNiEGxk63MLaIkdt7uFcROpeMw26ZWiSs398j25ZLdVgfh/UqUgwmdSn84JTIgEnXXjsxDVPX6y0qTa6czm2ROEjIx7f2reM/m8oBYy1pQ5uzRaQyfMrf+DU4VF/XtR/7ILliWhU9+8pP4kz/5k8yvFMHLrLuCLr/8clxzzTUoFovIjR1A9857QSqTAACnC6j2eCZOHEda7nxq/dNaLnftzkpEIJ21C85Dp5q1y4LYacjaKdHGjJ1wti7uvQoxZEbxKqFDJJrR90vkXoy67kSawnVk5zIodC3tbp7R7Jzfn64V+wrIHBM6EcIyx5iaO3NtkcokXuJuxUMPPYRisYgvf/nLeOMb36il/Fkhe1eRBl7+8pfja1/7GubMmQN7ahjdz/0G1uRQ5HtF5c7pysHtK9W/KCB31FKswDL+baLtzbE6xE6mcg0+mFoldnHXmsr8aK0WO7Wdtb/ZVZVmdebnzdbFXW+8X1Kz0NyatHRZJ5BBmfNRLBvt7U59T6zMEYKp4xambh8nc2GsiUGsPPQItm7dioGBAXzta1/Deeedx3UcnUSGryY1Tj75ZHzjG9/AqlWrYFWn0L3jHuSO7MbkPBvTS/sb3h+UuySxq2uCbfgj5etvl3ExU0UpaweofXNvdz87XrFL+vvRkLFT/Tvbj8Drsu9LCKC2fbtHZ7a7yTWD2bmWktHsnE5oMbnpNC0zl9b0miZzrOk1d2Q35u55EIODg1i9ejWuu+46nHzyyRxH0HnM6itq+fLl+MY3voFzzz0XhLoo7fkd7OGnUO2OP2ziqA2mAGD629VoW3NsJ/ezYxwNYqdShpTYacJ2VAhd0v3Hc30lNcEaoVNjlstcGuF+c6IEs3NxUEIwNQco7H8KpT2/Q7lcxnnnnYdvfOMbWLZsmWTJs0/Hz1PHg+M4+Nd//Vdcf/313u/di5GvnIaufZOJ21HbBnIW3K5c3TQopOoiNzIFazR5e+/NXuUVngKFOArru7Lt2jVfneuCCnbGDj5A/Lnq0gg+VGTL6jhK50lpPjv/c4rYnrdSd91oORY5pqiHM+9DUXGqlMg57EQfyBHb80pZ1OTKR4XQMaJG84l8YYjcvoOErt3Z0PD2ojKnMhenjvnpFOST9nY3ZOrYFCWpMldreg1n6kr7vHlmcyPp880On9SDV6w+ggceeAAAcOWVV+Kqq66CNcuF+qiQOsYdd9yBv/mbv0G5XIab60EOZ6Jrf/p2UXKXGyvDPjzKv/OQ3BFXceLadk5CXJt8WPTSqVtZQkZKpMtbEwvJ80WT5Cx94+htRSqWKLETPRYVsdItdopSRwSmHcic1LVaMiyrXixEM8Dhc91OoZM571mSuhYKHaBB6gpqi9i782e6OXHLnL8BwciZS/1fRWQOAIbXEKzMb8XevXtRKBTwqU99ChdffDFnyTubo0rqAGDLli343Oc+h3379gGwUBg7Dvb0YhCk37xBuXNzFn+2LkhA7pSzde1cWUIiW1e/vaSUqJS5XVm7YJnZ9qIVfFjsZI4jsL6p9LaS+GInK0QKa7OqrHHbQCcJHcOeWRFAXAoDzegq5W9Xc2s7pU61G0YHSx3L0gnLHAAQgunVCzA9Jy8scxQU1eJ+kDk7US6XsWzZMnzpS1/CiSeeKHwMncpRJ3UAMDIygmuvvRb3338/AMCeWoTC+PEg4MsAMLkj5SrIZHybfiLshm9Xtq7dUgeoZZs6uTlWFiZ2SjKvQaykNlWUutr+RbJ04f13crOrklzYtlofTcX+qW3tP9duqVNp6muj1Kk2vbrz++X7zBGCytLaAAdOmQMACgfl7u1wil7z27nnnovPfvaz6OvrEy9DB3NUSh0AuK6LH/7wh/j2t78N13VBqt0ojq2D5aQPwZ4J4q0/SlS+EbmufKXXgU2w9TFkhVQxa9dOsfMCyG/runqW/pFBR7ZOkbZNYdKpQgcA+bxajLzCapLtHhDRrvOuKnQK62sDbW56dV3QnpL0IAjaVQQE58dzrXEsO3MIzz33HCzLwlVXXYV3vvOds77/XBRHrdQxHnvsMXzxi1/E4OAgQC3kx1cjN72EqzkWAFB1Zi5emUogKFai22egCZbFkb6MVMSuTU2xSn3sZoLIbVfbp1SlzR5wqpk+DcgIXkcKXbv7dKlm6Vjzq8xx6BA6i6gtWyaz23Y2uboaupmgTVLHyp7LKV33PHPb+e8FRbWwF2TuLpTLZcydOxef//zncdZZZ0nvv9M5+jQ2xJlnnolvf/vb2LBhA0BcVHqfRblvMyippG/MYHKkKjai2xOi3iyiZTZ3AiL74FBZL7JNExUT1YrbCyK3XW2fxG6faOigIyYNTprYloeMCJ0ymkReCFmRZEhsq7QGsxdAfu4511X7kqgRqbolWHbZz80VS1JQUsGGNwKVnu0ol8s455xz8N3vfveoFjrAZOp8XNfFT37yE1x33XWoVqsgbgGFsRNhV+Ykb1h1QMoBAWSVAm/lQCnAvlUFbwaR7VWzdUm/pxGuiFqZtdMxKlZlyoA2N8MCgt/Iw5Wt6ghaDYhk7Foqgp00bUkUEUInNUjC31hQsnSUP4jotSpQVm0jXFWzc4xOytJF1X9SWb6ZY6b9Palvd3JH0Lf6RRw6dAj5fB5XX3013vrWtx6Vza1hjNSF2Lp1K770pS9h165dAIDc5HLkJ1bGD6IISx2DNwMWlDqGJSCGqlLHYvC8FkWc1LRK7o7WZtjAfrkq8biHnOp8dxrgFbuWSd0sFDrhuFHHwDtIRVezaxCR65R3RZGsyRyjU6QurvxCUth4rElSR+GgUtoJp/QiKKVYuXIl/tf/+l9H1ejWNIzURTA1NYV/+qd/wn/9138BAIhTQmFsDexq4/JisVIH8GXtoqQO4M/aNUvqkl4PkyQ1zZa7Nk910jFil/Sg4z32JjbD8Yhd06VOxyoFGRU6odhxx8Ajdc0QOgbPdcpx/jMrc0DbhQ7gkLq0uo5bCqOPNU7qHHsEi045jN27dwMA3vCGN+DDH/4wSqVS5PuPVozUJXDffffhq1/9am0QBZCbWo78xLEgwa6ISVLHSMvaxYkdwCd3zRS7tL8BfELTTLlTzdYBs1/s0h52POe4BSTJXVOlrtOzcwBXH7rU/SQdR1oTbDOFjpF0nSZsq+X8NlPmGO3O0tlWvLzzlJ9nkERKXROWOgoXldLzcLv3wHVdLFiwAJ/61Kfw0pe+NL08RyFG6lIYGRnBP/7jP+L2228HAJBqyetr59TmvuGROiA5a5ckdYykJtlmSx3Pe3iFphlypyNbp6N/HZBNseMVjqRrqIWd5ePErmlSd5QIXeq+eI4j7oHfCqEDhKWuY2QOUP9iiiY2vfIeQ2qWL/0Yg1Ln2KNYetoQdu7cCQC45JJL8NGPfvSom3tOBCN1nNxzzz34+7//+1DWbiWIa3lTmvAKQZTc8UgdEJ+1a5XUJb1XVGZ0y11WVpwAsid2ItKRJs4toinLezUGVI/RbqELrBahtD/e44iSr1YJHSPqGg2vrd1JMsfIYtOr6DHESiHfsdFSEcjn/L5zbvdeuK6LefPm4ROf+ATOP/98sfIchRipE2B4eBhf+9rXcMcddwAAiFNEYfx42JMDfNm6IMEmWV6pY0TJXavFLur9kktoaZO7NjfDAhpGxHpB5LeNEjsZ8Yg6t21A6xJfQdqcnQPaN2VJw35FjyWYrdOVZRQleH0Gyt/WtVoZqksJSqK16VW2DmuQQrHjov09cHKHMeeEQ9i/31sZ4qKLLsKf/dmfYWBgQK5MRxlG6iR44IEH8H//7/+trR8L2FPzUTi8HJZbEAsUrEBUJpNltFrqwtspZqi0rE4xG/rXeYHktw2KnYp8BM9pG9GyxBdjNmTnAKU56Or2LzWpcC2zpiUbJjkfHbs2a9u2ffAD0L4MPQuho+lVtd4KSp1gHeraFZQXvQincAgAsGTJEnziE5/AOeeco1amowwjdZJMTk7iO9/5Dm644QY4jgO4NgpHliM3vpB/NYowKjOna1iCSbliyYrcGbGbETvl9WZp26VOG7NB6CxrZpJb1XKoHEtOYekwvxCKEwxjFsgckAmhA+Ct96qCbQO2JZ6dA0W19xAKxw5ibGwMtm3jiiuuwB//8R+bka0SGKlTZOvWrfi7v/s7PPPMMwAAq9yNwtBK2OVe8WC6xExlLVnZJcuCMVj/QskY1HW9c6EyM7mq2CkOnGCiTRUX5QYgfxyBh40WUZaFWNkQwzauDgEwkbLkJUCD0M2shqJwPLoydYpSp0Xo2ihztLa9ynHMfIFUuL+t2koaqudTQvSd4hiOOd/Ftm3bAABr167FX/zFX5h55xQwUqcBx3Hw85//HN/+9rcxPj4OAMiNz0f+yApYrtpEjMIEP06ZtWTDl4PUerQuqOvOVFYSMWi1Wv8QFq38XQq4ikKl0r8usM5qx4td8BzIyBn7HNstdrJSp1PoAHEZYDLHflYpgx9T8piCItau/nTQ2IQtioalvGgohsyx6JI5vww6VmIQkDrXqqAy9wVUewcBAL29vfiTP/kTXH755bAlrwmDh5E6jQwODuKb3/wmbrnlFu8F10JhZBlyo4vq57aLo1lNqCKVRjDTFrzRBWPQajWwqfhDgLpufaaMPZBFpudoVzNsRF/HtohdxANI+HZPGmnMS1im2iV3olKnczBE8F4SEQOdza0NsQWPLwsjX6FxZKvIOW2CzHnFEDsW3TLnl6NFUkdBUe07gNyKQUxMTAAALrvsMrz//e/H3Llz1ctgMFLXDJ5++mn8wz/8g98kSypdKBxZAXtqILm/XbP7xfEuOxYewSkqd4FsXf3uxeSuQewAMblrl9hFla0dYhfzIBK65XVMcRIlU+1aJJ4X3dm5ILyC0EyhAwTXco2RrxZnzFoudE2SuZmicNaFTZI5vww6zmuC1FFQOKVhLN5Q8ZfgXLduHT72sY/h5JNPVt+3wcdIXZNwXRe33norrrvuOhw5cgQAYE31eXJXiVnbTofUAekP/rQbOJitCyIid6FsXf3uOeUuIQa33LVa7FKW42qZ2KU8jLhvex0TEifJVCvljkfqmpWdC8IjCs0WOn8/HMebhZUk0GKha7LMeUVJP55mypxfDh1ZOtuOvQ6cwjhOurSExx57DAAwMDCAq6++GpdeeiksHfs21GGkrsmMjo7i+uuvx4033ohyuQwAsMfnoTC8HJZTbNyglaNYk5YdS5IPHrmLydbV7z5d7iKzdXVBOPrd6ehfB6SLHWf2sCVix/lQSrz9dawJyyNSrRK7tLI0MzsXJu7zaUb/uSTSjplHuFowtYkWoQOSs4IaRA5IlzlG0jG1Qub8cjSp6dW1yyjP2QOn1m+uUCjgiiuuwLve9S709koMJDRwYaSuRezbtw/f+ta38Ktf/cp7gRLkRxcjP7IEhAZuiHZMTRKuXKKaYKNIk7ukTFvd7knwl8YwaWLnbxuTvdOVrQOSxU6gv19TxU7w4RRbBYhci3FiJtLk2Wy5iytLK7JzYaI+o1Zl5xr2G/N+kf5uTWyG1SZ0qs3hCfCK3ExRoo+plTLnl0Nz0yu1qqj07wdZOOgnMi6++GJcddVVWLJkifq+DIkYqWsxzzzzDL7xjW/4qWi4NvIjS5AfWwRC7dY1wUbRsHQZp3iEK8q6VS6Ss3WNRYjI3nHK4UyQiOydLrGLm+pEYnSuFrEDGo9J4iEVWQ3IXIthMRMdnNBMsQuXRdOExtzZuSDhPqs65kuDpAA1DH4QHJQ0s3PxfYf328z1W2UHqyQgKnMzxZk5prp7r0Uy55dDV/NnLgdKHFT6DqB4zAjGxsYAAKeffjo+9KEPYd26dXr2Y0jFSF0boJTigQcewL/8y7/4CxXDyaEwshS5kQV8I2XTdyK/LSH82bow4eydhNh5m9bLHXe2riFQ4AHVrP51CvPpaRc7hYeVtodLUMxkpxFphtypTJETFU5FxNjnpCk7V1ceGfxpShTmjmtCM6x2oWuzzHnFqdVpOrJygNpcfxquO2oTVPsPo+f4MQwNDQEAVq9ejauuugovf/nL9WVaDVwYqWsjjuPgjjvuwHe/+128+OKLAABSLSA/vAS5sQXyK1MAepoavULKbReqLIQybQEavtHKlif4QNcpdqpyoLspVkdTkpZ1hF15oQvG0ImGFQz8UJpErC3NrVFYRM/50Sh22oROF7V7TOWRSQjJhMyxsqicH296kkHMWV/GgQMHAADLly/HH//xH+PVr361mW+uTRipywDVahW33HIL/u3f/g0HDx4EAJBK0ZO78flycscybaqVmqossBn0VZf/Qq1CdFw9D3sdl72uJbR0Zuw0xdGx7JBWVM+z7iWpVIWunc2tUeQ1LPsFaJM6YmtqFtRRHg11F4CZL4FtljlATegoXFT7hrDgDNdPRixcuBDvec97cOmllyKnYwk5gzRG6jLE9PQ0fvGLX+D666/3p0GZydzNF2uWZVkt9tBot9yFYikvW+XHarPgZUXsgs1LqmJXE3ElsQv2ZdSF6lJlOpak0pWd0xDLX79V9RznczNdJdQKBOUl4TKYpVNpatV6/TN0La0mOvExcVHtG8Tc9VXs378fgDc9yR/90R/hTW96E4rFiNkcDC3HSF0GmZiYwC9+8Qv8x3/8BwYHveHgpJpHfqTWLEsFRtgF++4As0vugJlKs51ypyJ2wSW0asciLHdhOWCfjWrTeS2OlNwFHzy6H2yyS5XJdCRvRnZOMV7D+q2y55dl58IDpMQLVPs/1MVBOE6GhI59No4jV0c1Q+YAaaFrOKciq/sQB9X+QfStncbhw4cBAPPnz8c73vEOvOENb0CpVJIqk6E5GKnLMNPT0/jlL3+JH/3oR36zLJwc8iOLkR9d6I2WTSKqD1oW5a4Wr6Ozd7JiF7WElmjWLmmSW1VBrMURFruYVTW0IrqqhehUDwzdMqcQ18/OhRE9tyw7F0ZmOiQdK4ZkReiCn4mo0DVL5ILoWlKNZ+Jj4qAycAjdx01ieHgYALBo0SK8613vwqWXXmoycxnFSF0HUC6Xceutt+IHP/gB9u3b573oWsiNLkR+dBEspxC9YdLAAt1yB6gLnoaOyF452iR4omIXN5BAROzSxEBU7FJWQeCSO55VPnTCc85lVi3Q2dQaB+c+GrJzYUTOaZzQAWJSFyd0fiyBFUfaKXRRn4GI0LVC5gD5LyXRb4j9k2uXUR04hMKKCYyPjwMAli1bhiuvvBKXXHIJ8vk8dzkMrcdIXQdRrVbxq1/9Cj/60Y9mpkKhBPb4XORHFsOudDduFGyCjUJ0XdckdGXvApdkpppnAY6VHDj3lzYylFfsRFYv0BQrVex41+XVCc/5TlsuqRn95tLg2Fdsdi5M2jmNam6NgueeSxM6P1bKaiO142q50KWc99TR+q0SuSC8128asct5TaIy5yAwZwROra5YuXIl/uiP/givfvWrzQCIDsFIXQfiui4eeugh/PjHP56ZxBiANdmH/MgS2FN9MyNmZSYRNtk7PtKW2FJdZSFN7GQmvOVd/i0tDhKydiJNRK2SuwSpa3l2LkjC/lKzc2GSzmVSdi4Mz9rRqiuF6MzOBcuVBs/nm5Sla4fMAXqXUAtOEwUKpzSKypyDcLvH/NfPOOMM/OEf/iFe+tKXmvVZOwwjdR3Oli1b8OMf/xh33XWX/+3KKpeQG12E3Pg8b1BFWrYujC65A7KdvQOaK3hxYif6QIwbQCE76W3kihhysSLFTmJ1De1ErWwRKldbZS5lv9zZuTBR51JE6BhR13PUgAiuWNGfRcuETuSzjRK6dolcEF0rbbCJj4mLau8Qlp+Tx44dOwAAtm3jla98Jd7+9rebFSA6GCN1s4S9e/fihhtuwE033YTJyUnvRcdGfmwBcqMLYE1LpM6b0TQLHF2CFxY7lRUWglk7FQmJao6VjRfO2qnModVMuYtr6muXzAUJlEE4OxcmeA55m1ujCN9Xotm5hnj1n0PThU7mcw0KXRZEjqFxhQ03X0a1/zBKx05jZGQEAFAqlfCGN7wBb33rW83arLMAI3WzjNHRUdx00034+c9/jr1793ovUsCe6ENueAHsyT65yYybkb0Djg7BY2KnY4UFV9NEqEB91k5Vbpjc6ZqktQnUTWibBZljWJa6zDHYuZPJzoVhn6Wq0AXRKXSapogB4Ald1ibcZiieMwoKp3sU1YHDcHvH/Ht0yZIlePOb34zXv/716Ovr01VaQ5sxUjdLcRwHDz/8MH7605/ioYce8l8n5QLyIwuQG50H4kos46JT7gBIrS+bFAuaxUK33CnHmSmPlocQO/eaqgFtK2MA2uWO2Fa2ZA6YETpNy5f5GUkdZbRtT/qzLHSKnyetVmdWqtGBji9vQRTOGbWqqPYPYeHpFvbs2eO/vnHjRrz5zW/Gy172MrOU1yzESN1RwO7du/Hzn/8ct956K8bGap1hXYLc+BzkRubBmuoRz97pbprVJXbBmMhY9k530w5VXPUBCK1FqWFNXNfVl0n0Y+qJR3QshaVZ6LyQGqSOPZx1lc+2Z64NTctaaRU6BZmrG9mq+YsWgLZKMAWF2zWBav8g7IUTmJ6eBgD09vbida97HS6//HIcc8wxespnyCRG6o4iJicn8atf/Qo//elP8dxzz/mvk3IRudF5yI/OBXEE5iAKV6wqlXYzxI7F9X9UWDGiIa5CWVUflMGVBBTELvzAoOwzUJoEOpBJzJjcKUlds2TOf00hvm3rLV9N6BhKYteM/nMSQlcncsFsskofV2DmXmbZUVWhk+w/R+0KKn1DWHpWAbt27fJfP+GEE/DmN78ZF110kVn54SjBSN1RCKUUTz/9NG666SbceeedMwMrKGCPDyA3Og/2BEffu6TKVWa0XTOkLrwP/0eJFSNi40qUW/ZBGX74BwZiiMhd3ANDKWsX8/llRe6kpK7ZMlf3d8F9NSE754VrjCe7VFw7hS5W5Px4CqN4w+fDIoCl0JQpMbrV7yvXPwgMjPuzH3R1deFVr3oVXv/612P9+vV6PwND5jFSd5QzMTGBO++8EzfffDOeeuop/3VSzSM3Ohe50bmwKl3xAXgqWZH5sZotdsF9+T9qnjmeV/JkxC5pRQGBrF3qA0Mma5fy2bVb7oSkTveDMDgYIvY9AvtscnYujHC2rk1ClypyfjyBuSL9eAnzMspk6STnnnPz06j2DWLgRIpDhw75r5988sm47LLLcOGFF6Knp0esLIZZg5E6g89zzz2Hm2++Gbfddps/3B0ArKkScmNzkRub09g8K9oUwjObfavELrhP/8eU20FUwtIET6SfHc/yWxxZO96HrXDWjuNza1p1w3H+UqWuGRmNtOxc3Xs53tPC7FwYLrHT3X/OC5ZYz3CLnB+PYzUXPx7H6ikiQscp7g1dI+wqqr1HUO0bgts16b8+MDCASy65BJdddhlWr17NVwbDrMZInaGBcrmMe+65B7fddhseeeQRP63vT40yNhf2+IA3sTEg32k5af3JVotdcN/+j02YVT5O8tIemKKrNCRk7YQ7Xwc/j9hzIvZ5tUPuYqWu3TJXt13M+3XLXC2m3LUQc46bNf9cRP0iLHJ+zIT1lv14nNcyr9AJNquzc0iJC6dnGNW+I0D/hF8P27aNDRs24LLLLsN5551n1mI11GGkzpDI0NAQ7rzzTtx+++3YvHnzzB9cC7nxAa95drpfbu67IOGHQTvFLliGhpdCEwsrxQ8dX9wDU3ZlgYisndJ8V0lyJ/lZtVLuGqQuSzLnbx/arkky54WUnCoj6jptcnNrw1qsMlPnhOVLRuQYaUInOfCFgsLtGUe1bwiFRdMz/Z0BrFu3DhdffDEuvPBCzJs3Tyq+YfZjpM7Aze7du3H77bfj9ttvn5nYGAAc25seZXwOrCnJyY2DEJINqQsTlcXTOZcaDTRzsrg6JqNlDy9NZW2QOw2fUyvkjqissJCGqszVxSJ655tjKMpckPAKIs0QOulsXGTMmnypiFyQqIERKiJXGofTN4zeY10cOXLE/9uyZctw8cUX4zWveY2ZisTAhZE6gzCUUjz55JO4/fbbcdddd2F4eHjmj46N3MQc2ONz5FevYLC+XLofwjpihgWvGXLHpkrQAZM7jeWsG0yhScCbWR2RnIZ56sLolDnA+7x1D4IApJpak2CfUzNi+uiYyNpx6+VYxyTDwSydish1j6HaO4zelW5dHTowMIALL7wQF198MU4++WQzetUghJE6gxLVahW///3v8etf/xp33323XsGLaurTvUyZjpjBiY41TiwcjK0FzVm7yObYDMuddqnjGdHKHasWR3eGjmWodDePaqDhMw6vkyxLUNx0rfAQlDdCZprFBaBw4XaPo9o7jO4VVYyOjvp/GxgYwCte8QpccMEFOOuss5BrxhcQw1GBkTqDNqrVKh5//HFf8ILNCHBs2JP9yE0MeILnclZatUwQpbTxoaQ42XFkTJW44VUsdM1Wr22t10AcDXJHozJ0GuSuWVVSM6QOUMxWBWUuiK0oIgGZq3u5jWIXKXH+HxVkLpx989czVpwMOCoLJyh01HLgdI/C6RlBaZkzs6IPgLlz5+IVr3gFXvnKV+L00083ImfQgpE6Q1NggnfXXXfh7rvvxtDQ0MwfKWBN9XpZvIl+WNVicjDXBQ1JghYZq4md1rhJy5PJCpSOrF3cviXlLlLo6t9Qiyv+sO4YqQPks3VxMhf8u0zcGJmre0sLxY5rYJGo0MVJXBAZoeNpSuW4htxcGU7PCJzeEZC+qZnZAwDMmzcPr3jFK/CqV70Kp512mll71aAdI3WGpuM4DjZv3ox7770X9913H55//vm6v1vTXbCZ4JW7G5tpA9m6OKSzeM2Iy7PurIzgycodz74E5S5V6mbeWIvL/+Ce1VKXJnNBRLJ1HDLnv7VJUif1RYZX6IIil9bXTkToRPrExWTpvPVWJz2R6xkBLU7X/X3lypU477zzcN555+GUU04xImdoKkbqDC1n9+7duO+++3DffffhiSeegBt84Ds52JN9yE3015ppa3MwcYgdQzjb1oy4zV6xQmilB4H3csgdt9DVb1SL274JitsqdSIyF9wmLbaAzNVtpmMEbFJzKleAhGuBJxsXRZrQyQ48Cgkdtates2r3GPqPJXUtEbZt49RTT8V5552Hc88914xaNbQUI3WGtjI8PIwHH3wQ9957Lx5++OG6eZkAwJouwZ7s97J4kyUQKv7Q55IxnuwaT9xwbIm4PjzrzepeASMcP2J7Kamb2bgWt0XrxAZoy+hXGZkLEpetk5S5uhAyEw8HUb22GFEjUkVHvsadZx2jxwkBtQnc0gSc7jE43aOgXVN1b+nu7sY555yD8847Dy996UvR39+vvl+DQQIjdYbMUKlU8NRTT+Ghhx7Cww8/jG3bttW/wbVgT/TBnuiFNdEDUilITZmSKHmcWTuh2AGUbreoh2iS3OkaqBGIpSR0dXGDfa3cwMsdJnVAY7aubqSk4oCHcLZOg8wFibtetfYJrQvsymfh4ghm5zSdFwoKmq/A6R2H2zuBwsJKwxfONWvWYOPGjTj77LNx6qmnmpUdDJnASJ0hsxw+fBiPPPIIHn74YTzyyCP106UAIJU8rMkeT/Ime2BVC1L7aVhnUeMt0czYAKJHEOqeNy8Qm1aqKW+UiT2TvetYqQtm1HRMoVEXPzDRra55C9PQef3oWA0iDtvWdk7cXAVuzzic7gm4PeOg+fpyDwwM+BK3ceNGzJ8/X8t+DQadGKkzdASO42Dr1q14+OGH8dvf/hZPPfUUqqGHBSkXfMmzJ3tAHMVvzuzhozDJaCLBB6fuSYYBPROtBnGcwHQtmmPXMoDhlQp00nSp0y1zwMx5sPTJi49u8QcANyBsLL5Giaub9FhR6NxcBW73BJyecbjdE6CFSt3fbdvGKaecgrPPPhvnnHMO1qxZA0t2nWuDoUUYqTN0JFNTU3jiiSfw2GOP4dFHH8WWLVvqpg4AAFIuwprshj3ZA2uqW7y51nFmskjhJjAdD9iggEUJgco+miB3Detv+vvS0xwbmwXU1dTYzHnALEtffA3zoyWiS+bcCFljsTWtXhL3eCK2JTZfXK051e2egFuahNM9AVos173Htm2sXbsWZ555Js4880yceuqpKJVKSuU3GFqNkTrDrGB8fBybNm3Co48+ikcffRTbt29vfCBUc7Anu2FN9cCa7IY1XUqXvKDYBWmY6kRS9IIPwYZ9aBA9XXJHA1m0yP2oxKagjsMnASoDA5otdarZurRjU83WqUhWksAFUZjUmvdRxCN03jQjU3USh1zoSx8hOPHEE32JO+2009DT0yNcboMhSxipM8xKRkZG8Pjjj+PJJ5/EE088gWeeeaahuRYugTXV7TXZTpVgTXeDOBEPfiZGabeKiuglyV04ZhiefajIXZrQRe5P4P1JWbokRKfxaPaM/TLZOlFJkxE7UcHiFbggMvMcCuL3W4yaK86uwu2a8vrDlSaRn+dgerp+vrhcLoe1a9di/fr1OO2003DGGWegr69PuBwGQ5YxUmc4KpiensaWLVuwadMmX/SCay8ySCXvid5Uyft/uguE1h4icVm7JERFT2b9SxHRE5U7GaGr21/KtiJZuiR4Jt1thdTxZOtUm5N5xY7nnMoIXJiUplYdj5hgdo4S18vClSa9f11TDf3hAKC/vx/r16/H+vXrceqpp2LdunUoFlNWrzEYOhwjdYajEtd1sWvXLl/yNm/ejF27djU+gChAyl2wpkqwp7phTRRApgsgVKGZLU30eLN2iftIWH6K7SNN7lSFLkyU4Mlm6dKIkJ6mSx0Qn63TPcghSeyiBCtK3uLey0tEdk7344QSCtpdgdtT9gWOdFfqJyyvccwxx/gCt379eqxcudIMbDAcdRipMxhqjI2NYcuWLdi8eTOeeeYZbN68GQcPHmx8IwXIdBHWVBcs9v9UF4ir0JE9diJjS03uouKFCcZ33JnpS3SPng3CVgjRkaXjwSKtkzqWrWv29COEzOwn+EWgWXPMMWqZOe0CZztwu6ZBS2W4pWm4pWnYfW5jtwkACxcuxLp163DSSSfhpJNOwoknnmiaUg0GGKkzGBI5dOhQneRt3boVIyMjke8llZwndwHZI5W81ATJM0HJzEPacbyHuMiaoNz7qcV0HW/qkmYKXQ1aLrdG6IDWSV0NYttAvkX7C14jTZifkGVSCWv+VHxkUFDQQhW0NA23y5M3WiqDFqIztn19fVi3bp0vcevWrcOCBQuUymAwzFaM1BkMAlBKceDAAWzfvh3bt2/H1q1bsX37duzduzd6A5d48+dNF2FNF70M33RRXPZ4+trpFD4mdbqbYBmuC1pu7AfVNFoldYEpcEhXk/pvNVHcov9e25/glCqevFVAuypeBq5YgdtVBu0qA1b0MSxduhQnnHAC1qxZg+OPPx5r1qzB4sWLtaxVazAcDRipMxg0MDo6imeffRbbtm3zhe/5559HuVyO3iAse+UCrHIBpJzSX4/JnVtrugwSXtkgiIrwNUPwKpWWZAN9miV1CdUnKeSzM7dcirhFzUHIMnOp04cQF7RY8aSt6Emb21UGLVZi5a1QKGD16tW+uJ1wwgk4/vjj0dvby39MBoOhASN1BkOTcBwHe/fuxY4dO7Bz507/X6LswWvGrZO84M8IDXSIkrsodAmfDsFrtdABeqVOoMpUEjuJUaii4hZFlMxRUsu6FctwawLn/V6JbTYFPHk79thjsWrVqrp/S5cuRa6FzeEGw9GCkTqDocUEZe/555/Hzp078cILL2D37t2R06z4UG/KFfbPE70cyJQNUskBU0Su/16S8AHx0hcUMx7Jc5z6pcBaiazU6ZiOI5fzBjOIyF3MxL5pI4V5xa1hO1CQLsAtVEG7XE/YCtXa/xWQkhs54pTR29uLFStWNAjckiVLYOvKVhoMhlSM1BkMGWJ4eNgXvOD/L7zwAiYnJ5M3dmvSN53zZK+c87J+FbuW/ct5zb6i4pcmfYzgyNqw5LUjOxeEV+qaWB0mZu1c6g0cSUFG2igoYFHQggNacIB81fu5WPX+FRwv25byEZdKJaxYsQLHHHMMVqxYUfdvYGDA9HszGDKAkTqDoQOglOLw4cPYs2cP9u3bh3379mHv3r3Yu3cv9u3bhwMHDjSsfRuJQ+pFr2L78oeqDVK1QSq2uPxFiJ8vca7bshG1SZBCfuaXdlR7rgvk8/W/BxAVNl/W8g6Qcz05y3uCRvMO4P/uAHb68dq2jUWLFmHJkiVYunQpFi9ejCVLlmDZsmVYsWIF5s2bZ8TNYMg4RuoMhllAtVrF4cOH60Rv//79OHjwIA4dOoSDBw9ibGyMP6ALkKrtiV6lJnvs96oNUrUAxwZxrNrPVvqEzBHS2UrRI62aYgSInGg5raqlhAK2C5pzPUmzXdCcA+S9/2neBXI1Ucu5QN5Jza4F6e3txYIFC7BgwQIsWrQIS5cuxZIlS/x/8+fPN/3cDIYOx0idwXCUMDk5iUOHDvmSFxS+w4cP48iRIxgaGsLExITcDlwCVC1P9BzbE72qBbjea3AJiGt52ULXex0VOvM3xwIoAVwCWnXV5veLQLfUUdQGqzAZs2b+p5YLWC6o7WXT6v5uz0gbctT/PW6kaBqlUgkDAwOYP38+Fi5c6IvbggUL6n4vlUpaj99gMGQPI3UGg6GOqakpX/DY/4ODg/7PQ0NDGBsbw+joKEZHRzE2NpbYiV4aF54oUgJS+7/ud7ZLWpM/GvF74GdiEfieSGpSFvRGQv2/gVCAUC97ZtGZ39nPFnuP3kMmhKC3txd9fX3o7e3FnDlzMHfuXMyZM8f/Ofj7nDlzjKwZDAYfI3UGg0EJ13UxPj5eJ3ns55GREUxOTmJychITExOpP3dqdWTbNkqlkv+vq6ur7nf2r7u7u07agv/39fWhp6fHrFdqMBikMVJnMBgyAaUUlUoF5XIZ5XK57ufg75VKBdPT06hWq3Bdb6oNSikcxwGl1H/Ndd261yzLAiGk7n/2L/x6LpdDoVBAPp9HPp9P/Jn9M4MIDAZDuzFSZzAYDAaDwTALMHl+g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhllArt0FMBgYlFJMTU21uxgGg8EgRFdXFwgh7S6GwWCkzpAdpqamcMkll7S7GAaDwSDEbbfdhlKp1O5iGAym+dVgMBgMBoNhNmAydYZMUnh4EQitfecgFohFAGIBFgEIAbHY32qvEwJYBIS9x/8b8bfx/wGB16z6v3sb+q9RQma++gRi+K+TmX0FX6PEC+P/zfLieq8T/29sG1p7zf87MBPDqr2f/R31+6jbplZ8akX8re79qCvjzGuk4W8N2yBYjtDfEfN6TLy4cjRskxTXf502bh/Yxv97IBatvY7Adt7faKA83t9J8G/+e9nfqB+TBN9PqP83/xJjr7Nwtfd4lwL1f2fbWLXfvb95v7Pt/L8RCoKZ7azaa/4/UH87i6DudW97d2Y7sPe7sNk2td9nYrl+PDsQ34b3us3i+e91YbOYYOVwZ96PmdheTBcWvP17f/Pi2bXXCFzYbPvANjbgbQdvP+x8sN+9fdHaz6j9jcKqnRcbBBYAu/ZhWyC11whsQmDBAql9cpWyjbe8bwkMhixhpM6QTRxSq17hSR1qAlZ7Ws78jQDWjMEQz5BqQdjT3ULDU3vGmOpNgsVseMoj9FpwH4h4LbwdZmQuIHUNrwUkLPh7uIj174/Yxkr4W9xhNJQj5rCT/hZ3qmTjBWJGCV9TpS7q7wj/Tv3YwXIE9xn1N18CEXhP8P0N29CIfdG6f0GpmxHF2r+4v4GJnxcyKIBM/gAmZ/ClKPg3T+rcGSkiQSnyfrYI8YSr9j/8n4m/nRcHtZhsW9S2q70e9bfANnZNSG2/nEzqaKrUBePZ7Hyg/jULwTIGPkODISOY5leDwWAwGAyGWYCROoPBYDAYDIZZgJE6g8FgMBgMhlmAkTqDwWAwGAyGWYCROoPBYDAYDIZZwP+/vfuPqbL8/zj+PByFc/gxBZPUCYItdVPUTaFsmS5rOhRs/KFYzTHWD+sfW9Kw1iasP9CWtmZrbi1ktUjcKlGiNbeWuWmp5U/aUPuhTkRLAg9wjijnfP843rf3gfOD/NQXuHk9NnbOfV/X+z4X1yWe9+77uq9bSZ2IiIiIDSipExEREbEBrVMnQ5MzQCAQXHA0uO6aw/Lq6LMgsPFqeY91X8DyfgBllkXL7i4RG2n/3ddAyHtC4gIAAWP/3WMGcEAAM9Zabh4jZHE1a1vCbAdCmtSnPyL89K07kLXoopUN+LMGWGb9yKhxgRjHDERoY+TFh0PXlrOUmXXvffHhu+2wrFPHva9TF+BuXMARCP0h+BosI2S/3xEAh//uMTE+y29ZT+9OnTvlAYffPB4hx7/zanzWne24O3WMV6DfPr/lz9p473eAn7vr1Pnv7HMQaZ06h7lgsJO7Y2Zsx92J6bv23cAXH3Zwd/HhcH+XIoNLSZ0MST151wa7Cf8N4zvzHvXNSUQM1n9a/sFsyD2zZtW6iCRyL/SXIyIiImIDjkAgoGedyJAQCATw+XyD3QyJwefzsXLlSgDq6+txuVyD3CL5N2l8/zmXy4XDoXPnMvh0+VWGDIfDgdvtHuxmyD/gcrk0Zjam8RUZXnT5VURERMQGlNSJiIiI2ICSOhEREREbUFInIiIiYgO6+1VERETEBnSmTkRERMQGlNSJiIiI2ICSOhEREREbUFInIiIiYgNK6kRERERsQEmdiIiIiA0oqRMRERGxASV1IiIiIjagpE5ERETEBkYNdgNEJLavv/6aqqqqmPW2bdvG/Pnzw5ZdvnyZ2tpajh49SltbG263m2nTplFQUMDixYtjHru5uZndu3dz4sQJ2tvbSUlJYebMmRQVFTFv3ryY8T///DOff/45TU1NeDwexo4dy9y5c1m1ahXTp0+PGX/gwAH27t3LuXPn6O7uJi0tjdzcXNasWcPkyZNjxg8mn8/HiRMnaG5u5uzZs5w9e5arV68CUFJSQmlpacxjtLW1UVtby+HDh7l69SoJCQlkZ2ezbNkyli9fjsPhiBqv8RexPz0mTGQYMJK6uLg4xo4dG7FeZWUlc+bM6bf/8OHDbNq0CZ/PB0BSUhJerxe/3w9Afn4+5eXlERODhoYGtm7dSm9vLwDJycl0dXVh/PcRKzGprq6mpqYGAIfDQVJSEp2dnQA4nU42bNjAihUrwsYGAgG2bNlCY2MjAHFxcbjdbrq6ugBwuVxUVlayYMGCiJ8/2I4fP8769evDlg0kqWtubqasrIyOjg4A3G43PT095njk5eVRVVXF6NGjw8Zr/EVGBp2pExlG0tPT2b179z+KaWlpoaKiAp/PR05ODhs3biQjI4Pu7m527dpFTU0NjY2NZGZm8vTTT/eLP3PmjPmFvnDhQtavX096ejodHR18+OGH7N27l5qaGrKysnj88cf7xX/77bfmF3phYSHPP/88Y8aM4dq1a7z33nscPHiQrVu3kpWVxaxZs/rFf/bZZ+YXeklJCcXFxSQmJnLx4kU2b97MmTNnqKioYOfOnUyaNOkf9c3/p5SUFKZNm2b+bN++nba2tphxnZ2dlJeX09HRQWZmJm+++SYzZszg1q1b7Nu3j/fff58jR46wfft2Xn311X7xGn+RkUNz6kRsrrq6Gq/XS1paGps3byYjIwOAxMRESktLKSgoAOCTTz7B4/H0i9+xYwe9vb1MnTqVyspK0tPTARgzZgxlZWXk5eWF1LPq7e1lx44dADz00EOUlZUxZswYIJigVlRUkJ2dHVLPyuPx8PHHHwPBhKC0tJTExEQAMjMz2bJlC2lpaXi9Xqqrq//nvvqvzJ49m6+++op3332Xl156iSVLlhAfHz+g2F27dtHW1kZCQgJvv/02M2bMAGD06NEUFRWZZ8j27dvHpUuX+sVr/EVGDiV1Ijbm9Xo5cOAAAE899RQpKSn96jz77LMAdHV1cfDgwZCylpYWTp06BUBxcTGjRvU/uW/Et7a2cvLkyZCyEydO0NraCsAzzzzTL3b06NEUFxcDcOrUKVpaWkLKv//+e7q7u0M+xyolJYWVK1cCwTlXXq+3X52hwOl03nPsN998A8CSJUvCnokqKirC7XbT29vL/v37Q8o0/iIji5I6ERs7ffo0N2/eBIJnSsKZOHEiU6ZMAeDo0aMhZdbtSPE5OTnm2ZO+8ceOHQOCZ4VycnLCxj/88MNhP88an5WVxYQJE8LGG+26efMmp0+fDltnuLp48aJ5Q0Wk/k9MTGT27NlA//7T+IuMLErqRIaR9vZ2nnvuOZYuXcoTTzzB6tWreeuttzh+/HjY+r/99pv5furUqRGPa5T9/vvvIfuN7dTUVFJTU8PGOp1OMjMzo8ZPmTIl4tmq1NRU8+aPP/74I2z7s7OzY7Y93OcPd9bxG0gfROo/a51o8Rp/keFNSZ3IMOLz+Th79iyjRo0iEAhw5coV9u/fz/r169m8eTO3b98Oqf/XX38BwctUCQkJEY973333AXD9+vWw8UZ5JOPHj/9X4o36BuN4Rnk4LpeL5OTksPHDnbU/o/WB0b9dXV3m5UrQ+IuMNLr7VWQYGDduHCUlJSxatIiMjAzi4+Pp7e3ll19+YefOnRw7dozGxkZcLhevvPKKGWfMMXK5XFGPb5RbEwLrdqx4I2H4r+KjJSTG8Ts7O/vFD3fW3ydaH1j7t7u727wcqvEXGVl0pk5kGMjLy6O0tJQHHnjAvGvS6XSSk5PDO++8w6OPPgrAnj17wt4BKSIi9qekTmSYi4uL4+WXXwbA7/dz6NAhs8ztdgOYi85GYpQbZ3gMxnaseGMy/n8Vb5RHEqn9w53194nWB9b+tcZo/EVGFiV1IjYwefJkc/0v67IQxlwmj8cT9YvRmIs0bty4kP1GfKy5Sn/++ee/Et937pVxPKM8HJ/PZz6dINbcreHG2p/R+sDo36SkpJDERuMvMrIoqROxMeudgdY7IfuKdJehsf3333/T3t4eNra3t5eLFy9Gjb9w4UK/hWkN1mNnZWWFbX+0uxoHeofocDTQOzuNPojUf9Y60eI1/iLDm5I6ERu4fPmy+VzQiRMnmvtzcnLMSeZHjhwJG9va2sqFCxcAyM3NDSmzbv/4449h40+fPm1OUO8bP3/+fCA44f3MmTNh463HjRR/4cIFc722vozfKyEhIeJaaMNVRkYG999/PxC5/71er7lAcN/+0/iLjCxK6kSGOOOh6dHKP/jgAyA4v+6RRx4xy9xuN4sWLQKCN1EYl6msamtrgeB8pIULF4aUTZo0yVzYtq6urt+SKQCffvopABMmTGDOnDkhZXPnzjUXjTXqWd2+fZu6ujog+Citvk9MeOyxx0hMTCQQCISN93g81NfXA7Bo0SJzDpldOBwOli5dCgSfoXrlypV+db788ku8Xi9Op5Mnn3wypEzjLzKyKKkTGeJaW1t54YUXqK+vp6WlxUzy/H4/TU1NvPbaa+bjnQoLC82FYA2lpaW43W6uX7/Oxo0bzbtjvV4vNTU15pfi2rVrwz5G6sUXX8TpdHL+/HkqKirM+U03btxg27Zt5pmWdevW9Vtg1ul0sm7dOgB++OEHtm3bxo0bN4DgPKmKigp+/fXXkHpWKSkprF27FoD6+npqamrMZTouXbrE66+/zvXr13G73eYzUIcqj8dDe3u7+eP3+4HgTQDW/X2X5SguLiYtLQ2fz0d5eTnNzc0A3Lp1iz179vDRRx8BUFBQYD7X1UrjLzJyOAKxTgOIyKC6cuUKq1evNrfj4+Nxu914vV56enrM/fn5+ZSVlYV9Pufhw4fZtGmTeZdgcnIyXq/XnOeUn59PeXk5DocjbBsaGhrYunWrWT85OZmuri4zwSwpKYn6pVpdXU1NTQ0QPPuUlJRknjVyOp1s2LCBFStWhI0NBAJs2bKFxsZGs77b7TbjXS4XlZWVLFiwIOLnDwWrVq0yn4MazbJly3jjjTdC9jU3N1NWVmZeYk9MTKSnp8c8c5abm0tVVZW53E1fGn+RkUFJncgQd/PmTRoaGmhqauL8+fO0t7fj8XiIj49n/PjxzJo1i+XLl8ecT3T58mVqa2s5evQobW1tuN1uHnzwQQoLC1m8eHHMdjQ3N1NXV8fJkydpb28nJSWFmTNnUlRUxLx582LG//TTT3zxxRc0NTXh8XgYO3Ysc+bMYfXq1UyfPj1m/HfffcfevXs5d+4cXq+XtLQ0cnNzWbNmDZMnT44ZP9j+l6QOoK2tjdraWg4dOsS1a9eIj49n6tSpLFu2jPz8fOLiol940fiL2J+SOhEREREb0Jw6ERERERtQUiciIiJiA0rqRERERGxASZ2IiIiIDSipExEREbEBJXUiIiIiNqCkTkRERMQGlNSJiIiI2ICSOhEREREbUFInIiIiYgNK6kRERERsQEmdiIiIiA0oqRMRERGxASV1IiIiIjagpE5ERETEBpTUiYiIiNiAkjoRERERG1BSJyIiImID/wdRBzfxdvdYzAAAAABJRU5ErkJggg==", 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xxhk4+eST0dbWxrzagqmHkDqBLXK5HJ577jk89NBDeO6551Aw3ESkbKsmcunp9iJygOuonC2Zs1sH72mAqt286ghcxcebTeisZM6MG7mrI3Nl1Qixq47CSd59ota24y56Ngam1JU8i+2rynkobSM45NSusq4rsVgMxx13HM444wy8613vEsmOBXURUieoCqUUGzduxEMPPYRHH30UY2NjpfekXIvWtJruCpfI2a3Xq/kcjULnUOKMTEmhM2JX7hyIXEUVzSR2PKWOqqDFFDXEo/Q51Cg2ksSlHjvbj5vk2Rx1XFXwaoizGsmh0D6Mee9MYMeOHaXXW1tbcfLJJ+Pd7343jjrqKM/2jaCxEVInqGDv3r148MEH8dBDD5WN3CKFKCLpbkQmuiEVquRdMouERNgFqjhXKxeIi/Wwi0RAOSQcDYXQBSVzZqrJnQuZKyuel9gFLXUAV7GjNcpxKxO0ViSQg+A52Y6uJM9hOpkKwasTEdWmLctAaR9G5yHaQDSdefPm4d3vfjfe/e53iwEWgjKE1AkAANlsFk8++STuvfdevPLKK5NvqBIi6emIpHrK04/UkoawiJzVOvD8dSsR0GhRCjilCxNCVwVd7jjJXFnRzSJ2PkmdEacCVlPozPgseEDx+0gEiDqYV5YxV2BJ8mxsEy1NygQK7cOIzckglUppZRCCNWvW4JxzzsEJJ5yAmNP5cAVNh5C6Kc727dtxzz334KGHHsLo6CgA7UIhpdsRSXVDTk8HUSV7khAGmatXv1upM4qcEQ5SJ4SuNqVLFY+0LCaYxI5S0EyG+7pYfj/JZkSJk9jZlTojdgTMkdTpBCV3gH3Bc5kEmjhI2UKJikLbCA47uxuvvvpq6fVp06bhzDPPxDnnnINly5a5Wh9B4yKkbgqSTqfx+OOP45577inrlEsKMUQmehAZ64ak2PzF1wgiZ6rTWdlVJM5IWKJ0utBRypwdn7gVJg9kDrC4Kfstdl4JnBVOv5tR+HhF6wz96liwkjAmoTPjQvCYxa6s/jqS50buiHYdIw76DquRLArThtC5nJY1z65YsQIXXnghTjvtNCQSCfZ1EjQcQuqmENu3b8ef//xnPPzww5iYmAAAbdLpsXZExnq0abrqJQXWYZW5IETOVH/tcm1InBE/hY4Q0EiV761QEBcyRVRqb9RjrT6DXkbnqtbJ9/JFIrK/AlcNl9+rlB7DRdJelmidFboccZE6I4yCx0XuSutQRfJY5Y6YclTaFDwKCqVlHGsvWYynnnoK+eKcwG1tbTjnnHNwwQUXYMGCBWzrJGgohNQ1OYqi4JlnnsEdd9xR1leO5GOIjM9AZLwbkupgWpwgZY7XQAfzRdqpyBnxotm1lrxZ4ZfQVUOWuQudo8sSl1ky1Ml9EIaUHpykzoyjZj5eo2l1FIVvn1adMMgdUCl4HKJ2ZS/ZFTypgPy0QfSsJOjt7S29vnr1alx44YU4/vjjEQlihg6BLwipa1JGRkZw33334c4770RfXx8Abd5BMjYN0fEZkDI25lw1EpTM8R6xaugrwyxyOi6FjkZlKG0xREZdRIWCFjpgsskX0P53WR7TJYlFgowiZ6aJxc5MNdHzROrKKg6H4HGXu9K6FCWPU9Su7C0bgqdF78bwzg/OxXPPPVf6njNmzMB73/tevPe978X06dPZ1k0QWoTUNRnbtm3DHXfcgYcffhi5XHGuS0VGdHwGImMz7PeVA5pH5HRkyb3IGXFwraZxGfmO8r4tUl5tbKFTae0mY4eCxyWlR91KaoicmQYXO9btWZI8l/3qKqi1PUMgeI5ToThaF8I2f20NsSt9xIbgqZEcCh2DaF2cw/DwMAAtsfFZZ52Fiy66CIsXL3a+boJQIqSuCaCU4vnnn8fvfve7stFQUjaJyNhMRFJdINSBKAUhc16InJ6ewPDcUbNmLerc66wkzkjTC50RG3LH9TJkJUJOZM5I0GLnU7TOc5xsR7eCV+c712uC9lzuAGeCZ0PsSh+tI3iUUChtI1hySis2bdpUev3YY4/Fhz70IaxevVokNW5whNQ1MPl8Ho888ghuu+02bN++HUBx4MNoO6JjsyBlW0PRxFptRCV1M3K2xrqYRa6sTh5SZyF09STOjCupayShM1JF7jy5BKmUXeTMNLDYud62xQ73ALRzlTW5Nus2dCIYbiOTZUX5IHY6dgTPgdiVFrESPH3QCijUeArHXDwXTz31VOn7Ll68GB/+8IdxxhlniJx3DYqQugZkYmIC99xzD/74xz9ODmNXJUTGejSZc9LECtiXOWOHfhczNFgKoBu5qyNyZXVzkjqnEmdkSgqdGUr599ky0yxzoQYdrTOKnY5TwXO7DeuJE+fbmC56nsldrRaNapLHIHalRY2CZ1pPNZJFvuMAonMmkE5rib27urrw/ve/H+973/vQ3t7OXK/Af4TUNRAHDhzA7bffjrvvvhvj4+MAAFKIIDI6E9HxGSDUYZ8Ns8zZTKvBVebK1sdhvjmbIleq34XQ0XgUmZkJQAXkLHs/oyCbXUMjdIC2vygFtRIGngix80bqzNiRPF7b0Hyu+3ELcyCwoZe7KutHJQX5aQPoXFEoBQtaW1vxvve9DxdddJEYVNEgCKlrAPbt24ff/va3uO+++0r5h0gujujoLEQmukHg8CRn6ffGKHOO+9jVqoNB5MrWxYHUqYkosjMsInEupE4Inb4ylTdlT+VOiJ07sXO6b6oJHu/tV/xh4DmWSYhrX0u4iZ2OWfBciF2piCrJtikolLZhzD1OLnXricViOP/88/GRj3xEzDUbcoTUhZje3l7ccssteOCBB1Ao3pikdAuio7MhZzqd9ZfTcSpZfsmcEcnUVOBC5MrWqY7UVRW50gcCjNI1g9DZaELzTO7CIHYqdZ6AV5Imm87CHq2zwih4XkixPnOKVyPm7VxvatTNXe6AScHjIHZAHblrGcXiUxN48803AWh9ts8++2xccsklmD9/Ppf6BXwRUhdC9uzZg9/85jd48MEHoRQvhFK6DbHBWZDzHWxi0wgypyPL3EROx0ro6kpc2YeF0LnC7j5sZrFjkToHdZM6Hdt9jdZVg6d8VZsKj2cdTNda06wQXoidjp15aauh588zyKGV4FFQqMlxHHpuRymBvS53f//3f4+5c+eyr4OAO0LqQkRvby9uvvlmPPTQQ5Myl2pDbGiKyJxet0S4563Spc6RyBkJqtlVF7pYFPnuVkeLkoKKyOBE5RuqCpKzcZP2W+iMeCV3PMTO72idy7p12QuF1BlxK1/15jd2Wz6Pa5BhHRwlLXaCLmUsefDMiZH1+WerRO+U+ASO+kA31q1bB0CTu3POOQd///d/L5plQ4KQuhAwMDCAW265BXfddVepmVWeaEd0aBbkwrTJviNe/uILSuaq1etgUut6qC0xZGYlXRTgbZQuM7sVe0+snKotNkwwe13aUJD9OkleRWTAQujqoQtfkEKnE1ax09OluFjeb7EDyqWuXlTPEq8iqCzyVU/oeNTBO1+b09kunFxbjU2xTuXO6liuE71T4hM44sJOvPTSSwCAaDSK8847D5dccglmzJjhrH4BV4TUBcjY2Bh+97vf4fbbb0emOIG4lGpDbHA25GyrdiEiDqNWPsicZyJnxKXUqfEo8l0JUJlAjbpcX05RusycNuw9odqItsqXYsMEs19IV75hA5KrEqWzA6WTkTxKAdZZBXjdFL2QuyDFLiCpA2pH6+qKntcjlQH71yKnUue0fI8T8BK7o2lZxU7HruDVOpZrRO+UxDgOPW9aqVk2FovhAx/4AC655BKRCiUghNQFQCaTwe23345bb721lJpEyrRoMpdun5Q5wDuh81vmnNbHIHW6yOlQAlCZgEZcrDej0I0siWHi7HGom9vK37C5KrERU5TOAcxROqBc6Kq8b0vyOAqdHjHkntfOTXlNEK2rR4Xk+SF1RmpdL1ilzm75Ps+qUFPyWJtjzdQSPDvHch25O+Q9rVi/fj0AoL29HZdccgne//73Ix6P1y9bwA0hdT6iqioefPBB/PKXvyzlASLZhCZzqWkgkixkTsem1FmJXOlvt0IH2JK6kSUxJD64r+w1iVAMjLeg8OY0x1XGhglmvZgBYTg1PRU6i89XCJ4HMlf2Mk+xE9E625QEz2+xA6yvHzykrlb5AU2VxU3uao2MrSZ3do/lKk2z2mjZMcw9HqVUKDNnzsQ//dM/4ayzztJmOxJ4jpA6n3j55Zfxk5/8BFu3bgUAkHxMk7nxYmoSr5ta/ZQ5FwmKS9SQuloiZ8SrKN3I0hgSH5iUOIlQSKT8NDow3orcm9NAHJ5droSOV5Mrw7JQVM+FrvS2EDsNH6J1FagUkEhw84Pq1xWeUmcuPyRzn1oKHi+x0zELntNj2SJ6R0FRaB9Cx+GZUvBiyZIl+Nd//Vccc8wxzsoXOEZIncfs3LkT//3f/41nn31We0GVEB2ahehIDwiV2JpawyhzPETOiEnq7IqcEVdSZxC64YNjSL6/tsQZYRU6gL0fXWBCp6Pve0qBggtRsTOrCdyJnVFIKKWN2wzrc7QOQGWuvAAET193z+sNUWSpTPB4ix1QLncsx7OV3BEV+Y4DiB80VupmdPzxx+NTn/oUFixY4LwOgS2E1HnE2NgYbrrpJtx5551QFAWyLIMMdiI2OBtEjXjfb84PmeMtckZkiUnkSp91IXTDS6KY/t49yCvaBaqexJnpH2v1tdk1NEJnKteR3NmUubJFHMpYNQkIVOwaNVpnhU+CZ153nnWWjRA2lxsSySPmPJ51F3BwjY5E3P1IsZI7qYBzv3QY/vSnP0FRFEQiEVx00UX4+7//e7S2OkvTJKiPkDrO6P3mfvazn2FoaAgAIE9MQ2xgDqR8UVDC1tTqtCmDEFDZ4YTeNqHJGHLdk+lHnIhcWTkOpW54SRTdF7xdeq6obLI6pZpdgfrHmR25YxC60qI2ZMzOTb9hxS5MUmfGI8mrOYLXzYwzdbZJGCWPRG2ObmWZfcJNBgILuVOjGRx5UWcpx9306dPxz//8z3jPe94j+ttxREgdRzZv3owf/vCHeP311wEAJBdH/MA8bUQr4F9Tq6rWv5ES4vykNYgolQjfi5pEQGUZNBFBrtPdaCk7Qje8NIru975d9lqEaDdlFaQUpXPClGt2tfvDoZbYuRC6UhFVZMzJDX6qSR3AsQnWDhwFz856O62LafBIiCTPltyxTivGWe4KLaOYeUwBu3fvBgCsWLECV1xxBZYvX85ej6CEkDoOjI6O4he/+AXuvvtu7eKgSogNzkJkpAdEzxjLOzrnJjmsU6Grst6uxa4ocmVleih1QwdH0XP+pMjpEmeEVeiAKdbsytLsbpY7DkJXKsogZKzyMNXEzpdonRkOcud0vevVx+sWWFZPWAXPzXyxLHJnqk+XOwoVhY4BRA8awcTEBCRJwoUXXojLLrsMbW1tViUJbCKkzgWUUjzyyCP48Y9/jOHhYQCAPNaJ2MBcSEpxhgC30Tlemf31+jnInA6T1FmIXFmZnKXOjsgZYZW6/rFW5Dc3SLOrV/3oHNSPfIHfca0XWyjwEQZWsasldXUkKKgpvHyN1pUqndxGhGFqK9Z1rtmnkiOW9QQgeVXlzo3Y6di9j1SpS5c7Vc5j7WVz8cgjjwAAurq68JnPfAannXZacCOsGxwhdYz09vbiBz/4Qal/AMnFEe+fDzlj+JXBEp3zYndwljkjtsSujsiVledS6qhMMLgi5kjkdIKK0vna7Bq00BXXwVYXASfoU+m5GXQATtG6ICJnjGIXtNQZsSt4PG5ZFSOgOVJXRsIgeDzEDrB3X6lRly53SnIMPcfk8Pbb2nV79erV+OIXv4j58+dzWc2phJA6hxQKBdx+++246aabtKm9KEF0cBaiwzMqm1qB6nKkqpMXf8K5f5qOhzKnU1PqHMgcoAldviPONDhiZEkM2XePIior6GpN2RY5I35G6fLzcrjq2AfwnxtPd+zxuf4WHHSP/e8nZxXE9o5qT4JodjVibHJ1m/5Ex3jMNrDY+S11gTS/AraaqGsJXphvWY6jSz4LXpnc8RI7oPZ9xkY9JCJrKVA694PMHkIul0M8Hsdll12GD37wg2IghQOE1Dlg27ZtuP7667F582YAgJRuRbx//uSoVqB6dM4ocToNLHM6FVLnUOTKynIYpdNFTicZy6MrmWKq2wuhy8/P4o8n/cxyuVczC/Gfm5wLXWp/Kw66h4LBWTW56xubfEGlINmc/QJ4Cp35dRa5q3bMBi12DRSt0/oAF+t0mtLIY7EDrOWO6y3L+B3czmkNl+lVfBSXktzxFDvA+r7joA4SkaFGsjjs/a3461//CgA47LDDcNVVV2HRokWcVrK5cd6hYQpSKBTw29/+FjfffDMURQEUGbGBOYiMdWmzQegYhc5K4oyEQehcyFwZLkTOKSNLY8ierYtcBpLkUWZ5BxAK5Bdk8ccTywVOBkW0in3JRGUf58LwlaWciti+cdOLBDRpkOhakue2D12tL0sIEJGdiV2t41Y/t1yKHTMSARBg/axYSRoH0XFD2QAYhv53NTF/X1a55YXxePH4ekrzhu1qnuPXDfq0gcZ7EFVtix0tKCCFCDb9IY9Y+3xEFw/hjTfewD/90z/h0ksvxUc/+lFEeB8HTYaI1NVhx44d+O53v4s333wTACCPT0PswPzJgRDA5A3PzkW8iWSOSqSURoXazZdUq7wqkbqRpTFkztJETqvO2mriEYUpUuc0SrewfRD/OusxSERFDCpykCCDIkHs3cT/mlmA7206C6rqbB+k+otROoeuIOVUxPvGnPXXNAqeVxE6q8/ZScXjpF43ETNFYe/j2khNsA7yzpXhQ6SuKjyuofXW36HceZYE2SeJ4Sp3Ovo9iTEiSOMKVn20E8899xwAYNmyZfjqV7+KpUuX8lrDpkNIXRUURcEf//hH/PKXv0QulwMUWcs5V5yrleqROCKBOJEp3kLns8yVRM4IB6kz96ezK3I6rEIH1Jc6XeKMRItmZVfkjLyYOQjfe/1MR8uk9rfioHudCx1QlLre0fofNKNSkLzLuVGdpi2pJXYsx67DJlRqJYJC7PjjVup03FxPnXxnG4LndR6+hpY7N+sekaC0DSO+bBijo6OIRqP4xCc+gYsuugiSVzMaNTBC6izo7e3Fd77zHaxfvx4AIE+0I7pvHqSc4QBqJJnTP++m31ytZTlJXa4zXpI5OyJnhGeUrpbEGWEROuYo3b5WLLrb+anKFKXTcSt1rHnorMSO9YZpI1pnKXLmMliYClJnlDMn0RheUmfE6TWWMYlyNXxNruyD4HGXO6oCURdlxlWsurizNI/60Ucfja9+9auYOXMmpxVsDoTUmfjf//1f3HDDDdoExKqE2L5ZkEc6y/vONZLQeSlzOi6lrtCZQN/xLVCPHXEsc4D7KN2clhFbEmfGqdQxCx1jlK4hhc64vC52bm+WVaStrsyZy2ChAcSOm9QZsSN4XogdYP966zY6aRI8HlLHNLNFowieokxuM0a5o6BQpo9AWngAmUwGbW1tuOKKK3D66ae7X78mQfQ4LJJOp/GjH/0I999/PwBASiUR650HKW86+OwKXYPKnG2Rc0mhM4HxhZOjhqkEyLJ/gx7mto7gwz0voFPSZNCOxBlhidKpkBwLHQCAgqnZVVu2AYUOmBw8oXA4JkwDJxzJ3BSAEAIqgU1yiGQtZ6wRPB7YGXDAo7k56IEVRfTBJF7KHc1p/WtdyZ1x8FK+2F/XodwREESGOkEzbTj0bIJNmzbhmmuuwXPPPYcvfvGLaGlpYV+/JkFE6gBs2bIF3/rWt7Br1y4QQiD3dyN6YEZ4onNhlzkHkTqjzOn958bnS8CxI8wjWe1E6ua3DuOC7pdLz2WiIkHy6JScJ/4FmjhKFwahA/gmJi6VWXAndI0SrQuyCbYexDQq0i/M12OP+hDavkdYwG26sjBH7szngYvIHQXFh69dg1//+tdQVRULFizAt771rSk/iGJKSx2lFH/605/w05/+FPl8HiQfQax3HuRUa/kHmzQ6xy0qV0fqKqJypirHF0iQjhtiqrqW0BlFTiYqZEwe6lFSQLuUKXvNLmEfHBFYs2uYhQ7QpM5NUmGAeZtOySbYMKJfn30aGOJE8njeiktNwR6nRmGSO6tzgUXuqAoUClDac5i2egL9/f2IxWL43Oc+h/POO2/KTjM2ZZtf0+k0vve975XmnJPH2hHrnQOiVk6nEojQOZU5QMuNZwdJAo14e7LXEzmvqCVyZliEjoW/Zhbghk1nOF+wEZtd3eJRhE6HRCLuxc4pDZC3zlUTLCPUUBfxqwnTuA98aBamhu4DbqJ4zOjf1yO549IsC0wed/mcM7FTKeSRKMYfb8dx/7QUzz//PL73ve/hlVdewZVXXjklm2OnpNTt2rUL3/jGN7B9+3aAAtH9sxAZMiUSBsIhdJTW71dESOD9OnSsmle9Qo/SORE5YDJKx4JffelS+1tx0H0uRrs6xa3Q2f1BUQ07xzkLvAVOn2PWJY6iMm63rddU61dXdzFSErtABE9fZ5/6/FHT8W28t3gSpTMSJrmrlRhcpUz97Ygi47WfH0B09kyocwbwyCOPYPPmzfjOd74z5WaimHLNr48//jiuu+46pFIprbl173zIaZPN+y1z+gTnOsa5Y+vtHqepTQx1cInWSRLyM9qYo3Ks/ekWdg7jk/Mfg0IlWyJnJEoK4e9Lx5DCJNDRrm7Fg3eEro7MuYrWOUziXDZAgwXWbWtVX42ygmiCpTXq803uyiv1v06A249yR02OHjbN1pU7O1HrWk2yVAWqzGGttKQx7V1Z9Pf3I5lM4utf/zpOPPHE+vU1CVNG6hRFwc9//nP87ne/AwBIqRbE98wHUXxsbjXLWzWcJFQMUuoMQscalXPSn27R9CFcPu9xAFrTqQQVKpx/d1apc9OXbnH3IG5eerutZZ5Iz8GVz1wE2BTByEAU8x8tVM7tapcpJnQ6nohdnf5zvoqd3boMZTOLnQdSZ8R3wfNb7ozbz4VsMfUjC0ru7HZHkEil2NWQOgCgcgErLunEK6+8AgC49NJLcemll06JZMVTQupSqRS+9a1vlZIWRga6Ee2fydbcalfm7AqcFWGWOknSUk0UyXe1YGxh5dRedrEjdbrMaXOpajdihUrMQufVAIkdhen404HVpedLW/rxqa5XkacqZBDEib3eDo+kO/H5Zz5qe70oBSL7YjjoL1kQ4/RCeRWRoTr5+6ao0AGcpM7hIIhQSp2pHmr8brbr8lbqdJpS7mptOwfC5XpggEdyV1XsnPQxNUft6kgdoI2OPeeao3DHHXcAANauXYuvf/3raG1trblco9P0Utfb24urrrqq2H+OILZ3LiJjHeUfchudUxRQ881JIiAsvwqcLuOH1JlEjhouHoXpSU+kzhyV02VOx43UuY3SmeXNiGr4obC0pR9f7FrvqJ7HMtPw2ec+Cqo4+25SfwyL7suWvUZMp7al5LmRujAJHaOgMYudorqbV9YpPJtg69RTdf3qCRiD2DmVOiNNI3h2tpsN4eI22tNPuXN6Dun7PBKpK3U6hemjwNIh5HI5LFy4ENdffz3mzZvnrN4Goqmlbv369fj617+O4eFhoBBB/O0FkDPJ8g+xCJ2VxJkJu9QV66opdgaZo1UuGG6kztyfbsn0QfzzvCcAWIucERapY43S7cj34P7BI8teU81RXhOLkgP4fPdfEYX9C6QboTvogRxInRtkRRRvYCK4KB3PgREuIm6OpY4xQldeRIijdbWkruKzps/5LHU6DS93TrebhXR5kr7DD7ljHREuEUeRZCWZwbTjM+jv70dHRweuvfZaHHHEEWx1h5ymHf360EMP4brrrkOhUADJJBB/ewGkQrT8Q3abWwFN4rzKn8WKG6GrRo2oHHeKU4JZNa/WgjVKB9RPY3L36Dtwy2OTnWppZx6nrthcV+Iq6iGqI6EDtO/lWOgORHHQX+oLHVC+LwkAUApaPH6IU8EKi9C5/E1qK8WJVR0NkKaECUkCsSt2RplilDPjCFhWfB85G+RsGYC9GTNcQikt/Vjincy4bKRsrZGwtcrITLZK2BlxK6cTGH8iguXv68LmzZvx+c9/Hl/72tdw6qmnOq477DSd1FFKceutt+LGG28EAMij7Yj1zgOhppOvhtBRRZ389S8RQPI2p1sosBGV48nwIRI+eMFTeFfbVtsy5xVlIqcCRJn8/qpCHAvdouQAPtP1CuAwSveF5z/sqB4AACUgCuuIxcnlqOFcqCt4PFJs8EgNoi/PeGOwXT5nCCFcU1jUqcyz7xFGdMFrmLQobhM368c9R/EyH5teTUNWJncuzl+ay9kSO1KIYNftBaz9l7V45pln8M1vfhN79+7FxRdf3FSJiptK6hRFwX/913+VOkbaHRBRJnGA6URrXqGjsgTEJqOXXsvc8CES1p6t9TGLSApapBwSxPmURiwYc9P9eeSd+N3jayffpAAp8PvufkfpnCLlFEQOjFd9nzl6ZwfjDcONcPDM62WO1oVVgiQpvDnrJAKEKGg5laJ3VKUVCbY9qcdDuSMuI4528+QRKuHl/96HD37rg7j99ttx4403ore3F1/4whcgezz7hl80jdRls1l85zvfweOPPw4AiO6bhehQd/mHDDJXJnK1fi3pvyCaNFrnRuQKnQmML6jfn06XuYikIC5p23x2bBSrW95yXCdr0+tdQ0fjvqffqT2xKXHK9DzeteJvjuphidIxwylKV/UjVnLnttlVR+8TwyJ2Vp/nEa1zuh4ummB9jdb5BWMSYq9puOgdU5WGY8mFfNk5JrnInemcocXndmemILFYSeTKyrERtSMguP//vIZo9wwoCwZw9913Y2xsDF/72tcQczszRghoCqmbmJjAV77yFbz66qs1R7gCAM0WD4QQXnwaDkKq5qczR+V0mTMiE2/3wV9GVuLuZ95ZlJ/yZlVbECAuO2sWZonSsTS9Sv0xT6J0VlBZAigFcdOntFq/NKdiV+tzbsSOSAANUaiJJ07F2Um/urLlwhWtMzMV5E6rtrjfPIqslepxWr6Nc5PHtGN2y4gOdILkZdBlA3jssccwPj6Ob3/720gmkzWXCzsNL3VjY2O48sorsWnTJkCREN+zAHKqmIdGUScPvBBNpVUVP/LTeczwcoK1Z22oKnJecv/wkbj32aMnX9BljsJ2Il8dP6N0LE2vhMJxlK4kdCwRIkK86Z/lROw8iGyZp25yjN8DJsLcBMsIj8ESTghN0yyHwEKt7WaWO6C2gLFGjm3JncPzw24/ObdlREbboWyWkTx8EC+++CK++MUv4vrrr8e0adNc1R0kDS11w8PDuOKKK7B161ZAkZHYtRBSKg5acB7BELAztILghDM3AKgeleOBVdNrmcgVJY4LIY/SLXyQ8RhnvHATRS0XOyfl1PusHbGzW5/NaJ2lzEkyoPoXamrKJlhGdLnyU+6M9fkevfMRO02zPI7DqnLHmvqHU9Su3vLyeAuU9RLajx7G66+/js985jP4wQ9+gO7u7prLhZWGlbqBgQF84QtfwI4dO0AKMmJ/mwuSkUFhfSOmlIKoCH+0roEYODyBoy7diAhRkZTtSwZrfzoj9w8fiXufOxpQa4scS5TOT3yP0jFQMWDC7rzEdj8D1BY7zuLjOjonqI7LfnVTRu4Cwo+mWVooTJbLIYLtVu5siV06gfxL09F9fAzbt2/H5z//efzwhz9sSLFrSKnbv38/vvCFL2D37t1ATkbsrXmQso3fwbERKHQmMDE/AQBIzQXaIxmmclj6090/chTufrY42KGOzLmBten1U9NfhpNTqlGidJbYidqx9MmqSGjLsM41onV1hY4lWtcIOesarF+dUa6aumnWBW62S0XTLOeRn7RQABSFqzSa5azaYIlqy+rLVEPKxjHxjISZJ8nYuXMnPv/5z+NHP/oRurq63K24zzSc1A0ODpaEjuQiiP1tHqRctP6CjYSdEak+59UpdCYwMS8BEJQGR5hT/3nBy+lFuGPXOzAykUR2b6tnIlcGY9Or3blddRoySlfxAQdRO9uVMjTxmjGJXVijc0xNsCz96mrNRR3ySc5F9M47qEq176efK5zkjhZnqqHFqbykGJ97tNdROykXxeiTScw4cQZ27tyJz33ucw0ndg01TdjIyAg++9nPYvv27ZrQbZsHKW//YGEeLCHLzlKasEwRJknORI3DwA8ajYAmqqckKYkcUCZzADC0QsKJ737NUbOrzuzYKI5t3Vb1fV3kAEClBIpKMDaehNLrbFQS8wCJQ//mSOoWJQfw2a6XkKEq3sh31F8AwIDShmfHliGtOLvYPb93Eab/vA2RlH27lXIKIv1jjurRsZ2rzixhbi4rag0BcULxRsUkdCx96xinDvNlLthaUmdFURyZ1s2HiKXfggeET+54bQPL7+VC7miNqQd5yR3gLFJntWwtChhHx+kF9Pf3Y9GiRfjhD3/YMGLXMJG68fFxXHnlldi+fTuQl7UInQOhY8ap0DUBVlE5M1SmzEJXrT+dLnO6yAWCjSjdpsFZGHl+Zun54wtzOOHUzQC06JsdVCpBpcTRoJLn+haj/ZZpoDJFvr381CUKtRQ9T6N0ZR82ROzCIHTFdao7R7PAmpCPsA0ieleqi6quk+VyWxeXVBVVxshdLaEDADWX5x61Y122mtip2SwkRDHyv8CM02dgx44duPLKK/GjH/0I7e3tzHX6RUNIXSqVwpe+9CVs3rwZyEuIh7zJ1fGUI06jdEDxlze4DfyoFZXjjbE/nVVULky8PjAbY+tmlL1GKCAZXaEg2ZY5NygqgZy1vphTmZSJXpnk+TklFaDN68pyXPIUOgDUTVlO+9a5iE75MgqWkKZMhxIUpWS5TTILQVU4N8sCmtgB7FE7NZuteE2K10+Cb8ZK7IxlS1lN7LpO6cK2bdvwla98BTfccAPiDHX5SeibXwuFAq666iq88MILQEFC7M2ZkHNJpoOMqfmVIVJHZIeSxiJ1gOsmWBqNID+7o25UzorBwwnOfvdLjuvUm16dROXGJhJQelsAh0eq0+ZXqQBEJkhZX0GtD1v1ZVILCvj+6behXUrbrmdQacPz40uhOtjgz/QuRvJ/pleVumrIaQWJXcOOxY5pijBKAWNkzOmxyUPqVLXsu1JKmSebryt11USOob5QNsGWFnO4bir1LXVHEM2w1b6bn4LH43szNSfX+I71onTVsCt3VjJXURaDcOliV618NZlD9NgxTExM4Pjjj8e3v/1tRDxK6MyDUPeQpZTi+9//viZ0CkFsywxIaR9HufqcCdw3JAk0GoHS046J+QlQydvInM6ixAC6IuP42ub34Y87j0ZekexF5ijxTOjiQwTznlAw7wkF3Ru0tDdSYfJRd2AGgSOh03EidABAafUoXTXkrIrE7hHtiT5a1c8BNk5uPB4InWcoSrhHugZNyPqe+QVVlFIEz9N6ghBZHQ+OfT1yV/MzNoTOyeeM1GvGldIx5F9qRSwWw7PPPov/+I//gBriiHd4dRPAr371K9x///0ABaJ/64E04XHYs1klTkeSSvN5AgCtMc0XTxYlBnBa6yZIhOLZ1FLkHY745El8iKBnvSHDOqUlcfNlZK3fWElOnRGrXKJ0Oiqtf5P3UOgIKUZeWW6E5iZYIXL20a+lU3A6xinRNGtqlmWN0unUapJ1Kmr6551E7dRUqmYUUhpPQHl9GuQVQ/jLX/6C7u5uXH755Y7Wyy9CK3X33nsvbr75ZgBAZGcX5BEP5mNrdokDKkTOL3SRAwCJUESh4tn0Ety8412+r4tR5IwS55bUggK+f9ptjpbRm16d8EzvYrT8uhNOwpVlUbpq8EpHUk3odGqJXSNE6HyQuaadXYLztFiB4+A7GKN2YRM8biN5PYra6XLHEnkrlZXN2hI7fSaMsu9isb/k4RZgqwplySB++9vfYuHChXjPe97DvH5eEUqpe/HFF3HDDTcAAOS90xDpb+NX+FQQOcBTmRtaIeGEM9ZbvmeMykVRfgHMU9lxlG5sIgGlz5nQxwckzHjNOhpXjdw0GSNLHG6vEDe9AtAGLNjBIHdMUTo72InYMZVbX+iYo3UqY1OTVRJlL3A68CHowRLNJngO4BW9C7TptQa8RyOruTyXY6Se2NFClQhjlQEi8kAbPnr1efj1r3+N733ve5gzZw5WrVrlej15EjrD2bNnD66++mooigLpQAsie+zl/aoFIYQ9R12YMXcCL/aVo9GIp9E5KlO0RiZ/QS1KDODj3U/j491P44y2NxAnSoXQsVdmrz9dbFjCrHXArHVA15sKpAItPexE5igBEMLDYzJKZx9bUbpqsHS+Z00b4jZK52WETrW+qE9FHI/mt1WoNPkIAqpOPvysttjvzo++dzXXwyM5JBLhFwXkdHyo2Sx7xM9iP/3+M4/h1FNPRaFQwNe//nW8/fbbLteQL6GSulQqha9+9asYGxsDGY8huqMbhPFOq4ucJxekMCH7I3JW6DKnixxXmbNBucipkyLncMYFFlIL/Wl69TxKN1kRiN4vxqtIjvFGElahUxW2xMOCcpzc2F3cvLkIhF9yp+dwLD6CFjyq0iknd0aqRunMmAaHEBA8+/2tWLFiBUZHR3HVVVdhfJwtF6gXhEbqKKX47ne/qyUXzsmIbesBcdBMZZS4QEVO8nmEoc9kpkuQV4x5E5WzSXxIqhA5p1NnGWFreqW+NL0GhqrWly6WKB2PmwiD0NmK1POUOYYbWtP/AK1H0F1j/I7cWQhezY97JGANJXcucdNHzyh3RJWw/bYxzJgxA7t27cK1114bmj6xoZG6X//613jyyScBlWhCl6/f3S8UEmciTOvCk8x0CQNHEkwspJBl1bHMPZU+2PEgibGJBJR9Wn86XeRmrQOmb1arihxRAclhZCusTa/P9S1G8jedjpZhano1RunMeBG1U2wIo5/Ui86JJtipRQDNsmGI3nktd5wKci13ajbrbi5oXezyMkaekBCNRvHUU0/httuctdx4RSik7uWXX8ZNN90EAIjsnF41dQmRZZBYDCQSaVp5ChtGmXOTz06lxPEgifxQArOeKxe5elE5QqmWoy5kDCpteHF8saNlFJUgkvGh6bUeVlE71r50rqcRU0EZ5yS1jNaFralVVScjAnYelNr/rMAZQfS7C0HzrFdyF5YmWRKJTpbBSvGckibi+MxnPgMA+PnPf45XX32VvUxOBC51Q0ND+Pd//3dQSiH3tyJyoHyka0nkYjF3v5glEnx43wrW2SQ8RBc5HjLHwngqgaFd05HYF+HSvMqb1MICrj/1D46Xy9MGj/gEHV0rCh2/8oIXHeONm+qS5hWKUtqHlNKyh6AOAUbvdMHzex2aXe5Ky7tBUfCTj/4RZ555JhRFwdVXX42BgQF3Zbok0JQmqqriu9/9LgYGBkDSEUR2TQdQHPYtmjx8JzNdwsQCChBaVeJiB4/iF0f9hnvd46kE8geKqUsotHltbVxPWvIZpKKJup9LFrJIRyojwNkOGaOLnfen65RSZS+NqUlsy86qukieyohL9hN0svS94970aoWqaj9C/I7SWQgdpZQtYs8ic7LsPNplkdok6FGPJczrZXEKiNYQC/TjN8htYxQ7HwIVRrHjJmOGsriIo81k16UoHcOyVctUVDz5nY1Y/OHF2L59O77zne/g+9//PiQpmCBSoFL3hz/8AevWrdP60W2fBSlS/+bc8FjtaEoDvUjYkTkdWVbRIbnobGrAUuQcMHtiED954me4/eC1+N0hJ1f93Ie2P4n373wWnz/mE+hr6ap43+qGZgVRgOg4kBuO4JX0orL3FCpBrdExT7FbSZHn+xchckcX8q3lFzyiApF0jQ3lVZ45I35H7DhF6ErzwBLiz3RiYJA4H9etDIsbq8NDdmph3Ed2rt1e7dOABK8R5c5S6MzLsoqdKmHPnycQPzaOl156CXfccQcuuugiprLcEthpu2XLFtx4440AgOieHkh5D2aMcItEtKmCnHy+5vshukrKMtJzEoE0serNq/n+JKBAezAK3ZzUED6z/l58dMsTloMkPrT9SXzqzfswJz2EH77wc8xODdoqXyoAsZHyR3QcmnzSYiJlw6Oe0I0rzqa4U1QJck6TbONDlYF8q1R6FJIujimnUbriMkwjWN32pXMJZV1vVlSf6/MC/TtUewg0Aj62J9cjgCZiXhApHM2yLsRYykTxr//6rwCAG2+8UcvkEQCBWEY+n8e1116rJRgeboU8OC2I1WBDIiCyZP3QJ0yXJOtHGJBl0JY4xg7rxr7Vki8yp08PViFzNa4/8UEZXZusP9CSz5SETkcTu8fLBknoQqeji12yUB5ptBK4yARKAmd8TCyguPCs551uAq5YSR6VgMSOofoLBwHnZtfyouuX65vQBSU8QV1bhOCV45XcOW3F8XiAB88onalgz+SubpTOvAwjP/3w73Hssccil8vh29/+NnK5HHNZrARyNfjNb36Dv/3tb0BBQmzPDEcJhn3t50EsBK4R+5kURY62xEHjEYAQUBnwo99+ikbwyvhB2L+925bMlaCoOjgiFU3g9oPXVrz+6Y334UPbnwRQKXQ6fzroeK1vXfECLOdpVYGzXC0CdESc56dzwrP7F0P9wwzbny9JuT5K1eu5UP2CQ7OrpdARxsFJ1fr5CrGxjuI12ww+djEmGQ6aRojemSXKA7kjThPzM4gdicchxRN47Ze96OjowNatW/GrX/3KcTlu8b1P3datW/Gb32gd7aN7ZoAUQjL9rFVTa6NflGRZkzjA9z57KRrBgNIKFRLyVNJkjiN6H7rPrL+37PVPvXkfPrT9KczIjlYs85Pl5+APi04sXWwLLTImZkq2BmT4iaJKbLNIGNFvKnr02OJ9X5pefbi5VRsw4XmEzkbZRJbDMzjCT/RtQ9VwZh3wizCIHcCt751nUTrryor/FUdsM57LUkyL0hFZcpafzu7gC9PcsqQQQfqVBLBkBLfddhtOO+00LFu2zNE6u8HXs61QKOC6666bbHYdbqu/kFdIBIhEJh9O+s6FGYuonF9Cl6IR7C50YHehA/1KO1SPD6/fHXIyfnzkeRWvVxW6xSeVv0gA6vFFiqU/HVcobczoncsonadC1wyROT9vzgHNs9oUeHHtDtO+sCOYLiJ3utC5wmIdSTxeelghj7TilFNOgaIo+N73vgfFxx92vkrdn/70J2zdupWp2dU1RAq3xLm94eoyZxQ5n2VOFzmvZc5INbEzYil0TUQ0paLtTRsDQMLSJFQPBqEz9q2zJXQsTbB+yZwP521g3UjCJBRTnUaTbQ7Nso6bYfXlDBJXTeTMPP/jt9Da2oo333wTd955J1O9LPh29z1w4EBp1ojoni7vm11lGYhFJx8+T3bvC4SARixkzifMMhcUty07Gf1x68E2/fFp3IRuYn7wgySqYveXYDFyR5ymPglp02tllR6Kl0RE/kxeVBOKqdxUGyQ25I570yvrvrYpd9WidKxi5xRSiODyyy8HoM02sX//fl/q9e0MuvHGG5FKpUAm4pCHO/hXMBUkTscobz5H5QDvZS4+KGP6m3UuMBSQcxRyjuKjmx63bHIFtKZYffCEW6jkzyAJ5Y/2B0kwE/TsEB7ge9oSAR8aLWLUzDTSfqghd1yaXTnw07/7Mw4//HCk02n89Kc/9aVOX8xn/fr1ePDBBwEKxN7u5tPsOpUkDghE3owoSRXKnCy6W1PeR+YoIBUqb85GkZPy2vsf3vYEPv1G5ShXI5/afD83sfMaRZXY5nt1APFLfFiidE0omwIHUNWzSeUFDjDJXWiidNXKMsidnXX1LVoHgm13DIMQgkcffRQbN270vE7Pv5mqqvjRj34EAJAH2iGl2GaNILIEEosC0cjUkDggcJEDJmUOnXnMnzWETx/0mKPl7x8+Eg+9vJK5fiuR06kmdFZNsWaxK4189RA/BklE0zb707khgAgY8SP3GmtqE6fViCZbx3g172hDEYb0WdTdyFNfKeWks9e1yy+xk9JxnHPOOQCAn/zkJ57Ptez5t3rssce0wRGKhOjeyimaaqGLHIlFJ/uyhOFA9xKHIkdyeZAUn2m7jBhljkgURKKIygpaHU4RllUjIDnn+0yXObPI6VQTup8sPwcfPPWr+MnycyreKxM7H0a++gKF8zlJ/YBl6jtTlM4XsWsWJAmU0tKjWdDlriGkosnhth9C1G/SL7H73+s2IJlM4vXXX8ejjz7qaV2efqNCoYBf/vKXAIDIvg4QpfYvVqPElYncVIA1Iqfy64yuJFUos7NQZpfLnF/QGIXUnUOhtbrMAUCykMEHtj9b8bpxlOsfFp9kKXbv3/lsxYwSU44wNnHyWqdmEHUOGAWv2qPRCIXcNXtQwYyFgIViP1SBRdL8EDtSiODiiy8GoI0v8HKmCU+/zX333Yc9e/YAeRmR/srBEVNa4qwI6EKryxw68yAy1R4ByJzcngchtO60ZelIAp9dezl6k9NLr1mlLTGLXW+iE58/5hPajBIh5Nn9i6Hc7u0gCcf96dw2vbq8CYYuWidGwAZO4FIRcJeYsMC0HzyM0rmRs1rLEk6DLn77mf9FT08P+vr6cP/993Mp0wrP8opks1n8z//8DwAguq8TEokCMcPFsBF+UavaRPe+5HRiaa5yiZJUgY48QOCrxOnQGIXcngcAEOKs/r6WLnx27eX4v8/ciD8tOh5/OOhEy8/povf+nc/i88d8An0tzroA6EzMp3jvmevQJmewKHbA3jrmO7BpfLntOvqH27BgRw5qTEJmekjEgRA4nnLD/OOEEFc/WIgkOctbJxExCnYKUBKKoGat0K/XDRj1tIXNbWoUO19nnGgwCJXwsY99DD/60Y9wyy234Nxzz0U0yn+UrmdSd++99+LAgQMguQgiI9PLf92KHR8oNCoj0ykBnVnfZc4ocoBzmTPS19KFfzj1C8hIcRCL0bI6f1h8Eu5ZcKzjCF2+HZhYrE2l1TpzAidO2wIJKmRiTzAkQlFQ7d9sqCqBqBRyVkHLvvI6rETPl0ESvKgldl40Bwux8wZ9RGSI+kUBCHa9vJA7Nz/wjevhc6BAFzxLuQtplM5YhqNpxBj4+SfuQ/dJ3di/fz8eeOABvPe97+VehydbuVAo4Pe//z0AIHKgG8T/KWaDQ5+WKWTQqIxCexyF9jiUZFSLQAbYxKo/3JKO2BtNXU/o8tOA4SMLZY+JJXkgqgJRFVFZQZQUbAudK6jWTGp8aKKXLz0SQ4o/gyRYkhR7gCfNsLTBpk4LE2HNLRfkOoUgW0EFrAnAXQpYRdNsyIWuWlksTa8kGqn+wGTfultuuQWFgsP5t23giW098cQT6OvrAwoyIl4kGhbYhkZlKInibBMB/IidFslA6tY6hfKQOF5kp0kYPtJwQhEKRMKzfhVQgBguznJWQXSsODMEIfZH8gb5g8MqWudgfUQzbEjhNFk8V4KOKAbVNFutvoCid6XInYe9SSilXLtIuY7YqbRmv9tffvJBdJ3Qhb6+Pjz88MN4z3vew16XBdyPeEopbr31VgBAdHA6CA3JSW4HiVQ+GhQ9Mqcko4Dsr9BJUNEiZbWHnHMUlaO9Ccxex188ctNk9K+KlR6ji0kpCoeoyl3o+vKdeHzQfn86x1BMXqgpBVHUuoMgfEs6XHMlQnJOhT1KF5bt5JSwRfDCtC5hQY/eVTv+OYswkUj4jos6lPLislKjBYVQCRdddBEA4Pbbb+c+Ep17pO7ll1/W8tKpBJHB6fUXCAqbwhbYxNcMlKJyQCCROQkqElK+/gdroRLIWT4nfm6ajNHF2i8mKmkPACi0UORm8g97G1EgIaf6PNiBUhCFOovc1cKrplc9YscQNRTRugbCMDtE4B3owxhNDAP6OevnfY5nFLV4XPGO1rFSlmhcUapG7H79hUcRPyqOrVu34rXXXsOqVau4rQP3o/vPf/4zACAyVD8vnS8Us0yDSE0RgbMkFi2PygUUmXMtdBzIdURw4KgYDhwVw8hSGWoEUCOTQgcAIADkJr7R65E7G9G7RsR1/7qwR+makFAlERb7vxJj5I5jRK2mzLuN3nl5H+eVtqhKxI4oMs466ywAWrSOJ1wjdQcOHMAzzzyjFTzkUZSuVuoPK/MPQuD0KATLzcduahPj9yJFkfMZLpE5DmQ7ZIzP17a1MSIngCZ4qg+zZzi9SRKinR9+9PET0bpQEZoUGEFEqezAuj68RdXP6CaH6F1YonUVVInYPfyfG4GDgaeffhoHDhxAT08Pl+q47qn7778fiqJASiUhZT1O8GqMwFlF4hoxImfnpAzB9wpDZC7VI2PPyRL2nCxh4EhiHZETaBQjd44u+h4P7Qel2sWO9UbEKmkiShMqQhG9Yx0h2mzUEiKGiBqTsNuN3jVClM6IRcROysaxcuVKqKqKv/zlL9yq4nYLpJTivvu0uTgjg528itUgBJDkyYePAheK6XRCIKlqXsJYNh68zM3QZG5wJYWaKD7CPGrVJht752DurTFvK1HDJTSs5xYtKM6bbHidOyoN51y7DU4ommfDInf1BjIEiU3p4hKBrVZPowldDTb/pR8A8MADD3BzDW7Nr6+//jp6e3u1ju6j7bU/rFLrHUOI6MSqE5Ioo5qXgEywfSNTM2QMHaYd8FSioLEQXuxcohRkRMe9HbxROu94zl7CciGik2JEKQUBnK2PfqGvdh2pV7dAUIswNcv6lYqEpWy/0sY4aAYOsgmW1BNCi2ZYebQdyYNHsHv3bmzcuBErV650vR7c9sb//u//AtBW0lYaE3P0TY/ATWX0xJUhEDo1L0Edi2pCRwGnM0XxoBSVO2IyKteMQucrpamVamxHHxIOG3+VUgdRCVowRMmo6m9fORGlm1qELVpWK4LnZj3dSpApouZZP0mv/cCPKJ3p+kFUGSeffDKASYdyC5etVCgU8OijjwIAIqMd1k2jjdzXjQW7KRtCloU8aJlTuvOlvnK6zAmR4wxvEXLSrEutxci22JmbYxok75XnqCoIIZYPgUtYhclLIQxjE21R7oLuI8nUjOlns6uilLnQYz9/HYA2aYPKYeAYF6nbsGEDhoaGgIIMaaKVR5HNTchEDghe5nqmj+GTRz6Jdy7bIaJyNpByCiL7R+0vYHWxcHtDMN5UHIidq750Vti5iagUUBskylbrZq2q1o8aCNFrcoKM0lWUV8xCwLuPpJdROg5CV7fp1Ux+squNNNGKtrY2DAwMYOPGja7XhUufumeffRYAII+3gUBcMCzx8EJKJtKIEIJCd9LxsmV95gJwqJ7pY7howSuIEgXtchotkZz/K8GRjBpDX6EDD/cfhrfuWlr5/kyKI9dudV8RhTai1S7mi2u1/nVOm16NQqGn8WE81uv2r6sWlaMqAI9/afvd9BrC+aMFgppUES/XCajN5droSxva9CYWEBCsXbsWDz74IB5//HEceeSRrsrjInXPPfccAE3qfIOlkzQjTAeInofLjwOL0rJ5QetB8ip6Xh2HlG/DgWMU32VuZtcoPjD/VQAoyVzYKagSduRm2PqsSiVklAiiE5UbVt5FsKX/kIrXO4YpYv2DoFEZ+c6E6/W1hRcDJ2qJXZWm1/KPWItd1Shdqd4a14NGitIJnEMk0QzPgs/SE5r8hGZqzPzgKfkCENUU7LH/txGYD6xbt851sa6lbvfu3di1axdACeSp2vRqdXKwZr2nFFDhibCSvAoprYV9CaWIpqmvQqfLXNhFrmfWKH5y+G/LXhtTE3gjM9912ZJCIY1Xvh5Na30wSY4i1j9R9p6noscqdoz9eZiH7de7aVMVUCVvfuiJARIaYRYnPZpjZx3D1A+tWXDYPGpb8BogGbHjplcjRbGTJ1ohyzJ2796NvXv3Yu7cucxFupa6v/71rwAAKZUEcTLXJaUA1MYa8VrtAHE7bZHHmGXOb8IsczNmj+C/Dru17LUEUTBbLr+J9/l1U7eQJaPo6YKnxmUUZkxDpN9Gv7p6TXm62LlpejW/bo7W2YjSTX6UIc0JYN0MG4IoXShyXU4VnMjdVIan7Li8h1cVvFrl8m6pCypaBwD5Akg0gsMPPxzr16/Hiy++iAsuuIC5ONdS98orrwAA5FSL26ICw5bN682pTuHZtOWQoGVuUGlDi5TDRxb8NVQyl5udx+9P+28AQCspYIYc/A0g10YwckQXOjYOVr5pEL2S4FEKkrHZ/9DuQAK7+bnsROksxM6J3BjFrm7Ta1m9HnTLEFG6xiMMcqcf+0LqbVPqf8dJsBxF64IUOwDHHHNM8FJHKcVrr70GAA016tVyJ9vZ8azzufqIUeSA4GTujfQ8qCChiM6lFhbwmRMeKT2fGx3CorANyCCAGrVxDOpCpajaRciLUdR2fojY6cjPYeCE9n0d3JiN0bqwROnEoIfgCFLuSpGmYt3NKHdetbRRG614PvarrwVVFPcSmi/gN19/GFgEbNy40VXTsSup2717NwYHBwGVQMr41LnbiJud2iAjY2yTL0Ae1UTFK5Hrf7sT34xdgGuW3mX5vlHm8lQ7yKPE2U31+I6/YXRlEus3LHK1rkaRa5GymBsdKr3XKadclR0qvMp+zyvCrAZwQ+N5sc97PMuHwB/CJHdAcwieR0LHexCFH9E6HmInjUUQiUQwODiI3t5e5n51rqTuzTff1FYmk7A3i4TAOxyOgGVCIZjIlc9P2l+Yhs2ZOQBQJnOsJKQ8psXYInu1RM7ImJrAW3kFS6IZ5vUMFbUEzG6UqFqWenO5rAlPCWG/kTkd3agPmhBROoEZIsGXyJmV8JS9FmD0LsQBjVCNivUZQiUccsgheOONN7Bx40ZmqXNlYlu2bNEKYY3SOW1a4YSTaYkE1vQXpuHp8eXYlJmLLI0gSyOuhY4VeUEKl178IL580n04ON6Hg+N9VYUOABQqIedxXrNTZ2yBdP6Ap3WUUTVZLYcEwxVl+nzOSgxzQvO4rjRplE6TTe+vf0HPLFAXu10XvJAgIhUf4UtEbwsPonQVQmfnHPbiGGPsQ0s59L09/PDDAQCbNm1iLsNVpM611E0VWNJFeJTWxC0TmRieHl/OJSrnho4FI/j9qv8HAEipEewqTA9sXaxokXLobplAP7r9qTBMk5BXgUgSqJ9C6CY66BIRpWsgghzQYBW9A8IddPBD6DjjV3oTt82wd/3gSWAB8NZbbzGXwSx1lFJs27YNwBSTupAOliD5ApDOgSZj9T/MQGxIRttOYHhFO7IHc8lZzUTnwmHcdtRNaCEU8yNasuv9ygR2NWdQxRpFBcnlK1/3un8dhwg3s9hJRGtSbfZUFWG+mTc7QY9WDUvzbC0aKQWZGwIaCStltPv3W2+9xSyizHfnoaEhjI+Pa9MV5bwRCVuEZARM4HgUGdBljqiAlAekvP/bWhc5AGUyN6WpdrFnETs7Nw7jHK8u8VXsWKN1LppeXUfppmqEz7hfvRxVWY+g5Q6wHlwBuF+nEEbyXUfpbDpAI0TrSCYGSZIwMjKCgYEB9PT0OC6DWep2796trUQ+6m6QREBJiJkTnHqJz+vS/tYE8sk2HFhT2RfALHOsZNQoBgtt6IpYTKNQh86Fw/jtkb9Cu6TWFLluKYlV8f14NTuTfUXrMEMq4NiWbViXOtizOrjRAH1GfW+KFbjD6wipuXw/BK8eYbg3VHz3AJtog2h2tZPaxCtcROtYBZJQCXPmzMGePXvw9ttv+yt1b7/9trYSuShrEQIg0AuHlFO06akM8JI5Had97ySouHjGOnzlvL/UlTkdmUhIeLwdZUKQcJieJXC86EQsy8Em4/UjWhfWARJW3T5U1VZS50aZ3NwSfV8HdXMPU3/Van3wAP9H87ou0v/t6Vi2WMVOVZmFUJe63t5erFq1yvHyzFK3d+9eAICUjU69JlCWfnXGwRJhuDiY4C1zTpGgIlGsuFNK4dBY485Qwkq+lWD08C5Me91iVokwwUnsGrZ/Xb1rXd7FtnE6c40k2doXTTFVWaPIXVgii7z2eZMInd+wRutmz54NAOjr62Oql1nqBga0dA0kz6HTvNsmWEap9LUJNqTD1hODBXS9FgVRgpe5RubevpU48PsFZa9JeaCtX0FyX2XevXx7DMPLyvuiUglQYj4fI6wX/qDFznFFNqN1Qf9A9UO+Gj2dSaPIXdCY18+4vZptwJGX5y1rInbGaN2Dv3wOmB2A1A0OatEEkg8urUXT4+GBSvIKkM0h0hqDnLHfhN6xDfjNUyfg70582lX9tWSuT+nAq9kBrIrHXdVRC6cJiJ/NzMIXnvwIutZZbys5B7SMVF4opQKFlKqckiyWzWPGmMVUZYUGutgGKXZeRetclkeVBtp/jY4fcldLsoOUO7fHfYCjWB1H6Tj3q3McQXPRlMoyaEJ3Kt2xnOJe6gqRyQzuDRhSDeWACUbspDXRZY7oE7g7jAxIOUAeZz/B7ETmclRGhnqbNqVWAuJnM7NwzRvnlb1WUCVIoxG09PO5aROFgljInvYmh/xqfiV+baSIXb3tymObufkOLPtcDDYRkbsGwrNmV+Ocz42Oon2P0dFRpsWZ75ylCguydjF0uz19bIKtsHSn/VjCSo1UChUy5zNhbmZ9Kj0H3950Tul5XpGRsYhe0u4c9h0Tx6wXfJAPwHo/VctRFyRBDZ7gHa1rwChdU/SV40U9ufN8BK+ezzHAEZshxluhQzibYOE8WkcK2mdHRkaY6mOWunRa6ydEVP0GFI5oXWhHeQX0a66ezEX6xzAtJmP0IG+aOp/Ytwy9L8yBsiSN767+syd1AM7SmvQXpuGv44twINuKbYM9yCsy0un6uRaliAol4dNNtJbYhfFGzkHsCCHOJcWp2Hk5y0SzRs38TmfCq7wgxKp0bAUcPTQT8Hp4LnSlv+3Jk59NsIAzsSNBRep0qYNaPFhUCkhNFAJtYHSRA1A3MkcKCqQc/yjLE/uWoXfdHEh5glgaGJ/wNvVNvbQmfYVOvDq+EACQV2VkVRkj2SRGx5OerpeSIMjObkO8z3mePs+ToPIu163YEQKCgKJPQc9T6td3Dvp7+kmzyl2DDXLwRej8wEW0zhHFQFkuV6V7Th2YpE5RlFKFROV5sAaTiLjUbBnGJlgnIWWVak1zihpYNMcsc0FiJXJGuhMTyPZE8PaBTs/WgRICNeriuApDdnsnBCV2xGUzbAM2vTZtZJA3QUpQWCN3jYa5SbvaPnVwvwxrtI5QbZ3y+TxTWhRmqStRPGYppYBSHHQQwJxpAACVgkohboL1CmM0Tin+76GgdvwN+M3TJ+DvTpgcAas3s0p5gljKfR1uRsDqMmclckYikoK4HNJEs0a8Ejsvfnn63beOJfJkboJtxAESCHd/Oj0642lqE6/huX3NcgcIwWOllqR7PWDCr2gdtPM7nU6jpcVZzlYmqZO8jGgFFa3zA5796mo1q6oU8HDzSTlAHtMqeKzvEOx7cTY3mdNxOgL2oVQU39r2dziye29dmXMD7c5h35o4Zr3o869/L/qC6dHpsP0I8jta14hRugahKeSOJ2XHtE+C10z30qCbnl1G65ySy+X8kboySPnFlypqY0brwtwEaySg0atm2t4muO2ek7jLnBMeSkXxbxs/CADIF2Rk01FMZGNYOXOvZ3VKERVK0tn2d9WvzogX8tVsYuegfO2cb8woHRMs35XTTdTYr6pM8IK+SYeFoNOyNAIeHCtMsz54PRKWTpYdiThXtPBF6oDmjtax4LHIORkBGx9T0fJ2CplZSRSS9g+flu1RfK31ffgOhxGwf0nF8eWN70e+ICMzUT5qNVcI30Ad1/3qAEBVQdJZe8eBnZu3UUR4iR3vptd6Ymf1PZ1G6xo1StfA/enKondu+0I2G7RO9E5sK76oFJAdXvc8j9ZNXteSSecD+ZilLhaLIZfLgUoqiKmtr2GjdWHDmBzYw+9iZwSsLnNEUUHyCkgh4agOKQ8Uxt2NgK0lc6ywDJbwpQlWl7hSpaaoktsRZWYpCGvEjgW7oqBLBStUDUyuwtyfzi5EIlO3WdbOeVZP8ATW2B0sEdCxVy9aR2VtveLxOGQGh2Jufm1tbS1KnQLCoRW3gmaN1tWTNPMsDyxNwhybkksyp1KQ3OSggsT+FDq3tWH4YO/EXR8s0adM4y5zOhFJQSLiLJmvZ02wZpGrFQXyItFmGMWuWrSuGWQg7E2vgvDAGqFrtvunHewMlnB7PrgZMFHvvJe0fe20L50Os421tLRgaGgIVLY+2KiigpAAkxGzROuC6ldnJXJucTlYoprM6ZC8Ajnj7Uijm/euxRvPLUHk4DHbMpdJxbBh/1xP+9WxULUJ1onIVSwbIrHzctQrS/86r5v1qBpYGhPfonQeN/VRlYa7ObHR0gkJ7GESOpZ+dVRRQBj6u+nHUq1oHQ1K6tra2rQ/qkgdAPfDi5s5WlcReagVlfE+ghI5MI5pMRnZrmhNmXNDcmcUX//rhfj2O++s+plbe4/D3+5bCgCQskA8CkzMsR+doypx3K+uK57C/J5hT/PVleFG5CrKCpHY+QWPqBMPIQtqgATPAQ/Ndm31AiF3zYPVucPSr44F4/FT41iiEe0Hcnt7O1M1zFLX3d1dXIHqN37Rt05fjxD/Gi1C8gXEekcRGU9wlzkdOQekx6wFTZc5KQu0DE0e8KmZ3u87liZYY7+6SEpBcsewjYUoSL6gndA8ozxTQezCFK1rtChd3bxeJoToWdOIcldr3zfzfra6JnLqglA6BxXFE7fRnaqnp4dpeWapmzFjhrYCUY+Tt/odrePRBBsGiXPyPfT1VRRHQsejX92tvcdh2/1LIWfKZa5UxyCFsiWBzCEZ5jq4sTeBhQ9Nbh85nUF0/5gma1m2KV244dVk1nb6jvidcNgtUy1K5xSqgqrUu+md3GDcdkH94HArd2H5odTMQm9uJaxz3thtgi1L30aLky3YWp/K+qs1wdKodj3VA2dOYZY63SJrSR0hpDjCrF7HQA8P8mK0rhrMUTxVDccFphb1+tW5lE83/epu6X0X3rp/CeQM0GohczpSAZCzVd+2hKVfXUUTrEngAEDK5RAdNCXlkwhIyuEKFpfjfoO2PerL4X7nnUXdhxHdJXhH6xotSucC88hUnpLHpT+dj9n9LWnEyN1UxFaKp/pNsMznX7Xlqrx+1j8eh/vvv99/qZs1a5a2XjEbkR3zvG1m6m10CXAVratxs7PcUZSC2NiB+rJET2Tq5QWGZ3NYlZs6yReANAFN8h1haqTz1ShuePpiZKaTmjLnBpZ+dRFJwdsHOrHwZu2UkLNZRIZsTF7rZn94IXYFpX50lkXmOR7fpfMGsF8mpXykZqpF6RjEqVqaEeProYni+fkDoRpC7lzjSWSY47W16rWnXhOsw2OCUoq9e7VgxJw5cxwtq8MsdQsXahOlqwkbzU4qdTdI0q+OjAac3ECYslIHgZ2bkYcXpvggRfeGcajxCAD7ee68aoJ9fucizLx9Mrnj/JSKeN8Y1zrqwkPszImEAfcjuK2W5yF2PI4vp9uMV7QuqChdCNEFT8idgUaXu4CaXsOeq7CWCzhqgrVa3qIJdteuXQCABQsWMJXJLHWlCqOKlqvONNdmheS47VTotm+dV32OwgylxciNd9/bTr+6+CBF16YUSEGFlMoXpc4+PJtgjSI3J0OR2F/enEqjMkjefh8xGpGARBwkw9AE6wYrkTM/9yI1j1nsHPans+yTUu9GbBWlY5HhoKN0LuoMa7JhL5toKyuzsQ3CLneN8OPfR8IkdFbBGVfnnZPjtVgXlVQMDg4CmAycOYVZ6trb29HV1YXBwUHQRB4kZUPY6jXD1qLUPyzEKU7C1ARbdkB5OBtFjX518UGKrjfTIHkFUmpydGlkNIPWvRIm5nrXzGtugn1+5yLMuCOJOelKkSuDZf/JbqNiNgWllshV+6wfYueqKJti1ww0cNOr0+VryZ0v+enCJHdA40bvPMRzoXPqG6YWQdtCZxWwYmh2BQAa11o+u7q6JtPGOcTVVBBLlizB4OAg1EQWUspGc1oDNsPaJTRNsC4vHjz61SUGKKZvrpS5EgqFnHV2UWdpgs2+NQ1/u+1QAKgvcy6gEodoXS2x0wXNaZQobGJX5dhkFju7MkxVPjdVlZZvSz+idiGO0tUiNP3vwiB3Yai/Hj4HSsIUobPCcfer8hec1aVM9oNWW7R7yMEHH+yoDCOu9uSKFSvKVsQWbtMfUB9+5TUaejLjKoM+HDc7OTwotSZYBfFBijnPptC1cRzySMZa6Bhx0gQr98ax4PYIFjySR9vOFNp2ppDYb2PQAwAqEdCow18eEtxH64DyZnJVrXyw4GbZelQ75qp+vHbflGrHb80LrBNhkAj7w2r9Jan2w/Q9mPEpSucVVKXub+JuxdbhseoZta7VU4RmEjqLhV3VfdblxwAAli9fzlyGq0jdoYdqURC1pTx6Ujdi5bYZljVa12z96kJyYZBSObS/OYiW9gRXkXOC3BvH3Ge0HwxSLo/YkIuoGcOvatfROpU6a151VLYHEbtiSh+ezaehbYpVKduPUeP2zuerv1e1Xn+jdF7fbEvlBymcYYncAeFaF58QQmfCtO83b94MYDJgxoIrqdMrpokcqKSCqDZvGm6bYf1OSOwEv/rVeQjJF4CMBJqI1vmcApIqCr0kQXIwEIalX11ikELZmkBm2eSPCF3mXIucASoRwOGACeZonS5zXjfleSB2pX4gdmTM5gWvrCy7aUxqNcNyanp1dbG3EsJa+7usibexo3ShJUxCFfZ8p5wIu9C5QrGRSsqMeVCGpGL79p0AAozUzZgxA7Nnz0ZfXx/U1jTksVb7C7sZDRvSQROh6VdnRm+CdSIddSSjJHR6065KQTJZ0ETcXvkM/eqkAiAXfc4LmSvDy2idMSrn52hKu3UxiF89sWvEfmEA2KN0ZWWw9YWk1KJlwaMbY6hvuF4eO0EnMDYThOB5fA8N9bFlxM9WPIt9q7amoSgK5s6di5kzZzIX7XpvHn300doKtdnrs1S5BtX7sNRE1fsmOL1gNsgBVosApyEjeQXSyES50AEApSAO++5p0Tpn02u17VGx4PYI5j+WR2Jf2huhg0d969RiiplCwZ/onBG9H4+ieHaTrNovjrEcRyJodc0Ia5TODTb6/oWaMEYR/erj5rSORv0h1Ii4OHe4BHJUFR/42ikAgFWrVrkqipvUKSxSR9XqkmWz83IoB040wclICgpIZrIfEMkrkEZTkzLHI+eXg2hdbFzF9A2j6HxjBC07Rz2TuTIYo3Vl0cqSyBlkzk9qDaDxpDqL+hjqopRO6R9gzdSXrmEI2wCGMEUQWaBq+O7NVvgtdFWWeeWVVwBMOhUrrppfjStAk1lQWYGk2iyyJGUqoEruf2UaD54Am2R9a4J12rfOaRMs1ZoISV4BSWftjaItKM6aYG0QG1fRun0cRFFA0sWoXqx2Xz9euOpb51dfOSvs3phYm57M8x5XFFveFMskKHouMyfXBmPfOh5ROrdNr7yjdHapdv1rhBusmSAkK0z97byG573S6vgKUfcoS0IidDRSwObN2wGEQOp6enqwbNkybN26Fcq0CUjDHW6LdI755lRP8PwYBRu2vhpOUSlINg/kC/ajcsUmWCeX4chY1nLAhKXM6eQLkDIEap2BHFywsQ9JQQWZMESqgxI6lhsg43FaT9Rcj2TVz2FqndjaL1xFzPyO0tWLuJmvhcVtrOeR8yUZrFP0ebWDgKfchal5l8v3acAfCEZc3v95Ch0AKNNSoJRi+fLl6OnpcbFmHJpfAeCEE07QVqxjgq2AWs2wbtFDwMaHxzRsp3CgGJ1QDX2wPN5eBbWsCVZvZm3bNgJpPF0pdEBRHv3Zxua+daSgQhqZKHuQsZShiVUJpq9cgLmVqhdLQc2pPOxgvhY4uTZIJBxROr9huX6aJI9IpPQIFYQE+wM5iGZZL7+vm+/TKE2qOlbr6pXQ1bru19mfx35MyySydu1a1tUqwVXq1PYUKGHc4V6KXZB1eYlTeagnaSqHi1exCdYJkbEspm8ary9zASDlFMgDY9UFrpbEeZl6hveNxqubFmWQI/OF2On5yqnJJ4gBEmH5Qchd8HiIwFSUOy9xep443YdhbHoNWYQOAKik4qWXXgLAR+pcN78C2pQWemoTZdoEIiPtbAW56V8XxubOMK6TFTxkToehCZZk85BGJkAjDprZPGyClXLaCF8AmrAVXERsJIlv5K4R0zvoYseawgiwf21QKaC6TUESQBoTV3W5iLrYwCh2oRhUoR+jjSJYYWp6DSm+RIeDGOFqYzmlI4V8JoM5c+a4mh5Mh4tKE0Jw5plnAgAKnaPuCmuSKJpvv7jd3DyMTa08sRmtI4oCabw4opZhuD/PJlgppyDSP4pI/yikoTEgl9ceboSuVDiH08yQ5sPTYyvoiF2tc99upECl7h5FCCEVD1s0QpTOzyY0r+oK6gdzM0TsGiHYwJOQCh0ArP7oUgDAmWeeyWWQJbf4qC516rQUqFzgVawznJxoTSKPjtGbYL2QOUMdtXLWlcmcopbkkjgVqHwBUsbdtGS6zEnD43xFrqIixlOtisx5IQClOnj1JSuYrgN2yq4nALXOWR5ROqDmOtoSvUaI0jULQTbJeiV3fnwfr5tew0SIhY7KCl544QUAkw7lFm5St2jRIm1qCwIUOsfcFdZMwhXGX3QBrZOlzLlZL8ZonZRTENk3XC5zeR9+iNgVO8Pgh1qROR5iR6sJYzWxqZPOxEaFNcq2Ua4b6fOIMrlr4ihdKJpeqxEGufMxH6TvdTglDP3piORqPbwWOgBQusahKAoOOeQQHHTQQWz1meC65d/97ncDAApdo1Ddmn0TiF1DNMF6hakJlihKdZnT8Thap8ucdGAEyOb8k7mylahxyplEzs7xw3qM1Su/lti5Pq6rle2kedUreEQpJany4QWNcH30O8LT6IMpfInSTYGmV5dS6YfQUVDMXdsGADjvvPPY6rOA69Xm7LPPRiKRAE3moLZmOFz8Ve0i6+TiFcYm2DD+kvJ6nYpNsGXROVuRGP7RugqZ05sFwyLDLvvLOVnGSR1cm2IrC2cv2+q85dX0ykjdbVVD8kSUzgMaXe68pNmbXsMQJbSB2pbBzp07kUwmuTW9Apylrq2trbRySs8IAE4XLBa5CwlTOlqXL9SPzpnhGK2rKnM6QV109Zu6X4Mf4EzmzMv5InZOz22rG00jXR/cRvEa4buGQQaaPSoVRnEMUqoaROgA4ITLDwUAnHHGGWhtbeVWLvctcOGFFwIAlI5xqFF3ndgr8ELumqCZlxmvR1HWy4tXa1mHnzdG6+rKnBG/ZVhVQXN50IICqqjcZK6atPEQRiaxq7XNywvXymYRAP289WGARC20eWoZI2D69cyXFoMpEqUzE3TUzi5TtOmVSzoTl/3n/EaN5fHEE08AmHQmXnDfCsuWLcM73vEObcDEjGEAHkSrdLmrJnhh/PUSxnXyAnOzA0szBGO0Th5O2Zc54/r5IXYGmSt/ne9xYeyPx/O88yxip1JQvX+j45Uy7LegxYN1WxvXu0Z6lYrPOF4/n4UuDFE6M40id17SjE2vtb5T2GZHKXLe/zkGiqJg9erVWLZsGdeyPVHbj33sYwAApXsUVNZuBJ41LzVA0+yUaILl3YfEQVlEUUHGJkDGJkAzWftRIoa6HFNN5so+w7H+WkLgEkopqBfHmFqMWLKInaI0dpSuHlaSZzX1oY/TIDY8zSJ3YQwU+B0ta6DonA6NUtx7770AgIsvvph7+Z5skTVr1mjpTSRaitYBHsuNOXonBkzYg8dIxnpleBStI4oKMp4C0hlQVXUnHLxlxY7MlX3e5X6wEjlex7RKNVHWH/p5xhNWsaNUG8Gsr5PVw2t4ROls12XjOOUkek0VpbMiTHInml5ZFua3In4hSfjI909GNpvF8uXL8c53vpN/FdxLhDYcWI/WFbpHQKXJk9yXqJUuabXyB/mM4+/Nut5+TyYfQPlEUbUBGFVkjukY49UM61Tmypb1QA7ciJ0uc+ZIWKm/pPvpuKgxqsoidvlCRZNzRfNzPdELa5RuKhHkNTqEslMXlu3VLE2vDdZ/roQkgUoK7rjjDgBaiyaPGSQqquFeYpGTTjoJCxcuBCIqCjOGyt7TLoY+nMTGZgtaR/KCjtZVWz9fJNgH4eQQrSuTuUKBf1Mgc8RF1daHVebKynKwDnabWZ0e19VkzgwXsVMrntsWOxv9Bu2InivBCluUjhOBROmC/AEeZNTOryhdvWb7EDfjU5Vqx6QPMueFaOmj3C/6jxMwNjaGhQsX4sQTT+RfDzyUOkmScNlllwHQBkzQSHk/p5LYeSVS5oPS3DfFLFE+XExKNxSv6/YqWhfERbeggBQUbdoxBzLHHBG2u+10kdPXh3e/uHrvs4ia3c856aPmxQAKu2LHmDi6TPKK606LckdtSp7vUbpGEDrmCmnt534SpibZRsMD4SrJXKNiSFtEIwX88Y9/BAB84hOfgCzL3lTpSalFTj75ZBx66KGATJGfNVjxfumXs19D+o1YTuZt6JNnY8JvFpibBr2mVh28ZI6lHFWTOb2p1Vl1nJthrUTOq2O3Wplum1NrvWcnOmcFi9iZm14r3q8jdpxH91YUb0fw/IzS+QlrpIaneAbdbSbMcheC7kQ8qNefzixzXFKf+IkpB+W7v7YKmUwGhx9+uGdROsBjqSOE4JOf/CQAbSSsGstZfs4zuXN6kSlF8OqEpDmLnifwitYFdQFRVdBcThMoRXXfrOkEo9j5KXJmrNJd8CxTf84qc0aYxK7ePK418vjxmN7N5jliFrwpE6VzInes6+jFICueeC13U3SARC2qRucaqR+dSejUWB733HMPAODyyy/3polXr9qzkousWrUK73rXuwAC5OcO1PxsoJE7u3Doe9AQ0TqvLqZ2yi2KVGCRUUAbgBGEyJnxol7eSXt1dLFzmlKmHuZoncdRulpoyYJVpibnUqLhkEJVan09C0P/qmaXO7uENUrHQbgavqlVx2KWmNWXzYeiKDj22GOxatUqb6v3tPQi//Iv/wJZlqF2TEBpn6j7ea5yxxqtc0oYD0aWaIIfF89qdRiic1UTrzJVZ385rZ9VwCLnNVTlE50zoxabS/MFPpE0wLoZ1sconSWlqc3U8kfdOll+zPk5mr1GXbV+wHoVpQsjPOVuCkfpjE2pTSVzFkKntE/gmWeegSzL+NSnPuX9anheA4DFixfjoosuAgDk5/WDEpvNHo0QuQOaI1rn5ObkQd1lMudVio4alMlcM0PVYvMyx++p0lKuuLJRprzFDgg0SgegdoSuxjnUUM2utT9Yvl5+C11YRFCXu5BKU9jRRc7uccfUn87PPnhV5nCmREX3Wu3vD33oQ1i0aJH3q+J5DUUuvfRSzJgxAzReQGHmkKNlfZe7qRSts7oJ+SF2erSOY1Nr7eqsy55SMqcq5ULn9jtbyFxZldXErt4giWroUUC3+DQtXNm5FeLjq2qza+2FgmuWDbop1oxfYhem72zEj75uYe5PZxQ604+3j/zgJPT29mLGjBn4h3/4B39Wx5daALS0tOAzn/kMAKAwc7jqoIlalMmdowX9kJQGi9bVi8r5ceMrDkDwLD2HCeP2njIyB5RH56wGSrCg0qoyV1Z1VbFz2i1CBVUUqNmsFtXN5YA8w7RibmBNUqwoWtRAf9hayB9hYhI615VyOufCJHdOxW4KN702FVUidACgxnK49dZbAQCf/vSn0dLS4s8q+VJLkZNPPhnHHHMMIFHkF+wHhYubs9c342aM1gXZxGqGw2wELEwpmQPsNbc62Ram6JytVdDFzmWUrSyiq2r7URc825Ln87FvuY2cCp6XhGEQhFvCJHZeNcmG5Tua8SMZcBjOEytqCB0FxcEfbEcul8OaNWtwyimn+LZahPrcQaW3txeXXnop0uk0Inu7Ee2fzlQOIQwXRacHoMRwghLJ8XoxDW/261dYjQOXCQuZY5Z0p/t/qogcMClzgP3vXW97GqJzrBBCAFnWJMwh1M4sE8XvQAgBotHy93gMjnAI07byaQqxho7SVSNs0Smr78uyjk63m1/bwQ+pY03SyyiDtu7Hde6L+dmjKMwdQGtrK26++WbMmjWLaV1Y8L2hes6cOZPNsLMHocadX9wBEa1rSLjPPGBzO4dpoI0fEZpaza21qPV5DkIHFM9blnQgdvvgmaJ4XJpo/RQ6lU7ObenhHJdNKXR6HWFrlnUbvQvLdxFo1BE6NZGDtGgMgNbs6qfQAQFIHQCce+65OPbYYwGJIrdwH3MzrGNE3zrn8GiusppE3QBT1FWnnrSETOYIIe6+bz14jG616nfHQeigqkA+PznS2YkssXwfcxMty+CMMNxQzZLnUvYCEbogCJPcAf6Nlm2iKB0zXl1f6wgdBcWSD0xDLpfDsccei3POOceb9ahBIHuFEIIvf/nLaG9vB23JojCzdlJi7jjZ4WGO1oVZ7PQErTZv3NzFLizRObPMFeEudlajW92gbz+H/eeql1dM5mwYWGE3asckY2V1G/rh6YNzbC/LOHOEH9cMhptqYEIXpFyFTe6cELb19jiCXFldSJrTq+SgM3PRf56ITZs2oa2tDV/60pc8nTmiGoGpdk9PD774xS8CAAqzh6G0jju+gDKPhFVpeWdl3geOX9E6bUG25bxEVZnWi5vohFjmjJS+L4/vTCTtFzrP726cFssNetoaC2yJHe+cenblzu9mV8cVObxeBnVehOUa1YhyZ2y+9SrSV0vQfOgKUL1qEo5ooM1+5Up7CrfccgsA4Morr8SMGTO8XKuqBLrFTj/9dJx//vkAAXIH7QeNcJ5eqBbmE8UsecYbrU/RukCTqtbDVsZ8LTpHi8liff0+YZkBwobMGeHaHEskQC4+3GIQGrvfxZIaQqdDKa3aHOs6Sld1verIXZjPRcCd0AVwgw4VjSh3RqxEz630cW7idwORSLgidDagkQJaj8mBUooLLrgAp512mscrVp3Az+zPfvazWLJkCRBVkVu0H9Th1EXM0TrzSW11chgFz+nJwtjE0ZD960wyZ8Tp9/G0v5mXOJQ5M1zFjrgUuyoRKsffy4bQGbGM2vkxGMogd6X1DXOzKy/8uHGHWZ7CvG5+ESK5D5XMAfaFDhSHXToDQ0NDWLp0KT796U97vGK1CXyPxuNxfOtb30IymYTankFh9pA/udTsXEjd/vrRm3rtro9+gwmz2JlRVUuZc0NDiZ1LmTPC9Xuzil2dJkfb39Gh0OkYxc6zKJ0VxkgvYx/Chm129UruGkGaGj1q1wRwlzm3ZdnsP6fzoR+ehJdffhnJZBJXX3014vG4u/pdErjUAcDChQtxxRVXAAAKc4ahdIxrb9iUO27ROi/Qxa7eo1EwJjIuRufqEepmZVY4ypyRQMXOwaCWmt+ZUeh0dLELopNxqf7i/44SLPuBl/3opnKz7FSUu4D3dV2ZC2D9nF5zlM4J/PrXvwYAXHHFFTjooIO8WC1HhOYMPuuss3DRRRcBAHKL+qEms5NvehW5C6tMhT1aV6WptRZN0wzrkcwZCUTsGAYFWH5/l0JXhiSB8Ogf6KjOyu+kyx13cQvjdIcAH7lrVEGainLnI7rIhaqZtYjT67mazEI6bBQA8OEPfxhnnXWWF6vlmNBIHQB88pOfxOrVq7X8dUv2gUbM/Wuqy13oo3VOYRU7L6GUe1NrLUIldj7InBFPxK6aILlICl22PTgLnf4/kX2SOxvb20ruwtqPztVoVzcCGbbrFgtC7rgSVpED2AaC0YiC6aeqyGQyWLNmDf7lX/7Fo7Vzju/ThNVjbGwMl19+Od5++21I4wnEts0BoTU2uKHtm/lGKMs+JYV0Pk1ZWKYQs9PMageW7+PL7CHVME475TOlU5Pnd6cqoBj2JadZPiilTFN/WaGdxxbniqpq8/Z6gZ83nDD0o+NYV/myobqd8CVsU5C5JczztrpZNwd1Wl7X6yUYJhTLL+3Aa6+9hnnz5uHnP/852tvbna6lZ4QqUgcA7e3tuPbaa9HW1ga1LYP8wv7aM04YonfMk7WLZtiaZfESOq04hjQvAQqdX5G5euvBDWNzLMdp24gsQYrHQWIx94VVu6h6FbUTQsdcV/myIb2O8qKZondTte9kkZrX9Rr3OwqKtVcuxWuvvYaWlhZce+21oRI6IISROp0XXngBX/7yl6EoCiL7OhDd221vweINobTD7F6wwxqtA4KJ2HmcZ67e9/EkSmWXAKNzQA3x9SJix0vs9Em3qTo57yoDVaN0ZnhF7fxuEvKhHx2z1LntsxfOW4l3BP1jzw1hnxGCdf1s1Gfrul7lGpSfN4jCrBHIsozvfe97WnexkBFaXT/mmGNw1VVXAQAKs0ZQmDHsaPlS3xe7I0zDGq3zC8NE2H70m6tVftl+8xOf+81ZUXO78xIQ/eYtS5My5gbjehHJXdTObioBPWoXjTivo1RGyIWOASF0PmK4ZjYUYRc6j3B7XS/MHEFh1ggA4Ctf+UoohQ4IsdQBwNlnn43LL78cAJCfP4hC53j9hUyh07KRa7UErxkHTdhZxiBxvs8CUbEqhv3kNyGQOVvb3u20YubjT5aAaIRd7qym8iGaLDqVO8fbXtKmRiPRiHO5awSh86vZVQidexpV8MKIB9Lp6rpOCArTJ5CfPwgA+Jd/+ZfQjHS1ItRSBwAXX3wxPvCBDwAA8ov2Q5mWYi6rquDpF0O/ZCJosdNFzseRrFYY6w5DdC4ImEWaRUqqHXeEsEXt6s3NaJK7uoLnIOFneT2kJHe2EEI3WQePNClezUkq4I8TYXJxfIQlSuf6hzohUKZNQD14AADwgQ98AB/96Ec5rZ03hF7qCCH49Kc/jVNPPVWbI3bxPijtdcTOZkLcCslTFKBQaN5fWz6nJLHDVI/OucLuhdPuxdlp1M7uDaIod2bBM4oel31gJ2onhI6pDlsIuWvc769fI4wPwP8BFRzrc3VNUVVN6NpToCsGoSgKzjjjDHz6058OfuBcHUI7UMJMoVDAN77xDTzzzDOAShD722zI48nqC7D+6oc2kq/s4GKZ+9VWRd4OmmiIXRvwyNYwwGU/VduOrDfveoMo6kXpnCARLaF1Lu982Wr7UJ8VIm/Im9cIQgd4L3V+JDFuhGsPb0JyPakKkZzve8ZzPJBUJgCf63rRHZT2DMgRg8hmszjxxBNxzTXXIBJx0YfXJxpG6gAgl8vha1/7GtatWwcoBLG/zYE8kai+AKPYWea7Mx9svESPo9g10K6cvOH5/Ysw4JGtxcrLn/Pqy2i+ufPoK6VHsI3wFDq9PJWCZrP1P2um3n6kFJRj6hbb+Ny/zbbY+TUrRam+BromuSXsUucUF+d4UPnpXF3XDb6gtmQgvWMY6XQaxx13HL7zne8gGo2yl+0jDSV1AJDNZvGVr3wFL730EqBIiG+bDSlVRezcROvsJDK2OgBZcmgxil3DolLrm4vXYhd0dK5W3TwHqVTbvqwY5c4LodNhidbZ2Z961M5PuQtLk2hZ8ZyPC9sVN9Qtho1mEzqgcaJ0hvqYr+8GV1BaM4gePYqJiQm8853vxHXXXYd4PM5WbgA0nNQBQCaTwZe+9CW8+uqrWsTurRpNsV6LXcVCDidRNy7nlEYTO3N0zgqvxC5IobNbr2EieVfVSZImibym7DLDc1YH4zHMEq1zsk/9krugRqHaqsLGOehZ5Q13q7GHEDrToj5KnakuphH0BpT2NKSVw8hkMli1ahWuv/56JJM1unmFkIaUOgBIp9P42te+pkXsVILYWzMhj7ZYn2A8m2FtLSgxyCBjBKRRxM5JlMCDSFAgQsdap4uoHZGkyeO9KC/c5E7fL/p+dCt3Vseuk2idi+0LeCB3Qc3kwFRdAHLXmLea+gipMyzmZqSpgzqr1ONG6pRpKeCwIeRyORxzzDH49re/jUSiRveukNKwUgdoTbHXXHMNnn76aYACse0zIQ+3am8ad67f0TpAiB1QfpPzqYNuGX5H58yjRt1Mr8YgdmVCZ0RR3Iud1f5wK3fVjlu7Yud23/KUuwYSuvKqfW6SbdzbjTVC6EyLehylq1G+K6HrnICybACKouDEE0/EN7/5TcR4THkYAA0tdYA2Kva73/0uHnnkEYAC0V09iAyY5mKzO/VQFZibYVmkTl/WKWESO143iiA7zTqlWhoQl2Kn/Vf/FK0qdDpuonb19oNxX9sVvHrHqx2x47V/3cpdgwrd5Cr4HLVr7FvOJM0odEA4o3S8pv8CKq6The5RKIuHoKoqzjjjDHz1q19tiFGu1Wh4qQMARVFwww034N577wUARPZ2ItLXCQLzCFY2uWuIaB0QDrHj+cu/EaTOTk43N2IH1IzaEf14tntcO43aOd0HdgTP7nFaT+x4719jMmy7gtfgQmdERO0c0oxSF0SUrla9Dsqse703XSMpKApzhlGYMwwAOPfcc3HllVdC5jF1YoA0hdQBWjTjF7/4BW655RYAgHygDdFdPdZip+NA8HwTu0aN1nl1Q3ApuJ6KndOTn3PUrm50rhp2o3Zum8CtjgdFdXacVhM7r2+odqJ3TSR0OiJqZ5NmFDogmCidVb0M5dW81lsIXX7hASg92tSj//AP/4CPf/zjocld6oamkTqdO++8Ez/84Q+hqiqkkSRi22eCqIYdWm2n2bg5imZYC/z6de9iW3hyorL+muMUtWMWOiP15M6LkcgscyxbiZ1fF99qcteEQgeY8t2JqJ01TXDjtyToKJ3Le5fldd7iGkklFUddPhvr1q2DJEn44he/iPe+972u6g4TTSd1APD000/jmmuuQTabBUnFEP/bLJC8oY3cYZh2cjGfm2H1ZZ3ih9gFkfPK5bbgInc8QvMcxM5tP9EyrOTO65yBqsP+a2ax8/vGamyazbsYdNIoQjf5oo8r0CC3IiF1psVcbg9OzZ3ERiscjRaw8ANJbNmyBfF4HFdffTXWrl3Lpf6w0JRSBwBvvPEGrrrqKgwPDwM5GfG3ZkFKGRIIOjkxDQfIlBe7oBKY6gTZHMtTpAD3cgfwXR9d7njmoTNTnD3CsdQBk2IX9E3VELWzva1CLHOAjRkpvF7/RrkNBX3seUWQI1453KtK1/Ua10O1JYPW47MYHBxER0cHrr/+ehx22GGu6w4bTSt1ALBnzx585StfwY4dOwCVILqzB5GhNu1NF5mnp9zAiaBFzkwQYscpRU4FPMQO4LdOqjo5MIP3vLz68aiXyyh2gMtomVuMl0zD/qsqeGE6d0w4mjfWq+/RiLegZpI7v4XOPK+6C+xE5wCgMH0cZPkIcrkcFi9ejGuvvRZz5851VXdYaWqpA4CJiQn8+7//O5599lkAQKSvA5G907UBFG7Fruw1m2X5OXACYD9pwiZyVvjVz45jQuuqhEHuVOv+blwEz3wcuhG74rEZmNhVu2RaCV6IzyFHQle+IMeVaJLbTyNLnh9Sx2F0a1lxdvvPgaIwdwiF2SMAgLVr1+Ib3/gGWlpamOptBJpe6gAt5cn/+3//rzQyVhpJIrZjBojqIheNldiVvV/lPb+bYWutixm9WSzMFyjj4cohWXNduWPsf8lEkGJXReiMuJI7q2OQpRnWoiO/73Jn55KpquVpaPycd7YOzDJXXoj7MoDmkbpahPl66rXQccg/V1ackxGusoJ3/Ms8PPfccwCASy65BJdddhkk3j/IQ8aUkDqdRx55BNdddx1yuRxIJoLY9pmQMi6mAakndpbLkPCIndVNVb/gSy4imV5Q7TDl0DxddR8yJrN0jd9yZ0PozDgSvGrHOku0rkpnfl/Fzua2qpvrLgDR4yJ0k4W5XH7K3Hrs4/c11wup4zA7REWRDq/FajKLrtMoent7EYvF8KUvfQlnnXWW7foamSkldQCwefNmfOMb30BfX5/Wz253N+TB9sp8dnZhETtgUu6sXq8Gq9jVSiNR6yIfFrGrd4jyFjsXzfJc4CV1OvXWi5NcWIpevQu3U7Grdrz6GbXjJXVGPM4Px1XmJgt1seyUuu3Yo5GFzqPBfE7vrVQiULrHQZaNIpfLYe7cufjWt76FQw45xPn6NShTTuoAYHR0FN/97ndL/ezkgTZEd/eAUFYxYBQ7oPLA9uBXDgB3zWZBip3dw5PTSGHCQ8x4lMFb7ADr9WKI0tnF9qXFrtjZOYb9itqxNMHW/Kx3Axa4C52QOf4EcY3lIXUuZ/2pWj7D9qCSivxBQ1C6tYTCxx9/PL72ta+hvb29zpLNxZSUOgBQVRW33norfvnLX0JVVZB0TGuOzTJM4utG6gD2kbR+EYTYsR6WLvrZEcLxe4Y1agdMrpuHQgc4kDrAXv86u3LiR9SOd7SuUaROCJ03NFKUjtc0Whb3Pdb7qJrIYd57k3jrrbcgSRIuu+wyXHzxxU3ff86KKSt1Oq+88gquueYaDA4Oas2xb3dDHmBojhVixwceh6NTsTPPE8vze4ZZ7nw49blF61jEhKraKNQAt10YpE5bJODBEVP7NlObBhC6suZWHvcdTknhKSiUGeMgy8aRy+Uwffp0fPOb38TRRx/tfh0blKmnsSbe8Y534Je//CVWr14NSNp8cLnF+0Blp6PyHDS1WC7PdtPyDZV6f2HmVT51kI7FLHSl5Tmti6qWP1jh+YuT5/fjhX6RlzhOpk30nJIcplTzGkdpjthuyq4y/wuh84Yw9Fm2QD9eKo4bjoEEQiyuvQ6gsoI1XzgI+YMGkcvlcOyxx+JXv/rVlBY6QETqSqiqij/+8Y+48cYbUSgUgLyM2M4ZkMcc5rMRETvneHUI1utnZyV01crggT69F+A+nxxr/QHguBkWKI/YuYkyGWd/0NeDR+TOy8EStgpm/w6+JhwWt5fqhKwfHZcUJXZXQ3ZXjtKewbS1Cg4cOIBoNIrLL78cH/zgB6dkc6sZIXUmtmzZgm9961vYtWsXACCyrwOR3unOBlEIsbOHX4eeVXOsHaEzl+EG83flMeWYEzkJ8DR3fIkxi52bJLkWy3KRuwaWOm1xe4NOXCNuL9aEROgcRW95RukYpY4SFYX5I1Bmj4FSioULF+L//J//M6VGt9ZDSJ0FmUwG//Vf/4W7774bAEAyUcR2zoCUspnTLgipAxpL7Pw+7Ixi51TozOU4pVaOPcB7uQvBKc4kdlQF3MxDW0eoXMmd7b6CHo2ABbwTOx4yp59relkhOAZDRUBS56oJntf9hfH6q7blMPPMCHbv3g0AOP/88/HpT38ayWSSz3o1CULqavDMM8/ge9/7njaIggKR/Q6idlNB7ABncmfOY8Zrblq7FMXObejf0QXZzunlpdyF6PR23Ayr51dkjdTZjJIxyZ2D7xLWaJ1WBDW/4K7AatefWrkypxpTWejgMEonSVp0bs4w1LljUFUVPT09+NKXvoTjjjuO2zo1E0Lq6jA6Oor/+3//Lx566CEAAElHEdvlIGoHuEtQzEKYxM58UzbeNFhm1nADIYAsu5NtY1n1cHpq8WiSBSblxKdTm1Jqa5sySZ22IFsUy+EyjuSrSaSuVBSPBNT1rjtC7BpT6Ipl8MKW1OkzQ7RmMefsGHbs2AEAOPvss/HZz352yuWec4KQOps89dRTuOGGG8qjdn3TQdR6F7Li5jWfzHZFr1HFzngjrnXz8UvsdKGTJL43lloy66Y8HgMpQiZ1+mfrYhS6yQUn37MDg6Q0nNQB3MSOWm1zJ9i93kzl5tiARrq6zivH+V5SU+qK1z0qU+TnDIHO1qJzXV1duOKKK3DiiSdyXZdmREidA0ZGRvCjH/0IjzzyCACAZCOIvt0DebTOCNl6fap0qoleo4idGbs3Ca/Fzih0RrySO1659gDncudxQmEzpanBHPSTqXvJqSUYdqN2Quocwyx2LNeZqRa1Cyp1SciidICF1BmvcYRAmZbC9OMp9u3bBwA444wz8LnPfQ4dHR1c16NZEVLHwHPPPYf//M//1OaPBSAPtSL6djdIIVJ9IafTXRmRXPQD81LsrJq43AooT7krypxWfLW+PiE//O3Knc/ROa0qg2A57Pxc9bJjRyzsiJ1DqdO+S4P1qQO456p0JHZury1TSeycSl21Fh5HdYZP6ACD1OnXtOJ3pJEC8vMHoEyfAADMnj0bV1xxBY499lju69DMCKljJJ1O46abbsLtt98ORVEARUJ0bxfkAzVmo3CzqauE0LXkqvVyrXE4MZ32UXIjdzzErlp0rhphPw1qyZ3P0TnAJHQ6PMTOrlTUao71uj+dsX4vym4EseN1TSn9HfLzLwhcRve4TOflhdRFi8EPXeZAofSMIX5oBuPj45BlGRdddBH+8R//UYxsZUBInUu2bNmC73//+3jzzTcBACQVQ2x3T/WBFG42N2NH+tKNlkWW3CR+DUrsnAqdTiOcCka5CyA6p1VXI1LmphmWpfnPal28bnrV6/Wq7IClTiuyyr7gLXMV7zXAOegHbptrXUbpqEq15b2Quli09LfSmsFB57Zi69atAIDly5fj3/7t30TeORcIqeOAoii488478ctf/hITE1roWB5oQ3Rvl3WTrFuxA5g70nMZ+emEIJpjJVmTC9bBBo1wShASyHrWFDqAPVrnpqO+eZ2E1HGhQuy8FrrSZxrg/POSAITOKmchl0ifBSQW1Zpa5w5C6R4HALS1teGf/umfcOGFF0L2qN6pgpA6jgwODuLnP/857r//fu0FhSDSNx2R/g4QajG/qBtcpr/wVe7c5kdylPXclGTYzShScWpUQO0kA2YRO7ejL/V9pShM0WUvpc7xvNAhmgfa0ZRi9Qtz+Pkpev752I+u2v71KkpHCYUyN4XYIRmkUikAwLnnnotPfOITmD59Ovf6piJC6jzgjTfewA9/+MPJJtlMFNE93ZBGk+X97aaS2AHeNsdWm+e1uFxTR+18wpbQ6ThthnUrdVpB4ZQ6lvKbSezE/LH28aEfnZ39yTtKR0GhdmYw58yW0hScK1aswOc//3kcdthhXOua6gip8whVVfHAAw/gxhtvxPDwMABAGktocpeOT35QiJ09ajXHWs3talGviNqxQxVVuznb/fXuVOrcJr81i6EDEXE88lWvz8nH/ZA6wJtBE+4K4LMiQPOfgx41uzrdh7yjdGpLDof//Vy88sorAICOjg5cfvnlOOeccyDxSLYuKENInceMjY3hlltuwR133IFcLgcAkAdaEdnTCakQ49M3aqqIHVAetasWnatTb9jlzkkyXz8oCR3g7GJvQ+y4R+nM2LihMc2m0ORSx6XZ1aPIYVPKHUehc7vveEXpaKyA/IIRqD1aM2ssFsNFF12Ej33sY2hra+NSh6ASIXU+0dfXh1/84hd4+OGHtRdUAnlfG6J9nSCK4UbJKhwcpphqGLkjEiBL7L8m3cidx6eL+XQMWu7KhE6Hk9hxEzqtsNrRvho3uqaSOsDV9gy1zFXU0yS3Lg5CxwseUToqqyjMHYW8KFsKZJx11lm47LLLMHv2bB6rKaiBkDqfefPNN/Hf//3fpVA0ChIie9sh97eDqNVmlLB5kjW72OlROjvNrTbrdiR2PkXprPB7v5T6z7lNa1FP6njMOepEDi2kpemkDmASq4YSuop6G/Q2xmUeap7zsrJH6aikQpk9jsShCsbHtVGtRx11FD71qU9hxYoVvFZRUAchdQFAKcVzzz2Hn/3sZ6WJipGXEOmdBnl/e8VI2YqbYi0R4TB3aCDRoWpyZ25u5T0iy27ULkChM+LHvrGMzlWsiDux8zVKZ4VBYEIpdYBvYtfQMleqvwFvY00idJRQKDPH0f4OgqGhIQDA4sWLcdlll+GEE04IvLVhqiGkLkAURcEjjzyCX/3qV9i7d6/2YlZGZG8H5IHWyjQoRaqeJKY59Bpa7HhH5WzWbSl3IRE6I17tH9vRM6f7xCB23IWOtSyVsg2S0Ot18vEQSh23dCVBC52ZMN/SeJ63Lq+LFYMqHJZHQaHMmEDXcVHs378fADBv3jz84z/+I04//XSRby4ghNSFgEKhgPvvvx//8z//g/7+fgAAyUQg906rKXdmLCN6jSR3en8OP2XOah1gkDufTg83pyGvfeRYthjFjluzK8AWpTMubk7TYkfwGPZVIFIHWO5LrrnnatQTGvy8xfl1vWS8NhLzD2cGKKFQeiYw84RkKRgxY8YM/MM//APOOeccRCI15kAXeI6QuhCRzWZx11134ZZbbimlQSFZWZO7A2225c4IqSV1NoXPU7Ez/5rzsqnVCbrc+dHcyekUZF3Xsvr1G76HYsctSgfwlzoj1QSvkaQOKG1rT2SuSl2hhsf5FmSTosNzjofIAUWZmzGO7uPi2LdvHwAtPcnf/d3f4YILLkA8Hq9TgsAPhNSFkFQqhbvuugu///3vMTg4qL2Yk7U+dwdaQVSHJ7Wd5trqC5c+60pwqoXiaw2UcJqyhDcOZ0ZgxYtTkHn+VcDbaB1VtZsqj+3KoRnXdkJlo+A1mtQBAFX9kbpiXaGFR/qooKlzzrltVjVDJRXKzAl0HC1jYGAAANDd3Y2PfvSjOP/885FMJl2VL+CLkLoQk81mcc899+B3v/tdqVkWeQmRvmmQ+9vKU6HYgFlQ9GZcuBgdJcsuUpgEI3dE9qc+r09Bq/1es06vonWqSWzc3iDdNuPqfeocLaP6J3UAV7FjXgemykIodk0qdLwlTofKKpRZ42g9AhgZGQEAzJw5Ex/72MdwzjnniMhcSBFS1wDkcjk88MAD+O1vf4u+vj7tRYVA7m9DZF87SM5+HwZXkaei3DGLnbHPHAt+Nsk2cJSOC7zFzix0peVcbONCgX1ZOIjSmWGQozBIna/ROkOdoaCJhM4ridOhcQWFWWNIHKxiYmICADB37lxccsklOPvssxGNRrnWJ+CLkLoGolAo4OGHH8bvfve7yVQoFJAGWhDpmwYpHbNVDg+xA1xE7dzInddRuwbsS2cb/YZud7s7bdqstU+qSR3AfsPM5V3NTsIsdfl85Wt1ujKEQuqAqSd2jd5/Tl8F47XWi2ufRKAmcyjMHgWZlYVSPF4XLlyIv/u7v8Ppp58uBkA0CELqGhBVVbFu3Trcdtttk0mMAUgjCch97ZBGEyCofyEKXO7C1iTrU3ROx7dTz+ombme784rW1RK60rIOt7uilkfMGI4jrlJnhS56qsq+rz0aqeq72BXr9be+JhI6L0SOqqCgUKfnocwehdqRLb21atUqfOQjH8Fxxx0n5mdtMITUNTibN2/Gbbfdhscff7z064qkopD3tUMebKk7qMK1xDRLk2yzCV29m7Zf0To7Qlda1sH2z1lFyxwsz9KfTseu1BkIldQBwYldsW7v62iC5lZwFjrDdtfSkqSw4Izp2L59OwBAlmWccsop+PCHPyxmgGhghNQ1Cb29vbj99ttx7733Ip1Oay8WJMj7WyEfaIeUrR465yV2QAM3yfrY7Ap4JHVOb9JeROuAyf3gROhKy9pYJ3OUzoyN78UcpQP8lTqgOcWuWD//MpsjOqdDIi77r5m2sRovQJk1gdYVEkZHRwEAyWQS559/Pj74wQ+KuVmbACF1TcbY2Bjuvfde3Hnnnejt7dVepIA0nIC8rw3SSLFp1uLGF3jUDgi+SdYHufPslPNC6ozlOr0Js37PetveKkpnRY3v52qQBMMMFKGTOmPUJkixm1wJDmU0mdCxROmskk2DQu3MQpk1DtqVKx2Ls2fPxvve9z6cd955aG9v57HKghAgpK5JURQFL7zwAv70pz9h3bp1pddJWoa8vx1yf2tlShQeTZBBR+2A0MtdaKQO8K4ZFnB3k6223etF6awwf0efm14BDvvc4ym9ghQ7IpHy+v08zspWhKWVQJ95hm/U0bbQ1aiXylp+uVnHt2PPnj2l19esWYP3ve99eNe73iWm8mpChNRNAXbv3o0777wTDzzwAMbHx7UXFQJpMIHI/laQsRgIKT+5iSxpUTPWuTGF3Fni6enmtdQBwYodi9AZKc5m4WofBCV1ALvY2dhnQUldRXoOWKxLrfX3IzpX4/pRElKOUldX6GqJHChoWw7KzBQiCxRks9rgh7a2NrznPe/BhRdeiAULFnBbV0H4EFI3hUin03j44Yfxpz/9CW+99VbpdZKOQN7fAvlAC0i+KGBFmSKEVJ8Nwo7w8WiSDbq/nb4OcCd3pblVXaThqAnrjTnMYgdM7kO7za51mDJS53A/+Sl2VjJXjZrrpc9QwoJk75pUa119ETo7Uh5VoPSkMPfETuzatav0+sEHH4z3ve99OOOMM8TMD1MEIXVTEEop3njjDdx777149NFHJwdWUEAaSkDe3wppOK71vSMSSDRiLXb1hE6XPh5RO6C+3Ln4xe1oHeBc7kqnmfkGxUvw3N6Qwy52qsvZI0qr4XI9GKWOS91A/f3sUjC8FjsnMmcX1nV2uy6eCZ3NMrW+chkoM1MgM/Kl7AeJRAKnnnoqzjvvPBxxxBG+juoXBI+QuilOKpXCo48+ivvuuw+vv/765BtZGXJ/C+QDSUjZuNYcK0nVo3ZWWEmfPoesmwuqLnasFyuOcgfYE7xSlM5mmY7xS+r0ulhuZiyXGr0uTrLRlFLnwShSL+TOC6ELAsr6w8YCEjMkjLf5o0VNFKDMmMD0oxI4cOBA6fXDDjsM5557Lk477TS0tra6XjdBYyKkTlDirbfewn333YcHH3ywNNwdAMh4FPKBFsgDrZBo1LncWVASOw793QKVO8N6VJO7qlE6G2XahsdN2OtoHeBc7MwC6fJ7urrcMY585VK3eT18gJfYNYvMAe6jc2USh8mWC6ooNfcrjShQetJQelKgbZM/LDo6OnD22Wfj3HPPxeLFi5nXS9A8CKkTVJDL5fDUU0/hwQcfxIsvvlgK62upUeKQB1ohj7WDSO7nAGxGudNWRfubSehqlFsVv6TOzSjF0nI217XaDZTxu7pLK+JykIbb+svWhW+zXy3ciF0zyRzgXOjMAgdYdz+pJnRUUqFOz0DpSYH0FErXYVmWsXr1apx77rlYu3atmItVUIaQOkFNhoaG8Oijj+Khhx7Cpk2bJt9QCOShFshD7ZBSrbamJatFU8mdcV0A/nnGrG6WvOqodiPmIXNG6l127NxAHX7nppE6wLdoHeBc7JpS5rQ/an6uWhSubvm53OTfoFA7slB6UogvxGR/ZwArVqzAWWedhdNOOw1dXV02114w1RBSJ7DN7t278dBDD+Ghhx6aTGwMAHkJ8kgr5JF2SONJV4IXCrkDvJlrsVGwyOsGgH90qNalx0lUxIZ0uM8TFzKp8zFap1NP7ppN5gDr6JxVBA5gGwRGFQVUKUCdloXanUb78hiGh4dL78+dOxdnnXUWzjzzTJGKRGALIXUCx1BKsXHjRjz00EN4/PHHMTIyMvlmQYI80gZ5uM2V4Am5c4jVDZ7nunslEFaXHxZhqSMcTSd1QCBiB1TKXTPKHKB9TxKtnF7R1Qh+vWxQqO1pKNPG0HZItOwa2tHRgdNOOw1nnXUWDjvsMDF6VeAIIXUCVxQKBbz66qt47LHH8OSTT1oL3kgrpLEWJsELjdwB4RY8pzd3l9nquWK8BLkRlRpi15RSB/jaDNvUGETN2B+Wh8DpUFIUuc4JtCwmGBsbK73X0dGBk046CSeffDKOPvpoRCLV5+oWCGohpE7AjUKhgNdee60keMZmBCgS5NEWSKOtkEdbQFRnF0uucqcVyF5OGOUugIgNV/TLEA9JMckdl0ucy5Gv3NbDTBDROqvjvxGOvxqCxlPejFBJhdKRgtqZRnIBJmf0ATB9+nScdNJJOOWUU3DUUUcJkRNwQUidwBN0wXv88cfx5JNPYmhoaPJNCkjjScijrZBGWiHl7Y/e4iJ3QPNF7xrhploPPZcfr+9SlLswROl0GjZax2Fiec+pI2ZeiZsZNZbXRq1OmwDpzE1mDwDQ1dWFk046CaeeeiqOPPJIMfeqgDtC6gSeoygKNm3ahKeffhrPPPMMdu7cWfY+Sccgj7ZBHm0FScVsNdOW+pmI6J1Go0sdryZYM27negXCL3VeRuv8Oq6par+uKn34/JI2M1SWQFuyUKZNQJk2AZrMlb2/cOFCrF27FmvXrsXhhx8uRE7gKULqBL6ze/duPPPMM3jmmWewYcMGqMZmrYIMeayl9CBKeZOE+XAti9y5TSPSyNG7Rpa6aoMlAPffi0dTbNilDuAvdh7kbqyJjTmRJ3/IBfgDSk8WHClAaUtDbU9h2tJIWUuELMtYuXIl1q5di+OPP16MWhX4ipA6QaCMjIzg+eefx9NPP40XXnihLC8TAEipOKSxFshjrZBSiepRPGPEzu1oPJ6jzfwQvGYTOiNhGDjBoT8dU71OcSueXuVpdElgMmeIqFFCobZkoE5LQWlLgbZkyz7a0tKCY489FmvXrsVxxx2HadOm+buuAkERIXWC0JDP5/H6669j3bp1eOGFF7B169byDygS5PGkJnjjSZBctFLyzM2xruaY5ZxKwAvBo6omRo2Y9sDJzBIA9zQnk6tRK18evyhd3brcwiLAvI/JRpQ5q1keQIF4AUpbCmp7CrHZasUPzmXLlmHNmjU45phjsHLlSjGzgyAUCKkThJaBgQG8+OKLeOGFF/Diiy+Wp0sBQHIRbcDFRAuk8WTlgIuwRu8AfjdTXeoqyg+55DE1g/JNSFyNiktio0TqAPvbKKRROcBjmbMQOL0+NZqH2paG0pqC2pYGjRXKPtfR0VGSuDVr1qC7u5v/+gkELhFSJ2gIFEXBli1b8MILL+Cll17C66+/jkKh/KJLstGS5MnjSZBCsT8ez+gdEC7BqyZ1lvWEQPRcD1qwGbXjODUbVRT3620sy2uqiV0jROUAPjJXZTCCsR41UoDaltL6xrWmQOPl1xNZlnH44YfjmGOOwbHHHotly5ZBCrI/n0BgAyF1goYkk8lgw4YNeOWVV/Dyyy9j8+bNZakDAIBkopAmkpBTSUgTCa25VpLCLXiAs5uvE6mrWp8H38GPiBRgLS+c59rlJmKU+iN1AP/5hnXCFJWrmXeuvDyqqqCxvNYvrjUNpS0NGs+bipOxfPlyvOMd78A73vEOrFy5Eslk0vl6CQQBIqRO0BRMTExg/fr1ePnll/Hyyy9j27ZtlU1deRnyRBJSKgFpIgkpmwAhhhtDowkeD6FrdMxyx1voKOXW9AoAUBRPm2DNU0pRPfefW4KSOQfiZoSCQk1mNIlrSUFpyQBR048+QnDIIYeUJO7II49Ea2ur7e8gEIQRIXWCpmR0dBSvvfYaNm7ciA0bNuDNN9+saK6FSkqCJ6cTkDKGFCphFDygXPKE1E2iNzmGNUpXKpB/tK5m06Wqlkukk+3jlcgBk+tZN2GwvQgelRWoyTSUYiQu2qUimy0foRqJRLB8+XIcccQROPLII7Fq1Sq0t7c7+g4CQdgRUieYEmSzWWzevBnr168viZ5x7kUdkotASicgpZPaI5MAgctkoX72ZZuqp7MHETvuUTqtUNdSVzHBu92mS7PgAZXbiZPIlSUCrhGVsyttRqikQk1kJiNxySxoLF/xuWnTpuGII47AEUccgZUrV2LFihWIx+OO6xMIGgkhdYIpiaqq2LVrV0nyNm3ahF27dlXe9ChAsnFI6QTkdLHJNhsHoS46TPs9YKHZT3ErgeMgd570f2OQOmaJq0dR8ryYiYEY5zF1IYqUUKjxbFHetAdpKZQnLC+yYMGCksAdccQRWLhwoRjYIJhyCKkTCIqMj49j8+bN2LRpE958801s2rQJ/f39lR/URS+TgKT/n0mAqJxujn5IXzOc9naEzTiQwoHgeRKl0wquKXUVAgfwT+3hlSTCNH2fQ6isQE1kDY8M5Ha1stsEgBkzZmDFihU49NBDceihh+KQQw4RTakCAYTUCQQ1OXDgQJnkbdmyBaOjo5afJfmIJncG2SN5iwTJLAjRm4Q1+mYeKVtrxgmvRqkapM4XgdPhnTKkrGhj2fWPUwqqjUQtyhvV/49VyhsAtLe3Y8WKFSWJW7FiBXp6enitvkDQVAipEwgcQCnF/v37sW3bNmzbtg1btmzBtm3b0Nvba72ASkByMU3ysnEtwpeNu5e9qdhPj3eajirpULhF6arJUz5f+30eeBiN04qvL3IleYvnQOM5TeKKf0Oy3pdz5szBwQcfjGXLlmHp0qVYtmwZZs2aZS3AAoGgAiF1AgEHxsbG8Le//Q1bt24tCd/OnTuRy+WsFzDLXi4GKRcDycXY++s1Y189r/KtVYNTyhFCSHXZUfhOPVassPy5B8JYTeQoUcvlLZ6HGs/WlLdYLIbFixeXxO3ggw/G0qVL0dbWxn29BYKphJA6gcAjFEVBb28vtm/fjh07dpQeNWUPWjNumeQZ/3Ya3WvkZltCJsv2Q+6czpvKikpBLfqJOcJniaNEBU0UoMYLoLGcJnExTeJotPp3icViOOigg7Bo0aKyx5w5cxAxDqYQCARcEFInEPiMUfZ27tyJHTt24O2338bu3bst06yUoNCabYsPKRcre04KEfvS12jNWV7LnV9Cp1eXL7ib3o23xEVk0EgBNJoDjeaL0lYo/U0SiuWIU522tjbMnz+/QuBmz54N2YPRtQKBwBohdQJBiBgZGSkJnvH/t99+G+l0uvbCuvQVZU/SRa8QKUkfVKm2+IVd9ryQO5+FrlStoqddKSaRrrbtHQocMUXAKCggqUVpK2j/x/JQo3lN2oriVu/3QDKZxPz587FgwQLMnz+/7NHR0SH6vQkEIUBInUDQAFBKMTAwgD179qCvrw99fX3o7e1Fb28v+vr6sH///oq5by1RyWRUzyB7ZQ9Fri5/Yblx10uia7ucAITOKnKlKM7m/IVB1mQFNKKARvKatMVU7e9IMdIWKQBS/e8pyzJmzpyJ2bNnY86cOZg1axZmz56NuXPnYv78+ejq6hLiJhCEHCF1AkETUCgUMDAwUCZ6+/btQ39/Pw4cOID+/n6Mj4/bL1Almtwpk6Kn/R8tvi6DKJL2uiIBquwuIbNbWCTPK6Gr19woWb9PiQpIiiZpkgrICqhcjKzpfxef6+9VG4hgRVtbG3p6etDT04OZM2dizpw5mD17dunR3d0t+rkJBA2OkDqBYIqQTqdx4MCBkuQZhW9gYADDw8MYGhpCKpViq0AXQXVS+KDKIKqkRf7K/pdBVGJ6LgGUlB6uUr5Uu6zpc8Q6xULUKIp1SKomYcUHlcnka2TyPe1/BVRSQOWitEnK5P8OBM1IMplER0cHuru7MWPGjJK49fT0lD1PJpNM5QsEgsZBSJ1AICgjk8mUBE//f3BwsPT30NAQxsfHMTY2hrGxMYyPj9fsRM+MahA8SgAqaeJoED+AQHMrTQCJ/rf5fxBoT4qXO2K47BX/psbXCQUIBS3+D0l/rpbe0x58vzIhBG1tbWhvb0dbWxs6Ozsxffp0dHZ2lv42Pu/s7BSyJhAISgipEwgErlBVFRMTE2WSp/89OjqKdDqNdDqNVCpV9+9GvRzJsoxkMll6JBKJsuf6o6WlpUzajP+3t7ejtbVVzFcqEAiYEVInEAhCAaUU+XweuVwOuVyu7G/j83w+j2w2i0JBm9hdLU5MrxQTB+uvqapa9pokSSCElP2vP8yvRyIRxGIxRKNRRKPRmn/rDzGIQCAQBI2QOoFAIBAIBIImQMT5BQKBQCAQCJoAIXUCgUAgEAgETYCQOoFAIBAIBIImQEidQCAQCAQCQRMgpE4gEAgEAoGgCRBSJxAIBAKBQNAECKkTCAQCgUAgaAKE1AkEAoFAIBA0AULqBAKBQCAQCJoAIXUCgUAgEAgETYCQOoFAIBAIBIImQEidQCAQCAQCQRMgpE4gEAgEAoGgCRBSJxAIBAKBQNAECKkTCAQCgUAgaAKE1AkEAoFAIBA0AULqBAKBQCAQCJoAIXUCgUAgEAgETYCQOoFAIBAIBIImQEidQCAQCAQCQRMgpE4gEAgEAoGgCRBSJxAIBAKBQNAECKkTCAQCgUAgaAKE1AkEAoFAIBA0AULqBAKBQCAQCJqASNArIBDoUEqRyWSCXg2BQCBwRCKRACEk6NUQCITUCcJDJpPB2WefHfRqCAQCgSMefPBBJJPJoFdDIBDNrwKBQCAQCATNgIjUCUJJ7IWZILT4m4NIIBIBiARIBCAERNLfK75OCCAREP0zpfdIaZnSAzC8JpW/ry1Yeo0SMvnTx1BG6XUyWZfxNUq0YkrvSVq52uuk9J6+DC2+VnofmCxDKn5efx/ldZQtU1x9Klm8V/Z5lK3j5Guk4r2KZWBcD9P7qPJ6lfKqrUfFMrXKLb1OK5c3LFN631AWLb4Ow3Lae9SwPtr7xPhe6bP6e7RUJjF+ntDSe6VDTH9dL674Ge1QoKXn+jJS8bn2nvZcX670HqEgmFxOKr5WeoCWlpMIyl7Xllcnl4P+eRWyvkzx+WRZaqk82VC+DO11WS+v9FkVsl4m9PVQJz+PybK1MlVI0OrX3tPKk4uvEaiQ9eUNy8iAthy0evTtoT/X6qLFv1F8j0IqbhcZBBIAubizJZDiawQyIZAggRT3XD4n4wP/PBsCQZgQUicIJwopXl6hSR2KAla8W06+RwBp0mCIZkjFQvS7u4SKu/akMZWbhF5mxV0epteMdcDiNfNymJQ5g9RVvGaQMONz8yqWf95iGanGe9W+RsV6VPnatd6rtqlYyzOUaSV8nkqd1fswP6elso3rYazT6r2SBMLwGePnK5ahFnXRsodR6iZFsfio9h508dOKNAqgLn+ALmcoSZHxPU3q1EkpIkYp0v6WCNGEq/g/Sn+T0nJaOSiWqS+L4nLF163eMywjF4VULq2nLnW0rtQZy5P17YHy1yQY19GwDwWCkCCaXwUCgUAgEAiaACF1AoFAIBAIBE2AkDqBQCAQCASCJkBInUAgEAgEAkETIKROIBAIBAKBoAkQUicQCAQCgUDQBAipEwgEAoFAIGgCRJ46QTiRKSjVEo5qedeI4X9iSgis/2/4G8bXqOFvG+8ZkpZNpoit9vrk/7Tsb5QtRwGA6q9PlklBAIrSssb3S2WUJVczrovFc1q2SqbtUeVh/qydXHS13rNdl833jFXWXI7WKZNWWcfqyYfLc8sZ3it9lj358OR6GPLUgT1PHcXkcpTQ8ge0/7X3UPa6SihA1MkyodelGvLpFT9TfJ8StVQeysov/q/XVXwuFT+j/w+g4jXVcFrrf6sEUDGZp04tvkZQLU8dKSUMljG5z/TnUnEZc+47+8mHCSaTD1udlwJBsAipE4SS3DH7g14Fb9DvmYyYnUQg0DEeWmqQK8KM0apFI5JAwII4cwQCgUAgEAiaAEIpFXOdCEIBpRSZTCbo1RDUIZPJ4IILLgAA3HXXXUgkEgGvkYAnYv86J5FIgBAROxcEj2h+FYQGQgiSyWTQqyFwQCKREPusiRH7VyBoLETzq0AgEAgEAkETIKROIBAIBAKBoAkQUicQCAQCgUDQBAipEwgEAoFAIGgCxOhXgUAgEAgEgiZAROoEAoFAIBAImgAhdQKBQCAQCARNgJA6gUAgEAgEgiZASJ1AIBAIBAJBEyCkTiAQCAQCgaAJEFInEAgEAoFA0AQIqRMIBAKBQCBoAoTUCQQCgUAgEDQBQuoEAoFAIBAImoBI0CsgEAjq88ADD+Daa6+t+7kf/OAHWL16teV7e/bswa233ooXX3wRg4ODSCaTOOSQQ3D++efjlFNOqVv25s2b8Yc//AGvvvoqhoeH0d7ejsMPPxzvf//78c53vrPu8i+//DLuuOMOvP766xgbG0NnZydWrVqFD33oQ1i+fHnd5Z944gncfffd2Lp1K1KpFLq6urBmzRp89KMfxfz58+suHySZTAavvvoqNm/ejC1btmDLli3Yt28fAODSSy/Fxz/+8bplDA4O4tZbb8Vzzz2Hffv2IR6PY/HixXj3u9+Nc889F4SQmsuL/S8QND9imjCBoAHQpU6SJHR2dlb93DXXXIOjjjqq4vXnnnsO3/zmN5HJZAAAra2tSKfTUFUVAHDOOefgy1/+clUxuPfee3HDDTdAURQAQFtbGyYmJqBfPuqJyU033YSbb74ZAEAIQWtrK8bHxwEAsizjiiuuwHnnnWe5LKUU119/Pe6//34AgCRJSCaTmJiYAAAkEglcc801eNe73lW1/qB55ZVX8LnPfc7yPTtSt3nzZlx55ZUYGRkBACSTSeRyudL+OOaYY3DttdciGo1aLi/2v0AwNRCROoGggZg5cyb+8Ic/OFpm7969uPrqq5HJZLBy5UpcddVVWLBgAVKpFG677TbcfPPNuP/++7Fw4UJcfPHFFctv3LixdEM/8cQT8bnPfQ4zZ87EyMgIfvGLX+Duu+/GzTffjEWLFuG0006rWP7RRx8t3dDf+9734p//+Z/R0dGB/fv340c/+hGeeuop3HDDDVi0aBGOOOKIiuV/97vflW7ol156KT7ykY+gpaUFu3btwnXXXYeNGzfi6quvxq9+9SvMnTvX0bbxk/b2dhxyyCGlx49//GMMDg7WXW58fBxf/vKXMTIygoULF+LrX/86VqxYgXw+j3vuuQf/9V//hRdeeAE//vGP8cUvfrFiebH/BYKpg+hTJxA0OTfddBPS6TS6urpw3XXXYcGCBQCAlpYWfPzjH8f5558PAPjNb36DsbGxiuV/9rOfQVEULFmyBNdccw1mzpwJAOjo6MCVV16JY445puxzRhRFwc9+9jMAwLHHHosrr7wSHR0dADRBvfrqq7F48eKyzxkZGxvDr3/9awCaEHz84x9HS0sLAGDhwoW4/vrr0dXVhXQ6jZtuusn1tvKKI488Evfddx/+8z//E5/85Cdx+umnIxaL2Vr2tttuw+DgIOLxOP7jP/4DK1asAABEo1G8//3vL0XI7rnnHuzevbtiebH/BYKpg5A6gaCJSafTeOKJJwAAF154Idrb2ys+c8kllwAAJiYm8NRTT5W9t3fvXqxfvx4A8JGPfASRSGVwX1++r68Pr732Wtl7r776Kvr6+gAAH/vYxyqWjUaj+MhHPgIAWL9+Pfbu3Vv2/pNPPolUKlVWj5H29nZccMEFALQ+V+l0uuIzYUCWZeZlH3zwQQDA6aefbhmJev/7349kMglFUfDwww+XvSf2v0AwtRBSJxA0MRs2bEA2mwWgRUqsmDNnDg466CAAwIsvvlj2nvF5teVXrlxZip6Yl3/ppZcAaFGhlStXWi5/3HHHWdZnXH7RokWYPXu25fL6emWzWWzYsMHyM43Krl27SgMqqm3/lpYWHHnkkQAqt5/Y/wLB1EJInUDQQAwPD+Oyyy7D2WefjTPOOAMf/vCH8e///u945ZVXLD//1ltvlf5esmRJ1XL197Zv3172uv58+vTpmD59uuWysixj4cKFNZc/6KCDqkarpk+fXhr8sWPHDsv1X7x4cd11t6q/0THuPzvboNr2M36m1vJi/wsEjY2QOoGggchkMtiyZQsikQgopejt7cXDDz+Mz33uc7juuutQKBTKPn/gwAEAWjNVPB6vWm5PTw8AYGBgwHJ5/f1qzJgxg8vy+ud19PL0961IJBJoa2uzXL7RMW7PWttA374TExOl5kpA7H+BYKohRr8KBA1Ad3c3Lr30Upx88slYsGABYrEYFEXBG2+8gV/96ld46aWXcP/99yORSODzn/98aTm9j1EikahZvv6+UQiMz+strwuDV8vXEhK9/PHx8YrlGx3j96m1DYzbN5VKlZpDxf4XCKYWIlInEDQAxxxzDD7+8Y9j6dKlpVGTsixj5cqV+P73v48TTjgBAHDnnXdajoAUCAQCQfMjpE4gaHAkScK//uu/AgBUVcWzzz5bei+ZTAJAKelsNfT39QiPjv683vJ6Z3yvltffr0a19W90jN+n1jYwbl/jMmL/CwRTCyF1AkETMH/+/FL+L2NaCL0v09jYWM0bo94Xqbu7u+x1ffl6fZX6+/u5LG/ue6WXp79vRSaTKc1OUK/vVqNh3J61toG+fVtbW8vERux/gWBqIaROIGhijCMDjSMhzVQbZag/HxoawvDwsOWyiqJg165dNZffuXNnRWJaHWPZixYtslz/WqMa7Y4QbUTsjuzUt0G17Wf8TK3lxf4XCBobIXUCQROwZ8+e0rygc+bMKb2+cuXKUifzF154wXLZvr4+7Ny5EwCwZs2asveMz9etW2e5/IYNG0od1M3Lr169GoDW4X3jxo2WyxvLrbb8zp07S/nazOjfKx6PV82F1qgsWLAAs2bNAlB9+6fT6VKCYPP2E/tfIJhaCKkTCEKOPml6rfd/+tOfAtD61x1//PGl95LJJE4++WQA2iAKvZnKyK233gpA64904oknlr03d+7cUmLb3//+9xUpUwDgt7/9LQBg9uzZOOqoo8reW7VqVSlprP45I4VCAb///e8BaFNpmWdMOOmkk9DS0gJKqeXyY2NjuOuuuwAAJ598cqkPWbNACMHZZ58NQJtDtbe3t+Izf/7zn5FOpyHLMs4888yy98T+FwimFkLqBIKQ09fXh0984hO46667sHfv3pLkqaqK119/Hf/2b/9Wmt7pve/9/+3dvUsrSwDG4dezsLiagATsrASxULCQFHaWIX4UFkabIDamNxC1MVZiYf4DJVXARlSCtZUKYmGRIhgrEUFIWLLIagQ9hdzBc67XFLc4Muf3wBY7zLALU+zL7HxMm41g/7G4uCjP81Sv17WysmJWx4ZhqGKxaD6K6XT602OklpaW5DiOarWa8vm8md/UbDZVKBTMSEsmk/nXBrOO4yiTyUiSzs/PVSgU1Gw2Jb3Pk8rn87q5ufml3kfRaFTpdFqSdHh4qGKxaLbpuL291erqqur1ujzPM2egfldBEMj3fXO9vr5Kel8E8LH892055ubmFIvF9PT0pFwup2q1Kkl6eXnRwcGBdnZ2JElTU1PmXNeP6H/g79Hx1m4YAMAfdX9/r1QqZe5d15XneQrDUK1Wy5Qnk0lls9lPz+c8OzvT+vq6WSUYiUQUhqGZ55RMJpXL5dTR0fHpO5TLZW1vb5v6kUhEj4+PJmAuLCx8+VHd3d1VsViU9D761N3dbUaNHMfR8vKyJicnP2379vamra0tHR8fm/qe55n2nZ2d2tjY0NjY2H8+/zuYnZ0156B+JZFIaG1t7ZeyarWqbDZrfrF3dXWp1WqZkbN4PK7NzU2z3c3v6H/g70CoA7655+dnlctlVSoV1Wo1+b6vIAjkuq56e3s1PDysiYmJtvOJ7u7uVCqVdHFxoUajIc/zNDAwoOnpaY2Pj7d9j2q1qr29PV1dXcn3fUWjUQ0NDWlmZkajo6Nt219eXmp/f1+VSkVBEKinp0cjIyNKpVIaHBxs2/7k5ERHR0e6vr5WGIaKxWKKx+Oan59XX19f2/Z/2v8JdZLUaDRUKpV0enqqh4cHua6r/v5+JRIJJZNJ/fjx9Y8X+h+wH6EOAADAAsypAwAAsAChDgAAwAKEOgAAAAsQ6gAAACxAqAMAALAAoQ4AAMAChDoAAAALEOoAAAAsQKgDAACwAKEOAADAAoQ6AAAACxDqAAAALECoAwAAsAChDgAAwAKEOgAAAAsQ6gAAACxAqAMAALAAoQ4AAMACPwGAQuvaG7D/PAAAAABJRU5ErkJggg==\n", 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", 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\n", + "image/png": 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", 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" ] @@ -955,7 +2185,7 @@ "outputs": [ { "data": { - "image/png": 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++9//au3atbp+/bpq1KihiIgIjR8/3h5sfH191bFjR+3bt0+xsbHKzc1VcHCwxo0bp6FDh8rNrVKc7AIAAOWgUgSgqKioIm9hz+Pn56dnn322nCoCAACVWaUIQABgtJQLRd88URFV9/OUr9nb2WUAVQYBCIBLqe7nKQ8vd21/+7CzSykRDy93DXylCyEIMAgBCIBL8TV7a+ArXWRJzXR2KcWWciFN298+LEtqJgEIMAgBCIDL8TV7EyQAF8etUQAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuh5ehospKS8qodG/8BgCUDwIQqqS0pAyt+cvXyrbmOLuUEvHwcld1P09nlwEAVR4BCFWSJTVT2dYcdX/ibgUG+zq7nGKr7ucpX7O3s8sAgCqPAIQqLTDYV+ZGAc4uAwBQwbAIGgAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDL4W3wAFBJpFxIc3YJJVLdz1O+Zm9nlwEUigAEABVcdT9PeXi5a/vbh51dSol4eLlr4CtdCEGokCpFAPrxxx/1/vvv6+TJk7p69aqqV6+u0NBQDRs2TJ06dcrX9+zZs1q4cKHi4+Pl4eGhDh06aOLEiQoMDHRO8QBQSr5mbw18pYssqZnOLqXYUi6kafvbh2VJzSQAoUKqFAEoMTFR6enp6tOnj8xmsywWi+Li4jRjxgw9/fTTio6OliRdvnxZkyZNkq+vr8aOHauMjAytXLlSP/zwgxYvXqxq1ao5+ZsAgGN8zd4ECcBAlSIAdejQQR06dMjX9oc//EFjx47V6tWr7QFoxYoVslgseu+991SnTh1JUvPmzRUTE6ONGzfa+wEAANdWae8Cc3d3V+3atZWW9r9FgXFxcerYsaM9/EjSfffdp5CQEG3bts0ZZQIAgAqoUpwBypORkSGr1aqbN29q586d2rNnj3r06CFJunLliq5du6aIiIgC+zVv3ly7d+8uctykpCQlJyfbPyckJBhfPAAAqDAqVQB66623tG7dOkmSm5ubunbtqqlTp0qSPcAEBQUV2C8oKEg3btxQZmamPD09C2xft26dli5dWnaFAwCACqVSBaBBgwape/fuSkpK0rZt25STk6OsrCxJktVqlaRCFzrnhR6r1VpoAIqOjs53N1lCQoJmz55dFl8BAABUAJUqAIWGhio0NFSS1KdPH8XExGj69OlavHixvLy8JMkeiH4pM/PWraN5fX7NbDbLbDaXUdUAAKCiqbSLoCWpe/fuOnHihM6fP2+/9PXLtTx5kpOT5e/vX+jZHwAA4HoqdQDKu+yVlpamWrVqKTAwUCdPnizQ7/jx4woPDy/v8gAAQAVVKQLQtWvXCrRlZ2dr06ZN8vLyUlhYmCSpW7du2rVrly5dumTvd+DAAZ0/f95+txgAAEClWAP06quv6ubNm2rdurVq1aql5ORkbdmyRefOndOECRNUo0YNSdKIESO0fft2TZkyRQMHDlRGRoY++ugjNW7cWH379nXytwAAABVFpQhAPXv21H//+1+tXbtW169fV40aNRQREaHx48erc+fO9n516tTRggULtHDhQi1evNj+LrAJEyaw/gcAANhVigAUFRWlqKioYvVt1KiRXnvttTKuCAAAVGaVYg0QAACAkQhAAADA5RCAAACAyyEAAQAAl+PQIughQ4aUeuJBgwZp4MCBpR4HAACgpBwKQImJifLx8ZGvr69Dk16+fFlpaWkO7QsAAFBaDt8GP3jwYI0aNcqhfbt16+botAAAAKXGGiAAAOByHDoDtHz5cgUEBDg8aWn3BwAAKA2HAlDDhg1LNWlp9wcAACgNLoEBAACXQwACAAAup8QBKDc3Vz/88IOSkpIKbMvOztahQ4eMqAsAAKDMlGgNUGJioqZNm6aEhASZTCa1b99eM2bMsC9ovnHjhqZMmaLt27eXRa0AAACGKNEZoEWLFslsNmvlypVasmSJrFarJkyYkO9skM1mM7xIAAAAI5UoAH333Xd64oknVK9ePTVt2lSvvfaa7r77bk2cOFGXLl2SJJlMpjIpFAAAwCglCkAWi0XVqlX7385ubpo2bZratGmjSZMm6cKFC4YXCAAAYLQSBaCGDRvq5MmTBdqfeuoptW/fXtOnTzesMAAAgLJSogDUtWtXbdmypdBtMTExioqKYg0QAACo8EoUgEaMGKFXXnmlyO0xMTGKi4srdVEAAABliQchAgAAl+PQu8AK8+2332rv3r1KT09XnTp1FB4ermbNmqlu3bpGTQEAAGAIQwLQBx98oCVLluRb/5N3O7yvr689DDVr1ky9evUyYkoAAACHGRKAPv/8c/n4+Gj69Olq0qSJEhMTdfr0aZ06dUqnTp3S4cOHdfDgQZlMJgIQAABwOkMC0I0bN9SvXz916dJFklS/fn3de++99u1ZWVn64YcfdOrUKSOmAwAAKBVDAlB4eLgsFkuR26tVq6aIiAhFREQYMR0AAECpGHIX2KBBg7Rr1y5dv37diOEAAADKlCEBqHv37oqKitL06dN15coVI4YEAAAoM4bdBl+/fn1t3LhRI0aMUPv27XXvvfeqadOmCg8Pl6enp1HTAAAAlJohAWjRokVatWqV/Tb47du3a/v27TKZTHJzc1PDhg3VrFkzRUREaMCAAUZMCQAA4DBDAtCmTZsUGBioF154QU2aNNGVK1d06tQpff/99/Zb4Tdt2qTNmzcTgAAAgNMZEoAsFosefvhhtWzZUpIUEhKikJAQ9ezZ097n0qVL3AYPAAAqBEMCUEREhFJSUm7bp06dOqpTp44R0wEAKomUC2nOLqHEqvt5ytfs7ewyUMYMCUAjRozQ888/r8uXL6t27dpGDAkAqMSq+3nKw8td298+7OxSSszDy10DX+lCCKriDAlACQkJioyM1NNPP61Zs2apUaNGRgxrd/z4ccXGxurgwYNKTEyUv7+/WrZsqTFjxigkJMTe78UXX1RsbGyB/Rs2bKgVK1YYWhMAoGi+Zm8NfKWLLKmZzi6lRFIupGn724dlSc0kAFVxhgSgN998UyaTSTabTX/+85/VsmVL3XvvvfYXoJb2rNCHH36o+Ph49ejRQ02aNFFycrI+++wzjRkzRosWLVLjxo3tfT09PTVt2rR8+/v4+JRqfgBAyfmavQkRqLAMCUCzZs3SqVOn7C9AjY+PV3x8vP2N8AEBAWratKkiIiI0duzYEo8/ePBg/f3vf1e1atXsbT179tTo0aP1wQcf6LnnnrO3u7u7q3fv3qX/UgAAoMoyJAB1795d3bt3t39OSUmx3/6eF4oOHDig/fv3OxSAWrVqVaAtJCREYWFhSkhIKLAtJydHFouFMz8AAKBQhj0J+pcCAwPVpk0btWnTxt5mtVp15swZw+aw2Wy6du2awsLC8rVbLBb17dtXFotFfn5+ioqK0vjx41WjRg3D5gYAAJWbIQHoxx9/1JUrV9SqVSt5exd+vdfLy0stWrQwYjpJ0pYtW3TlyhX9+c9/trcFBQVp2LBhatasmWw2m/bs2aPPP/9cZ86c0fz58+XhUfjXTUpKUnJysv1zYWeVAABA1WFIAFq+fLl27NihlStXFhmAjJSQkKB58+apZcuW6tOnj739sccey9cvKipKISEhWrJkieLi4hQVFVXoeOvWrdPSpUvLsmQAAFCBGPI2+CNHjqhdu3Yym82Fbj9//ryeffZZxcfHl3qu5ORkPfPMM/Lx8dE///lPubu737b/4MGD5ebmpv379xfZJzo6WkuWLLH/PPvss6WuEwAAVFyGnAG6evVqvufx/FpISIjOnj2rNWvWFLqgubjS0tI0bdo0paWlaeHChUUGrl/y8vKSv7+/bty4UWQfs9lcrLEAAEDVYMgZIB8fH6Wnp9+2z1133aVjx445PIfVatX06dN1/vx5zZ07t8Di56Kkp6fr+vXrCgwMdHhuAABQtRgSgO68807t3r1bubm5RfYJDAzUtWvXHBo/JydHM2fO1NGjRzVr1izdddddBfpYrdZCQ9iyZctks9nUrl07h+YGAABVjyGXwB566CE9++yzWrhwoZ588slC+1y8eFGenp4Ojf/WW29p586d6tixo1JTU7V58+Z823v37q2rV6/q0UcfVa9evdSwYUNJ0t69e7V79261a9dOnTt3dmhuAABQ9RgSgLp06aIePXrok08+0YULF/TYY4/lez3FgQMH9M033ygyMtKh8U+fPi1J2rVrl3bt2lVge+/eveXr66uOHTtq3759io2NVW5uroKDgzVu3DgNHTpUbm6GnOwCAABVgGEPQnzuuefk6+ur9evXa8+ePapbt67q1q2ra9eu6dy5c7LZbBo2bJhDYy9YsOA3+/j5+XH3FgAAKBbDApC7u7uefvpp3X///fr444+1f/9+/fzzz5Kk+vXra9y4cfmeDA0AAOAshr8Ko3Xr1mrdurWkW7et22w2+fn5GT0NAACAw8rkXWB5fH19y3J4AAAAh7AyGAAAuByHAtA//vEPxcXFOTxpafcHAAAoDYcC0NatW/Xjjz86PGlp9wcAACgNh9cAnTp1SrGxsUbWAgAAUC4cDkDffPONdu7cWeL9bDabo1MCAAAYwqEANH369FJP3LRp01KPAQAA4AiHAlDfvn2NrgMAAKDccBs8AABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXI7DT4IuSk5Ojq5fv66srKxCt9epU8foKQEAAErEsAB08uRJvfvuu/ruu++UnZ1daB+TyaRt27YZNSUAAIBDDAlAp06d0sSJE+Xu7q42bdpo165dCg8PV82aNfX9998rJSVFkZGRqlu3rhHTAQAAlIohAWjZsmWSpHfeeUdhYWHq1q2bunTpolGjRslqteqtt97S9u3bDXmHGAAAQGkZsgg6Pj5enTp1UlhYmL0t763vXl5emjJlisxms5YsWWLEdAAAAKViSAC6efOm6tevb//s4eGhjIyM/03i5qbIyEgdOHDAiOkAAABKxZAAFBgYqNTUVPvnmjVr6qeffsrXJzMzUxaLxYjpAAAASsWQABQWFqZz587ZP7dq1Ur79u3TkSNHJElnz57Vtm3bFBoaasR0AAAApWLIIugOHTpo4cKFSkpKktls1vDhw7Vjxw5NnDhRfn5+SktLU25urkaMGGHEdAAAAKViSAD63e9+px49esjPz0+SFB4ernnz5mn58uW6ePGiIiIiNGDAAHXo0MGI6QAAAErFkADk4eGhmjVr5mtr1aqVXn75ZSOGBwAAMBTvAgMAAC7HsFdhZGdn69NPP9WXX36pc+fOyWq12l97cerUKa1fv16DBg1SSEiIUVMCAFAmUi6kObuEEqnu5ylfs7ezy6hUDAlAVqtVTz31lI4cOaKAgAD5+Pjku+W9Xr162rBhg/z8/DR27FgjpgQAwHDV/Tzl4eWu7W8fdnYpJeLh5a6Br3QhBJWAIQFo+fLlio+P12OPPaZhw4bp/fff13/+8x/7dl9fX0VGRmrfvn0EIABAheVr9tbAV7rIkprp7FKKLeVCmra/fViW1EwCUAkYEoC++uor3XPPPRo+fLikW299/7X69evr1KlTRkwHAECZ8TV7EyRcgCGLoC9fvqyIiIjb9vH29tbNmzeNmA4AAKBUDDkD5O3trZSUlNv2uXjxogICAoyYDk6QlpRR6U4JAwBQFEMCUMuWLbVr1y6lpqbaH4b4S5cuXdLu3bvVpUsXh8Y/fvy4YmNjdfDgQSUmJsrf318tW7bUmDFjCtxVdvbsWS1cuFDx8fHy8PBQhw4dNHHiRAUGBjo0N26FnzV/+VrZ1hxnl1IiHl7uqu7n6ewyAAAVkCEBaOjQoZoyZYqmTp2qyZMnKyfn1l+UFotFR48e1RtvvKGcnBwNGTLEofE//PBDxcfHq0ePHmrSpImSk5P12WefacyYMVq0aJEaN24s6daluEmTJsnX11djx45VRkaGVq5cqR9++EGLFy9WtWrVjPi6LseSmqlsa466P3G3AoN9nV1OsXFbKACgKIYEoMjISE2ZMkULFizQpEmT7O19+vSRJLm5uSkmJuY31wkVZfDgwfr73/+eL8D07NlTo0eP1gcffKDnnntOkrRixQpZLBa99957qlOnjiSpefPmiomJ0caNGxUdHe3oV4SkwGBfmRtxGRMAUPkZ9iDE/v37KzIyUmvXrtXx48d148YN+fj4qHnz5vr973+vRo0aOTx2q1atCrSFhIQoLCxMCQkJ9ra4uDh17NjRHn4k6b777lNISIi2bdtGAAIAAJIMDECSFBYWpsmTJxs5ZJFsNpuuXbumsLAwSdKVK1d07dq1Qs8yNW/eXLt37y6XugAAQMVnyG3w3bt31z/+8Q8jhiq2LVu26MqVK+rZs6ckKTk5WZIUFBRUoG9QUJBu3LihzMzC72JKSkrSyZMn7T+/PKsEAACqHkPOANWoUUO1a9c2YqhiSUhI0Lx589SyZUv7OiOr1SpJhS509vT0tPfJ+/MvrVu3TkuXLi27ggEAQIViSABq3ry5zpw5Y8RQvyk5OVnPPPOMfHx89M9//lPu7u6SJC8vL0lSVlZWgX3yzvzk9fm16OhoderUyf45ISFBs2fPNrp0AABQQRgSgEaPHq3JkycrNjbWfkamLKSlpWnatGlKS0vTwoULZTab7dvyLn3lXQr7peTkZPn7+xd69keSzGZzvrEAAEDVZkgA2r9/vyIjIzV37lx9+umnuvPOO3XHHXcUeCeYyWTSyJEjHZrDarVq+vTpOn/+vF5//XX74uc8tWrVUmBgoE6ePFlg3+PHjys8PNyheQEAQNVjSAB6//337X/OW0hcGEcDUE5OjmbOnKmjR4/qxRdf1F133VVov27duik2NlaXLl2y3wp/4MABnT9/XoMHDy7xvAAAoGoyJADNnz/fiGGK9NZbb2nnzp3q2LGjUlNTtXnz5nzbe/fuLUkaMWKEtm/frilTpmjgwIHKyMjQRx99pMaNG6tv375lWiMAAKg8DHsSdFk6ffq0JGnXrl3atWtXge15AahOnTpasGCBFi5cqMWLF9vfBTZhwoQi1/8AAADXY+iDEMvKggULit23UaNGeu2118qwGgAAUNkZHoBycnJ0/fr1Qm9Hl5TvNRUAAADOYFgAOnnypN5991199913ys7OLrSPyWTStm3bjJoSAADAIYYEoFOnTmnixIlyd3dXmzZttGvXLoWHh6tmzZr6/vvvlZKSosjISNWtW9eI6QAAAErFkAC0bNkySdI777yjsLAwdevWTV26dNGoUaNktVr11ltvafv27Zo+fboR0wEAAJSKIS9DjY+PV6dOnfI9nNBms0m69fqJKVOmyGw2a8mSJUZMBwAAUCqGBKCbN2+qfv369s8eHh7KyMj43yRuboqMjNSBAweMmA4AAKBUDAlAgYGBSk1NtX+uWbOmfvrpp3x9MjMzZbFYjJgOAACgVAwJQGFhYTp37pz9c6tWrbRv3z4dOXJEknT27Flt27ZNoaGhRkwHAABQKoYsgu7QoYMWLlyopKQkmc1mDR8+XDt27NDEiRPl5+entLQ05ebmasSIEUZMBwAAUCqGBKDf/e536tGjh/z8/CRJ4eHhmjdvnpYvX66LFy8qIiJCAwYMUIcOHYyYDgAAoFQMCUAeHh6qWbNmvrZWrVrp5ZdfNmJ4AAAAQxmyBggAAKAyIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcgx5DpAkZWdn69NPP9WXX36pc+fOyWq1atu2bZKkU6dOaf369Ro0aJBCQkKMmhIAAMAhhgQgq9Wqp556SkeOHFFAQIB8fHzyvfi0Xr162rBhg/z8/DR27FgjpgQAAHCYIZfAli9frvj4eI0bN06ff/65HnzwwXzbfX19FRkZqX379hkxHQAAQKkYEoC++uor3XPPPRo+fLhMJpNMJlOBPvXr19elS5eMmA4AAKBUDAlAly9fVkRExG37eHt76+bNm0ZMBwAAUCqGBCBvb2+lpKTcts/FixcVEBBgxHQAAAClYkgAatmypXbt2qXU1NRCt1+6dEm7d+9W69atjZgOAACgVAwJQEOHDlVqaqqmTp2q+Ph45eTkSJIsFosOHDigp59+Wjk5ORoyZIgR0wEAAJSKIbfBR0ZGasqUKVqwYIEmTZpkb+/Tp48kyc3NTTExMb+5TggAAKA8GPYgxP79+ysyMlJr167V8ePHdePGDfn4+Kh58+b6/e9/r0aNGhk1FQAAQKkYFoAkKSwsTJMnTzZySAAAAMPxLjAAAOByDAlAEydO1Pr164u8CwwAAKAiMeQS2NGjR3XkyBHNnz9fHTp0UO/evdWhQwd5eBh6hQ0AAMAQhiSUzz77TFu2bNHmzZu1Y8cOff311/Lz81OPHj10//33q1WrVkZMAwAAipByIc3ZJZRIdT9P+Zq9nTa/IQEoMDBQgwYN0qBBg5SQkKDNmzdry5YtWrt2rdatW6d69eqpd+/euv/++9WgQQMjpgQAALoVJDy83LX97cPOLqVEPLzcNfCVLk4LQYZfowoNDdXYsWM1duxYHTp0SJs3b9b27du1bNky/ec//9G2bduMnhIAAJfla/bWwFe6yJKa6exSii3lQpq2v31YltTMqhOAfikyMlK1a9dWQECAVq9ebX9CdEmlp6dr5cqVOnbsmI4fP67U1FTNmDFDffv2zdfvxRdfVGxsbIH9GzZsqBUrVjg0NwAAFZ2v2dupl5MqozIJQDdu3NBXX32lzZs369ixY5KkGjVqqEePHg6Nd/36dS1dulR16tRReHi4Dh48WGRfT09PTZs2LV+bj4+PQ/MCAICqybAAlJWVpZ07d2rz5s3au3evsrKy5OHhoQ4dOuiBBx5Qx44d5enp6dDYQUFB+uyzzxQUFKQTJ05o3LhxRfZ1d3dX7969Hf0aAADABRgSgF566SXFxcUpPT1dNptNzZs3V+/evRUVFaWAgIBSj+/p6amgoKBi98/JyZHFYuHMDwAAKJQhAWjDhg2qW7euBgwYoN69eyskJMSIYR1isVjUt29fWSwW+fn5KSoqSuPHj1eNGjWcVhMAAKhYDAlAb775pu6++24jhiqVoKAgDRs2TM2aNZPNZtOePXv0+eef68yZM5o/f36RD2ZMSkpScnKy/XNCQkJ5lQwAAJzAkABUEcKPJD322GP5PkdFRSkkJERLlixRXFycoqKiCt1v3bp1Wrp0aTlUCAAAKgKHAtDcuXMlSePGjVPNmjXtn4tj+vTpjkzpsMGDB+tf//qX9u/fX2QAio6OVqdOneyfExISNHv27PIqEQAAlDOHAtDGjRtlMpn0yCOPqGbNmtq4cWOx9jOZTOUegLy8vOTv768bN24U2cdsNstsNpdjVQAAwJkcCkCrVq2SJHtoyPtcEaWnp+v69esKDAx0dikAAKCCcCgA1a1b97afncFqtSonJ6fA3V7Lli2TzWZTu3btnFQZAACoaAxZBH3p0iX5+vre9rk76enpSk1NVZ06dRya45NPPlFaWpr9bq2dO3fq8uXLkqQBAwYoNTVVjz76qHr16qWGDRtKkvbu3avdu3erXbt26ty5s0PzAgCAqseQADRkyBCNHj1aI0eOLLLPmjVr9O9//1vbt293aI5Vq1YpMTHR/nnHjh3asWOHJKl3797y9fVVx44dtW/fPsXGxio3N1fBwcEaN26chg4dKjc3N4fmBQAAVY8hAchms8lms/1mn9JYvXr1b/Z59tlnSzUHAABwDeV2WuTKlSs8jRkAAFQIDp8B+vWDA4t6Q3tubq4uX76srVu3qkWLFo5OBwAAYBiHA9D7779v/7PJZNKhQ4d06NChIvubzWaNHz/e0ekAAAAM43AAmj9/vqRba3umTJmivn37qk+fPgX6ubm5yd/fXw0bNmQhMgAAqBAcDkCRkZH2P48aNUr33HNPvjYAAICKypBTMvfdd5+++eabfG9U/6WkpCQtXLhQR48eNWI6AACAUjEkAK1atUo7d+5UUFBQodvNZrN27dpVrFvZAQAAypohAejEiRO6++67b9undevWOnbsmBHTAQAAlIohASglJeU336Zes2ZNXbt2zYjpAAAASsWQAOTr62t/L1dRLl26JG9vbyOmAwAAKBVDAlCLFi20Y8cOXbp0qdDtly5d0tdff6277rrLiOkAAABKxZAANHjwYFmtVk2YMEGxsbFKSkqSdOvur40bN+qJJ55QZmamhgwZYsR0AAAApWLIy1AjIyM1YcIEvf3225o7d66kW0+HznsBqslk0qRJk3hOEAAAqBAMCUCSNGjQIN17771au3atTpw4obS0NPn6+qp58+b63e9+p8aNGxs1FQAAQKkYFoAkqUmTJoqJiTFySAAAAMPxci4AAOByDDsDlJ2drU8//VRffvmlzp07J6vVqm3btkmSTp06pfXr12vQoEEKCQkxakoAAACHGBKArFarnnrqKR05ckQBAQHy8fGRxWKxb69Xr542bNggPz8/jR071ogpAQAAHGbIJbDly5crPj5e48aN0+eff64HH3ww33ZfX19FRkZq3759RkwHAABQKoYEoK+++kr33HOPhg8fLpPJJJPJVKBP/fr1i3xQIgAAQHkyJABdvnxZERERt+3j7e2tmzdvGjEdAABAqRgSgLy9vZWSknLbPhcvXlRAQIAR0wEAAJSKIQGoZcuW2rVrl1JTUwvdfunSJe3evVutW7c2YjoAAIBSMSQADR06VKmpqZo6dari4+OVk5MjSbJYLDpw4ICefvpp5eTk8C4wAABQIRj2LrApU6ZowYIFmjRpkr29T58+kiQ3NzfFxMT85johAACA8mDYgxD79++vyMhIrV27VsePH9eNGzfk4+Oj5s2b6/e//70aNWpk1FQAAACl4lAA+uabbxQaGlrgqc5hYWGaPHmyIYUBAACUFYfWAD377LPaunWr/fOQIUO0Zs0aw4oCAAAoSw4FIA8PD2VnZ9s/JyYmKi0tzbCiAAAAypJDAah27dr57vaSVOjTnwEAACoih9YA9erVS8uWLdNDDz0kf39/SdLq1au1YcOG2+5nMpm0cuVKR6YEAAAwjEMB6E9/+pM8PT21e/duJSUlyWQyyWazyWaz3Xa/39oOAABQHhwKQB4eHhoxYoRGjBghSerWrZsGDx6sUaNGGVkbAABAmXBoDdA333yj8+fP2z+PGjVKkZGRRtUEAABQpgy5DT42NlanT582rCgAAICy5PAlsPK8DT49PV0rV67UsWPHdPz4caWmpmrGjBnq27dvgb5nz57VwoULFR8fLw8PD3Xo0EETJ05UYGBgmdUHAAAql0pxG/z169e1dOlSJSQkKDw8vMh+ly9f1qRJk3ThwgWNHTtWQ4cO1bfffquYmBhlZWWVWX0AAKByqRS3wQcFBemzzz5TUFCQTpw4oXHjxhXab8WKFbJYLHrvvfdUp04dSVLz5s0VExOjjRs3Kjo6usRzAwCAqsehM0B/+tOfNHbsWDVp0kQmkynfbfC3+8nNzXWoSE9PTwUFBf1mv7i4OHXs2NEefiTpvvvuU0hIiLZt2+bQ3AAAoOqpMrfBX7lyRdeuXVNERESBbc2bN9fu3budUBUAAKiIHApAv1YRboNPTk6WpELPFAUFBenGjRvKzMyUp6dnge1JSUn2/SUpISGh7AoFAABOZ0gAGj169G/2ycrKUmZmpnx8fIyYsgCr1SpJqlatWoFteaHHarUWGoDWrVunpUuXlkldAACg4nFoDZAkDRkyRGvWrMnXtnfvXi1cuLDQ/itWrNCDDz7o6HS/ycvLS5IKvdsrMzMzX59fi46O1pIlS+w/zz77bJnVCQAAnM/hM0CFPfvn6NGjWrNmjSZOnFjqwkoq79LXLy9l5UlOTpa/v3+hZ38kyWw2y2w2l2l9AACg4nD4DFBFU6tWLQUGBurkyZMFth0/fvy2zw8CAACupcoEIOnW3Wi7du3SpUuX7G0HDhzQ+fPn1aNHDydWBgAAKhJDFkGXh08++URpaWn2S1w7d+7U5cuXJUkDBgyQr6+vRowYoe3bt2vKlCkaOHCgMjIy9NFHH6lx48aFvjYDAAC4pkoTgFatWqXExET75x07dmjHjh2SpN69e8vX11d16tTRggULtHDhQi1evNj+LrAJEyYUuf4HAAC4nkoTgFavXl2sfo0aNdJrr71WxtUAAIDKrFQBaPPmzTp69Kj984ULFyRJf/nLXwr0zdsGAADgbKUKQBcuXCg02Ozdu7fQ/mX5xngAAIDicjgArVq1ysg6AAAAyo3DAahu3bpG1gEAAFBuqtRzgAAAAIqDAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXA4BCAAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC7Hw9kFuKK0pAxZUjOdXUaxpVxIc3YJAAAYigBUztKSMrTmL18r25rj7FJKxMPLXdX9PJ1dBgAAhiAAlTNLaqayrTnq/sTdCgz2dXY5xVbdz1O+Zm9nlwEAgCEIQE4SGOwrc6MAZ5cBAIBLYhE0AABwOQQgAADgcqrUJbCDBw9q8uTJhW5btGiRWrZsWc4VAQCAiqhKBaA8AwYMUPPmzfO1BQcHO6kaAABQ0VTJANS6dWt1797d2WUAAIAKqsquAUpPT1d2drazywAAABVQlTwDNGfOHGVkZMjd3V133323Hn/8cd15553OLgsAAFQQVSoAeXh4qFu3bmrfvr0CAgJ09uxZrVq1ShMnTtTbb7+tZs2aFbpfUlKSkpOT7Z8TEhLKq2QAAOAEVSoAtWrVSq1atbJ/7ty5s7p3767Ro0fr3Xff1auvvlrofuvWrdPSpUvLqUoAAOBsVSoAFaZBgwbq3LmzduzYoZycHLm7uxfoEx0drU6dOtk/JyQkaPbs2eVZJgAAKEdVPgBJUu3atZWVlSWLxSIfH58C281ms8xmsxMqAwAAzlBl7wL7pYsXL8rT01Pe3rzMEwAAVLEAlJKSUqDt9OnT2rlzp9q0aSM3tyr1dQEAgIOq1CWw559/Xl5eXrrrrrt0xx136OzZs1q/fr2qV6+uxx57zNnlAQCACqJKBaAuXbpoy5YtWr16tW7evKnAwEB17dpVo0aNUoMGDZxdHgAAqCCqVAAaOHCgBg4c6OwyAABABceiGAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXA4BCAAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDL8XB2AUbLzMzUv/71L23evFmpqalq0qSJxowZozZt2ji7NAAAUEFUuTNAc+bM0erVq3X//ffrySeflJubm6ZNm6bDhw87uzQAAFBBVKkAdOzYMW3dulXjxo3TE088oejoaL3xxhuqW7euFi1a5OzyAABABVGlAlBcXJzc3d0VHR1tb/Py8tKDDz6oo0eP6tKlS06sDgAAVBRVKgCdOnVKDRo0kI+PT7725s2bS5JOnz7tjLIAAEAFU6UWQScnJysoKKhAe15bUlJSofslJSUpOTnZ/jkvKCUkJBheY8rFNCVnJurM2dNKzvQ1fHwAACq6sv67MDQ0VNWrV79tnyoVgKxWq6pVq1ag3dPT0769MOvWrdPSpUsLtM+ePdvQ+n7pv8+X2dAAAFQKZfV34ZIlSxQREXHbPlUqAHl5eSkrK6tAe2Zmpn17YaKjo9WpUyf759TUVCUkJGjr1q2aPHlysed/8803NWnSpNv2SUhI0OzZs/Xss88qNDS02GNXZcX5vTmLM2orizmNGrM04ziyb0n34Rh0TEU+BqXyr6+s5nOF47C4fcv6OCzOmFUqAAUFBenKlSsF2vMub5nN5kL3M5vNBbbdd9992rdv328myF/y9fUtdv/Q0NASjV2VleT3Vt6cUVtZzGnUmKUZx5F9S7oPx6BjKvIxKJV/fWU1nyschyUd35nHYZVaBB0eHq6ffvpJN2/ezNd+7Ngx+/aS6NWrV5n2xy0V+ffmjNrKYk6jxizNOI7syzFYPir676286yur+VzhOKzo/y/9kslms9mcXYRRjh07pvHjx+vxxx/XsGHDJN26/DVy5EgFBATonXfecXKF0smTJzV27NhiXZ8EYDyOQcD5KsJxWKUugbVo0UI9evTQu+++q5SUFAUHBys2NlaJiYl65plnnF2epFuX6UaNGlXo3WoAyh7HIOB8FeE4rFJngKRbd3rlvQssLS1NjRs31pgxY9S2bVtnlwYAACqIKheAAAAAfkuVWgQNAABQHASgCiYzM1Nz587VwIED1adPH40fP15HjhxxdlmAS3nllVfUv39/9enTRyNHjtTOnTudXRLgso4cOaJu3bpp2bJlho7LJbAKJiMjQ6tWrVLfvn1Vq1Ytbdu2TW+88YZWrVqlGjVqOLs8wCUkJCSoXr168vT01PHjxxUTE6OVK1cqICDA2aUBLiU3N1dPPPGEbDabOnbsqJEjRxo2NmeAKhhvb2+NGjVKderUkZubm6KiouTh4aHz5887uzTAZYSGhtpfoWMymZSVlVXkuwQBlJ3169erefPmZfK06Cp1G7wzpKena+XKlTp27JiOHz+u1NRUzZgxQ3379i3QNzMz036HWmpqqpo0aaIxY8aoTZs2RY5//vx5paamKjg4uCy/BlBpldUx+Prrr2vDhg3KzMxU+/bt1bhx4/L4OkClVBbH4fXr1/Xxxx9r0aJFevPNNw2vmTNApXT9+nUtXbpUCQkJv/mk6Tlz5mj16tW6//779eSTT8rNzU3Tpk3T4cOHC+1vtVo1e/ZsPfLII/L15c3xQGHK6hiMiYnRpk2bNG/ePLVp00Ymk6msvgJQ6ZXFcbhkyRINGjRIfn5+ZVO0DaVitVptSUlJNpvNZjt+/LitS5cutg0bNhTod/ToUVuXLl1sH374ob3NYrHYhg4dahs/fnyB/llZWbZp06bZZs2aZcvNzS27LwBUcmV1DP7SM888Y9u1a5exhQNViNHH4cmTJ22PPvqoLTs722az2WwvvPCCbenSpYbWzBmgUvL09CzWkyzj4uLk7u6u6Ohoe5uXl5cefPBBHT16VJcuXbK35+bmavbs2TKZTPrrX//KvzyB2yiLY/DXcnJydOHCBUPqBaoio4/DQ4cO6fz58xowYID69++vr776Sh9++KHmzJljWM2sASonp06dUoMGDeTj45OvvXnz5pKk06dPq06dOpKkV199VcnJyXr11Vfl4cF/IsAIxT0G09LS9O2336pTp07y9PTU119/rYMHD2rcuHHOKBuoUop7HEZHRysqKsq+fcGCBapXr54eeeQRw2rhb9dykpycXGg6zmvLu8MkMTFRX3zxhTw9PfMl5JdfflmtW7cun2KBKqi4x6DJZNIXX3yhefPmyWazKTg4WM8995yaNm1arvUCVVFxj8Pq1aurevXq9u1eXl7y9vY2dD0QAaicWK1WVatWrUB73q22VqtVklS3bl3t2LGjXGsDXEFxj0EfHx/Nnz+/XGsDXEVxj8Nf++tf/2p4LawBKideXl7Kysoq0J6ZmWnfDqDscAwCzleRjkMCUDkJCgpScnJygfa8NrPZXN4lAS6FYxBwvop0HBKAykl4eLh++ukn3bx5M1/7sWPH7NsBlB2OQcD5KtJxSAAqJ927d1dOTo7WrVtnb8vMzNSGDRvUokUL+x1gAMoGxyDgfBXpOGQRtAE++eQTpaWl2U/h7dy5U5cvX5YkDRgwQL6+vmrRooV69Oihd999VykpKQoODlZsbKwSExP1zDPPOLN8oNLjGAScr7Idh7wN3gCDBw9WYmJiodtWrVqlevXqSbq1uj3v/SdpaWlq3LixxowZo7Zt25ZnuUCVwzEIOF9lOw4JQAAAwOWwBggAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAFCEjRs3qmvXrvafmTNnFtpvyZIl6tq1q+Lj48u3wF9JSEjIV+/gwYOdWg9QkXk4uwAAFcfPP/+sIUOG3LZP3bp1tXr16nKqqGLo3LmzwsPD1bhx40K3f//993Jzc1PTpk0Nm3PDhg2aO3euHn30UY0cObLIflarVX/84x915coVzZs3T6NGjZIkrVmzxrBagKqIAASggODgYN1///2FbvP19S3napyvS5cu6tu3b5HbT506pZCQEFWvXt2wOfPC1g8//HDbfitXrlRiYqL69++vyMhIRUZGSpJiY2MNqwWoighAAAoIDg7Wn//8Z2eXUSkkJSXp6tWr+r//+z9Dx23UqJHc3Nz0448/3nbuDz/8UP7+/hozZoyh8wNVHWuAADjs4MGD6tq1q/7973/rxIkTiomJ0QMPPKC+ffvqb3/7m37++edC9zt06JCmT5+uhx9+WFFRURo2bJiWLFkii8VS5Pjx8fGKiYlRv3791LVrV3uf7OxsrVixQkOHDlWvXr00bNgwrVixQhcvXlTXrl314osv2vvu379fXbt21euvv15oXRcuXFC3bt301FNPFft3cOrUKUlSs2bN8rUnJCToT3/6kx544AFt3brV3p6Tk6P//ve/mjRpkvr27atevXppzJgxiouLy7e/l5eXgoOD9dNPPyk7O7vQuRcvXqyMjAyNGTNG/v7+xa4ZAAEIgAFOnDihSZMmycPDQ9HR0YqIiNDXX3+tmJgYWa3WfH0///xzTZ48WfHx8Wrfvr0GDBig2rVra/ny5YqJiVFWVlaB8Y8cOaLJkyfLZDLp4YcfVs+ePe3bXnrpJb377ruSpP79+6tt27ZavXq1FixYUGCc//u//1NwcLC+/PLLAmFLkr744gvZbDY9/PDDxf7uhQWgrVu3aty4ccrOztaiRYsUFRUl6dZ6naefflovvfSS0tPT1bdvX/Xt21eXLl3Sc889p82bN+cbu3HjxsrOzlZCQkKBeY8dO6bNmzcrPDy8RPUCuIVLYAAKuHDhgv79738Xuq1ly5Zq165dvrbdu3fr+eeft/9FL0kvvPCCNm3apG+++cbefvbsWc2fP19NmjTRvHnzFBAQYO+/YsUKvfvuu/rkk080dOjQfOPv379f06dPV79+/fK1HzhwQJs2bVLTpk311ltv2dfg/PGPfyz0klBegHrnnXe0bdu2fOt6srOzFRsbqzvuuEOdO3cuzq9J0q0F0CaTSU2bNlV2drbeeustffLJJ+rUqZP+9re/5Vsz9dJLL+nAgQOaPHmyBgwYYG8fOXKkRo8erffee0+9e/e2tzdp0kRxcXE6e/asmjRpkm/eN998UzabTZMnT5a7u3ux6wVwC2eAABRw4cIFLV26tNCfPXv2FOjfunXrfOFHkj2sHD9+3N62du1a5eTkaPLkyfnCjyQNHz5cgYGB+S4X5WnWrFmB8CPJfsZk5MiR+RYgm81mDRw4sNDv1q9fP1WrVk3//e9/87V/++23Sk5OVp8+feThUfx/G546dUr169fXzZs3NWnSJH322Wd69NFH9eKLL+YLPwcOHNCXX36p6OjofOEnr9727dsrMTFRKSkp9vaiFkJv2bJFR48eVVRUlFq3bl3sWgH8D2eAABTQtm1bvfrqq8XuHxERUaCtVq1akqS0tDR727FjxyRJe/fu1YEDBwrs4+HhoXPnzhVov/POOwud9/Tp05Kku+++u8C2u+66q9B9AgMD1bVrV23dulUJCQkKDQ2VJHsgeuihhwrdrzCpqan6+eefFRwcrDFjxshms+nll19W27ZtC/T99NNPJUm5ubmFnl3Lu8yVm5trb8s76/PLhdAWi0XvvPOOvL299fjjjxe7VgD5EYAAlFqNGjUKtOVdlvnlX+g3btyQJC1fvrxE49esWbPQ9vT0dLm5uRU4m3S7fSQpOjpaW7du1RdffKEJEyYoKSlJe/bsUWRkpEJCQopdV976n9TUVN24cUMjR44sNPxIty7jSbfWGRXF09NTgYGB9s/169eXt7d3vgD04Ycf6sqVKxo7dqxq165d7FoB5EcAAlBufHx8JN16Rk1hoamkatSoodzcXF2/fj1fcJCkq1evFrnfPffco4YNG2rTpk0aN26cNmzYoJycnBKd/ZH+F4CmTZumjz76SCtWrFCLFi3UoUOHfP1SU1OVkZGhzp0757sr7beYTCaFhYXp5MmTslgsunHjhlauXKng4ODffGAlgNtjDRCActOiRQtJ0tGjRw0ZLzw8XJIKfQXFkSNHbrtvdHS0UlJS9PXXX2vDhg3y8/NTt27dSjR/XgBq0aKFXnzxRdWqVUszZ860X5r7tevXr5dofOnWZbDc3FydPXtW77zzjiwWiyZOnChPT88SjwXgfwhAAMpN//795e7urvnz5+vSpUsFtqempur7778v9nh5T6teunRpvtvtk5OTf/NVEH369JGnp6cWLlyoixcvqnfv3vLy8ir23NKtO8Bq1qwps9msO+64Q3PnzpWbm5ueeeYZJSUl2fv5+fmpQYMGOnbsWKFrn7KysooMbHkLob/44gt9+eWXateunTp16lSiOgEUxCUwAAXc7jZ4SXrkkUdKHBakW3+Zx8TE6PXXX9cjjzyi9u3bKzg4WOnp6bp48aK+++479enTR08//XSxxrvvvvvUq1cvffnllxo1apQ6d+6srKwsbdu2Tc2bN9euXbvk5lb4v/P8/f3Vo0cPbdq0SZJK/Cwdq9Wq8+fP53sCdOPGjfX8889rxowZmj59uhYuXGi/O+3xxx/Xc889p6eeekrt27dXaGioLBaLrly5ovj4eLVt27bQhdt5C6HXrVsnDw8PTZo0qUR1AigcAQhAAXm3wRdl0KBBDgUg6VbQCA8P1+rVq/Xdd99p165d8vHxUZ06dTRo0CD16dOnROP99a9/VWhoqDZs2KBPP/1UtWrV0qBBg3Tvvfdq165dt11r1KdPH23atEktW7Ys8kWnRTlz5oxycnLsl+HytG/fXhMnTtT8+fP1j3/8Q7Nnz5abm5u6dOmiN954Qx999JGOHj2qPXv2yN/fX7Vr11a/fv2KfNfYL+saOHCgGjZsWKI6ARTOZLPZbM4uAgCM9sUXX+jll19WTEyM+vfvX2ifjz76SIsWLdIzzzyjBx98sMD2jRs3as6cOZoxY8ZtX4ZaEQ0ePFiStHr1aidXAlRMrAECUKklJyfr1/+Ou3Lliv7zn//I3d29wB1ZeaxWqz777DP5+fkVeIjjr82ZM0ddu3bVzJkzjSq7TCQkJKhr167q2rWrEhMTnV0OUKFxCQxApfbBBx/o22+/VevWrRUYGKjLly9r165dSk9P1+jRo1WnTp18/Q8fPqxDhw5p7969SkxM1Lhx4/I9RfqXwsPDNWrUKPvnkl4mK28BAQH56v3lk6gB5MclMACV2p49e7Rq1SqdOXNGqamp8vT0VJMmTdS/f3/7XWK/9O9//1tLly5VQECAHnjgAY0fP75Er74AUDUQgAAAgMthDRAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5fx/mXPbp8glsIcAAAAASUVORK5CYII=\n", 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++9//au3atbp+/bpq1KihiIgIjR8/3h5sfH191bFjR+3bt0+xsbHKzc1VcHCwxo0bp6FDh8rNrVKc7AIAAOWgUgSgqKioIm9hz+Pn56dnn322nCoCAACVWaUIQABgtJQLRd88URFV9/OUr9nb2WUAVQYBCIBLqe7nKQ8vd21/+7CzSykRDy93DXylCyEIMAgBCIBL8TV7a+ArXWRJzXR2KcWWciFN298+LEtqJgEIMAgBCIDL8TV7EyQAF8etUQAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuh5ehospKS8qodG/8BgCUDwIQqqS0pAyt+cvXyrbmOLuUEvHwcld1P09nlwEAVR4BCFWSJTVT2dYcdX/ibgUG+zq7nGKr7ucpX7O3s8sAgCqPAIQqLTDYV+ZGAc4uAwBQwbAIGgAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDL4W3wAFBJpFxIc3YJJVLdz1O+Zm9nlwEUigAEABVcdT9PeXi5a/vbh51dSol4eLlr4CtdCEGokCpFAPrxxx/1/vvv6+TJk7p69aqqV6+u0NBQDRs2TJ06dcrX9+zZs1q4cKHi4+Pl4eGhDh06aOLEiQoMDHRO8QBQSr5mbw18pYssqZnOLqXYUi6kafvbh2VJzSQAoUKqFAEoMTFR6enp6tOnj8xmsywWi+Li4jRjxgw9/fTTio6OliRdvnxZkyZNkq+vr8aOHauMjAytXLlSP/zwgxYvXqxq1ao5+ZsAgGN8zd4ECcBAlSIAdejQQR06dMjX9oc//EFjx47V6tWr7QFoxYoVslgseu+991SnTh1JUvPmzRUTE6ONGzfa+wEAANdWae8Cc3d3V+3atZWW9r9FgXFxcerYsaM9/EjSfffdp5CQEG3bts0ZZQIAgAqoUpwBypORkSGr1aqbN29q586d2rNnj3r06CFJunLliq5du6aIiIgC+zVv3ly7d+8uctykpCQlJyfbPyckJBhfPAAAqDAqVQB66623tG7dOkmSm5ubunbtqqlTp0qSPcAEBQUV2C8oKEg3btxQZmamPD09C2xft26dli5dWnaFAwCACqVSBaBBgwape/fuSkpK0rZt25STk6OsrCxJktVqlaRCFzrnhR6r1VpoAIqOjs53N1lCQoJmz55dFl8BAABUAJUqAIWGhio0NFSS1KdPH8XExGj69OlavHixvLy8JMkeiH4pM/PWraN5fX7NbDbLbDaXUdUAAKCiqbSLoCWpe/fuOnHihM6fP2+/9PXLtTx5kpOT5e/vX+jZHwAA4HoqdQDKu+yVlpamWrVqKTAwUCdPnizQ7/jx4woPDy/v8gAAQAVVKQLQtWvXCrRlZ2dr06ZN8vLyUlhYmCSpW7du2rVrly5dumTvd+DAAZ0/f95+txgAAEClWAP06quv6ubNm2rdurVq1aql5ORkbdmyRefOndOECRNUo0YNSdKIESO0fft2TZkyRQMHDlRGRoY++ugjNW7cWH379nXytwAAABVFpQhAPXv21H//+1+tXbtW169fV40aNRQREaHx48erc+fO9n516tTRggULtHDhQi1evNj+LrAJEyaw/gcAANhVigAUFRWlqKioYvVt1KiRXnvttTKuCAAAVGaVYg0QAACAkQhAAADA5RCAAACAyyEAAQAAl+PQIughQ4aUeuJBgwZp4MCBpR4HAACgpBwKQImJifLx8ZGvr69Dk16+fFlpaWkO7QsAAFBaDt8GP3jwYI0aNcqhfbt16+botAAAAKXGGiAAAOByHDoDtHz5cgUEBDg8aWn3BwAAKA2HAlDDhg1LNWlp9wcAACgNLoEBAACXQwACAAAup8QBKDc3Vz/88IOSkpIKbMvOztahQ4eMqAsAAKDMlGgNUGJioqZNm6aEhASZTCa1b99eM2bMsC9ovnHjhqZMmaLt27eXRa0AAACGKNEZoEWLFslsNmvlypVasmSJrFarJkyYkO9skM1mM7xIAAAAI5UoAH333Xd64oknVK9ePTVt2lSvvfaa7r77bk2cOFGXLl2SJJlMpjIpFAAAwCglCkAWi0XVqlX7385ubpo2bZratGmjSZMm6cKFC4YXCAAAYLQSBaCGDRvq5MmTBdqfeuoptW/fXtOnTzesMAAAgLJSogDUtWtXbdmypdBtMTExioqKYg0QAACo8EoUgEaMGKFXXnmlyO0xMTGKi4srdVEAAABliQchAgAAl+PQu8AK8+2332rv3r1KT09XnTp1FB4ermbNmqlu3bpGTQEAAGAIQwLQBx98oCVLluRb/5N3O7yvr689DDVr1ky9evUyYkoAAACHGRKAPv/8c/n4+Gj69Olq0qSJEhMTdfr0aZ06dUqnTp3S4cOHdfDgQZlMJgIQAABwOkMC0I0bN9SvXz916dJFklS/fn3de++99u1ZWVn64YcfdOrUKSOmAwAAKBVDAlB4eLgsFkuR26tVq6aIiAhFREQYMR0AAECpGHIX2KBBg7Rr1y5dv37diOEAAADKlCEBqHv37oqKitL06dN15coVI4YEAAAoM4bdBl+/fn1t3LhRI0aMUPv27XXvvfeqadOmCg8Pl6enp1HTAAAAlJohAWjRokVatWqV/Tb47du3a/v27TKZTHJzc1PDhg3VrFkzRUREaMCAAUZMCQAA4DBDAtCmTZsUGBioF154QU2aNNGVK1d06tQpff/99/Zb4Tdt2qTNmzcTgAAAgNMZEoAsFosefvhhtWzZUpIUEhKikJAQ9ezZ097n0qVL3AYPAAAqBEMCUEREhFJSUm7bp06dOqpTp44R0wEAKomUC2nOLqHEqvt5ytfs7ewyUMYMCUAjRozQ888/r8uXL6t27dpGDAkAqMSq+3nKw8td298+7OxSSszDy10DX+lCCKriDAlACQkJioyM1NNPP61Zs2apUaNGRgxrd/z4ccXGxurgwYNKTEyUv7+/WrZsqTFjxigkJMTe78UXX1RsbGyB/Rs2bKgVK1YYWhMAoGi+Zm8NfKWLLKmZzi6lRFIupGn724dlSc0kAFVxhgSgN998UyaTSTabTX/+85/VsmVL3XvvvfYXoJb2rNCHH36o+Ph49ejRQ02aNFFycrI+++wzjRkzRosWLVLjxo3tfT09PTVt2rR8+/v4+JRqfgBAyfmavQkRqLAMCUCzZs3SqVOn7C9AjY+PV3x8vP2N8AEBAWratKkiIiI0duzYEo8/ePBg/f3vf1e1atXsbT179tTo0aP1wQcf6LnnnrO3u7u7q3fv3qX/UgAAoMoyJAB1795d3bt3t39OSUmx3/6eF4oOHDig/fv3OxSAWrVqVaAtJCREYWFhSkhIKLAtJydHFouFMz8AAKBQhj0J+pcCAwPVpk0btWnTxt5mtVp15swZw+aw2Wy6du2awsLC8rVbLBb17dtXFotFfn5+ioqK0vjx41WjRg3D5gYAAJWbIQHoxx9/1JUrV9SqVSt5exd+vdfLy0stWrQwYjpJ0pYtW3TlyhX9+c9/trcFBQVp2LBhatasmWw2m/bs2aPPP/9cZ86c0fz58+XhUfjXTUpKUnJysv1zYWeVAABA1WFIAFq+fLl27NihlStXFhmAjJSQkKB58+apZcuW6tOnj739sccey9cvKipKISEhWrJkieLi4hQVFVXoeOvWrdPSpUvLsmQAAFCBGPI2+CNHjqhdu3Yym82Fbj9//ryeffZZxcfHl3qu5ORkPfPMM/Lx8dE///lPubu737b/4MGD5ebmpv379xfZJzo6WkuWLLH/PPvss6WuEwAAVFyGnAG6evVqvufx/FpISIjOnj2rNWvWFLqgubjS0tI0bdo0paWlaeHChUUGrl/y8vKSv7+/bty4UWQfs9lcrLEAAEDVYMgZIB8fH6Wnp9+2z1133aVjx445PIfVatX06dN1/vx5zZ07t8Di56Kkp6fr+vXrCgwMdHhuAABQtRgSgO68807t3r1bubm5RfYJDAzUtWvXHBo/JydHM2fO1NGjRzVr1izdddddBfpYrdZCQ9iyZctks9nUrl07h+YGAABVjyGXwB566CE9++yzWrhwoZ588slC+1y8eFGenp4Ojf/WW29p586d6tixo1JTU7V58+Z823v37q2rV6/q0UcfVa9evdSwYUNJ0t69e7V79261a9dOnTt3dmhuAABQ9RgSgLp06aIePXrok08+0YULF/TYY4/lez3FgQMH9M033ygyMtKh8U+fPi1J2rVrl3bt2lVge+/eveXr66uOHTtq3759io2NVW5uroKDgzVu3DgNHTpUbm6GnOwCAABVgGEPQnzuuefk6+ur9evXa8+ePapbt67q1q2ra9eu6dy5c7LZbBo2bJhDYy9YsOA3+/j5+XH3FgAAKBbDApC7u7uefvpp3X///fr444+1f/9+/fzzz5Kk+vXra9y4cfmeDA0AAOAshr8Ko3Xr1mrdurWkW7et22w2+fn5GT0NAACAw8rkXWB5fH19y3J4AAAAh7AyGAAAuByHAtA//vEPxcXFOTxpafcHAAAoDYcC0NatW/Xjjz86PGlp9wcAACgNh9cAnTp1SrGxsUbWAgAAUC4cDkDffPONdu7cWeL9bDabo1MCAAAYwqEANH369FJP3LRp01KPAQAA4AiHAlDfvn2NrgMAAKDccBs8AABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXI7DT4IuSk5Ojq5fv66srKxCt9epU8foKQEAAErEsAB08uRJvfvuu/ruu++UnZ1daB+TyaRt27YZNSUAAIBDDAlAp06d0sSJE+Xu7q42bdpo165dCg8PV82aNfX9998rJSVFkZGRqlu3rhHTAQAAlIohAWjZsmWSpHfeeUdhYWHq1q2bunTpolGjRslqteqtt97S9u3bDXmHGAAAQGkZsgg6Pj5enTp1UlhYmL0t763vXl5emjJlisxms5YsWWLEdAAAAKViSAC6efOm6tevb//s4eGhjIyM/03i5qbIyEgdOHDAiOkAAABKxZAAFBgYqNTUVPvnmjVr6qeffsrXJzMzUxaLxYjpAAAASsWQABQWFqZz587ZP7dq1Ur79u3TkSNHJElnz57Vtm3bFBoaasR0AAAApWLIIugOHTpo4cKFSkpKktls1vDhw7Vjxw5NnDhRfn5+SktLU25urkaMGGHEdAAAAKViSAD63e9+px49esjPz0+SFB4ernnz5mn58uW6ePGiIiIiNGDAAHXo0MGI6QAAAErFkADk4eGhmjVr5mtr1aqVXn75ZSOGBwAAMBTvAgMAAC7HsFdhZGdn69NPP9WXX36pc+fOyWq12l97cerUKa1fv16DBg1SSEiIUVMCAFAmUi6kObuEEqnu5ylfs7ezy6hUDAlAVqtVTz31lI4cOaKAgAD5+Pjku+W9Xr162rBhg/z8/DR27FgjpgQAwHDV/Tzl4eWu7W8fdnYpJeLh5a6Br3QhBJWAIQFo+fLlio+P12OPPaZhw4bp/fff13/+8x/7dl9fX0VGRmrfvn0EIABAheVr9tbAV7rIkprp7FKKLeVCmra/fViW1EwCUAkYEoC++uor3XPPPRo+fLikW299/7X69evr1KlTRkwHAECZ8TV7EyRcgCGLoC9fvqyIiIjb9vH29tbNmzeNmA4AAKBUDDkD5O3trZSUlNv2uXjxogICAoyYDk6QlpRR6U4JAwBQFEMCUMuWLbVr1y6lpqbaH4b4S5cuXdLu3bvVpUsXh8Y/fvy4YmNjdfDgQSUmJsrf318tW7bUmDFjCtxVdvbsWS1cuFDx8fHy8PBQhw4dNHHiRAUGBjo0N26FnzV/+VrZ1hxnl1IiHl7uqu7n6ewyAAAVkCEBaOjQoZoyZYqmTp2qyZMnKyfn1l+UFotFR48e1RtvvKGcnBwNGTLEofE//PBDxcfHq0ePHmrSpImSk5P12WefacyYMVq0aJEaN24s6daluEmTJsnX11djx45VRkaGVq5cqR9++EGLFy9WtWrVjPi6LseSmqlsa466P3G3AoN9nV1OsXFbKACgKIYEoMjISE2ZMkULFizQpEmT7O19+vSRJLm5uSkmJuY31wkVZfDgwfr73/+eL8D07NlTo0eP1gcffKDnnntOkrRixQpZLBa99957qlOnjiSpefPmiomJ0caNGxUdHe3oV4SkwGBfmRtxGRMAUPkZ9iDE/v37KzIyUmvXrtXx48d148YN+fj4qHnz5vr973+vRo0aOTx2q1atCrSFhIQoLCxMCQkJ9ra4uDh17NjRHn4k6b777lNISIi2bdtGAAIAAJIMDECSFBYWpsmTJxs5ZJFsNpuuXbumsLAwSdKVK1d07dq1Qs8yNW/eXLt37y6XugAAQMVnyG3w3bt31z/+8Q8jhiq2LVu26MqVK+rZs6ckKTk5WZIUFBRUoG9QUJBu3LihzMzC72JKSkrSyZMn7T+/PKsEAACqHkPOANWoUUO1a9c2YqhiSUhI0Lx589SyZUv7OiOr1SpJhS509vT0tPfJ+/MvrVu3TkuXLi27ggEAQIViSABq3ry5zpw5Y8RQvyk5OVnPPPOMfHx89M9//lPu7u6SJC8vL0lSVlZWgX3yzvzk9fm16OhoderUyf45ISFBs2fPNrp0AABQQRgSgEaPHq3JkycrNjbWfkamLKSlpWnatGlKS0vTwoULZTab7dvyLn3lXQr7peTkZPn7+xd69keSzGZzvrEAAEDVZkgA2r9/vyIjIzV37lx9+umnuvPOO3XHHXcUeCeYyWTSyJEjHZrDarVq+vTpOn/+vF5//XX74uc8tWrVUmBgoE6ePFlg3+PHjys8PNyheQEAQNVjSAB6//337X/OW0hcGEcDUE5OjmbOnKmjR4/qxRdf1F133VVov27duik2NlaXLl2y3wp/4MABnT9/XoMHDy7xvAAAoGoyJADNnz/fiGGK9NZbb2nnzp3q2LGjUlNTtXnz5nzbe/fuLUkaMWKEtm/frilTpmjgwIHKyMjQRx99pMaNG6tv375lWiMAAKg8DHsSdFk6ffq0JGnXrl3atWtXge15AahOnTpasGCBFi5cqMWLF9vfBTZhwoQi1/8AAADXY+iDEMvKggULit23UaNGeu2118qwGgAAUNkZHoBycnJ0/fr1Qm9Hl5TvNRUAAADOYFgAOnnypN5991199913ys7OLrSPyWTStm3bjJoSAADAIYYEoFOnTmnixIlyd3dXmzZttGvXLoWHh6tmzZr6/vvvlZKSosjISNWtW9eI6QAAAErFkAC0bNkySdI777yjsLAwdevWTV26dNGoUaNktVr11ltvafv27Zo+fboR0wEAAJSKIS9DjY+PV6dOnfI9nNBms0m69fqJKVOmyGw2a8mSJUZMBwAAUCqGBKCbN2+qfv369s8eHh7KyMj43yRuboqMjNSBAweMmA4AAKBUDAlAgYGBSk1NtX+uWbOmfvrpp3x9MjMzZbFYjJgOAACgVAwJQGFhYTp37pz9c6tWrbRv3z4dOXJEknT27Flt27ZNoaGhRkwHAABQKoYsgu7QoYMWLlyopKQkmc1mDR8+XDt27NDEiRPl5+entLQ05ebmasSIEUZMBwAAUCqGBKDf/e536tGjh/z8/CRJ4eHhmjdvnpYvX66LFy8qIiJCAwYMUIcOHYyYDgAAoFQMCUAeHh6qWbNmvrZWrVrp5ZdfNmJ4AAAAQxmyBggAAKAyIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcgx5DpAkZWdn69NPP9WXX36pc+fOyWq1atu2bZKkU6dOaf369Ro0aJBCQkKMmhIAAMAhhgQgq9Wqp556SkeOHFFAQIB8fHzyvfi0Xr162rBhg/z8/DR27FgjpgQAAHCYIZfAli9frvj4eI0bN06ff/65HnzwwXzbfX19FRkZqX379hkxHQAAQKkYEoC++uor3XPPPRo+fLhMJpNMJlOBPvXr19elS5eMmA4AAKBUDAlAly9fVkRExG37eHt76+bNm0ZMBwAAUCqGBCBvb2+lpKTcts/FixcVEBBgxHQAAAClYkgAatmypXbt2qXU1NRCt1+6dEm7d+9W69atjZgOAACgVAwJQEOHDlVqaqqmTp2q+Ph45eTkSJIsFosOHDigp59+Wjk5ORoyZIgR0wEAAJSKIbfBR0ZGasqUKVqwYIEmTZpkb+/Tp48kyc3NTTExMb+5TggAAKA8GPYgxP79+ysyMlJr167V8ePHdePGDfn4+Kh58+b6/e9/r0aNGhk1FQAAQKkYFoAkKSwsTJMnTzZySAAAAMPxLjAAAOByDAlAEydO1Pr164u8CwwAAKAiMeQS2NGjR3XkyBHNnz9fHTp0UO/evdWhQwd5eBh6hQ0AAMAQhiSUzz77TFu2bNHmzZu1Y8cOff311/Lz81OPHj10//33q1WrVkZMAwAAipByIc3ZJZRIdT9P+Zq9nTa/IQEoMDBQgwYN0qBBg5SQkKDNmzdry5YtWrt2rdatW6d69eqpd+/euv/++9WgQQMjpgQAALoVJDy83LX97cPOLqVEPLzcNfCVLk4LQYZfowoNDdXYsWM1duxYHTp0SJs3b9b27du1bNky/ec//9G2bduMnhIAAJfla/bWwFe6yJKa6exSii3lQpq2v31YltTMqhOAfikyMlK1a9dWQECAVq9ebX9CdEmlp6dr5cqVOnbsmI4fP67U1FTNmDFDffv2zdfvxRdfVGxsbIH9GzZsqBUrVjg0NwAAFZ2v2dupl5MqozIJQDdu3NBXX32lzZs369ixY5KkGjVqqEePHg6Nd/36dS1dulR16tRReHi4Dh48WGRfT09PTZs2LV+bj4+PQ/MCAICqybAAlJWVpZ07d2rz5s3au3evsrKy5OHhoQ4dOuiBBx5Qx44d5enp6dDYQUFB+uyzzxQUFKQTJ05o3LhxRfZ1d3dX7969Hf0aAADABRgSgF566SXFxcUpPT1dNptNzZs3V+/evRUVFaWAgIBSj+/p6amgoKBi98/JyZHFYuHMDwAAKJQhAWjDhg2qW7euBgwYoN69eyskJMSIYR1isVjUt29fWSwW+fn5KSoqSuPHj1eNGjWcVhMAAKhYDAlAb775pu6++24jhiqVoKAgDRs2TM2aNZPNZtOePXv0+eef68yZM5o/f36RD2ZMSkpScnKy/XNCQkJ5lQwAAJzAkABUEcKPJD322GP5PkdFRSkkJERLlixRXFycoqKiCt1v3bp1Wrp0aTlUCAAAKgKHAtDcuXMlSePGjVPNmjXtn4tj+vTpjkzpsMGDB+tf//qX9u/fX2QAio6OVqdOneyfExISNHv27PIqEQAAlDOHAtDGjRtlMpn0yCOPqGbNmtq4cWOx9jOZTOUegLy8vOTv768bN24U2cdsNstsNpdjVQAAwJkcCkCrVq2SJHtoyPtcEaWnp+v69esKDAx0dikAAKCCcCgA1a1b97afncFqtSonJ6fA3V7Lli2TzWZTu3btnFQZAACoaAxZBH3p0iX5+vre9rk76enpSk1NVZ06dRya45NPPlFaWpr9bq2dO3fq8uXLkqQBAwYoNTVVjz76qHr16qWGDRtKkvbu3avdu3erXbt26ty5s0PzAgCAqseQADRkyBCNHj1aI0eOLLLPmjVr9O9//1vbt293aI5Vq1YpMTHR/nnHjh3asWOHJKl3797y9fVVx44dtW/fPsXGxio3N1fBwcEaN26chg4dKjc3N4fmBQAAVY8hAchms8lms/1mn9JYvXr1b/Z59tlnSzUHAABwDeV2WuTKlSs8jRkAAFQIDp8B+vWDA4t6Q3tubq4uX76srVu3qkWLFo5OBwAAYBiHA9D7779v/7PJZNKhQ4d06NChIvubzWaNHz/e0ekAAAAM43AAmj9/vqRba3umTJmivn37qk+fPgX6ubm5yd/fXw0bNmQhMgAAqBAcDkCRkZH2P48aNUr33HNPvjYAAICKypBTMvfdd5+++eabfG9U/6WkpCQtXLhQR48eNWI6AACAUjEkAK1atUo7d+5UUFBQodvNZrN27dpVrFvZAQAAypohAejEiRO6++67b9undevWOnbsmBHTAQAAlIohASglJeU336Zes2ZNXbt2zYjpAAAASsWQAOTr62t/L1dRLl26JG9vbyOmAwAAKBVDAlCLFi20Y8cOXbp0qdDtly5d0tdff6277rrLiOkAAABKxZAANHjwYFmtVk2YMEGxsbFKSkqSdOvur40bN+qJJ55QZmamhgwZYsR0AAAApWLIy1AjIyM1YcIEvf3225o7d66kW0+HznsBqslk0qRJk3hOEAAAqBAMCUCSNGjQIN17771au3atTpw4obS0NPn6+qp58+b63e9+p8aNGxs1FQAAQKkYFoAkqUmTJoqJiTFySAAAAMPxci4AAOByDDsDlJ2drU8//VRffvmlzp07J6vVqm3btkmSTp06pfXr12vQoEEKCQkxakoAAACHGBKArFarnnrqKR05ckQBAQHy8fGRxWKxb69Xr542bNggPz8/jR071ogpAQAAHGbIJbDly5crPj5e48aN0+eff64HH3ww33ZfX19FRkZq3759RkwHAABQKoYEoK+++kr33HOPhg8fLpPJJJPJVKBP/fr1i3xQIgAAQHkyJABdvnxZERERt+3j7e2tmzdvGjEdAABAqRgSgLy9vZWSknLbPhcvXlRAQIAR0wEAAJSKIQGoZcuW2rVrl1JTUwvdfunSJe3evVutW7c2YjoAAIBSMSQADR06VKmpqZo6dari4+OVk5MjSbJYLDpw4ICefvpp5eTk8C4wAABQIRj2LrApU6ZowYIFmjRpkr29T58+kiQ3NzfFxMT85johAACA8mDYgxD79++vyMhIrV27VsePH9eNGzfk4+Oj5s2b6/e//70aNWpk1FQAAACl4lAA+uabbxQaGlrgqc5hYWGaPHmyIYUBAACUFYfWAD377LPaunWr/fOQIUO0Zs0aw4oCAAAoSw4FIA8PD2VnZ9s/JyYmKi0tzbCiAAAAypJDAah27dr57vaSVOjTnwEAACoih9YA9erVS8uWLdNDDz0kf39/SdLq1au1YcOG2+5nMpm0cuVKR6YEAAAwjEMB6E9/+pM8PT21e/duJSUlyWQyyWazyWaz3Xa/39oOAABQHhwKQB4eHhoxYoRGjBghSerWrZsGDx6sUaNGGVkbAABAmXBoDdA333yj8+fP2z+PGjVKkZGRRtUEAABQpgy5DT42NlanT582rCgAAICy5PAlsPK8DT49PV0rV67UsWPHdPz4caWmpmrGjBnq27dvgb5nz57VwoULFR8fLw8PD3Xo0EETJ05UYGBgmdUHAAAql0pxG/z169e1dOlSJSQkKDw8vMh+ly9f1qRJk3ThwgWNHTtWQ4cO1bfffquYmBhlZWWVWX0AAKByqRS3wQcFBemzzz5TUFCQTpw4oXHjxhXab8WKFbJYLHrvvfdUp04dSVLz5s0VExOjjRs3Kjo6usRzAwCAqsehM0B/+tOfNHbsWDVp0kQmkynfbfC3+8nNzXWoSE9PTwUFBf1mv7i4OHXs2NEefiTpvvvuU0hIiLZt2+bQ3AAAoOqpMrfBX7lyRdeuXVNERESBbc2bN9fu3budUBUAAKiIHApAv1YRboNPTk6WpELPFAUFBenGjRvKzMyUp6dnge1JSUn2/SUpISGh7AoFAABOZ0gAGj169G/2ycrKUmZmpnx8fIyYsgCr1SpJqlatWoFteaHHarUWGoDWrVunpUuXlkldAACg4nFoDZAkDRkyRGvWrMnXtnfvXi1cuLDQ/itWrNCDDz7o6HS/ycvLS5IKvdsrMzMzX59fi46O1pIlS+w/zz77bJnVCQAAnM/hM0CFPfvn6NGjWrNmjSZOnFjqwkoq79LXLy9l5UlOTpa/v3+hZ38kyWw2y2w2l2l9AACg4nD4DFBFU6tWLQUGBurkyZMFth0/fvy2zw8CAACupcoEIOnW3Wi7du3SpUuX7G0HDhzQ+fPn1aNHDydWBgAAKhJDFkGXh08++URpaWn2S1w7d+7U5cuXJUkDBgyQr6+vRowYoe3bt2vKlCkaOHCgMjIy9NFHH6lx48aFvjYDAAC4pkoTgFatWqXExET75x07dmjHjh2SpN69e8vX11d16tTRggULtHDhQi1evNj+LrAJEyYUuf4HAAC4nkoTgFavXl2sfo0aNdJrr71WxtUAAIDKrFQBaPPmzTp69Kj984ULFyRJf/nLXwr0zdsGAADgbKUKQBcuXCg02Ozdu7fQ/mX5xngAAIDicjgArVq1ysg6AAAAyo3DAahu3bpG1gEAAFBuqtRzgAAAAIqDAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXA4BCAAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC7Hw9kFuKK0pAxZUjOdXUaxpVxIc3YJAAAYigBUztKSMrTmL18r25rj7FJKxMPLXdX9PJ1dBgAAhiAAlTNLaqayrTnq/sTdCgz2dXY5xVbdz1O+Zm9nlwEAgCEIQE4SGOwrc6MAZ5cBAIBLYhE0AABwOQQgAADgcqrUJbCDBw9q8uTJhW5btGiRWrZsWc4VAQCAiqhKBaA8AwYMUPPmzfO1BQcHO6kaAABQ0VTJANS6dWt1797d2WUAAIAKqsquAUpPT1d2drazywAAABVQlTwDNGfOHGVkZMjd3V133323Hn/8cd15553OLgsAAFQQVSoAeXh4qFu3bmrfvr0CAgJ09uxZrVq1ShMnTtTbb7+tZs2aFbpfUlKSkpOT7Z8TEhLKq2QAAOAEVSoAtWrVSq1atbJ/7ty5s7p3767Ro0fr3Xff1auvvlrofuvWrdPSpUvLqUoAAOBsVSoAFaZBgwbq3LmzduzYoZycHLm7uxfoEx0drU6dOtk/JyQkaPbs2eVZJgAAKEdVPgBJUu3atZWVlSWLxSIfH58C281ms8xmsxMqAwAAzlBl7wL7pYsXL8rT01Pe3rzMEwAAVLEAlJKSUqDt9OnT2rlzp9q0aSM3tyr1dQEAgIOq1CWw559/Xl5eXrrrrrt0xx136OzZs1q/fr2qV6+uxx57zNnlAQCACqJKBaAuXbpoy5YtWr16tW7evKnAwEB17dpVo0aNUoMGDZxdHgAAqCCqVAAaOHCgBg4c6OwyAABABceiGAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5RCAAACAyyEAAQAAl0MAAgAALocABAAAXA4BCAAAuBwCEAAAcDkEIAAA4HIIQAAAwOUQgAAAgMshAAEAAJdDAAIAAC6HAAQAAFwOAQgAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDL8XB2AUbLzMzUv/71L23evFmpqalq0qSJxowZozZt2ji7NAAAUEFUuTNAc+bM0erVq3X//ffrySeflJubm6ZNm6bDhw87uzQAAFBBVKkAdOzYMW3dulXjxo3TE088oejoaL3xxhuqW7euFi1a5OzyAABABVGlAlBcXJzc3d0VHR1tb/Py8tKDDz6oo0eP6tKlS06sDgAAVBRVKgCdOnVKDRo0kI+PT7725s2bS5JOnz7tjLIAAEAFU6UWQScnJysoKKhAe15bUlJSofslJSUpOTnZ/jkvKCUkJBheY8rFNCVnJurM2dNKzvQ1fHwAACq6sv67MDQ0VNWrV79tnyoVgKxWq6pVq1ag3dPT0769MOvWrdPSpUsLtM+ePdvQ+n7pv8+X2dAAAFQKZfV34ZIlSxQREXHbPlUqAHl5eSkrK6tAe2Zmpn17YaKjo9WpUyf759TUVCUkJGjr1q2aPHlysed/8803NWnSpNv2SUhI0OzZs/Xss88qNDS02GNXZcX5vTmLM2orizmNGrM04ziyb0n34Rh0TEU+BqXyr6+s5nOF47C4fcv6OCzOmFUqAAUFBenKlSsF2vMub5nN5kL3M5vNBbbdd9992rdv328myF/y9fUtdv/Q0NASjV2VleT3Vt6cUVtZzGnUmKUZx5F9S7oPx6BjKvIxKJV/fWU1nyschyUd35nHYZVaBB0eHq6ffvpJN2/ezNd+7Ngx+/aS6NWrV5n2xy0V+ffmjNrKYk6jxizNOI7syzFYPir676286yur+VzhOKzo/y/9kslms9mcXYRRjh07pvHjx+vxxx/XsGHDJN26/DVy5EgFBATonXfecXKF0smTJzV27NhiXZ8EYDyOQcD5KsJxWKUugbVo0UI9evTQu+++q5SUFAUHBys2NlaJiYl65plnnF2epFuX6UaNGlXo3WoAyh7HIOB8FeE4rFJngKRbd3rlvQssLS1NjRs31pgxY9S2bVtnlwYAACqIKheAAAAAfkuVWgQNAABQHASgCiYzM1Nz587VwIED1adPH40fP15HjhxxdlmAS3nllVfUv39/9enTRyNHjtTOnTudXRLgso4cOaJu3bpp2bJlho7LJbAKJiMjQ6tWrVLfvn1Vq1Ytbdu2TW+88YZWrVqlGjVqOLs8wCUkJCSoXr168vT01PHjxxUTE6OVK1cqICDA2aUBLiU3N1dPPPGEbDabOnbsqJEjRxo2NmeAKhhvb2+NGjVKderUkZubm6KiouTh4aHz5887uzTAZYSGhtpfoWMymZSVlVXkuwQBlJ3169erefPmZfK06Cp1G7wzpKena+XKlTp27JiOHz+u1NRUzZgxQ3379i3QNzMz036HWmpqqpo0aaIxY8aoTZs2RY5//vx5paamKjg4uCy/BlBpldUx+Prrr2vDhg3KzMxU+/bt1bhx4/L4OkClVBbH4fXr1/Xxxx9r0aJFevPNNw2vmTNApXT9+nUtXbpUCQkJv/mk6Tlz5mj16tW6//779eSTT8rNzU3Tpk3T4cOHC+1vtVo1e/ZsPfLII/L15c3xQGHK6hiMiYnRpk2bNG/ePLVp00Ymk6msvgJQ6ZXFcbhkyRINGjRIfn5+ZVO0DaVitVptSUlJNpvNZjt+/LitS5cutg0bNhTod/ToUVuXLl1sH374ob3NYrHYhg4dahs/fnyB/llZWbZp06bZZs2aZcvNzS27LwBUcmV1DP7SM888Y9u1a5exhQNViNHH4cmTJ22PPvqoLTs722az2WwvvPCCbenSpYbWzBmgUvL09CzWkyzj4uLk7u6u6Ohoe5uXl5cefPBBHT16VJcuXbK35+bmavbs2TKZTPrrX//KvzyB2yiLY/DXcnJydOHCBUPqBaoio4/DQ4cO6fz58xowYID69++vr776Sh9++KHmzJljWM2sASonp06dUoMGDeTj45OvvXnz5pKk06dPq06dOpKkV199VcnJyXr11Vfl4cF/IsAIxT0G09LS9O2336pTp07y9PTU119/rYMHD2rcuHHOKBuoUop7HEZHRysqKsq+fcGCBapXr54eeeQRw2rhb9dykpycXGg6zmvLu8MkMTFRX3zxhTw9PfMl5JdfflmtW7cun2KBKqi4x6DJZNIXX3yhefPmyWazKTg4WM8995yaNm1arvUCVVFxj8Pq1aurevXq9u1eXl7y9vY2dD0QAaicWK1WVatWrUB73q22VqtVklS3bl3t2LGjXGsDXEFxj0EfHx/Nnz+/XGsDXEVxj8Nf++tf/2p4LawBKideXl7Kysoq0J6ZmWnfDqDscAwCzleRjkMCUDkJCgpScnJygfa8NrPZXN4lAS6FYxBwvop0HBKAykl4eLh++ukn3bx5M1/7sWPH7NsBlB2OQcD5KtJxSAAqJ927d1dOTo7WrVtnb8vMzNSGDRvUokUL+x1gAMoGxyDgfBXpOGQRtAE++eQTpaWl2U/h7dy5U5cvX5YkDRgwQL6+vmrRooV69Oihd999VykpKQoODlZsbKwSExP1zDPPOLN8oNLjGAScr7Idh7wN3gCDBw9WYmJiodtWrVqlevXqSbq1uj3v/SdpaWlq3LixxowZo7Zt25ZnuUCVwzEIOF9lOw4JQAAAwOWwBggAALgcAhAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAFCEjRs3qmvXrvafmTNnFtpvyZIl6tq1q+Lj48u3wF9JSEjIV+/gwYOdWg9QkXk4uwAAFcfPP/+sIUOG3LZP3bp1tXr16nKqqGLo3LmzwsPD1bhx40K3f//993Jzc1PTpk0Nm3PDhg2aO3euHn30UY0cObLIflarVX/84x915coVzZs3T6NGjZIkrVmzxrBagKqIAASggODgYN1///2FbvP19S3napyvS5cu6tu3b5HbT506pZCQEFWvXt2wOfPC1g8//HDbfitXrlRiYqL69++vyMhIRUZGSpJiY2MNqwWoighAAAoIDg7Wn//8Z2eXUSkkJSXp6tWr+r//+z9Dx23UqJHc3Nz0448/3nbuDz/8UP7+/hozZoyh8wNVHWuAADjs4MGD6tq1q/7973/rxIkTiomJ0QMPPKC+ffvqb3/7m37++edC9zt06JCmT5+uhx9+WFFRURo2bJiWLFkii8VS5Pjx8fGKiYlRv3791LVrV3uf7OxsrVixQkOHDlWvXr00bNgwrVixQhcvXlTXrl314osv2vvu379fXbt21euvv15oXRcuXFC3bt301FNPFft3cOrUKUlSs2bN8rUnJCToT3/6kx544AFt3brV3p6Tk6P//ve/mjRpkvr27atevXppzJgxiouLy7e/l5eXgoOD9dNPPyk7O7vQuRcvXqyMjAyNGTNG/v7+xa4ZAAEIgAFOnDihSZMmycPDQ9HR0YqIiNDXX3+tmJgYWa3WfH0///xzTZ48WfHx8Wrfvr0GDBig2rVra/ny5YqJiVFWVlaB8Y8cOaLJkyfLZDLp4YcfVs+ePe3bXnrpJb377ruSpP79+6tt27ZavXq1FixYUGCc//u//1NwcLC+/PLLAmFLkr744gvZbDY9/PDDxf7uhQWgrVu3aty4ccrOztaiRYsUFRUl6dZ6naefflovvfSS0tPT1bdvX/Xt21eXLl3Sc889p82bN+cbu3HjxsrOzlZCQkKBeY8dO6bNmzcrPDy8RPUCuIVLYAAKuHDhgv79738Xuq1ly5Zq165dvrbdu3fr+eeft/9FL0kvvPCCNm3apG+++cbefvbsWc2fP19NmjTRvHnzFBAQYO+/YsUKvfvuu/rkk080dOjQfOPv379f06dPV79+/fK1HzhwQJs2bVLTpk311ltv2dfg/PGPfyz0klBegHrnnXe0bdu2fOt6srOzFRsbqzvuuEOdO3cuzq9J0q0F0CaTSU2bNlV2drbeeustffLJJ+rUqZP+9re/5Vsz9dJLL+nAgQOaPHmyBgwYYG8fOXKkRo8erffee0+9e/e2tzdp0kRxcXE6e/asmjRpkm/eN998UzabTZMnT5a7u3ux6wVwC2eAABRw4cIFLV26tNCfPXv2FOjfunXrfOFHkj2sHD9+3N62du1a5eTkaPLkyfnCjyQNHz5cgYGB+S4X5WnWrFmB8CPJfsZk5MiR+RYgm81mDRw4sNDv1q9fP1WrVk3//e9/87V/++23Sk5OVp8+feThUfx/G546dUr169fXzZs3NWnSJH322Wd69NFH9eKLL+YLPwcOHNCXX36p6OjofOEnr9727dsrMTFRKSkp9vaiFkJv2bJFR48eVVRUlFq3bl3sWgH8D2eAABTQtm1bvfrqq8XuHxERUaCtVq1akqS0tDR727FjxyRJe/fu1YEDBwrs4+HhoXPnzhVov/POOwud9/Tp05Kku+++u8C2u+66q9B9AgMD1bVrV23dulUJCQkKDQ2VJHsgeuihhwrdrzCpqan6+eefFRwcrDFjxshms+nll19W27ZtC/T99NNPJUm5ubmFnl3Lu8yVm5trb8s76/PLhdAWi0XvvPOOvL299fjjjxe7VgD5EYAAlFqNGjUKtOVdlvnlX+g3btyQJC1fvrxE49esWbPQ9vT0dLm5uRU4m3S7fSQpOjpaW7du1RdffKEJEyYoKSlJe/bsUWRkpEJCQopdV976n9TUVN24cUMjR44sNPxIty7jSbfWGRXF09NTgYGB9s/169eXt7d3vgD04Ycf6sqVKxo7dqxq165d7FoB5EcAAlBufHx8JN16Rk1hoamkatSoodzcXF2/fj1fcJCkq1evFrnfPffco4YNG2rTpk0aN26cNmzYoJycnBKd/ZH+F4CmTZumjz76SCtWrFCLFi3UoUOHfP1SU1OVkZGhzp0757sr7beYTCaFhYXp5MmTslgsunHjhlauXKng4ODffGAlgNtjDRCActOiRQtJ0tGjRw0ZLzw8XJIKfQXFkSNHbrtvdHS0UlJS9PXXX2vDhg3y8/NTt27dSjR/XgBq0aKFXnzxRdWqVUszZ860X5r7tevXr5dofOnWZbDc3FydPXtW77zzjiwWiyZOnChPT88SjwXgfwhAAMpN//795e7urvnz5+vSpUsFtqempur7778v9nh5T6teunRpvtvtk5OTf/NVEH369JGnp6cWLlyoixcvqnfv3vLy8ir23NKtO8Bq1qwps9msO+64Q3PnzpWbm5ueeeYZJSUl2fv5+fmpQYMGOnbsWKFrn7KysooMbHkLob/44gt9+eWXateunTp16lSiOgEUxCUwAAXc7jZ4SXrkkUdKHBakW3+Zx8TE6PXXX9cjjzyi9u3bKzg4WOnp6bp48aK+++479enTR08//XSxxrvvvvvUq1cvffnllxo1apQ6d+6srKwsbdu2Tc2bN9euXbvk5lb4v/P8/f3Vo0cPbdq0SZJK/Cwdq9Wq8+fP53sCdOPGjfX8889rxowZmj59uhYuXGi/O+3xxx/Xc889p6eeekrt27dXaGioLBaLrly5ovj4eLVt27bQhdt5C6HXrVsnDw8PTZo0qUR1AigcAQhAAXm3wRdl0KBBDgUg6VbQCA8P1+rVq/Xdd99p165d8vHxUZ06dTRo0CD16dOnROP99a9/VWhoqDZs2KBPP/1UtWrV0qBBg3Tvvfdq165dt11r1KdPH23atEktW7Ys8kWnRTlz5oxycnLsl+HytG/fXhMnTtT8+fP1j3/8Q7Nnz5abm5u6dOmiN954Qx999JGOHj2qPXv2yN/fX7Vr11a/fv2KfNfYL+saOHCgGjZsWKI6ARTOZLPZbM4uAgCM9sUXX+jll19WTEyM+vfvX2ifjz76SIsWLdIzzzyjBx98sMD2jRs3as6cOZoxY8ZtX4ZaEQ0ePFiStHr1aidXAlRMrAECUKklJyfr1/+Ou3Lliv7zn//I3d29wB1ZeaxWqz777DP5+fkVeIjjr82ZM0ddu3bVzJkzjSq7TCQkJKhr167q2rWrEhMTnV0OUKFxCQxApfbBBx/o22+/VevWrRUYGKjLly9r165dSk9P1+jRo1WnTp18/Q8fPqxDhw5p7969SkxM1Lhx4/I9RfqXwsPDNWrUKPvnkl4mK28BAQH56v3lk6gB5MclMACV2p49e7Rq1SqdOXNGqamp8vT0VJMmTdS/f3/7XWK/9O9//1tLly5VQECAHnjgAY0fP75Er74AUDUQgAAAgMthDRAAAHA5BCAAAOByCEAAAMDlEIAAAIDLIQABAACXQwACAAAuhwAEAABcDgEIAAC4HAIQAABwOQQgAADgcghAAADA5fx/mXPbp8glsIcAAAAASUVORK5CYII=", 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\n", 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", "text/plain": [ "
" ] @@ -1011,9 +2241,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python [conda env:cosi_nomegalib]", + "display_name": "cosipy", "language": "python", - "name": "conda-env-cosi_nomegalib-py" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1025,7 +2255,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.10.13" } }, "nbformat": 4, From 35b8293b6017df2ebd927a4dfb77870108895fdc Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Thu, 24 Oct 2024 10:14:25 -0700 Subject: [PATCH 12/46] Create LMDR.ipynb and add response creation attempt with h5py. Switching to histpy.Histogram() --- cosipy/response/FullDetectorResponse.py | 1 + ...1keV-DC2-Galactic-ImageDeconvolution.ipynb | 80 +- .../imagedeconvolution_parfile_gal_511keV.yml | 4 +- .../tutorials/response/DetectorResponse.ipynb | 1103 ++++++++++++----- docs/tutorials/response/LMDR.ipynb | 766 ++++++++++++ .../Point_source_injector.ipynb | 304 ++++- .../continuum_fit/crab/SpectralFit_Crab.ipynb | 10 +- 7 files changed, 1839 insertions(+), 429 deletions(-) create mode 100644 docs/tutorials/response/LMDR.ipynb diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py index e4a10050..71f4ffb9 100644 --- a/cosipy/response/FullDetectorResponse.py +++ b/cosipy/response/FullDetectorResponse.py @@ -1,5 +1,6 @@ from .PointSourceResponse import PointSourceResponse from .DetectorResponse import DetectorResponse +from .ListModeResponse import ListModeResponse from astromodels.core.model_parser import ModelParser import matplotlib.pyplot as plt from astropy.time import Time diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb index f8f62c51..aae99afa 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/511keV-DC2-Galactic-ImageDeconvolution.ipynb @@ -790,7 +790,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "id": "5fa73486", "metadata": {}, "outputs": [], @@ -800,10 +800,22 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "id": "a4b47308-3e13-400d-bebc-b5d1e093201d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'ImageDeconvolution' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m image_deconvolution \u001b[38;5;241m=\u001b[39m \u001b[43mImageDeconvolution\u001b[49m()\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# set data_interface to image_deconvolution\u001b[39;00m\n\u001b[1;32m 4\u001b[0m image_deconvolution\u001b[38;5;241m.\u001b[39mset_dataset([data_interface])\n", + "\u001b[0;31mNameError\u001b[0m: name 'ImageDeconvolution' is not defined" + ] + } + ], "source": [ "image_deconvolution = ImageDeconvolution()\n", "\n", @@ -861,64 +873,24 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 1, "id": "879053e3-ac7b-4a0a-ad58-24e3fb137065", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "#### Initialization Starts ####\n", - "<< Instantiating the model class AllSkyImage >>\n", - "---- parameters ----\n", - "coordinate: galactic\n", - "energy_edges:\n", - " unit: keV\n", - " value:\n", - " - 509.0\n", - " - 513.0\n", - "nside: 16\n", - "scheme: ring\n", - "unit: cm-2 s-1 sr-1\n", - "\n", - "<< Setting initial values of the created model object >>\n", - "---- parameters ----\n", - "algorithm: flat\n", - "parameter:\n", - " unit: cm-2 s-1 sr-1\n", - " value:\n", - " - 1e-4\n", - "\n", - "<< Registering the deconvolution algorithm >>\n", - "A directory ./results already exists. Files in ./results may be overwritten. Make sure that is not a problem.\n", - "---- parameters ----\n", - "algorithm: RLparallel\n", - "parameter:\n", - " acceleration: true\n", - " alpha_max: 10.0\n", - " background_normalization_optimization: true\n", - " background_normalization_range:\n", - " albedo:\n", - " - 0.01\n", - " - 10.0\n", - " iteration_max: 50\n", - " numproc: 6\n", - " response_weighting: true\n", - " response_weighting_index: 0.5\n", - " save_results: true\n", - " save_results_directory: ./results\n", - " smoothing: true\n", - " smoothing_FWHM:\n", - " unit: deg\n", - " value: 2.0\n", - "\n", - "#### Initialization Finished ####\n" + "ename": "NameError", + "evalue": "name 'image_deconvolution' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mimage_deconvolution\u001b[49m\u001b[38;5;241m.\u001b[39m_deconvolution\u001b[38;5;241m.\u001b[39minitialize()\n", + "\u001b[0;31mNameError\u001b[0m: name 'image_deconvolution' is not defined" ] } ], "source": [ - "image_deconvolution.initialize()" + "image_deconvolution._deconvolution.initialize()" ] }, { @@ -1583,7 +1555,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "cosipy", "language": "python", "name": "python3" }, diff --git a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml index 1577573d..b084a316 100644 --- a/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml +++ b/docs/tutorials/image_deconvolution/511keV/GalacticCDS/imagedeconvolution_parfile_gal_511keV.yml @@ -20,10 +20,10 @@ model_definition: unit: "cm-2 s-1 sr-1" # do not change it as for now deconvolution: - algorithm: "RL" # Choose from RL, RLsimple and RLparallel + algorithm: "RLparallel" # Choose from RL, RLsimple and RLparallel parameter: - iteration_max: 50 + iteration_max: 10 acceleration: True alpha_max: 10.0 response_weighting: True diff --git a/docs/tutorials/response/DetectorResponse.ipynb b/docs/tutorials/response/DetectorResponse.ipynb index 2ece2fa6..59701546 100644 --- a/docs/tutorials/response/DetectorResponse.ipynb +++ b/docs/tutorials/response/DetectorResponse.ipynb @@ -33,263 +33,7 @@ "execution_count": 1, "id": "366b09f0-aff2-47cd-93ee-2dcff45185e5", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
10:44:04 WARNING   The naima package is not available. Models that depend on it will not be         functions.py:48\n",
-       "                  available                                                                                        \n",
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-       "                  performances in 3ML                                                                              \n",
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-       "                  performances in 3ML                                                                              \n",
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Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=400489;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=161444;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", - "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# %%capture\n", "import numpy as np\n", @@ -307,7 +51,7 @@ "from pathlib import Path\n", "\n", "from scoords import Attitude, SpacecraftFrame\n", - "from cosipy.response import FullDetectorResponse\n", + "from cosipy.response import FullDetectorResponse, ListModeResponse\n", "from cosipy.spacecraftfile import SpacecraftFile\n", "from cosipy import test_data\n", "from cosipy.util import fetch_wasabi_file\n", @@ -344,8 +88,8 @@ "source": [ "data_dir = Path(\"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data\") # Current directory by default. Modify if you can want a different path\n", "\n", - "ori_path = data_dir/\"20280301_3_month.ori\"\n", - "response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\"\n", + "ori_path = data_dir / \"20280301_3_month.ori\"\n", + "response_path = data_dir / \"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\"\n", "\n", "# download orientation file ~684.38 MB\n", "if not ori_path.exists():\n", @@ -390,7 +134,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\n" + "/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\n" ] } ], @@ -420,7 +164,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "FILENAME: '/Users/imartin5/software/cosipy/docs/tutorials/response/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5'\n", + "FILENAME: '/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5'\n", "AXES:\n", " NuLambda:\n", " DESCRIPTION: 'Location of the simulated source in the spacecraft coordinates'\n", @@ -459,7 +203,7 @@ "source": [ "with FullDetectorResponse.open(response_path) as response:\n", "\n", - " print(repr(response))" + " print(repr(response)) # Their a function method `__repr__` that gets invoked by this built in python utility `repr`" ] }, { @@ -488,7 +232,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "cad81d6b-7c7b-41d5-9868-da58d25d4a3d", "metadata": {}, "outputs": [ @@ -499,17 +243,22 @@ "NSIDE = 8\n", "SCHEME = RING\n", "NPIX = 768\n", - "Pixel size = 7.33 deg\n" + "Pixel size = 7.33 deg\n", + "\n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", - " \n", + " # XXX: What is DRM? Detector Response \"Matrix\"?\n", + " # XXX: Shouldn't sparse be set to False by default? l.109 FullDetectorResponse.py\n", " print(f\"NSIDE = {response.nside}\")\n", " print(f\"SCHEME = {response.scheme}\")\n", " print(f\"NPIX = {response.npix}\")\n", - " print(f\"Pixel size = {np.sqrt(response.pixarea()).to(u.deg):.2f}\")" + " print(f\"Pixel size = {np.sqrt(response.pixarea()).to(u.deg):.2f}\")\n", + " print(response.axes) # XXX: Why is a list `axes` converted to object of type `histpy.axes.Axes`?\n", + " # XXX: What is the difference between `HealpixAxis` and `Axis`\n", + " # XXX: Variable name `new` is annoying in method open_h5()" ] }, { @@ -522,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "id": "d4972c53-f653-4694-8190-8524362b6ef7", "metadata": {}, "outputs": [ @@ -537,14 +286,566 @@ ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", - " \n", + " # pix2skycoord is returned by constructor of class `HealpixBase` which is a method under `mhealpy` \n", " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", " drm = response[0]" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 11, + "id": "c470f476", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_axes': ,\n", + " '_sparse': False,\n", + " '_contents': array([[[[0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n", + " [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n", + " [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n", + " ...,\n", + " [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n", + " [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n", + " [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " 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" '_sumw2': None,\n", + " 'sumw2': None,\n", + " 'bin_error': ,\n", + " 'slice': ,\n", + " '_spec': None,\n", + " '_aeff': None}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drm.__dict__" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "id": "5d4c8849", "metadata": {}, "outputs": [ @@ -557,7 +858,7 @@ "Unit(\"cm2\")" ] }, - "execution_count": 25, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -568,7 +869,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "id": "6acc1e23", "metadata": {}, "outputs": [ @@ -578,7 +879,7 @@ "['DRM']" ] }, - "execution_count": 4, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -592,7 +893,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 13, "id": "e8adf052", "metadata": {}, "outputs": [ @@ -602,7 +903,7 @@ "['AXES', 'CONTENTS']" ] }, - "execution_count": 6, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -613,7 +914,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 14, "id": "6f45fb1d", "metadata": {}, "outputs": [ @@ -623,7 +924,7 @@ "['NuLambda', 'Ei', 'Em', 'Phi', 'PsiChi']" ] }, - "execution_count": 8, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -634,7 +935,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 80, "id": "54a9ba60", "metadata": {}, "outputs": [ @@ -703,7 +1004,7 @@ " 767, 768])" ] }, - "execution_count": 21, + "execution_count": 80, "metadata": {}, "output_type": "execute_result" } @@ -714,7 +1015,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "id": "5fa04060", "metadata": {}, "outputs": [ @@ -724,7 +1025,7 @@ "(768, 10, 10, 36, 768)" ] }, - "execution_count": 12, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -733,6 +1034,27 @@ "hf['DRM/CONTENTS'].shape" ] }, + { + "cell_type": "code", + "execution_count": 232, + "id": "eca1e06b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.00591716, 0.00196464, -0.00195695, -0.00584795, -0.00970874])" + ] + }, + "execution_count": 232, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(510 - Ei)/Ei" + ] + }, { "cell_type": "markdown", "id": "9bf2f221-0300-4dd1-8dc7-eb4e0e694997", @@ -743,14 +1065,72 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 64, "id": "5a621225-5619-4d43-9670-b4bd03b1d801", "metadata": {}, "outputs": [], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", - " \n", - " drm = response.get_interp_response(SkyCoord(lon = 0*u.deg, lat = 0*u.deg, frame = SpacecraftFrame()))" + " # XXX: How is SpacecraftFrame object defined here?\n", + " drm = response.get_interp_response(SkyCoord(lon = 0*u.deg, lat = 0*u.deg, frame = SpacecraftFrame()))\n", + " drm2 = response.get_interp_response(SkyCoord(lon = 0*u.deg, lat = 3*u.deg, frame = SpacecraftFrame()))\n", + " drm3 = response.get_interp_response(SkyCoord(lon = 0*u.deg, lat = 90*u.deg, frame = SpacecraftFrame()))" + ] + }, + { + "cell_type": "markdown", + "id": "7f3a52b9", + "metadata": {}, + "source": [ + "Get the interpolated effective area" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "ee6698a7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$6.3406481 \\; \\mathrm{cm^{2}}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drm.get_effective_area(511 * u.keV)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "144564c3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$99.27511 \\; \\mathrm{cm^{2}}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drm3.get_effective_area(511 * u.keV) # XXX: Why is effective area increasing dramatically towards +90 deg but not symmetrically towards -90 deg?" ] }, { @@ -763,7 +1143,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 17, "id": "6680c76c-3483-462e-bb40-5a00b282cdba", "metadata": {}, "outputs": [ @@ -773,15 +1153,37 @@ "array(['Ei', 'Em', 'Phi', 'PsiChi'], dtype=',\n", + " )" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "You can further project it into the initial energy to get the effective area:" + "drm2.get_spectral_response().plot() # NOTE: Inference: Slight difference in colorbar limits for (l,b)=(0,0) and (0,3). Overall structure looks the same. \n", + " # Difference is probably due to exposure but could also be due to something else" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "a20f628e-b891-4dcb-b305-8a94c01f2d4a", + "execution_count": null, + "id": "8e2f6be1", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -837,62 +1265,103 @@ } ], "source": [ - "ax,plot = drm.get_effective_area().plot();\n", - "\n", - "ax.set_ylabel(f'Aeff [{drm.unit}]');" + "drm.get_dispersion_matrix().plot();" ] }, { - "cell_type": "markdown", - "id": "64edb047-2d80-4011-9fa3-665a1bdd282e", + "cell_type": "code", + "execution_count": 21, + "id": "43fa0c3d", "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Get the interpolated effective area" + "# XXX: What is the difference between spectral response plot and this dispersion matrix plot?\n", + "drm.get_dispersion_matrix().plot()" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "6ad17044-46a6-4646-b5d2-1cec399228f2", + "execution_count": 23, + "id": "28cba543", "metadata": {}, "outputs": [ { "data": { - "text/latex": [ - "$6.3406481 \\; \\mathrm{cm^{2}}$" - ], "text/plain": [ - "" + "(,\n", + " )" ] }, - "execution_count": 11, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "drm.get_effective_area(511*u.keV)" + "drm2.get_dispersion_matrix().plot()" ] }, { "cell_type": "markdown", - "id": "983b731f-1dad-434a-8430-544c76b0e862", + "id": "f37ad594-0be7-41f0-b7ec-16e2251a78b8", "metadata": {}, "source": [ - "Or the energy dispersion matrix" + "You can further project it into the initial energy to get the effective area:" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "2003abb9-c2a5-487f-b869-f0e4b46bc053", + "execution_count": 30, + "id": "a20f628e-b891-4dcb-b305-8a94c01f2d4a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "
" + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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+       "                  software installed and configured?                                                               \n",
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+       "                  software installed and configured?                                                               \n",
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10:03:51 WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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         WARNING   Env. variable OMP_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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ply\n", + "\n", + "from mhealpy import HealpixMap, HealpixBase\n", + "import pandas as pd\n", + "from pathlib import Path\n", + "\n", + "from scoords import Attitude, SpacecraftFrame\n", + "from cosipy.response import FullDetectorResponse, ListModeResponse\n", + "from cosipy.spacecraftfile import SpacecraftFile\n", + "from cosipy import test_data\n", + "from cosipy.util import fetch_wasabi_file\n", + "from histpy import Histogram\n", + "import gc\n", + "\n", + "from threeML import Model, Powerlaw\n", + "\n", + "from cosipy.response import FullDetectorResponse" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"Unable to synchronously open object (object 'hist' doesn't exist)\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)\n", + "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n", + "\u001b[0;32m----> 1\u001b[0m image_response \u001b[38;5;241m=\u001b[39m \u001b[43mHistogram\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", + "\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/histpy/histogram.py:1847\u001b[0m, in \u001b[0;36mHistogram.open\u001b[0;34m(cls, filename, name)\u001b[0m\n", + "\u001b[1;32m 1837\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n", + "\u001b[1;32m 1838\u001b[0m \u001b[38;5;124;03mRead histogram from disk.\u001b[39;00m\n", + "\u001b[1;32m 1839\u001b[0m \n", + "\u001b[0;32m (...)\u001b[0m\n", + "\u001b[1;32m 1842\u001b[0m \u001b[38;5;124;03m name (str): Name of group where the histogram was saved.\u001b[39;00m\n", + "\u001b[1;32m 1843\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n", + "\u001b[1;32m 1845\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m h5\u001b[38;5;241m.\u001b[39mFile(filename, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n", + "\u001b[0;32m-> 1847\u001b[0m hist_group \u001b[38;5;241m=\u001b[39m \u001b[43mf\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\n", + "\u001b[1;32m 1849\u001b[0m unit \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "\u001b[1;32m 1850\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124munit\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m hist_group\u001b[38;5;241m.\u001b[39mattrs:\n", + "\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/group.py:357\u001b[0m, in \u001b[0;36mGroup.__getitem__\u001b[0;34m(self, name)\u001b[0m\n", + "\u001b[1;32m 355\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid HDF5 object reference\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[1;32m 356\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(name, (\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m)):\n", + "\u001b[0;32m--> 357\u001b[0m oid \u001b[38;5;241m=\u001b[39m \u001b[43mh5o\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_lapl\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[1;32m 358\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAccessing a group is done with bytes or str, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n", + "\u001b[1;32m 360\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnot \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mtype\u001b[39m(name)))\n", + "\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "\n", + "File \u001b[0;32mh5py/h5o.pyx:189\u001b[0m, in \u001b[0;36mh5py.h5o.open\u001b[0;34m()\u001b[0m\n", + "\n", + "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open object (object 'hist' doesn't exist)\"" + ] + } + ], + "source": [ + "image_response = Histogram.open('transformed_response_example.h5')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Creating example response file" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0. , 0. , 0. , 0.12, 0.88],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0.88, 0.12, 0. , 0. , 0. ]])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lmfit.lineshapes import gaussian\n", + "\n", + "Ei = np.array([507, 509, 511, 513, 515])\n", + "\n", + "R = np.zeros((5,5))\n", + "for i in np.arange(5):\n", + " Z = gaussian(x=Ei[i], center=Ei)\n", + " R[i, :] = np.round(Z / np.sum(Z), 2)\n", + "\n", + "for i in range(1,4):\n", + " R[i,i] -= 0.01\n", + "\n", + "R[::-1, :]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Axis NuLambda has 3 bins\n", + "Axis Ei has 5 bins\n", + "Axis Em has 5 bins\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]],\n", + "\n", + " [[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]],\n", + "\n", + " [[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]]])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "h = Histogram([np.arange(4), np.arange(506, 517, 2), np.arange(506, 517, 2)], contents=np.stack([R, R, R]), labels=['NuLambda', 'Ei', 'Em'])\n", + "# h = Histogram([np.arange(506, 517, 2), np.arange(506, 517, 2)], contents=R, labels=['Ei', 'Em'])\n", + "\n", + "for axis in h.axes:\n", + " print(f\"Axis {axis.label} has {axis.nbins} bins\")\n", + "\n", + "h.contents" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "h.project('Ei', 'Em').draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m response:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(response[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:85\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 81\u001b[0m filename \u001b[38;5;241m=\u001b[39m Path(filename)\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filename\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.h5\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 85\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_h5\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(filename\u001b[38;5;241m.\u001b[39msuffixes[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.rsp.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:108\u001b[0m, in \u001b[0;36mFullDetectorResponse._open_h5\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m 104\u001b[0m new\u001b[38;5;241m.\u001b[39m_file \u001b[38;5;241m=\u001b[39m h5\u001b[38;5;241m.\u001b[39mFile(filename, mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 106\u001b[0m new\u001b[38;5;241m.\u001b[39m_drm \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_file[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m new\u001b[38;5;241m.\u001b[39m_unit \u001b[38;5;241m=\u001b[39m u\u001b[38;5;241m.\u001b[39mUnit(\u001b[43mnew\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_drm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUNIT\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 111\u001b[0m new\u001b[38;5;241m.\u001b[39m_sparse \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_drm\u001b[38;5;241m.\u001b[39mattrs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSPARSE\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/attrs.py:56\u001b[0m, in \u001b[0;36mAttributeManager.__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[38;5;129m@with_phil\u001b[39m\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name):\n\u001b[1;32m 54\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Read the value of an attribute.\u001b[39;00m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 56\u001b[0m attr \u001b[38;5;241m=\u001b[39m \u001b[43mh5a\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_id\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 57\u001b[0m shape \u001b[38;5;241m=\u001b[39m attr\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 59\u001b[0m \u001b[38;5;66;03m# shape is None for empty dataspaces\u001b[39;00m\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/h5a.pyx:80\u001b[0m, in \u001b[0;36mh5py.h5a.open\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"" + ] + } + ], + "source": [ + "with FullDetectorResponse.open('transformed_response_example.h5') as response:\n", + " print(response['DRM'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f = h5py.File('response_example.h5', mode='w', track_order=True)\n", + "grp = f.create_group('DRM')\n", + "\n", + "dset_contents = grp.create_dataset('CONTENTS', shape=(3,5,5), dtype=float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "grp_axes = grp.create_group('AXES', track_order=True)\n", + "\n", + "# 1 more than shape of contents dataset\n", + "dset_axis_NL = grp_axes.create_dataset('NuLambda', shape=4, dtype=float)\n", + "dset_axis_Ei = grp_axes.create_dataset('Ei', shape=6, dtype=float)\n", + "dset_axis_Em = grp_axes.create_dataset('Em', shape=6, dtype=float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "('/DRM/CONTENTS', '/DRM/CONTENTS')" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dset_contents.name, hf['DRM/CONTENTS'].name" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f['DRM/AXES/NuLambda'][:] = np.arange(4)\n", + "f['DRM/AXES/Ei'][:] = np.arange(506, 517, 2)\n", + "f['DRM/AXES/Em'][:] = np.arange(506, 517, 2)\n", + "\n", + "for i in range(3):\n", + " f['DRM/CONTENTS'][i, :, :] = R" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['NuLambda', 'Ei', 'Em']" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "list(f['DRM/AXES'].keys())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]],\n", + "\n", + " [[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]],\n", + "\n", + " [[0.88, 0.12, 0. , 0. , 0. ],\n", + " [0.11, 0.78, 0.11, 0. , 0. ],\n", + " [0. , 0.11, 0.78, 0.11, 0. ],\n", + " [0. , 0. , 0.11, 0.78, 0.11],\n", + " [0. , 0. , 0. , 0.12, 0.88]]])" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f['DRM/CONTENTS'][:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([506., 508., 510., 512., 514., 516.])" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f['DRM/AXES/Em'][:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f = h5py.File('transformed_response_example.h5', mode='w', track_order=True)\n", + "grp = f.create_group('DRM')\n", + "\n", + "dset_contents = grp.create_dataset('CONTENTS', shape=(3,5,5), dtype=float)\n", + "grp_axes = grp.create_group('AXES', track_order=True)\n", + "\n", + "# 1 more than shape of contents dataset\n", + "dset_axis_NL = grp_axes.create_dataset('NuLambda', shape=4, dtype=float)\n", + "dset_axis_Ei = grp_axes.create_dataset('Ei', shape=6, dtype=float)\n", + "dset_axis_Em = grp_axes.create_dataset('Em', shape=6, dtype=float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "e_col = np.linspace(-0.0075, 0.0075, 6)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[503.958 505.946 507.934 509.922 511.91 ]\n", + "[505.479 507.473 509.467 511.461 513.455]\n", + "[507. 509. 511. 513. 515.]\n", + "[508.521 510.527 512.533 514.539 516.545]\n", + "[510.042 512.054 514.066 516.078 518.09 ]\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[0.01 , 0.01 , 0.01 , 0.01 , 0.01 ],\n", + " [0.19 , 0.19 , 0.19 , 0.19 , 0.185],\n", + " [0.6 , 0.6 , 0.6 , 0.6 , 0.61 ],\n", + " [0.19 , 0.19 , 0.19 , 0.19 , 0.185],\n", + " [0.01 , 0.01 , 0.01 , 0.01 , 0.01 ]])" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(5):\n", + " Em = (e_col[i]+e_col[i+1])/2 * Ei + Ei\n", + " print(Em)\n", + " R[i, :] = gaussian(x=Em, center=Ei)\n", + "\n", + "R /= np.sum(R, axis=0)\n", + "R = np.round(R, 2)\n", + "R[2, :4] = 0.6\n", + "R[2, 4] = 0.61\n", + "R[1:4:2, 4] = 0.185\n", + "\n", + "R[::-1]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f['DRM/AXES/NuLambda'][:] = np.arange(4)\n", + "f['DRM/AXES/Ei'][:] = np.arange(506, 517, 2)\n", + "f['DRM/AXES/Em'][:] = e_col\n", + "\n", + "for i in range(3):\n", + " f['DRM/CONTENTS'][i, :, :] = R" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "f.close()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cosipy", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/tutorials/source_injector/Point_source_injector.ipynb b/docs/tutorials/source_injector/Point_source_injector.ipynb index 1bffb719..2057087b 100755 --- a/docs/tutorials/source_injector/Point_source_injector.ipynb +++ b/docs/tutorials/source_injector/Point_source_injector.ipynb @@ -29,15 +29,15 @@ }, { "cell_type": "code", - "execution_count": 160, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ - "%%capture\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from scipy.interpolate import interp1d\n", "import astropy.units as u\n", + "import pandas as pd\n", "from pathlib import Path\n", "from astropy.coordinates import SkyCoord\n", "from astromodels.functions.function import Function1D, FunctionMeta\n", @@ -54,11 +54,11 @@ }, { "cell_type": "code", - "execution_count": 161, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "data_dir = Path(\"\") # Current directory by default. Modify if you want a different path" + "data_path = Path(\"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data\") # Current directory by default. Modify if you want a different path" ] }, { @@ -75,20 +75,20 @@ "metadata": {}, "outputs": [], "source": [ - "%%capture\n", - "zipped_response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.zip\"\n", - "response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.h5\"\n", + "# %%capture\n", + "# zipped_response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.zip\"\n", + "# response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.h5\"\n", "\n", - "# download response file ~839.62 MB\n", - "if not response_path.exists():\n", + "# # download response file ~839.62 MB\n", + "# if not response_path.exists():\n", " \n", - " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.zip\", zipped_response_path)\n", + "# fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.earthocc.zip\", zipped_response_path)\n", "\n", - " # unzip the response file\n", - " shutil.unpack_archive(zipped_response_path)\n", + "# # unzip the response file\n", + "# shutil.unpack_archive(zipped_response_path)\n", " \n", - " # delete the zipped response to save space\n", - " os.remove(zipped_response_path)" + "# # delete the zipped response to save space\n", + "# os.remove(zipped_response_path)" ] }, { @@ -97,12 +97,12 @@ "metadata": {}, "outputs": [], "source": [ - "%%capture\n", - "orientation_path = data_dir/\"20280301_3_month.ori\"\n", + "# %%capture\n", + "# orientation_path = data_dir/\"20280301_3_month.ori\"\n", "\n", - "# download orientation file ~684.38 MB\n", - "if not orientation_path.exists():\n", - " fetch_wasabi_file(\"COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori\", orientation_path)" + "# # download orientation file ~684.38 MB\n", + "# if not orientation_path.exists():\n", + "# fetch_wasabi_file(\"COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori\", orientation_path)" ] }, { @@ -128,17 +128,27 @@ }, { "cell_type": "code", - "execution_count": 164, + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "response_path = data_path / \"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\"\n", + "orientation_path = data_path / \"20280301_3_month.ori\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
21:42:22 WARNING   The current value of the parameter beta (-2.0) was above the new maximum -2.15. parameter.py:794\n",
+       "
08:06:29 WARNING   The current value of the parameter beta (-2.0) was above the new maximum -2.15. parameter.py:794\n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[38;5;46m21:42:22\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The current value of the parameter beta \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;37m-2.0\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m was above the new maximum \u001b[0m\u001b[1;37m-2.15\u001b[0m\u001b[1;38;5;251m.\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=842829;file:///Users/krishnatejavedula/miniconda3/envs/COSI-SI/lib/python3.10/site-packages/astromodels/core/parameter.py\u001b\\\u001b[2mparameter.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=333730;file:///Users/krishnatejavedula/miniconda3/envs/COSI-SI/lib/python3.10/site-packages/astromodels/core/parameter.py#794\u001b\\\u001b[2m794\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[38;5;46m08:06:29\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The current value of the parameter beta \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;37m-2.0\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m was above the new maximum \u001b[0m\u001b[1;37m-2.15\u001b[0m\u001b[1;38;5;251m.\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=652798;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/core/parameter.py\u001b\\\u001b[2mparameter.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=392555;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/core/parameter.py#794\u001b\\\u001b[2m794\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -155,7 +165,7 @@
     "piv_inj = 100. * u.keV\n",
     "K_inj = 7.56e-4 / u.cm / u.cm / u.s / u.keV\n",
     "\n",
-    "spectrum_inj = Band()\n",
+    "spectrum_inj = Band()       # https://astromodels.readthedocs.io/en/latest/notebooks/Band.html\n",
     "\n",
     "spectrum_inj.alpha.min_value = -2.14\n",
     "spectrum_inj.alpha.max_value = 3.0\n",
@@ -174,6 +184,156 @@
     "spectrum_inj.piv.unit = piv_inj.unit"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
    \n",
+       "\n",
+       "
  • description: Band model from Band et al., 1993, parametrized with the peak energy
    • \n",
+       "\n",
+       "
  • formula: $K \\begin{cases} \\left(\\frac{x}{piv}\\right)^{\\alpha} \\exp \\left(-\\frac{(2+\\alpha) x}{x_{p}}\\right) & x \\leq (\\alpha-\\beta) \\frac{x_{p}}{(\\alpha+2)} \\\\ \\left(\\frac{x}{piv}\\right)^{\\beta} \\exp (\\beta-\\alpha)\\left[\\frac{(\\alpha-\\beta) x_{p}}{piv(2+\\alpha)}\\right]^{\\alpha-\\beta} &x>(\\alpha-\\beta) \\frac{x_{p}}{(\\alpha+2)} \\end{cases} $
    • \n",
+       "\n",
+       "
  • default parameters: \n",
+       "
      \n",
+       "\n",
+       "
    • K: \n",
+       "
        \n",
+       "\n",
+       "
      • value: 0.0001
        • \n",
+       "\n",
+       "
      • desc: Differential flux at the pivot energy
        • \n",
+       "\n",
+       "
      • min_value: 1e-50
        • \n",
+       "\n",
+       "
      • max_value: None
        • \n",
+       "\n",
+       "
      • unit: 
        • \n",
+       "\n",
+       "
      • is_normalization: True
        • \n",
+       "\n",
+       "
      • delta: 1e-05
        • \n",
+       "\n",
+       "
      • free: True
        • \n",
+       "\n",
+       "
      \n",
+       "\n",
+       "
      • \n",
+       "\n",
+       "
    • alpha: \n",
+       "
        \n",
+       "\n",
+       "
      • value: -1.0
        • \n",
+       "\n",
+       "
      • desc: low-energy photon index
        • \n",
+       "\n",
+       "
      • min_value: -1.5
        • \n",
+       "\n",
+       "
      • max_value: 3.0
        • \n",
+       "\n",
+       "
      • unit: 
        • \n",
+       "\n",
+       "
      • is_normalization: False
        • \n",
+       "\n",
+       "
      • delta: 0.1
        • \n",
+       "\n",
+       "
      • free: True
        • \n",
+       "\n",
+       "
      \n",
+       "\n",
+       "
      • \n",
+       "\n",
+       "
    • xp: \n",
+       "
        \n",
+       "\n",
+       "
      • value: 499.99999999999994
        • \n",
+       "\n",
+       "
      • desc: peak in the x * x * N (nuFnu if x is a energy)
        • \n",
+       "\n",
+       "
      • min_value: 10.0
        • \n",
+       "\n",
+       "
      • max_value: None
        • \n",
+       "\n",
+       "
      • unit: 
        • \n",
+       "\n",
+       "
      • is_normalization: False
        • \n",
+       "\n",
+       "
      • delta: 50.0
        • \n",
+       "\n",
+       "
      • free: True
        • \n",
+       "\n",
+       "
      \n",
+       "\n",
+       "
      • \n",
+       "\n",
+       "
    • beta: \n",
+       "
        \n",
+       "\n",
+       "
      • value: -2.0
        • \n",
+       "\n",
+       "
      • desc: high-energy photon index
        • \n",
+       "\n",
+       "
      • min_value: -5.0
        • \n",
+       "\n",
+       "
      • max_value: -1.6
        • \n",
+       "\n",
+       "
      • unit: 
        • \n",
+       "\n",
+       "
      • is_normalization: False
        • \n",
+       "\n",
+       "
      • delta: 0.2
        • \n",
+       "\n",
+       "
      • free: True
        • \n",
+       "\n",
+       "
      \n",
+       "\n",
+       "
      • \n",
+       "\n",
+       "
    • piv: \n",
+       "
        \n",
+       "\n",
+       "
      • value: 100.0
        • \n",
+       "\n",
+       "
      • desc: pivot energy
        • \n",
+       "\n",
+       "
      • min_value: None
        • \n",
+       "\n",
+       "
      • max_value: None
        • \n",
+       "\n",
+       "
      • unit: 
        • \n",
+       "\n",
+       "
      • is_normalization: False
        • \n",
+       "\n",
+       "
      • delta: 10.0
        • \n",
+       "\n",
+       "
      • free: False
        • \n",
+       "\n",
+       "
      \n",
+       "\n",
+       "
      • \n",
+       "\n",
+       "
    \n",
+       "\n",
+       "
    • \n",
+       "\n",
+       "
\n"
+      ],
+      "text/plain": [
+       ""
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Band.info()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -183,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 165,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -201,7 +361,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 166,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -211,40 +371,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Define an injector by the response\n",
-    "injector = SourceInjector(response_path=response_path)"
+    "injector = SourceInjector(response_path=response_path)  # XXX: Why does class constructor have this. Can't this be added as a parameter to the function inject_point_source()?"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 5.17 s, sys: 2.89 s, total: 8.05 s\n",
-      "Wall time: 8.34 s\n"
+      "CPU times: user 3.02 s, sys: 1.05 s, total: 4.07 s\n",
+      "Wall time: 4.27 s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 168,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
"
       ]
@@ -283,23 +443,52 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Load data from the text file, skipping the index column\n",
-    "dataFlux = np.genfromtxt(\"crab_spec.dat\",comments = \"#\",usecols = (2),skip_footer=1,skip_header=5)\n",
-    "dataEn = np.genfromtxt(\"crab_spec.dat\",comments = \"#\",usecols = (1),skip_footer=1,skip_header=5)\n"
+    "dataFlux = np.genfromtxt(\"crab_spec.dat\", usecols=2, skip_footer=1, skip_header=5)\n",
+    "dataEn = np.genfromtxt(\"crab_spec.dat\", usecols=1, skip_footer=1, skip_header=5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([6.22916e-04, 5.07161e-04, 4.12162e-04, 3.34285e-04, 2.70525e-04,\n",
+       "       2.18397e-04, 1.75844e-04, 1.41395e-04, 1.13695e-04, 9.14211e-05,\n",
+       "       7.35111e-05, 5.91097e-05, 4.75297e-05, 3.82183e-05, 3.07310e-05,\n",
+       "       2.47106e-05, 1.98696e-05, 1.59770e-05, 1.28470e-05, 1.03302e-05,\n",
+       "       8.30642e-06, 6.67913e-06, 5.37064e-06, 4.31849e-06, 3.47247e-06,\n",
+       "       2.79219e-06, 2.24518e-06, 1.80533e-06, 1.45165e-06, 1.16726e-06,\n",
+       "       9.38588e-07, 7.54712e-07, 6.06858e-07, 4.87970e-07, 3.92373e-07,\n",
+       "       3.15505e-07, 2.53695e-07, 2.03994e-07, 1.64030e-07, 1.31896e-07,\n",
+       "       1.06056e-07, 8.52791e-08, 6.85723e-08, 5.51385e-08, 4.43364e-08,\n",
+       "       3.56506e-08, 2.86664e-08, 2.30504e-08, 1.85347e-08, 1.49036e-08])"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataFlux"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 170,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "
"
       ]
@@ -375,13 +564,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 177,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
     "spectrum = SpecFromDat(K=1/18, dat=\"crab_spec.dat\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# XXX: Create function Write_Spec_Dat_format() to take energy and flux and convert to required format"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -391,7 +589,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -409,7 +607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 179,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -419,7 +617,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 180,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -429,30 +627,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 181,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 7.5 s, sys: 3.21 s, total: 10.7 s\n",
-      "Wall time: 10.9 s\n"
+      "CPU times: user 4.78 s, sys: 1.34 s, total: 6.12 s\n",
+      "Wall time: 6.42 s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
-     "execution_count": 181,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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datasmWbMmKH27dsbERsAAIShkC1EK1as8GmczWbTmDFjNGbMmCAnAoyR585T/Kx4o2P4zG6zK7VHqpISkoyOAgA+C9lCBJid3WaXXFKpp1S5rlyj4/jOJaVsTKEQAQgrFCIgRKX2SFXKxhS5ilxGR/FZnjtPpZ7SsMoMABKFqFJOp1NOp1Nut9voKDChpISksJtliZ8VH16zWQDwvyhEleAuMwAAzCGsn0MEAAAQCBQiAABgehQiAABgehQiAABgehQiAABgetxlVgluuwcAwBwoRJXgtnsAAMyBU2YAAMD0KEQAAMD0KEQAAMD0KEQAAMD0KEQAAMD0KEQAAMD0KEQAAMD0eA5RJXgwIwAA5kAhqgQPZgQAwBw4ZQYAAEyPQgQAAEyPQgQAAEyPQgQAAEyPQgQAAEyPQgQAAEyPQgQAAEyP5xBVggczAgBgDhSiSvBgRgAAzIFTZgAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPR4dUcleJcZAADmQCGqBO8yA/yT585T/Kx4o2P4zG6zK7VHqpISkoyOAsAgFCIAAWO32SWXVOopVa4r1+g4vnNJKRtTKESAiVGIAARMao9UpWxMkavIZXQUn+W581TqKQ2rzAACj0IEIGCSEpLCbpYlflZ8eM1mAQgK7jIDAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmx6s7KuF0OuV0OuV2u42OAgAAgohCVAmHwyGHw6Hs7GwlJycbHQcAAAQJp8wAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDp1TA6QChzOp1yOp1yu91GRwEAAEFEIaqEw+GQw+FQdna2kpOTjY4DAACChFNmAADA9ChEAADA9ChEAADA9ChEAADA9LioGgAk5bnzFD8r3ugYPrPb7ErtkaqkhCSjowA3BAoRAFOz2+ySSyr1lCrXlWt0HN+5pJSNKRQiIEAoRABMLbVHqlI2pshV5DI6is/y3Hkq9ZSGVWYg1PldiI4cOaKDBw+qe/fuqlOnjiSpqKhI8+fP19atW2Wz2fToo49q4MCBAQsLAIGWlJAUdrMs8bPiw2s2CwgDfl9U/f7772vx4sWqXbu2d9nChQu1Zs0aXbhwQWfOnNHs2bP19ddfByQoAABAsPhdiA4cOKAOHTrIYrFIki5fvqy1a9eqTZs2+uSTT7R8+XLddNNNWrlyZcDCAgAABIPfhaiwsFA333yz9+eDBw/q/PnzGjhwoGw2mxo0aKAuXbro8OHDAQkKAAAQLH4XosjISF26dMn78+7du2WxWNShQwfvsnr16qmwsLB6CQEAAILM70LUqFEj7dq1y/vzxo0b1bhxYzVq1Mi77OzZs6pXr171EgIAAASZ33eZ9e7dWwsWLNCoUaMUFRWlI0eO6Iknnig35ujRo4qPD58HnQEAAHPye4bo4YcfVvfu3ZWdna29e/eqU6dOevzxx73rjx07psOHD+vOO+8MSFAAAIBg8XuGyGq16tVXX9X58+dlsVjK3X4vSfXr19fixYvLnUIDAAAIRX7PEO3evVunT59WnTp1KpQhSbrppptkt9u5ywwAAIQ8vwvR+PHjtXbt2krHZGZmavz48f7uAgAA4LrwuxB5PB6fxpQ9uBEAACBU+V2IfHHixAnve84AAABCVZUuqn7jjTfK/fzll1/q1KlTFcaVlJTozJkz2rNnjzp16lS9hAAAAEFWpUL082uGLBaLDh8+fNWLpi0Wi1q3bq1nn322egkBAACCrEqFaPny5ZJ+ujbo0Ucf1eDBg5WUlFRhXEREhOx2u2rVqhWYlAAAAEFUpUL082cKTZo0SbfddhvPGQIAAGHP7wcz9uvXL5A5AAAADON3ISqTlZWlgwcPyu12q7S0tMJ6i8WiYcOGVXc3AAAAQeN3IfrHP/6hKVOmaN++fZU+kyhUCtG4ceOUlZWlyMhISdIdd9yht956y+BUAAAgFPhdiObPn6+9e/eqffv26tu3r26++WZv2QhVEyZMUO/evY2OAQAAQozfhWjbtm1q06aN5syZw9OoAQBAWPO7EBUVFaldu3ZBKUMXLlzQsmXLlJWVpQMHDsjlcmny5MlXvJC7uLhYixcv1vr16+VyudS8eXONGDFCHTt2rDB23rx5mjdvnlq2bKmxY8eqefPmAc8OAADCj9+v7mjRosUVn1IdCIWFhUpLS1NOTo5atGhR6djp06drxYoV6tWrl8aNG6eIiAhNmDBBe/bsKTdu9OjRWr58uVauXKm7775bv//973XhwoWg5AcAAOHF70I0fPhwbd26Vfv37w9kHklSTEyMPv74Y6Wnp+uZZ5656risrCxt2LBBI0eO1JgxY5SYmKg5c+aoUaNGWrBgQbmxCQkJql27tmw2m37729+qdu3aQckOAADCj9+nzL7//nt17txZ48aNU69evdSyZcurvsi1b9++Vdq21WpVTEzMNcdt3rxZkZGRSkxM9C6z2WwaMGCAFi5cqNOnTys2NvaKn7VYLJXeHQcAAMzD70I0ffp0b6lYu3at1q5dW+F6Io/HI4vFUuVC5KtDhw4pPj6+QhFr06aNJOnw4cOKjY2Vy+XSwYMHvdc8ffzxx3K5XEpISLjidvPz83Xu3Dnvzzk5OUHJDwAAQoPfhWjSpEmBzOGXc+fOXXEmqWxZfn6+JKmkpEQLFy7Ut99+qxo1aqhFixaaMWOGoqOjr7jdNWvWKC0tLWi5AQBAaAnrV3cUFRUpKiqqwnKr1epdL0k33XSTFi1a5PN2ExMT1aVLF+/POTk5mjZtWjXTAgCAUFXtV3cYyWaz6dKlSxWWFxcXe9f7o0GDBmrQoEG1sgEAgPDhdyE6ffq0z2OvdmFzdcXExOjs2bMVlpdd/0OpAQAAvvC7EA0ZMsSnhzJaLBZt3LjR391UqkWLFtq1a5fOnz9f7sLqrKws73oAAIBr8bsQ9enT54qFyO1268iRI8rLy1P79u3VqFGjagWsTPfu3bVs2TKtWbNGjz32mKSfTpdlZGQoISEhaDNTAADgxuJ3IZoyZcpV13k8Hi1btkwffvihJk6c6Nf2V61aJbfb7T39tXXrVp05c0aSNGjQIEVHRyshIUE9evTQwoULVVBQoLi4OK1bt06nTp3ye78/53Q65XQ65Xa7q70tAAAQuoJyUbXFYtFjjz2m7du365133vHrDq3ly5eXezXIli1btGXLFklS7969vbfMT5kyRbGxscrMzJTb7VazZs00Y8YMtW/fvtrfw+FwyOFwKDs7W8nJydXeHgAACE1BvcusVatW+uyzz/z67IoVK3waZ7PZNGbMGI0ZM8av/QAAAPj9LjNf5ObmqqSkJJi7AAAAqLaAzxCVlpbq7NmzWrdunbZu3ao777wz0LsAAAAIKL8L0X333Vfpbfcej0d2u11jx471dxcAAADXhd+FqOxFqb9ksVhkt9vVunVr9e/fX/Xr169WQCNxlxmAUJbnzlP8rHijY/jMbrMrtUeqkhKSjI4CVOB3IZo7d24gc4Qk7jIDEIrsNrvkkko9pcp15Rodx3cuKWVjCoUIISms32UGAGaU2iNVKRtT5CpyGR3FZ3nuPJV6SsMqM8wlIIVo7969OnTokC5cuKDatWurZcuWatu2bSA2DQD4haSEpLCbZYmfFR9es1kwnWoVor179+qNN95Qbu5Pf8k9Ho/3uqL4+HhNmjRJ//zP/1z9lAAAAEHkdyE6duyYXnrpJV28eFF33323OnTooJiYGH3//ffatWuXvv76a7300kt69913deuttwYwMgAAQGD5XYjS0tJ06dIlvfnmm+rUqVO5dUOHDtWOHTs0efJkpaWl6ZVXXqluTgAAgKDxuxDt3r1b3bt3r1CGynTq1Endu3fXN99843c4o3HbPQAA5uB3ITp//rwaN25c6ZjGjRvr/Pnz/u7CcNx2DwCAOfj9LrOYmBjt37+/0jFZWVmKiYnxdxcAAADXhd+FqEuXLtq9e7f+8z//U0VFReXWFRUV6b333tOuXbv0m9/8ptohAQAAgsnvU2bDhg3Ttm3b9N///d9as2aN2rRpo/r16+uHH37QwYMHVVBQoCZNmmjYsGGBzAsAABBwfheievXqacGCBXr33Xe1YcMGbd++3bvOarWqX79+Gj16tOrWrRuQoAAAAMFSrQcz3nTTTZo0aZJeeukl5eTkeJ9U3bRpU9WowVtBAABAeKhya3n//fd18eJFPfXUU97SU6NGDTVv3tw75tKlS1q0aJFq1aqlxx9/PHBpAQAAgqBKhegvf/mL3nvvPY0ePbrSGaCoqCjVrVtXCxYsUEJCgu68885qBzUCzyECAMAcqnSXWWZmpux2ux5++OFrjn3ooYdkt9u1du1av8MZzeFw6I033tBzzz1ndBQAABBEVSpE+/bt01133SWr1XrNsVarVXfffbf27t3rdzgAAIDroUqFKD8/X02aNPF5fOPGjXXu3LkqhwIAALieqlSIIiIidPnyZZ/HX758WRERfj/7EQAA4LqoUluJiYnRsWPHfB5/7NgxNWjQoMqhAAAArqcqFaI77rhDf/3rX5WXl3fNsXl5efrrX/+qdu3a+R0OAADgeqhSIXrooYd0+fJlTZ06VQUFBVcdV1hYqD/84Q8qKSnRwIEDq5sRAAAgqKr0HKJWrVpp8ODBSk9P15NPPqmBAweqQ4cOatiwoaSfLrr+5ptv9Omnn6qgoEBDhgxRq1atghIcAAAgUKr8pOqxY8fKarXqww8/1JIlS7RkyZJy6z0ejyIiIvT4449rxIgRAQsKAAAQLFUuRBaLRSNHjtSAAQOUkZGhffv26fvvv5ck/dM//ZPatm2rfv36KS4uLuBhrzeeVA0AgDn4/QbWuLg4JScnBzJLyHE4HHI4HMrOzr7hvysAAGbGQ4IAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDpUYgAAIDp+f3qDjPgXWYAAJgDhagSvMsMAABz4JQZAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPQoRAAAwPR7MCAC4bvLceYqfFW90jCqx2+xK7ZGqpIQko6MgiChEAICgs9vskksq9ZQq15VrdJyqcUkpG1MoRDc4ChEAIOhSe6QqZWOKXEUuo6NUSZ47T6We0rDLjaqjEAEAgi4pISksZ1jiZ8WH34wW/MJF1QAAwPSYIaqE0+mU0+mU2+02OgoAAAgiClElHA6HHA6HsrOzlZycbHQcAAAQJJwyAwAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAApkchAgAAplfD6AChzOl0yul0yu12Gx0FAAAEEYWoEg6HQw6HQ9nZ2UpOTjY6DgAACBJOmQEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOjEAEAANOrYXQAAABCXZ47T/Gz4o2O4TO7za7UHqlKSkgyOkrYoBABAHAVdptdckmlnlLlunKNjuM7l5SyMYVCVAUUIgAAriK1R6pSNqbIVeQyOorP8tx5KvWUhlXmUEAhAgDgKpISksJuliV+Vnx4zWaFCC6qBgAApkchAgAApkchAgAApkchAgAApkchAgAApme6QrRv3z7dd999+tOf/mR0FAAAECJMVYhKS0s1f/58tW7d2ugoAAAghJjqOUSffvqp2rRpo/PnzxsdBQAAhJCQnCG6cOGC3nvvPb300ksaMGCAunXrprVr115xbHFxsRYsWKCHHnpIDodDo0aN0tdff11hXGFhodLT0/XUU08FOz4AAAgzIVmICgsLlZaWppycHLVo0aLSsdOnT9eKFSvUq1cvjRs3ThEREZowYYL27NlTbtyiRYs0ePBg2e32YEYHAABhKCQLUUxMjD7++GOlp6frmWeeueq4rKwsbdiwQSNHjtSYMWOUmJioOXPmqFGjRlqwYIF33N///ncdPHhQ999///WIDwAAwkxIXkNktVoVExNzzXGbN29WZGSkEhMTvctsNpsGDBighQsX6vTp04qNjdXu3bv13XffadCgQZIkt9utyMhInTx5UpMnTw7a9wAAAOEhJAuRrw4dOqT4+HjVqVOn3PI2bdpIkg4fPqzY2FglJiaqZ8+e3vVz585V48aNNXTo0CtuNz8/X+fOnfP+nJOTE4T0AAAgVIR1ITp37twVZ5LKluXn50uSatasqZo1a3rX22w21apV66rXE61Zs0ZpaWmBDwwAAEJSWBeioqIiRUVFVVhutVq9669kypQplW43MTFRXbp08f6ck5OjadOmVSMpAAAIZWFdiGw2my5dulRheXFxsXe9Pxo0aKAGDRpUKxsAAAgfIXmXma9iYmLKXetTpmwZpQYAAPgirAtRixYtdOLEiQpPns7KyvKuBwAAuJawLkTdu3dXSUmJ1qxZ411WXFysjIwMJSQkKDY2tlrbdzqdmjRpkubNm1fdqAAAIISF7DVEq1atktvt9p7+2rp1q86cOSNJGjRokKKjo5WQkKAePXpo4cKFKigoUFxcnNatW6dTp05p4sSJ1c7gcDjkcDiUnZ2t5OTkam8PAACEppAtRMuXL9epU6e8P2/ZskVbtmyRJPXu3VvR0dGSfrpjLDY2VpmZmXK73WrWrJlmzJih9u3bGxEbAACEoZAtRCtWrPBpnM1m05gxYzRmzJggJwIAADeqsL6GCAAAIBAoRAAAwPRC9pRZKHA6nXI6nXK73UZHAQAAQUQhqgR3mQEAYA6cMgMAAKZHIQIAAKZHIQIAAKZHIQIAAKZHIQIAAKZHIQIAAKbHbfeV4DlEAACYA4WoEjyHCAAAc+CUGQAAMD0KEQAAMD0KEQAAMD0KEQAAMD0KEQAAMD0KEQAAMD1uu68EzyECAMAcKESV4DlEAACYA6fMAACA6VGIAACA6VGIAACA6VGIAACA6VGIAACA6VGIAACA6VGIAACA6fEcokrwYEYAAMyBQlQJHswIAIA5cMoMAACYHoUIAACYHoUIAACYHoUIAACYHoUIAACYHoUIAACYHoUIAACYHoUIAACYHoUIAACYHk+qBgDgBpTnzlP8rHijY/jMbrMrtUeqkhKSDNk/hagSvMsMABBu7Da75JJKPaXKdeUaHcd3LillYwqFKBTxLjMAQLhJ7ZGqlI0pchW5jI7iszx3nko9pYZmphABAHADSUpIMmyWxV/xs+INn83iomoAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6FCIAAGB6vNy1Ek6nU06nU2632+goAAAgiChElXA4HHI4HNqzZ4+effZZ5eTkBHwf1gKr6pyvI2uJVdnZ2QHfPgAAoS7Y/y1s2rSpatasWekYi8fj8QR8zzeY9evXa9q0aUbHAAAAfli0aJFatWpV6RgKkQ8KCgq0c+dOrV69Ws8//7zPn5s3b56ee+65Ssfk5ORo2rRpevnll9W0adPqRr0h+PJ7M4oR2YKxz0Btszrb8eezVf0Mx6B/QvkYlK5/vmDtzwzHoa9jg30c+jJDxCkzH9x0003q3bu3vvjii2s2zJ+Ljo72eXzTpk2rtO0bWVV+b9ebEdmCsc9AbbM62/Hns1X9DMegf0L5GJSuf75g7c8Mx2FVt2/kcchdZlXgcDiCOh4/CeXfmxHZgrHPQG2zOtvx57Mcg9dHqP/erne+YO3PDMdhqP9d+jlOmRksOztbycnJPp3fBBB4HIOA8ULhOGSGyGAxMTEaPny4YmJijI4CmBLHIGC8UDgOmSECAACmxwwRAAAwPQoRAAAwPQpRiCsuLtYbb7yhpKQk9e3bV6NHj9a+ffuMjgWYyltvvaUHH3xQffv21bBhw7R161ajIwGmtW/fPt13333605/+FNDtcg1RiPvxxx+1fPly9evXTw0bNtTGjRs1Z84cLV++XLVr1zY6HmAKOTk5aty4saxWqw4cOKAXX3xRy5YtU7169YyOBphKaWmpxowZI4/Ho1//+tcaNmxYwLbNDFGIq1WrloYPH67Y2FhFRESoZ8+eqlGjhr777jujowGm0bRpU1mtVkmSxWLRpUuXlJ+fb3AqwHw+/fRTtWnTJihPs+ZJ1QF24cIFLVu2TFlZWTpw4IBcLpcmT56sfv36VRhbXFysxYsXa/369XK5XGrevLlGjBihjh07XnX73333nVwul+Li4oL5NYCwFaxjcNasWcrIyFBxcbE6d+6sZs2aXY+vA4SlYByHhYWFSk9P14IFCzRv3ryAZ2aGKMAKCwuVlpamnJwctWjRotKx06dP14oVK9SrVy+NGzdOERERmjBhgvbs2XPF8UVFRZo2bZqGDh2q6OjoYMQHwl6wjsEXX3xRmZmZmj17tjp27CiLxRKsrwCEvWAch4sWLdLgwYNlt9uDE9qDgCoqKvLk5+d7PB6P58CBA56uXbt6MjIyKozbv3+/p2vXrp6lS5d6l128eNHz6KOPekaPHl1h/KVLlzwTJkzwvPrqq57S0tLgfQEgzAXrGPy5iRMnev785z8HNjhwAwn0cZidne15+umnPZcvX/Z4PB7P66+/7klLSwtoZmaIAsxqtfr0pM3NmzcrMjJSiYmJ3mU2m00DBgzQ/v37dfr0ae/y0tJSTZs2TRaLRVOmTOH/mQKVCMYx+EslJSXKzc0NSF7gRhTo43D37t367rvvNGjQID344IP64osvtHTpUk2fPj1gmbmGyCCHDh1SfHy86tSpU255mzZtJEmHDx9WbGysJGnmzJk6d+6cZs6cqRo1+FcGBIKvx6Db7da2bdvUpUsXWa1Wffnll9q1a5dGjhxpRGzghuLrcZiYmKiePXt618+dO1eNGzfW0KFDA5aF/7oa5Ny5c1dsz2XLyu5gOXXqlD777DNZrdZyDfrNN99Uu3btrk9Y4Abk6zFosVj02Wefafbs2fJ4PIqLi1NKSopatmx5XfMCNyJfj8OaNWuqZs2a3vU2m021atUK6PVEFCKDFBUVKSoqqsLyslt7i4qKJEmNGjXSli1brms2wAx8PQbr1KmjP/7xj9c1G2AWvh6HvzRlypSAZ+EaIoPYbDZdunSpwvLi4mLvegDBwzEIGC+UjkMKkUFiYmJ07ty5CsvLljVo0OB6RwJMhWMQMF4oHYcUIoO0aNFCJ06c0Pnz58stz8rK8q4HEDwcg4DxQuk4pBAZpHv37iopKdGaNWu8y4qLi5WRkaGEhATvHWYAgoNjEDBeKB2HXFQdBKtWrZLb7fZO+W3dulVnzpyRJA0aNEjR0dFKSEhQjx49tHDhQhUUFCguLk7r1q3TqVOnNHHiRCPjA2GPYxAwXrgdh7ztPgiGDBmiU6dOXXHd8uXL1bhxY0k/XT1f9v4Wt9utZs2aacSIEbrnnnuuZ1zghsMxCBgv3I5DChEAADA9riECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECAACmRyECYCrdunUr96eoqMi7bu3aterWrZvWrl1rYML/88knn5TL+m//9m9GRwJuWLztHkBQ5OXl6ZFHHql0TKNGjbRixYrrlKj8fvv27StJioyMDOq+du7cqZdeekkdO3bU22+/XenY1157TU6nUykpKerVq5datWql4cOHy+12a+XKlUHNCZgdhQhAUMXFxalXr15XXBcdHX2d0/ykUaNGeuqpp67Lvu6++27Fxsbqm2++0enTpxUbG3vFcW63W19++aWio6PVrVs3SVLr1q3VunVr5eXlUYiAIKMQAQiquLi461Y+QlFERIT69euntLQ0rVu3TsOGDbviOKfTqaKiIvXv3182m+06pwTANUQAQka3bt00btw4nT17Vq+99poeeOAB9enTRxMmTNDJkyclScePH9eUKVM0YMAA9enTRykpKfr++++DmuvMmTMaNmyYHA6HNm3a5F3+ww8/aN68eXrsscfUs2dPPfDAA3r55Zd19OjRcp/v37+/LBaL1q5dK4/Hc8V9ZGRkSJIGDBgQtO8B4OooRABCisvl0tixY5WXl6c+ffqoQ4cO2r59u1588UUdPXpUY8aM0Y8//qj+/furdevW2rx5s1599dWg5Tl+/LjGjBmjM2fO6K233lL37t0lSbm5uRoxYoTS09PVpEkTPfzww+rcubN27typZ555RllZWd5tNGrUSHfddZdOnjypXbt2VdjH0aNHdfDgQbVs2VK33XZb0L4LgKvjlBmAoMrNzdV77713xXW33367OnXqVG7ZkSNHNGTIED377LPeZbNmzdLq1av17LPP6l/+5V80ePBgSZLH49HEiRO1fft2ZWdnq1WrVgHNvn//fk2cOFE1atTQvHnz1KJFC++6119/Xd9//71mzpype+65x7v8ySefVHJyst58802lpaV5lw8YMEB/+ctflJGRoTvvvLPcfpgdAozHDBGAoMrNzVVaWtoV/+zYsaPC+Fq1amnEiBHllvXs2VOSVK9ePSUlJXmXWywW77ojR44ENPe2bdv0wgsvyG6365133ilXhv7+979r37596tOnT7kyJEm33HKL7r//fh09erTcqbOuXbuqXr162rx5s86fP+9dfvnyZa1fv15Wq/WqF58DCD5miAAE1T333KOZM2f6PD4+Pl41a9YstywmJkaS1KxZM1ksliuuy8/Pr2bS/7Nx40Z9/fXXat68ud566y3Vr1+/3Pqy02E//PDDFWe/vv32W+//NmvWTJK8hWflypVyOp0aOHCgJGnr1q0qKCiQw+GQ3W4P2HcAUDUUIgAhpU6dOhWWlT0rqLJ1ly9fDliG/fv3q6SkRHfccUeFMiRJ//jHPyT9NIu0bdu2q27nxx9/LPfzgAEDtHLlSmVkZHgLEafLgNBAIQKAXxg5cqS++uorrVy5UpGRkRo7dmy59WXF7Pnnn9egQYN83m7z5s3VunVrHThwQMeOHZPdbtfOnTvVuHHjCtcVAbi+uIYIAH7BarXq9ddf17333qvly5dr/vz55da3adNG0k8zSVVVNhP0P//zP8rMzFRJSYn3tnwAxqEQAcAVWK1WTZs2Tb/+9a+1YsUKzZs3z7suISFBCQkJ2rBhgzZs2FDhs6Wlpdq9e/cVt+twOFSzZk2tX79eGRkZioiI8L5GBIBxOGUGIKgqu+1ekoYOHRqyT2aOiopSamqqpk6dqvT0dHk8Ho0bN06SNHXqVI0fP16vvvqqVq5cqZYtW8pms+nMmTPat2+fCgsL5XQ6K2yzTp06uu+++5SZmamCggJ16tTpqq/zAHD9UIgABFXZbfdXM3jw4JAtRNL/laI//OEPWrlypTwej55//nk1adJEixcv1vLly/Xll19q7dq1ioiIUExMjNq1a+d9gOOVDBgwQJmZmZJ+eoo1AONZPFd7jjwA3IC6deum9u3ba+7cuUZH8VleXp4eeeQR9e3bV1OmTDE6DnBDYoYIgOns3r3b+0b5zz//PGRnqD755BO9/fbbRscATIFCBMBUhg8fXu7nsucYhaJWrVqVy9uyZUvjwgA3OE6ZAQAA0+O2ewAAYHoUIgAAYHoUIgAAYHoUIgAAYHoUIgAAYHoUIgAAYHoUIgAAYHoUIgAAYHoUIgAAYHr/H716K15r4Xb+AAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "
"
       ]
@@ -484,7 +682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 182,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
@@ -493,13 +691,13 @@
        "Text(0.5, 1.0, 'Comparison b/w model and piecewise injected counts')"
       ]
      },
-     "execution_count": 182,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
"
       ]
@@ -529,7 +727,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "COSI",
+   "display_name": "cosipy",
    "language": "python",
    "name": "python3"
   },
@@ -543,7 +741,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,
diff --git a/docs/tutorials/spectral_fits/continuum_fit/crab/SpectralFit_Crab.ipynb b/docs/tutorials/spectral_fits/continuum_fit/crab/SpectralFit_Crab.ipynb
index f4a2f72a..ee658d56 100644
--- a/docs/tutorials/spectral_fits/continuum_fit/crab/SpectralFit_Crab.ipynb
+++ b/docs/tutorials/spectral_fits/continuum_fit/crab/SpectralFit_Crab.ipynb
@@ -1607,7 +1607,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "
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       ]
@@ -1658,7 +1658,7 @@
     },
     {
      "data": {
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5jBo1ir179xodxexkrzvdMjuOxMREEhMTqa6uNjpKt+Lj7cMkJuHj7cOwYcPM221tbc3FDxwaBOnl9b+BnqGhoeY/W1tbt2rr4eFh7sIGGDJkSKtz/rmtu7t7q9fBwcGt2v55wKerqysjR47k+5zvKaCAuvq6DnxSERHpK1QQHUdCQgIJCQnmHiI5xMvDizGMwcujfU+1dAdhIWEsYAFhIWFGRxER6fGCg4O7Ve9QV9AYIumwquoqssmmqrrK6CgiIiJdQgWRdFhOQQ7v8A45BTlGR2m3tKw0nuAJ0rLSjI4iIiLdkAoi6bCI0Aj+zt+JCI0wOkq7ebp7cjqn4+nuaXQUERHphlQQSYfZ29njhhv2dvZGR2m3Qd6DmMAEBnkPMjqKiIh0QyqIpMMKSwpZwxoKSwqNjtJuNbU1FFBATW2N0VFERKQbUkEkHVZXX0cJJT3qEfadeTt5lVfZmbfT6Cgihvn444+Jj48nLi6OyMhIJk2aREtLi9GxDLV06VIOHjxodAzpBvTYvXRYWEgY85nfox5hDwsJ4yZu6lGZRbpSaWkpCxYs4PfffzcvrJmcnHzC5RQ6oiuWkTjVHnzwQe644w7s7XvOEACxDPUQSZ/g6OB4aD0zB0ejo0gfVlJSQkpKivl1WloaBQUFwKFZdpOTk6mqOjSdxe7du1stDpqRkUFeXh4AjY2NJCcnd2gdsZKSEmxtbfH0/N+DBSNHjjQXRJs3b2bs2LHExsYyevRofvrpJ+DQjMR/nmC1urq6zcKdTz75JBMnTuSee+6hoqKCuXPnEhMTw4gRI8yLxTY2NrJ48WJGjx5NXFwcs2bNory8/KhZv/jiC04//XTzEiK//vorAOvWrWPkyJHExsYyYcIE0tIOPTW6YcOGVstXbN++3Txh6+H8999/v3kpjMNLhSxYsACAM888k7i4OPbs2cMrr7xCVFQUcXFxxMTEmM8tvV/PKuWlW0jLSuMxHuPsrLO71erdx1O8u5j/8l/O/PFMo6N0iJOXkxaj7UVefvllXnnlFQoLD42/mzVrFhMnTuSZZ56hsLCQ+Ph41q9fz8SJE3nrrbf45z//yf79+wGYM2cO0dHRvPLKK+zdu5f4+HjWrl3LBRdc0K5zjxgxgrFjxxIYGMiECRM488wzufLKK/H39+fgwYNccsklrFq1ismTJ/Pjjz9y2WWXkZ2d3a5jNzQ0sGHDBuDQemH9+/dn69atWFtbU1ZWBsDjjz9O//79+e233wB4+OGHeeCBB8xrqR2WmZnJDTfcwPfff8+wYcNobGyktraWPXv2cNVVV7F+/XpiYmJYvXo1M2fOZPv27SfMt2/fPuLj43nooYdYt24dixYtYtq0abz00ku8/PLL/Pzzz/Tv3x+A22+/nfT0dPz8/GhsbKShoaFd34H0fCqIpMO8BngxlrF4Deg5M1U32jWSaZXJp4s+5Wd+NjpOu9k52bEwfaGKol7ixhtv5NJLLzW/fvfdd3FxcQEgICCApKQk8/p911xzDeeff7657RtvvGFen8nLy4ukpCSGDh3a7nNbW1vz0UcfsWPHDjZu3MhXX33FI488wubNm6mrq8Pe3p7JkycDcPbZZzNw4EC2bduGr++Jf+k53AsEsHbtWpKSkrC2PnQDwtvbG4BPP/2UyspKPvzwQwAOHjx41PzffPMN06ZNMy8LZGdnh5ubG2vWrDH32gDMnj2bhQsXUlJScsJ8zs7OzJgxA4CxY8eyc+exxxKee+65XHPNNVx00UVMnTq11fJE0rupIJIOG+g1kHGMY6DXQKOjtNuYhDFk52bzx69/4Oriiu9AX+rq68jKySI0OBQnRyd2l+1mf/l+IsMiAcjclYmzkzP+Pv7UN9STuSuTIYFD6O/cn7J9ZezZt4foYdEAZOdmU11TTeKPicyaPov95fsJDgjG1cWVfQf2Uby7mJiIQz/Id+XvwtbGlkD/QJqbm0nNTCXQPxB3V3f2l++nsKSQmIgY9u7Yy3+u+g+1e2tVEPUSvr6+rQqMP6+Y7uDg0GqNvkGDBjFo0P+mifjzwtJ2dnat2nZEREQEERER3HjjjUyZMoXPP/+chISEo44lsrKywtbWlubmZvO2+vr6Nu0O964cj8lk4oUXXuDcc8/tVG6TydTpjH9e6NPGxqZV2yN9/PHHJCUlsWHDBqZNm8ayZcuYNWtWpzJLz6IxRNJhNbU15JHX4x5hdwt0Y+49c/lg4wf4jvSlun81U66awn77/fiO9OXTTZ9yze3X4DvSF9+Rvtzy0C28te4tfEf60uzdzJSrplDUXITvSF++3vI1M2+aaW571+N38fZXb+Pi64Kdvx1TrppCdnU2viN92bhjIxddd5G57QPPPcBT/34K35G+uIa7MuWqKWwv247vSF9+z/+dKVdNYeCIgVj7WPMxH/eo6Q2k+yoqKjKPCwI4cOAAOTk5DB06lIiICBoaGvjuu+8A+Pnnn9mzZw8xMTH4+PjQ1NRERkYGAG+99dZxzzN9+nQef/xx89Nrh2+ZTZ8+nRUrVlBbWwtAbW0tqampbfafPHkyX331FZmZmcChsUcVFRWMHTuWLVu2kJ6eDhzqXQsICMDHx4eQkBBycnLYt28fAG+//Xa7vxcXFxfzWKympiZ27tzJqFGjuOOOO7jsssvMt/ik91MPkXTYzrydvM7r/DXvr4SeHXriHbqRzz77DHd3dwDCwsJISkoy/+bdFbczgoKCaGxsbHU7Y+bMmZx55v/GLr344ovmJ3GcnZ1JSkoiJCQEgIsuuoikpCRsbGyoqq6ihRaampos9G1IX9LU1MRDDz1ETk4OTk5ONDU1ce2115pvJX300Ufceuut1NTU4ODgwAcffICzszMAzzzzDFOnTiUgIICpU6ce9zz/+te/+Pvf/87w4cOxt7fn9NNPZ9WqVSxevJgHH3yQM844w9zTc/fddxMdHd1q/9DQUF599VWuuOIKGhsbsbGx4eWXX2b06NG8/fbbzJ49m+bmZtzd3Xn//fcB8Pf354477mDUqFEEBwczfvz4dn8vt99+O+eeey6Ojo58/fXXXHfddRw4cABbW1u8vb15/fXX230s6dmsTCaTyegQ3d3h1e5XrVrVqtu6r8rZlMOKM1dw28+3ETI2xOg4vVZJcgkr41cyP2l+jxm8LofU19eTk5NDSEhIq9s1ImI5J3vd6ZaZdJhDPwe88MKhn37QW5LJZKKZZvQ7i4iI5akgkg4r3l3MOtZRvLvY6Ci9WsqOFB7mYVJ2pJy4sYiInBQVRNJh1TXV7GQn1TXVRkfp1QJ8A5jBDAJ8A4yOIp3U15fFEDmVTrY3XYOqpcOGDRnGQhYybIjm57AkD3cPTuM0PNw9jI4iHWRvb4+1tTXFxcV4e3tjb2/fpUtkiEhrJpOJsrIyrKyssLOz69QxVBCJdFPlleWkkkp5ZTm+aFB1T2JtbU1ISAglJSUUF+vWssipYGVlRUBAADY2Np3aXwWRdNiO7B38i38xPnu8nn6yoPyifD7gA24ouoFIIo2OIx1kb29PYGAgTU1Nx50IUES6hp2dXaeLIVBBJJ3g7uZOLLG4u7kbHaVXix4WzWIWm2fDlp7ncPd9Z7vwReTU0aBq6TAfbx8mMQkfbx+jo/RqNjY2OOBwUr/xiIhI+6ggkg6rraulmGJq62qNjtKr5Rfl8yEfkl+Ub3QUEZFeTwWRdFh2bjYrWUl2brbRUXq1puYmaqihqVlLd4iIWJoKIumw0OBQ5jOf0OCetY5ZTzMkcAjXci1DAocYHUVEpNdTQSQd5uTohB9+ODk6GR1FRESkS+gps26gIr+C2r09ZzxO6s+pfMu3TC+brvlxLOjw0h1jd4zV9AYiIhamgshgFfkVPB/5PA21DZRSijvuOOFELbWUU44PPlhjzX72Y8KEJ54AFFOMG24440wddRzgAIMYhA02HOAAzTTjhRcAJZTgggv96U899exnPwMZiC22lFNOI4144w1AKaU444wLLjTQwD724Y03dthRQQUNNGDCRIpVCvXW9YZ9b32B3yA/JjMZv0F+RkcREen1VBAZrHZvLY21jUx9ZSpj547l+Uee5+IpF/PRlx/x2H2PkbMph372/bjhjhs4ePAgbz/zNgB+8X48vuRxZl88my+/+5K5d84l9btUBrgN4OYlN1Oyp4SPVn4EwNCzhnLPzfcw94q5bPh5A1feciWbv9yM3yA/7nrkLlJ2pPDV218BMHzScG6cfSPzr5/Pr3/8ysVzL+b7j74nNDiUpSuWsmHTBjZ8sIF/ev0Tt0A3w763vsBzgCejGY3nAE+jo4iI9HpWppNdDa0H+eKLL3jnnXfYv38/3t7ePProo/j7+59wv4yMDObNm8eqVasIDw/v0ky/fP4LN8y4gVWfrsJhsAPBwcF4eHiwf/9+cnNziYuLw9raml27dtHS0kJo6KGBzMnJyQQGBuLl5cWBAwfIyckhNjYWW1tbcnJyaGxsZNiwQ2uNbdmyBT8/PwYOHEhlZSXZ2dkMHz4ce3t78vPzqa2tJSIiAoBt27YxcOBAfHx8qK6uJjMzk6ioKBwcHCgsLKSyspKoqKgu/Q7k6DI2ZvDQxIe4f8P9hE/o2r93IiLSWp/pIfrpp5/48MMP+ec//0lQUBBFRUW4uroaHYvmluZDt6FMJkaOHGne7uHhgYfH/xb1HDKk9ZNGf247YMAABgwYYH4dEhLSqm1cXJz5z66urq32DQwMbNU2NjbW/Of+/fu3ahsQoFXXT6Xcwlz+zb+5pvAawlFBJCJiSX2mIHrzzTe5+eabCQ4OBrrPP+5DAodwNVfr0WppIzI0ktu5nchQrWMmImJp3bIgqq2t5c033yQrK4usrCwqKiqYM2cO119//VHbvvLKK6xfv56qqioCAwOZPXs2kyZNMrdpbm4mKyuLnTt38o9//AMbGxumTp3KnDlzsLKyOpUfTaTd7OzscMFF62CJiJwC3XIeooqKCtasWUNjYyPjxo07btslS5awbt065syZw2OPPUZERAQPPvgg33zzjbnNgQMHaG5u5vfff+eNN97g6aef5ptvvmHdunWW/igntC19Gw/yINvStxkdRbqZwpJCPuMzCksKjY4iItLrdcseIh8fH7744gusrKwoLy9n7dq1R223adMmNm/ezP33309CQgJwaGxNaWkpL774Iueeey42Njb069cPgNmzZ+Pi4oKLiwvTp0/nt99+Y+rUqafscx2Nv48/F3AB/j4nHtwtfUt9Qz1llFHfoOkNREQsrVv2EFlZWbXrVtYPP/yAo6MjEydObLV92rRp7N27l7S0NABcXFzw8vJq9/n37t1LRkaG+b+8vLwO5e8IzwGejGKUHq2WNkKDQ5nLXC2RIiJyCnTLHqL2ysnJISgoCFvb1h9j6NCh5vdjYmIAmDp1Kv/5z38YNmwY1dXVrF27lmuuueaox/3888954403LJr9sIqqCnawg4qqCs36LCIiYpAeXRBVVFTg59d2Fl8XFxcAKisrzdvmzJnDv/71Ly699FKcnJy46KKLOP/884963OnTp3PWWWeZX+fl5bFs2bIuTv//H7swj3d5lzmFc4ggwiLnkJ4pNTOV5SznrMyztHSHiIiF9eiCCGj3U2J2dnbcdddd3HXXXSds6+Xl1aFbbCcjMjSSO7lTj1ZLGwM9BzKOcQz0HGh0FBGRXq9bjiFqLzc3NyoqKtpsr6qqAugWEy+eiJ2dHc4469FqacPb05uzOAtvT2+jo4iI9Ho9uodoyJAhJCYm0tTU1Goc0a5du4C2MzZ3RwXFBXzCJ0wtnqrbItJKdU01OeSQm5xrdJQOcfJy0jp3ItLj9OiCaNy4caxZs4aNGze2mohx3bp1eHl5nfSaW4mJiSQmJlJdXX2yUY+p4WAD+9lPw8EGi51DeqbiymLe5E36zeuHHz1nxXs7JzsWpi9UUSQiPUq3LYh++eUX6uvrqa2tBQ4NbN6wYQMAY8aMwcHBgTFjxjBq1ChWrFhBbW0t/v7+fPvtt/z6668sWbIEGxubk8qQkJBAQkKCeXFXSwgNDuUGbtCj1dLGGZPOIHljMu527jj0c7DIOWrLakn7OI2oS6Jw8nY66eOVpZfxyVWfULu3VgWRiPQo3bYgWrFiBaWlpebX69evZ/369QC89957+Poeur20bNkyVq1axauvvmpeuuOBBx5o1WMk0hM5ODhw2vjTLH6eoZOHWvwcIiLdXbctiN5///12tXNycmLRokUsWrTIwoksY3vGdv7BPzgz40yNIZJWCgoKePzxx7nzzjsZPHiw0XFERHq1Hv2UWW8wyGsQE5nIIK9BRkeRbqaqqooNGzaYn5oUERHLUUFkMG9Pb87kTD1aLW1ERUWxbds2mpubKSkpAaCmpobk5GTq6uoAKCoqIjU11bxPamoqhYWHFoOtq6sjOTnZ/FBASUkJ27b9bxHh9PR08vPzAWhoaCA5Odk8menu3bvZsmWLuW1GRga5ubkANDY2kpycTHl5OQBlZWUkJyeb29ZR14XfgojIqaGC6DgSExNZvHgxzz77rMXOUVVdxU52UlWtXgA5uqlTp/Lyyy8DkJaWRnx8PFlZWQA899xzzJgxw9z2kksu4emnnwYOTT8RHx9PSkoKAK+++iqTJ082t509ezaPPvoocKhYio+P57fffgNg9erVjB8/3tz2hhtuYOnSpQCUl5cTHx/P999/D8DHH3/M6NGjAdh3YB8f8iGFJYVd/j2IiFiSlclkMhkdors7/JTZqlWrCA8P79Jjf736a6ZcNYV176xj8uzJJ95B+pyUlBS8vLzw9fWlpqaGjIwMIiMjcXR0pKioiPLycqKjo4FDPURubm4EBARQV1dHeno6w4YNo3///pSUlFBWVkZsbCxwqIfI2dmZwMBAGhoaSE1NJTQ0FFdXV3bv3k1JSQlxcXHAoWugX79+BAcH09jYSEpKCkOGDMHd3Z2ysjIKCgoYOXIkv3z+C9fOuJY3P3uTMdPHGPWViYh0mAqidrBkQZT7Sy5PjX2Kv236G8Fjgrv02CKnWklyCSvjVzI/ab4eEhCRHkW3zAzWz74fAxhAP/t+RkcROWnNzc0c5CDNzc1GRxER6RAVRAYrLCnkC77QmAvpFVIzU/kH/yA1M/XEjUVEuhEVRAarq6+jgALq6vVkjvR8g/0GcymXMthP8yaJSM+igshgYSFhLGABYSFhRkcROWkD3AYQQwwD3AYYHUVEpENUEIlIlzlQcYCtbOVAxQGjo4iIdEi3XbqjOzgVq92nZaXxBE9wdtbZeipHeryC4gI+4RNuLL6RKKKMjiMi0m4qiI7jVKx27+nuyemcjqe7p0WOL3IqDQ8fzhKWMDx8uNFRREQ6RLfMDDbIexATmMAgb61lJj2ftbU1tthiba0fLSLSs+inlsFqamsooICa2hqjo4ictLzCPN7lXfIK84yOIiLSISqIDLYzbyev8io783YaHUXkpLWYWmimmRZTi9FRREQ6RAWRwcJCwriJm/TYvfQKIYNDmM1sQgaHGB1FRKRDVBAZzNHBkYEMxNHB0egoIiIifZYKIoMV7y7mv/yX4t3FRkcROWnb0rexlKVsS99mdBQRkQ7RY/fHcSrmIaqqriKDDKqqqyx2DpFTxd/Hn4u4CH8ff6OjiIh0iAqi4zgV8xCFDw3nFm4hfGi4RY4vcip5DvAknng8B2heLRHpWXTLTES6THllOWmkUV5ZbnQUEZEOUUFksIydGTzN02TszDA6ishJyy/K533eJ78o3+goIiIdooLIYK4urkQTjauLq9FRRE5aVFgUd3EXUWFax0xEehYVRAbzHehLAgn4DtTCrtLz2dra4oQTtrYanigiPYsKIoPV1ddRSil19XVGRxE5aflF+XzER7plJiI9jgoig2XlZPESL5GVk2V0FJGT1tjUSCWVNDY1Gh1FRKRDVBAZLDQ4lHnMIzQ41OgoIidtaNBQruM6hgYNNTqKiEiHqCAymJOjE/744+ToZHQUERGRPksjH4/jVMxUvbtsN+tZz4yyGfiigdXSs23P2M4jPMKZGWfiO1J/n0Wk51BBdBynYqbq/eX7SSaZ/eX7LXJ8kVPJx9uHSUzCx9vH6CgiIh2iW2YGiwyL5HZuJzIs0ugoIifNy8OLMYzBy8PL6CgiIh2iHiIR6TJV1VVkk01OUo7RUTrEycsJt0A3o2OIiIFUEBksc1cmL/ACE3dN1JgL6fFKqkp4h3dwmu+EH35Gx2k3Oyc7FqYvVFEk0oepIDKYs5MzwQTj7ORsdBSRkzb2vLGk/pKKM87Y29kbHaddytLL+OSqT6jdW6uCSKQPU0FkMH8ff6YxDX8ff6OjiJw0e3t7os7QOmYi0vNoULXB6hvq2cc+6hvqjY4ictLy8/O58cYbyc/X0h0i0rOoIDJY5q5MnuVZMndlGh1F5KTV1taSnJxMbW2t0VFERDpEt8wMNiRwCNdyLUMChxgdReSkRURE8PvvvxsdQ0Skw9RDZLD+zv0JIYT+zv2NjiIiItJnqSA6jsTERBYvXsyzzz5rsXOU7SvjJ36ibF+Zxc4hcqps27YNb29vtm3bZnQUEZEO0S2z4zgVS3fs2beHH/iBPfv2WOT4IqfSwIEDue222xg4cKDRUUREOkQ9RAaLHhbNYhYTPSza6CgiJ83Hx4dbbrmF4uJi6usPPTlZWFhIWlqauc327dspLi4G2g7CLi4uZvv27ea2aWlpFBYWAlBfX09ycrJ5seXS0tJWPVE7duwwP9128OBBkpOTqaysBGDPnj1s2bLF3DYzM5OcnEOzaTc1NVFOeVd+DSLSA6kgEpEutWXLFuLj48nLywNgxYoVXH755eb3L7zwQl544QXgUBETHx/Pjh07AHjhhRe48MILzW0vv/xyVqxYAUBeXh7x8fEkJiaydOlSnn76aSZNmmRue/XVV/PII48Ahwqg+Ph4Nm3aBMC7777LWWedZW47f/587rvvPgByC3N5iqcoLCns8u9CRHoO3TIzWHZuNq/wCufmnqulO6RXiIuLIykpiaCgIABuu+025s6da35/7dq1eHh4AIeeSktKSiIiIgKAm266iVmzZpnbfvDBB7i6ugIQFBREUlISrq6ubNmyhVmzZnHFFVeY27799ts4OTkBh27dJSUlERoaCsCsWbMYP368ue3KlSuxs7MDYIDbAC7kQj3YINLHqSAymEM/B7zxxqGfg9FRRLpE//79GTlypPl1QEBAq/eHDx9u/rOTk1Ortn5+fvj5/W8NtKio/8167eDgYG67dOnSNuc9XFTBoRmz/3zcgQMHthrXNGzYMPOfPQd4MopRuLu6t+fjiUgvpVtmBgvwDWAGMwjwDThxYxHpcvsO7COJJPYd2Gd0FBExkAoigzU2NlJFFY2NjUZHEemTikqLWMMaikqLjI4iIgZSQWSw9Ox0nuRJ0rPTjY4i0ifFRsaylKXERsYaHUVEDKSCyGDBAcFcyZUEBwQbHUVERKTPUkFkMFcXV4YxDFcXV6OjiPRJOQU5rGY1OQU5RkcREQOpIDLYvgP7+I3fNKBTxCDWVtbYYIO1lX4civRl+glgsOLdxXzN1xTvLjY6ikifFBQQxCxmERQQZHQUETGQCiKDxUTEcB/3ERMRY3QUkT6ppaWFJppoaWkxOoqIGEgFkYj0adsztrOMZWzP2H7ixiLSa6kgMtiu/F28yZvsyt9ldBSRPmmw32Au5mIG+w02OoqIGEhLdxxHYmIiiYmJ5tW1LcHWxhZnnLG10f8KESMMcBvACEYwwG2A0VFExED6V/g4EhISSEhIICMjg3nz5lnkHIH+gVzGZQT6B1rk+CJyfAcqDpBCCgcqDuCLFlgW6at0y8xgzc3N1FNPc3Oz0VFE+qSC4gI+4iMKiguMjiIiBlJBZLDUzFSWs5zUzFSjo4j0SdHDormXe4keFm10FBExkAoigwX6B3I5l+uWmYhBbGxssMceGxsbo6OIiIFUEBnM3dWdaKJxd3U3OopIn5RXmMf7vE9eYZ7RUUTEQCqIDLa/fD9/8Af7y/cbHUWkT2puaaaBBppbNI5PpC9TQWSwwpJCPuMzCksKjY4i0icNCRzC1VzNkMAhRkcREQOpIDKYlu4QERExngoig1lZWWGDDVZWVkZHEemTtqVv40EeZFv6NqOjiIiBVBAZLLcgl3/zb3ILco2OItIn+fv4cwEX4O/jb3QUETGQCiIR6dM8B3gyilF4DvA0OoqIGEgFkcGCBwdzJVcSPDjY6CgifVJFVQU72EFFVYXRUUTEQCqIDGYymWimGZPJZHQUkT4przCPd3lX8xCJ9HFa3NVgKTtSeJiHOWvHWfjF+xkdR6TPiQyN5E7uxKvJi5LkEouco7aslrSP04i6JAonb6cuOaaTlxNugW5dciwRUUFkuADfAGYwgwDfAKOjiPRJbr5uuDu5s3bOWoufK3llcpcdy87JjoXpC1UUiXQRFUQG83D34DROw8Pdw+goIn3SgZYDbJ+2nb9d+zcG+w02Ok67lKWX8clVn1C7t1YFkUgXUUFksPLKclJJpbyyHF98jY4j0uc0NDSQX5KPW5gbvuG6BkX6Kg2qNlh+UT4f8AH5RflGRxHpk8LDw/nxxx8JDw83OoqIGEgFkcGih0WzmMVED4s2OoqIiEifpYLIYDY2NjjggI2NjdFRRPqkLVu24OrqypYtW4yOIiIG0hii40hMTCQxMZHq6mqLnSO/KJ8P+ZApRVPwHanxCyKnmq+vL0uXLsXXV9efSF+mgug4EhISSEhIICMjg3nz5lnkHE3NTdRQQ1Nzk0WOLyLHN2jQIG677TajY4iIwXTLzGBDAodwLdcyJHCI0VFE+qTKykoSExOprKw0OoqIGEgFkYj0adnZ2Zx33nlkZ2cbHUVEDKSCyGCHl+5I2ZFidBSRPik6OpqcnByio/Wkp0hfpjFEBvMb5MdkJuM3SOuYiRihX79+BAcHGx1DRAymHiKDeQ7wZDSj8RzgaXQUkT4pPz+fhQsXkp+vyVFF+jIVRAarrKokk0wqqzSgU8QINTU1bNq0iZqaGrZt20ZJyaEV76urq0lOTqaurg6AwsJCUlNTzfulpqZSVFQEQF1dHcnJydTU1ABQUlJCSsr/boOnpaVRUFAAQH19PcnJyVRVVQGwe/dutm7dam6bkZFBXl4eAI2NjSQnJ1NRUQFAWVkZf/zxh0W+B5G+TgWRwXILc/k3/ya3MNfoKCJ9UmRkJMnJyURGRjJ58mReffVVAFJSUoiPj2fXrl0APP3001xyySXm/WbMmMFzzz0HQFZWFvHx8aSlpQHw8ssvM3XqVHPbWbNm8fjjjwOHCqv4+HiSkpIAeOuttzjnnHPMbefMmcPDDz8MwN69e4mPj+fHH38E4P3332fMmDEW+R5E+jork8lkMjpEd3d4HqJVq1Z1+XpH+b/m88yYZ7j1l1sJPCOwS48tIh2zbds2vL298fX1pbq6mszMTCIjI3F0dKSwsJCKigrz4OvU1FTc3d3x9/enrq6O9PR0wsPDcXZ2pqSkhL179xITEwMc6iFycXFh8ODB1NfXk5aWRlhYGC4uLuzevZvS0lJGjBgBHPp54+DgQFBQEI2NjaSkpDB06FDc3NwoKyujsLCQ2rxarr74at7+5G3O+stZhn1fIr2JBlUbzM7ODhdcsLOzMzqKSJ8XGxtr/nP//v0ZOXKk+XVAQAABAQHm139+Ks3R0bFVW19f31YzX0dFRZn/7ODg0KrtoEGDGDRokPn1n3/psrOza9XW29sbb29vfi38FWecsbXRj3CRrqJbZgYrLCnkMz6jsKTQ6Cgi0kME+gdyGZcR6K9eZZGuooLIYPUN9ZRRRn1DvdFRRKSHaG5upp56mpubjY4i0mt0uiDKyclh3bp15qcqABoaGnjyySe55JJLuOKKK1izZk2XhOzNQoNDmctcQoNDjY4iIj1EamYqy1lOambqiRuLSLt0uiB6++23efnll3FycjJvW7lyJZ9//jm1tbXs2bOHJ5980vwkhYiIdI1A/0Au53LdMhPpQp0uiNLT0znttNOwsrICoKmpiS+//JLIyEg+++wz3nvvPdzd3Xn//fe7LGxvpN/0RKSj3F3diSYad1d3o6OI9BqdLoj279/f6smItLQ0amtrmTFjBv369cPLy4uzzjpLCyaewEDPgYxjHAM9BxodRUR6iP3l+/mDP9hfvt/oKCK9RqcLIhsbGxobG82vt23bhpWVFaeddpp5m5ubm3mGVTk6b09vzuIsvD29jY4iIj2Enk4V6XqdLoh8fHxaTSG/YcMGfH198fHxMW8rKyvDzc3t5BL2ctU11eSQQ3VNtdFRRKSHiImI4T7uIyYixugoIr1Gpwui888/n+zsbBYsWMDNN99MdnY2kyZNatUmMzOz1URm0tau/F28yZvsyt9ldBQR6SGsrKywwcY8hlNETl6nC6JLLrmEiRMnsmPHDlJSUjj99NO5+uqrze+np6eTm5vbapZVaWvYkGHcwi0MGzLM6Cgi0kPkFvz/ayAW5BodRaTX6PS87/b29jz44IPU1NRgZWXV6vF7ODR1/auvvtrqFpq05dDPAU88cejnYHQUERGRPqvTPURbtmxh9+7dODs7tymGANzd3XF1ddVTZidQVFrEl3xJUWmR0VFEpIcIHhzMlVxJ8OBgo6OI9BqdLoj+9re/8dVXXx23zTfffMPf/va3zp6iT6iprSGXXGpqa07cWEQEMJlMNNOMyWQyOopIr9Hpgqg9F6LJZNKgvxMYNmQYN3GTxhCJSLul7EjhYR4mZUeK0VFEeg2LLu5aWFiIs7OzJU8hItLnBPgGMIMZBPjqKV6RrtKhQdXLly9v9fqHH36gtLS0Tbvm5mbKysrYunUrZ5xxxskl7OXSs9J5kicZlzUO35G+RscRkR7Aw92D0zgND3cPo6OI9BodKoj+PGbIysqK7OzsYw6atrKyIiIigptvvvnkEvZyHu4ejGSkfrCJSLuVV5aTSirlleX4ol+kRLpChwqi9957Dzg0NmjWrFlcfvnlXHbZZW3aWVtb4+LigqOjY9ek7MUGeQ/iHM5hkPegEzcWEQHyi/L5gA+4oegGIok0Oo5Ir9ChgujPcwotXryYYcOGaZ6hk1RbV0sRRdTW1RodRUR6iOhh0SxmMdHDoo2OItJrdHpQ9dSpUxk6dGhXZumTsnOzWcUqsnM1X5OItI+NjQ0OOGBjY2N0FJFeo9MzVR+WlpbGjh07qK6upqWlpc37VlZWXHvttSd7mpN26623kpaWZv4BEhERwdNPP21wKggLCWMBCwgLCTM6ioj0EPlF+XzIh5y+8XSjo3SYk5cTboFa9Fu6n04XRJWVldx7771s3779uHMSdZeCCOCuu+7i/PPPNzpGK44Ojvjgg6ODxluJSPvYudpRZ13HutvW8Tu/Gx2nQ+yc7FiYvlBFkXQ7nS6InnvuOVJSUoiLi2PKlCkMHDhQ3bedULKnhEQSuWjPRXpaRETaZeSEkSTlJFG7t2eNPSxLL+OTqz6hdm+tCiLpdjpdEG3atInIyEieeuqpLp+Nura2ljfffJOsrCyysrKoqKhgzpw5XH/99Udt+8orr7B+/XqqqqoIDAxk9uzZTJo0qU3bZ599lmeffZahQ4eycOFCwsKMv01VWVVJKqlUVlUaHUVEehC3QDcVFSJdqNODqg8ePMiIESMssjRHRUUFa9asobGxkXHjxh237ZIlS1i3bh1z5szhscceIyIiggcffJBvvvmmVbsFCxbw3nvv8eGHHzJ27FjuvPNOqquruzx7R4UPDWcRiwgfGm50FBHpIf744w/69evHH3/8YXQUkV6j0z1EYWFhR52luiv4+PjwxRdfYGVlRXl5OWvXrj1qu02bNrF582buv/9+EhISABg5ciSlpaW8+OKLnHvuuebbeFFRUeb9/vrXv/Lll1+yfft2xowZ0+a4e/fuZd++febXeXl5XfnxREROSkBAACtWrCAgQEt3iHSVThdE1113HXfffTepqalER3ftXBjt7XX64YcfcHR0ZOLEia22T5s2jYceeoi0tDRiYmKOeY5jDQb//PPPeeONNzoSudMydmbwLM8yYecELd0hIu3i7e3NwoULjY4h0qt0uiAqKytj7Nix3HrrrZx33nmEhYUdcyHXKVOmdDrg8eTk5BAUFIStbeuPcXh+pJycHGJiYqiqqmLHjh3mW3yfffYZ+/fvZ/jw4Uc97vTp0znrrLPMr/Py8li2bJlFPoNLfxfCCcelv4tFji8ivU9FRQU//vgjZ599Nm5uGkck0hU6XRD985//NPeyfPXVV3z11VdtenZMJhNWVlYWK4gqKirw8/Nrs93F5VBxUVl5aKByc3MzK1euJD8/H1tbW0JDQ3nsscfM7Y7k5eWFl5eXRTIfyW+QH+dzPn6D2n4OEZGj2blzJxdeeCFJSUmMHDnS6DgivUKnC6LFixd3ZY5Oa8/tNXd3d1atWnUK0nRcXX0de9hDXX2d0VFEpIeIiYmhuLj4lP3iJtIXdLogmjp1alfm6BQ3NzcqKirabK+qqgLA1dX1VEfqsKycLF7gBabnTGfImUOMjiMiPYCdnR2+vhpzKNKVOv3YfXcwZMgQ8vLyaGpqarV9165dAISEhBgRq0OGBg3lBm5gaJDWhROR9snLy2Pu3Ll6AlakC3W6h2j37t3tbjto0KDOnua4xo0bx5o1a9i4cWOriRjXrVuHl5dXq0ftOyMxMZHExESLzlfk7OTMYAbj7HT0AekiIkeqr68nNTWV+vp6o6OI9BqdLohmzpzZrvE7VlZWrF+/vsPH/+WXX6ivr6e29tDU9Hl5eWzYsAGAMWPG4ODgwJgxYxg1ahQrVqygtrYWf39/vv32W3799VeWLFly0kuJJCQkkJCQQEZGBvPmzTupYx3L7rLdbGQjM8pmaOkOEWmX8PBwNm3aZHQMkV6l0wXR5MmTj1oQVVdXs3PnTkpKSoiLi8PHx6dTx1+xYkWriR/Xr19vLqzee+898/3zZcuWsWrVKl599VXz0h0PPPDAUZfu6I72le/jd35nX/m+EzcWERERi+h0QXTvvfce8z2TycS7777Lf/7zH+6+++5OHf/9999vVzsnJycWLVrEokWLOnUeo0WFRXEHdxAVdnK390Sk79i6dSvnnHMO69evZ8SIEUbHEekVLDKo2srKiiuuuIKQkBBeeOEFS5xCRKTP8vHx4Z577ul0D7yItGXRp8zCw8NJTk625Cl6vKycLF7iJbJysoyOIiI9xKBBg7jzzjst9sCKSF/U6Vtm7VFUVERzc7MlT2FRp+IpM0cHRwYzGEcHR4udQ0R6l6qqKpKSkoiPjz/mjPsi0jFd3kPU0tLC7t27efPNN/npp5+6fOHXUykhIYHly5dzyy23WOwcAb4BXMAFBPhq1WoRaZ+srCzOOeccsrKyKCgoIC0tzfxeSkoKJSUlANTU1JCcnExd3aGZ8IuKikhNTTW3TU1NpbCwEIC6ujqSk5PNvwCWlJTw7bffsnTpUkpKSkhPTyc/Px+AhoYGkpOTzcsj7d69my1btpiPm5GRQW5uLgCNjY0kJydTXl5uke9CpKt0uiCaMGECEydObPPfueeey1//+ldee+01nJ2duemmm7oyb6/TcLCBAxyg4WCD0VFEpIeIiooiKyuLqKgoHn/8cWbNmmV+b+rUqbz88ssApKWlER8fT1bWoVvyzz33HDNmzDC3veSSS3j66aeBQxPaxsfHk5KSAsCrr77KFVdcYW47e/ZsHn30UeBQsRQfH89vv/0GwOrVqxk/fry57Q033MDSpUsBKC8vJz4+nu+//559B/axmc3sO6CnaqX7sTKZTKbO7Hjrrbce9bF7KysrXFxcCA8PZ9q0aXh4eJx0SKMdnodo1apVhIeHd+mxv179NVOumsK6d9YxefbkLj22iPR+BQUFVFVVmSeiTUlJwcvLC19fX2pqasjIyCAyMhJHR0eKioooLy8399ynpqbi5uZGQEAAdXV1pKenM2zYMPr3709JSQllZWXExsYCkJ6ejrOzM4GBgTQ0NJCamkpoaCiurq7s3r3bPNUKHPqZ2a9fP4KDg2lsbCQlJYUhQ4bw6xe/MvWqqXz1zlf6eSfdTqcLor7EkgVR5veZLJuwjCUblzBs/LAuPbaISHdSklzCyviVzE+aj+9ITUQr3UuPXsusN3Dp78JQhuLSXwMjRUREjNIlT5mlpKSQnZ1NTU0NTk5OhIWFERMT0xWH7vXK9pXxMz9z8b6LtXSHiPRqu/J38TZvk5CfoB4i6XZOqiBKS0vjH//4h/kpBZPJZB5XFBAQwOLFixk+fPjJp+zFdu/dzQY2sHtv+xfLFRHpiWysbehHP2ysT26dSRFL6HRBlJuby9///nfq6+sZPXo0cXFxeHh4cODAAf744w9+++037rjjDl566SWCg4O7MPKpcyrmIRoePpx7uZfh4SocRaR3CwoIYiYzCQoIMjqKSBudLojeeOMNmpqaeOKJJzj99NNbvXfllVeyefNm7r77bt544w3z45c9zalY7V5EpK9obm7mIAd79IS90nt1elD1H3/8wYQJE9oUQ4eNGjWKCRMm8Mcff3Q6XF+QnZvNq7xKdm620VFERCwqNTOVf/APUjNTT9xY5BTrdEFUU1ODr+/xB8UdngdDjq2ffT888KCffT+jo4iIWNRgv8FcyqUM9htsdBSRNjpdEHl6eraaAv5o0tLS8PT07Owp+oTBfoO5mIv1A0JEer0BbgOIIYYBbgOMjiLSRqcLorPPPpstW7bwyiuv0NDQetmJhoYGXnvtNf744w/OPvvskw7ZmzU2NlJDDY2NjUZHERGxqAMVB9jKVg5UHDA6ikgbnR5Ufe211/Lzzz/zzjvv8PnnnxMZGcmAAQM4cOAAO3bsoLy8HD8/P6699tquzNvrpGen8ziPMyl7EoFnBBodR0TEYgqKC/iET7ix+EaiiDI6jkgrnS6IXF1defnll3nhhRf47rvv+OWXX8zv2dvbM3XqVBYsWICrq2uXBO2tggKCmMUsPYYqIr3e8PDhLGGJphmRbumkJmZ0dXVl8eLF3HHHHeTl5VFbW4uTkxNBQUHY2nbJJNiGOhXzELm5uBFBBG4ubhY7h4hId2BtbY0ttlhba9Uo6X46/LfyrbfeYuXKlTQ1NZm32draMnToUGJiYhg6dCgmk4lVq1bxzjvvdGnYUy0hIYHly5dzyy23WOwc+w7sYzOb2Xdgn8XOISLSHeQV5vEu75JXmGd0FJE2OlQQbd68mddeew1XV9fj9gDZ2dnh6urKK6+8QlJS0kmH7M2KSov4gi8oKi0yOoqIiEW1mFpoppkWU4vRUUTa6FBB9PXXX+Pi4sIll1xywrYXX3wxLi4ufPXVV50O1xfERsbyAA8QGxlrdBQREYsKGRzCbGYTMjjE6CgibXSoINq+fTvx8fHY29ufsK29vT2jRo1i+/btnQ4nIiIicip0qCDau3cvfn5+7W7v6+vLvn0aG3M8u/J38TZvsyt/l9FRREQsalv6NpaylG3p24yOItJGhwoia2vrVoOpT6SpqUlPE5yAjbUN/eiHjbWN0VFERCzK38efi7gIfx9/o6OItNGhasXT05OcnJx2t8/JycHLy6vDofqSoIAgZjJT8xCJSK/nOcCTeOLxHKAlnaT76VBBFBsbS3JyMiUlJSdsW1JSQnJyMiNGjOh0uL6gubmZgxykubnZ6CgiIhZVXllOGmmUV5YbHUWkjQ4VRBdffDFNTU3cf//9lJeXH7NdRUUFDzzwAM3NzcyYMeNkM/ZqqZmp/IN/kJp5/IVyRUR6uvyifN7nffKL8o2OItJGh6aTDg8P5/LLL+eDDz7gmmuuYcaMGZx22ml4e3sDhwZdJyUlsWbNGsrLy5k5cybh4eEWCX4qnIqZqgf7DeZSLtVq9yLS60WFRXEXd+Hd7E1J8onvNHRGbVktaR+nEXVJFE7eTl1yTCcvJ9wCtZpAb2dlMplMHdnh8CzU//nPfzjariaTCWtra6688krmzp2LlZVVl4U1SkZGBvPmzWPVqlVdXuCVJJewMn4l85Pm4zvSt0uPLSLSnVTkV/B85PM01jYaHaVD7JzsWJi+UEVRL9fhBcesrKyYP38+F1xwAV9++SXbt29n//79AHh4eBATE8PUqVPx99dTBO1xoOIAW9nKgYoD+KKCSER6r/3N+9l6/lZuu/42Av0DjY7TLmXpZXxy1SfU7q1VQdTLdXoFVn9/f+bNm9eVWfqkguICPuETbiy+kSiijI4jImIxjY2N7D6wmwHhA/Adpl8ApXvp+UvS93DDw4ezhCUMDx9udBQREYsaNmwYGzZsMDqGyFFp1kSDWVtbY4utJrAUERExkP4VNlheYR7v8i55hXlGRxERsagtW7bg7OzMli1bjI4i0oYKIoO1mFpoppkWU4vRUURELMrPz49//vOfHVoTU+RU0Rgig4UMDmE2swkZHGJ0FBERixo4cCC33nqr0TFEjko9RCIickpUVlby9ddfU1lZaXQUkTZUEBlsW/o2lrKUbenbjI4iImJR2dnZTJkyhezsbKOjiLShW2bHcSqW7vD38eciLsLfRxNZikjvNnz4cAoKChg4cKDRUUTaUEF0HAkJCSQkJJiX7rAEzwGexBOP5wBPixxfRKS7sLe3JyAgwOgYIkelW2YGK68sJ400yivLjY4iImJR+fn53HjjjeTna7V76X5UEBksvyif93mf/CL9gBCR3q22tpbk5GRqa2uNjiLShm6ZGSwqLIq7uIuoMK1jJiK9W0REBL///rvRMUSOSj1EBrO1tcUJJ2xtVZuKiIgYRQWRwfKL8vmIj3TLTER6vW3btuHt7c22bZpmRLofFUQGa2xqpJJKGpsajY4iImJRAwcO5LbbbtNj99It6T6NwYYGDeU6rmNo0FCjo4iIWJSPjw/33HOP0TFEjko9RCIickpUV1fz448/WnSyW5HOUkFksO0Z23mER9iesd3oKCIiFpWZmcm4cePIzMw0OopIGyqIDObj7cMkJuHj7WN0FBERi4qKimLHjh24urqSlpZm3r59+3aKi4uBtnMVFRcXs337/35hTEtLo7CwEID6+nqSk5PNPU6lpaV8++23LF26lJKSEnbs2GGeBPLgwYMkJyebF5bds2cPW7ZsMR83MzOTnJwcAJqamkhOTubAgQMW+iakO1JBZDAvDy/GMAYvDy+jo4iIWJSDgwPh4eG88MILXH755ebtF154IS+88AIAO3bsID4+nh07dgDwwgsvcOGFF5rbXn755axYsQKAvLw84uPjzYXN66+/zsyZM81tr776ah555BHgUAEUHx/Ppk2bAHj33Xc566yzzG3nz5/PfffdB0BlZSXx8fGsX7+efQf2kUQS+w7s6+qvQ7oZDao2WFV1FdlkU1VdhS++RscREbG42267jblz55pfr127Fg8PD+DQ5I1JSUlEREQAcNNNNzFr1ixz2w8++ABXV1cAgoKCSEpKYtiwYQBcd911XHDBBcTGxgLw9ttv4+TkBBx6wi0pKYnQ0FAAZs2axfjx483HXblyJXZ2dgC4urqSlJRESEgIv335G2tYw8LShQxnuEW+D+kerEwmk8noEN3d4cVdV61aRXh4eJce++vVXzPlqimse2cdk2dP7tJji4jIySlJLmFl/ErmJ83Hd6R+ae3NdMvMYBGhEfydvxMRGmF0FBERkT5Lt8yOIzExkcTERIs+ImpvZ48bbtjb2VvsHCIi0jk5BTmsZjXnFZynHqJeTj1Ex5GQkMDy5cu55ZZbLHaOwpJC1rCGwpJCi51DREQ6x9rKGhtssLbSP5e9nf4PG6yuvo4SSqirrzM6ioiIHCEoIIhZzCIoIMjoKGJhKogMFhYSxnzmExYSZnQUERE5QktLC0000dLSYnQUsTAVRCIiIsewPWM7y1im1QT6ABVEBkvLSuMxHiMtK+3EjUVE5JQa7DeYi7mYwX6DjY4iFqaCyGBeA7wYy1i8BmimahGR7maA2wBGMIIBbgOMjiIWpoLIYAO9BjKOcQz0Gmh0FBEROcKBigOkkMKBCq1r1tupIDJYTW0NeeRRU1tjdBQRETlCQXEBH/ERBcUFRkcRC1NBZLCdeTt5ndfZmbfT6CgiInKE6GHR3Mu9RA+LNjqKWJgKIoMNGzKMm7mZYUOGGR1FRESOYGNjgz322NjYGB1FLEwFkcEc+jnghRcO/RyMjiIiIkfIK8zjfd4nrzDP6ChiYSqIDFa8u5h1rKN4d7HRUURE5AjNLc000EBzS7PRUcTCVBAZrLqmmp3spLrGcgvIiohI5wwJHMLVXM2QwCFGRxELU0FksGFDhrGQhRpDJCIiYiBbowOIiIh0V9vSt/EgDxLxZQTjGW90nHZz8nLCLdDN6Bg9igoig+3I3sG/+Bfjs8fjO9LX6DgiIvInoVGhTLebTtJ9Sey4b4fRcdrNzsmOhekLVRR1gAoig7m7uRNLLO5u7kZHERGRIww9bShvZr9J7d5ai52jtqyWtI/TiLokCidvp5M+Xll6GZ9c9Qm1e2tVEHWACiKD+Xj7MIlJ+Hj7GB1FRESOUF5ezvdbvmf8+PG4u7tb7DxDJw+12LGlfTSo2mC1dbUUU0xtneV++xARkc7ZtWsXM2bMYNeuXUZHEQtTQWSw7NxsVrKS7Nxso6OIiMgRYmJi2LNnDzExMUZHEQvTLbPjSExMJDExkepqy80RFBocynzmExocarFziIhI59jZ2eHt7W10DDkF1EN0HAkJCSxfvpxbbrnFYudwcnTCDz+cHE9+IJ2IiHSt3Nxc5syZQ25urtFRxMJUEBmstKyUb/mW0rJSo6OIiMgRGhoayM7OpqGhwegoYmG6ZWaw8opytrGN8opyo6OIiMgRwsPD+fHHH42OIaeAeogMFhEawd/5OxGhEUZHERER6bNUEImIiBzDli1bcHV1ZcuWLUZHEQtTQWSwzF2ZPM/zZO7KNDqKiIgcwdfXl6VLl+Lrq6WVejuNITJYf+f+DGUo/Z37Gx1FRESOMGjQIG677TajY8gpoB4ig/kN8mMKU/Ab5Gd0FBEROUJlZSWJiYlUVlYaHUUsTAWRweob6tnLXuob6o2OIiIiR8jOzua8884jO1urCfR2KogMlrkrk+d4TmOIRES6oejoaHJycoiOjjY6iliYxhAZbGjQUK7jOoYGaaVjEZHupl+/fgQHBxsdQ04B9RAZzNnJmSCCcHZyNjqKiIgcIT8/n4ULF5Kfn290FLEwFUQG27N3Dz/wA3v27jE6ioiIHKGmpoZNmzZRU1NjdBSxMN0yM9jeA3vZxCb2HthrdBQRETlCZGQkycnJRseQU0A9RAaLCoviLu4iKizK6CgiIiJ9lgoiERGRY9i2bRu+vr5s27bN6ChiYSqIDJaVk8VKVpKVk2V0FBEROYK3tzcLFy7E29vb6ChiYRpDZDBHB0d88cXRwdHoKCIicgRfX1+WLFlidAw5BdRDZLAA3wAu4iICfAOMjiIiIkeorq5m06ZNVFdXGx1FLEwFkcEONh6kggoONh40OoqIiBwhMzOTM888k8zMTAoLC0lNTTW/l5qaSlFREQB1dXUkJyebH88vKSkhJSXF3DYtLY2CggIA6uvrSU5OpqqqCoDdu3ezdetWc9uMjAzy8vIAaGxsJDk5mYqKCgDKysr4448/zG2zsrLIyckBoLm5meTkZMory7v6a+gTVBAZbEf2Dv7Fv9iRvcPoKCIicoTIyEi2b99OZGQkTz/9NJdccon5vRkzZvDcc88BhwqT+Ph40tLSAHj55ZeZOnWque2sWbN4/PHHASgsLCQ+Pp6kpCQA3nrrLc455xxz2zlz5vDwww8DsHfvXuLj4/nxxx8BeP/99xkzZoy57f/93/9x7733AofmTIqPj+eHX3/o8u+hL9AYIoOFDA7hKq4iZHCI0VFEROQIjo6O5nXMFi1axJw5c8zvffbZZ7i7uwMQFhZGUlIS4eHhANx4441ceuml5rbvvvsuLi4uAAQEBJCUlERYWBgA11xzDeeff7657RtvvIGDgwMAXl5eJCUlMXTooeWdZs6cyZlnnmlu++KLL2Jre+ifcmdnZ5KSkqgvqOdLvmR/+X588e3Kr6NXszKZTCajQ3R3GRkZzJs3j1WrVpn/sneVkuQSVsavZH7SfHxH6i+uiIicnK9Xf82Uq6aw7p11TJ492eg4PYZumRls7/69/MIv7N2vmapFROTkxUTEcB/3ERMRY3SUHkUFkcFKy0r5lm8pLSs1OoqIiPQCVlZW2GCDlZWV0VF6FBVEBhsePpz/x/9jePhwo6OIiEgvkFuQy7/5N7kFuUZH6VFUEImIiEifp4LIYDvzdvI6r7Mzb6fRUUREpBcIHhzMlVxJ8OBgo6P0KCqIDGZna4crrtjZ2hkdRUREegGTyUQzzegh8o5RQWSwQP9ALuVSAv0DjY4iIiK9QMqOFB7mYVJ2pJy4sZj1uYJo+/btTJgwgTfffNPoKAA0NTVRSy1NTU1GRxERkV4gwDeAGczQGpkd1KcKopaWFp599lkiIyONjmKWlpXGYzxGWlaa0VFERKQX8HD34DROw8Pdw+goPUqfKog+//xzYmJiCAzsPrenAv0DmclM3TITEZEuUV5ZTiqpWuS1g7plQVRbW8uLL77IbbfdxkUXXcT48eN57bXXjtn2mWee4eKLLyYhIYHrr7+eb7/9tk27iooKPvzww1br0HQH7q7uRBGFu6u70VFERKQXyC/K5wM+IL8o3+goPUq3LIgqKipYs2YNjY2NjBs37rhtlyxZwrp165gzZw6PPfYYERERPPjgg3zzzTet2q1cuZKZM2fSv39/S0bvsH0H9pFEEvsO7DM6ioiI9ALRw6JZzGKih0UbHaVH6Zar3fv4+PDFF19gZWVFeXk5a9euPWq7TZs2sXnzZu6//34SEhIAGDlyJKWlpbz44ouce+652NjYkJGRQWZmJrfffnu7zr9371727ftfgZKXl3fyH+oYikqLWMMaFpYuZDiarVpERE6OjY0NDjhgY2NjdJQepVsWRO1df+WHH37A0dGRiRMntto+bdo0HnroIdLS0oiJiWHr1q3k5uYyY8YMAOrq6rC2tqawsJD/9//+X5vjfv7557zxxhsn+zHaJTYylqUsJTYy9pScT0REerf8onw+5EOmFE3Bd6Sv0XF6jG5ZELVXTk4OQUFB2Nq2/hhDhw41vx8TE8OFF17Yqmh6/vnn8fHx4corrzzqcadPn85ZZ51lfp2Xl8eyZcu6/gOIiIh0sabmJmqooalZ07l0RI8uiCoqKvDz82uz3cXFBYDKykoAnJyccHJyMr/fr18/nJyccHNzO+pxvby88PLyskDitnIKcljNas4rOE+VvIiInLQhgUO4lmsZEjjE6Cg9So8uiKD9t9f+7N5777VAks6xtrLGBhusrbrl+HYREZE+oUf/K+zm5kZFRUWb7VVVVQC4urqe6kgdFhQQxCxmERQQZHQUERHpBbR0R+f06IJoyJAh5OXltVn2YteuXQCEhIQYEatDWlpaaKKJlpYWo6OIiEgv4DfIj8lMxm9Q2yElcmw9uiAaN24cdXV1bNy4sdX2devW4eXlRVRU1EkdPzExkcWLF/Pss8+e1HGOZ3vGdpaxjO0Z2y12DhER6Ts8B3gymtF4DvA0OkqP0m3HEP3yyy/U19dTW1sLHHrSa8OGDQCMGTMGBwcHxowZw6hRo1ixYgW1tbX4+/vz7bff8uuvv7JkyZKTnoMhISGBhIQEMjIymDdv3sl+pKMa7DeYi7mYwX6DLXJ8ERHpWyqrKskkk8qqSnzRwzrt1W0LohUrVlBaWmp+vX79etavXw/Ae++9h6/vof/Jy5YtY9WqVbz66qtUVVURGBjIAw88wKRJkwzJ3VED3AYwghEMcBtgdBQREekFcgtz+Tf/5prCawgn3Og4PUa3LYjef//9drVzcnJi0aJFLFq0yMKJLONAxQFSSOFAxQFV8iIictIiQyO5nduJDI00OkqP0qPHEPUGBcUFfMRHFBQXGB1FRER6ATs7O1xwwc7OzugoPYoKIoNFD4vmXu7VInwiItIlCksK+YzPKCwpNDpKj9Jtb5l1B4mJiSQmJlJdXW2xc9jY2GCPvRbhExGRLlHfUE8ZZdQ31BsdpUdRD9FxJCQksHz5cm655RaLnSOvMI/3eZ+8wjyLnUNERPqO0OBQ5jKX0OBQo6P0KCqIDNbc0kwDDTS3NBsdRUREpM9SQWSwIYFDuJqrtQifiIh0idTMVJaznNTMVKOj9CgqiERERHqRgZ4DGcc4BnoONDpKj6KCyGDb0rfxIA+yLX2b0VFERKQX8Pb05izOwtvT2+goPYoKIoP5+/hzARfg7+NvdBQREekFqmuqySGH6hrLPSHdG+mxe4N5DvBkFKO0CJ+IiHSJXfm7eJM3mbpxKv2d+xsdp92cvJxwC3Qz7PwqiI7jVMxDVFFVwQ52UFFVoaU7RETkpMWdHsdtDreRcl8KO+7bYXScdrNzsmNh+kLDiiIVRMdxKla7zyvM413eZU7hHCKIsMg5RESk7xg0bBD3Z9xP7d5ai52jtqyWtI/TiLokCidvp5M+Xll6GZ9c9Qm1e2tVEPVVkaGR3MmdWoRPRES6REFBAY8/8Th33nkngwcPtth5hk4earFjG0GDqg1mZ2eHM85ahE9ERLpEVVUVGzZsoKqqyugoPYoKIoMVFBfwCZ9otXsREekSUVFRbNu2jaioKKOj9CgqiAzWcLCB/eyn4WCD0VFERET6LBVEBgsNDuUGbtAifCIi0iVSUlIICAggJSXF6Cg9igoiERGRXsTLy4u5c+fi5eVldJQeRU+ZHcepmIdoe8Z2/sE/ODPjTHxHah4iERE5Ob6+vixdutToGD2OeoiOIyEhgeXLl3PLLbdY7ByDvAYxkYkM8hpksXOIiEjfUVNTw++//05NTY3RUXoUFUQG8/b05kzO1CJ8IiLSJTIyMhg9ejQZGRlGR+lRVBAZrKq6ip3spKpa80WIiMjJi4yMZOvWrURGasLfjlBBZLCcghze5m1yCnKMjiIiIr2Ao6MjsbGxODo6Gh2lR1FBZLDwoeEsYhHhQ8ONjiIiIr1AUVER99xzD0VFRUZH6VFUEBmsn30/BjCAfvb9jI4iIiK9QHl5OR988AHl5eVGR+lRVBAZrLCkkC/4gsKSQqOjiIhILxAdHU12djbR0dFGR+lRVBAZrK6+jgIKqKuvMzqKiIhIn6WJGY/jVEzMGBYSxgIWEBYSZrFziIhI35Gamsoll1zCxx9/rF6iDlBBdBwJCQkkJCSQkZHBvHnzjI4jIiJyQm5ubkyfPh03Nzejo/QoumVmsLSsNJ7gCdKy0oyOIiIivUBAQACPP/44AQEBRkfpUVQQGczT3ZPTOR1Pd0+jo4iISC9QV1dHamoqdXUam9oRKogMNsh7EBOYwCBvrWUmIiInLz09neHDh5Oenm50lB5FBZHBamprKKCAmlotwiciIidv2LBh/PzzzwwbNszoKD2KCiKD7czbyau8ys68nUZHERGRXqB///6MHTuW/v37Gx2lR1FBZLCwkDBu4iY9di8iIl2ipKSEZcuWUVJSYnSUHkUFkcEcHRwZyEAcHbQIn4iInLyysjKef/55ysrKjI7So6ggMljx7mL+y38p3l1sdBQREekFYmNjKSkpITY21ugoPYoKIoNVVVeRQQZV1VVGRxEREemzVBAZLHxoOLdwC+FDw42OIiIivUB6ejojR44kPT2dhoYGkpOTqaysBGD37t1s2bLF3DYjI4Pc3FwAGhsbSU5Opry8HDh06y05OdncNisri127dgFQWFjIjTfeSFraoUmF9+/fT3JyMi0tLQDs2rWL7Oxs877Jycns3bsXgAMHDpCcnExTUxMAOTk53eLBIhVEx5GYmMjixYt59tlnjY4iIiLSLs7OzowdOxYvLy9KSkqIj4/nt99+A2D16tWMHz/e3PaGG25g6dKlAJSXlxMfH8/3338PwMcff8zo0aPNbW+++WbuvvtuAPLy8li5ciWffvopAF9++SXx8fE0NjYCcMcdd7Bo0SLzvvHx8ea269evJz4+3lyk3Xfffdz1yF1d/0V0kJXJZDIZHaK7O7yW2apVqwgP79qenA0fbOCSmZfw8fsfM/HyiV16bBER6Zvq6upwdHSkoaGB1NRUQkNDcXV1Zffu3ZSUlBAXFwcc+vetX79+BAcH09jYSEpKCkOGDMHd3Z2ysjIKCgoYOXIkcKiHyMbGhiFDhlBYWMjDDz/MokWLiIqKYv/+/eTm5hIXF4e1tTW7du2ipaWF0NBQ4FAPUWBgIF5eXhw4cICcnBxiY2OxtbUlJyeHoi1FfHvJt8xPmo/vSF9DvjMt7mowVxdXoonG1cXV6CgiItJLODoeenK5X79+5oIGYNCgQQwa9L+VEf78S76dnV2rtt7e3nh7e5tfh4X9b3qYgIAAXn75ZfNrDw8PPDw8zK+HDBnSKs+fjztgwAAGDBhgfh0SEkL2L9k8wiOcmXGmYQWRbpkZzHegLwkk4DvQmL8AIiIiRvPx9mESk/Dx9jEsgwoig9XV11FKKXX1WoRPRET6Ji8PL8YwBi8PL8MyqCAyWFZOFi/xElk5WUZHERERMURVdRXZZBs6BY0KIoOFBocyj3mEBocaHUVERMQQOQU5vMM75BTkGJZBBZHBnByd8McfJ0cno6OIiIgYIiI0gr/zdyJCIwzLoILIYLvLdrOe9ewu2210FBEREUPY29njhhv2dvaGZVBBZLD95ftJJpn95fuNjiIiImKIwpJC1rCGwpJCwzKoIDJYZFgkt3M7kWGRRkcRERExRF19HSWUGPrEtQoiERERMVRYSBjzmU9YSNiJG1uICiKDZe7K5AVeIHNXptFRRERE+iwVRAZzdnImmGCcnZyNjiIiImKItKw0HuMx0rLSDMuggshg/j7+TGMa/j7+RkcRERExhNcAL8YyFq8Bmqm6z6pvqGcf+6hvqDc6ioiIiCEGeg1kHOMY6DXQsAxa7f44EhMTSUxMpLq62mLnyNyVybM8ywW7LiBkbIjFziMiItJd1dTWkEceNbU1hmVQQXQcCQkJJCQksG3bNm6++Wby8vK6/Bw2NjbMcp6FjY0NGRkZXX58ERGR7m7T5k287/w+4zePp9m7ucuPHxQUhIODw3HbWJlMJlOXn7mX+e9//8uyZcuMjiEiIiKdsGrVKsLDw4/bRgVRO5SXl/Pbb7/x6aefsmjRonbv9+yzz3LLLbcct01eXh7Lli1jyZIlBAUFnWzUXqE935tRjMhmqXN2xXFP5hid3bcj++ka7JzufA3Cqc/Xna/Bkz1OZ/bt6D7d4TpsTw+Rbpm1g7u7O+effz7ffffdCSvMP+vfv3+72wcFBXXo2L1ZR763U82IbJY6Z1cc92SO0dl9O7KfrsHO6c7XIJz6fN35GjzZ43Rm347u01OuQz1l1gEJCQkWbS+HdOfvzYhsljpnVxz3ZI7R2X07sl93/rvUnXX37+1U5+vO1+DJHqcz+/bWfwt1y8xgGRkZzJs3r133N0Wk6+kaFDFed7gO1UNkME9PT+bMmYOnp6fRUUT6JF2DIsbrDteheohERESkz1MPkYiIiPR5KohERESkz1NBJCIiIn2eCiIRERHp81QQiYiISJ+ngqibO3jwIP/85z+59NJLmTJlCgsWLCAlJcXoWCJ9ytKlS5kxYwZTpkxhzpw5/Pzzz0ZHEumztm/fzoQJE3jzzTe79Lh67L6bq6ur47333mPq1Kl4e3vz9ddf88ILL/DBBx+ccF0WEekaOTk5BAQEYGdnR1paGrfffjvvvvsubm5uRkcT6VNaWlr4v//7P6ysrBg7dizXXnttlx1bPUTdnKOjI3PmzGHQoEFYW1szdepUWlpaKCwsNDqaSJ8REhKCnZ0dADY2NjQ2NrJ3716DU4n0PZ9//jkxMTEEBgZ2+bG1uGsXq62t5c033yQrK4usrCwqKiqYM2cO119//VHbvvLKK6xfv56qqioCAwOZPXs2kyZNOubx8/LyaGhowM/Pz5IfQ6THstQ1+NBDD/H9999z8OBBxowZw5AhQ07FxxHpkSxxHVZUVPDhhx/y0ksv8cwzz3R5ZhVEXayiooI1a9YwdOhQxo0bx9q1a4/ZdsmSJezYsYMbb7yRwYMHk5iYyIMPPkhLSwvnnXdem/b19fU88sgjXHPNNTg5OVnyY4j0WJa6Bu+//36amppITk4mLy8PKysrS38UkR7LEtfhypUrmTlzJv3797dIZhVEXczHx4cvvvgCKysrysvLj/mXYNOmTWzevJn777/fvBLwyJEjKS0t5cUXX+Tcc8/FxsbG3L6pqYkHHniAoKAgrr766lPyWUR6IktdgwC2traMHj2ajz76iICAAMaOHWvxzyPSE3X1dZiRkUFmZia33367xTJrDFEXs7Kyatdvjj/88AOOjo5MnDix1fZp06axd+9e0tLSzNtaWlp45JFHsLa25u6779ZvpiLHYYlr8EgtLS0UFRWdbFSRXqurr8OtW7eSm5vLjBkzuOiii/juu+9YvXo1jzzySJdlVg+RQXJycggKCsLWtvX/gqFDh5rfj4mJAeCJJ55g3759PP74423ai0jntPca3LdvHykpKZxxxhnY2dnx/fff88cff3DjjTcaEVukV2nvdXjhhRe2Kpqef/55fHx8uPLKK7ssi/51NUhFRcVRB0a7uLgAUFlZCUBpaSlr167F3t6e6dOnm9s99thjjBgx4tSEFemF2nsNAnz44Yc8+uijWFlZERAQwNKlSwkNDT1lWUV6q/Zeh05OTq3Gzvbr1w8nJ6cunfpCBZGB2tOd6OPjw/fff38K0oj0Pe25Bj09PXnuuedOQRqRvqkzw0DuvffeLs+hMUQGcXNzo6Kios32qqoqAFxdXU91JJE+RdegiPG603WogsggQ4YMIS8vj6amplbbd+3aBRyaCE5ELEfXoIjxutN1qILIIOPGjaOuro6NGze22r5u3Tq8vLyIiooyKJlI36BrUMR43ek61BgiC/jll1+or6+ntrYWODS79IYNGwAYM2YMDg4OjBkzhlGjRrFixQpqa2vx9/fn22+/5ddff2XJkiVt5j8RkfbTNShivJ52HWpxVwuYOXMmpaWlR33vvffew9fXFzg0XfmqVataTVd+1VVXHXfpDhE5MV2DIsbradehCiIRERHp8zSGSERERPo8FUQiIiLS56kgEhERkT5PBZGIiIj0eSqIREREpM9TQSQiIiJ9ngoiERER6fNUEImIiEifp4JIROQk/etf/+Kiiy4yL1EA8NprrzF+/Hj++OMPA5P9zyOPPMLll19OQ0OD0VFEuiWtZSYirZSUlPDXv/71uG1CQ0N57bXXTlGi7q2goIDPP/+c+fPn4+TkZNFzffbZZzz55JNMnz6dO+6447ht586dS2ZmJqtWrSI8PJxrr72WxMREPvjgA6666iqL5hTpiVQQichR+fv7c9555x31PU9Pz1Ocpvt6/fXXsbe3Z8aMGRY/V0JCAs8//zzfffcdt9xyC/369Ttqu507d5KZmUlYWBjh4eEABAQEcPbZZ/Pvf/+bSy+9FEdHR4vnFelJVBCJyFH5+/tz/fXXGx2jWysvL+f7779n4sSJFu8dAnB2dmbChAl8/fXXbNy4kfPPP/+o7dauXQvAtGnTWm0///zz2bhxI99++y0XXnihxfOK9CQaQyQiJ238+PHceuutlJeXs3z5cqZPn05CQgILFiw45hia2tpaXnvtNa655hoSEhKYNm0ad9xxB9u2bWvT9tZbb2X8+PEcPHiQV199lSuuuIJzzjmn1W27jRs3Mm/ePBISEpgxYwaPPfYYVVVVzJw5k5kzZ5rbPfLII4wfP5709PSj5nrxxRcZP34833///Qk/97fffsvBgweZOHHiCdsetnPnTi6++GIuuugi0tLSzNuLi4t59NFHueyyy5g0aRJ/+ctf+Mc//tFmtfALLrgAgK+++uqox29sbCQxMRF7e/s2BdOYMWNwdHTkyy+/bHdekb5CBZGIdInq6mpuuukmdu7cyXnnncf48ePJyMjgjjvuYNeuXa3aVlZW8n//93+88cYbuLq68pe//MXcftGiRfzwww9HPceSJUv48ssvGTFiBJdffjl+fn4AfPHFF9x3330UFRUxefJkpkyZQmpqKrfddhtNTU2tjjF9+nTgf70of9bU1MTXX3+Nh4cHZ5555gk/c1JSEgDR0dEn/oKArVu3csstt2BjY8Nzzz1HVFQUAGlpacydO5d169YRHh7OZZddxogRI/jmm2+48cYbKS4uNh8jLi6OgIAAkpOTKSkpaXOOn376iYqKCsaPH4+Li0ur9+zs7Bg2bBjp6enU1dW1K7NIX6FbZiJyVEVFRcccOB0dHc0ZZ5zRalt2djZ/+ctf+Nvf/oa19aHftUaOHMljjz3Gxx9/3GoQ8FNPPUVOTg6LFy9udVtn//79zJ8/n8cff5zRo0e3GSOzb98+Xn/9dVxdXc3bqqqqeOaZZ3BycuKVV14xF0nz5s3jrrvuIiMjAx8fH3P7mJgYQkJC+Pbbb7n55ptbjaX5+eef2b9/P1deeSW2tif+8bh9+3a8vb0ZMGDACdv+8MMPPPjgg/j5+fHEE08wcOBA4FARtnTpUlpaWli1ahWhoaHmfbZt28aiRYt45plnWL58uXn7tGnTWLlyJevWreO6665rdZ4vvvgC+F9P0pHCw8PZunUr6enpjBw58oS5RfoK9RCJyFEVFRXxxhtvHPW/X3/9tU17R0dHFixYYC6GAKZMmYKNjQ07duwwbysvL2f9+vXEx8e3GePi4eHBFVdcQXl5ubn35c+uu+66VsUQwI8//khdXR0XXnihuRgCsLW15YYbbjjqZ5s+fTq1tbV89913rbavXbsWKyurdo2vaWxspLy8vF3F0Nq1a7n//vsJCwvjueeeMxdDcKgIKy0t5YorrmhVDAHExsZy1lln8csvv1BTU2Pefvh7/eqrrzCZTObte/fuZfPmzfj4+Byz2Dmct6ys7IS5RfoS9RCJyFGNHj2aJ554ot3tAwIC2gwstrW1xcPDg+rqavO2HTt20NzczMGDB4/aA1VYWAhAXl5em9tWkZGRbdrv3LkTgOHDh7d5LzIyEhsbmzbbzz//fF566SXWrl1r7kkpKyvj999/N9+SOpGKigqANreljvT+++/z008/MWbMGB566CEcHBxavZ+amgpAfn7+Ub+P/fv309LSQkFBAREREQB4eXlxxhln8PPPP5OcnEx8fDxwaFxRc3Mz06ZNw8rK6qh5DheUh/OLyCEqiESkSzg7Ox91u42NDS0tLebXlZWVAKSkpJCSknLM49XX17fZ5uHh0Wbb4Z4Td3f3Nu9ZW1vj5ubWZruLiwvnnHMO69atIzc3l+DgYL788kuam5vb/fTV4dt5J5ro8PAg8TPOOKNNMQSHbvkBfPPNN8c9zpHfxwUXXMDPP//MV1991aogsra2ZurUqcc8zuG8x3pkX6SvUkEkIqfU4cLpr3/9KwsXLuzQvkfr9Th8vPLy8jbvtbS0UFFRgbe3d5v3pk+fzrp161i7di0LFy7kq6++wtXVlfHjx7cri4uLC7a2tuYC71juvvtu3nrrLZ555hmsra25+OKLW71/uFdt+fLl7RrIfdjYsWPx8PBg48aN/P3vfyc7O5vCwkJGjx7NoEGDjrnf4bxHKyBF+jKNIRKRUyoiIgIrKyvzraKTNXToUODQAOcjpaen09zcfNT9hg8fzpAhQ/j666/55ZdfKC4u5rzzzutQz0lISAilpaVtnmT7MxcXF/71r38xbNgw/vWvf/Hxxx+3ev/wk2Yd/T5sbW2ZPHkyDQ0NfPvtt+ZH6Y81mPqwgoICAIYMGdKh84n0diqIROSU8vT05JxzzmH79u385z//aTUo+LC0tLSj3jI7mrPPPhtHR0fWrl3b6vH0pqYmXn311ePue9FFF1FRUcHjjz8O0OHJCuPi4jh48KB5HNOxuLi4sGLFCiIiInjqqaf46KOPWuUfNGgQ7733Hlu2bGmzb1NT01HnZoL/FT+ffvopGzZswM3NjbPPPvu4WdLS0vD09GTw4MEn+HQifYtumYnIUR3vsXvgpGaxvu222ygoKODFF1/k66+/Jjo6mv79+7Nnzx4yMjIoLCzkk08+OeqYmyO5uLhw88038/jjjzN37lzOPfdcnJ2d+eWXX7C3t8fLy+uYA4wnT57Myy+/zN69e4mKijL3NrXXuHHj+OCDD0hKSjIvkXG8nE8++SS33347Tz/9NCaTicsuuwx7e3seeugh7rrrLm699Vbi4+MJCQkBYPfu3Wzbtg03NzfeeeedNscMDAwkJibGPBbrwgsvxM7O7pgZioqKKCkp4S9/+UuHPqdIX6CCSESO6vBj98dyMgWRq6srL7zwAh9//DHfffcdiYmJtLS04OHhQWhoKNdee+1RB0Mfy0UXXYSLiwtvv/0269atw9nZmbPOOosFCxZw+eWX4+/vf9T9+vfvz9lnn01iYmKnlrKIi4sjMDCQ//73v1x55ZUnbH+4p+j222/nmWeewWQycfnllxMZGclrr73Gf/7zH3755RdSUlKws7PDy8uLcePGMWnSpGMe84ILLjAXREdOY3Ck//73v8D/JqcUkf+xMh2tv1pEpBcoLCzkyiuv5JxzzuHBBx88aptrrrmG3bt388knn3RqPbLPP/+cJ554gpdeesk8Hqg7ampqYvbs2fj4+PD0008bHUek29EYIhHp8aqqqjh48GCrbQ0NDTz33HPAoVtbR7Np0yZyc3OZPHlypxdnveCCCwgKCuL111/v1P6nyn//+19KS0u56aabjI4i0i3plpmI9Hhbtmzh0Ucf5fTTT2fgwIFUVFSQnJxMaWkpI0eO5Nxzz23V/tNPP2XPnj2sWbOGfv36ccUVV3T63DY2Ntxzzz38+uuv1NbWnpJV7zvDysqKO++884RjnUT6Kt0yE5Eer6CggFdffZXt27eb5yPy9/fn3HPPZdasWW0epZ85cyZlZWUMHjyYBQsWdGj+HxHpnVQQiYiISJ+nMUQiIiLS56kgEhERkT5PBZGIiIj0eSqIREREpM9TQSQiIiJ9ngoiERER6fNUEImIiEifp4JIRERE+rz/D+lLeKBtdJtKAAAAAElFTkSuQmCC\n",
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",
       "text/plain": [
        "
"
       ]
@@ -1710,7 +1710,7 @@
     },
     {
      "data": {
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\n",
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",
       "text/plain": [
        "
"
       ]
@@ -1739,7 +1739,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "cosipy",
    "language": "python",
    "name": "python3"
   },
@@ -1753,7 +1753,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

From d04f3c3933595a161658a1ee2cef122b12f4232b Mon Sep 17 00:00:00 2001
From: avalluvan <62253557+avalluvan@users.noreply.github.com>
Date: Fri, 25 Oct 2024 13:28:06 -0700
Subject: [PATCH 13/46] Created general code for multidimensional interpolation

---
 cosipy/response/__init__.py        |   1 +
 docs/tutorials/response/LMDR.ipynb | 604 ++++++++++++++++++-----------
 2 files changed, 375 insertions(+), 230 deletions(-)

diff --git a/cosipy/response/__init__.py b/cosipy/response/__init__.py
index 12e0002c..d4d22bfc 100644
--- a/cosipy/response/__init__.py
+++ b/cosipy/response/__init__.py
@@ -1,3 +1,4 @@
 from .PointSourceResponse import PointSourceResponse
 from .DetectorResponse import DetectorResponse
+from .ListModeResponse import ListModeResponse
 from .FullDetectorResponse import FullDetectorResponse
diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb
index 25e8f942..030d71c9 100644
--- a/docs/tutorials/response/LMDR.ipynb
+++ b/docs/tutorials/response/LMDR.ipynb
@@ -8,12 +8,12 @@
     {
      "data": {
       "text/html": [
-       "
10:03:50 WARNING   The naima package is not available. Models that depend on it will not be         functions.py:48\n",
+       "
13:26:06 WARNING   The naima package is not available. Models that depend on it will not be         functions.py:48\n",
        "                  available                                                                                        \n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[38;5;46m10:03:50\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The naima package is not available. Models that depend on it will not be        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=212276;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py\u001b\\\u001b[2mfunctions.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=820808;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py#48\u001b\\\u001b[2m48\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m13:26:06\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The naima package is not available. Models that depend on it will not be        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=237033;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py\u001b\\\u001b[2mfunctions.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=394487;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py#48\u001b\\\u001b[2m48\u001b[0m\u001b]8;;\u001b\\\n",
        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mavailable                                                                        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
       ]
      },
@@ -28,7 +28,7 @@
        "
\n"
       ],
       "text/plain": [
-       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The GSL library or the pygsl wrapper cannot be loaded. Models that depend on it \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=911903;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py\u001b\\\u001b[2mfunctions.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=617105;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The GSL library or the pygsl wrapper cannot be loaded. Models that depend on it \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=843802;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py\u001b\\\u001b[2mfunctions.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=501788;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n",
        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mwill not be available.                                                           \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
       ]
      },
@@ -51,7 +51,7 @@
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+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed                                             \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=945094;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=359005;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -223,7 +223,7 @@
        "
\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=594137;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=248709;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=95360;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=149502;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -238,7 +238,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=902352;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=282003;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=329392;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=192020;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -253,7 +253,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=403318;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=5174;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=377458;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=739035;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -269,78 +269,25 @@ "from astropy.coordinates import SkyCoord\n", "from astropy.io import fits\n", "from astropy.time import Time\n", + "import pandas as pd\n", + "from sparse import COO\n", + "\n", + "from lmfit.lineshapes import gaussian\n", "\n", "import matplotlib.pyplot as plt\n", - "import matplotlib.pyplot as ply\n", + "from matplotlib.colors import LogNorm\n", "\n", - "from mhealpy import HealpixMap, HealpixBase\n", - "import pandas as pd\n", "from pathlib import Path\n", "\n", - "from scoords import Attitude, SpacecraftFrame\n", - "from cosipy.response import FullDetectorResponse, ListModeResponse\n", + "from cosipy.response import FullDetectorResponse, DetectorResponse, ListModeResponse\n", "from cosipy.spacecraftfile import SpacecraftFile\n", "from cosipy import test_data\n", - "from cosipy.util import fetch_wasabi_file\n", - "from histpy import Histogram\n", - "import gc\n", "\n", - "from threeML import Model, Powerlaw\n", + "from histpy import Histogram\n", + "from mhealpy import HealpixMap, HealpixBase\n", + "from scoords import Attitude, SpacecraftFrame\n", "\n", - "from cosipy.response import FullDetectorResponse" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "ename": "KeyError", - "evalue": "\"Unable to synchronously open object (object 'hist' doesn't exist)\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)\n", - "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n", - "\u001b[0;32m----> 1\u001b[0m image_response \u001b[38;5;241m=\u001b[39m \u001b[43mHistogram\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", - "\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/histpy/histogram.py:1847\u001b[0m, in \u001b[0;36mHistogram.open\u001b[0;34m(cls, filename, name)\u001b[0m\n", - "\u001b[1;32m 1837\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n", - "\u001b[1;32m 1838\u001b[0m \u001b[38;5;124;03mRead histogram from disk.\u001b[39;00m\n", - "\u001b[1;32m 1839\u001b[0m \n", - "\u001b[0;32m (...)\u001b[0m\n", - "\u001b[1;32m 1842\u001b[0m \u001b[38;5;124;03m name (str): Name of group where the histogram was saved.\u001b[39;00m\n", - "\u001b[1;32m 1843\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n", - "\u001b[1;32m 1845\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m h5\u001b[38;5;241m.\u001b[39mFile(filename, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n", - "\u001b[0;32m-> 1847\u001b[0m hist_group \u001b[38;5;241m=\u001b[39m \u001b[43mf\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\n", - "\u001b[1;32m 1849\u001b[0m unit \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", - "\u001b[1;32m 1850\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124munit\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m hist_group\u001b[38;5;241m.\u001b[39mattrs:\n", - "\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/group.py:357\u001b[0m, in \u001b[0;36mGroup.__getitem__\u001b[0;34m(self, name)\u001b[0m\n", - "\u001b[1;32m 355\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid HDF5 object reference\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[1;32m 356\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(name, (\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m)):\n", - "\u001b[0;32m--> 357\u001b[0m oid \u001b[38;5;241m=\u001b[39m \u001b[43mh5o\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_lapl\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[1;32m 358\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", - "\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAccessing a group is done with bytes or str, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n", - "\u001b[1;32m 360\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnot \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mtype\u001b[39m(name)))\n", - "\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "\n", - "File \u001b[0;32mh5py/h5o.pyx:189\u001b[0m, in \u001b[0;36mh5py.h5o.open\u001b[0;34m()\u001b[0m\n", - "\n", - "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open object (object 'hist' doesn't exist)\"" - ] - } - ], - "source": [ - "image_response = Histogram.open('transformed_response_example.h5')" + "from threeML import Model, Powerlaw" ] }, { @@ -352,7 +299,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -365,14 +312,12 @@ " [0.88, 0.12, 0. , 0. , 0. ]])" ] }, - "execution_count": 4, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from lmfit.lineshapes import gaussian\n", - "\n", "Ei = np.array([507, 509, 511, 513, 515])\n", "\n", "R = np.zeros((5,5))\n", @@ -388,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -422,14 +367,13 @@ " [0. , 0. , 0. , 0.12, 0.88]]])" ] }, - "execution_count": 17, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "h = Histogram([np.arange(4), np.arange(506, 517, 2), np.arange(506, 517, 2)], contents=np.stack([R, R, R]), labels=['NuLambda', 'Ei', 'Em'])\n", - "# h = Histogram([np.arange(506, 517, 2), np.arange(506, 517, 2)], contents=R, labels=['Ei', 'Em'])\n", "\n", "for axis in h.axes:\n", " print(f\"Axis {axis.label} has {axis.nbins} bins\")\n", @@ -439,24 +383,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 18, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 18, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, @@ -477,69 +414,147 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "eps_col = np.linspace(-0.0075, 0.0075, 6)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, "metadata": {}, "outputs": [ { - "ename": "KeyError", - "evalue": "\"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m response:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(response[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:85\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 81\u001b[0m filename \u001b[38;5;241m=\u001b[39m Path(filename)\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filename\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.h5\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 85\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_h5\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(filename\u001b[38;5;241m.\u001b[39msuffixes[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.rsp.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:108\u001b[0m, in \u001b[0;36mFullDetectorResponse._open_h5\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m 104\u001b[0m new\u001b[38;5;241m.\u001b[39m_file \u001b[38;5;241m=\u001b[39m h5\u001b[38;5;241m.\u001b[39mFile(filename, mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 106\u001b[0m new\u001b[38;5;241m.\u001b[39m_drm \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_file[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m new\u001b[38;5;241m.\u001b[39m_unit \u001b[38;5;241m=\u001b[39m u\u001b[38;5;241m.\u001b[39mUnit(\u001b[43mnew\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_drm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUNIT\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 111\u001b[0m new\u001b[38;5;241m.\u001b[39m_sparse \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_drm\u001b[38;5;241m.\u001b[39mattrs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSPARSE\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/attrs.py:56\u001b[0m, in \u001b[0;36mAttributeManager.__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[38;5;129m@with_phil\u001b[39m\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name):\n\u001b[1;32m 54\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Read the value of an attribute.\u001b[39;00m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 56\u001b[0m attr \u001b[38;5;241m=\u001b[39m \u001b[43mh5a\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_id\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 57\u001b[0m shape \u001b[38;5;241m=\u001b[39m attr\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 59\u001b[0m \u001b[38;5;66;03m# shape is None for empty dataspaces\u001b[39;00m\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/h5a.pyx:80\u001b[0m, in \u001b[0;36mh5py.h5a.open\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"" + "name": "stdout", + "output_type": "stream", + "text": [ + "[503.958 505.946 507.934 509.922 511.91 ]\n", + "[505.479 507.473 509.467 511.461 513.455]\n", + "[507. 509. 511. 513. 515.]\n", + "[508.521 510.527 512.533 514.539 516.545]\n", + "[510.042 512.054 514.066 516.078 518.09 ]\n" ] + }, + { + "data": { + "text/plain": [ + "array([[0.01 , 0.185, 0.61 , 0.185, 0.01 ],\n", + " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", + " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", + " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", + " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ]])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "with FullDetectorResponse.open('transformed_response_example.h5') as response:\n", - " print(response['DRM'])" + "for i in range(5):\n", + " Em = (eps_col[i]+eps_col[i+1])/2 * Ei + Ei\n", + " print(Em)\n", + " R[i, :] = gaussian(x=Em, center=Ei)\n", + "\n", + "R /= np.sum(R, axis=0)\n", + "R = np.round(R, 2)\n", + "R[2, :4] = 0.6\n", + "R[2, 4] = 0.61\n", + "R[1:4:2, 4] = 0.185\n", + "\n", + "R = R.transpose(1,0)\n", + "\n", + "R[::-1]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ - "f = h5py.File('response_example.h5', mode='w', track_order=True)\n", - "grp = f.create_group('DRM')\n", - "\n", - "dset_contents = grp.create_dataset('CONTENTS', shape=(3,5,5), dtype=float)" + "htransformed = Histogram([np.arange(4), np.arange(506, 517, 2)*u.keV, eps_col], contents=np.stack([R, R, R]), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$[[[0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.185,~0.61,~0.185,~0.01]],~\n", + "\n", + " [[0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.185,~0.61,~0.185,~0.01]],~\n", + "\n", + " [[0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", + " [0.01,~0.185,~0.61,~0.185,~0.01]]] \\; \\mathrm{cm^{2}}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "grp_axes = grp.create_group('AXES', track_order=True)\n", - "\n", - "# 1 more than shape of contents dataset\n", - "dset_axis_NL = grp_axes.create_dataset('NuLambda', shape=4, dtype=float)\n", - "dset_axis_Ei = grp_axes.create_dataset('Ei', shape=6, dtype=float)\n", - "dset_axis_Em = grp_axes.create_dataset('Em', shape=6, dtype=float)" + "htransformed.write('transformed_response_example.h5', overwrite=True)\n", + "htransformed.contents" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "('/DRM/CONTENTS', '/DRM/CONTENTS')" + "(,\n", + " )" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -547,86 +562,126 @@ } ], "source": [ - "dset_contents.name, hf['DRM/CONTENTS'].name" + "htransformed.project('Ei', 'eps').draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load example response" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "f['DRM/AXES/NuLambda'][:] = np.arange(4)\n", - "f['DRM/AXES/Ei'][:] = np.arange(506, 517, 2)\n", - "f['DRM/AXES/Em'][:] = np.arange(506, 517, 2)\n", - "\n", - "for i in range(3):\n", - " f['DRM/CONTENTS'][i, :, :] = R" + "image_response = Histogram.open('transformed_response_example.h5')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "dr = ListModeResponse(image_response.axes[1:],\n", + " contents = image_response.slice[1].contents.reshape(5,5),\n", + " sparse = False,\n", + " unit = image_response.unit)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Bilinear interpolated value: 0.6 cm2\n", + "0.0\n", + "0.0\n", + "1.0\n", + "0.0\n", + "Multidimensional interpolated value: 0.6 cm2\n" + ] + }, { "data": { + "text/latex": [ + "$0.6 \\; \\mathrm{cm^{2}}$" + ], "text/plain": [ - "['NuLambda', 'Ei', 'Em']" + "" ] }, + "execution_count": 9, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "list(f['DRM/AXES'].keys())" + "Ei0 = 511*u.keV\n", + "Em0 = 511*u.keV\n", + "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.19 cm2\n", + "0.6 cm2\n", + "0.19 cm2\n", + "0.6 cm2\n", + "0.19 cm2 0.6 cm2 0.19 cm2 0.6 cm2\n", + "0.6542842215256062\n", + "0.28040752351098924\n", + "0.04571577847438243\n", + "0.0195924764890221\n", + "Multidimensional interpolated value: 0.5732236154650042 cm2\n", + "0.0195924764890221 0.04571577847438243 0.28040752351098924 0.6542842215256062\n" + ] + }, { "data": { + "text/latex": [ + "$0.57322362 \\; \\mathrm{cm^{2}}$" + ], "text/plain": [ - "array([[[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]],\n", - "\n", - " [[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]],\n", - "\n", - " [[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]]])" + "" ] }, + "execution_count": 11, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "f['DRM/CONTENTS'][:]" + "Ei0 = 510.4*u.keV\n", + "Em0 = 510.3*u.keV\n", + "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { + "image/png": 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RZFWCDFUWBmhVwr1z0BYsWAA/Pz8x3VggptFo4OLiYpCuUCjE56aMGjVK7+ewsDCEhITgww8/xPbt2zFu3Diz2m9LXINGRERE9crPzw9BQUHi58HpTeDeerOKigqDdK1WKz6Xon///mjWrBlOnDhhXqNtjCNoREREJJkAGXQWrkETJJRXqVTIy8szSFer1QBgNKh7mBYtWqCwsFByubrAETQiIiKSrEqQW+VTWwEBAbh27RpKSkr00tPT08XnUgiCgJs3b9rtsRsM0IiIiMjuhYWFoaqqCklJSWKaVqvF7t270b59e3EHZ25ursGu0IKCAoP6duzYgYKCAnTr1s2m7TYXpzgbkOKhHSAoPeu7GURENifjHdp2T4AMOqHupjjbt2+P8PBwrFmzBgUFBWjdujX27t2LmzdvYu7cuWK+xYsX4/Tp0zh8+LCYNmrUKPTp0wf+/v5QKBQ4e/YskpOTERgYqHeumj1hgEZERESS3TsHzcJdnBLXsM2fPx8+Pj7Yt28fiouL4e/vjyVLlqBjx441luvfvz/OnTuHlJQUaLVa+Pj4YOzYsXj99dfh6upqwRvYDgM0IiIiahCUSiWmTJmCKVOmmMyzYsUKg7Q5c+bYslk2wQCNiIiIJLt3F6eFU5wWlndkDNCIiIhIMh3k0Fk4xWlpeUfGniEiIiKyMxxBIyIiIsl0wr3rniytg4xzqABNq9Vi3bp12L9/P4qKitCuXTtMmDABXbp0eWjZvLw8rFy5EsePH4dOp0OnTp0wffp0tGrVyiDvzp07sWXLFty8eRPNmzfHyJEjMWLEiBrrnzVrFn777TdERUVh5syZZr8jERGRPdBZYQ2apeUdmUNNccbGxiIhIQH9+/fHW2+9Bblcjjlz5iA1NbXGcqWlpZgxYwZOnz6NcePGYfz48cjMzMT06dNx9+5dvbyJiYn4+OOP8cQTT2DGjBl4+umnERcXh2+//dZk/SkpKUhLS7PKOxIREdkDnSC3yoeMc5gRtPT0dCQnJ2Py5MkYO3YsAGDgwIGIjo5GfHw84uPjTZbdsWMHrl27htWrVyMkJAQA0K1bN0RHR2Pr1q2YOHEiAECj0eDLL79E9+7d8eGHHwIAIiIioNPpsHHjRkRGRqJJkyZ6dWs0Gnz++ed45ZVXsG7dOlu8OhERETkYhwldU1JS4OTkpHcisFKpxJAhQ5CWlobc3FyTZQ8dOoTg4GAxOAMAPz8/dO7cGQcPHhTTTp48ibt372L48OF65aOiolBWVoajR48a1L1582YIgoAxY8ZY8HZERET2RQfZ/w6rNf9j6WXrjsxhArTMzEz4+vrC3d1dL7066MrKyjJaTqfT4dKlSwgODjZ4FhISgpycHJSWlorfAcAgb1BQEORyOS5evKiXnpubi2+//RZ/+ctfoFQqa/0u+fn5yMjIED8P3ilGRERU33TC/1+HZv6nvt/CfjnMFKdarYZKpTJIr07Lz883Wq6wsBBarfahZR9//HGo1Wo4OTnBy8tLL5+Liws8PDygVqv10j///HMEBgaib9++kt4lKSkJGzZskFSGiIiIHIfDBGgajQYuLi4G6QqFQnxuqhyAWpXVaDRwdjbeZQqFQu87Tp48iZSUFKxatUrCW9wTGRmJHj16iD9nZ2dj0aJFkushIiKyFQGWL/IXHGciz+ocJkBTKpWoqKgwSNdqteJzU+UA1KqsUqlEZWWl0Xq0Wq2Yr7KyEnFxcRgwYIDeurba8vb2hre3t+RyREREdUVnhTVkXINmmsOEriqVymCKEYCYZirg8fDwgEKhqFVZlUqFqqoq3LlzRy9fRUUFCgsLxSnRffv24erVq4iMjMSNGzfED3DvSI8bN26gvLzczDclIiIiR+cwI2gBAQE4deoUSkpK9DYKpKeni8+Nkcvl8Pf3x4ULFwyepaeno1WrVnBzcwMABAYGAgAuXLiA7t27i/kuXLgAnU4nPs/NzUVlZSWmTp1qUOe+ffuwb98+LF68GL169TLzbYmIiOqXTpBZ4SYBjqCZ4jABWlhYGLZs2YKkpCTxHDStVovdu3ejffv28PHxAXAveCovL4efn59YNjQ0FKtXr8aFCxfEHZpXrlzBqVOnMHr0aDFf586d4eHhgcTERL0ALTExEa6urmJa3759xWDtfn/729/wwgsvICIiwqypTyIiIntxbxemhZelM0AzyWECtPbt2yM8PBxr1qxBQUEBWrdujb179+LmzZuYO3eumG/x4sU4ffo0Dh8+LKZFRUVh586dmDt3LsaMGQMnJyckJCTAy8tL7/wypVKJN998E8uWLcP777+Prl274syZM9i/fz9iYmLg4eEB4N4ZavcHgPdr2bIlR86IiIioRg4ToAHA/Pnz4ePjg3379qG4uBj+/v5YsmQJOnbsWGM5Nzc3xMXFYeXKldi4caN4F+e0adPg6emplzcqKgrOzs7YunUrfv75Z7Ro0QLTpk3DqFGjbPdiREREdoZ3cdqWTBAEHhNn5zIyMhATEwNN6zAISs/6bg4Rkc3JdPXdgobr2MZZNq2/+neSzww/KHxdLapLe60cuXHZWLt2LYKCgqzUQsfgUCNoREREVDc4gmZbDnPMBhEREZGj4AgaERERSSbA8l2cAg+qNYkBGhEREUnGKU7b4hQnERERkZ3hCBoRERFJxrs4bYsBGhEREUkmWGGKU+AUp0mc4iQiIiKyMxxBIyIiIsl0guWL/HU8Kt8kBmhEREQkGac4bYtTnERERER2hiNoREREJJkOMsgsneLkLk6TGKARERGRZDrIIOMxGzbDAI2IiIgk4xo02+IaNCIiIiI7wxE0IiIikkwnyADexWkzDNCIiIhIMsEK56AJPAfNJE5xEhEREdkZjqARERGRZDrB8mM2uEnANAZoREREJJkAy9egCTxmwyROcRIRERHZGY6gERERkWQCZFYYAeMImikM0IiIiEgyaxyzAUHGqTwT2C9EREREdoYjaERERCSZIMAKI2hWaYpDYoBGREREkllritPJOs1xOAzQiIiISDpBZvE5Zpaeo+bIuAaNiIiIyM5wBI2IiIgk08EKI2g8ZsMkjqARERGRZIJgnY8UWq0W8fHxiIqKQr9+/TBp0iQcP35ccttnzZqF3r17Y9myZZLL1hUGaERERNQgxMbGIiEhAf3798dbb70FuVyOOXPmIDU1tdZ1pKSkIC0tzYattA4GaERERCSZABl0Fn6k3ESQnp6O5ORkTJw4EVOmTEFkZCSWL1+Oxx57DPHx8bWqQ6PR4PPPP8crr7xi7mvXGQZoREREJNm9KUqZhZ/af19KSgqcnJwQGRkppimVSgwZMgRpaWnIzc19aB2bN2+GIAgYM2aMOa9cp7hJgIiIiOpVdna23s8qlQre3t56aZmZmfD19YW7u7teekhICAAgKysLPj4+Jr8jNzcX3377Ld59910olUortdx2GKARERGRZDpBdu+wWkv8r/yiRYv0kqOjozF+/Hi9NLVaDZVKZVBFdVp+fn6NX/X5558jMDAQffv2taTFdcahAjStVot169Zh//79KCoqQrt27TBhwgR06dLloWXz8vKwcuVKHD9+HDqdDp06dcL06dPRqlUrg7w7d+7Eli1bcPPmTTRv3hwjR47EiBEj9PKkpKTgxx9/xIULF3D79m20aNEC3bt3x5///Gc0adLEau9MRERUH8zZhWmsDgBYsGAB/Pz8xHRjgZhGo4GLi4tBukKhEJ+bcvLkSaSkpGDVqlWWNbgOOVSAFhsbi0OHDmHUqFHw9fXFnj17MGfOHMTFxaFDhw4my5WWlmLGjBkoKSnBuHHj4OzsjISEBEyfPh3r169H06ZNxbyJiYn417/+hdDQUIwePRqpqamIi4tDeXk5Xn31VTHf0qVLoVKpMGDAAPj4+OD333/H9u3b8d///hfr1q1rEMOrREREdcHPzw9BQUE15lEqlaioqDBI12q14nNjKisrERcXhwEDBojToQ2BwwRo1bs7Jk+ejLFjxwIABg4ciOjoaMTHx9e4w2PHjh24du0aVq9eLf6f161bN0RHR2Pr1q2YOHEigHvR+Zdffonu3bvjww8/BABERERAp9Nh48aNiIyMFEfHFi5ciE6dOul9T1BQED766CMcOHAAQ4cOtXofEBER1R3LD6qFhF2cKpUKeXl5BulqtRoADNasVdu3bx+uXr2K2bNn48aNG3rPSktLcePGDXh5ecHV1VVCu23PYXZxWrK749ChQwgODtaLrP38/NC5c2ccPHhQTDt58iTu3r2L4cOH65WPiopCWVkZjh49KqY9GJwBQO/evQEAly9flvp6REREdsXyHZzSAryAgABcu3YNJSUleunp6enic2Nyc3NRWVmJqVOnYvTo0eIHuBe8jR492qzDbm3NYUbQzN3dodPpcOnSJbz00ksGz0JCQnD8+HGUlpbCzc0NmZmZAIDg4GC9fEFBQZDL5bh48SIGDBhgso3VUb6np6ekdyMiIrI31tgkIOWy9LCwMGzZsgVJSUniTJlWq8Xu3bvRvn178Xd8bm4uysvLxTVtffv2RWBgoEF9f/vb3/DCCy8gIiLCLqc+HSZAM3d3R2FhIbRa7UPLPv7441Cr1XBycoKXl5dePhcXF3h4eIgBmCn//ve/4eTkhNDQ0Brz5efn69X14PZjIiKiR0379u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHwZwb0bs/g0I92vZsiV69epVJ+2XymECNHN3d1Sn16asRqOBs7PxLlMoFDXuIDlw4AB27dqFsWPHok2bNjW8CZCUlIQNGzbUmIeIiKg+WXMXZ23Nnz8fPj4+2LdvH4qLi+Hv748lS5agY8eOljXEDjlMgGbu7o7q9NqUVSqVqKysNFqPVqs1+R1nzpzBkiVL0LVrV8TExDzkTYDIyEj06NFD/Dk7O9vgjBgiIqJ69b+bBCytQwqlUokpU6ZgypQpJvOsWLGiVnVVj7DZK4cJ0Mzd3eHh4QGFQmF0evLBsiqVClVVVbhz547eNGdFRQUKCwuNTpNmZWVh3rx58Pf3x8KFC02OwN3P29vbZHuJiIjI8TnMLk5zd3fI5XL4+/vjwoULBs/S09PRqlUruLm5AYC4yPDBvBcuXIBOpzNYhJiTk4PZs2fDy8sLH3/8sVgPERFRQyfACrs4JRyz8ahxmAAtLCwMVVVVSEpKEtNM7e54cNF9aGgoLly4oBd4XblyBadOnUJYWJiY1rlzZ3h4eCAxMVGvfGJiIlxdXdG9e3cxTa1W4+2334ZcLsfSpUu5c5OIiByKYKUPGecwU5zm7u4A7p1jtnPnTsydOxdjxoyBk5MTEhIS4OXlpXfjvVKpxJtvvolly5bh/fffR9euXXHmzBns378fMTEx8PDwEPO+8847uH79OsaOHYuzZ8/i7Nmz4jMvL69aXT9FREREjyaHCdAA83d3uLm5IS4uDitXrsTGjRvFuzinTZtmMPIVFRUFZ2dnbN26FT///DNatGiBadOmYdSoUXr5srKyAACbN282+L6OHTsyQCMiogZN6kGzpuog42SCYOkmWbK1jIwMxMTEQNM6DILSs76bQ0RkczJdfbeg4Tq2cZZN66/+nZQ/phsqW3g8vEANnG8VwnvLMaxdu/ahd3E+ahxqBI2IiIjqBkfQbMthNgkQEREROQqOoBEREZF0VrhJgNs4TWOARkRERJJVn4NmaR1kHAO0BmTNtM0I8NfWdzOIiGyukcz41XlUG7bdJEB1gwEaERERSScAqOO7OB8lDNCIiIhIMsEKa9B40Jdp3MVJREREZGc4gkZERETSWeMyTY6gmcQAjYiIiCTjQbW2xSlOIiIiIjvDETQiIiIyD6cobYYBGhEREUnGKU7bYoBGRERE0nGTgE1xDRoRERGRneEIGhEREZlB9r+PpXWQMQzQiIiISDpOcdoUAzQiIiKih9i7d6/FdQQGBqJdu3a1yssAjYiIiKR7xEbQYmNjIZOZNyUrCAJkMhmio6MZoBEREZENCbJ7H0vraEB69OiBnj17mlX2n//8p6T8DNCIiIiIaiEwMBCDBw82qywDNCIiIqoTQgOaorRUnz598MQTT9RZeQZoREREJN0jtgbtgw8+qNPyPKiWiIiIyM5wBI2IiIikE2CFTQJWaYlD4ggaERERSScAMgs/DTVAU6vVSElJwZEjR1BUVGQy3+nTp7FhwwazvoMjaERERCTdI7YGrdqWLVvw5ZdforKyEgCgUCjw2muvYdy4cQbnpJ06dQpff/01oqOjJX8PR9CIiIiIauHXX39FfHw8FAoFhg4diuHDh8PNzQ3r1q3Du+++C61Wa7XvsmgETafTQS7Xj/HOnTuHo0ePQqFQYPDgwWjRooVFDSQiIiJ7ZIWDahvYZenfffcdXF1dsXr1arRp0wYAMHHiRCxduhTJycl49913ERsbC6VSafF3mT2C9tlnn2HAgAF6c6+HDh3C9OnT8c0332D9+vWYMGECbt26ZXEjiYiIyM4IVvo0IBcuXEDv3r3F4AwA3Nzc8P777+OVV17BiRMn8O6770Kj0Vj8XWYHaKdOnUKnTp3QpEkTMW3dunVwd3fH3/72N/zlL39BUVERtmzZYnEjiYiIiOpbWVmZyZnBSZMm4bXXXsPJkycxd+5ci4M0s6c4b926hWeffVb8+fr167hy5Qqio6MxYMAAAEBqaip+/fVXixpIREREdugR3CTg7e2NvLw8k88nTJgAANi0aRPmzJmDoKAgs7/L7ACtvLwcjRo1En8+c+YMZDIZunXrJqa1bdsWJ0+eNLtxREREZKcewQDtiSeewIkTJ2rMc3+Qdu7cObO/y+wpTpVKhStXrog/Hzt2DI0aNdKLFktKSuDi4mJ244iIiIjsRffu3ZGfn4+jR4/WmG/ChAl4/fXXxaM4zGH2CFrHjh2RnJyMbdu2QalU4vDhw+jVqxecnJzEPNevX0fz5s3NbhwRERHZKcEKuzgt3gVat8LCwiAIAlxdXR+a980330SrVq1w8+ZNs77L7ADttddew08//YTPPvtMbOwbb7whPi8tLcWZM2cwePBgc7+CiIiI7JQM/7sNwMI6GhIPDw8MGzas1vktiYHMDtB8fX2xceNGpKSkAAB69OiBxx57THx+9epVREZGol+/fmY3TiqtVot169Zh//79KCoqQrt27TBhwgR06dLloWXz8vKwcuVKHD9+HDqdDp06dcL06dPRqlUrg7w7d+7Eli1bcPPmTTRv3hwjR47EiBEjLKqTHkFVAuTHNJDlVkHwcYKumxJwamj/uaon7DsicnAWHVTr7e1tNDABgKCgIIt2L5gjNjYWhw4dwqhRo+Dr64s9e/Zgzpw5iIuLQ4cOHUyWKy0txYwZM1BSUoJx48bB2dkZCQkJmD59OtavX4+mTZuKeRMTE/Gvf/0LoaGhGD16NFJTUxEXF4fy8nK8+uqrZtVJjx6n3aVQvHcH8htVYpqupRO0H3qh6iW3emyZ/WPfEdmJR3CTgDGZmZnIysqCWq02uuZMJpPhz3/+s+R6rXIX5927d5GVlYWSkhK4u7sjICCgzgOQ9PR0JCcnY/LkyRg7diwAYODAgYiOjkZ8fDzi4+NNlt2xYweuXbuG1atXIyQkBADQrVs3REdHY+vWrZg4cSIAQKPR4Msvv0T37t3x4YcfAgAiIiKg0+mwceNGREZGiufC1bZOevQ47S6FMibf4D9MsptVUMbkQ7PWm4GGCew7IrIXd+7cwcKFC3Hq1CkAgCAYjzbrJUC7ceMGVqxYgf/+9796DZPJZOjevTumT5+Oli1bWvIVtZaSkgInJydERkaKaUqlEkOGDMGaNWuQm5sLHx8fo2UPHTqE4OBgMZACAD8/P3Tu3BkHDx4Ug6mTJ0/i7t27GD58uF75qKgoHDhwAEePHhXPgKttnfSIqRKgeO8OIBiuvZAJ99bLKt6/g7KBjThl9yD2HZFdkQlWWIPWgEfQli1bhpMnT+KFF15A3759oVKp9DZKWsrsAC0nJwdTp07FnTt34Ovri2eeeQZeXl64c+cOzp07h59//hnp6en44osv6mTNVWZmJnx9feHu7q6XXh0gZWVlGQ3QdDodLl26hJdeesngWUhICI4fP47S0lK4ubkhMzMTABAcHKyXLygoCHK5HBcvXsSAAQMk1WlMfn4+1Gq1+HN2dvZD3p4aCvkxjd7U3INkAiC7XgX5MQ10Lz58l9CjhH1HRPbk119/RadOnbBkyRKb1G92gLZq1SoUFBTg7bffRkREBGSy//83VkEQkJSUhGXLlmHVqlVYuHChVRpbE7VaDZVKZZBenZafn2+0XGFhIbRa7UPLPv7441Cr1XBycoKXl5dePhcXF3h4eIhBlZQ6jUlKSsKGDRtMvCk1ZLJc0wGGOfnsmSAAt35/Ei3aXYTMCgNaj1LfETUIj+AxG/dzdna26Vp7swO0EydOoEePHnpTitVkMhmGDRuG//73v/jtt98samBtaTQao4fiKhQK8bmpcgBqVVaj0cDZ2XiXKRQKvXy1rdOYyMhI9OjRQ/w5OzsbixYtMpmfGg7Bp3bD37XNZ89uXHgKKV9OR2jMCrQKTre4vkep74gahHrYJGDuaQ2HDx9GYmIiLl26hMLCQnh6eqJ9+/Z444034O/vb1bTO3ToIM6s2YLZNwnodDq0bdu2xjz+/v7Q6XTmfoUkSqUSFRUVBularVZ8bqocgFqVVSqVJk8F1mq1evlqW6cx3t7e4i7YoKAg+Pn5mcxLDYuumxK6lk4m/9IoyABdq/8dG9HAXU3tfO9/z3S2Sn2PUt8RkXGxsbFISEhA//798dZbb0Eul2POnDlITU2tsdylS5fQpEkTjBw5EjNnzsSwYcOQmZmJSZMmISsry6y2TJw4ERkZGdi2bZtZ5R/G7BG0J598EpcvX64xzx9//FFnR22oVCqjF5hWTzt6e3sbLefh4QGFQqG35stUWZVKhaqqKty5c0dvmrOiogKFhYXi9KWUOukR4ySD9kMvKGPyIcj0F8hWBx7ahV4NcpG7oJMh85feqCi/t7byyv8Cs6upndFYde/PvYtrKQJfPAyZ3Iy/djtw3xE1WHW4yN+S0xqio6MN0oYOHYoRI0Zgx44dmD17tuT2tG3bFitXrsS0adOwbds2tGvXzmAdfLV3331Xcv1mB2gxMTGYOXMmdu7ciaFDhxo8T0pKwq+//oply5aZ+xWSBAQE4NSpU+JRH9XS09PF58bI5XL4+/vjwoULBs/S09PRqlUrcTF/YGAgAODChQvo3r27mO/ChQvQ6XTicyl10qOn6iU3aNZ6Q/HeHcjuW/QutHSCdmHDPcurUqvA2X2R0Ja6AxAgk+v+l65E6p5IADIo3ErwxPP/hYur6Sn+mjhq3xE1RHW9i9OS0xqM8fLygqurK4qLi6U0WXT9+nXMnz8fxcXFKC4uRk5OjtF8MpmsbgO0EydOoFOnTli6dCm2bNmCZ555Bs2aNcPt27dx9uxZXLt2DV26dMGJEyf0bn439zyQhwkLC8OWLVuQlJQkRtZarRa7d+9G+/btxf/TcnNzUV5erjdtGBoaitWrV+PChQviDs0rV67g1KlTGD16tJivc+fO8PDwQGJiol6AlpiYCFdXV7202tZJj6aql9xQNrCRQ52G7+KqwaBZi/DLN28i/3I7CLp7a8Hu/a8A77ZZeHHcOrODs2qO2HdEj7oHTytQqVQGM03mntZwv6KiIlRVVUGtVuO7775DSUkJnnvuObPaHBcXh+vXr2PYsGHo16+f/Ryz8dVXX4n/fPXqVVy9etUgz6+//opff/1VL81WAVr79u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHxbToqKisHPnTsydOxdjxoyBk5MTEhIS4OXlhTFjxoj5lEol3nzzTSxbtgzvv/8+unbtijNnzmD//v2IiYmBh4eH5DrpEeYkc7jjINy97qDP5GXY9t6nqNL+/7VgTgot+k75FHInK61JdcC+I2pwrLhJ4MGNcNHR0Rg/frxemrmnNdxv8uTJuHLlCgCgUaNGeP311zFkyBBzWo4zZ87gxRdfxKxZs8wq/zBmB2hxcXHWbIdVzJ8/Hz4+Pti3bx+Ki4vh7++PJUuWoGPHjjWWc3NzQ1xcHFauXImNGzeK92ZOmzYNnp6eenmjoqLg7OyMrVu34ueff0aLFi0wbdo0jBo1yuw6iRzJ7Stt9YIzAKjSKqG+8gSaP/F7PbWKiKzOigHaggUL9Ga2jAVi5p7WcL93330XpaWluH79Onbv3g2NRgOdTge5XPqeSRcXF7Rp00ZyudoyO0B7WNBTH5RKJaZMmYIpU6aYzLNixQqj6S1atKj1eW0RERGIiIh4aD4pdRI5ipz0e/fe+j59Ch0jtuHUf0Yi51xH5KR1YIBGREb5+fk9dFOhuac13O/pp58W/7lv37547bXXAABTp06V0lwAQJcuXXDu3DnJ5WrL7GM2AKCyshIJCQmYOHEiBg0ahPDwcPFZZmYmPv30U6NTn0TkuFo/lYrur65Dz+jVaOKdj17Rq9D91XVo/VTN2+CJqGGp3iRg6ae2VCqVVU9HaNKkCTp37owDBw5IKldtypQpUKvV+OKLL2o1eieV2SNoGo0Gb7/9Ns6dO4emTZvC3d0d5eXl4vOWLVti9+7daNKkCWJiYqzSWCKyf82f+F1vpEwmA9p2Pl6PLSIi27DCTQIGN+uaZu5pDTXRaDQoKSmRXA4APvzwQzRu3BgJCQn4z3/+A19fX6MnNMhkMixfvlxy/WaPoG3atAlnz57FxIkTsWPHDoNFdo0bN0bHjh1x/Dj/w0xERORwBCt9aiksLAxVVVVISkoS00yd1vDgrtA7d+4Y1Hfjxg2cOHHC7PNaT58+jaysLAiCgNLSUly8eBGnT582+jGH2SNoP/74Izp16oRXXnkFAPTu4qzWqlUrm16DQERERI8GS05riI6OxnPPPYeAgAA0adIE165dw65du1BZWYlJkyaZ1Z6UlBSL36kmZgdot27dQq9evWrM06hRI7OHDomIiMiOWeGgWqm7QM09raH6fvBjx46htLQUXl5e6NKlC8aNG4d27dqZ334bMjtAa9SoEQoKCmrMc/36dTRt2tTcryAiIiJ7VQ+XpZt7WsP48eMNzlWzVFVVFcrLy9GoUSOjx3RUP3d1dTXrAFuz16A99dRT+OWXX1BUVGT0eW5uLv773//i2WefNfcriIiIiOzShg0bMGzYMBQWFhp9XlRUhGHDhmHTpk1m1W92gDZmzBgUFRVh5syZOHv2LKqq7t2LV15ejhMnTmD27NmoqqritUZEREQOqK6P2bA3v/zyCzp37mzy8HlPT088//zzOHLkiFn1W3RQ7V//+lesWLEC06dPF9MHDRoE4N6F4bNmzTJ7dwQRERHZuQYcYFnqxo0b6NSpU4152rRpg7Nnz5pVv9kBGgAMHz4cHTt2RGJiIs6fP4/CwkK4u7sjJCQEUVFReOKJJyypnoiIiMguVVZWPvSKKJlMJt50IJVFARoAtG3bFjNmzLC0GiIiImpI6mGTgD1p3bo1Tp48WWOekydPomXLlmbVb9FVT0RERPRoetTXoPXu3RtZWVlYt26duA6/WlVVFb788ktkZWUhLCzMrPotHkEjIiIietSMHj0aycnJ2LRpE5KTk9GpUyc0b94ceXl5OHXqFK5fvw4/Pz+MGTPGrPoZoBERERFJ5ObmhpUrV+Jf//oXfvrpJ+Tk5IjP5HI5QkNDMWvWLKP3c9YGAzQiIiKS7hFfgwbcO0rjww8/xO3bt5GRkYHi4mI0btwYwcHB8PLysqhuBmhEREQkmTXWkDXkNWj3a9asGbp3727VOrlJgIiIiOghFi5caNEF6VLLM0AjIiIi8wgWfhqQ5ORk/PHHH3VWnlOcREREJN0juAYtMzMTe/furZPvYoBGREREVAtHjhzBzz//LLmcIEiPRBmgERERkWSP2iaBd9991+I6AgMDa52XARoRERFJ94hNcQ4ePLhOv4+bBIiIiIjsDEfQiIiISDpr3KXZgEbQ6hoDNCIiIjIPAyyb4RQnERERkZ3hCBoRERFJ94htEqhrDNCIiIhIskftmI26xgCtAZm4ciwEpWd9N4OIyOZkuvpuQcN1bGMdfRFH0GyKa9CIiIiI7AxH0IiIiEg6jqDZFAM0IiIikkwGK6xBs0pLHBOnOImIiIjsDEfQiIiISDpOcdoUAzQiIiKSjMds2JbDBGhFRUVYtWoVDh8+DI1Gg5CQEEyZMgVBQUG1Kn/58mWsXLkSZ8+ehbOzM7p3745p06bB09NTL59Op8OWLVuwY8cO3L59G76+vhg3bhz69eunl2ffvn1ISUlBZmYmioqK0LJlS/Tp0wdjxoyBUqm05qsTERGRg3GIAE2n02Hu3Ln4/fffMWbMGDRt2hQ7duzAjBkzsHbtWrRp06bG8rdu3cL06dPRuHFjxMTEoKysDFu2bMGlS5ewevVquLi4iHnXrl2Lb7/9FhEREQgODsaRI0ewcOFCyGQy9O3bFwBQXl6O2NhYPPXUUxg2bBi8vLyQlpaGr776CidPnsTy5cshk3FpJBERNWCc4rQphwjQDh06hHPnzmHhwoUICwsDAPTp0wevvPIKvvrqK7z//vs1lv/mm29QXl6OL7/8Ej4+PgCAkJAQzJo1C3v27EFkZCQAIC8vD1u3bkVUVBRmzpwJABg6dCimT5+OL774AmFhYXBycoKLiws+//xzPPPMM+J3RERE4LHHHsP69etx4sQJPP/88zboCSIiojrCAM2mHGIXZ0pKCpo1a4bevXuLaZ6enggPD8eRI0eg1WofWv7FF18UgzMAeP7559GmTRscPHhQTDty5AgqKysRFRUlpslkMgwfPhx5eXlIS0sDALi4uOgFZ9V69eoFAMjOzjbvRYmIiOiR4BAB2sWLFxEYGAi5XP91QkJCUF5ejqtXr5osm5eXhzt37hhdqxYSEoLMzEzx58zMTDRq1Ah+fn4G+aqf1+T27dsAgKZNm9aYLz8/HxkZGeKHAR0REdkbmZU+ZJxDTHHevn0bzz77rEG6SqUCAKjVarRr185oWbVarZf3wfKFhYXQarVQKBRQq9Xw8vIyWD9WXTY/P7/Gdm7evBnu7u7o1q1bjfmSkpKwYcOGGvMQERHVO05R2ozdBWg6nQ4VFRW1yqtQKCCTyaDRaKBQKIw+BwCNRmOyjupn928EMFZeoVBAo9E8NJ8pmzZtwm+//YZZs2ahSZMmNbwVEBkZiR49eog/Z2dnY9GiRTWWISIiqlNWOGaDAZ5pdhegnTlzBjNmzKhV3k2bNsHPzw9KpdLoOrPqtJqOtah+ZiwofLC8UqmsVb4HJScn48svv8SQIUMwfPjwGt7oHm9vb3h7ez80HxERETkmuwvQHn/8ccybN69WeaunFps1ayZOVd6vpunLB+swVd7Dw0McIVOpVDh16hQEQdCb5qwuayyoOn78OD766CN0794db7/9dq3ei4iIyO5xF6dN2V2AplKpMHjwYEllAgMDkZqaCp1Op7dR4Pz583B1da3xHLTmzZvD09MTGRkZBs/Onz+PgIAA8eeAgADs3LkT2dnZaNu2rZienp4uPr9feno6FixYgKCgIPzjH/+As7PddTcREZF5GKDZlEPs4gwNDcXt27dx+PBhMa2goAAHDx7Eiy++qLc+LScnBzk5OQblf/nlF+Tm5oppJ06cwNWrVxEeHi6m9ezZE87Ozti+fbuYJggCEhMT0bx5czz99NNi+uXLlzF37lw89thjWLJkCW8PICIiolpziCGdsLAwfP/994iNjcXly5fFmwR0Oh3Gjx+vl7f6gNmEhAQxbdy4cTh06BD++te/YuTIkSgrK8PmzZvh7++vN5rXokULjBo1Cps3b0ZlZSVCQkLw008/ITU1Fe+99x6cnJwAAKWlpZg9ezaKioowZswYHD16VK8NrVq10gvmiIiIGhrexWlbDhGgOTk54eOPP8YXX3yBbdu2QaPRIDg4GPPmzcPjjz/+0PI+Pj5YsWIFVq5cidWrV4t3cU6dOtVgd+ikSZPQpEkTJCUlYe/evfD19cWCBQvQv39/Mc/du3dx69YtAMDq1asNvm/QoEEM0IiIqGHjFKdNyQRBYPfYuYyMDMTExEDTOgyC0rO+m0NEZHMyXX23oOE6tnGWTeuv/p1UHBAOnZunRXXJSwvQOOsg1q5da/TA+EeZQ4ygERERUd2SwQpTnFZpiWNigEZERETScYrTphxiFycRERGRI+EIGhEREUnGXZy2xQCNiIiIpKuHKU6tVot169Zh//79KCoqQrt27TBhwgR06dKlxnIpKSn48ccfceHCBdy+fRstWrRA9+7d8ec///mh92PXF05xEhERkXSClT4SxMbGIiEhAf3798dbb70FuVyOOXPmIDU1tcZyS5cuRXZ2NgYMGIAZM2aga9eu2L59OyZPngyNRiOtEXWEI2hERERk99LT05GcnIzJkydj7NixAICBAwciOjoa8fHxiI+PN1l24cKF6NSpk15aUFAQPvroIxw4cABDhw61advNwRE0IiIikqz6mA2LPhK+LyUlBU5OToiMjBTTlEolhgwZgrS0NL3rGh/0YHAGAL179wZw72pGe8QAjYiIiKSr4ynOzMxM+Pr6wt3dXS89JCQEAJCVlSWp+Wq1GgDg6ekpqVxd4RQnERER1avs7Gy9n1UqFby9vfXS1Go1VCqVQdnqtPz8fEnf+e9//xtOTk4IDQ2V2Nq6wQCNiIiIpBMEyCy9LfJ/5RctWqSXHB0djfHjx+ulaTQauLi4GFRRfWe2lMX+Bw4cwK5duzB27Fi0adNGaqvrBAM0onoi1+nQ8dYleJcWIt/NA6db+EMn56qD2mDfEdkBKx6zsWDBAvj5+YnJxkbKlEolKioqDNK1Wq34vDbOnDmDJUuWoGvXroiJiTGj0XWDARpRPQjLTsXbv+6AT+ldMS3XrSn+1XU4Dvl1qMeW2T/2HZHj8fPze+hl6SqVCnl5eQbp1WvJHpwSNSYrKwvz5s2Dv78/Fi5cCGdn+w2D+FdOojoWlp2KJYe+RvP7AgwAaF56F0sOfY2w7JrP83mUse+I7IfFOzgl3kQQEBCAa9euoaSkRC89PT1dfF6TnJwczJ49G15eXvj444/h5uYm+Z3rEgM0ojok1+nw9q87IMDwXz457o32z/o1EXKdru4bZ+fYd0R2qA4PqQ0LC0NVVRWSkpLENK1Wi927d6N9+/bw8fEBAOTm5hpsOlCr1Xj77bchl8uxdOlSu925eT/7HdsjckAdb13Sm5p7kBzAY6UF6HjrEk4+VvPfBh817DuiR1v79u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHxbT3nnnHVy/fh1jx47F2bNncfbsWfGZl5fXQ6+Kqg8M0IjqkHdpoVXzPUrYd0T2RWaFTQJSL0ufP38+fHx8sG/fPhQXF8Pf3x9LlixBx44dayxXfUba5s2bDZ517NiRARrRoy7fzcOq+R4l7DsiO1MPl6UrlUpMmTIFU6ZMMZlnxYoVBmn3j6Y1FFyDRlSHTrfwR65bU5haJaUDcNPNE6db+NdlsxoE9h2RfanrTQKPGgZoRHVIJ5fjX12HQwYYBBo63LuX7tOuw3imlxHsOyJ6lPC/ZER17JBfB8wN+zPy3Jrqpd9y88TcsD/zLK8asO+I7Egd38X5qOEaNKJ6cMivAw63eZqn4ZuBfUdkH2SA5ZsErNEQB8UAjaie6ORyHgdhJvYdETk6BmhEREQknSCIl51bVAcZxQCNiIiIpLPGLkzGZyZx0QYRERGRneEIGhEREUlXDwfVPkoYoBEREZFkMgGGhxJKxQDNJE5xEhEREdkZjqARERGRdJzitCkGaERERCSZjAGaTTFAIyIiIul4DppNcQ0aERERkZ3hCBoRERFJxilO22KARkREROZhgGUzDhOgFRUVYdWqVTh8+DA0Gg1CQkIwZcoUBAUF1ar85cuXsXLlSpw9exbOzs7o3r07pk2bBk9PT718Op0OW7ZswY4dO3D79m34+vpi3Lhx6Nevn8m6Kysr8cYbbyA7OxuTJ0/G2LFjLXlVIiIicnAOEaDpdDrMnTsXv//+O8aMGYOmTZtix44dmDFjBtauXYs2bdrUWP7WrVuYPn06GjdujJiYGJSVlWHLli24dOkSVq9eDRcXFzHv2rVr8e233yIiIgLBwcE4cuQIFi5cCJlMhr59+xqtf9u2bbh165ZV35mIiKg+cYrTthxik8ChQ4dw7tw5zJs3D2+88Qb+9Kc/YcWKFZDL5fjqq68eWv6bb75BeXk5li9fjpEjR+K1117DP/7xD2RlZWHPnj1ivry8PGzduhVRUVF45513EBERgX/+85/o0KEDvvjiC1RVVRnUfefOHXz99dd45ZVXrPrORERE9ap6F6elHzLKIQK0lJQUNGvWDL179xbTPD09ER4ejiNHjkCr1T60/IsvvggfHx8x7fnnn0ebNm1w8OBBMe3IkSOorKxEVFSUmCaTyTB8+HDk5eUhLS3NoO7Vq1ejTZs26N+/vyWvSERERI8QhwjQLl68iMDAQMjl+q8TEhKC8vJyXL161WTZvLw83Llzx+hatZCQEGRmZoo/Z2ZmolGjRvDz8zPIV/38funp6di7dy+mT58OmUxW6/fJz89HRkaG+MnOzq51WSIiorogE6zzIeMcYg3a7du38eyzzxqkq1QqAIBarUa7du2MllWr1Xp5HyxfWFgIrVYLhUIBtVoNLy8vg2Crumx+fr6YJggC4uLi0KdPHzz99NO4ceNGrd8nKSkJGzZsqHV+IiKiOsc1aDZldwGaTqdDRUVFrfIqFArIZDJoNBooFAqjzwFAo9GYrKP62f0bAYyVVygU0Gg0D81Xbc+ePbh06RIWLlxYq3e5X2RkJHr06CH+nJ2djUWLFkmuh4iIiBomuwvQzpw5gxkzZtQq76ZNm+Dn5welUml0nVl1mlKpNFlH9TNjQeGD5ZVKZa3ylZSUYM2aNRg7dqzeurba8vb2hre3t+RyREREdcnSKUoOoJlmdwHa448/jnnz5tUqb/XUYrNmzcSpyvvVNH35YB2mynt4eIgjZCqVCqdOnYIgCHrTnNVlq4OqLVu2oKKiAn369BGnNvPy8gAAxcXFuHHjBry9vY2OxhERETUIOlgeoems0hKHZHcBmkqlwuDBgyWVCQwMRGpqKnQ6nd5GgfPnz8PV1bXGc9CaN28OT09PZGRkGDw7f/48AgICxJ8DAgKwc+dOZGdno23btmJ6enq6+BwAcnNzUVRUhNdff92gzk2bNmHTpk1Yt24dAgMDJb0nERGR3eAaNJuyuwDNHKGhoTh06BAOHz6MsLAwAEBBQQEOHjyIF198UW99Wk5ODgCgdevWeuX37t2L3NxccUryxIkTuHr1Kl5++WUxX8+ePbFy5Ups374dM2fOBHBvM0BiYiKaN2+Op59+GgAwYsQI9OrVS6+Nd+7cwdKlSzF48GD07NkTLVu2tH5HEBERkUNwiAAtLCwM33//PWJjY3H58mXxJgGdTofx48fr5a0OrBISEsS0cePG4dChQ/jrX/+KkSNHoqysDJs3b4a/v7/eaF6LFi0watQobN68GZWVlQgJCcFPP/2E1NRUvPfee3BycgIABAUFGRzbUT3V2bZtW4PgjYiIqKGxyjEZAgfRTHGIAM3JyQkff/wxvvjiC2zbtg0ajQbBwcGYN28eHn/88YeW9/HxwYoVK7By5UqsXr1avItz6tSpBrtDJ02ahCZNmiApKQl79+6Fr68vFixYwINoiYjoEWONmwAYnpkiEwTes2DvMjIyEBMTA03rMAhKz/puDhGRzcm4eNxsxzbOsmn91b+TZK49IZM3taguQXcXQvkRrF271uiB8Y8yhxhBIyIiorrFKU7bYoBGRERE0nEXp005xF2cRERERI6EI2hEREQkmUwQILN0GTuXwZvEAK0BabwzFfIS3j5AREQ12FhH3yPA8psAGJ+ZxClOIiIiIjvDETQiIiKSTCYIkFk6BMYpTpMYoBEREZF01oitGJ+ZxACNiIiIpBOscM4GR9BM4ho0IiIiIjvDETQiIiKSTgBkllbBATSTGKARERGReRhh2QynOImIiIjsDEfQiIiISDKZzvIpThnAoSITGKARERGRdNbYxclzNkxi3EpERERkZziCRkRERNJx8MumGKARERGRZNa46klqea1Wi3Xr1mH//v0oKipCu3btMGHCBHTp0qXGcleuXEFiYiLS09ORmZkJrVaLrVu3omXLlpY036Y4xUlEREQNQmxsLBISEtC/f3+89dZbkMvlmDNnDlJTU2ssl5aWhm3btqG0tBR+fn511FrLMEAjIiIiMwj3NgpY8pEwgpaeno7k5GRMnDgRU6ZMQWRkJJYvX47HHnsM8fHxNZbt0aMHdu/eja+//hr9+vWz8L3rBgM0IiIikk5npU8tpaSkwMnJCZGRkWKaUqnEkCFDkJaWhtzcXJNlPTw84ObmJuHl6h/XoBEREZFkMkGAzMKbBKrXoGVnZ+ulq1QqeHt766VlZmbC19cX7u7ueukhISEAgKysLPj4+FjUHnvCAI2IiIjq1aJFi/R+jo6Oxvjx4/XS1Go1VCqVQdnqtPz8fNs1sB4wQCMiIiLpBFjtLs4FCxboLd43FohpNBq4uLgYpCsUCvG5I2GARkRERGYQLA/QZPfK+/n5ISgoqMasSqUSFRUVBularVZ87ki4SYCIiIjsnkqlglqtNkivTntwzVpDxwCNiIiIpKvjXZwBAQG4du0aSkpK9NLT09PF546EARoRERFJVr2L09JPbYWFhaGqqgpJSUlimlarxe7du9G+fXtxB2dubq7BrtCGiGvQiIiIyO61b98e4eHhWLNmDQoKCtC6dWvs3bsXN2/exNy5c8V8ixcvxunTp3H48GExrbi4GNu2bQMAnDt3DgDwf//3f2jcuDEaN26MESNG1O3L1AIDNCIiIpJOsMImAYnl58+fDx8fH+zbtw/FxcXw9/fHkiVL0LFjxxrLFRUVYd26dXppW7duBQA89thjDNCIiIjIUVghQJN4WbpSqcSUKVMwZcoUk3lWrFhhkNayZUu9EbWGgGvQiIiIiOwMR9CIiIhIOmscVGudc24dEgM0IiIikk7iMRlGyazREMfEAI2IiIiks8Jl6da6KsoROUyAVlRUhFWrVuHw4cPQaDQICQnBlClTHnp1RLXLly9j5cqVOHv2LJydndG9e3dMmzYNnp6eevl0Oh22bNmCHTt24Pbt2/D19cW4cePQr18/gzp1Oh2SkpKQlJSEK1euwNXVFe3atcP06dMd7kA9IiIish6HCNB0Oh3mzp2L33//HWPGjEHTpk2xY8cOzJgxA2vXrkWbNm1qLH/r1i1Mnz4djRs3RkxMDMrKyrBlyxZcunQJq1ev1rucde3atfj2228RERGB4OBgHDlyBAsXLoRMJkPfvn316v3nP/+JAwcOYODAgfjTn/6EsrIyZGZm4s6dOzbpByIiorpT97s4HyUOEaAdOnQI586dw8KFCxEWFgYA6NOnD1555RV89dVXeP/992ss/80336C8vBxffvmleBJxSEgIZs2ahT179iAyMhIAkJeXh61btyIqKgozZ84EAAwdOhTTp0/HF198gbCwMDg5OQEAfvzxR+zduxeLFi1C7969bfTmRERE9UQn3PtYWgcZ5RDHbKSkpKBZs2Z6gZCnpyfCw8Nx5MgR8ab7msq/+OKLYnAGAM8//zzatGmDgwcPimlHjhxBZWUloqKixDSZTIbhw4cjLy8PaWlpYnpCQgJCQkLQu3dv6HQ6lJWVWeNViYiI6BHgEAHaxYsXERgYCLlc/3VCQkJQXl6Oq1evmiybl5eHO3fuGF2rFhISgszMTPHnzMxMNGrUCH5+fgb5qp8DQElJCc6fP4/g4GCsWbMGgwcPxsCBAzF69Gj8+OOPZr8nERGR3ai+ScDSDxnlEFOct2/fxrPPPmuQrlKpAABqtRrt2rUzWlatVuvlfbB8YWEhtFotFAoF1Go1vLy8IJPJDPIBQH5+PgAgJycHgiDgxx9/hJOTEyZPngx3d3d8//33+Mc//gF3d3d069bN5Pvk5+eL7QLgEJe+EhGRg+E5aDZldwGaTqdDRUVFrfIqFArIZDJoNBooFAqjzwFAo9GYrKP62f0bAYyVVygU0Gg0D80HQJzOvHv3LlatWoX27dsDAHr06IHRo0dj48aNNQZoSUlJ2LBhg8nnRERE5NjsLkA7c+YMZsyYUau8mzZtgp+fH5RKpdF1ZtVpSqXSZB3Vz4wFhQ+WVyqVtc4H3Lv7qzo4AwA3Nzf06NED+/fvR2VlJZydjXd/ZGQkevToIf6cnZ2NRYsWmXwHIiKiusddnLZkdwHa448/jnnz5tUqb/XUYrNmzfSmBKvVNH35YB2mynt4eIgjZCqVCqdOnYIgCHrTnNVlvb299f63WbNmBnV6enqisrIS5eXlaNy4sdE2eXt7i3UQERHZJe7itCm7C9BUKhUGDx4sqUxgYCBSU1Oh0+n0NgqcP38erq6uNZ6D1rx5c3h6eiIjI8Pg2fnz5/UOlA0ICMDOnTuRnZ2Ntm3biunp6enic+BegNWsWTPk5eUZ1KlWq6FQKODm5ibpHYmIiOjR4RC7OENDQ3H79m0cPnxYTCsoKMDBgwfx4osv6q1Py8nJQU5OjkH5X375Bbm5uWLaiRMncPXqVYSHh4tpPXv2hLOzM7Zv3y6mCYKAxMRENG/eHE8//bSY3qdPH9y6dQvHjx/Xa9ORI0fQuXNngx2nREREDYqgs86HjLK7ETRzhIWF4fvvv0dsbCwuX74s3iSg0+kwfvx4vbzVB8wmJCSIaePGjcOhQ4fw17/+FSNHjkRZWRk2b94Mf39/vdG8Fi1aYNSoUdi8eTMqKysREhKCn376CampqXjvvffEQ2qr6zx48CDee+89vPzyy2jcuDESExNRWVmJiRMn2rhHiIiIbIy7OG3KIQI0JycnfPzxx/jiiy+wbds2aDQaBAcHY968eXj88ccfWt7HxwcrVqzAypUrsXr1avEuzqlTpxrsDp00aRKaNGmCpKQk7N27F76+vliwYAH69++vl69Zs2b4/PPP8fnnn+O7775DZWUlnnrqKSxYsID3cBIRUcMnWGENGs9BM0kmCOwde5eRkYGYmBi4nGoGeYnhMR9ERETVDui+s2n91b+TXK8Hw0lr2XrqKkUpyltdwNq1a40eGP8oc4gRNCIiIqpj1rgJgGNEJjFAIyIiIukYoNkUtxISERER2RmOoBEREZF0HEGzKQZoREREJJ0gADoLzzFjgGYSpziJiIiI7AxH0IiIiEg6TnHaFAM0IiIiko4Bmk1xipOIiIjIznAEjYiIiKTjVU82xQCNiIiIpBMECAJ3cdoKAzQiIiKSTmeFETRLyzswrkEjIiIisjMcQSMiIiLpuIvTphigERERkXSCzgo3CVhY3oFxipOIiIjIznAEjYiIiKQTYIUpTqu0xCExQCMiIiLJBJ0OgoVTnJaWd2Sc4iQiIiKyMxxBIyIiIum4i9OmGKARERGRdLzqyaY4xUlERERkZziCRkRERNIJguXnmHEEzSQGaERERCSZoBMgWDjFaWl5R8YAjYiIiMygs8JNADxmwxSuQSMiIiKyMxxBIyIiIskEneVTlLyK0zQGaERERCSdYIUpTkZoJjFAawA0Gg0AQGhUydl6IiKqUUZGBvz8/ODq6mrT7xHcLP+dJLhVWqUtjogBWgOQmZkJAKgMLqznlhARkb2LiYnBJ598gm7dutmkfk9PT7i6uqI8yDq/k1xdXeHp6WmVuhwJA7QGwM/PDwAwd+5cBAQE1HNrGpbs7GwsWrQICxYsEPuRaod9Zxn2n/nYd+ar7rtGjRrZ7Dt8fHywadMmFBQUWKU+T09P+Pj4WKUuR8IArQFo0qQJACAgIABBQUH13JqGyc/Pj31nJvadZdh/5mPfmU+pVNq0fh8fHwZVNsZjNoiIiIjsDAM0IiIiIjvDAK0BUKlUiI6Ohkqlqu+mNDjsO/Ox7yzD/jMf+8587DvHIRME3lRKREREZE84gkZERERkZxigEREREdkZBmhEREREdoYBGhEREZGd4UG1dejUqVOYMWOG0Wfx8fF46qmnxJ/Pnj2LVatW4eLFi3B3d0d4eDhiYmLg5uZmUDYjIwNfffUVzp49C61Wi1atWiEiIgIjR4602bvUNVv03dWrV7Fu3TqcPXsWhYWF8PHxQb9+/TBmzBib32FX12rbf7/++it+/PFHnD9/HtnZ2WjRogUSEhKMltPpdNiyZQt27NiB27dvw9fXF+PGjUO/fv1s9h71wdp9l52djd27d+P48ePIyclBo0aN8OSTT2L8+PEIDg626bvUNVv8ubvf/v37xVPz9+3bZ9W22wNb9V9OTg7WrVuH3377DaWlpWjevDn69OmDmJgYm7wHmYcBWj0YMWIEQkJC9NJat24t/nNmZiZmzpwJPz8/TJs2Dbdu3cLWrVtx7do1fPLJJ3rlfv31V8ybNw+BgYH485//jEaNGiEnJwd5eXl18i51zVp9l5ubi0mTJqFx48aIioqCh4cH0tLSsH79emRkZCA2NrbO3qkuPaz/fvjhB/z444948sknH7pNf+3atfj2228RERGB4OBgHDlyBAsXLoRMJkPfvn1t0v76ZK2+27lzJ3bt2oXQ0FAMHz4cJSUlSEpKwuTJk/HJJ5/g+eeft9k71Bdr/rmrVlpailWrVtn0SiN7Yc3+y8zMxIwZM+Dt7Y3Ro0ejadOmyM3Nxa1bt2zSdrKAQHXm5MmTQq9evYSDBw/WmG/27NnC8OHDheLiYjHtP//5j9CrVy/h2LFjYlpxcbEwbNgwYf78+UJVVZWtmm0XrN13GzduFHr16iVcunRJr/yiRYuEXr16CYWFhVZtf32rbf/l5eUJFRUVgiAIwpw5c4RRo0YZzXfr1i0hPDxc+PTTT8U0nU4nTJ06VfjTn/4kVFZWWq3t9c3afXfhwgWhpKREL62goECIiIgQpkyZYpU22wtr99394uPjhVdffVVYuHChMGDAAGs01+5Yu/+qqqqE119/XZg0aZJQXl5u7eaSlXENWj0pLS1FZWWlQXpJSQl+++03DBgwAO7u7mL6wIED0ahRIxw8eFBM++GHH3D79m3ExMRALpejrKwMOp2uTtpfn6zRdyUlJQAALy8vvTpUKhXkcjmcnR13cNlU/wGAt7d3rd79yJEjqKysRFRUlJgmk8kwfPhw5OXlIS0tzWrttSfW6LugoCCD6famTZuiQ4cOyM7Otko77ZE1+q7a1atX8d1332Hq1KlwcnKyVhPtmjX67/jx4/jjjz8QHR0NpVKJ8vJyVFVVWbupZCWO+1vIjsXGxqKsrAxOTk7o0KEDJk+eLK49uXTpEqqqqgwuCHZxcUFgYCAyMzPFtN9++w3u7u7Iz8/H3/72N1y9ehWNGjXCgAEDMG3aNJtfllsfrNV3nTp1wr///W8sWbIE48ePh4eHB86dO4fExESMGDHCYadNauo/KTIzM9GoUSP4+fnppVdPw2RmZqJDhw5WabO9sFbfmXL79m00bdrUavXZE2v33WeffYZOnTqhe/fuen/xclTW6r/ffvsNwL3/JsbExCAjIwMuLi7o1asXZs2aBQ8PD2s3nSzAAK0OOTs7IzQ0FC+88AKaNm2Ky5cvY+vWrZg2bRq++OILPPnkk1Cr1QBgdB2BSqXCmTNnxJ+vXbuGqqoqzJ8/H0OGDMHEiRNx+vRpbNu2DcXFxfjggw/q7N1szdp9161bN7z55pv45ptv8PPPP4vpr732mkMulK1N/0mhVqvh5eUFmUyml17d9/n5+VZre32zdt8Zc+bMGaSlpeH111+3Qovthy367ujRozh+/Di++uorG7TYvli7/65duwYA+Pvf/46uXbvi1Vdfxe+//45vvvkGt27dwueff27w7zTVHwZodeiZZ57BM888I/7cs2dPhIWF4Y033sCaNWuwdOlSaDQaAPf+hvMghUIBrVYr/lxWVoby8nIMGzZM3OkTGhqKiooKJCUlYfz48WjTpo2N36puWLvvAKBly5Z49tlnERoaCg8PDxw9ehTffPMNmjVrhhEjRtj2hepYbfpPCo1GY7Kfq587Cmv33YPu3LmDhQsXomXLlhg7dqylzbUr1u67iooKfPbZZxg2bBjatm1r5dbaH2v3X1lZGQAgODgY7733HgAgLCwMSqUSa9aswYkTJxxyk0pDxTVo9czX1xc9e/bEqVOnUFVVJU5LVlRUGOTVarXiL0AAYt4Hd8xVH3PgqOuAqlnSd8nJyfjkk08wZ84cREREIDQ0FO+++y4GDRqE1atX4+7du3X2HvXlwf6TQqlUmuzn6ueOzJK+u19ZWRnmzp2LsrIyfPTRR0aP0XE0lvRdQkIC7t69i/Hjx9uodfbP0n9vAcPfGf379wcAnDt3zjqNJKtggGYHWrRogYqKCpSXl4tTRNXTdfdTq9Xw9vYWf67O26xZM7181Qvfi4qKbNVku2Fu323fvh2BgYFo0aKFXr4ePXqgvLxcb72aI7u//6RQqVS4ffs2BEHQS6/u+/v72lGZ23fVKioqsGDBAly6dAkfffQR/P39rdxC+2VO3xUXF2Pjxo0YOnQoSkpKcOPGDdy4cQNlZWUQBAE3btzAnTt3bNhq+2Hun73qfy8f/J3h6ekJ4NH4ndGQMECzA9evX4dCoUCjRo3wxBNPwMnJCRkZGXp5KioqkJmZiYCAADGtejH8g2eeVa//qf6XzpGZ23d37twxuuO1epfUo7Kz6f7+kyIgIADl5eUGuw7T09PF547O3L4D7h3yu3jxYpw8eRLvvfceOnbsaP0G2jFz+q6oqAhlZWXYvHkzRo8eLX5SUlJQXl6O0aNHG5wT6ajM/bNXvWbtwd8Z1X+xehR+ZzQkDNDqUEFBgUFaVlYWfv75Z3Tp0gVyuRyNGzfG888/j/3796O0tFTMt2/fPpSVlSE8PFxMq/7nXbt26dW5a9cuODk5oVOnTrZ5kXpg7b5r06YNMjMzcfXqVb06k5OTIZfL0a5dO5u9S32oTf9J0bNnTzg7O2P79u1imiAISExMRPPmzfH0009b2mS7Ye2+A4Dly5fjxx9/xMyZMxEaGmqFVtona/adl5cXFi9ebPDp1KkTFAoFFi9ejHHjxlmx9fXPFv/eKhQK7NmzR+8vqDt37gQArj+zM9wkUIc++OADKJVKPP300/Dy8sLly5fxn//8B66urpg0aZKYb8KECZg6dSqmT5+OyMhI8TT8Ll26oFu3bmK+J598Ei+99BJ2796NqqoqdOzYEadPn8bBgwcxbtw4h5pmsnbfjRkzBseOHcO0adPwpz/9CR4eHvjll19w7NgxDB061KH6Dqh9//3+++84cuQIgHvXwRQXF+Prr78GcG9UrEePHgDuTbGMGjUKmzdvRmVlJUJCQvDTTz8hNTUV7733nkOdTWXtvktISMCOHTvw1FNPwdXVFfv379f7vl69ejnMMS/W7DtXV1f06tXL4Dt++uknXLhwweizhs7af/ZUKhVee+01rFu3DrNnz0avXr2QlZWFnTt3ol+/fga3FVD9kgkPLiIhm/n+++9x4MAB5OTkoKSkBJ6ennjuuecQHR0NX19fvbypqanifZJubm4IDw/HpEmTDBYRV1ZWYtOmTdizZw/y8/Ph4+ODqKgovPzyy3X5ajZni75LT0/HV199hczMTBQWFqJly5YYNGgQxo4d63AH1da2//bs2WPymqtBgwZh/vz54s86nQ7//ve/kZSUBLVaDV9fX7z66qsYMGCAzd+nLlm77z766CPs3bvX5Pdt3boVLVu2tO5L1BNb/Ll70EcffYSUlBSHvIvTFv0nCAL+7//+D//3f/+HGzduoFmzZhg0aBCio6Md7r97DR0DNCIiIiI7wzVoRERERHaGARoRERGRnWGARkRERGRnGKARERER2RkGaERERER2hgEaERERkZ1hgEZERERkZxigEREREdkZBmhEREREdoYBGhHZzMsvv1zra8f27NmD3r17i5+///3ves/feust9O7d2watNM9f/vIXvfaeOnWqvptERA6EF28RUa3cuHEDo0ePrjHPY489hoSEBIu+p2fPnggICIC/v79F9dTGwoUL8cMPP+D9999Hv379TOYrKSnB8OHD4eLigu3bt0OpVGLo0KHo2rUrTp8+jdOnT9u8rUT0aGGARkSStG7dGv379zf6rHHjxno/L1u2THL9vXr1wuDBg81qm1RDhgzBDz/8gN27d9cYoP3www/QaDQYNGgQlEolAGDo0KEAgPXr1zNAIyKrY4BGRJK0bt0a48ePr3Vee9a5c2e0bNkSJ0+eRG5uLnx8fIzm2717N4B7AR0RUV3gGjQishkpa9DMlZycjL59++KNN95Afn6+mH769Gm8++67iIiIQN++fTF27FisXbsW5eXlYh6ZTIaXXnoJOp1ODMIe9Mcff+D8+fNo164dgoODbfouRETVGKARUYO1bds2LFy4EO3bt8dnn30Gb29vAMCOHTswY8YMnD17Fi+88AJGjBiBFi1aYNOmTZg1axYqKirEOgYNGgS5XI49e/ZAEASD7+DoGRHVB05xEpEkOTk5WL9+vdFnTz31FLp161Yn7Vi7di02bdqEXr164f333xfXhl2+fBlxcXFo164dli1bhqZNm4plvvnmG6xZswbbtm3DmDFjAAA+Pj7o0qULjh07hpMnT+K5554T81dWVuLAgQNQKBQYMGBAnbwXERHAAI2IJMrJycGGDRuMPhs5cqTNA7SqqiosXboUu3btQkREBGbNmgUnJyfxeWJiIqqqqjBjxgy94AwAXnnlFSQkJCA5OVkM0IB7o2PHjh3Drl279AK0o0eP4vbt2wgPD4eHh4dN34uI6H4M0IhIkq5du2Lp0qX19v3vvfcejhw5gtdeew0xMTEGz9PT0wEAv/76K06cOGHw3NnZGVeuXNFL69mzJzw9PfHTTz+huLhY3I26a9cuAJzeJKK6xwCNiBqUM2fOQKFQ4IUXXjD6vLCwEACwadOmWtfp7OyMAQMGICEhAT/88AOGDx8OtVqNY8eOwcfHB88//7xV2k5EVFsM0IioQVm2bBlmzZqFd955B5988gmeeeYZvefu7u4AgL1798LNza3W9Q4dOhQJCQnYtWsXhg8fjv3796OqqgqDBw+GXM79VERUt/hfHSJqUJ588kksX74cLi4ueOedd3D27Fm95+3btwcApKWlSaq3bdu2eOqpp5CRkYHff/8du3fvFo/hICKqawzQiKjBCQgIEIO02bNnIzU1VXw2fPhwODk5IS4uDrm5uQZli4qKcPHiRaP1Vq81+/TTT5GdnY3nnnsOjz32mG1egoioBpziJCJJajpmAwBeffVV8cgLW2rXrh2WL1+OmTNn4p133sHHH3+MZ599Fv7+/pg1axY+/fRTvPrqq3jhhRfQunVrlJaW4vr16zhz5gwGDRqE2bNnG9TZp08ffPbZZ+KoHDcHEFF9YYBGRJLUdMwGAIwaNapOAjRAP0ibM2cOlixZgo4dOyIiIgIBAQFISEjAmTNn8Msvv8Dd3R0+Pj4YNWoUBg0aZLQ+Nzc3hIeHY/fu3fDw8ECvXr3q5D2IiB4kE4wdnU1EVMf27NmD2NhYzJs3r84uS7eG9evXY8OGDYiLi0OnTp3quzlE5CC4Bo2I7EpsbCx69+6Nv//97/XdlBr95S9/Qe/evWscTSQiMhenOInILgQEBCA6Olr82d/fv/4aUwtDhw5F165dxZ+5mYCIrIlTnERERER2hlOcRERERHaGARoRERGRnWGARkRERGRnGKARERER2RkGaERERER2hgEaERERkZ1hgEZERERkZxigEREREdkZBmhEREREdub/AUGWBZpWCt8xAAAAAElFTkSuQmCC", "text/plain": [ - "array([506., 508., 510., 512., 514., 516.])" + "
" ] }, "metadata": {}, @@ -634,111 +689,200 @@ } ], "source": [ - "f['DRM/AXES/Em'][:]" + "fig, ax = plt.subplots()\n", + "dr.draw(ax=ax)\n", + "ax.scatter(Ei0, dr.transform_Em_to_eps(Em0, Ei0), marker='*')\n", + "for e1 in dr.neighbors[0]:\n", + " for e2 in dr.neighbors[1]:\n", + " ax.scatter(e1, dr.transform_Em_to_eps(e2, Ei0), c='r')\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 118, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.005 0.005 0.98 0.005 0.005]\n", + "[0.02530253 0.47234723 0.47974797 0.02260226 0. ]\n", + "[0.0019 0.1481 0.6929 0.1554 0.0017]\n", + "[0. 0.0223 0.4764 0.4778 0.0235]\n" + ] + } + ], "source": [ - "f.close()" + "mu = 511\n", + "\n", + "# Create model 0\n", + "model0 = np.array([0.005,0.005, 0.98, 0.005, 0.005])\n", + "print(model0)\n", + "\n", + "# Create model 1\n", + "counts, bins = np.histogram(np.random.normal(loc=mu-1, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "bincenters = (bins[1:]+bins[:-1])/2 * u.keV\n", + "model1 = counts / np.sum(counts)\n", + "print(model1)\n", + "\n", + "# Create model 2\n", + "counts, bins = np.histogram(np.random.normal(loc=mu, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "model2 = counts / np.sum(counts)\n", + "print(model2)\n", + "\n", + "# Create model 3\n", + "counts, bins = np.histogram(np.random.normal(loc=mu+1, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "model3 = counts / np.sum(counts)\n", + "print(model3)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 200, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$[510.2826,~510.37249,~514.74124,~509.09524,~509.89007,~512.51471,~508.54299,~512.85188,~512.16756,~512.62646] \\; \\mathrm{keV}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 200, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "f = h5py.File('transformed_response_example.h5', mode='w', track_order=True)\n", - "grp = f.create_group('DRM')\n", - "\n", - "dset_contents = grp.create_dataset('CONTENTS', shape=(3,5,5), dtype=float)\n", - "grp_axes = grp.create_group('AXES', track_order=True)\n", - "\n", - "# 1 more than shape of contents dataset\n", - "dset_axis_NL = grp_axes.create_dataset('NuLambda', shape=4, dtype=float)\n", - "dset_axis_Ei = grp_axes.create_dataset('Ei', shape=6, dtype=float)\n", - "dset_axis_Em = grp_axes.create_dataset('Em', shape=6, dtype=float)" + "# Simulate events\n", + "Ntot = 10\n", + "a = np.random.normal(loc=511, scale=1.414, size=Ntot) * u.keV\n", + "a" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 205, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "-10" + ] + }, + "execution_count": 205, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "e_col = np.linspace(-0.0075, 0.0075, 6)" + "loglikes = []\n", + "runningsum = 0\n", + "loglike = -Ntot\n", + "bins = np.arange(506, 517, 2)\n", + "n_mu, n_sigma = 30, 30\n", + "pred_mu, pred_sigma = np.meshgrid(np.linspace(508, 514, n_mu), np.linspace(0.5, 2.5, n_sigma))\n", + "for i in range(n_mu):\n", + " for j in range(n_sigma):\n", + " bincenters = (bins[1:]+bins[:-1])/2\n", + " counts = gaussian(x=bincenters, center=pred_mu[i, j], sigma=pred_sigma[i, j])\n", + " model5 = counts / np.sum(counts)\n", + "\n", + " for Em in a:\n", + " for model, Ei in zip(model5, bincenters*u.keV):\n", + " rsp_val = dr.get_interp_response({'Ei': Ei, 'Em': Em})\n", + " if rsp_val < 1e-3 * u.cm**2:\n", + " rsp_val = 1e-3 * u.cm**2\n", + " runningsum += rsp_val * model / u.cm**2\n", + "\n", + " loglike += np.log(runningsum)\n", + " runningsum = 0\n", + " loglikes.append(loglike)\n", + " loglike = -Ntot\n", + "\n", + "loglike" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 206, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[503.958 505.946 507.934 509.922 511.91 ]\n", - "[505.479 507.473 509.467 511.461 513.455]\n", - "[507. 509. 511. 513. 515.]\n", - "[508.521 510.527 512.533 514.539 516.545]\n", - "[510.042 512.054 514.066 516.078 518.09 ]\n" - ] - }, { "data": { "text/plain": [ - "array([[0.01 , 0.01 , 0.01 , 0.01 , 0.01 ],\n", - " [0.19 , 0.19 , 0.19 , 0.19 , 0.185],\n", - " [0.6 , 0.6 , 0.6 , 0.6 , 0.61 ],\n", - " [0.19 , 0.19 , 0.19 , 0.19 , 0.185],\n", - " [0.01 , 0.01 , 0.01 , 0.01 , 0.01 ]])" + "(511.51724137931035, 1.5344827586206897)" ] }, + "execution_count": 206, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "for i in range(5):\n", - " Em = (e_col[i]+e_col[i+1])/2 * Ei + Ei\n", - " print(Em)\n", - " R[i, :] = gaussian(x=Em, center=Ei)\n", - "\n", - "R /= np.sum(R, axis=0)\n", - "R = np.round(R, 2)\n", - "R[2, :4] = 0.6\n", - "R[2, 4] = 0.61\n", - "R[1:4:2, 4] = 0.185\n", - "\n", - "R[::-1]" + "pred_mu[np.argmax(loglikes)//n_mu, np.argmax(loglikes)%n_mu], pred_sigma[np.argmax(loglikes)//n_sigma, np.argmax(loglikes)%n_sigma]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 210, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "f['DRM/AXES/NuLambda'][:] = np.arange(4)\n", - "f['DRM/AXES/Ei'][:] = np.arange(506, 517, 2)\n", - "f['DRM/AXES/Em'][:] = e_col\n", - "\n", - "for i in range(3):\n", - " f['DRM/CONTENTS'][i, :, :] = R" + "plt.scatter(pred_mu, pred_sigma, c=loglikes, vmin=-30)\n", + "plt.xlabel('Predicted energy (keV)')\n", + "plt.ylabel('Predicted line broadening (keV)')\n", + "plt.title('Unbinned RL Monte Carlo')\n", + "plt.colorbar()\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m response:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(response[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:85\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 81\u001b[0m filename \u001b[38;5;241m=\u001b[39m Path(filename)\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filename\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.h5\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 85\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_h5\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(filename\u001b[38;5;241m.\u001b[39msuffixes[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.rsp.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:108\u001b[0m, in \u001b[0;36mFullDetectorResponse._open_h5\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m 104\u001b[0m new\u001b[38;5;241m.\u001b[39m_file \u001b[38;5;241m=\u001b[39m h5\u001b[38;5;241m.\u001b[39mFile(filename, mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 106\u001b[0m new\u001b[38;5;241m.\u001b[39m_drm \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_file[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m new\u001b[38;5;241m.\u001b[39m_unit \u001b[38;5;241m=\u001b[39m 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attr\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 59\u001b[0m \u001b[38;5;66;03m# shape is None for empty dataspaces\u001b[39;00m\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/h5a.pyx:80\u001b[0m, in \u001b[0;36mh5py.h5a.open\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"" + ] + } + ], "source": [ - "f.close()" + "with FullDetectorResponse.open('transformed_response_example.h5') as response:\n", + " print(response['DRM'])" ] } ], From ac47f23777a2fdff7f81995d3dc7d5ec5045f882 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Tue, 29 Oct 2024 17:12:03 -0700 Subject: [PATCH 14/46] Attempted listmode response on the fly generation --- docs/tutorials/response/LMDR.ipynb | 90 +++++++++++++++++------------- 1 file changed, 50 insertions(+), 40 deletions(-) diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index 030d71c9..00aa7a0a 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -8,12 +8,12 @@ { "data": { "text/html": [ - "
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        "                  available                                                                                        \n",
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-       "\u001b[38;5;46m13:26:07\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m ROOT minimizer not available                                               \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=890103;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=114963;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1345\u001b\\\u001b[2m1345\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m ROOT minimizer not available                                               \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=487563;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=184020;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1345\u001b\\\u001b[2m1345\u001b[0m\u001b]8;;\u001b\\\n"
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13:26:07 WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
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         WARNING   The cthreeML package is not installed. You will not be able to use plugins which  __init__.py:94\n",
        "                  require the C/C++ interface (currently HAWC)                                                     \n",
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+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The cthreeML package is not installed. You will not be able to use plugins which \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=370388;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=550387;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#94\u001b\\\u001b[2m94\u001b[0m\u001b]8;;\u001b\\\n",
        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mrequire the C/C++ interface \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mcurrently HAWC\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m                                      \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m              \u001b[0m\n"
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Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=502523;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=442598;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251msoftware installed and configured? \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -195,7 +195,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin FermiLATLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=922242;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=715093;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin FermiLATLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=139071;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=559848;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251msoftware installed and configured? \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -209,7 +209,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=945094;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=359005;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=667892;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=444233;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -223,7 +223,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=95360;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=149502;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=667837;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=32020;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -238,7 +238,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=329392;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=192020;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=522249;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=811914;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -253,7 +253,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=377458;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=739035;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=702737;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=608934;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -595,37 +595,47 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Bilinear interpolated value: 0.6 cm2\n", - "0.0\n", - "0.0\n", - "1.0\n", - "0.0\n", - "Multidimensional interpolated value: 0.6 cm2\n" + "Bilinear interpolated value: 0.3597186950576376 cm2\n" ] }, { - "data": { - "text/latex": [ - "$0.6 \\; \\mathrm{cm^{2}}$" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" + "ename": "TypeError", + "evalue": "only dimensionless scalar quantities can be converted to Python scalars", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mUnitConversionError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:987\u001b[0m, in \u001b[0;36mQuantity.to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 986\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 987\u001b[0m scale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munit\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_to\u001b[49m\u001b[43m(\u001b[49m\u001b[43munit\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 988\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m 989\u001b[0m \u001b[38;5;66;03m# Short-cut failed; try default (maybe equivalencies help).\u001b[39;00m\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1160\u001b[0m, in \u001b[0;36mUnitBase._to\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m self_decomposed\u001b[38;5;241m.\u001b[39mscale \u001b[38;5;241m/\u001b[39m other_decomposed\u001b[38;5;241m.\u001b[39mscale\n\u001b[0;32m-> 1160\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnitConversionError(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m is not a scaled version of \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mother\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mUnitConversionError\u001b[0m: 'Unit(\"cm2\")' is not a scaled version of 'Unit(dimensionless)'", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mUnitConversionError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:1355\u001b[0m, in \u001b[0;36mQuantity.__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1354\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1355\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mfloat\u001b[39m(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdimensionless_unscaled\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (UnitsError, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:990\u001b[0m, in \u001b[0;36mQuantity.to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 988\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m 989\u001b[0m \u001b[38;5;66;03m# Short-cut failed; try default (maybe equivalencies help).\u001b[39;00m\n\u001b[0;32m--> 990\u001b[0m value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_to_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43munit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 991\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:896\u001b[0m, in \u001b[0;36mQuantity._to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 894\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mnames \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39munit, StructuredUnit):\n\u001b[1;32m 895\u001b[0m \u001b[38;5;66;03m# Standard path, let unit to do work.\u001b[39;00m\n\u001b[0;32m--> 896\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munit\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 897\u001b[0m \u001b[43m \u001b[49m\u001b[43munit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mview\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mndarray\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mequivalencies\u001b[49m\n\u001b[1;32m 898\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 900\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 901\u001b[0m \u001b[38;5;66;03m# The .to() method of a simple unit cannot convert a structured\u001b[39;00m\n\u001b[1;32m 902\u001b[0m \u001b[38;5;66;03m# dtype, so we work around it, by recursing.\u001b[39;00m\n\u001b[1;32m 903\u001b[0m \u001b[38;5;66;03m# TODO: deprecate this?\u001b[39;00m\n\u001b[1;32m 904\u001b[0m \u001b[38;5;66;03m# Convert simple to Structured on initialization?\u001b[39;00m\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1196\u001b[0m, in \u001b[0;36mUnitBase.to\u001b[0;34m(self, other, value, equivalencies)\u001b[0m\n\u001b[1;32m 1195\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1196\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_converter\u001b[49m\u001b[43m(\u001b[49m\u001b[43mUnit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mother\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m(value)\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1125\u001b[0m, in \u001b[0;36mUnitBase._get_converter\u001b[0;34m(self, other, equivalencies)\u001b[0m\n\u001b[1;32m 1123\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m v: b(converter(v))\n\u001b[0;32m-> 1125\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1108\u001b[0m, in \u001b[0;36mUnitBase._get_converter\u001b[0;34m(self, other, equivalencies)\u001b[0m\n\u001b[1;32m 1107\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1108\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply_equivalencies\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1109\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mother\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_normalize_equivalencies\u001b[49m\u001b[43m(\u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1110\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m UnitsError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# Last hope: maybe other knows how to do it?\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m \u001b[38;5;66;03m# We assume the equivalencies have the unit itself as first item.\u001b[39;00m\n\u001b[1;32m 1114\u001b[0m \u001b[38;5;66;03m# TODO: maybe better for other to have a `_back_converter` method?\u001b[39;00m\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1086\u001b[0m, in \u001b[0;36mUnitBase._apply_equivalencies\u001b[0;34m(self, unit, other, equivalencies)\u001b[0m\n\u001b[1;32m 1084\u001b[0m other_str \u001b[38;5;241m=\u001b[39m get_err_str(other)\n\u001b[0;32m-> 1086\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnitConversionError(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00munit_str\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mother_str\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m are not convertible\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mUnitConversionError\u001b[0m: 'cm2' (area) and '' (dimensionless) are not convertible", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[4], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m Ei0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m511.9\u001b[39m\u001b[38;5;241m*\u001b[39mu\u001b[38;5;241m.\u001b[39mkeV\n\u001b[1;32m 2\u001b[0m Em0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m511\u001b[39m\u001b[38;5;241m*\u001b[39mu\u001b[38;5;241m.\u001b[39mkeV\n\u001b[0;32m----> 3\u001b[0m \u001b[43mdr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_interp_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mEi\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mEi0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mEm\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mEm0\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/ListModeResponse.py:133\u001b[0m, in \u001b[0;36mListModeResponse.get_interp_response\u001b[0;34m(self, target)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;66;03m# Generate permutations and fill fQ\u001b[39;00m\n\u001b[1;32m 132\u001b[0m permutations \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(itertools\u001b[38;5;241m.\u001b[39mproduct(\u001b[38;5;241m*\u001b[39mindices))\n\u001b[0;32m--> 133\u001b[0m fQ \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marray\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcontents\u001b[49m\u001b[43m[\u001b[49m\u001b[43mperm\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mperm\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpermutations\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;66;03m# Reshape fQ\u001b[39;00m\n\u001b[1;32m 136\u001b[0m fQ \u001b[38;5;241m=\u001b[39m fQ\u001b[38;5;241m.\u001b[39mreshape([\u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim)\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:1357\u001b[0m, in \u001b[0;36mQuantity.__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1355\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mfloat\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mto_value(dimensionless_unscaled))\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (UnitsError, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n\u001b[0;32m-> 1357\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 1358\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124monly dimensionless scalar quantities can be \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1359\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconverted to Python scalars\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1360\u001b[0m )\n", + "\u001b[0;31mTypeError\u001b[0m: only dimensionless scalar quantities can be converted to Python scalars" + ] } ], "source": [ - "Ei0 = 511*u.keV\n", + "Ei0 = 511.9*u.keV\n", "Em0 = 511*u.keV\n", "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" ] From c2576768623bfabccd7340f746767ac56f3419ba Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Sun, 3 Nov 2024 13:50:20 -0800 Subject: [PATCH 15/46] Add ListModeResponse.py --- cosipy/response/ListModeResponse.py | 154 +++++ docs/tutorials/response/LMDR.ipynb | 837 +++++++++++++--------------- 2 files changed, 547 insertions(+), 444 deletions(-) create mode 100644 cosipy/response/ListModeResponse.py diff --git a/cosipy/response/ListModeResponse.py b/cosipy/response/ListModeResponse.py new file mode 100644 index 00000000..b52f7062 --- /dev/null +++ b/cosipy/response/ListModeResponse.py @@ -0,0 +1,154 @@ +from pathlib import Path +import itertools + +import numpy as np +import astropy.units as u +from astropy.units import Quantity + +from histpy import Histogram, Axis, Axes, HealpixAxis +import mhealpy as hp +from mhealpy import HealpixBase, HealpixMap +from scoords import SpacecraftFrame, Attitude + +class ListModeResponse(Histogram): + """ + Handles nonlinear parametrizations of detector response + and supports extensions of list mode analysis + """ + + def __init__(self, *args, **kwargs): + # Overload parent init. Called in class methods. + super().__init__(*args, **kwargs) + + def _get_nearest_neighbors(self, centers, target: dict): + """ + Given n-dimensional axes, identify the indices of the nearest neighbors. + Ensures there are at least 2 dimensions. + """ + if len(centers) < 2: + raise ValueError("At least 2 dimensions are required") + + if len(centers) != len(target): + raise ValueError("Dimensions of centers and target must be equal") + + indices = [] + for dim_centers, key_target in zip(centers, target): + dim_target = target[key_target] + dim_index = np.sort(np.argpartition(np.abs(dim_centers - dim_target), 1)[:2]).tolist() + indices.append(dim_index) + + # for i, dim_centers in enumerate(centers): + # print(f"Dimension {i} centers: {dim_centers}") + + # for i, dim_indices in enumerate(indices): + # print(f"Dimension {i} indices: {dim_indices}") + + return indices + + def transform_eps_to_Em(self, eps, Ei0): + return (eps + 1) * Ei0 + + def transform_Em_to_eps(self, Em, Ei0): + return Em/Ei0 - 1 + + def _create_nd_array(self): + shape = tuple([2] * self.ndim) + array = np.zeros(2**self.ndim).reshape(shape) + return array + + def get_interp_response(self, target: dict): + """ + Currently only supports nonlinear spectral responses ( + and for a particular parametrization) + TODO: In the future, this will also support nonlinear / + piecewise-linear directional responses. + """ + + centers = [] + for axis in self.axes.labels: + if axis == 'eps': + Em_centers = self.transform_eps_to_Em(self.axes[axis].centers, target['Ei']) + centers.append(Em_centers) + else: + centers.append(self.axes[axis].centers) + + # Ei_centers = self.axes['Ei'].centers + # eps_centers = self.axes['eps'].centers # TODO: Does this make sense? As eps is nonlinearly binned + + indices = self._get_nearest_neighbors(centers, target) + + xindex = indices[0] + yindex = indices[1] + + x1, x2 = self.axes['Ei'].centers[xindex] + y1, y2 = Em_centers[yindex] + xdist = x2 - x1 + ydist = y2 - y1 + + fQ00 = self.contents[xindex[0], yindex[0]] + fQ01 = self.contents[xindex[0], yindex[1]] + fQ10 = self.contents[xindex[1], yindex[0]] + fQ11 = self.contents[xindex[1], yindex[1]] + + tx = (target['Ei'] - x1) / xdist if xdist != 0 else 0 + ty = (target['Em'] - y1) / ydist if ydist != 0 else 0 + + interpolated_response_value = (fQ00 * (1 - tx) * (1 - ty) + + fQ10 * tx * (1 - ty) + + fQ01 * (1 - tx) * ty + + fQ11 * tx * ty) + + print(f'Bilinear interpolated value: {interpolated_response_value}') + + # neighbors = [] + # dists = [] + # for i in range(self.ndim): + # neighbors.append(centers[i][indices[i]]) + # dists.append(np.diff(neighbors[-1])) + + # Initialize neighbors and dists + neighbors = [centers[i][indices[i]] for i in range(self.ndim)] + dists = [np.diff(neighbors[i]) for i in range(self.ndim)] + + # Assign to self.neighbors + self.neighbors = neighbors + + # Convert indices to a numpy array + indices = np.array(indices) + + # Initialize fQ with zeros + fQ = np.zeros(2 ** self.ndim) * self.contents.unit + + # Generate permutations and fill fQ + permutations = list(itertools.product(*indices)) + for j, perm in enumerate(permutations): + fQ[j] = self.contents[perm] + # fQ = np.array([self.contents[perm] for perm in permutations]) + + # Reshape fQ + fQ = fQ.reshape([2] * self.ndim) + + t = np.where(dists == 0, 0, [(target[key] - neighbors[i][0]) / dists[i] for i, key in enumerate(target)]) + + # Compute the interpolated response value for multidimensional interpolation + # TODO: May / may not break for higher dimensions + interpolated_response_value = 0 + fQ_flat = fQ.flatten('F')[::-1] + + for idx in range(2**self.ndim): + weight = np.prod([1 - t[dim] if (idx >> dim) & 1 else t[dim] for dim in range(self.ndim)]) + interpolated_response_value += fQ_flat[idx] * weight + + print(f'Multidimensional interpolated value: {interpolated_response_value}') + + # eps_centers = self.axes['eps'].centers + # print(x1, y1, eps_centers[yindex[0]]) + # print(x1, y2, eps_centers[yindex[1]]) + # print(x2, y1, eps_centers[yindex[0]]) + # print(x2, y2, eps_centers[yindex[1]]) + # print(fQ00, fQ01, fQ10, fQ11) + # print(fQ) + # print(xdist, ydist) + # print(dists) + + return interpolated_response_value \ No newline at end of file diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index 00aa7a0a..cc244298 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -2,265 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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         WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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         WARNING   Env. variable OMP_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
-       "                  performances in 3ML                                                                              \n",
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         WARNING   Env. variable MKL_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
-       "                  performances in 3ML                                                                              \n",
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         WARNING   Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to 1 for optimal     __init__.py:387\n",
-       "                  performances in 3ML                                                                              \n",
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Histogram\n", + "import mhealpy as hmap\n", "from mhealpy import HealpixMap, HealpixBase\n", "from scoords import Attitude, SpacecraftFrame\n", "\n", - "from threeML import Model, Powerlaw" + "from threeML import Model, Powerlaw, Gaussian" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Set initial conditions\n", + "nbins = 5\n", + "sigma_rsp = 1" ] }, { @@ -299,41 +56,80 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[0. , 0. , 0. , 0.12, 0.88],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0.88, 0.12, 0. , 0. , 0. ]])" + "array([[0. , 0. , 0. , 0.11, 0.89],\n", + " [0. , 0. , 0.11, 0.79, 0.11],\n", + " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", + " [0.11, 0.79, 0.11, 0. , 0. ],\n", + " [0.89, 0.11, 0. , 0. , 0. ]])" ] }, - "execution_count": 2, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Ei = np.array([507, 509, 511, 513, 515])\n", + "Ei = np.linspace(507, 515, nbins)\n", "\n", "R = np.zeros((5,5))\n", "for i in np.arange(5):\n", - " Z = gaussian(x=Ei[i], center=Ei)\n", + " Z = gaussian(x=Ei[i], center=Ei, sigma=sigma_rsp)\n", " R[i, :] = np.round(Z / np.sum(Z), 2)\n", "\n", - "for i in range(1,4):\n", - " R[i,i] -= 0.01\n", + "adjust = 1 - np.sum(R, axis=0)\n", + "for i in range(nbins):\n", + " if np.abs(adjust[i]) < 0.001:\n", + " continue\n", + " elif np.abs(adjust[i]) - 0.01 < 0.001:\n", + " R[i, i] += adjust[i]\n", + " elif np.abs(adjust[i]) - 0.02 < 0.001:\n", + " R[[i-1,i+1], i] += adjust[i] / 2\n", + " else:\n", + " print(i, adjust[i])\n", + " raise\n", "\n", "R[::-1, :]" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(R, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: How to expand bincenters to bin edges using numpy?\n", + "# Search key: np.arange(506, 517, 2)" + ] + }, + { + "cell_type": "code", + "execution_count": 77, "metadata": {}, "outputs": [ { @@ -348,26 +144,26 @@ { "data": { "text/plain": [ - "array([[[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]],\n", + "array([[[0.89, 0.11, 0. , 0. , 0. ],\n", + " [0.11, 0.79, 0.11, 0. , 0. ],\n", + " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", + " [0. , 0. , 0.11, 0.79, 0.11],\n", + " [0. , 0. , 0. , 0.11, 0.89]],\n", "\n", - " [[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]],\n", + " [[0.89, 0.11, 0. , 0. , 0. ],\n", + " [0.11, 0.79, 0.11, 0. , 0. ],\n", + " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", + " [0. , 0. , 0.11, 0.79, 0.11],\n", + " [0. , 0. , 0. , 0.11, 0.89]],\n", "\n", - " [[0.88, 0.12, 0. , 0. , 0. ],\n", - " [0.11, 0.78, 0.11, 0. , 0. ],\n", - " [0. , 0.11, 0.78, 0.11, 0. ],\n", - " [0. , 0. , 0.11, 0.78, 0.11],\n", - " [0. , 0. , 0. , 0.12, 0.88]]])" + " [[0.89, 0.11, 0. , 0. , 0. ],\n", + " [0.11, 0.79, 0.11, 0. , 0. ],\n", + " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", + " [0. , 0. , 0.11, 0.79, 0.11],\n", + " [0. , 0. , 0. , 0.11, 0.89]]])" ] }, - "execution_count": 3, + "execution_count": 77, "metadata": {}, "output_type": "execute_result" } @@ -383,23 +179,23 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 4, + "execution_count": 78, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -414,55 +210,67 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 81, "metadata": {}, "outputs": [], "source": [ - "eps_col = np.linspace(-0.0075, 0.0075, 6)" + "eps_upper_limit = ((Ei[-1] - Ei[0]) / Ei[0]).round(3) / 2\n", + "eps_col_edges = np.linspace(-eps_upper_limit, eps_upper_limit, nbins+1)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 88, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[503.958 505.946 507.934 509.922 511.91 ]\n", - "[505.479 507.473 509.467 511.461 513.455]\n", + "[503.7552 505.7424 507.7296 509.7168 511.704 ]\n", + "[505.3776 507.3712 509.3648 511.3584 513.352 ]\n", "[507. 509. 511. 513. 515.]\n", - "[508.521 510.527 512.533 514.539 516.545]\n", - "[510.042 512.054 514.066 516.078 518.09 ]\n" + "[508.6224 510.6288 512.6352 514.6416 516.648 ]\n", + "[510.2448 512.2576 514.2704 516.2832 518.296 ]\n", + "[0.01 0.01 0.01 0.01 0. ]\n" ] }, { "data": { "text/plain": [ - "array([[0.01 , 0.185, 0.61 , 0.185, 0.01 ],\n", - " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", - " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", - " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ],\n", - " [0.01 , 0.19 , 0.6 , 0.19 , 0.01 ]])" + "array([[0. , 0.17, 0.66, 0.17, 0. ],\n", + " [0. , 0.17, 0.66, 0.17, 0. ],\n", + " [0. , 0.17, 0.66, 0.17, 0. ],\n", + " [0. , 0.17, 0.66, 0.17, 0. ],\n", + " [0. , 0.17, 0.66, 0.17, 0. ]])" ] }, - "execution_count": 7, + "execution_count": 88, "metadata": {}, "output_type": "execute_result" } ], "source": [ "for i in range(5):\n", - " Em = (eps_col[i]+eps_col[i+1])/2 * Ei + Ei\n", + " Em = (eps_col_edges[i]+eps_col_edges[i+1])/2 * Ei + Ei\n", " print(Em)\n", - " R[i, :] = gaussian(x=Em, center=Ei)\n", + " R[i, :] = gaussian(x=Em, center=Ei, sigma=sigma_rsp)\n", "\n", "R /= np.sum(R, axis=0)\n", "R = np.round(R, 2)\n", - "R[2, :4] = 0.6\n", - "R[2, 4] = 0.61\n", - "R[1:4:2, 4] = 0.185\n", + "\n", + "adjust = 1 - np.sum(R, axis=0)\n", + "print(adjust)\n", + "for i in range(nbins):\n", + " if np.abs(adjust[i]) < 0.001:\n", + " continue\n", + " elif np.abs(adjust[i]) - 0.01 < 0.001:\n", + " R[2, i] += adjust[i]\n", + " elif np.abs(adjust[i]) - 0.02 < 0.001:\n", + " R[[1,3], i] += adjust[i] / 2\n", + " else:\n", + " print(i, adjust[i])\n", + " raise\n", "\n", "R = R.transpose(1,0)\n", "\n", @@ -471,88 +279,42 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 95, "metadata": {}, "outputs": [], "source": [ - "htransformed = Histogram([np.arange(4), np.arange(506, 517, 2)*u.keV, eps_col], contents=np.stack([R, R, R]), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" + "htransformed = Histogram([np.arange(4), np.arange(506, 517, 2)*u.keV, eps_col_edges], contents=np.stack([R, R, R]), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 96, "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$[[[0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.185,~0.61,~0.185,~0.01]],~\n", - "\n", - " [[0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.185,~0.61,~0.185,~0.01]],~\n", - "\n", - " [[0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.19,~0.6,~0.19,~0.01],~\n", - " [0.01,~0.185,~0.61,~0.185,~0.01]]] \\; \\mathrm{cm^{2}}$" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "htransformed.write('transformed_response_example.h5', overwrite=True)\n", - "htransformed.contents" + "# htransformed.contents" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 11, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -574,7 +336,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -583,7 +345,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 98, "metadata": {}, "outputs": [], "source": [ @@ -595,90 +357,34 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Bilinear interpolated value: 0.3597186950576376 cm2\n" - ] - }, - { - "ename": "TypeError", - "evalue": "only dimensionless scalar quantities can be converted to Python scalars", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mUnitConversionError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:987\u001b[0m, in \u001b[0;36mQuantity.to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 986\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 987\u001b[0m scale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munit\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_to\u001b[49m\u001b[43m(\u001b[49m\u001b[43munit\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 988\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m 989\u001b[0m \u001b[38;5;66;03m# Short-cut failed; try default (maybe equivalencies help).\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1160\u001b[0m, in \u001b[0;36mUnitBase._to\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m self_decomposed\u001b[38;5;241m.\u001b[39mscale \u001b[38;5;241m/\u001b[39m other_decomposed\u001b[38;5;241m.\u001b[39mscale\n\u001b[0;32m-> 1160\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnitConversionError(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m is not a scaled version of \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mother\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mUnitConversionError\u001b[0m: 'Unit(\"cm2\")' is not a scaled version of 'Unit(dimensionless)'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mUnitConversionError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:1355\u001b[0m, in \u001b[0;36mQuantity.__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1354\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1355\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mfloat\u001b[39m(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdimensionless_unscaled\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (UnitsError, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:990\u001b[0m, in \u001b[0;36mQuantity.to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 988\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m 989\u001b[0m \u001b[38;5;66;03m# Short-cut failed; try default (maybe equivalencies help).\u001b[39;00m\n\u001b[0;32m--> 990\u001b[0m value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_to_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43munit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 991\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:896\u001b[0m, in \u001b[0;36mQuantity._to_value\u001b[0;34m(self, unit, equivalencies)\u001b[0m\n\u001b[1;32m 894\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mnames \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39munit, StructuredUnit):\n\u001b[1;32m 895\u001b[0m \u001b[38;5;66;03m# Standard path, let unit to do work.\u001b[39;00m\n\u001b[0;32m--> 896\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munit\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 897\u001b[0m \u001b[43m \u001b[49m\u001b[43munit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mview\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mndarray\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mequivalencies\u001b[49m\n\u001b[1;32m 898\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 900\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 901\u001b[0m \u001b[38;5;66;03m# The .to() method of a simple unit cannot convert a structured\u001b[39;00m\n\u001b[1;32m 902\u001b[0m \u001b[38;5;66;03m# dtype, so we work around it, by recursing.\u001b[39;00m\n\u001b[1;32m 903\u001b[0m \u001b[38;5;66;03m# TODO: deprecate this?\u001b[39;00m\n\u001b[1;32m 904\u001b[0m \u001b[38;5;66;03m# Convert simple to Structured on initialization?\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1196\u001b[0m, in \u001b[0;36mUnitBase.to\u001b[0;34m(self, other, value, equivalencies)\u001b[0m\n\u001b[1;32m 1195\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1196\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_converter\u001b[49m\u001b[43m(\u001b[49m\u001b[43mUnit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mother\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m(value)\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1125\u001b[0m, in \u001b[0;36mUnitBase._get_converter\u001b[0;34m(self, other, equivalencies)\u001b[0m\n\u001b[1;32m 1123\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m v: b(converter(v))\n\u001b[0;32m-> 1125\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1108\u001b[0m, in \u001b[0;36mUnitBase._get_converter\u001b[0;34m(self, other, equivalencies)\u001b[0m\n\u001b[1;32m 1107\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1108\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply_equivalencies\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1109\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mother\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_normalize_equivalencies\u001b[49m\u001b[43m(\u001b[49m\u001b[43mequivalencies\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1110\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m UnitsError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# Last hope: maybe other knows how to do it?\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m \u001b[38;5;66;03m# We assume the equivalencies have the unit itself as first item.\u001b[39;00m\n\u001b[1;32m 1114\u001b[0m \u001b[38;5;66;03m# TODO: maybe better for other to have a `_back_converter` method?\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/core.py:1086\u001b[0m, in \u001b[0;36mUnitBase._apply_equivalencies\u001b[0;34m(self, unit, other, equivalencies)\u001b[0m\n\u001b[1;32m 1084\u001b[0m other_str \u001b[38;5;241m=\u001b[39m get_err_str(other)\n\u001b[0;32m-> 1086\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnitConversionError(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00munit_str\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mother_str\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m are not convertible\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mUnitConversionError\u001b[0m: 'cm2' (area) and '' (dimensionless) are not convertible", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[4], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m Ei0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m511.9\u001b[39m\u001b[38;5;241m*\u001b[39mu\u001b[38;5;241m.\u001b[39mkeV\n\u001b[1;32m 2\u001b[0m Em0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m511\u001b[39m\u001b[38;5;241m*\u001b[39mu\u001b[38;5;241m.\u001b[39mkeV\n\u001b[0;32m----> 3\u001b[0m \u001b[43mdr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_interp_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mEi\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mEi0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mEm\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mEm0\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/ListModeResponse.py:133\u001b[0m, in \u001b[0;36mListModeResponse.get_interp_response\u001b[0;34m(self, target)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;66;03m# Generate permutations and fill fQ\u001b[39;00m\n\u001b[1;32m 132\u001b[0m permutations \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(itertools\u001b[38;5;241m.\u001b[39mproduct(\u001b[38;5;241m*\u001b[39mindices))\n\u001b[0;32m--> 133\u001b[0m fQ \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marray\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcontents\u001b[49m\u001b[43m[\u001b[49m\u001b[43mperm\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mperm\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpermutations\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;66;03m# Reshape fQ\u001b[39;00m\n\u001b[1;32m 136\u001b[0m fQ \u001b[38;5;241m=\u001b[39m fQ\u001b[38;5;241m.\u001b[39mreshape([\u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim)\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/astropy/units/quantity.py:1357\u001b[0m, in \u001b[0;36mQuantity.__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1355\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mfloat\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mto_value(dimensionless_unscaled))\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (UnitsError, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n\u001b[0;32m-> 1357\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 1358\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124monly dimensionless scalar quantities can be \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1359\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconverted to Python scalars\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1360\u001b[0m )\n", - "\u001b[0;31mTypeError\u001b[0m: only dimensionless scalar quantities can be converted to Python scalars" - ] - } - ], - "source": [ - "Ei0 = 511.9*u.keV\n", - "Em0 = 511*u.keV\n", - "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" - ] - }, - { - "cell_type": "code", - "execution_count": 11, + "execution_count": 100, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.19 cm2\n", - "0.6 cm2\n", - "0.19 cm2\n", - "0.6 cm2\n", - "0.19 cm2 0.6 cm2 0.19 cm2 0.6 cm2\n", - "0.6542842215256062\n", - "0.28040752351098924\n", - "0.04571577847438243\n", - "0.0195924764890221\n", - "Multidimensional interpolated value: 0.5732236154650042 cm2\n", - "0.0195924764890221 0.04571577847438243 0.28040752351098924 0.6542842215256062\n" + "Bilinear interpolated value: 0.6300401095675922 cm2\n", + "Multidimensional interpolated value: 0.6300401095675922 cm2\n" ] }, { "data": { "text/latex": [ - "$0.57322362 \\; \\mathrm{cm^{2}}$" + "$0.63004011 \\; \\mathrm{cm^{2}}$" ], "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 100, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Ei0 = 510.4*u.keV\n", - "Em0 = 510.3*u.keV\n", + "Ei0 = 511.1*u.keV\n", + "Em0 = 511*u.keV\n", "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" ] }, @@ -726,24 +432,26 @@ ], "source": [ "mu = 511\n", + "sigma_inj = 1\n", + "bins = np.arange(506, 517, 2)\n", "\n", "# Create model 0\n", "model0 = np.array([0.005,0.005, 0.98, 0.005, 0.005])\n", "print(model0)\n", "\n", "# Create model 1\n", - "counts, bins = np.histogram(np.random.normal(loc=mu-1, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "counts, bins = np.histogram(np.random.normal(loc=mu-1, scale=sigma_inj, size=10000), bins=bins)\n", "bincenters = (bins[1:]+bins[:-1])/2 * u.keV\n", "model1 = counts / np.sum(counts)\n", "print(model1)\n", "\n", "# Create model 2\n", - "counts, bins = np.histogram(np.random.normal(loc=mu, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "counts, bins = np.histogram(np.random.normal(loc=mu, scale=sigma_inj, size=10000), bins=bins)\n", "model2 = counts / np.sum(counts)\n", "print(model2)\n", "\n", "# Create model 3\n", - "counts, bins = np.histogram(np.random.normal(loc=mu+1, scale=1, size=10000), bins=np.arange(506, 517, 2))\n", + "counts, bins = np.histogram(np.random.normal(loc=mu+1, scale=sigma_inj, size=10000), bins=bins)\n", "model3 = counts / np.sum(counts)\n", "print(model3)" ] @@ -772,7 +480,7 @@ "source": [ "# Simulate events\n", "Ntot = 10\n", - "a = np.random.normal(loc=511, scale=1.414, size=Ntot) * u.keV\n", + "a = np.random.normal(loc=511, scale=np.sqrt(sigma_rsp**2 + sigma_inj**2), size=Ntot) * u.keV\n", "a" ] }, @@ -793,20 +501,26 @@ } ], "source": [ + "bins = np.arange(506, 517, 2)\n", + "bincenters = (bins[1:]+bins[:-1])/2\n", + "\n", + "# Phase space sampling edges\n", + "nbins_mu, nbins_sigma = 30, 30\n", + "pred_mu, pred_sigma = np.meshgrid(np.linspace(508, 514, nbins_mu), np.linspace(0.5, 2.5, nbins_sigma))\n", + "\n", + "# Initial values\n", "loglikes = []\n", "runningsum = 0\n", "loglike = -Ntot\n", - "bins = np.arange(506, 517, 2)\n", - "n_mu, n_sigma = 30, 30\n", - "pred_mu, pred_sigma = np.meshgrid(np.linspace(508, 514, n_mu), np.linspace(0.5, 2.5, n_sigma))\n", - "for i in range(n_mu):\n", - " for j in range(n_sigma):\n", - " bincenters = (bins[1:]+bins[:-1])/2\n", - " counts = gaussian(x=bincenters, center=pred_mu[i, j], sigma=pred_sigma[i, j])\n", - " model5 = counts / np.sum(counts)\n", + "\n", + "for i in range(nbins_mu):\n", + " for j in range(nbins_sigma):\n", + " # Calculate model counts for sampled mu, sigma\n", + " model_counts = gaussian(x=bincenters, center=pred_mu[i, j], sigma=pred_sigma[i, j])\n", + " models = model_counts / np.sum(model_counts)\n", "\n", " for Em in a:\n", - " for model, Ei in zip(model5, bincenters*u.keV):\n", + " for model, Ei in zip(models, bincenters*u.keV):\n", " rsp_val = dr.get_interp_response({'Ei': Ei, 'Em': Em})\n", " if rsp_val < 1e-3 * u.cm**2:\n", " rsp_val = 1e-3 * u.cm**2\n", @@ -837,7 +551,7 @@ } ], "source": [ - "pred_mu[np.argmax(loglikes)//n_mu, np.argmax(loglikes)%n_mu], pred_sigma[np.argmax(loglikes)//n_sigma, np.argmax(loglikes)%n_sigma]" + "pred_mu[np.argmax(loglikes)//nbins_mu, np.argmax(loglikes)%nbins_mu], pred_sigma[np.argmax(loglikes)//nbins_sigma, np.argmax(loglikes)%nbins_sigma]" ] }, { @@ -865,6 +579,241 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setting up HealpixBase" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "mEq = HealpixBase(order=6, scheme='ring')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(6, 64, 49152)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mEq.order, mEq.nside, mEq.npix" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "theta0 = np.deg2rad(90)\n", + "phi0 = np.deg2rad(45)\n", + "sigma = np.deg2rad(1) # Gaussian on sphere with 1-sigma width = 1 deg\n", + "disc_pix = mEq.query_disc(hmap.ang2vec(theta0, phi0), 3*sigma)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([23200, 23455, 23456, 23711, 23712, 23713, 23966, 23967, 23968,\n", + " 23969, 24222, 24223, 24224, 24225, 24226, 24478, 24479, 24480,\n", + " 24481, 24734, 24735, 24736, 24737, 24738, 24990, 24991, 24992,\n", + " 24993, 25247, 25248, 25249, 25503, 25504, 25760])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "disc_pix" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "NUNIQ pixels in MOC map: 114\n", + "Equivalent single-resolution pixels: 49152\n" + ] + } + ], + "source": [ + "m = HealpixMap.moc_from_pixels(mEq.nside, disc_pix, density=True)\n", + "\n", + "print(\"NUNIQ pixels in MOC map: {}\".format(m.npix))\n", + "print(\"Equivalent single-resolution pixels: {}\".format(mEq.npix))\n", + "\n", + "# Fill the map. This code would look exactly the same if this were a\n", + "# single-resolution map\n", + "for pix in range(m.npix):\n", + "\n", + " theta,phi = m.pix2ang(pix)\n", + "\n", + " m[pix] = np.exp(-((theta-theta0)**2 + (phi-phi0)**2) / 2 / sigma**2)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "m.write_map('example.fits')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "XTENSION= 'BINTABLE' / binary table extension \n", + "BITPIX = 8 / array data type \n", + "NAXIS = 2 / number of array dimensions \n", + "NAXIS1 = 16 / length of dimension 1 \n", + "NAXIS2 = 114 / length of dimension 2 \n", + "PCOUNT = 0 / number of group parameters \n", + "GCOUNT = 1 / number of groups \n", + "TFIELDS = 2 / number of table fields \n", + "TTYPE1 = 'UNIQ ' \n", + "TFORM1 = 'K ' \n", + "TTYPE2 = 'CONTENTS' \n", + "TFORM2 = 'D ' \n", + "PIXTYPE = 'HEALPIX ' / HEALPIX pixelisation \n", + "ORDERING= 'NUNIQ ' / Pixel ordering scheme: RING, NESTED, or NUNIQ \n", + "NSIDE = 64 / Resolution parameter of HEALPIX \n", + "INDXSCHM= 'EXPLICIT' / Indexing: IMPLICIT or EXPLICIT \n", + "MOCORDER= 6 / Best resolution order " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def fits_to_h5(fits_file, h5_file):\n", + " with fits.open(fits_file) as hdul:\n", + " header0 = hdul[0].header\n", + " header1 = hdul[1].header\n", + " \n", + " with h5py.File(h5_file, 'w') as hdf:\n", + " hdf.create_group('header0')\n", + " for key, value in header0.items():\n", + " hdf['header0'].attrs[key] = value\n", + " \n", + " hdf.create_group('header1')\n", + " for key, value in header1.items():\n", + " hdf['header1'].attrs[key] = value\n", + " \n", + " data = hdul[1].data\n", + " dset = hdf.create_dataset('data', data=data)\n", + "\n", + "# Example usage\n", + "fits_to_h5('example.fits', 'example.h5')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Unsupported file format. Only .h5 and .rsp.gz extensions are supported.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mexample.fits\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:89\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n\u001b[1;32m 88\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 89\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 90\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnsupported file format. Only .h5 and .rsp.gz extensions are supported.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mValueError\u001b[0m: Unsupported file format. Only .h5 and .rsp.gz extensions are supported." + ] + } + ], + "source": [ + "FullDetectorResponse.open('example.fits')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "OSError", + "evalue": "Unable to synchronously open file (file signature not found)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mh5py\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mFile\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mexample.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m 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alignment_interval\u001b[38;5;241m=\u001b[39malignment_interval,\n\u001b[1;32m 557\u001b[0m meta_block_size\u001b[38;5;241m=\u001b[39mmeta_block_size,\n\u001b[1;32m 558\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[1;32m 559\u001b[0m fcpl \u001b[38;5;241m=\u001b[39m make_fcpl(track_order\u001b[38;5;241m=\u001b[39mtrack_order, fs_strategy\u001b[38;5;241m=\u001b[39mfs_strategy,\n\u001b[1;32m 560\u001b[0m fs_persist\u001b[38;5;241m=\u001b[39mfs_persist, fs_threshold\u001b[38;5;241m=\u001b[39mfs_threshold,\n\u001b[1;32m 561\u001b[0m fs_page_size\u001b[38;5;241m=\u001b[39mfs_page_size)\n\u001b[0;32m--> 562\u001b[0m fid \u001b[38;5;241m=\u001b[39m \u001b[43mmake_fid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muserblock_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfcpl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mswmr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mswmr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 564\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(libver, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[1;32m 565\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_libver \u001b[38;5;241m=\u001b[39m libver\n", + "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/files.py:235\u001b[0m, in \u001b[0;36mmake_fid\u001b[0;34m(name, mode, userblock_size, fapl, fcpl, swmr)\u001b[0m\n\u001b[1;32m 233\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m swmr \u001b[38;5;129;01mand\u001b[39;00m swmr_support:\n\u001b[1;32m 234\u001b[0m flags \u001b[38;5;241m|\u001b[39m\u001b[38;5;241m=\u001b[39m h5f\u001b[38;5;241m.\u001b[39mACC_SWMR_READ\n\u001b[0;32m--> 235\u001b[0m fid \u001b[38;5;241m=\u001b[39m \u001b[43mh5f\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 236\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr+\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 237\u001b[0m fid \u001b[38;5;241m=\u001b[39m h5f\u001b[38;5;241m.\u001b[39mopen(name, h5f\u001b[38;5;241m.\u001b[39mACC_RDWR, fapl\u001b[38;5;241m=\u001b[39mfapl)\n", + "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mh5py/h5f.pyx:102\u001b[0m, in \u001b[0;36mh5py.h5f.open\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mOSError\u001b[0m: Unable to synchronously open file (file signature not found)" + ] + } + ], + "source": [ + "h5py.File('example.h5', mode='r')" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(14, 7))\n", + "axMoll = fig.add_subplot(projection = \"mollview\")\n", + "m.plot(axMoll, vmin=0, vmax=1)\n", + "m.plot_grid(axMoll, color='white', linewidth = .2)\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": 11, From 7de27fdac4c50c3b85cb6ac3b537aeb267630b94 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Wed, 6 Nov 2024 15:51:12 -0800 Subject: [PATCH 16/46] Used histpy functions to dramatically simplify the codebase --- cosipy/response/ListModeResponse.py | 240 +++++++--- docs/tutorials/response/LMDR.ipynb | 704 +++++++++++++++++++++++----- 2 files changed, 760 insertions(+), 184 deletions(-) diff --git a/cosipy/response/ListModeResponse.py b/cosipy/response/ListModeResponse.py index b52f7062..788b5e36 100644 --- a/cosipy/response/ListModeResponse.py +++ b/cosipy/response/ListModeResponse.py @@ -4,6 +4,9 @@ import numpy as np import astropy.units as u from astropy.units import Quantity +from astropy.coordinates import (UnitSphericalRepresentation, SkyCoord, + BaseRepresentation, CartesianRepresentation, + BaseCoordinateFrame) from histpy import Histogram, Axis, Axes, HealpixAxis import mhealpy as hp @@ -45,16 +48,98 @@ def _get_nearest_neighbors(self, centers, target: dict): return indices + def _get_all_interp_weights(self, target: dict): + + indices = [] + weights = [] + + for label in self.axes.labels: + axis = self.axes[label] + axis_scale = axis._scale + axis_type = str(type(axis)).split('.')[-1].strip("'>") # XXX: Could probably be simplified using `isinstance()` + + # Scale + if axis_scale in ['linear', 'log']: # To ensure nonlinear binning parametrizations are converted to a linear scale. + + # Axis Type + if axis_type in ['Axis', 'HealpixAxis']: + idx, w = axis.interp_weights(target[label]) + else: + raise ValueError(f'Axis type: {axis_type} is not supported') + + elif axis_scale == 'nonlinear': + pass + + else: + raise ValueError(f'Scale: {axis_scale} is not supported') + + indices.append(idx) + weights.append(w) + + return (indices, weights) + def transform_eps_to_Em(self, eps, Ei0): - return (eps + 1) * Ei0 + # return (eps + 1) * Ei0 + return eps def transform_Em_to_eps(self, Em, Ei0): - return Em/Ei0 - 1 + # return Em/Ei0 - 1 + return Em def _create_nd_array(self): shape = tuple([2] * self.ndim) array = np.zeros(2**self.ndim).reshape(shape) return array + + # def _standarize_theta_phi_lonlat(self, theta, phi, lonlat): + + # if isinstance(theta, (SkyCoord, BaseRepresentation)): + # # Support astropy + + # if isinstance(theta, SkyCoord): + + # if self.coordsys is None: + # raise ValueError("Undefined coordinate system") + + # theta = theta.transform_to(self.coordsys) + + # coord = theta.represent_as(UnitSphericalRepresentation) + + # theta,phi = coord.lon.deg, coord.lat.deg + + # lonlat = True + + # return theta,phi,lonlat + + # def get_interp_weights(self, theta, phi = None, lonlat = False): + # """ + # Return the 4 closest pixels on the two rings above and below the + # location and corresponding weights. Weights are provided for bilinear + # interpolation along latitude and longitude + + # Args: + # theta (float or array): Zenith angle (rad) + # phi (float or array): Azimuth angle (rad) + + # Return: + # tuple: (pixels, weights), each with of (4,) if the input is scalar, + # if (4,N) where N is size of + # theta and phi. For MOC maps, these pixel numbers might repeate. + # """ + + # theta, phi, lonlat = self._standarize_theta_phi_lonlat(theta, phi, lonlat) + + # pixels,weights = hp.get_interp_weights(self.nside, theta, phi, + # nest = self.is_nested, + # lonlat = lonlat) + + # if self.is_moc: + # pixels = self.nest2pix(pixels) + + # return (pixels, weights) + + def get_neighbors(self, indices): + return [axis.centers[idx] for idx, axis in zip(indices, self.axes)] def get_interp_response(self, target: dict): """ @@ -62,93 +147,96 @@ def get_interp_response(self, target: dict): and for a particular parametrization) TODO: In the future, this will also support nonlinear / piecewise-linear directional responses. + XXX: To get the correct interpolated response, ensure + all scales passed into this function are in linear scale """ - centers = [] - for axis in self.axes.labels: - if axis == 'eps': - Em_centers = self.transform_eps_to_Em(self.axes[axis].centers, target['Ei']) - centers.append(Em_centers) - else: - centers.append(self.axes[axis].centers) - - # Ei_centers = self.axes['Ei'].centers - # eps_centers = self.axes['eps'].centers # TODO: Does this make sense? As eps is nonlinearly binned - - indices = self._get_nearest_neighbors(centers, target) - - xindex = indices[0] - yindex = indices[1] - - x1, x2 = self.axes['Ei'].centers[xindex] - y1, y2 = Em_centers[yindex] - xdist = x2 - x1 - ydist = y2 - y1 + # centers = [] + # axis_types = [] + # for axis in self.axes.labels: + # scale = self.axes[axis]._scale + # print(scale) + # axis_type = str(type(self.axes[axis])).split('.')[-1].strip("'>") + # print(axis_type) + + # # Scale + # if scale in ['linear', 'log']: # To ensure nonlinear binning parametrizations are converted to a linear scale. + + # # Axis Type + # if axis_type == 'HealpixAxis': + # centers.append(self.axes[axis].centers) # TODO: HealpixAxis type? Will this be different? + # elif axis_type == 'Axis': + # centers.append(self.axes[axis].centers) + # else: + # raise ValueError(f'Axis type: {axis_type} is not supported') + + # elif scale == 'nonlinear': # XXX: For now, eps_to_Em is the only nonlinear transformation that has been implemented + # # This "nonlinear" transformation is still represented on a linear scale. So need to find a different attribute to use for `if <> == 'nonlinear'` comparison + # this_edges = self.transform_eps_to_Em(self.axes[axis].edges, target['Ei']) + # this_centers = (this_edges[:-1] + this_edges[1:]) / 2 + # centers.append(this_centers) + + # elif scale == 'log': + + # this_centers = np.log2(self.axes[axis].centers.value) # I chose log2 instead of ln as the former was used in `histpy.axis` too. Also see https://stackoverflow.com/questions/33809789/why-are-log2-and-log1p-so-much-faster-than-log-and-log10-in-numpy + # centers.append(this_centers) + + # else: + # raise ValueError(f'Scale: {scale} is not supported') + + # indices = self._get_nearest_neighbors(centers, target) + indices, weights = self._get_all_interp_weights(target) + perm_indices = list(itertools.product(*indices)) + perm_weights = list(itertools.product(*weights)) + interpolated_response_value = 0 + for idx, w in zip(perm_indices, perm_weights): + interpolated_response_value += np.prod(w) * self.contents[idx] - fQ00 = self.contents[xindex[0], yindex[0]] - fQ01 = self.contents[xindex[0], yindex[1]] - fQ10 = self.contents[xindex[1], yindex[0]] - fQ11 = self.contents[xindex[1], yindex[1]] + self.neighbors = self.get_neighbors(indices) + + return interpolated_response_value - tx = (target['Ei'] - x1) / xdist if xdist != 0 else 0 - ty = (target['Em'] - y1) / ydist if ydist != 0 else 0 + # interpolated_response_value = 0 + # for i, axis in enumerate(self.axes): + # for j, idx in enumerate(indices[i]): + # print(axis.centers[idx]) + # print(weights[i][j]) + # interpolated_response_value += weights[i][j] * axis.centers[idx] - interpolated_response_value = (fQ00 * (1 - tx) * (1 - ty) + - fQ10 * tx * (1 - ty) + - fQ01 * (1 - tx) * ty + - fQ11 * tx * ty) - - print(f'Bilinear interpolated value: {interpolated_response_value}') - - # neighbors = [] - # dists = [] - # for i in range(self.ndim): - # neighbors.append(centers[i][indices[i]]) - # dists.append(np.diff(neighbors[-1])) + # return interpolated_response_value - # Initialize neighbors and dists - neighbors = [centers[i][indices[i]] for i in range(self.ndim)] - dists = [np.diff(neighbors[i]) for i in range(self.ndim)] + # # Initialize neighbors and dists + # neighbors = [centers[i][indices[i]] for i in range(self.ndim)] + # dists = [np.diff(neighbors[i]) for i in range(self.ndim)] # Only linear dimensions should be used to calculate distance measures. - # Assign to self.neighbors - self.neighbors = neighbors + # # Assign to self.neighbors + # self.neighbors = neighbors - # Convert indices to a numpy array - indices = np.array(indices) + # # Convert indices to a numpy array + # indices = np.array(indices) - # Initialize fQ with zeros - fQ = np.zeros(2 ** self.ndim) * self.contents.unit + # # Initialize fQ with zeros + # fQ = np.zeros(2 ** self.ndim) * self.contents.unit - # Generate permutations and fill fQ - permutations = list(itertools.product(*indices)) - for j, perm in enumerate(permutations): - fQ[j] = self.contents[perm] - # fQ = np.array([self.contents[perm] for perm in permutations]) + # # Generate permutations and fill fQ + # permutations = list(itertools.product(*indices)) + # for j, perm in enumerate(permutations): + # fQ[j] = self.contents[perm] + # # fQ = np.array([self.contents[perm] for perm in permutations]) - # Reshape fQ - fQ = fQ.reshape([2] * self.ndim) + # # Reshape fQ + # fQ = fQ.reshape([2] * self.ndim) - t = np.where(dists == 0, 0, [(target[key] - neighbors[i][0]) / dists[i] for i, key in enumerate(target)]) - - # Compute the interpolated response value for multidimensional interpolation - # TODO: May / may not break for higher dimensions - interpolated_response_value = 0 - fQ_flat = fQ.flatten('F')[::-1] + # t = np.where(dists == 0, 0, [(target[key] - neighbors[i][0]) / dists[i] for i, key in enumerate(target)]) - for idx in range(2**self.ndim): - weight = np.prod([1 - t[dim] if (idx >> dim) & 1 else t[dim] for dim in range(self.ndim)]) - interpolated_response_value += fQ_flat[idx] * weight + # # Compute the bilinearly interpolated response value for multidimensional interpolation + # interpolated_response_value = 0 + # fQ_flat = fQ.flatten('F')[::-1] - print(f'Multidimensional interpolated value: {interpolated_response_value}') + # for idx in range(2**self.ndim): + # weight = np.prod([1 - t[dim] if (idx >> dim) & 1 else t[dim] for dim in range(self.ndim)]) + # interpolated_response_value += fQ_flat[idx] * weight - # eps_centers = self.axes['eps'].centers - # print(x1, y1, eps_centers[yindex[0]]) - # print(x1, y2, eps_centers[yindex[1]]) - # print(x2, y1, eps_centers[yindex[0]]) - # print(x2, y2, eps_centers[yindex[1]]) - # print(fQ00, fQ01, fQ10, fQ11) - # print(fQ) - # print(xdist, ydist) - # print(dists) + # print(f'Multidimensional interpolated value: {interpolated_response_value}') - return interpolated_response_value \ No newline at end of file + # return interpolated_response_value \ No newline at end of file diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index cc244298..7c8f05e7 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -2,9 +2,265 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "                  available                                                                                        \n",
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+       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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+       "                  software installed and configured?                                                               \n",
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+       "                  software installed and configured?                                                               \n",
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         WARNING   No fermitools installed                                              lat_transient_builder.py:44\n",
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         WARNING   Env. variable OMP_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
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         WARNING   Env. variable MKL_NUM_THREADS is not set. Please set it to 1 for optimal         __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
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         WARNING   Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to 1 for optimal     __init__.py:387\n",
+       "                  performances in 3ML                                                                              \n",
+       "
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HealpixBase\n", "from scoords import Attitude, SpacecraftFrame\n", @@ -38,7 +294,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -56,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -69,7 +325,7 @@ " [0.89, 0.11, 0. , 0. , 0. ]])" ] }, - "execution_count": 75, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -99,7 +355,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -108,7 +364,7 @@ "array([1., 1., 1., 1., 1.])" ] }, - "execution_count": 76, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -119,7 +375,7 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -129,7 +385,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -163,7 +419,7 @@ " [0. , 0. , 0. , 0.11, 0.89]]])" ] }, - "execution_count": 77, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -179,17 +435,17 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 78, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -210,7 +466,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -220,7 +476,7 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -245,7 +501,7 @@ " [0. , 0.17, 0.66, 0.17, 0. ]])" ] }, - "execution_count": 88, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -279,16 +535,17 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ - "htransformed = Histogram([np.arange(4), np.arange(506, 517, 2)*u.keV, eps_col_edges], contents=np.stack([R, R, R]), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" + "NuLambdalen = 48\n", + "htransformed = Histogram([np.arange(NuLambdalen+1), np.arange(506, 517, 2)*u.keV, eps_col_edges], contents=np.tile(R, (NuLambdalen, 1, 1)), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" ] }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -298,23 +555,23 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 33, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -336,7 +593,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 79, "metadata": {}, "outputs": [], "source": [ @@ -357,7 +614,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -377,7 +634,7 @@ "" ] }, - "execution_count": 100, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } @@ -588,25 +845,25 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 73, "metadata": {}, "outputs": [], "source": [ - "mEq = HealpixBase(order=6, scheme='ring')" + "mEq = HealpixBase(order=1, scheme='ring')" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(6, 64, 49152)" + "(1, 2, 48)" ] }, - "execution_count": 6, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" } @@ -617,7 +874,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 75, "metadata": {}, "outputs": [], "source": [ @@ -629,19 +886,16 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([23200, 23455, 23456, 23711, 23712, 23713, 23966, 23967, 23968,\n", - " 23969, 24222, 24223, 24224, 24225, 24226, 24478, 24479, 24480,\n", - " 24481, 24734, 24735, 24736, 24737, 24738, 24990, 24991, 24992,\n", - " 24993, 25247, 25248, 25249, 25503, 25504, 25760])" + "array([], dtype=int64)" ] }, - "execution_count": 8, + "execution_count": 76, "metadata": {}, "output_type": "execute_result" } @@ -652,15 +906,15 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 77, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "NUNIQ pixels in MOC map: 114\n", - "Equivalent single-resolution pixels: 49152\n" + "NUNIQ pixels in MOC map: 12\n", + "Equivalent single-resolution pixels: 48\n" ] } ], @@ -681,113 +935,347 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ - "m.write_map('example.fits')" + "def HealpixBase_to_h5(m, hist, h5_file):\n", + " with h5py.File(h5_file, 'w') as hdf:\n", + " drm = hdf.create_group('DRM')\n", + " data = hist.contents\n", + " hdf['DRM'].attrs['UNIT'] = str(data.unit)\n", + " hdf['DRM'].attrs['SPARSE'] = False\n", + "\n", + " axis_grp = drm.create_group('AXES', track_order=True)\n", + "\n", + " axis = axis_grp.create_dataset('NuLambda', data=np.arange(m.npix+1))\n", + " axis.attrs['DESCRIPTION'] = 'Location of the simulated source in the spacecraft coordinates'\n", + " axis.attrs['NSIDE'] = m.nside\n", + " axis.attrs['SCHEME'] = m.scheme\n", + " axis.attrs['TYPE'] = 'healpix'\n", + "\n", + " axis = axis_grp.create_dataset('Ei', data=image_response.axes['Ei'])\n", + " axis.attrs['DESCRIPTION'] = 'Initial simulated energy'\n", + " axis.attrs['TYPE'] = 'linear'\n", + " axis.attrs['UNIT'] = str(hist.axes['Ei'].unit)\n", + "\n", + " axis = axis_grp.create_dataset('eps', data=image_response.axes['eps'])\n", + " axis.attrs['DESCRIPTION'] = 'Measured energy'\n", + " axis.attrs['TYPE'] = 'nonlinear'\n", + " axis.attrs['UNIT'] = ' '\n", + "\n", + " # axis = axis_grp.create_dataset('Phi', data=np.arange(m.npix))\n", + " # axis.attrs['DESCRIPTION'] = 'Compton angle'\n", + " # axis.attrs['TYPE'] = 'linear'\n", + " # axis.attrs['UNIT'] = str(hist.axes['Phi'].unit)\n", + "\n", + " # axis = axis_grp.create_dataset('PsiChi', data=np.arange(m.npix+1))\n", + " # axis.attrs['DESCRIPTION'] = 'Location in the Compton Data Space'\n", + " # axis.attrs['NSIDE'] = m.nside\n", + " # axis.attrs['SCHEME'] = m.scheme\n", + " # axis.attrs['TYPE'] = 'healpix'\n", + " \n", + " dset = drm.create_dataset('CONTENTS', data=data.value)\n", + "\n", + "# Example usage\n", + "HealpixBase_to_h5(mEq, image_response, 'example.h5')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load FullDetectorResponse" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "response_path = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def get_interp_response(self, coord):\n", + " pixels, weights = self.get_interp_weights(coord)\n", + " dr = ListModeResponse(self.axes[1:],\n", + " sparse=self._sparse,\n", + " unit=self.unit)\n", + " for p, w in zip(pixels, weights):\n", + " dr += self[p]*w\n", + "\n", + " return dr" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pixel 0 centered at \n" + ] + } + ], + "source": [ + "with FullDetectorResponse.open(response_path) as response:\n", + " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", + " dr = response[0]\n", + " data = response._file['DRM']['CONTENTS'][0]\n", + " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit) \n", + " dr = get_interp_response(response, SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "XTENSION= 'BINTABLE' / binary table extension \n", - "BITPIX = 8 / array data type \n", - "NAXIS = 2 / number of array dimensions \n", - "NAXIS1 = 16 / length of dimension 1 \n", - "NAXIS2 = 114 / length of dimension 2 \n", - "PCOUNT = 0 / number of group parameters \n", - "GCOUNT = 1 / number of groups \n", - "TFIELDS = 2 / number of table fields \n", - "TTYPE1 = 'UNIQ ' \n", - "TFORM1 = 'K ' \n", - "TTYPE2 = 'CONTENTS' \n", - "TFORM2 = 'D ' \n", - "PIXTYPE = 'HEALPIX ' / HEALPIX pixelisation \n", - "ORDERING= 'NUNIQ ' / Pixel ordering scheme: RING, NESTED, or NUNIQ \n", - "NSIDE = 64 / Resolution parameter of HEALPIX \n", - "INDXSCHM= 'EXPLICIT' / Indexing: IMPLICIT or EXPLICIT \n", - "MOCORDER= 6 / Best resolution order " + "(array([399, 368, 400, 401]),\n", + " array([0.05555556, 0.94444444, 0. , 0. ]))" ] }, - "execution_count": 12, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def fits_to_h5(fits_file, h5_file):\n", - " with fits.open(fits_file) as hdul:\n", - " header0 = hdul[0].header\n", - " header1 = hdul[1].header\n", - " \n", - " with h5py.File(h5_file, 'w') as hdf:\n", - " hdf.create_group('header0')\n", - " for key, value in header0.items():\n", - " hdf['header0'].attrs[key] = value\n", - " \n", - " hdf.create_group('header1')\n", - " for key, value in header1.items():\n", - " hdf['header1'].attrs[key] = value\n", - " \n", - " data = hdul[1].data\n", - " dset = hdf.create_dataset('data', data=data)\n", + "dr.axes['PsiChi'].interp_weights(SkyCoord(lon=5, lat=0, unit=u.deg, frame=SpacecraftFrame()))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$1.4900613 \\times 10^{-6} \\; \\mathrm{cm^{2}}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Ei0 = 511.*u.keV\n", + "Em0 = 600*u.keV\n", + "Phi0 = 12*u.deg\n", + "PsiChi0 = 386\n", + "interpolated_response_value = dr.get_interp_response({'Ei': Ei0, 'Em': Em0, 'Phi': Phi0, 'PsiChi': PsiChi0})\n", "\n", - "# Example usage\n", - "fits_to_h5('example.fits', 'example.h5')\n" + "interpolated_response_value" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "metadata": {}, "outputs": [ { - "ename": "ValueError", - "evalue": "Unsupported file format. Only .h5 and .rsp.gz extensions are supported.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mexample.fits\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:89\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n\u001b[1;32m 88\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 89\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 90\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnsupported file format. Only .h5 and .rsp.gz extensions are supported.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mValueError\u001b[0m: Unsupported file format. Only .h5 and .rsp.gz extensions are supported." - ] + "data": { + "text/plain": [ + "[,\n", + " ,\n", + " ,\n", + " array([386.5, 387.5, 418.5, 419.5])]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "FullDetectorResponse.open('example.fits')" + "dr.neighbors" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 8, "metadata": {}, "outputs": [ { - "ename": "OSError", - "evalue": "Unable to synchronously open file (file signature not found)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m 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554\u001b[0m locking, page_buf_size, min_meta_keep, min_raw_keep,\n\u001b[1;32m 555\u001b[0m alignment_threshold\u001b[38;5;241m=\u001b[39malignment_threshold,\n\u001b[1;32m 556\u001b[0m alignment_interval\u001b[38;5;241m=\u001b[39malignment_interval,\n\u001b[1;32m 557\u001b[0m meta_block_size\u001b[38;5;241m=\u001b[39mmeta_block_size,\n\u001b[1;32m 558\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[1;32m 559\u001b[0m fcpl \u001b[38;5;241m=\u001b[39m make_fcpl(track_order\u001b[38;5;241m=\u001b[39mtrack_order, fs_strategy\u001b[38;5;241m=\u001b[39mfs_strategy,\n\u001b[1;32m 560\u001b[0m fs_persist\u001b[38;5;241m=\u001b[39mfs_persist, fs_threshold\u001b[38;5;241m=\u001b[39mfs_threshold,\n\u001b[1;32m 561\u001b[0m fs_page_size\u001b[38;5;241m=\u001b[39mfs_page_size)\n\u001b[0;32m--> 562\u001b[0m fid \u001b[38;5;241m=\u001b[39m \u001b[43mmake_fid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m 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\u001b[38;5;241m|\u001b[39m\u001b[38;5;241m=\u001b[39m h5f\u001b[38;5;241m.\u001b[39mACC_SWMR_READ\n\u001b[0;32m--> 235\u001b[0m fid \u001b[38;5;241m=\u001b[39m \u001b[43mh5f\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 236\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr+\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 237\u001b[0m fid \u001b[38;5;241m=\u001b[39m h5f\u001b[38;5;241m.\u001b[39mopen(name, h5f\u001b[38;5;241m.\u001b[39mACC_RDWR, fapl\u001b[38;5;241m=\u001b[39mfapl)\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/h5f.pyx:102\u001b[0m, in \u001b[0;36mh5py.h5f.open\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mOSError\u001b[0m: Unable to synchronously open file (file signature not found)" + "data": { + "text/plain": [ + "(, )" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Ei0, dr.transform_Em_to_eps(Em0, Ei0)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([509.49 , 509.694, 509.898, 510.102, 510.306, 510.51 ])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "eps = np.linspace(-0.001, 0.001, 6)\n", + "(eps + 1) * 510" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "dr.project('Ei', 'Em').draw(ax=ax)\n", + "ax.scatter(Ei0, dr.transform_Em_to_eps(Em0, Ei0), marker='*')\n", + "for e1 in dr.neighbors[0]:\n", + " for e2 in dr.neighbors[1]:\n", + " ax.scatter(e1, dr.transform_Em_to_eps(e2, Ei0), c='r')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'_unit': Unit(\"keV\"), '_edges': array([1150., 1164.]), '_label': 'Ei', '_scale': 'log'}\n", + "{'_unit': Unit(\"keV\"), '_edges': array([1150., 1164.]), '_label': 'Em', '_scale': 'log'}\n", + "{'_unit': Unit(\"deg\"), '_edges': array([ 0., 3., 6., 9., 12., 15., 18., 21., 24., 27., 30.,\n", + " 33., 36., 39., 42., 45., 48., 51., 54., 57., 60., 63.,\n", + " 66., 69., 72., 75., 78., 81., 84., 87., 90., 93., 96.,\n", + " 99., 102., 105., 108., 111., 114., 117., 120., 123., 126., 129.,\n", + " 132., 135., 138., 141., 144., 147., 150., 153., 156., 159., 162.,\n", + " 165., 168., 171., 174., 177., 180.]), '_label': 'Phi', '_scale': 'linear'}\n" ] } ], "source": [ - "h5py.File('example.h5', mode='r')" + "with h5py.File('example.h5', mode='r') as file:\n", + "\n", + " drm = file['DRM']\n", + " unit = u.Unit(drm.attrs['UNIT'])\n", + " sparse = drm.attrs['SPARSE']\n", + "\n", + " # Axes\n", + " axes = []\n", + "\n", + " for axis_label in drm[\"AXES\"]:\n", + "\n", + " axis = drm['AXES'][axis_label]\n", + " axis_type = axis.attrs['TYPE']\n", + "\n", + " if axis_type == 'healpix':\n", + "\n", + " axes += [HealpixAxis(edges=np.array(axis),\n", + " nside=axis.attrs['NSIDE'],\n", + " label=axis_label,\n", + " scheme=axis.attrs['SCHEME'],\n", + " coordsys=SpacecraftFrame())]\n", + "\n", + " else:\n", + " axes += [Axis(np.array(axis) * u.Unit(axis.attrs['UNIT']),\n", + " scale=axis_type,\n", + " label=axis_label)]\n", + "\n", + " new_axes = Axes(axes)\n", + "\n", + " # Init HealpixMap (local coordinates, main axis)\n", + " HealpixBase.__init__(new,\n", + " base=axes['NuLambda'],\n", + " coordsys=SpacecraftFrame())" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "hf = h5py.File('example.h5', mode='r')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['BITPIX',\n", + " 'GCOUNT',\n", + " 'INDXSCHM',\n", + " 'MOCORDER',\n", + " 'NAXIS',\n", + " 'NAXIS1',\n", + " 'NAXIS2',\n", + " 'NSIDE',\n", + " 'ORDERING',\n", + " 'PCOUNT',\n", + " 'PIXTYPE',\n", + " 'TFIELDS',\n", + " 'TFORM1',\n", + " 'TFORM2',\n", + " 'TTYPE1',\n", + " 'TTYPE2',\n", + " 'XTENSION']" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(hf['header1'].attrs)" ] }, { From 4c231886371846c40274883c3d9a9eb4405083ab Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Thu, 7 Nov 2024 08:57:13 -0800 Subject: [PATCH 17/46] Modified code to accept len(dr.axes) or len(dr.axes)-1 number of inputs. Can also work with eps-to-Em mapping. Need to generalize --- cosipy/response/FullDetectorResponse.py | 10 +- cosipy/response/ListModeResponse.py | 206 +++----------- docs/tutorials/response/LMDR.ipynb | 345 +++++++++++++----------- 3 files changed, 227 insertions(+), 334 deletions(-) diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py index 71f4ffb9..36660f61 100644 --- a/cosipy/response/FullDetectorResponse.py +++ b/cosipy/response/FullDetectorResponse.py @@ -807,7 +807,7 @@ def filename(self): return Path(self._file.filename) - def get_interp_response(self, coord): + def get_interp_response(self, coord, unbinned=False): """ Get the bilinearly interpolated response at a given coordinate location. @@ -823,9 +823,13 @@ def get_interp_response(self, coord): pixels, weights = self.get_interp_weights(coord) - + if unbinned: + dr = ListModeResponse(self.axes[1:], + sparse=self._sparse, + unit=self.unit) - dr = DetectorResponse(self.axes[1:], + else: + dr = DetectorResponse(self.axes[1:], sparse=self._sparse, unit=self.unit) diff --git a/cosipy/response/ListModeResponse.py b/cosipy/response/ListModeResponse.py index 788b5e36..8baf5491 100644 --- a/cosipy/response/ListModeResponse.py +++ b/cosipy/response/ListModeResponse.py @@ -22,38 +22,15 @@ class ListModeResponse(Histogram): def __init__(self, *args, **kwargs): # Overload parent init. Called in class methods. super().__init__(*args, **kwargs) + self.mapping = {'Ei': 'Ei', 'Em': 'Em', 'Phi': 'Phi', 'PsiChi': 'PsiChi'} # key_target : label - def _get_nearest_neighbors(self, centers, target: dict): - """ - Given n-dimensional axes, identify the indices of the nearest neighbors. - Ensures there are at least 2 dimensions. - """ - if len(centers) < 2: - raise ValueError("At least 2 dimensions are required") - - if len(centers) != len(target): - raise ValueError("Dimensions of centers and target must be equal") - - indices = [] - for dim_centers, key_target in zip(centers, target): - dim_target = target[key_target] - dim_index = np.sort(np.argpartition(np.abs(dim_centers - dim_target), 1)[:2]).tolist() - indices.append(dim_index) - - # for i, dim_centers in enumerate(centers): - # print(f"Dimension {i} centers: {dim_centers}") - - # for i, dim_indices in enumerate(indices): - # print(f"Dimension {i} indices: {dim_indices}") - - return indices - def _get_all_interp_weights(self, target: dict): indices = [] weights = [] - for label in self.axes.labels: + for key in target: + label = self.mapping[key] axis = self.axes[label] axis_scale = axis._scale axis_type = str(type(axis)).split('.')[-1].strip("'>") # XXX: Could probably be simplified using `isinstance()` @@ -63,7 +40,13 @@ def _get_all_interp_weights(self, target: dict): # Axis Type if axis_type in ['Axis', 'HealpixAxis']: - idx, w = axis.interp_weights(target[label]) + if key == label: # If key and label are the same, then there was no reparametrization along this axis + idx, w = axis.interp_weights(target[key]) + else: + centers = self.transform_eps_to_Em(axis.centers, target['Ei']) # Transform coordinates to more physical units # TODO: Generalize this + absdiff = np.abs(centers - target[key]) # Calculate absolute difference to given target + idx = np.argpartition(absdiff, (1,2))[:2] # Find indices corresponding to two smallest absdiff + w = 1 - np.partition(absdiff, (1,2))[:2] / (centers[1] - centers[0]) # Calculate weights corresponding to two smallest absdiff else: raise ValueError(f'Axis type: {axis_type} is not supported') @@ -79,67 +62,23 @@ def _get_all_interp_weights(self, target: dict): return (indices, weights) def transform_eps_to_Em(self, eps, Ei0): - # return (eps + 1) * Ei0 - return eps + return (eps + 1) * Ei0 def transform_Em_to_eps(self, Em, Ei0): - # return Em/Ei0 - 1 - return Em - - def _create_nd_array(self): - shape = tuple([2] * self.ndim) - array = np.zeros(2**self.ndim).reshape(shape) - return array - - # def _standarize_theta_phi_lonlat(self, theta, phi, lonlat): - - # if isinstance(theta, (SkyCoord, BaseRepresentation)): - # # Support astropy - - # if isinstance(theta, SkyCoord): - - # if self.coordsys is None: - # raise ValueError("Undefined coordinate system") - - # theta = theta.transform_to(self.coordsys) + return Em/Ei0 - 1 + + def get_nearest_neighbors(self, target: dict, indices=None): + if indices is not None: + neighbors = {} + for idx, key in zip(indices, target): + label = self.mapping[key] + neighbors[label] = self.axes[label].centers[idx] + return neighbors - # coord = theta.represent_as(UnitSphericalRepresentation) - - # theta,phi = coord.lon.deg, coord.lat.deg - - # lonlat = True - - # return theta,phi,lonlat - - # def get_interp_weights(self, theta, phi = None, lonlat = False): - # """ - # Return the 4 closest pixels on the two rings above and below the - # location and corresponding weights. Weights are provided for bilinear - # interpolation along latitude and longitude - - # Args: - # theta (float or array): Zenith angle (rad) - # phi (float or array): Azimuth angle (rad) - - # Return: - # tuple: (pixels, weights), each with of (4,) if the input is scalar, - # if (4,N) where N is size of - # theta and phi. For MOC maps, these pixel numbers might repeate. - # """ - - # theta, phi, lonlat = self._standarize_theta_phi_lonlat(theta, phi, lonlat) - - # pixels,weights = hp.get_interp_weights(self.nside, theta, phi, - # nest = self.is_nested, - # lonlat = lonlat) - - # if self.is_moc: - # pixels = self.nest2pix(pixels) - - # return (pixels, weights) - - def get_neighbors(self, indices): - return [axis.centers[idx] for idx, axis in zip(indices, self.axes)] + else: + target = dict(sorted(target.items())) + indices, _ = self._get_all_interp_weights(target) + return self.get_nearest_neighbors(target, indices) def get_interp_response(self, target: dict): """ @@ -147,96 +86,25 @@ def get_interp_response(self, target: dict): and for a particular parametrization) TODO: In the future, this will also support nonlinear / piecewise-linear directional responses. - XXX: To get the correct interpolated response, ensure - all scales passed into this function are in linear scale """ - # centers = [] - # axis_types = [] - # for axis in self.axes.labels: - # scale = self.axes[axis]._scale - # print(scale) - # axis_type = str(type(self.axes[axis])).split('.')[-1].strip("'>") - # print(axis_type) - - # # Scale - # if scale in ['linear', 'log']: # To ensure nonlinear binning parametrizations are converted to a linear scale. - - # # Axis Type - # if axis_type == 'HealpixAxis': - # centers.append(self.axes[axis].centers) # TODO: HealpixAxis type? Will this be different? - # elif axis_type == 'Axis': - # centers.append(self.axes[axis].centers) - # else: - # raise ValueError(f'Axis type: {axis_type} is not supported') - - # elif scale == 'nonlinear': # XXX: For now, eps_to_Em is the only nonlinear transformation that has been implemented - # # This "nonlinear" transformation is still represented on a linear scale. So need to find a different attribute to use for `if <> == 'nonlinear'` comparison - # this_edges = self.transform_eps_to_Em(self.axes[axis].edges, target['Ei']) - # this_centers = (this_edges[:-1] + this_edges[1:]) / 2 - # centers.append(this_centers) - - # elif scale == 'log': - - # this_centers = np.log2(self.axes[axis].centers.value) # I chose log2 instead of ln as the former was used in `histpy.axis` too. Also see https://stackoverflow.com/questions/33809789/why-are-log2-and-log1p-so-much-faster-than-log-and-log10-in-numpy - # centers.append(this_centers) - - # else: - # raise ValueError(f'Scale: {scale} is not supported') - - # indices = self._get_nearest_neighbors(centers, target) + target = dict(sorted(target.items())) # Sort dictionary by key (XXX: assuming response matrix also sorts in the same way) indices, weights = self._get_all_interp_weights(target) perm_indices = list(itertools.product(*indices)) perm_weights = list(itertools.product(*weights)) - interpolated_response_value = 0 - for idx, w in zip(perm_indices, perm_weights): - interpolated_response_value += np.prod(w) * self.contents[idx] - - self.neighbors = self.get_neighbors(indices) - - return interpolated_response_value - - # interpolated_response_value = 0 - # for i, axis in enumerate(self.axes): - # for j, idx in enumerate(indices[i]): - # print(axis.centers[idx]) - # print(weights[i][j]) - # interpolated_response_value += weights[i][j] * axis.centers[idx] - - # return interpolated_response_value - - # # Initialize neighbors and dists - # neighbors = [centers[i][indices[i]] for i in range(self.ndim)] - # dists = [np.diff(neighbors[i]) for i in range(self.ndim)] # Only linear dimensions should be used to calculate distance measures. - - # # Assign to self.neighbors - # self.neighbors = neighbors - # # Convert indices to a numpy array - # indices = np.array(indices) + if len(target) == len(self.axes): + interpolated_response_value = 0 + for idx, w in zip(perm_indices, perm_weights): + interpolated_response_value += np.prod(w) * self.contents[idx] - # # Initialize fQ with zeros - # fQ = np.zeros(2 ** self.ndim) * self.contents.unit + else: + interpolated_response_value = np.zeros(len(self.axes['Ei']) - 1) * self.contents.unit # XXX: Assuming all measured variables require interpolation + for idx, w in zip(perm_indices, perm_weights): + i = (Ellipsis,) + idx # XXX: Assuming 'Ei' is the first index + interpolated_response_value += np.prod(w) * self.contents[i] + # raise NotImplementedError('Support for len(target) < len(axes) is yet to be implemented') - # # Generate permutations and fill fQ - # permutations = list(itertools.product(*indices)) - # for j, perm in enumerate(permutations): - # fQ[j] = self.contents[perm] - # # fQ = np.array([self.contents[perm] for perm in permutations]) - - # # Reshape fQ - # fQ = fQ.reshape([2] * self.ndim) + self.neighbors = self.get_nearest_neighbors(target, indices) - # t = np.where(dists == 0, 0, [(target[key] - neighbors[i][0]) / dists[i] for i, key in enumerate(target)]) - - # # Compute the bilinearly interpolated response value for multidimensional interpolation - # interpolated_response_value = 0 - # fQ_flat = fQ.flatten('F')[::-1] - - # for idx in range(2**self.ndim): - # weight = np.prod([1 - t[dim] if (idx >> dim) & 1 else t[dim] for dim in range(self.ndim)]) - # interpolated_response_value += fQ_flat[idx] * weight - - # print(f'Multidimensional interpolated value: {interpolated_response_value}') - - # return interpolated_response_value \ No newline at end of file + return interpolated_response_value \ No newline at end of file diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index 7c8f05e7..2b49e90d 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -8,12 +8,12 @@ { "data": { "text/html": [ - "
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        "                  available                                                                                        \n",
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"\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m \u001b[0m\u001b[1;31m to disable these messages, turn off start_warning in your config file\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=342799;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=480837;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#40\u001b\\\u001b[2m40\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m \u001b[0m\u001b[1;31m to disable these messages, turn off start_warning in your config file\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=307427;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=618788;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#40\u001b\\\u001b[2m40\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -125,7 +125,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m ROOT minimizer not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=1701;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=267384;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1345\u001b\\\u001b[2m1345\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m ROOT minimizer not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=864213;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=421570;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1345\u001b\\\u001b[2m1345\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -138,7 +138,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Multinest minimizer not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=890665;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=628443;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1357\u001b\\\u001b[2m1357\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Multinest minimizer not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=210882;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=965488;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1357\u001b\\\u001b[2m1357\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -151,7 +151,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m PyGMO is not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=920539;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=647324;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1369\u001b\\\u001b[2m1369\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m PyGMO is not available \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=429735;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=901689;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1369\u001b\\\u001b[2m1369\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -165,7 +165,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The cthreeML package is not installed. You will not be able to use plugins which \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=317547;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=465211;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#94\u001b\\\u001b[2m94\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The cthreeML package is not installed. You will not be able to use plugins which \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=57710;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=562527;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#94\u001b\\\u001b[2m94\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mrequire the C/C++ interface \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mcurrently HAWC\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -180,7 +180,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin HAWCLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=539489;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=281405;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin HAWCLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=836643;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=556220;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251msoftware installed and configured? \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -195,7 +195,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin FermiLATLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=836922;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=173475;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin FermiLATLike.py. Do you have the relative instrument \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=991549;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=752502;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251msoftware installed and configured? \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -209,7 +209,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=99576;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=321870;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n" + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=897889;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=235590;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, @@ -223,7 +223,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=385686;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=75517;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable OMP_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=80941;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=923015;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -238,7 +238,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=302704;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=293514;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=319401;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=721044;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -253,7 +253,7 @@ "\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=208978;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=198053;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=409889;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=56883;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -262,7 +262,8 @@ } ], "source": [ - "# %%capture\n", + "import itertools\n", + "\n", "import numpy as np\n", "import astropy.units as u\n", "from astropy.units import Quantity\n", @@ -294,7 +295,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 49, "metadata": {}, "outputs": [], "source": [ @@ -593,7 +594,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -602,7 +603,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -614,17 +615,9 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Bilinear interpolated value: 0.6300401095675922 cm2\n", - "Multidimensional interpolated value: 0.6300401095675922 cm2\n" - ] - }, { "data": { "text/latex": [ @@ -634,7 +627,7 @@ "" ] }, - "execution_count": 63, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -642,17 +635,19 @@ "source": [ "Ei0 = 511.1*u.keV\n", "Em0 = 511*u.keV\n", - "dr.get_interp_response({'Ei': Ei0, 'Em': Em0})" + "target = {'Ei': Ei0, 'Em': Em0}\n", + "dr.mapping['Em'] = 'eps'\n", + "dr.get_interp_response(target)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 33, "metadata": {}, "outputs": [ { "data": { - "image/png": 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RZFWCDFUWBmhVwr1z0BYsWAA/Pz8x3VggptFo4OLiYpCuUCjE56aMGjVK7+ewsDCEhITgww8/xPbt2zFu3Diz2m9LXINGRERE9crPzw9BQUHi58HpTeDeerOKigqDdK1WKz6Xon///mjWrBlOnDhhXqNtjCNoREREJJkAGXQWrkETJJRXqVTIy8szSFer1QBgNKh7mBYtWqCwsFByubrAETQiIiKSrEqQW+VTWwEBAbh27RpKSkr00tPT08XnUgiCgJs3b9rtsRsM0IiIiMjuhYWFoaqqCklJSWKaVqvF7t270b59e3EHZ25ursGu0IKCAoP6duzYgYKCAnTr1s2m7TYXpzgbkOKhHSAoPeu7GURENifjHdp2T4AMOqHupjjbt2+P8PBwrFmzBgUFBWjdujX27t2LmzdvYu7cuWK+xYsX4/Tp0zh8+LCYNmrUKPTp0wf+/v5QKBQ4e/YskpOTERgYqHeumj1hgEZERESS3TsHzcJdnBLXsM2fPx8+Pj7Yt28fiouL4e/vjyVLlqBjx441luvfvz/OnTuHlJQUaLVa+Pj4YOzYsXj99dfh6upqwRvYDgM0IiIiahCUSiWmTJmCKVOmmMyzYsUKg7Q5c+bYslk2wQCNiIiIJLt3F6eFU5wWlndkDNCIiIhIMh3k0Fk4xWlpeUfGniEiIiKyMxxBIyIiIsl0wr3rniytg4xzqABNq9Vi3bp12L9/P4qKitCuXTtMmDABXbp0eWjZvLw8rFy5EsePH4dOp0OnTp0wffp0tGrVyiDvzp07sWXLFty8eRPNmzfHyJEjMWLEiBrrnzVrFn777TdERUVh5syZZr8jERGRPdBZYQ2apeUdmUNNccbGxiIhIQH9+/fHW2+9Bblcjjlz5iA1NbXGcqWlpZgxYwZOnz6NcePGYfz48cjMzMT06dNx9+5dvbyJiYn4+OOP8cQTT2DGjBl4+umnERcXh2+//dZk/SkpKUhLS7PKOxIREdkDnSC3yoeMc5gRtPT0dCQnJ2Py5MkYO3YsAGDgwIGIjo5GfHw84uPjTZbdsWMHrl27htWrVyMkJAQA0K1bN0RHR2Pr1q2YOHEiAECj0eDLL79E9+7d8eGHHwIAIiIioNPpsHHjRkRGRqJJkyZ6dWs0Gnz++ed45ZVXsG7dOlu8OhERETkYhwldU1JS4OTkpHcisFKpxJAhQ5CWlobc3FyTZQ8dOoTg4GAxOAMAPz8/dO7cGQcPHhTTTp48ibt372L48OF65aOiolBWVoajR48a1L1582YIgoAxY8ZY8HZERET2RQfZ/w6rNf9j6WXrjsxhArTMzEz4+vrC3d1dL7066MrKyjJaTqfT4dKlSwgODjZ4FhISgpycHJSWlorfAcAgb1BQEORyOS5evKiXnpubi2+//RZ/+ctfoFQqa/0u+fn5yMjIED8P3ilGRERU33TC/1+HZv6nvt/CfjnMFKdarYZKpTJIr07Lz883Wq6wsBBarfahZR9//HGo1Wo4OTnBy8tLL5+Liws8PDygVqv10j///HMEBgaib9++kt4lKSkJGzZskFSGiIiIHIfDBGgajQYuLi4G6QqFQnxuqhyAWpXVaDRwdjbeZQqFQu87Tp48iZSUFKxatUrCW9wTGRmJHj16iD9nZ2dj0aJFkushIiKyFQGWL/IXHGciz+ocJkBTKpWoqKgwSNdqteJzU+UA1KqsUqlEZWWl0Xq0Wq2Yr7KyEnFxcRgwYIDeurba8vb2hre3t+RyREREdUVnhTVkXINmmsOEriqVymCKEYCYZirg8fDwgEKhqFVZlUqFqqoq3LlzRy9fRUUFCgsLxSnRffv24erVq4iMjMSNGzfED3DvSI8bN26gvLzczDclIiIiR+cwI2gBAQE4deoUSkpK9DYKpKeni8+Nkcvl8Pf3x4ULFwyepaeno1WrVnBzcwMABAYGAgAuXLiA7t27i/kuXLgAnU4nPs/NzUVlZSWmTp1qUOe+ffuwb98+LF68GL169TLzbYmIiOqXTpBZ4SYBjqCZ4jABWlhYGLZs2YKkpCTxHDStVovdu3ejffv28PHxAXAveCovL4efn59YNjQ0FKtXr8aFCxfEHZpXrlzBqVOnMHr0aDFf586d4eHhgcTERL0ALTExEa6urmJa3759xWDtfn/729/wwgsvICIiwqypTyIiIntxbxemhZelM0AzyWECtPbt2yM8PBxr1qxBQUEBWrdujb179+LmzZuYO3eumG/x4sU4ffo0Dh8+LKZFRUVh586dmDt3LsaMGQMnJyckJCTAy8tL7/wypVKJN998E8uWLcP777+Prl274syZM9i/fz9iYmLg4eEB4N4ZavcHgPdr2bIlR86IiIioRg4ToAHA/Pnz4ePjg3379qG4uBj+/v5YsmQJOnbsWGM5Nzc3xMXFYeXKldi4caN4F+e0adPg6emplzcqKgrOzs7YunUrfv75Z7Ro0QLTpk3DqFGjbPdiREREdoZ3cdqWTBAEHhNn5zIyMhATEwNN6zAISs/6bg4Rkc3JdPXdgobr2MZZNq2/+neSzww/KHxdLapLe60cuXHZWLt2LYKCgqzUQsfgUCNoREREVDc4gmZbDnPMBhEREZGj4AgaERERSSbA8l2cAg+qNYkBGhEREUnGKU7b4hQnERERkZ3hCBoRERFJxrs4bYsBGhEREUkmWGGKU+AUp0mc4iQiIiKyMxxBIyIiIsl0guWL/HU8Kt8kBmhEREQkGac4bYtTnERERER2hiNoREREJJkOMsgsneLkLk6TGKARERGRZDrIIOMxGzbDAI2IiIgk4xo02+IaNCIiIiI7wxE0IiIikkwnyADexWkzDNCIiIhIMsEK56AJPAfNJE5xEhEREdkZjqARERGRZDrB8mM2uEnANAZoREREJJkAy9egCTxmwyROcRIRERHZGY6gERERkWQCZFYYAeMImikM0IiIiEgyaxyzAUHGqTwT2C9EREREdoYjaERERCSZIMAKI2hWaYpDYoBGREREkllritPJOs1xOAzQiIiISDpBZvE5Zpaeo+bIuAaNiIiIyM5wBI2IiIgk08EKI2g8ZsMkjqARERGRZIJgnY8UWq0W8fHxiIqKQr9+/TBp0iQcP35ccttnzZqF3r17Y9myZZLL1hUGaERERNQgxMbGIiEhAf3798dbb70FuVyOOXPmIDU1tdZ1pKSkIC0tzYattA4GaERERCSZABl0Fn6k3ESQnp6O5ORkTJw4EVOmTEFkZCSWL1+Oxx57DPHx8bWqQ6PR4PPPP8crr7xi7mvXGQZoREREJNm9KUqZhZ/af19KSgqcnJwQGRkppimVSgwZMgRpaWnIzc19aB2bN2+GIAgYM2aMOa9cp7hJgIiIiOpVdna23s8qlQre3t56aZmZmfD19YW7u7teekhICAAgKysLPj4+Jr8jNzcX3377Ld59910olUortdx2GKARERGRZDpBdu+wWkv8r/yiRYv0kqOjozF+/Hi9NLVaDZVKZVBFdVp+fn6NX/X5558jMDAQffv2taTFdcahAjStVot169Zh//79KCoqQrt27TBhwgR06dLloWXz8vKwcuVKHD9+HDqdDp06dcL06dPRqlUrg7w7d+7Eli1bcPPmTTRv3hwjR47EiBEj9PKkpKTgxx9/xIULF3D79m20aNEC3bt3x5///Gc0adLEau9MRERUH8zZhWmsDgBYsGAB/Pz8xHRjgZhGo4GLi4tBukKhEJ+bcvLkSaSkpGDVqlWWNbgOOVSAFhsbi0OHDmHUqFHw9fXFnj17MGfOHMTFxaFDhw4my5WWlmLGjBkoKSnBuHHj4OzsjISEBEyfPh3r169H06ZNxbyJiYn417/+hdDQUIwePRqpqamIi4tDeXk5Xn31VTHf0qVLoVKpMGDAAPj4+OD333/H9u3b8d///hfr1q1rEMOrREREdcHPzw9BQUE15lEqlaioqDBI12q14nNjKisrERcXhwEDBojToQ2BwwRo1bs7Jk+ejLFjxwIABg4ciOjoaMTHx9e4w2PHjh24du0aVq9eLf6f161bN0RHR2Pr1q2YOHEigHvR+Zdffonu3bvjww8/BABERERAp9Nh48aNiIyMFEfHFi5ciE6dOul9T1BQED766CMcOHAAQ4cOtXofEBER1R3LD6qFhF2cKpUKeXl5BulqtRoADNasVdu3bx+uXr2K2bNn48aNG3rPSktLcePGDXh5ecHV1VVCu23PYXZxWrK749ChQwgODtaLrP38/NC5c2ccPHhQTDt58iTu3r2L4cOH65WPiopCWVkZjh49KqY9GJwBQO/evQEAly9flvp6REREdsXyHZzSAryAgABcu3YNJSUleunp6enic2Nyc3NRWVmJqVOnYvTo0eIHuBe8jR492qzDbm3NYUbQzN3dodPpcOnSJbz00ksGz0JCQnD8+HGUlpbCzc0NmZmZAIDg4GC9fEFBQZDL5bh48SIGDBhgso3VUb6np6ekdyMiIrI31tgkIOWy9LCwMGzZsgVJSUniTJlWq8Xu3bvRvn178Xd8bm4uysvLxTVtffv2RWBgoEF9f/vb3/DCCy8gIiLCLqc+HSZAM3d3R2FhIbRa7UPLPv7441Cr1XBycoKXl5dePhcXF3h4eIgBmCn//ve/4eTkhNDQ0Brz5efn69X14PZjIiKiR0379u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHwZwb0bs/g0I92vZsiV69epVJ+2XymECNHN3d1Sn16asRqOBs7PxLlMoFDXuIDlw4AB27dqFsWPHok2bNjW8CZCUlIQNGzbUmIeIiKg+WXMXZ23Nnz8fPj4+2LdvH4qLi+Hv748lS5agY8eOljXEDjlMgGbu7o7q9NqUVSqVqKysNFqPVqs1+R1nzpzBkiVL0LVrV8TExDzkTYDIyEj06NFD/Dk7O9vgjBgiIqJ69b+bBCytQwqlUokpU6ZgypQpJvOsWLGiVnVVj7DZK4cJ0Mzd3eHh4QGFQmF0evLBsiqVClVVVbhz547eNGdFRQUKCwuNTpNmZWVh3rx58Pf3x8KFC02OwN3P29vbZHuJiIjI8TnMLk5zd3fI5XL4+/vjwoULBs/S09PRqlUruLm5AYC4yPDBvBcuXIBOpzNYhJiTk4PZs2fDy8sLH3/8sVgPERFRQyfACrs4JRyz8ahxmAAtLCwMVVVVSEpKEtNM7e54cNF9aGgoLly4oBd4XblyBadOnUJYWJiY1rlzZ3h4eCAxMVGvfGJiIlxdXdG9e3cxTa1W4+2334ZcLsfSpUu5c5OIiByKYKUPGecwU5zm7u4A7p1jtnPnTsydOxdjxoyBk5MTEhIS4OXlpXfjvVKpxJtvvolly5bh/fffR9euXXHmzBns378fMTEx8PDwEPO+8847uH79OsaOHYuzZ8/i7Nmz4jMvL69aXT9FREREjyaHCdAA83d3uLm5IS4uDitXrsTGjRvFuzinTZtmMPIVFRUFZ2dnbN26FT///DNatGiBadOmYdSoUXr5srKyAACbN282+L6OHTsyQCMiogZN6kGzpuog42SCYOkmWbK1jIwMxMTEQNM6DILSs76bQ0RkczJdfbeg4Tq2cZZN66/+nZQ/phsqW3g8vEANnG8VwnvLMaxdu/ahd3E+ahxqBI2IiIjqBkfQbMthNgkQEREROQqOoBEREZF0VrhJgNs4TWOARkRERJJVn4NmaR1kHAO0BmTNtM0I8NfWdzOIiGyukcz41XlUG7bdJEB1gwEaERERSScAqOO7OB8lDNCIiIhIMsEKa9B40Jdp3MVJREREZGc4gkZERETSWeMyTY6gmcQAjYiIiCTjQbW2xSlOIiIiIjvDETQiIiIyD6cobYYBGhEREUnGKU7bYoBGRERE0nGTgE1xDRoRERGRneEIGhEREZlB9r+PpXWQMQzQiIiISDpOcdoUAzQiIiKih9i7d6/FdQQGBqJdu3a1yssAjYiIiKR7xEbQYmNjIZOZNyUrCAJkMhmio6MZoBEREZENCbJ7H0vraEB69OiBnj17mlX2n//8p6T8DNCIiIiIaiEwMBCDBw82qywDNCIiIqoTQgOaorRUnz598MQTT9RZeQZoREREJN0jtgbtgw8+qNPyPKiWiIiIyM5wBI2IiIikE2CFTQJWaYlD4ggaERERSScAMgs/DTVAU6vVSElJwZEjR1BUVGQy3+nTp7FhwwazvoMjaERERCTdI7YGrdqWLVvw5ZdforKyEgCgUCjw2muvYdy4cQbnpJ06dQpff/01oqOjJX8PR9CIiIiIauHXX39FfHw8FAoFhg4diuHDh8PNzQ3r1q3Du+++C61Wa7XvsmgETafTQS7Xj/HOnTuHo0ePQqFQYPDgwWjRooVFDSQiIiJ7ZIWDahvYZenfffcdXF1dsXr1arRp0wYAMHHiRCxduhTJycl49913ERsbC6VSafF3mT2C9tlnn2HAgAF6c6+HDh3C9OnT8c0332D9+vWYMGECbt26ZXEjiYiIyM4IVvo0IBcuXEDv3r3F4AwA3Nzc8P777+OVV17BiRMn8O6770Kj0Vj8XWYHaKdOnUKnTp3QpEkTMW3dunVwd3fH3/72N/zlL39BUVERtmzZYnEjiYiIiOpbWVmZyZnBSZMm4bXXXsPJkycxd+5ci4M0s6c4b926hWeffVb8+fr167hy5Qqio6MxYMAAAEBqaip+/fVXixpIREREdugR3CTg7e2NvLw8k88nTJgAANi0aRPmzJmDoKAgs7/L7ACtvLwcjRo1En8+c+YMZDIZunXrJqa1bdsWJ0+eNLtxREREZKcewQDtiSeewIkTJ2rMc3+Qdu7cObO/y+wpTpVKhStXrog/Hzt2DI0aNdKLFktKSuDi4mJ244iIiIjsRffu3ZGfn4+jR4/WmG/ChAl4/fXXxaM4zGH2CFrHjh2RnJyMbdu2QalU4vDhw+jVqxecnJzEPNevX0fz5s3NbhwRERHZKcEKuzgt3gVat8LCwiAIAlxdXR+a980330SrVq1w8+ZNs77L7ADttddew08//YTPPvtMbOwbb7whPi8tLcWZM2cwePBgc7+CiIiI7JQM/7sNwMI6GhIPDw8MGzas1vktiYHMDtB8fX2xceNGpKSkAAB69OiBxx57THx+9epVREZGol+/fmY3TiqtVot169Zh//79KCoqQrt27TBhwgR06dLloWXz8vKwcuVKHD9+HDqdDp06dcL06dPRqlUrg7w7d+7Eli1bcPPmTTRv3hwjR47EiBEjLKqTHkFVAuTHNJDlVkHwcYKumxJwamj/uaon7DsicnAWHVTr7e1tNDABgKCgIIt2L5gjNjYWhw4dwqhRo+Dr64s9e/Zgzpw5iIuLQ4cOHUyWKy0txYwZM1BSUoJx48bB2dkZCQkJmD59OtavX4+mTZuKeRMTE/Gvf/0LoaGhGD16NFJTUxEXF4fy8nK8+uqrZtVJjx6n3aVQvHcH8htVYpqupRO0H3qh6iW3emyZ/WPfEdmJR3CTgDGZmZnIysqCWq02uuZMJpPhz3/+s+R6rXIX5927d5GVlYWSkhK4u7sjICCgzgOQ9PR0JCcnY/LkyRg7diwAYODAgYiOjkZ8fDzi4+NNlt2xYweuXbuG1atXIyQkBADQrVs3REdHY+vWrZg4cSIAQKPR4Msvv0T37t3x4YcfAgAiIiKg0+mwceNGREZGiufC1bZOevQ47S6FMibf4D9MsptVUMbkQ7PWm4GGCew7IrIXd+7cwcKFC3Hq1CkAgCAYjzbrJUC7ceMGVqxYgf/+9796DZPJZOjevTumT5+Oli1bWvIVtZaSkgInJydERkaKaUqlEkOGDMGaNWuQm5sLHx8fo2UPHTqE4OBgMZACAD8/P3Tu3BkHDx4Ug6mTJ0/i7t27GD58uF75qKgoHDhwAEePHhXPgKttnfSIqRKgeO8OIBiuvZAJ99bLKt6/g7KBjThl9yD2HZFdkQlWWIPWgEfQli1bhpMnT+KFF15A3759oVKp9DZKWsrsAC0nJwdTp07FnTt34Ovri2eeeQZeXl64c+cOzp07h59//hnp6en44osv6mTNVWZmJnx9feHu7q6XXh0gZWVlGQ3QdDodLl26hJdeesngWUhICI4fP47S0lK4ubkhMzMTABAcHKyXLygoCHK5HBcvXsSAAQMk1WlMfn4+1Gq1+HN2dvZD3p4aCvkxjd7U3INkAiC7XgX5MQ10Lz58l9CjhH1HRPbk119/RadOnbBkyRKb1G92gLZq1SoUFBTg7bffRkREBGSy//83VkEQkJSUhGXLlmHVqlVYuHChVRpbE7VaDZVKZZBenZafn2+0XGFhIbRa7UPLPv7441Cr1XBycoKXl5dePhcXF3h4eIhBlZQ6jUlKSsKGDRtMvCk1ZLJc0wGGOfnsmSAAt35/Ei3aXYTMCgNaj1LfETUIj+AxG/dzdna26Vp7swO0EydOoEePHnpTitVkMhmGDRuG//73v/jtt98samBtaTQao4fiKhQK8bmpcgBqVVaj0cDZ2XiXKRQKvXy1rdOYyMhI9OjRQ/w5OzsbixYtMpmfGg7Bp3bD37XNZ89uXHgKKV9OR2jMCrQKTre4vkep74gahHrYJGDuaQ2HDx9GYmIiLl26hMLCQnh6eqJ9+/Z444034O/vb1bTO3ToIM6s2YLZNwnodDq0bdu2xjz+/v7Q6XTmfoUkSqUSFRUVBularVZ8bqocgFqVVSqVJk8F1mq1evlqW6cx3t7e4i7YoKAg+Pn5mcxLDYuumxK6lk4m/9IoyABdq/8dG9HAXU3tfO9/z3S2Sn2PUt8RkXGxsbFISEhA//798dZbb0Eul2POnDlITU2tsdylS5fQpEkTjBw5EjNnzsSwYcOQmZmJSZMmISsry6y2TJw4ERkZGdi2bZtZ5R/G7BG0J598EpcvX64xzx9//FFnR22oVCqjF5hWTzt6e3sbLefh4QGFQqG35stUWZVKhaqqKty5c0dvmrOiogKFhYXi9KWUOukR4ySD9kMvKGPyIcj0F8hWBx7ahV4NcpG7oJMh85feqCi/t7byyv8Cs6upndFYde/PvYtrKQJfPAyZ3Iy/djtw3xE1WHW4yN+S0xqio6MN0oYOHYoRI0Zgx44dmD17tuT2tG3bFitXrsS0adOwbds2tGvXzmAdfLV3331Xcv1mB2gxMTGYOXMmdu7ciaFDhxo8T0pKwq+//oply5aZ+xWSBAQE4NSpU+JRH9XS09PF58bI5XL4+/vjwoULBs/S09PRqlUrcTF/YGAgAODChQvo3r27mO/ChQvQ6XTicyl10qOn6iU3aNZ6Q/HeHcjuW/QutHSCdmHDPcurUqvA2X2R0Ja6AxAgk+v+l65E6p5IADIo3ErwxPP/hYur6Sn+mjhq3xE1RHW9i9OS0xqM8fLygqurK4qLi6U0WXT9+nXMnz8fxcXFKC4uRk5OjtF8MpmsbgO0EydOoFOnTli6dCm2bNmCZ555Bs2aNcPt27dx9uxZXLt2DV26dMGJEyf0bn439zyQhwkLC8OWLVuQlJQkRtZarRa7d+9G+/btxf/TcnNzUV5erjdtGBoaitWrV+PChQviDs0rV67g1KlTGD16tJivc+fO8PDwQGJiol6AlpiYCFdXV7202tZJj6aql9xQNrCRQ52G7+KqwaBZi/DLN28i/3I7CLp7a8Hu/a8A77ZZeHHcOrODs2qO2HdEj7oHTytQqVQGM03mntZwv6KiIlRVVUGtVuO7775DSUkJnnvuObPaHBcXh+vXr2PYsGHo16+f/Ryz8dVXX4n/fPXqVVy9etUgz6+//opff/1VL81WAVr79u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHxbToqKisHPnTsydOxdjxoyBk5MTEhIS4OXlhTFjxoj5lEol3nzzTSxbtgzvv/8+unbtijNnzmD//v2IiYmBh4eH5DrpEeYkc7jjINy97qDP5GXY9t6nqNL+/7VgTgot+k75FHInK61JdcC+I2pwrLhJ4MGNcNHR0Rg/frxemrmnNdxv8uTJuHLlCgCgUaNGeP311zFkyBBzWo4zZ87gxRdfxKxZs8wq/zBmB2hxcXHWbIdVzJ8/Hz4+Pti3bx+Ki4vh7++PJUuWoGPHjjWWc3NzQ1xcHFauXImNGzeK92ZOmzYNnp6eenmjoqLg7OyMrVu34ueff0aLFi0wbdo0jBo1yuw6iRzJ7Stt9YIzAKjSKqG+8gSaP/F7PbWKiKzOigHaggUL9Ga2jAVi5p7WcL93330XpaWluH79Onbv3g2NRgOdTge5XPqeSRcXF7Rp00ZyudoyO0B7WNBTH5RKJaZMmYIpU6aYzLNixQqj6S1atKj1eW0RERGIiIh4aD4pdRI5ipz0e/fe+j59Ch0jtuHUf0Yi51xH5KR1YIBGREb5+fk9dFOhuac13O/pp58W/7lv37547bXXAABTp06V0lwAQJcuXXDu3DnJ5WrL7GM2AKCyshIJCQmYOHEiBg0ahPDwcPFZZmYmPv30U6NTn0TkuFo/lYrur65Dz+jVaOKdj17Rq9D91XVo/VTN2+CJqGGp3iRg6ae2VCqVVU9HaNKkCTp37owDBw5IKldtypQpUKvV+OKLL2o1eieV2SNoGo0Gb7/9Ns6dO4emTZvC3d0d5eXl4vOWLVti9+7daNKkCWJiYqzSWCKyf82f+F1vpEwmA9p2Pl6PLSIi27DCTQIGN+uaZu5pDTXRaDQoKSmRXA4APvzwQzRu3BgJCQn4z3/+A19fX6MnNMhkMixfvlxy/WaPoG3atAlnz57FxIkTsWPHDoNFdo0bN0bHjh1x/Dj/w0xERORwBCt9aiksLAxVVVVISkoS00yd1vDgrtA7d+4Y1Hfjxg2cOHHC7PNaT58+jaysLAiCgNLSUly8eBGnT582+jGH2SNoP/74Izp16oRXXnkFAPTu4qzWqlUrm16DQERERI8GS05riI6OxnPPPYeAgAA0adIE165dw65du1BZWYlJkyaZ1Z6UlBSL36kmZgdot27dQq9evWrM06hRI7OHDomIiMiOWeGgWqm7QM09raH6fvBjx46htLQUXl5e6NKlC8aNG4d27dqZ334bMjtAa9SoEQoKCmrMc/36dTRt2tTcryAiIiJ7VQ+XpZt7WsP48eMNzlWzVFVVFcrLy9GoUSOjx3RUP3d1dTXrAFuz16A99dRT+OWXX1BUVGT0eW5uLv773//i2WefNfcriIiIiOzShg0bMGzYMBQWFhp9XlRUhGHDhmHTpk1m1W92gDZmzBgUFRVh5syZOHv2LKqq7t2LV15ejhMnTmD27NmoqqritUZEREQOqK6P2bA3v/zyCzp37mzy8HlPT088//zzOHLkiFn1W3RQ7V//+lesWLEC06dPF9MHDRoE4N6F4bNmzTJ7dwQRERHZuQYcYFnqxo0b6NSpU4152rRpg7Nnz5pVv9kBGgAMHz4cHTt2RGJiIs6fP4/CwkK4u7sjJCQEUVFReOKJJyypnoiIiMguVVZWPvSKKJlMJt50IJVFARoAtG3bFjNmzLC0GiIiImpI6mGTgD1p3bo1Tp48WWOekydPomXLlmbVb9FVT0RERPRoetTXoPXu3RtZWVlYt26duA6/WlVVFb788ktkZWUhLCzMrPotHkEjIiIietSMHj0aycnJ2LRpE5KTk9GpUyc0b94ceXl5OHXqFK5fvw4/Pz+MGTPGrPoZoBERERFJ5ObmhpUrV+Jf//oXfvrpJ+Tk5IjP5HI5QkNDMWvWLKP3c9YGAzQiIiKS7hFfgwbcO0rjww8/xO3bt5GRkYHi4mI0btwYwcHB8PLysqhuBmhEREQkmTXWkDXkNWj3a9asGbp3727VOrlJgIiIiOghFi5caNEF6VLLM0AjIiIi8wgWfhqQ5ORk/PHHH3VWnlOcREREJN0juAYtMzMTe/furZPvYoBGREREVAtHjhzBzz//LLmcIEiPRBmgERERkWSP2iaBd9991+I6AgMDa52XARoRERFJ94hNcQ4ePLhOv4+bBIiIiIjsDEfQiIiISDpr3KXZgEbQ6hoDNCIiIjIPAyyb4RQnERERkZ3hCBoRERFJ94htEqhrDNCIiIhIskftmI26xgCtAZm4ciwEpWd9N4OIyOZkuvpuQcN1bGMdfRFH0GyKa9CIiIiI7AxH0IiIiEg6jqDZFAM0IiIikkwGK6xBs0pLHBOnOImIiIjsDEfQiIiISDpOcdoUAzQiIiKSjMds2JbDBGhFRUVYtWoVDh8+DI1Gg5CQEEyZMgVBQUG1Kn/58mWsXLkSZ8+ehbOzM7p3745p06bB09NTL59Op8OWLVuwY8cO3L59G76+vhg3bhz69eunl2ffvn1ISUlBZmYmioqK0LJlS/Tp0wdjxoyBUqm05qsTERGRg3GIAE2n02Hu3Ln4/fffMWbMGDRt2hQ7duzAjBkzsHbtWrRp06bG8rdu3cL06dPRuHFjxMTEoKysDFu2bMGlS5ewevVquLi4iHnXrl2Lb7/9FhEREQgODsaRI0ewcOFCyGQy9O3bFwBQXl6O2NhYPPXUUxg2bBi8vLyQlpaGr776CidPnsTy5cshk3FpJBERNWCc4rQphwjQDh06hHPnzmHhwoUICwsDAPTp0wevvPIKvvrqK7z//vs1lv/mm29QXl6OL7/8Ej4+PgCAkJAQzJo1C3v27EFkZCQAIC8vD1u3bkVUVBRmzpwJABg6dCimT5+OL774AmFhYXBycoKLiws+//xzPPPMM+J3RERE4LHHHsP69etx4sQJPP/88zboCSIiojrCAM2mHGIXZ0pKCpo1a4bevXuLaZ6enggPD8eRI0eg1WofWv7FF18UgzMAeP7559GmTRscPHhQTDty5AgqKysRFRUlpslkMgwfPhx5eXlIS0sDALi4uOgFZ9V69eoFAMjOzjbvRYmIiOiR4BAB2sWLFxEYGAi5XP91QkJCUF5ejqtXr5osm5eXhzt37hhdqxYSEoLMzEzx58zMTDRq1Ah+fn4G+aqf1+T27dsAgKZNm9aYLz8/HxkZGeKHAR0REdkbmZU+ZJxDTHHevn0bzz77rEG6SqUCAKjVarRr185oWbVarZf3wfKFhYXQarVQKBRQq9Xw8vIyWD9WXTY/P7/Gdm7evBnu7u7o1q1bjfmSkpKwYcOGGvMQERHVO05R2ozdBWg6nQ4VFRW1yqtQKCCTyaDRaKBQKIw+BwCNRmOyjupn928EMFZeoVBAo9E8NJ8pmzZtwm+//YZZs2ahSZMmNbwVEBkZiR49eog/Z2dnY9GiRTWWISIiqlNWOGaDAZ5pdhegnTlzBjNmzKhV3k2bNsHPzw9KpdLoOrPqtJqOtah+ZiwofLC8UqmsVb4HJScn48svv8SQIUMwfPjwGt7oHm9vb3h7ez80HxERETkmuwvQHn/8ccybN69WeaunFps1ayZOVd6vpunLB+swVd7Dw0McIVOpVDh16hQEQdCb5qwuayyoOn78OD766CN0794db7/9dq3ei4iIyO5xF6dN2V2AplKpMHjwYEllAgMDkZqaCp1Op7dR4Pz583B1da3xHLTmzZvD09MTGRkZBs/Onz+PgIAA8eeAgADs3LkT2dnZaNu2rZienp4uPr9feno6FixYgKCgIPzjH/+As7PddTcREZF5GKDZlEPs4gwNDcXt27dx+PBhMa2goAAHDx7Eiy++qLc+LScnBzk5OQblf/nlF+Tm5oppJ06cwNWrVxEeHi6m9ezZE87Ozti+fbuYJggCEhMT0bx5czz99NNi+uXLlzF37lw89thjWLJkCW8PICIiolpziCGdsLAwfP/994iNjcXly5fFmwR0Oh3Gjx+vl7f6gNmEhAQxbdy4cTh06BD++te/YuTIkSgrK8PmzZvh7++vN5rXokULjBo1Cps3b0ZlZSVCQkLw008/ITU1Fe+99x6cnJwAAKWlpZg9ezaKioowZswYHD16VK8NrVq10gvmiIiIGhrexWlbDhGgOTk54eOPP8YXX3yBbdu2QaPRIDg4GPPmzcPjjz/+0PI+Pj5YsWIFVq5cidWrV4t3cU6dOtVgd+ikSZPQpEkTJCUlYe/evfD19cWCBQvQv39/Mc/du3dx69YtAMDq1asNvm/QoEEM0IiIqGHjFKdNyQRBYPfYuYyMDMTExEDTOgyC0rO+m0NEZHMyXX23oOE6tnGWTeuv/p1UHBAOnZunRXXJSwvQOOsg1q5da/TA+EeZQ4ygERERUd2SwQpTnFZpiWNigEZERETScYrTphxiFycRERGRI+EIGhEREUnGXZy2xQCNiIiIpKuHKU6tVot169Zh//79KCoqQrt27TBhwgR06dKlxnIpKSn48ccfceHCBdy+fRstWrRA9+7d8ec///mh92PXF05xEhERkXSClT4SxMbGIiEhAf3798dbb70FuVyOOXPmIDU1tcZyS5cuRXZ2NgYMGIAZM2aga9eu2L59OyZPngyNRiOtEXWEI2hERERk99LT05GcnIzJkydj7NixAICBAwciOjoa8fHxiI+PN1l24cKF6NSpk15aUFAQPvroIxw4cABDhw61advNwRE0IiIikqz6mA2LPhK+LyUlBU5OToiMjBTTlEolhgwZgrS0NL3rGh/0YHAGAL179wZw72pGe8QAjYiIiKSr4ynOzMxM+Pr6wt3dXS89JCQEAJCVlSWp+Wq1GgDg6ekpqVxd4RQnERER1avs7Gy9n1UqFby9vfXS1Go1VCqVQdnqtPz8fEnf+e9//xtOTk4IDQ2V2Nq6wQCNiIiIpBMEyCy9LfJ/5RctWqSXHB0djfHjx+ulaTQauLi4GFRRfWe2lMX+Bw4cwK5duzB27Fi0adNGaqvrBAM0onoi1+nQ8dYleJcWIt/NA6db+EMn56qD2mDfEdkBKx6zsWDBAvj5+YnJxkbKlEolKioqDNK1Wq34vDbOnDmDJUuWoGvXroiJiTGj0XWDARpRPQjLTsXbv+6AT+ldMS3XrSn+1XU4Dvl1qMeW2T/2HZHj8fPze+hl6SqVCnl5eQbp1WvJHpwSNSYrKwvz5s2Dv78/Fi5cCGdn+w2D+FdOojoWlp2KJYe+RvP7AgwAaF56F0sOfY2w7JrP83mUse+I7IfFOzgl3kQQEBCAa9euoaSkRC89PT1dfF6TnJwczJ49G15eXvj444/h5uYm+Z3rEgM0ojok1+nw9q87IMDwXz457o32z/o1EXKdru4bZ+fYd0R2qA4PqQ0LC0NVVRWSkpLENK1Wi927d6N9+/bw8fEBAOTm5hpsOlCr1Xj77bchl8uxdOlSu925eT/7HdsjckAdb13Sm5p7kBzAY6UF6HjrEk4+VvPfBh817DuiR1v79u0RHh6ONWvWoKCgAK1bt8bevXtx8+ZNzJ07V8y3ePFinD59GocPHxbT3nnnHVy/fh1jx47F2bNncfbsWfGZl5fXQ6+Kqg8M0IjqkHdpoVXzPUrYd0T2RWaFTQJSL0ufP38+fHx8sG/fPhQXF8Pf3x9LlixBx44dayxXfUba5s2bDZ517NiRARrRoy7fzcOq+R4l7DsiO1MPl6UrlUpMmTIFU6ZMMZlnxYoVBmn3j6Y1FFyDRlSHTrfwR65bU5haJaUDcNPNE6db+NdlsxoE9h2RfanrTQKPGgZoRHVIJ5fjX12HQwYYBBo63LuX7tOuw3imlxHsOyJ6lPC/ZER17JBfB8wN+zPy3Jrqpd9y88TcsD/zLK8asO+I7Egd38X5qOEaNKJ6cMivAw63eZqn4ZuBfUdkH2SA5ZsErNEQB8UAjaie6ORyHgdhJvYdETk6BmhEREQknSCIl51bVAcZxQCNiIiIpLPGLkzGZyZx0QYRERGRneEIGhEREUlXDwfVPkoYoBEREZFkMgGGhxJKxQDNJE5xEhEREdkZjqARERGRdJzitCkGaERERCSZjAGaTTFAIyIiIul4DppNcQ0aERERkZ3hCBoRERFJxilO22KARkREROZhgGUzDhOgFRUVYdWqVTh8+DA0Gg1CQkIwZcoUBAUF1ar85cuXsXLlSpw9exbOzs7o3r07pk2bBk9PT718Op0OW7ZswY4dO3D79m34+vpi3Lhx6Nevn8m6Kysr8cYbbyA7OxuTJ0/G2LFjLXlVIiIicnAOEaDpdDrMnTsXv//+O8aMGYOmTZtix44dmDFjBtauXYs2bdrUWP7WrVuYPn06GjdujJiYGJSVlWHLli24dOkSVq9eDRcXFzHv2rVr8e233yIiIgLBwcE4cuQIFi5cCJlMhr59+xqtf9u2bbh165ZV35mIiKg+cYrTthxik8ChQ4dw7tw5zJs3D2+88Qb+9Kc/YcWKFZDL5fjqq68eWv6bb75BeXk5li9fjpEjR+K1117DP/7xD2RlZWHPnj1ivry8PGzduhVRUVF45513EBERgX/+85/o0KEDvvjiC1RVVRnUfefOHXz99dd45ZVXrPrORERE9ap6F6elHzLKIQK0lJQUNGvWDL179xbTPD09ER4ejiNHjkCr1T60/IsvvggfHx8x7fnnn0ebNm1w8OBBMe3IkSOorKxEVFSUmCaTyTB8+HDk5eUhLS3NoO7Vq1ejTZs26N+/vyWvSERERI8QhwjQLl68iMDAQMjl+q8TEhKC8vJyXL161WTZvLw83Llzx+hatZCQEGRmZoo/Z2ZmolGjRvDz8zPIV/38funp6di7dy+mT58OmUxW6/fJz89HRkaG+MnOzq51WSIiorogE6zzIeMcYg3a7du38eyzzxqkq1QqAIBarUa7du2MllWr1Xp5HyxfWFgIrVYLhUIBtVoNLy8vg2Crumx+fr6YJggC4uLi0KdPHzz99NO4ceNGrd8nKSkJGzZsqHV+IiKiOsc1aDZldwGaTqdDRUVFrfIqFArIZDJoNBooFAqjzwFAo9GYrKP62f0bAYyVVygU0Gg0D81Xbc+ePbh06RIWLlxYq3e5X2RkJHr06CH+nJ2djUWLFkmuh4iIiBomuwvQzpw5gxkzZtQq76ZNm+Dn5welUml0nVl1mlKpNFlH9TNjQeGD5ZVKZa3ylZSUYM2aNRg7dqzeurba8vb2hre3t+RyREREdcnSKUoOoJlmdwHa448/jnnz5tUqb/XUYrNmzcSpyvvVNH35YB2mynt4eIgjZCqVCqdOnYIgCHrTnNVlq4OqLVu2oKKiAn369BGnNvPy8gAAxcXFuHHjBry9vY2OxhERETUIOlgeoems0hKHZHcBmkqlwuDBgyWVCQwMRGpqKnQ6nd5GgfPnz8PV1bXGc9CaN28OT09PZGRkGDw7f/48AgICxJ8DAgKwc+dOZGdno23btmJ6enq6+BwAcnNzUVRUhNdff92gzk2bNmHTpk1Yt24dAgMDJb0nERGR3eAaNJuyuwDNHKGhoTh06BAOHz6MsLAwAEBBQQEOHjyIF198UW99Wk5ODgCgdevWeuX37t2L3NxccUryxIkTuHr1Kl5++WUxX8+ePbFy5Ups374dM2fOBHBvM0BiYiKaN2+Op59+GgAwYsQI9OrVS6+Nd+7cwdKlSzF48GD07NkTLVu2tH5HEBERkUNwiAAtLCwM33//PWJjY3H58mXxJgGdTofx48fr5a0OrBISEsS0cePG4dChQ/jrX/+KkSNHoqysDJs3b4a/v7/eaF6LFi0watQobN68GZWVlQgJCcFPP/2E1NRUvPfee3BycgIABAUFGRzbUT3V2bZtW4PgjYiIqKGxyjEZAgfRTHGIAM3JyQkff/wxvvjiC2zbtg0ajQbBwcGYN28eHn/88YeW9/HxwYoVK7By5UqsXr1avItz6tSpBrtDJ02ahCZNmiApKQl79+6Fr68vFixYwINoiYjoEWONmwAYnpkiEwTes2DvMjIyEBMTA03rMAhKz/puDhGRzcm4eNxsxzbOsmn91b+TZK49IZM3taguQXcXQvkRrF271uiB8Y8yhxhBIyIiorrFKU7bYoBGRERE0nEXp005xF2cRERERI6EI2hEREQkmUwQILN0GTuXwZvEAK0BabwzFfIS3j5AREQ12FhH3yPA8psAGJ+ZxClOIiIiIjvDETQiIiKSTCYIkFk6BMYpTpMYoBEREZF01oitGJ+ZxACNiIiIpBOscM4GR9BM4ho0IiIiIjvDETQiIiKSTgBkllbBATSTGKARERGReRhh2QynOImIiIjsDEfQiIiISDKZzvIpThnAoSITGKARERGRdNbYxclzNkxi3EpERERkZziCRkRERNJx8MumGKARERGRZNa46klqea1Wi3Xr1mH//v0oKipCu3btMGHCBHTp0qXGcleuXEFiYiLS09ORmZkJrVaLrVu3omXLlpY036Y4xUlEREQNQmxsLBISEtC/f3+89dZbkMvlmDNnDlJTU2ssl5aWhm3btqG0tBR+fn511FrLMEAjIiIiMwj3NgpY8pEwgpaeno7k5GRMnDgRU6ZMQWRkJJYvX47HHnsM8fHxNZbt0aMHdu/eja+//hr9+vWz8L3rBgM0IiIikk5npU8tpaSkwMnJCZGRkWKaUqnEkCFDkJaWhtzcXJNlPTw84ObmJuHl6h/XoBEREZFkMkGAzMKbBKrXoGVnZ+ulq1QqeHt766VlZmbC19cX7u7ueukhISEAgKysLPj4+FjUHnvCAI2IiIjq1aJFi/R+jo6Oxvjx4/XS1Go1VCqVQdnqtPz8fNs1sB4wQCMiIiLpBFjtLs4FCxboLd43FohpNBq4uLgYpCsUCvG5I2GARkRERGYQLA/QZPfK+/n5ISgoqMasSqUSFRUVBularVZ87ki4SYCIiIjsnkqlglqtNkivTntwzVpDxwCNiIiIpKvjXZwBAQG4du0aSkpK9NLT09PF546EARoRERFJVr2L09JPbYWFhaGqqgpJSUlimlarxe7du9G+fXtxB2dubq7BrtCGiGvQiIiIyO61b98e4eHhWLNmDQoKCtC6dWvs3bsXN2/exNy5c8V8ixcvxunTp3H48GExrbi4GNu2bQMAnDt3DgDwf//3f2jcuDEaN26MESNG1O3L1AIDNCIiIpJOsMImAYnl58+fDx8fH+zbtw/FxcXw9/fHkiVL0LFjxxrLFRUVYd26dXppW7duBQA89thjDNCIiIjIUVghQJN4WbpSqcSUKVMwZcoUk3lWrFhhkNayZUu9EbWGgGvQiIiIiOwMR9CIiIhIOmscVGudc24dEgM0IiIikk7iMRlGyazREMfEAI2IiIiks8Jl6da6KsoROUyAVlRUhFWrVuHw4cPQaDQICQnBlClTHnp1RLXLly9j5cqVOHv2LJydndG9e3dMmzYNnp6eevl0Oh22bNmCHTt24Pbt2/D19cW4cePQr18/gzp1Oh2SkpKQlJSEK1euwNXVFe3atcP06dMd7kA9IiIish6HCNB0Oh3mzp2L33//HWPGjEHTpk2xY8cOzJgxA2vXrkWbNm1qLH/r1i1Mnz4djRs3RkxMDMrKyrBlyxZcunQJq1ev1rucde3atfj2228RERGB4OBgHDlyBAsXLoRMJkPfvn316v3nP/+JAwcOYODAgfjTn/6EsrIyZGZm4s6dOzbpByIiorpT97s4HyUOEaAdOnQI586dw8KFCxEWFgYA6NOnD1555RV89dVXeP/992ss/80336C8vBxffvmleBJxSEgIZs2ahT179iAyMhIAkJeXh61btyIqKgozZ84EAAwdOhTTp0/HF198gbCwMDg5OQEAfvzxR+zduxeLFi1C7969bfTmRERE9UQn3PtYWgcZ5RDHbKSkpKBZs2Z6gZCnpyfCw8Nx5MgR8ab7msq/+OKLYnAGAM8//zzatGmDgwcPimlHjhxBZWUloqKixDSZTIbhw4cjLy8PaWlpYnpCQgJCQkLQu3dv6HQ6lJWVWeNViYiI6BHgEAHaxYsXERgYCLlc/3VCQkJQXl6Oq1evmiybl5eHO3fuGF2rFhISgszMTPHnzMxMNGrUCH5+fgb5qp8DQElJCc6fP4/g4GCsWbMGgwcPxsCBAzF69Gj8+OOPZr8nERGR3ai+ScDSDxnlEFOct2/fxrPPPmuQrlKpAABqtRrt2rUzWlatVuvlfbB8YWEhtFotFAoF1Go1vLy8IJPJDPIBQH5+PgAgJycHgiDgxx9/hJOTEyZPngx3d3d8//33+Mc//gF3d3d069bN5Pvk5+eL7QLgEJe+EhGRg+E5aDZldwGaTqdDRUVFrfIqFArIZDJoNBooFAqjzwFAo9GYrKP62f0bAYyVVygU0Gg0D80HQJzOvHv3LlatWoX27dsDAHr06IHRo0dj48aNNQZoSUlJ2LBhg8nnRERE5NjsLkA7c+YMZsyYUau8mzZtgp+fH5RKpdF1ZtVpSqXSZB3Vz4wFhQ+WVyqVtc4H3Lv7qzo4AwA3Nzf06NED+/fvR2VlJZydjXd/ZGQkevToIf6cnZ2NRYsWmXwHIiKiusddnLZkdwHa448/jnnz5tUqb/XUYrNmzfSmBKvVNH35YB2mynt4eIgjZCqVCqdOnYIgCHrTnNVlvb299f63WbNmBnV6enqisrIS5eXlaNy4sdE2eXt7i3UQERHZJe7itCm7C9BUKhUGDx4sqUxgYCBSU1Oh0+n0NgqcP38erq6uNZ6D1rx5c3h6eiIjI8Pg2fnz5/UOlA0ICMDOnTuRnZ2Ntm3biunp6enic+BegNWsWTPk5eUZ1KlWq6FQKODm5ibpHYmIiOjR4RC7OENDQ3H79m0cPnxYTCsoKMDBgwfx4osv6q1Py8nJQU5OjkH5X375Bbm5uWLaiRMncPXqVYSHh4tpPXv2hLOzM7Zv3y6mCYKAxMRENG/eHE8//bSY3qdPH9y6dQvHjx/Xa9ORI0fQuXNngx2nREREDYqgs86HjLK7ETRzhIWF4fvvv0dsbCwuX74s3iSg0+kwfvx4vbzVB8wmJCSIaePGjcOhQ4fw17/+FSNHjkRZWRk2b94Mf39/vdG8Fi1aYNSoUdi8eTMqKysREhKCn376CampqXjvvffEQ2qr6zx48CDee+89vPzyy2jcuDESExNRWVmJiRMn2rhHiIiIbIy7OG3KIQI0JycnfPzxx/jiiy+wbds2aDQaBAcHY968eXj88ccfWt7HxwcrVqzAypUrsXr1avEuzqlTpxrsDp00aRKaNGmCpKQk7N27F76+vliwYAH69++vl69Zs2b4/PPP8fnnn+O7775DZWUlnnrqKSxYsID3cBIRUcMnWGENGs9BM0kmCOwde5eRkYGYmBi4nGoGeYnhMR9ERETVDui+s2n91b+TXK8Hw0lr2XrqKkUpyltdwNq1a40eGP8oc4gRNCIiIqpj1rgJgGNEJjFAIyIiIukYoNkUtxISERER2RmOoBEREZF0HEGzKQZoREREJJ0gADoLzzFjgGYSpziJiIiI7AxH0IiIiEg6TnHaFAM0IiIiko4Bmk1xipOIiIjIznAEjYiIiKTjVU82xQCNiIiIpBMECAJ3cdoKAzQiIiKSTmeFETRLyzswrkEjIiIisjMcQSMiIiLpuIvTphigERERkXSCzgo3CVhY3oFxipOIiIjIznAEjYiIiKQTYIUpTqu0xCExQCMiIiLJBJ0OgoVTnJaWd2Sc4iQiIiKyMxxBIyIiIum4i9OmGKARERGRdLzqyaY4xUlERERkZziCRkRERNIJguXnmHEEzSQGaERERCSZoBMgWDjFaWl5R8YAjYiIiMygs8JNADxmwxSuQSMiIiKyMxxBIyIiIskEneVTlLyK0zQGaERERCSdYIUpTkZoJjFAawA0Gg0AQGhUydl6IiKqUUZGBvz8/ODq6mrT7xHcLP+dJLhVWqUtjogBWgOQmZkJAKgMLqznlhARkb2LiYnBJ598gm7dutmkfk9PT7i6uqI8yDq/k1xdXeHp6WmVuhwJA7QGwM/PDwAwd+5cBAQE1HNrGpbs7GwsWrQICxYsEPuRaod9Zxn2n/nYd+ar7rtGjRrZ7Dt8fHywadMmFBQUWKU+T09P+Pj4WKUuR8IArQFo0qQJACAgIABBQUH13JqGyc/Pj31nJvadZdh/5mPfmU+pVNq0fh8fHwZVNsZjNoiIiIjsDAM0IiIiIjvDAK0BUKlUiI6Ohkqlqu+mNDjsO/Ox7yzD/jMf+8587DvHIRME3lRKREREZE84gkZERERkZxigEREREdkZBmhEREREdoYBGhEREZGd4UG1dejUqVOYMWOG0Wfx8fF46qmnxJ/Pnj2LVatW4eLFi3B3d0d4eDhiYmLg5uZmUDYjIwNfffUVzp49C61Wi1atWiEiIgIjR4602bvUNVv03dWrV7Fu3TqcPXsWhYWF8PHxQb9+/TBmzBib32FX12rbf7/++it+/PFHnD9/HtnZ2WjRogUSEhKMltPpdNiyZQt27NiB27dvw9fXF+PGjUO/fv1s9h71wdp9l52djd27d+P48ePIyclBo0aN8OSTT2L8+PEIDg626bvUNVv8ubvf/v37xVPz9+3bZ9W22wNb9V9OTg7WrVuH3377DaWlpWjevDn69OmDmJgYm7wHmYcBWj0YMWIEQkJC9NJat24t/nNmZiZmzpwJPz8/TJs2Dbdu3cLWrVtx7do1fPLJJ3rlfv31V8ybNw+BgYH485//jEaNGiEnJwd5eXl18i51zVp9l5ubi0mTJqFx48aIioqCh4cH0tLSsH79emRkZCA2NrbO3qkuPaz/fvjhB/z444948sknH7pNf+3atfj2228RERGB4OBgHDlyBAsXLoRMJkPfvn1t0v76ZK2+27lzJ3bt2oXQ0FAMHz4cJSUlSEpKwuTJk/HJJ5/g+eeft9k71Bdr/rmrVlpailWrVtn0SiN7Yc3+y8zMxIwZM+Dt7Y3Ro0ejadOmyM3Nxa1bt2zSdrKAQHXm5MmTQq9evYSDBw/WmG/27NnC8OHDheLiYjHtP//5j9CrVy/h2LFjYlpxcbEwbNgwYf78+UJVVZWtmm0XrN13GzduFHr16iVcunRJr/yiRYuEXr16CYWFhVZtf32rbf/l5eUJFRUVgiAIwpw5c4RRo0YZzXfr1i0hPDxc+PTTT8U0nU4nTJ06VfjTn/4kVFZWWq3t9c3afXfhwgWhpKREL62goECIiIgQpkyZYpU22wtr99394uPjhVdffVVYuHChMGDAAGs01+5Yu/+qqqqE119/XZg0aZJQXl5u7eaSlXENWj0pLS1FZWWlQXpJSQl+++03DBgwAO7u7mL6wIED0ahRIxw8eFBM++GHH3D79m3ExMRALpejrKwMOp2uTtpfn6zRdyUlJQAALy8vvTpUKhXkcjmcnR13cNlU/wGAt7d3rd79yJEjqKysRFRUlJgmk8kwfPhw5OXlIS0tzWrttSfW6LugoCCD6famTZuiQ4cOyM7Otko77ZE1+q7a1atX8d1332Hq1KlwcnKyVhPtmjX67/jx4/jjjz8QHR0NpVKJ8vJyVFVVWbupZCWO+1vIjsXGxqKsrAxOTk7o0KEDJk+eLK49uXTpEqqqqgwuCHZxcUFgYCAyMzPFtN9++w3u7u7Iz8/H3/72N1y9ehWNGjXCgAEDMG3aNJtfllsfrNV3nTp1wr///W8sWbIE48ePh4eHB86dO4fExESMGDHCYadNauo/KTIzM9GoUSP4+fnppVdPw2RmZqJDhw5WabO9sFbfmXL79m00bdrUavXZE2v33WeffYZOnTqhe/fuen/xclTW6r/ffvsNwL3/JsbExCAjIwMuLi7o1asXZs2aBQ8PD2s3nSzAAK0OOTs7IzQ0FC+88AKaNm2Ky5cvY+vWrZg2bRq++OILPPnkk1Cr1QBgdB2BSqXCmTNnxJ+vXbuGqqoqzJ8/H0OGDMHEiRNx+vRpbNu2DcXFxfjggw/q7N1szdp9161bN7z55pv45ptv8PPPP4vpr732mkMulK1N/0mhVqvh5eUFmUyml17d9/n5+VZre32zdt8Zc+bMGaSlpeH111+3Qovthy367ujRozh+/Di++uorG7TYvli7/65duwYA+Pvf/46uXbvi1Vdfxe+//45vvvkGt27dwueff27w7zTVHwZodeiZZ57BM888I/7cs2dPhIWF4Y033sCaNWuwdOlSaDQaAPf+hvMghUIBrVYr/lxWVoby8nIMGzZM3OkTGhqKiooKJCUlYfz48WjTpo2N36puWLvvAKBly5Z49tlnERoaCg8PDxw9ehTffPMNmjVrhhEjRtj2hepYbfpPCo1GY7Kfq587Cmv33YPu3LmDhQsXomXLlhg7dqylzbUr1u67iooKfPbZZxg2bBjatm1r5dbaH2v3X1lZGQAgODgY7733HgAgLCwMSqUSa9aswYkTJxxyk0pDxTVo9czX1xc9e/bEqVOnUFVVJU5LVlRUGOTVarXiL0AAYt4Hd8xVH3PgqOuAqlnSd8nJyfjkk08wZ84cREREIDQ0FO+++y4GDRqE1atX4+7du3X2HvXlwf6TQqlUmuzn6ueOzJK+u19ZWRnmzp2LsrIyfPTRR0aP0XE0lvRdQkIC7t69i/Hjx9uodfbP0n9vAcPfGf379wcAnDt3zjqNJKtggGYHWrRogYqKCpSXl4tTRNXTdfdTq9Xw9vYWf67O26xZM7181Qvfi4qKbNVku2Fu323fvh2BgYFo0aKFXr4ePXqgvLxcb72aI7u//6RQqVS4ffs2BEHQS6/u+/v72lGZ23fVKioqsGDBAly6dAkfffQR/P39rdxC+2VO3xUXF2Pjxo0YOnQoSkpKcOPGDdy4cQNlZWUQBAE3btzAnTt3bNhq+2Hun73qfy8f/J3h6ekJ4NH4ndGQMECzA9evX4dCoUCjRo3wxBNPwMnJCRkZGXp5KioqkJmZiYCAADGtejH8g2eeVa//qf6XzpGZ23d37twxuuO1epfUo7Kz6f7+kyIgIADl5eUGuw7T09PF547O3L4D7h3yu3jxYpw8eRLvvfceOnbsaP0G2jFz+q6oqAhlZWXYvHkzRo8eLX5SUlJQXl6O0aNHG5wT6ajM/bNXvWbtwd8Z1X+xehR+ZzQkDNDqUEFBgUFaVlYWfv75Z3Tp0gVyuRyNGzfG888/j/3796O0tFTMt2/fPpSVlSE8PFxMq/7nXbt26dW5a9cuODk5oVOnTrZ5kXpg7b5r06YNMjMzcfXqVb06k5OTIZfL0a5dO5u9S32oTf9J0bNnTzg7O2P79u1imiAISExMRPPmzfH0009b2mS7Ye2+A4Dly5fjxx9/xMyZMxEaGmqFVtona/adl5cXFi9ebPDp1KkTFAoFFi9ejHHjxlmx9fXPFv/eKhQK7NmzR+8vqDt37gQArj+zM9wkUIc++OADKJVKPP300/Dy8sLly5fxn//8B66urpg0aZKYb8KECZg6dSqmT5+OyMhI8TT8Ll26oFu3bmK+J598Ei+99BJ2796NqqoqdOzYEadPn8bBgwcxbtw4h5pmsnbfjRkzBseOHcO0adPwpz/9CR4eHvjll19w7NgxDB061KH6Dqh9//3+++84cuQIgHvXwRQXF+Prr78GcG9UrEePHgDuTbGMGjUKmzdvRmVlJUJCQvDTTz8hNTUV7733nkOdTWXtvktISMCOHTvw1FNPwdXVFfv379f7vl69ejnMMS/W7DtXV1f06tXL4Dt++uknXLhwweizhs7af/ZUKhVee+01rFu3DrNnz0avXr2QlZWFnTt3ol+/fga3FVD9kgkPLiIhm/n+++9x4MAB5OTkoKSkBJ6ennjuuecQHR0NX19fvbypqanifZJubm4IDw/HpEmTDBYRV1ZWYtOmTdizZw/y8/Ph4+ODqKgovPzyy3X5ajZni75LT0/HV199hczMTBQWFqJly5YYNGgQxo4d63AH1da2//bs2WPymqtBgwZh/vz54s86nQ7//ve/kZSUBLVaDV9fX7z66qsYMGCAzd+nLlm77z766CPs3bvX5Pdt3boVLVu2tO5L1BNb/Ll70EcffYSUlBSHvIvTFv0nCAL+7//+D//3f/+HGzduoFmzZhg0aBCio6Md7r97DR0DNCIiIiI7wzVoRERERHaGARoRERGRnWGARkRERGRnGKARERER2RkGaERERER2hgEaERERkZ1hgEZERERkZxigEREREdkZBmhEREREdoYBGhHZzMsvv1zra8f27NmD3r17i5+///3ves/feust9O7d2watNM9f/vIXvfaeOnWqvptERA6EF28RUa3cuHEDo0ePrjHPY489hoSEBIu+p2fPnggICIC/v79F9dTGwoUL8cMPP+D9999Hv379TOYrKSnB8OHD4eLigu3bt0OpVGLo0KHo2rUrTp8+jdOnT9u8rUT0aGGARkSStG7dGv379zf6rHHjxno/L1u2THL9vXr1wuDBg81qm1RDhgzBDz/8gN27d9cYoP3www/QaDQYNGgQlEolAGDo0KEAgPXr1zNAIyKrY4BGRJK0bt0a48ePr3Vee9a5c2e0bNkSJ0+eRG5uLnx8fIzm2717N4B7AR0RUV3gGjQishkpa9DMlZycjL59++KNN95Afn6+mH769Gm8++67iIiIQN++fTF27FisXbsW5eXlYh6ZTIaXXnoJOp1ODMIe9Mcff+D8+fNo164dgoODbfouRETVGKARUYO1bds2LFy4EO3bt8dnn30Gb29vAMCOHTswY8YMnD17Fi+88AJGjBiBFi1aYNOmTZg1axYqKirEOgYNGgS5XI49e/ZAEASD7+DoGRHVB05xEpEkOTk5WL9+vdFnTz31FLp161Yn7Vi7di02bdqEXr164f333xfXhl2+fBlxcXFo164dli1bhqZNm4plvvnmG6xZswbbtm3DmDFjAAA+Pj7o0qULjh07hpMnT+K5554T81dWVuLAgQNQKBQYMGBAnbwXERHAAI2IJMrJycGGDRuMPhs5cqTNA7SqqiosXboUu3btQkREBGbNmgUnJyfxeWJiIqqqqjBjxgy94AwAXnnlFSQkJCA5OVkM0IB7o2PHjh3Drl279AK0o0eP4vbt2wgPD4eHh4dN34uI6H4M0IhIkq5du2Lp0qX19v3vvfcejhw5gtdeew0xMTEGz9PT0wEAv/76K06cOGHw3NnZGVeuXNFL69mzJzw9PfHTTz+huLhY3I26a9cuAJzeJKK6xwCNiBqUM2fOQKFQ4IUXXjD6vLCwEACwadOmWtfp7OyMAQMGICEhAT/88AOGDx8OtVqNY8eOwcfHB88//7xV2k5EVFsM0IioQVm2bBlmzZqFd955B5988gmeeeYZvefu7u4AgL1798LNza3W9Q4dOhQJCQnYtWsXhg8fjv3796OqqgqDBw+GXM79VERUt/hfHSJqUJ588kksX74cLi4ueOedd3D27Fm95+3btwcApKWlSaq3bdu2eOqpp5CRkYHff/8du3fvFo/hICKqawzQiKjBCQgIEIO02bNnIzU1VXw2fPhwODk5IS4uDrm5uQZli4qKcPHiRaP1Vq81+/TTT5GdnY3nnnsOjz32mG1egoioBpziJCJJajpmAwBeffVV8cgLW2rXrh2WL1+OmTNn4p133sHHH3+MZ599Fv7+/pg1axY+/fRTvPrqq3jhhRfQunVrlJaW4vr16zhz5gwGDRqE2bNnG9TZp08ffPbZZ+KoHDcHEFF9YYBGRJLUdMwGAIwaNapOAjRAP0ibM2cOlixZgo4dOyIiIgIBAQFISEjAmTNn8Msvv8Dd3R0+Pj4YNWoUBg0aZLQ+Nzc3hIeHY/fu3fDw8ECvXr3q5D2IiB4kE4wdnU1EVMf27NmD2NhYzJs3r84uS7eG9evXY8OGDYiLi0OnTp3quzlE5CC4Bo2I7EpsbCx69+6Nv//97/XdlBr95S9/Qe/evWscTSQiMhenOInILgQEBCA6Olr82d/fv/4aUwtDhw5F165dxZ+5mYCIrIlTnERERER2hlOcRERERHaGARoRERGRnWGARkRERGRnGKARERER2RkGaERERER2hgEaERERkZ1hgEZERERkZxigEREREdkZBmhEREREdub/AUGWBZpWCt8xAAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -665,15 +660,38 @@ "fig, ax = plt.subplots()\n", "dr.draw(ax=ax)\n", "ax.scatter(Ei0, dr.transform_Em_to_eps(Em0, Ei0), marker='*')\n", - "for e1 in dr.neighbors[0]:\n", - " for e2 in dr.neighbors[1]:\n", - " ax.scatter(e1, dr.transform_Em_to_eps(e2, Ei0), c='r')\n", + "for e1 in dr.neighbors['Ei']:\n", + " for e2 in dr.neighbors['eps']:\n", + " ax.scatter(e1, e2, c='r')\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$[506,~508,~510,~512,~514,~516] \\; \\mathrm{keV}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dr.axes['Ei'].edges" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [ { @@ -681,60 +699,65 @@ "output_type": "stream", "text": [ "[0.005 0.005 0.98 0.005 0.005]\n", - "[0.02530253 0.47234723 0.47974797 0.02260226 0. ]\n", - "[0.0019 0.1481 0.6929 0.1554 0.0017]\n", - "[0. 0.0223 0.4764 0.4778 0.0235]\n" + "[0.0204 0.4754 0.4811 0.0231 0. ]\n", + "[0.001 0.1558 0.6842 0.1572 0.0018]\n", + "[0. 0.0236 0.4736 0.4791 0.0237]\n" ] } ], "source": [ - "mu = 511\n", - "sigma_inj = 1\n", - "bins = np.arange(506, 517, 2)\n", + "# mu = 511\n", + "# sigma_inj = 1\n", + "# binedges = np.linspace(506, 516, 6) * u.keV\n", + "# bincenters = (binedges[1:]+binedges[:-1])/2\n", "\n", - "# Create model 0\n", - "model0 = np.array([0.005,0.005, 0.98, 0.005, 0.005])\n", - "print(model0)\n", + "# # Create model 0\n", + "# model0 = np.array([0.005,0.005, 0.98, 0.005, 0.005])\n", + "# print(model0)\n", "\n", - "# Create model 1\n", - "counts, bins = np.histogram(np.random.normal(loc=mu-1, scale=sigma_inj, size=10000), bins=bins)\n", - "bincenters = (bins[1:]+bins[:-1])/2 * u.keV\n", - "model1 = counts / np.sum(counts)\n", - "print(model1)\n", + "# # Create model 1\n", + "# counts, _ = np.histogram(np.random.normal(loc=mu-1, scale=sigma_inj, size=10000), bins=binedges.value)\n", + "# model1 = counts / np.sum(counts)\n", + "# print(model1)\n", "\n", - "# Create model 2\n", - "counts, bins = np.histogram(np.random.normal(loc=mu, scale=sigma_inj, size=10000), bins=bins)\n", - "model2 = counts / np.sum(counts)\n", - "print(model2)\n", + "# # Create model 2\n", + "# counts, _ = np.histogram(np.random.normal(loc=mu, scale=sigma_inj, size=10000), bins=binedges.value)\n", + "# model2 = counts / np.sum(counts)\n", + "# print(model2)\n", "\n", - "# Create model 3\n", - "counts, bins = np.histogram(np.random.normal(loc=mu+1, scale=sigma_inj, size=10000), bins=bins)\n", - "model3 = counts / np.sum(counts)\n", - "print(model3)" + "# # Create model 3\n", + "# counts, _ = np.histogram(np.random.normal(loc=mu+1, scale=sigma_inj, size=10000), bins=binedges.value)\n", + "# model3 = counts / np.sum(counts)\n", + "# print(model3)" ] }, { "cell_type": "code", - "execution_count": 200, + "execution_count": 121, "metadata": {}, "outputs": [ { "data": { "text/latex": [ - "$[510.2826,~510.37249,~514.74124,~509.09524,~509.89007,~512.51471,~508.54299,~512.85188,~512.16756,~512.62646] \\; \\mathrm{keV}$" + "$[509.747,~509.83029,~505.14983,~514.31033,~511.01409,~510.34,~508.91595,~508.39782,~512.90728,~513.92033] \\; \\mathrm{keV}$" ], "text/plain": [ - "" + "" ] }, - "execution_count": 200, + "execution_count": 121, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Common model parameters\n", + "sigma_inj = 2\n", + "binedges = np.linspace(506, 516, 6) * u.keV\n", + "bincenters = (binedges[1:]+binedges[:-1])/2\n", + "\n", "# Simulate events\n", "Ntot = 10\n", "a = np.random.normal(loc=511, scale=np.sqrt(sigma_rsp**2 + sigma_inj**2), size=Ntot) * u.keV\n", @@ -743,66 +766,112 @@ }, { "cell_type": "code", - "execution_count": 205, + "execution_count": 122, "metadata": {}, "outputs": [ { "data": { + "text/latex": [ + "$2.4258732 \\; \\mathrm{keV}$" + ], "text/plain": [ - "-10" + "" ] }, - "execution_count": 205, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# As we have injected gaussian data, we can calculate the exact std and mean\n", + "np.sqrt(np.std(a)**2 - 1*u.keV**2)" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$510.45329 \\; \\mathrm{keV}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.mean(a)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-35.212950330000226" + ] + }, + "execution_count": 129, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "bins = np.arange(506, 517, 2)\n", - "bincenters = (bins[1:]+bins[:-1])/2\n", - "\n", "# Phase space sampling edges\n", "nbins_mu, nbins_sigma = 30, 30\n", "pred_mu, pred_sigma = np.meshgrid(np.linspace(508, 514, nbins_mu), np.linspace(0.5, 2.5, nbins_sigma))\n", "\n", - "# Initial values\n", + "# List to save all log likelihood values\n", "loglikes = []\n", - "runningsum = 0\n", - "loglike = -Ntot\n", "\n", "for i in range(nbins_mu):\n", " for j in range(nbins_sigma):\n", + " # Initialize loglike with first term\n", + " loglike = -Ntot\n", + "\n", " # Calculate model counts for sampled mu, sigma\n", - " model_counts = gaussian(x=bincenters, center=pred_mu[i, j], sigma=pred_sigma[i, j])\n", - " models = model_counts / np.sum(model_counts)\n", + " model_counts = gaussian(x=bincenters.value, center=pred_mu[i, j], sigma=pred_sigma[i, j])\n", + " model = model_counts / np.sum(model_counts)\n", "\n", + " # Sum over all events\n", " for Em in a:\n", - " for model, Ei in zip(models, bincenters*u.keV):\n", - " rsp_val = dr.get_interp_response({'Ei': Ei, 'Em': Em})\n", + " # Temporary variable to sum over Rij*Mj for all j. \n", + " runningsum = 0\n", + " for model_element, Ei in zip(model, bincenters):\n", + " rsp_val = dr.get_interp_response({'Ei': Ei, 'Em': Em}) # Interpolated response value will be different for different Ei's. TODO: How do you transform this to a linear algebra problem?\n", " if rsp_val < 1e-3 * u.cm**2:\n", " rsp_val = 1e-3 * u.cm**2\n", - " runningsum += rsp_val * model / u.cm**2\n", + " runningsum += rsp_val.value * model_element\n", "\n", " loglike += np.log(runningsum)\n", - " runningsum = 0\n", " loglikes.append(loglike)\n", - " loglike = -Ntot\n", "\n", "loglike" ] }, { "cell_type": "code", - "execution_count": 206, + "execution_count": 130, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(511.51724137931035, 1.5344827586206897)" + "(510.48275862068965, 2.5)" ] }, - "execution_count": 206, + "execution_count": 130, "metadata": {}, "output_type": "execute_result" } @@ -813,12 +882,12 @@ }, { "cell_type": "code", - "execution_count": 210, + "execution_count": 131, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -832,6 +901,7 @@ "plt.xlabel('Predicted energy (keV)')\n", "plt.ylabel('Predicted line broadening (keV)')\n", "plt.title('Unbinned RL Monte Carlo')\n", + "plt.scatter(np.mean(a).value, np.sqrt(np.std(a).value**2 - sigma_rsp**2), marker='x', c='r')\n", "plt.colorbar()\n", "plt.show()" ] @@ -1001,23 +1071,6 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], - "source": [ - "def get_interp_response(self, coord):\n", - " pixels, weights = self.get_interp_weights(coord)\n", - " dr = ListModeResponse(self.axes[1:],\n", - " sparse=self._sparse,\n", - " unit=self.unit)\n", - " for p, w in zip(pixels, weights):\n", - " dr += self[p]*w\n", - "\n", - " return dr" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, "outputs": [ { "name": "stdout", @@ -1034,28 +1087,7 @@ " dr = response[0]\n", " data = response._file['DRM']['CONTENTS'][0]\n", " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit) \n", - " dr = get_interp_response(response, SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([399, 368, 400, 401]),\n", - " array([0.05555556, 0.94444444, 0. , 0. ]))" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dr.axes['PsiChi'].interp_weights(SkyCoord(lon=5, lat=0, unit=u.deg, frame=SpacecraftFrame()))" + " dr = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" ] }, { @@ -1082,7 +1114,9 @@ "Em0 = 600*u.keV\n", "Phi0 = 12*u.deg\n", "PsiChi0 = 386\n", - "interpolated_response_value = dr.get_interp_response({'Ei': Ei0, 'Em': Em0, 'Phi': Phi0, 'PsiChi': PsiChi0})\n", + "\n", + "target = {'Ei': Ei0, 'Em': Em0, 'Phi': Phi0, 'PsiChi': PsiChi0}\n", + "interpolated_response_value = dr.get_interp_response(target)\n", "\n", "interpolated_response_value" ] @@ -1091,29 +1125,6 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[,\n", - " ,\n", - " ,\n", - " array([386.5, 387.5, 418.5, 419.5])]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dr.neighbors" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, "outputs": [ { "data": { @@ -1121,7 +1132,7 @@ "(, )" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1132,7 +1143,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -1141,7 +1152,7 @@ "array([509.49 , 509.694, 509.898, 510.102, 510.306, 510.51 ])" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1153,7 +1164,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -1168,15 +1179,25 @@ } ], "source": [ + "label1 = 'Ei'\n", + "label2 = 'Em'\n", + "\n", "fig, ax = plt.subplots()\n", - "dr.project('Ei', 'Em').draw(ax=ax)\n", - "ax.scatter(Ei0, dr.transform_Em_to_eps(Em0, Ei0), marker='*')\n", - "for e1 in dr.neighbors[0]:\n", - " for e2 in dr.neighbors[1]:\n", - " ax.scatter(e1, dr.transform_Em_to_eps(e2, Ei0), c='r')\n", + "dr.project(label1, label2).draw(ax=ax)\n", + "ax.scatter(target[label1], target[label2], marker='*')\n", + "for e1 in dr.neighbors[label1]:\n", + " for e2 in dr.neighbors[label2]:\n", + " ax.scatter(e1, e2, c='r')\n", "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setting up HealpixBase (2)" + ] + }, { "cell_type": "code", "execution_count": null, From 71085fd1ef2afad0db878ab6c43a51474e591839 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Sat, 9 Nov 2024 04:02:33 -0800 Subject: [PATCH 18/46] Added comments to get_point_source_response() --- cosipy/response/FullDetectorResponse.py | 114 ++-- cosipy/response/ListModeResponse.py | 9 +- cosipy/response/PointSourceResponse.py | 3 +- cosipy/spacecraftfile/SpacecraftFile.py | 2 +- docs/tutorials/response/LMDR.ipynb | 754 +++++++++++++++--------- 5 files changed, 538 insertions(+), 344 deletions(-) diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py index 36660f61..297bb8c5 100644 --- a/cosipy/response/FullDetectorResponse.py +++ b/cosipy/response/FullDetectorResponse.py @@ -1,6 +1,7 @@ from .PointSourceResponse import PointSourceResponse from .DetectorResponse import DetectorResponse from .ListModeResponse import ListModeResponse +from .ListModePSR import ListModePSR from astromodels.core.model_parser import ModelParser import matplotlib.pyplot as plt from astropy.time import Time @@ -843,12 +844,13 @@ def get_interp_response(self, coord, unbinned=False): def get_point_source_response(self, exposure_map = None, coord = None, - scatt_map = None): + scatt_map = None, + unbinned = False): """ Convolve the all-sky detector response with exposure for a source at a given sky location. - Provide either a exposure map (aka dweel time map) or a combination of a + Provide either a exposure map (aka dwell time map) or a combination of a sky coordinate and a spacecraft attitude map. Parameters @@ -867,77 +869,81 @@ def get_point_source_response(self, # TODO: deprecate exposure_map in favor of coords + scatt map for both local # and interntial coords - - if exposure_map is not None: - if not self.conformable(exposure_map): - raise ValueError( - "Exposure map has a different grid than the detector response") - psr = PointSourceResponse(self.axes[1:], - sparse=self._sparse, - unit=u.cm*u.cm*u.s) + if unbinned: + pass - for p in range(self.npix): + else: + if exposure_map is not None: + if not self.conformable(exposure_map): + raise ValueError( + "Exposure map has a different grid than the detector response") - if exposure_map[p] != 0: - psr += self[p]*exposure_map[p] + psr = PointSourceResponse(self.axes[1:], + sparse=self._sparse, + unit=u.cm*u.cm*u.s) - return psr + for p in range(self.npix): - else: + if exposure_map[p] != 0: + psr += self[p]*exposure_map[p] - # Rotate to inertial coordinates + return psr - if coord is None or scatt_map is None: - raise ValueError("Provide either exposure map or coord + scatt_map") - - if isinstance(coord.frame, SpacecraftFrame): - raise ValueError("Local coordinate + scatt_map not currently supported") + else: - if self.is_sparse: - raise ValueError("Coord + scatt_map currently only supported for dense responses") + # Rotate to inertial coordinates - axis = "PsiChi" + if coord is None or scatt_map is None: + raise ValueError("Provide either exposure map or coord + scatt_map") + + if isinstance(coord.frame, SpacecraftFrame): + raise ValueError("Local coordinate + scatt_map not currently supported") - coords_axis = Axis(np.arange(coord.size+1), label = 'coords') + if self.is_sparse: + raise ValueError("Coord + scatt_map currently only supported for dense responses") - psr = Histogram([coords_axis] + list(deepcopy(self.axes[1:])), - unit = self.unit * scatt_map.unit) - - psr.axes[axis].coordsys = coord.frame + axis_label = "PsiChi" - for i,(pixels, exposure) in \ - enumerate(zip(scatt_map.contents.coords.transpose(), - scatt_map.contents.data)): + coords_axis = Axis(np.arange(coord.size+1), label = 'coords') # Create axis of length number of input coords + 1 - #gc.collect() # HDF5 cache issues + psr = Histogram([coords_axis] + list(deepcopy(self.axes[1:])), # Create new "NuLambda" axis + unit = self.unit * scatt_map.unit) - att = Attitude.from_axes(x = scatt_map.axes['x'].pix2skycoord(pixels[0]), - y = scatt_map.axes['y'].pix2skycoord(pixels[1])) + psr.axes[axis_label].coordsys = coord.frame # Set coordinate system of PsiChi axis to input coordinate frame. Axis coordsys was set when response file was opened and initialized using HealpixBase.__init__ - coord.attitude = att + for i,(pixels, exposure) in \ + enumerate(zip(scatt_map.contents.coords.transpose(), + scatt_map.contents.data)): - #TODO: Change this to interpolation - loc_nulambda_pixels = np.array(self.axes['NuLambda'].find_bin(coord), - ndmin = 1) - - dr_pix = Histogram.concatenate(coords_axis, [self[i] for i in loc_nulambda_pixels]) + #gc.collect() # HDF5 cache issues + + att = Attitude.from_axes(x = scatt_map.axes['x'].pix2skycoord(pixels[0]), + y = scatt_map.axes['y'].pix2skycoord(pixels[1])) - dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = att) + coord.attitude = att - self._sum_rot_hist(dr_pix, psr, exposure) + #TODO: Change this to interpolation + loc_nulambda_pixels = np.array(self.axes['NuLambda'].find_bin(coord), + ndmin = 1) + + dr_pix = Histogram.concatenate(coords_axis, [self[i] for i in loc_nulambda_pixels]) - # Convert to PSR - psr = tuple([PointSourceResponse(psr.axes[1:], - contents = data, - sparse = psr.is_sparse, - unit = psr.unit) - for data in psr[:]]) - - if coord.size == 1: - return psr[0] - else: - return psr + dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = att) + + self._sum_rot_hist(dr_pix, psr, exposure) + + # Convert to PSR + psr = tuple([PointSourceResponse(psr.axes[1:], + contents = data, + sparse = psr.is_sparse, + unit = psr.unit) + for data in psr[:]]) + + if coord.size == 1: + return psr[0] + else: + return psr @staticmethod def _sum_rot_hist(h, h_new, exposure, axis = "PsiChi"): diff --git a/cosipy/response/ListModeResponse.py b/cosipy/response/ListModeResponse.py index 8baf5491..16e05b7d 100644 --- a/cosipy/response/ListModeResponse.py +++ b/cosipy/response/ListModeResponse.py @@ -22,7 +22,7 @@ class ListModeResponse(Histogram): def __init__(self, *args, **kwargs): # Overload parent init. Called in class methods. super().__init__(*args, **kwargs) - self.mapping = {'Ei': 'Ei', 'Em': 'Em', 'Phi': 'Phi', 'PsiChi': 'PsiChi'} # key_target : label + self.mapping = {'Ei': 'Ei', 'Em': 'eps', 'Phi': 'Phi', 'PsiChi': 'PsiChi'} # key_target : label def _get_all_interp_weights(self, target: dict): @@ -50,11 +50,11 @@ def _get_all_interp_weights(self, target: dict): else: raise ValueError(f'Axis type: {axis_type} is not supported') - elif axis_scale == 'nonlinear': - pass + # elif axis_scale == 'nonlinear': + # pass else: - raise ValueError(f'Scale: {axis_scale} is not supported') + raise ValueError(f'{axis_scale} binning / scale scheme is not supported') indices.append(idx) weights.append(w) @@ -103,7 +103,6 @@ def get_interp_response(self, target: dict): for idx, w in zip(perm_indices, perm_weights): i = (Ellipsis,) + idx # XXX: Assuming 'Ei' is the first index interpolated_response_value += np.prod(w) * self.contents[i] - # raise NotImplementedError('Support for len(target) < len(axes) is yet to be implemented') self.neighbors = self.get_nearest_neighbors(target, indices) diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py index e16ca234..db48df69 100644 --- a/cosipy/response/PointSourceResponse.py +++ b/cosipy/response/PointSourceResponse.py @@ -68,6 +68,7 @@ def get_expectation(self, spectrum): spectrum_unit = getattr(spectrum, item).unit break + # Set overall spectrum unit based on model PDF if spectrum_unit == None: if isinstance(spectrum, Constant): spectrum_unit = spectrum.k.unit @@ -85,7 +86,7 @@ def get_expectation(self, spectrum): except: raise RuntimeError("Spectrum not yet supported because units of spectrum are unknown.") - if isinstance(spectrum, DiracDelta): + if isinstance(spectrum, DiracDelta): # Special numerical handling for DiracDelta type spectral profiles flux = Quantity([spectrum.value.value * spectrum_unit * lo_lim.unit if spectrum.zero_point.value >= lo_lim/lo_lim.unit and spectrum.zero_point.value <= hi_lim/hi_lim.unit else 0 * spectrum_unit * lo_lim.unit for lo_lim,hi_lim in zip(eaxis.lower_bounds, eaxis.upper_bounds)]) diff --git a/cosipy/spacecraftfile/SpacecraftFile.py b/cosipy/spacecraftfile/SpacecraftFile.py index ce2e3d69..6aa0d634 100644 --- a/cosipy/spacecraftfile/SpacecraftFile.py +++ b/cosipy/spacecraftfile/SpacecraftFile.py @@ -201,7 +201,7 @@ def source_interval(self, start, stop): Parameters ---------- start : astropy.time.Time - The star time of the orientation period. + The start time of the orientation period. stop : astropy.time.Time The end time of the orientation period. diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index 2b49e90d..97c6392c 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -8,12 +8,12 @@ { "data": { "text/html": [ - "
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        "                  require the C/C++ interface (currently HAWC)                                                     \n",
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        "                  performances in 3ML                                                                              \n",
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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        "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
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@@ -253,7 +253,7 @@
        "
\n" ], "text/plain": [ - "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=409889;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=56883;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=663334;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=323356;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mperformances in 3ML \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" ] }, @@ -295,77 +295,79 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "# Set initial conditions\n", - "nbins = 5\n", - "sigma_rsp = 1" + "sigma_rsp = 1.414" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Creating example response file" + "### Creating example spectral response file" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 85, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[0. , 0. , 0. , 0.11, 0.89],\n", - " [0. , 0. , 0.11, 0.79, 0.11],\n", - " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", - " [0.11, 0.79, 0.11, 0. , 0. ],\n", - " [0.89, 0.11, 0. , 0. , 0. ]])" + "array([[0. , 0. , 0.01, 0.1 , 0.28],\n", + " [0. , 0.01, 0.1 , 0.28, 0.1 ],\n", + " [0.01, 0.1 , 0.28, 0.1 , 0.01],\n", + " [0.1 , 0.28, 0.1 , 0.01, 0. ],\n", + " [0.28, 0.1 , 0.01, 0. , 0. ]])" ] }, - "execution_count": 3, + "execution_count": 85, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Set initial conditions\n", + "nbins = 5\n", + "\n", "Ei = np.linspace(507, 515, nbins)\n", "\n", "R = np.zeros((5,5))\n", "for i in np.arange(5):\n", " Z = gaussian(x=Ei[i], center=Ei, sigma=sigma_rsp)\n", - " R[i, :] = np.round(Z / np.sum(Z), 2)\n", + " # R[i, :] = np.round(Z / np.sum(Z), 2)\n", + " R[i, :] = np.round(Z, 2)\n", "\n", - "adjust = 1 - np.sum(R, axis=0)\n", - "for i in range(nbins):\n", - " if np.abs(adjust[i]) < 0.001:\n", - " continue\n", - " elif np.abs(adjust[i]) - 0.01 < 0.001:\n", - " R[i, i] += adjust[i]\n", - " elif np.abs(adjust[i]) - 0.02 < 0.001:\n", - " R[[i-1,i+1], i] += adjust[i] / 2\n", - " else:\n", - " print(i, adjust[i])\n", - " raise\n", + "# adjust = 1 - np.sum(R, axis=0)\n", + "# for i in range(nbins):\n", + "# if np.abs(adjust[i]) < 0.001:\n", + "# continue\n", + "# elif np.abs(adjust[i]) - 0.01 < 0.001:\n", + "# R[i, i] += adjust[i]\n", + "# elif np.abs(adjust[i]) - 0.02 < 0.001:\n", + "# R[[i-1,i+1], i] += adjust[i] / 2\n", + "# else:\n", + "# print(i, adjust[i])\n", + "# raise\n", "\n", "R[::-1, :]" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 86, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([1., 1., 1., 1., 1.])" + "array([0.39, 0.49, 0.5 , 0.49, 0.39])" ] }, - "execution_count": 4, + "execution_count": 86, "metadata": {}, "output_type": "execute_result" } @@ -376,58 +378,108 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# TODO: How to expand bincenters to bin edges using numpy?\n", - "# Search key: np.arange(506, 517, 2)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, + "execution_count": 87, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Axis NuLambda has 3 bins\n", + "Axis NuLambda has 48 bins\n", "Axis Ei has 5 bins\n", "Axis Em has 5 bins\n" ] }, { "data": { + "text/latex": [ + "$[[[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]],~\n", + "\n", + " [[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]],~\n", + "\n", + " [[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]],~\n", + "\n", + " \\dots,~\n", + "\n", + " [[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]],~\n", + "\n", + " [[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]],~\n", + "\n", + " [[0.28,~0.1,~0.01,~0,~0],~\n", + " [0.1,~0.28,~0.1,~0.01,~0],~\n", + " [0.01,~0.1,~0.28,~0.1,~0.01],~\n", + " [0,~0.01,~0.1,~0.28,~0.1],~\n", + " [0,~0,~0.01,~0.1,~0.28]]] \\; \\mathrm{cm^{2}}$" + ], "text/plain": [ - "array([[[0.89, 0.11, 0. , 0. , 0. ],\n", - " [0.11, 0.79, 0.11, 0. , 0. ],\n", - " [0. , 0.1 , 0.78, 0.1 , 0. ],\n", - " [0. , 0. , 0.11, 0.79, 0.11],\n", - " [0. , 0. , 0. , 0.11, 0.89]],\n", + "" ] }, - "execution_count": 6, + "execution_count": 87, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "h = Histogram([np.arange(4), np.arange(506, 517, 2), np.arange(506, 517, 2)], contents=np.stack([R, R, R]), labels=['NuLambda', 'Ei', 'Em'])\n", + "NuLambdalen = 48\n", "\n", + "h = Histogram([np.arange(NuLambdalen + 1), np.linspace(506, 516, 6)*u.keV, np.linspace(506, 516, 6)*u.keV], contents=np.tile(R, (NuLambdalen, 1, 1)), unit=u.cm**2, labels=['NuLambda', 'Ei', 'Em'])\n", "for axis in h.axes:\n", " print(f\"Axis {axis.label} has {axis.nbins} bins\")\n", "\n", @@ -436,23 +488,23 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 88, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(,\n", - " )" + "(,\n", + " )" ] }, - "execution_count": 7, + "execution_count": 88, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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vqVq1am7H7WkkRQAAwGURERFatGiRIiIi9OOPP2ro0KFllps/f77y8/P1zjvvKDo6WpLUpEkTjRw5UsuXL1evXr0qMuzLYkwRAAAWV7z3mZmPqwIDAxUREXHFcl9++aVuv/12Z0IkSa1bt1a9evW0bt06l+/rTbQUAQBgcYbJ2WfGv+tmZmaWOB4REaHIyEi3r3vixAmdPn1ajRo1KnWuSZMm+n//7/+5fW1vICkCAMDi3G3t+X19SZowYUKJ4ykpKRo8eLDb183KypKkMluUIiIidPbsWV24cEGBgYFu38OTSIoAAIAkaezYsYqNjXV+L0/32OWcP39eksocTF2cCJ0/f56kCAAAeIYhc7PPirvPYmNjy+zqcldQUJAkqaCgoNS5CxculCjjC0iKAACwOE91n3lacUtTcTfa72VlZSksLMxnWokkZp8BAAAvufbaaxUeHq69e/eWOrdnzx7FxcVVQlSXRlIEAIDFFe99ZubjLUlJSfr666917Ngx57Fvv/1Whw4dUqdOnbx2X3fQfQYAgMUZJrvPDDfrLly4UNnZ2c7usY0bN+r48eOSpOTkZNWoUUMDBgzQv/71L/3P//yP+vbtq7y8PH344Ye68cYby9wSpDKRFAEAALcsWLBAv/76q/P7+vXrtX79eklSly5dVKNGDUVHR+v111/XtGnT9NZbbzn3Pnv88cd9ajyRRFIEAIDlOQxzg6Udhnv10tPTy1Wufv36+sc//uHeTSoQSREAABZXWd1nVQ0DrQEAAERLEQAAlueQTTYz3WdenH1mJSRFAABYnEM22UwkNiRFRUiKAACwOMYUeQZjigAAAERLEQAAlucwbJIP7n1mNSRFAABYnGFynSLDzXWKqhq6zwAAAERLEQAAlucwzE3JZ6B1EZIiAAAszpC5MUUGU/Il0X0GAAAgiZYiAAAsz5DNZGsPLUUSSREAAJZndkq+DBtdR6L7DAAAQBItRQAAWJ5hyGRLkcdCsTSSIgAALM4T3Wf+ngvHskiKAACwOsNmaq0hM2scVSWMKQIAABAtRQAAWJ5DJluKmJIviaQIAADLMwyTm7oy0FoS3WcAAACSaCkCAMDyDNnkMNEF5kf3mSSSIgAALK+o+8zEhrB0n0mi+wwAAEASLUUAAFiew7AVLeDoLtYpkkRSBACA5ZmdfUb3WRG6zwAAAERLEQAAVYC5xRvF7DNJJEUAAFieYXLvM3MJVdVBUgQAgMWZHWjNhrBFGFMEAAAgWooAALA8Zp95BkkRAABWZ3JFazaELUL3GQAAgGgpAgDA8gyTU/INpuRLIikCAMDyDJnrAaP3rAjdZwAAAKKlCAAAy2PxRs/wuaRo27ZtGjFiRJnnZsyYoaZNm0qSNm/erLVr12rPnj3KzMxUVFSU0tPTS9XJzMzUsmXLtGXLFh0+fFghISGKj4/X4MGD1bhxY68+CwAAFYL+M48oV1L0t7/9zfSNEhISlJCQUO7yycnJatKkSYljdevWdf68evVqrV27VvHx8YqIiLjkdT7//HMtXbpUSUlJ6tOnj3JycrR48WINHz5ckyZNUuvWrV1/GAAAfAgtRZ5RrqRo+fLlpm5is9l03XXXuZQUtWzZUh07drzk+aFDh2rUqFEKCAjQ6NGjdeDAgTLLde7cWYMGDVL16tWdx+655x4NHDhQc+bMISkCAMANhw4d0qxZs7Rz506dPXtW0dHR6ty5s/r376/g4ODKDs8t5e4+u//++9W3b1+Xb2AYhvr37+9yPUnKzc1VYGCgAgJKhxkZGVmuazRq1KjUsZo1a6pFixbavn27W3EBAOBTTK5o7Wr32bFjxzRs2DDVqFFD9957r8LCwrRr1y7Nnj1be/fuVVpamolgKk+5k6IaNWrouuuu82YsJaSlpSkvL0/+/v5q0aKFhg8f7tExQKdOnVLNmjUvW+bkyZPKyspyfs/MzPTY/QEA8JSKXqdo5cqVys7O1htvvKH69etLknr16iWHw6EVK1bo3Llzuuaaa9yOp7KUKykaOXKkqYTElfoBAQFKSkpSu3btVLNmTR08eFALFixQamqqpk+frvj4eLfjKLZjxw7t2rVLDz/88GXLLV68WHPnzi113D+0uvz8rNk0WJmOpjSv7BAsbduzMyo7BMtqlTa8skOwrDpzd1Z2CNY2pbID8I6cnBxJUq1atUocj4iIkJ+fX5k9PFZQrqh79+5t6iau1G/evLmaN//PL8+EhAR17NhRgwYN0syZMzV58mRTsZw+fVrjx49XnTp19OCDD162bK9evdS+fXvn98zMTE2YMMHU/QEA8DhDkgf2Pru4RyQiIqLM4SqtWrXSBx98oJdfflmDBw9WWFiYfvjhB3322WdKTk5WSEiI+7FUonKncmvWrFGHDh1UrVo1b8ZTppiYGCUkJGj9+vWy2+3y9/d36zp5eXkaPXq08vLyNGnSpBKDr8sSGRlZ7rFLAABUFsPkmKLiuhf/wz8lJUWDBw8uVb5t27Z69NFHNX/+fG3cuNF5fODAgRoyZIj7gVSycidF48ePV1hYmDp37qzu3bsrLi7Om3GVEhUVpYKCAuXn5ys0NNTl+gUFBRo7dqx+/vlnTZ48WTfeeKMXogQAwLrGjh2r2NhY5/fLLXlTp04dtWzZUklJSQoLC9M333yj+fPnq3bt2kpOTq6IcD2u3EnRnXfeqQ0bNuif//ynFi1apPj4eHXv3l133nmnatSo4c0YJUlHjhxRYGCgW01yDodDL730kr777ju98MILuvnmmz0fIAAAlcVDizfGxsaWOWv7YmvWrNGkSZP0/vvvKyoqSpKUlJQkwzD01ltvqXPnzleczOSLyr332fPPP69FixbpySefVHx8vPbu3atXX31V9913nyZMmKBt27Z5JKAzZ86UOrZ//35t3LhRbdq0kZ+f69u1vfbaa1q7dq2efPJJJSUleSBKAAB8R/HijWY+rli0aJEaNmzoTIiKtW/fXvn5+crIyPDk41UYl4aHh4aGqk+fPurTp48OHDigpUuXatWqVVq1apVWr16tOnXq6J577lHXrl117bXXuhXQuHHjFBQUpGbNmqlWrVo6ePCglixZouDgYA0bNsxZ7qefftKGDRskSYcPH1Z2drbeffddSVJcXJxzgHR6ero+/fRTNW3aVMHBwVq5cmWJ+yUmJlp2QBgAAJXh9OnTZU65LywslCTZ7faKDskj3J4zV79+faWmpuqPf/yjNm7cqGXLlmnz5s165513NHv2bLVp00bdu3d3uWUmMTFRq1atUnp6unJychQeHq4OHTooJSVFMTExznL79u3TrFmzStQt/t61a1dnUrR//35J0q5du7Rr165S91uwYAFJEQDA+ipw/7J69eppy5YtOnTokOrVq+c8vmbNGvn5+alBgwYVF4wHmV5IoHhdoaSkJGVlZWnFihVatmyZNm3apC1btmjdunUuXa9v377lWjm7W7du6tat2xXLjRkzRmPGjHEpBgAArKSi9z7r37+/Nm3apNTUVN13330KCwvT119/rU2bNqlHjx6Wnbnt0dWVzp07p9OnTys7O1tS0RYfAADAyzw00Lq8br75Zr3xxhuaM2eOFi1apLNnz6pOnToaMmTIFdcA9GWmk6Lc3FytWbNGy5Yt0549e2QYhoKDg3X33Xere/funogRAAD4mJtuukmTJk2q7DA8yu2kaPv27Vq6dKnWr1+v8+fPyzAMNW7cWN27d1fnzp2vuDAiAADwFNu/P2bqw6Wk6MSJE1q+fLmWL1+uo0ePyjAMhYWFqUePHurevTsLIgIAUBkquPusqip3UvT0009r69atcjgcstlsuuWWW9S9e3clJiZWytYfAACg6vviiy9MX6Nhw4blmhFX7qRo8+bNio6OVrdu3XTPPfcoOjraVIAAAMBDqnBLUVpammw297r3DMOQzWZTSkqKZ5OiyZMnq3Xr1m4HBgAAvMSwFX3M1Pdh7du3V0JCglt1//a3v5W7bLmTojZt2pR5/ODBg8rMzFR+fr7uvvvuct8YAACgPBo2bFiutQnL4pWk6GJ79uzRpEmT9PPPPzuPFSdF27dv19NPP61x48a5ndkBAIDyq6pLA95xxx2qX79+hdR3Kyk6cOCA/ud//kd+fn66//779X//93/atGmT83zLli1Vs2ZN/etf/yIpAgDA26rwmKJx48ZVWH3Xt5yXNHv2bEnS22+/rccff1yNGzcucd5ms6lp06b68ccf3bk8AABAhXMrKdq+fbuSkpJKbNB6sejoaGVlZbkdGAAAKCdD/xls7dansh/AN7iVFOXl5alWrVqXLXP+/Hk5HA63ggIAAC4wJJuJj1WSoqysLH355ZfasGGDzp07d8ly27dv19y5c12+vltjiq699toSA6zLsm/fPl1//fXuXB4AALiiCo8pKvbRRx/pnXfeUWFhoSQpMDBQAwcO1IABA0otF7Rt2za9++67SklJcekebrUU3X777dqyZYu2bt1a5vm1a9dq9+7dSkxMdOfyAAAATps3b9aMGTMUGBioHj16qE+fPqpevbpmzZqlZ555RhcuXPDIfdxqKRo4cKD+9a9/adSoUeratatOnTolSVq0aJF27dqlNWvW6LrrrtMDDzzgkSABAMDlmFy80cc3hP34448VHByst956S/Xq1ZMkDR06VJMnT9aaNWv0zDPPKC0tTUFBQabu41ZLUXh4uKZOnarGjRtr6dKl+uabb2QYhl577TWtWrVKjRs31muvvaYaNWqYCg4AAJSD4YGPD/vxxx/VoUMHZ0IkSdWrV9fzzz+v//7v/9a3336rZ555RufPnzd1H7cXb7z++us1ffp0ZWRkaPfu3Tp79qyqV6+um266SU2aNDEVFAAAQLG8vDxFRUWVeW7YsGHy9/fXvHnzNHr0aL388stu38etpGj9+vXq0KGDpKKltxs2bFhmualTp+qJJ55wOzgAAFAOVXygdWRkpE6cOHHJ84899pgkad68eRo1apQaNWrk1n3c6j578cUXtWPHjsuWmTp1qhYuXOhWUAAAwAVVvPusfv36+vbbby9b5rHHHtPAgQO1fft2t/MPt5Ki66+/Xs8+++wlp+VPmzZNn3zyCVt8AAAA02677TadPHlS33zzzWXLPfbYY3r44Yed0/Zd5Vb32aRJk/SnP/1JTz/9tKZPn67o6GjnuenTp+vjjz9WQkKC/vrXv7oVFAAAcIFhcvaZqZlr3texY0cZhqHg4OArln300Ud1/fXX69dff3X5Pm61FEVFRWny5Mk6f/68/vd//1e//fabpKKEaMGCBbr99tv117/+Vf7+/u5cHgAAuMAmcyta+3ZKJIWFhal3795q1apVucp369ZNgwYNcvk+biVFknTDDTfo5Zdf1okTJ/T0009r2rRpWrBggW677Ta9+OKLCghwe2IbAABAhTOVuTRt2lQvvPCC/vKXv2jfvn1q166dJkyYQEIEAEBFquKzz8qSkZGh/fv3Kysrq8wxRDabTY888ohL1yxX9vLFF19c9nybNm20e/dutW/fXqtXry5xrmvXri4FBAAAcCmnT5/W+PHjtW3bNkmSYZSd0XktKUpLSyu12VpxIDabzRnQK6+8UuKYzWYjKQIAwMucu92bqG8Vr776qr777ju1a9dOd955pyIiIjw2hrlcSdEzzzzjkZsBAACYsXnzZrVq1crUytWXUq6kqFu3bh6/MQAA8JAqPiX/9wICAtxesfqK1/bKVQEAQMW5igZat2jRQhkZGV65drmm5BcUFMjhcLh9E7P1AQAAJGno0KHau3evV7YSK1dL0V133aVBgwa5PIrbU/UBAMAVWKi1x4wbbrhB06ZNU2pqqhYuXKgGDRooNDS0zLKujokuV1JkGMYlp7xVRH0AAHBpV9PssyNHjmjMmDHKzs5Wdna2Dh8+XGY5m83mnaRIkpYvX+5cE8BVZU3nBwAAcNWUKVN05MgR9e7dW507d674KfmS9Ouvv7q1uRoAAPCyq2ig9Y4dO3T77bdr5MiRHr92uZKiL7/80uM3BgAAHnIVJUXVqlVTvXr1vHJttzeEBQAAqGht2rTRDz/84JVrkxQBAGBxxQOtzXys4k9/+pOysrI0ffp0nT9/3qPXZvFGAAAsz+SK1rLOhKgXX3xRNWrUUHp6upYsWaKYmBhVr169VDmbzabXXnvNpWuTFAEAYHVX0Zii7du3O3/Ozc3Vvn37yiznzsx3kiIAAGAZ3pz8RVIEAIDVmR0XZKGWIm9ioDUAAFZneOBjEXa7XTk5OZfcU7X4vN1ud/naJEUAAMAte/fu1TPPPKPu3bvrrrvu0iOPPKJPPvnEq/ecO3euevfurbNnz5Z5/ty5c+rdu7fmzZvn8rVNdZ9lZGRo//79ysrKUmFhYanzNpuNTWABAPCyytj7bPPmzXr22WfVsGFDPfLIIwoJCdHhw4d14sQJ9wMph6+//lr/9V//pfDw8DLPh4eHq3Xr1tqwYYNSUlJcurZbSdHp06c1fvx4515ol9rslaQIAIAKUoFdYDk5OZo4caLatWunF198UX5+FdfxdPToUbVq1eqyZerVq6edO3e6fG23kqJXX31V3333ndq1a6c777zTo5uxAQAA37Z69WqdOnVKQ4YMkZ+fn/Ly8hQUFFQhyVFhYeEV72Oz2XThwgWXr+1WUrR582a1atVKL7/8sjvVAQCAJ3lonaLMzMwShyMiIhQZGVmq+NatWxUaGqqTJ0/qL3/5iw4dOqSQkBB16dJFqampCgoKMhHM5dWtW1fffffdZct89913qlOnjsvXdispCggIUKNGjdypCgAAPMxTY4omTJhQ4nhKSooGDx5cqvwvv/wiu92uMWPGqHv37ho6dKi2b9+uhQsXKjs7W+PGjXM/mCvo0KGD3n33Xc2aNUspKSkleqrsdrvmzJmj/fv36+GHH3b52m4lRS1atFBGRoY7VQEAgI8aO3asYmNjnd8jIiLKLJeXl6f8/Hz17t1bI0aMkCQlJSWpoKBAixcv1uDBg722k32/fv20Zs0azZs3T2vWrFGrVq107bXX6sSJE9q2bZuOHDmi2NhY9e/f3+Vru9X5N3ToUO3du1cLFy50pzoAAPBBsbGxatSokfNTVteZJGf32J133lnieOfOnSVJu3bt8lqM1atX17Rp05SYmKgjR47o888/15w5c/T555/r6NGjSkpK0uuvv17mfmhX4lZL0Q033KBp06YpNTVVCxcuVIMGDRQaGlpm2WeeecadWwAAgPKq4L3PIiIidODAAdWuXbvE8Vq1akkqWivIm8LDw/Xiiy/q1KlT2rt3r7Kzs1WjRg01btzYGYM73EqKjhw5ojFjxig7O1vZ2dk6fPhwmeVsNhtJEQAAXlbR6xQ1atRIW7du1YkTJ/SHP/zBefzkyZOSdMk1hDytdu3auu222zx2PbeSoilTpujIkSPq3bu3OnfuzJR8AACuIp06ddL777+vpUuX6pZbbnEeX7p0qfz9/a+4jpArxo8fr6SkJCUlJXm9vltJ0Y4dO3T77bdr5MiR7lQHAACeVoGLN8bHx+uee+7RsmXLZLfbdfPNN2v79u1at26dBgwYcMmxSO5Ys2aN/vCHP7idFLlS362kqFq1al4bVQ4AAFxUwWOKJOmpp55SdHS0li9frq+++krR0dFKTU3VAw88YCKQsmVkZOiLL77w+HUv5lZS1KZNG/3www+ejgUAAFhEQECABg0apEGDBnn9Xhs2bNDGjRtdrnepbcguxa2k6E9/+pMef/xxTZ8+XY8++qhXV64EAACXVxkbwlYUT0zYatiwYbnKuZUUvfjii6pRo4bS09O1ZMkSxcTElLkegM1m02uvvebOLQAAQHlVQvdZRenWrVuF3cutpGj79u3On3Nzc7Vv374yy9lsNreCAgAAqGhuJUVffvmlp+Nw2rZtm3PJ8IvNmDFDTZs2lVS0Ke3atWu1Z88eZWZmKioqSunp6WXWczgc+uijj/Tpp5/q1KlTiomJ0YABA5wrbwIAYGkmu898uaWoIrmVFFWE5ORkNWnSpMSxunXrOn9evXq11q5dq/j4+EvuzVLs7bff1vvvv6+ePXuqcePG2rBhg8aPHy+bzVZqiXIAACyJxMY0ryVFBQUFunDhwiW3/7iSli1bqmPHjpc8P3ToUI0aNUoBAQEaPXq0Dhw4UGa5EydOaMGCBbr33nv15JNPSpJ69OihJ554QtOnT1fHjh1ZeBIAAJR/Q9h+/frpk08+KXFs8+bNmjZtWpnl58+fr+7du5sKLjc3V4WFhWWei4yMVEDAlXO6DRs2qLCwUPfee6/zmM1mU58+fXTixAmvbloHAECFMDzwQflbin799VdlZ2eXOLZr1y598sknSk1N9XhgaWlpysvLk7+/v1q0aKHhw4ercePGLl8nIyNDISEhio2NLXG8uGsuIyNDLVq0KLPuyZMnlZWV5fyemZnp8v0BAPC2qjwlvyL53JiigIAAJSUlqV27dqpZs6YOHjyoBQsWKDU1VdOnT1d8fLxL18vKylKtWrVKzYQrHodUvHldWRYvXqy5c+eWOn6iZ0M5qoe7FAekbc/OqOwQLK1V2vDKDsGy6szdWdkhWJbdy7udw0Oq8JT8iuRzSVHz5s3VvHlz5/eEhAR17NhRgwYN0syZMzV58mSXrnf+/HlVq1at1PHAwEDn+Uvp1auX2rdv7/yemZmpCRMmuHR/AABgDT6XFJUlJiZGCQkJWr9+vex2u0sDo4OCglRQUFDq+IULF5znLyUyMtKjm9oBAOAVtBR5RLkHWle2qKgoFRQUKD8/36V6EREROnXqVKn9T4rHCpH0AACszqb/jCty61PZD+AjLJMUHTlyRIGBgQoJCXGpXlxcnPLz80sNkt69e7fzPAAAgEvdZytXriwxhf3w4cOSpKeffrpU2eJzrjpz5ozCw8NLHNu/f782btyotm3bys/PtTwuISFB06ZN06JFi5zrFBmGoc8++0zXXnutmjVr5lacAAD4DLrPPMKlpOjw4cNlJjubN28us7w7e5+NGzdOQUFBatasmWrVqqWDBw9qyZIlCg4O1rBhw5zlfvrpJ23YsMEZV3Z2tt59911JRa0/xQOko6KidP/99+vDDz9UYWGhmjRpoq+++krff/+9nnvuORZuBABYHlPyPaPcSdGCBQu8GYdTYmKiVq1apfT0dOXk5Cg8PFwdOnRQSkqKYmJinOX27dunWbNmlahb/L1r164lZo0NGzZM11xzjRYvXqwvvvhCMTExGjt2rO66664KeSYAAOD7yp0UXXfddd6Mw6lv377q27fvFct169ZN3bp1K9c1/fz8NGDAAA0YMMBseAAA+B66zzzCElPyAQDAZZAUeYRlZp8BAAB4Ey1FAABYnE3m1hpinaIiJEUAAFQFdIGZRlIEAIDVmZyST0JVhDFFAAAAoqUIAADrY/aZR5AUAQBgdSRFHkH3GQAAgGgpAgDA8tj7zDNIigAAsDq6zzyC7jMAAADRUgQAgOXZZLL7zGORWBtJEQAAVkf3mUfQfQYAACBaigAAsDxmn3kGSREAAFZH95lHkBQBAGB1JEUewZgiAAAA0VIEAIDlMSXfM0iKAACwOrrPPILuMwAAANFSBACA9RmGbIaJ5h4zdasQkiIAAKyO7jOPoPsMAACY9t5776lDhw565JFHKjsUt9FSBACAxdlMthSZXdH6+PHjmj9/vkJCQsxdqJKRFAEAUBVUYhfY9OnTddNNN8nhcOi3336rvEBMovsMAAC4bfv27fryyy/1xBNPVHYoptFSBACAxXmq+ywzM7PE8YiICEVGRl6ynt1u15QpU9S9e3c1aNDA/QB8BEkRAABW56HZZxMmTChxOCUlRYMHD75ktc8++0zHjh3Tq6++auLmvoOkCAAAi/NUS9HYsWMVGxvrPB4REXHJOr/99ptmz56thx9+WOHh4e7f3IeQFAEAAElSbGysGjVqVK6y77zzjq655holJyd7OaqKQ1IEAIDVVfDijYcOHdKSJUv0xBNP6OTJk87jFy5cUGFhoY4eParQ0FCFhYWZCKrikRQBAGBxNslc95mL5U+ePCmHw6EpU6ZoypQppc7369dPffv21Z///Gf3g6oEJEUAAMAl9evX10svvVTq+DvvvKPc3Fz9+c9/1vXXX18JkZlDUgQAgNUZhrlNXV2sGx4ersTExFLHP/74Y0kq85wVkBQBAGB1hsmtOtgQVhJJEQAA8JDXX3+9skMwhaQIAACrq+DZZ1UVSREAABZnMyQ5TFyApEgSG8ICAABIoqUIAADro/vMI0iKAACwOLN7n5EUFSEpAgDA6ip4naKqijFFAAAAoqUIAADLo/vMM0iKAACoCkhsTKP7DAAAQLQUAQBgeXSfeQZJEQAAVsfsM4+g+wwAAEC0FAEAYHl0n3kGSREAAFZHUuQRdJ8BAACIliIAAKoEm5lx1p4Lw9JIigAAsDqHzGVFDo9FYmkkRQAAWB1jijyCMUUAAACipQgAAMuzGeZ6z2TQWCSRFAEAUAWYXNGalEiSDyZF27Zt04gRI8o8N2PGDDVt2tT5fefOnXrzzTe1b98+hYaGqlOnThoyZIiqV69eot6hQ4c0a9Ys7dy5U2fPnlV0dLQ6d+6s/v37Kzg42KvPAwAArMHnkqJiycnJatKkSYljdevWdf6ckZGhJ598UrGxsUpNTdXx48e1YMEC/fLLL5o0aZKz3LFjxzRs2DDVqFFD9957r8LCwrRr1y7Nnj1be/fuVVpaWoU9EwAA3kD3mWf4bFLUsmVLdezY8ZLnZ86cqWuuuUavv/66QkNDJUl16tTR3//+d23evFm33nqrJGnlypXKzs7WG2+8ofr160uSevXqJYfDoRUrVujcuXO65pprvP48AAB4DbPPPMKnZ5/l5uaqsLCw1PGcnBxt3bpVXbp0cSZEknT33XcrJCRE69atK1FWkmrVqlXiGhEREfLz81NAgM/mhQAAoAL5bEaQlpamvLw8+fv7q0WLFho+fLgaN24sSfr5559lt9vVqFGjEnWqVaumhg0bKiMjw3msVatW+uCDD/Tyyy9r8ODBCgsL0w8//KDPPvtMycnJCgkJuWQMJ0+eVFZWlvN7Zmamh58SAADzbIYhm5mB1qYGaVcdPpcUBQQEKCkpSe3atVPNmjV18OBBLViwQKmpqZo+fbri4+OdiUpERESp+hEREdqxY4fze9u2bfXoo49q/vz52rhxo/P4wIEDNWTIkMvGsnjxYs2dO7fU8Q8Hfaz4G0u3YOHyWqUNr+wQLK3O3J2VHYJl2c+dq+wQAO8yZG5VanIiST6YFDVv3lzNmzd3fk9ISFDHjh01aNAgzZw5U5MnT9b58+clFbUMXSwwMFAXLlwocaxOnTpq2bKlkpKSFBYWpm+++Ubz589X7dq1lZycfMlYevXqpfbt2zu/Z2ZmasKECWYfEQAA+CCfS4rKEhMTo4SEBK1fv152u11BQUGSpIKCglJlL1y4oMDAQOf3NWvWaNKkSXr//fcVFRUlSUpKSpJhGHrrrbfUuXNn1axZs8z7RkZGKjIy0gtPBACA59gMQzYzzT10n0ny8YHWvxcVFaWCggLl5+c7u81+P96nWFZWVolEZtGiRWrYsKEzISrWvn175efnlxh/BACAJRke+MA6SdGRI0cUGBiokJAQ1a9fX/7+/tq7d2+JMgUFBcrIyFBcXJzz2OnTp+VwlO5oLZ7VZrfbvRs4AADeZhjmP/C9pOjMmTOlju3fv18bN25UmzZt5Ofnpxo1aqh169ZauXKlcnNzneVWrFihvLw8derUyXmsXr16ysjI0KFDh0pcc82aNfLz81ODBg289iwAAMA6fG5M0bhx4xQUFKRmzZqpVq1aOnjwoJYsWaLg4GANGzbMWe6xxx7T448/rieeeEK9evVyrmjdpk0btW3b1lmuf//+2rRpk1JTU3XfffcpLCxMX3/9tTZt2qQePXowZggAYH2GZDNTnYYiST6YFCUmJmrVqlVKT09XTk6OwsPD1aFDB6WkpCgmJsZZrlGjRnrllVf05ptvaurUqapevbq6d+9eInGSpJtvvllvvPGG5syZo0WLFuns2bOqU6eOhgwZogcffLCiHw8AAO8gszHN55Kivn37qm/fvuUq26JFC02fPv2K5W666aYS+6EBAABczOeSIgAA4Bqbw1z3mU3ywVHGFY+kCAAAqzPYEdYTyAsBAABESxEAANZHQ49HkBQBAGBxZrf5MLVFSBVCUgQAAFyyZ88effHFF9q2bZt+/fVXhYWFqWnTpnrsscdUr169yg7PbSRFAABYnsmtOmyu1f3ggw+0c+dOderUSQ0aNFBWVpYWLVqkxx57TDNmzNCNN97ofiyViKQIAACrc8jcuCIX5/M/8MADev7551WtWjXnsTvuuEODBg3S+++/r+eee85EMJWHpAgAAIuzGYZsJlqKXB1T1Lx581LH6tWrpxtuuEGZmZlux1HZSIoAAIAklUpoIiIiyr1HqGEYOn36tG644QYvRFYxSIoAALA6Qx7Z+2zChAklvqekpGjw4MHlqrtq1SqdOHGi3OV9EUkRAACW55mB1mPHjlVsbKzzcERERLmqZ2Zm6tVXX1XTpk3VtWtX9+OoZCRFAABAkhQbG6tGjRq5VCcrK0ujR49WaGioXnzxRfn7+3spOu8jKQIAwOoc//5UsOzsbI0aNUrZ2dmaNm1auccf+SqSIgAALM707DM36p4/f17PPPOMDh06pFdeecXSA6yLkRQBAACX2O12vfDCC9q1a5cmTpyoZs2aVXZIHkFSBACA1RkmB1q7WPeNN97Qxo0bdfvtt+vcuXNauXJlifNdunRxP5ZKRFIEAIDlmUyKXFy8cf/+/ZKkr7/+Wl9//XWp8yRFAADgqvD6669XdgheQVIEAIDVmV280fy6j1UCSREAAFZndkq+ixvCVlUkRQAAWJ3JKfme2CKkKvCr7AAAAAB8AS1FAABYXsXOPquqSIoAALA6h1H0MVMfdJ8BAABItBQBAGB9FbyidVVFUgQAgNWxTpFH0H0GAAAgWooAAKgCmH3mCSRFAABYHbPPPILuMwAAANFSBACA9RmOoo+Z+iApAgDA8ph95hEkRQAAWJ1hckwR6xRJYkwRAACAJFqKAACwPla09giSIgAArI6kyCPoPgMAABAtRQAAWB8tRR5BUgQAgNUZhuQws04RSZFE9xkAAIAkWooAALA+us88gqQIAACrIynyCLrPAAAAREsRAADWxzYfHkFSBACA1RmGDDM73ZMUSSIpAgDA+hwmW4rM1K1CGFMEAAAgWooAALA+Zp95BEkRAABWZzhMrmhtom4VQvcZAACAaCkCAMD6DJnsPvNYJJZGUgQAgMUZDocME91nZupWJXSfAQAAiJYiAACsj9lnHkFSBACA1bHNh0fQfQYAACBaigAAsD7DMLfWEC1FkkiKAACwPMNhyDDRfWamblXic0nRtm3bNGLEiDLPzZgxQ02bNnV+37lzp958803t27dPoaGh6tSpk4YMGaLq1auXqrt3717NmTNHO3fu1IULF3T99derZ8+e6tu3r9eeBQCAiuEwuSq163UvXLigWbNmaeXKlTp37pwaNGigxx57TG3atDERR+XyuaSoWHJyspo0aVLiWN26dZ0/Z2Rk6Mknn1RsbKxSU1N1/PhxLViwQL/88osmTZpUot7mzZv17LPPqmHDhnrkkUcUEhKiw4cP68SJExXyLAAAVDVpaWn617/+pfvvv18xMTFavny5Ro0apSlTpqhFixaVHZ5bfDYpatmypTp27HjJ8zNnztQ111yj119/XaGhoZKkOnXq6O9//7s2b96sW2+9VZKUk5OjiRMnql27dnrxxRfl58fYcgBA1WI4zHWBudrItHv3bq1Zs0bDhw/Xgw8+KEm6++67lZKSohkzZmjGjBlux1KZfDpDyM3NVWFhYanjOTk52rp1q7p06eJMiKSi/0NCQkK0bt0657HVq1fr1KlTGjJkiPz8/JSXlycHK3cCAKoSw2H+44Ivv/xS/v7+6tWrl/NYUFCQunfvrl27dunYsWOefsIK4bMtRWlpacrLy5O/v79atGih4cOHq3HjxpKkn3/+WXa7XY0aNSpRp1q1amrYsKEyMjKcx7Zu3arQ0FCdPHlSf/nLX3To0CGFhISoS5cuSk1NVVBQ0CVjOHnypLKyspzf9+/fL0nKPOzvyUe9avjlnqnsECzNEZJf2SFYlsNRUNkh4Cq1d+9excbGKjg42Kv3MaoXujEqqGR9ScrMzCxxPCIiQpGRkaXKZ2RkKCYmpkTDhCTnsJf9+/crOjraRESVw+eSooCAACUlJaldu3aqWbOmDh48qAULFig1NVXTp09XfHy8M1GJiIgoVT8iIkI7duxwfv/ll19kt9s1ZswYde/eXUOHDtX27du1cOFCZWdna9y4cZeMZfHixZo7d26p4y9NrWX+Qa9C12jdlQvhkvLjKzsCAK4aMmSIJk2apLZt23rl+uHh4QoODlZ+o7OmrxUQEKAJEyaUOJaSkqLBgweXKpuVlXXJ38FSUaOCFflcUtS8eXM1b97c+T0hIUEdO3bUoEGDNHPmTE2ePFnnz5+XVNQydLHAwEBduHDB+T0vL0/5+fnq3bu3c1ZbUlKSCgoKtHjxYg0ePFj16tUrM5ZevXqpffv2zu979uzRK6+8otGjRysuLs4jz3u1yMzM1IQJEzR27FjFxsZWdjiWw/tzH+/Ofbw7c4rfX0hIiNfuER0drXnz5unMmTOmr+VwOEqNuy0r8ZGk8+fPX/J3cPF5K/K5pKgsMTExSkhI0Pr162W3251dXgUFpZvEL1y44Pw/RZKz7J133lmiXOfOnbV48WLt2rXrkklRZGRkmc2GcXFxpbruUD6xsbG8OxN4f+7j3bmPd2fO5YZpeEJ0dHSFd1UFBQVd8ndw8Xkr8umB1r8XFRWlgoIC5efnOzPX34/3KZaVlVUikSkuW7t27RLlatUq6gI7d+6ct0IGAKBKioiIuOTvYEllNihYgWWSoiNHjigwMFAhISGqX7++/P39tXfv3hJlCgoKlJGRUaJrq/hfNxevSVTc3xkeHu7dwAEAqGLi4uL0yy+/KCcnp8Tx3bt3O89bkc8lRWX1i+7fv18bN25UmzZt5Ofnpxo1aqh169ZauXKlcnNzneVWrFihvLw8derUyXms+OelS5eWuObSpUvl7++vVq1alTu2iIgIpaSkXLKPFZfGuzOH9+c+3p37eHfmVOX317FjR9ntdi1evNh57MKFC1q2bJluuukmS848kySbYfjWLnAjRoxQUFCQmjVrplq1aungwYNasmSJAgICNH36dN1www2SiqY5Pv7444qNjVWvXr2cK1q3bNlS//jHP0pc829/+5uWLVumTp066eabb9b27du1bt06DRgwQEOHDq2EpwQAwNrGjRun9evX64EHHlDdunX1xRdfaM+ePXr11Vd18803V3Z4bvG5pOiTTz7RqlWrdPjwYeXk5Cg8PFy33HKLUlJSFBMTU6Ls999/79z7rHr16urUqZOGDRtWau+zwsJCzZs3T8uXL9fJkycVHR2te++9Vw888EBFPhoAAFXG+fPnnXufZWdn68Ybb9Rjjz3m3FHCinwuKQIAAKgMPjemCAAAoDKQFAEAAMgiizd6w7Zt25wrXF9sxowZatq0qfP7zp07nWOXQkND1alTJw0ZMqTU2CWpaAD4nDlztHPnTl24cEHXX3+9evbsqb59+3rtWSqaN97doUOHNGvWLO3cuVNnz55VdHS0OnfurP79+3t9z6CKVN53t3nzZq1du1Z79uxRZmamoqKilJ6eXmY9h8Ohjz76SJ9++qlOnTqlmJgYDRgwQJ07d/bac1QGT7+7zMxMLVu2TFu2bNHhw4cVEhKi+Ph4DR482LnPYlXijT97v7dy5Urn6s0rVqzwaOyVzVvv7vDhw5o1a5a2bt2q3NxcXXvttbrjjjs0ZMgQrzwHruyqTYqKJScnOzewK1a3bl3nzxkZGXryyScVGxur1NRU5yy3X375RZMmTSpRb/PmzXr22WfVsGFDPfLIIwoJCdHhw4dLrZFUVXjq3R07dkzDhg1TjRo1dO+99yosLEy7du3S7NmztXfvXqWlpVXYM1WUK7271atXa+3atYqPj7/idN63335b77//vnr27KnGjRtrw4YNGj9+vGw2W6mV3KsCT727zz//XEuXLlVSUpL69OmjnJwcLV68WMOHD9ekSZPUunVrrz1DZfLkn71iubm5evPNN726nYUv8OS7y8jI0IgRIxQZGal+/fqpZs2aOnbsmI4fP+6V2FFOxlXqu+++MxITE41169ZdttxTTz1l9OnTx8jOznYeW7JkiZGYmGhs2rTJeSw7O9vo3bu3MWbMGMNut3srbJ/g6Xf33nvvGYmJicbPP/9cov6ECROMxMRE4+zZsx6NvzKV992dOHHCKCgoMAzDMEaNGmXcf//9ZZY7fvy40alTJ+OVV15xHnM4HMbjjz9u3HfffUZhYaHHYq9snn53P/74o5GTk1Pi2JkzZ4yePXsaf/rTnzwSsy/x9Pv7vRkzZhgPPfSQMX78eKNLly6eCNenePrd2e124+GHHzaGDRtm5OfnezpcmMCYIhX9K6ewsLDU8ZycHG3dulVdunRRaGio8/jdd9+tkJAQrVv3n13fV69erVOnTmnIkCHy8/NTXl6eHA5HhcRfmTzx7opXRC3eeqVYRESE/Pz8FBBQNRs0L/XupKIl8svz3Bs2bFBhYaHuvfde5zGbzaY+ffroxIkT2rVrl8fi9SWeeHeNGjUq1Y1bs2ZNtWjRQpmZmR6J01d54v0VO3TokD7++GM9/vjj8vf391SIPssT727Lli06cOCAUlJSFBQUpPz8fNntdk+HCjdUzd82LkhLS1NeXp78/f3VokULDR8+3Dme4Oeff5bdbi+1EWK1atXUsGFDZWRkOI9t3bpVoaGhOnnypP7yl7/o0KFDCgkJUZcuXZSammrZzfEux1PvrlWrVvrggw/08ssva/DgwQoLC9MPP/ygzz77TMnJyVWySf5y784VGRkZCgkJKbWDeXETf0ZGhlq0aOGRmH2Fp97dpZw6dUo1a9b02PV8jaff39SpU9WqVSvddtttJf6xUxV56t1t3bpVUtHfh0OGDNHevXtVrVo1JSYmauTIkQoLC/N06CinqzYpCggIUFJSktq1a6eaNWvq4MGDWrBggVJTUzV9+nTFx8c7N7Yrq284IiJCO3bscH7/5ZdfZLfbNWbMGHXv3l1Dhw7V9u3btXDhQmVnZ2vcuHEV9mze5ul317ZtWz366KOaP3++Nm7c6Dw+cODAKjfgsDzvzhVZWVmqVauWbDZbiePF7714j7+qwNPvriw7duzQrl279PDDD3sgYt/ijff3zTffaMuWLZozZ44XIvYdnn53v/zyiyTphRde0K233qqHHnpIP/30k+bPn6/jx4/rjTfeKPXfNCrGVZsUNW/eXM2bN3d+T0hIUMeOHTVo0CDNnDlTkydP1vnz5yUVZfMXCwwM1IULF5zf8/LylJ+fr969eztnKSQlJamgoECLFy/W4MGDVa9ePS8/VcXw9LuTpDp16qhly5ZKSkpSWFiYvvnmG82fP1+1a9dWcnKydx+oApXn3bni/Pnzl3zHxeerCk+/u4udPn1a48ePV506dfTggw+aDdfnePr9FRQUaOrUqerdu7dz+6WqytPvLi8vT5LUuHFjPffcc5KK9hILCgrSzJkz9e2331bZgf6+jjFFvxMTE6OEhARt27ZNdrvd2eVVUFBQquyFCxecv3gkOctePNuneFp0VR3bUczMu1uzZo0mTZqkUaNGqWfPnkpKStIzzzyjrl276q233tJvv/1WYc9RGS5+d64ICgq65DsuPl+VmXl3v5eXl6fRo0crLy9PEydOLHO5jarIzPtLT0/Xb7/9psGDB3spOt9m9r9bqfTvi7vuukuS9MMPP3gmSLiMpOgiUVFRKigoUH5+vrMLorgr6PeysrIUGRnp/F5ctnbt2iXKFQ8ePnfunLdC9hnuvrtFixapYcOGioqKKlGuffv2ys/PLzH+qKr6/btzRUREhE6dOiXjot16it/7799zVeXuuytWUFCgsWPH6ueff9bEiRN14403ejhC3+bO+8vOztZ7772nHj16KCcnR0ePHtXRo0eVl5cnwzB09OhRnT592otR+wZ3/+wV/3d58e+L8PBwSVfH7wtfRVJ0kSNHjigwMFAhISGqX7++/P39tXfv3hJlCgoKlJGRobi4OOex4gHFF69JVDymo/gPe1Xm7rs7ffp0mTP1imd4XA2zMn7/7lwRFxen/Pz8UrOldu/e7Txf1bn77qSihS9feuklfffdd3ruuecsu7O3Ge68v3PnzikvL08ffvih+vXr5/x8+eWXys/PV79+/Uqt41YVuftnr3gM0sW/L4r/MXM1/L7wVVdtUnTmzJlSx/bv36+NGzeqTZs28vPzU40aNdS6dWutXLlSubm5znIrVqxQXl6eOnXq5DxW/PPSpUtLXHPp0qXy9/dXq1atvPMglcDT765evXrKyMjQoUOHSlxzzZo18vPzU4MGDbz2LBWtPO/OFQkJCQoICNCiRYucxwzD0GeffaZrr71WzZo1Mxuyz/D0u5Ok1157TWvXrtWTTz6ppKQkD0Tpuzz5/mrVqqWXXnqp1KdVq1YKDAzUSy+9pAEDBngw+srljf9uAwMDtXz58hL/IPz8888lifFEleiqHWg9btw4BQUFqVmzZqpVq5YOHjyoJUuWKDg4WMOGDXOWe+yxx/T444/riSeeUK9evZyrMrdp00Zt27Z1louPj9c999yjZcuWyW636+abb9b27du1bt06DRgwoEp1Y3j63fXv31+bNm1Samqq7rvvPoWFhenrr7/Wpk2b1KNHj6vy3f3000/asGGDpKKtALKzs/Xuu+9KKmr9ad++vaSi5vv7779fH374oQoLC9WkSRN99dVX+v777/Xcc89VqXVjPP3u0tPT9emnn6pp06YKDg7WypUrS9wvMTGxSi0H4cn3FxwcrMTExFL3+Oqrr/Tjjz+Wec7KPP1nLyIiQgMHDtSsWbP01FNPKTExUfv379fnn3+uzp07l1o1GxXHZlw8GOEq8cknn2jVqlU6fPiwcnJyFB4erltuuUUpKSmKiYkpUfb777937t9VvXp1derUScOGDSs1GLOwsFDz5s3T8uXLdfLkSUVHR+vee+/VAw88UJGP5nXeeHe7d+/WnDlzlJGRobNnz6pOnTrq2rWrHnzwwSq1eGN5393y5csvub1J165dNWbMGOd3h8OhDz74QIsXL1ZWVpZiYmL00EMPqUuXLl5/nork6Xc3ceJEffHFF5e834IFC1SnTh3PPkQl8safvYtNnDhRX375ZZXb+8wb784wDP3zn//UP//5Tx09elS1a9dW165dlZKSUqX+zrOaqzYpAgAA+L2rdkwRAADA75EUAQAAiKQIAABAEkkRAACAJJIiAAAASSRFAAAAkkiKAAAAJJEUAQAASCIpAgAAkERSBFw1HnjggXJvObN8+XJ16NDB+XnhhRdKnP/zn/+sDh06eCFK9/zxj38sEe+2bdsqOyQAFsQGK4AFHT16VP369btsmeuuu07p6emm7pOQkKC4uDjdeOONpq5THuPHj9fq1av1/PPPq3Pnzpcsl5OToz59+qhatWpatGiRgoKC1KNHD916663avn27tm/f7vVYAVRNJEWAhdWtW1d33XVXmedq1KhR4vurr77q8vUTExPVrVs3t2JzVffu3bV69WotW7bssknR6tWrdf78eXXt2lVBQUGSpB49ekiSZs+eTVIEwG0kRYCF1a1bV4MHDy53WV/2X//1X6pTp46+++47HTt2TNHR0WWWW7ZsmaSiJAoAPIkxRcBVwpUxRe5as2aN7rzzTg0aNEgnT550Ht++fbueeeYZ9ezZU3feeacefPBBvf3228rPz3eWsdlsuueee+RwOJyJz8UOHDigPXv2qEGDBmrcuLFXnwXA1YekCIBHLFy4UOPHj9dNN92kqVOnKjIyUpL06aefasSIEdq5c6fatWun5ORkRUVFad68eRo5cqQKCgqc1+jatav8/Py0fPlyGYZR6h60EgHwJrrPAAs7fPiwZs+eXea5pk2bqm3bthUSx9tvv6158+YpMTFRzz//vHOsz8GDBzVlyhQ1aNBAr776qmrWrOmsM3/+fM2cOVMLFy5U//79JUnR0dFq06aNNm3apO+++0633HKLs3xhYaFWrVqlwMBAdenSpUKeC8DVhaQIsLDDhw9r7ty5ZZ7r27ev15Miu92uyZMna+nSperZs6dGjhwpf39/5/nPPvtMdrtdI0aMKJEQSdJ///d/Kz09XWvWrHEmRVJRK9CmTZu0dOnSEknRN998o1OnTqlTp04KCwvz6nMBuDqRFAEWduutt2ry5MmVdv/nnntOGzZs0MCBAzVkyJBS53fv3i1J2rx5s7799ttS5wMCAvR///d/JY4lJCQoPDxcX331lbKzs52z6JYuXSqJrjMA3kNSBMBtO3bsUGBgoNq1a1fm+bNnz0qS5s2bV+5rBgQEqEuXLkpPT9fq1avVp08fZWVladOmTYqOjlbr1q09EjsAXIykCIDbXn31VY0cOVJPP/20Jk2apObNm5c4HxoaKkn64osvVL169XJft0ePHkpPT9fSpUvVp08frVy5Una7Xd26dZOfH/NDAHgHf7sAcFt8fLxee+01VatWTU8//bR27txZ4vxNN90kSdq1a5dL173hhhvUtGlT7d27Vz/99JOWLVvmnLIPAN5CUgTAlLi4OGdi9NRTT+n77793nuvTp4/8/f01ZcoUHTt2rFTdc+fOad++fWVet3js0CuvvKLMzEzdcsstuu6667zzEAAgus8AS7vclHxJeuihh5zT472pQYMGeu211/Tkk0/q6aef1t///ne1bNlSN954o0aOHKlXXnlFDz30kNq1a6e6desqNzdXR44c0Y4dO9S1a1c99dRTpa55xx13aOrUqc7WJwZYA/A2kiLAwi43JV+S7r///gpJiqSSidGoUaP08ssv6+abb1bPnj0VFxen9PR07dixQ19//bVCQ0MVHR2t+++/X127di3zetWrV1enTp20bNkyhYWFKTExsUKeA8DVy2aUtWwsgKva8uXLlZaWpmeffbbCNoT1hNmzZ2vu3LmaMmWKWrVqVdnhALAYxhQBuKS0tDR16NBBL7zwQmWHcll//OMf1aFDh8u2mgHAldB9BqCUuLg4paSkOL/feOONlRdMOfTo0UO33nqr8zsDsgG4g+4zAAAA0X0GAAAgiaQIAABAEkkRAACAJJIiAAAASSRFAAAAkkiKAAAAJJEUAQAASCIpAgAAkERSBAAAIEn6/wsSjRb3aQhJAAAAAElFTkSuQmCC", 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" ] @@ -467,7 +519,16 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 89, + "metadata": {}, + "outputs": [], + "source": [ + "h.write('spectral_response_example.h5', overwrite=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -477,7 +538,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -488,21 +549,20 @@ "[505.3776 507.3712 509.3648 511.3584 513.352 ]\n", "[507. 509. 511. 513. 515.]\n", "[508.6224 510.6288 512.6352 514.6416 516.648 ]\n", - "[510.2448 512.2576 514.2704 516.2832 518.296 ]\n", - "[0.01 0.01 0.01 0.01 0. ]\n" + "[510.2448 512.2576 514.2704 516.2832 518.296 ]\n" ] }, { "data": { "text/plain": [ - "array([[0. , 0.17, 0.66, 0.17, 0. ],\n", - " [0. , 0.17, 0.66, 0.17, 0. ],\n", - " [0. , 0.17, 0.66, 0.17, 0. ],\n", - " [0. , 0.17, 0.66, 0.17, 0. ],\n", - " [0. , 0.17, 0.66, 0.17, 0. ]])" + "array([[0.02, 0.14, 0.28, 0.14, 0.02],\n", + " [0.02, 0.14, 0.28, 0.14, 0.02],\n", + " [0.02, 0.14, 0.28, 0.14, 0.02],\n", + " [0.02, 0.15, 0.28, 0.15, 0.02],\n", + " [0.02, 0.15, 0.28, 0.15, 0.02]])" ] }, - "execution_count": 9, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -513,21 +573,21 @@ " print(Em)\n", " R[i, :] = gaussian(x=Em, center=Ei, sigma=sigma_rsp)\n", "\n", - "R /= np.sum(R, axis=0)\n", + "# R /= np.sum(R, axis=0)\n", "R = np.round(R, 2)\n", "\n", - "adjust = 1 - np.sum(R, axis=0)\n", - "print(adjust)\n", - "for i in range(nbins):\n", - " if np.abs(adjust[i]) < 0.001:\n", - " continue\n", - " elif np.abs(adjust[i]) - 0.01 < 0.001:\n", - " R[2, i] += adjust[i]\n", - " elif np.abs(adjust[i]) - 0.02 < 0.001:\n", - " R[[1,3], i] += adjust[i] / 2\n", - " else:\n", - " print(i, adjust[i])\n", - " raise\n", + "# adjust = 1 - np.sum(R, axis=0)\n", + "# print(adjust)\n", + "# for i in range(nbins):\n", + "# if np.abs(adjust[i]) < 0.001:\n", + "# continue\n", + "# elif np.abs(adjust[i]) - 0.01 < 0.001:\n", + "# R[2, i] += adjust[i]\n", + "# elif np.abs(adjust[i]) - 0.02 < 0.001:\n", + "# R[[1,3], i] += adjust[i] / 2\n", + "# else:\n", + "# print(i, adjust[i])\n", + "# raise\n", "\n", "R = R.transpose(1,0)\n", "\n", @@ -536,43 +596,43 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "NuLambdalen = 48\n", - "htransformed = Histogram([np.arange(NuLambdalen+1), np.arange(506, 517, 2)*u.keV, eps_col_edges], contents=np.tile(R, (NuLambdalen, 1, 1)), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" + "htransformed = Histogram([np.arange(NuLambdalen+1), np.linspace(506, 516, 6)*u.keV, eps_col_edges], contents=np.tile(R, (NuLambdalen, 1, 1)), unit=u.cm**2, labels=['NuLambda', 'Ei', 'eps'])" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ - "htransformed.write('transformed_response_example.h5', overwrite=True)\n", + "htransformed.write('reparam_spectral_response_example.h5', overwrite=True)\n", "# htransformed.contents" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(,\n", - " )" + " )" ] }, - "execution_count": 13, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", "text/plain": [ "
" ] @@ -589,7 +649,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Load example response" + "### Unbinned MC with example spectral response" ] }, { @@ -910,12 +970,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Setting up HealpixBase" + "### Create example full response file" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [], + "source": [ + "image_response = Histogram.open('spectral_response_example.h5')" ] }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -924,7 +993,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -933,7 +1002,7 @@ "(1, 2, 48)" ] }, - "execution_count": 74, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -944,7 +1013,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -956,7 +1025,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -965,7 +1034,7 @@ "array([], dtype=int64)" ] }, - "execution_count": 76, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -976,7 +1045,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -1005,16 +1074,36 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(48, 5, 5)" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "image_response.contents.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 91, "metadata": {}, "outputs": [], "source": [ "def HealpixBase_to_h5(m, hist, h5_file):\n", - " with h5py.File(h5_file, 'w') as hdf:\n", - " drm = hdf.create_group('DRM')\n", + " with h5py.File(h5_file, 'w') as hf:\n", + " drm = hf.create_group('DRM')\n", " data = hist.contents\n", - " hdf['DRM'].attrs['UNIT'] = str(data.unit)\n", - " hdf['DRM'].attrs['SPARSE'] = False\n", + " hf['DRM'].attrs['UNIT'] = str(data.unit)\n", + " hf['DRM'].attrs['SPARSE'] = False\n", "\n", " axis_grp = drm.create_group('AXES', track_order=True)\n", "\n", @@ -1029,10 +1118,15 @@ " axis.attrs['TYPE'] = 'linear'\n", " axis.attrs['UNIT'] = str(hist.axes['Ei'].unit)\n", "\n", - " axis = axis_grp.create_dataset('eps', data=image_response.axes['eps'])\n", + " # axis = axis_grp.create_dataset('eps', data=image_response.axes['eps'])\n", + " # axis.attrs['DESCRIPTION'] = 'Measured energy'\n", + " # axis.attrs['TYPE'] = 'linear'\n", + " # axis.attrs['UNIT'] = ' '\n", + "\n", + " axis = axis_grp.create_dataset('Em', data=image_response.axes['Em'])\n", " axis.attrs['DESCRIPTION'] = 'Measured energy'\n", - " axis.attrs['TYPE'] = 'nonlinear'\n", - " axis.attrs['UNIT'] = ' '\n", + " axis.attrs['TYPE'] = 'linear'\n", + " axis.attrs['UNIT'] = str(hist.axes['Em'].unit)\n", "\n", " # axis = axis_grp.create_dataset('Phi', data=np.arange(m.npix))\n", " # axis.attrs['DESCRIPTION'] = 'Compton angle'\n", @@ -1048,7 +1142,81 @@ " dset = drm.create_dataset('CONTENTS', data=data.value)\n", "\n", "# Example usage\n", - "HealpixBase_to_h5(mEq, image_response, 'example.h5')" + "HealpixBase_to_h5(mEq, image_response, 'normparam_full_response_example.h5')" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n", + " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n", + " 48]\n" + ] + } + ], + "source": [ + "with h5py.File('normparam_full_response_example.h5', mode='r') as file:\n", + "\n", + " drm = file['DRM']\n", + " unit = u.Unit(drm.attrs['UNIT'])\n", + " sparse = drm.attrs['SPARSE']\n", + "\n", + " # Axes\n", + " axes = []\n", + "\n", + " for i, axis_label in enumerate(drm[\"AXES\"]):\n", + "\n", + " axis = drm['AXES'][axis_label]\n", + " axis_type = axis.attrs['TYPE']\n", + "\n", + " if axis_type == 'healpix':\n", + " print(np.array(axis))\n", + " axes += [HealpixAxis(edges=np.array(axis),\n", + " nside=axis.attrs['NSIDE'],\n", + " label=axis_label,\n", + " scheme=axis.attrs['SCHEME'],\n", + " coordsys=SpacecraftFrame())]\n", + "\n", + " else:\n", + " axes += [Axis(np.array(axis) * u.Unit(axis.attrs['UNIT']),\n", + " scale=axis_type,\n", + " label=axis_label)]\n", + "\n", + " new_axes = Axes(axes)\n", + "\n", + " # Init HealpixMap (local coordinates, main axis)\n", + " # HealpixBase.__init__(base=axes['NuLambda'], \n", + " # coordsys=SpacecraftFrame())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(14, 7))\n", + "axMoll = fig.add_subplot(projection = \"mollview\")\n", + "m.plot(axMoll, vmin=0, vmax=1)\n", + "m.plot_grid(axMoll, color='white', linewidth = .2)\n", + "plt.show()" ] }, { @@ -1060,297 +1228,317 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 65, "metadata": {}, "outputs": [], "source": [ - "response_path = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5')" + "with FullDetectorResponse.open('reparam_full_response_example.h5') as response:\n", + " dr_re = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 66, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pixel 0 centered at \n" - ] + "data": { + "text/latex": [ + "$[-0.008,~-0.0048,~-0.0016,~0.0016,~0.0048,~0.008] \\; \\mathrm{}$" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "with FullDetectorResponse.open(response_path) as response:\n", - " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", - " dr = response[0]\n", - " data = response._file['DRM']['CONTENTS'][0]\n", - " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit) \n", - " dr = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" + "dr_re.axes['eps'].edges" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/latex": [ - "$1.4900613 \\times 10^{-6} \\; \\mathrm{cm^{2}}$" + "$[506,~508,~510,~512,~514,~516] \\; \\mathrm{keV}$" ], "text/plain": [ - "" + "" ] }, - "execution_count": 6, + "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Ei0 = 511.*u.keV\n", - "Em0 = 600*u.keV\n", - "Phi0 = 12*u.deg\n", - "PsiChi0 = 386\n", - "\n", - "target = {'Ei': Ei0, 'Em': Em0, 'Phi': Phi0, 'PsiChi': PsiChi0}\n", - "interpolated_response_value = dr.get_interp_response(target)\n", - "\n", - "interpolated_response_value" + "dr_re.axes['Ei'].edges" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "with FullDetectorResponse.open('normparam_full_response_example.h5') as response:\n", + " dr_norm = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { + "text/latex": [ + "$[506,~508,~510,~512,~514,~516] \\; \\mathrm{keV}$" + ], "text/plain": [ - "(, )" + "" ] }, - "execution_count": 7, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Ei0, dr.transform_Em_to_eps(Em0, Ei0)" + "dr_norm.mapping['Em'] = 'Em'\n", + "dr_norm.axes['Em'].edges" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { + "text/latex": [ + "$[506,~508,~510,~512,~514,~516] \\; \\mathrm{keV}$" + ], "text/plain": [ - "array([509.49 , 509.694, 509.898, 510.102, 510.306, 510.51 ])" + "" ] }, - "execution_count": 8, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "eps = np.linspace(-0.001, 0.001, 6)\n", - "(eps + 1) * 510" + "dr_norm.axes['Ei'].edges" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": {}, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "0.21250000000000002 cm2\n" + ] } ], "source": [ - "label1 = 'Ei'\n", - "label2 = 'Em'\n", + "target = {'Em': 508.5*u.keV, 'Ei': 508.5*u.keV}\n", "\n", - "fig, ax = plt.subplots()\n", - "dr.project(label1, label2).draw(ax=ax)\n", - "ax.scatter(target[label1], target[label2], marker='*')\n", - "for e1 in dr.neighbors[label1]:\n", - " for e2 in dr.neighbors[label2]:\n", - " ax.scatter(e1, e2, c='r')\n", - "plt.show()" + "# print(dr_re.get_interp_response(target))\n", + "print(dr_norm.get_interp_response(target))" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 10, "metadata": {}, + "outputs": [], "source": [ - "### Setting up HealpixBase (2)" + "response_path = Path('/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5')" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# Define data paths\n", + "data_dir = Path(\"/Users/penguin/Documents/Grad School/Research/COSI/COSIpy/docs/tutorials/data\") # Current directory by default. Modify if you can want a different path\n", + "ori_path = data_dir / \"20280301_3_month.ori\"\n", + "\n", + "# Read the full oritation\n", + "ori = SpacecraftFile.parse_from_file(ori_path)\n", + "scatt_map = ori.get_scatt_map(nside = 16, coordsys = 'galactic')\n", + "\n", + "# define the target coordinates (Crab)\n", + "target_coord = SkyCoord(184.5551, -05.7877, unit = \"deg\", frame = \"galactic\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, + "outputs": [], + "source": [ + "# # get the target movement in the reference frame attached to the detector\n", + "# target_in_sc_frame = ori.get_target_in_sc_frame(target_name = \"Crab\", target_coord = target_coord)\n", + "\n", + "# # To get the dwell time map, look at the DetectorResponse.ipynb tutorial notebook\n", + "# dwell_time_map = ori.get_dwell_map(response = response_path, src_path = target_in_sc_frame) # Dwell time map is in SpacecraftFrame() L.409 (SpacecraftFile.py)\n", + "\n", + "# with FullDetectorResponse.open(response_path) as response:\n", + "# psr = response.get_point_source_response(exposure_map=dwell_time_map)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with FullDetectorResponse.open(response_path) as response:\n", + " psr = response.get_point_source_response(scatt_map = scatt_map, coord = target_coord)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'_unit': Unit(\"keV\"), '_edges': array([1150., 1164.]), '_label': 'Ei', '_scale': 'log'}\n", - "{'_unit': Unit(\"keV\"), '_edges': array([1150., 1164.]), '_label': 'Em', '_scale': 'log'}\n", - "{'_unit': Unit(\"deg\"), '_edges': array([ 0., 3., 6., 9., 12., 15., 18., 21., 24., 27., 30.,\n", - " 33., 36., 39., 42., 45., 48., 51., 54., 57., 60., 63.,\n", - " 66., 69., 72., 75., 78., 81., 84., 87., 90., 93., 96.,\n", - " 99., 102., 105., 108., 111., 114., 117., 120., 123., 126., 129.,\n", - " 132., 135., 138., 141., 144., 147., 150., 153., 156., 159., 162.,\n", - " 165., 168., 171., 174., 177., 180.]), '_label': 'Phi', '_scale': 'linear'}\n" + "Pixel 0 centered at \n" ] } ], "source": [ - "with h5py.File('example.h5', mode='r') as file:\n", - "\n", - " drm = file['DRM']\n", - " unit = u.Unit(drm.attrs['UNIT'])\n", - " sparse = drm.attrs['SPARSE']\n", - "\n", - " # Axes\n", - " axes = []\n", - "\n", - " for axis_label in drm[\"AXES\"]:\n", - "\n", - " axis = drm['AXES'][axis_label]\n", - " axis_type = axis.attrs['TYPE']\n", - "\n", - " if axis_type == 'healpix':\n", - "\n", - " axes += [HealpixAxis(edges=np.array(axis),\n", - " nside=axis.attrs['NSIDE'],\n", - " label=axis_label,\n", - " scheme=axis.attrs['SCHEME'],\n", - " coordsys=SpacecraftFrame())]\n", - "\n", - " else:\n", - " axes += [Axis(np.array(axis) * u.Unit(axis.attrs['UNIT']),\n", - " scale=axis_type,\n", - " label=axis_label)]\n", - "\n", - " new_axes = Axes(axes)\n", - "\n", - " # Init HealpixMap (local coordinates, main axis)\n", - " HealpixBase.__init__(new,\n", - " base=axes['NuLambda'],\n", - " coordsys=SpacecraftFrame())" + "with FullDetectorResponse.open(response_path) as response:\n", + " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", + " dr = response[0]\n", + " data = response._file['DRM']['CONTENTS'][0]\n", + " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit) \n", + " dr = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\n" + ] + } + ], "source": [ - "hf = h5py.File('example.h5', mode='r')" + "with FullDetectorResponse.open(response_path) as response:\n", + " print(Histogram([Axis(np.arange(target_coord.size+1))] + list(response.axes[1:]), \n", + " unit = response.unit * scatt_map.unit))\n", + " print(response.axes['PsiChi'].coordsys)\n", + " response.axes['PsiChi'].coordsys = target_coord.frame\n", + " print(response.axes['PsiChi'].coordsys)" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['BITPIX',\n", - " 'GCOUNT',\n", - " 'INDXSCHM',\n", - " 'MOCORDER',\n", - " 'NAXIS',\n", - " 'NAXIS1',\n", - " 'NAXIS2',\n", - " 'NSIDE',\n", - " 'ORDERING',\n", - " 'PCOUNT',\n", - " 'PIXTYPE',\n", - " 'TFIELDS',\n", - " 'TFORM1',\n", - " 'TFORM2',\n", - " 'TTYPE1',\n", - " 'TTYPE2',\n", - " 'XTENSION']" + "" ] }, - "execution_count": 25, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "list(hf['header1'].attrs)" + "dr.axes['PsiChi'].coordsys" ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "text/latex": [ + "$1.4900613 \\times 10^{-6} \\; \\mathrm{cm^{2}}$" + ], "text/plain": [ - "
" + "" ] }, + "execution_count": 25, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "fig = plt.figure(figsize=(14, 7))\n", - "axMoll = fig.add_subplot(projection = \"mollview\")\n", - "m.plot(axMoll, vmin=0, vmax=1)\n", - "m.plot_grid(axMoll, color='white', linewidth = .2)\n", - "plt.show()" + "Ei0 = 511.*u.keV\n", + "Em0 = 600*u.keV\n", + "Phi0 = 12*u.deg\n", + "PsiChi0 = 386\n", + "\n", + "target = {'Ei': Ei0, 'Em': Em0, 'Phi': Phi0, 'PsiChi': PsiChi0}\n", + "interpolated_response_value = dr.get_interp_response(target)\n", + "\n", + "interpolated_response_value" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "metadata": {}, "outputs": [ { - "ename": "KeyError", - "evalue": "\"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mFullDetectorResponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtransformed_response_example.h5\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m response:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(response[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:85\u001b[0m, in \u001b[0;36mFullDetectorResponse.open\u001b[0;34m(cls, filename, Spectrumfile, norm, single_pixel, alpha, emin, emax)\u001b[0m\n\u001b[1;32m 81\u001b[0m filename \u001b[38;5;241m=\u001b[39m Path(filename)\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filename\u001b[38;5;241m.\u001b[39msuffix \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.h5\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 85\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_h5\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(filename\u001b[38;5;241m.\u001b[39msuffixes[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.rsp.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_open_rsp(filename,Spectrumfile,norm ,single_pixel,alpha,emin,emax)\n", - "File \u001b[0;32m~/Documents/Grad School/Research/COSI/COSIpy/cosipy/response/FullDetectorResponse.py:108\u001b[0m, in \u001b[0;36mFullDetectorResponse._open_h5\u001b[0;34m(cls, filename)\u001b[0m\n\u001b[1;32m 104\u001b[0m new\u001b[38;5;241m.\u001b[39m_file \u001b[38;5;241m=\u001b[39m h5\u001b[38;5;241m.\u001b[39mFile(filename, mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 106\u001b[0m new\u001b[38;5;241m.\u001b[39m_drm \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_file[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDRM\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m new\u001b[38;5;241m.\u001b[39m_unit \u001b[38;5;241m=\u001b[39m u\u001b[38;5;241m.\u001b[39mUnit(\u001b[43mnew\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_drm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUNIT\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 111\u001b[0m new\u001b[38;5;241m.\u001b[39m_sparse \u001b[38;5;241m=\u001b[39m new\u001b[38;5;241m.\u001b[39m_drm\u001b[38;5;241m.\u001b[39mattrs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSPARSE\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32m~/miniconda3/envs/cosipy/lib/python3.10/site-packages/h5py/_hl/attrs.py:56\u001b[0m, in \u001b[0;36mAttributeManager.__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[38;5;129m@with_phil\u001b[39m\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name):\n\u001b[1;32m 54\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Read the value of an attribute.\u001b[39;00m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 56\u001b[0m attr \u001b[38;5;241m=\u001b[39m \u001b[43mh5a\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_id\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 57\u001b[0m shape \u001b[38;5;241m=\u001b[39m attr\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 59\u001b[0m \u001b[38;5;66;03m# shape is None for empty dataspaces\u001b[39;00m\n", - "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mh5py/h5a.pyx:80\u001b[0m, in \u001b[0;36mh5py.h5a.open\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open attribute (can't locate attribute: 'UNIT')\"" - ] + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "with FullDetectorResponse.open('transformed_response_example.h5') as response:\n", - " print(response['DRM'])" + "dr = dr_norm\n", + "label1 = 'Ei'\n", + "label2 = 'Em'\n", + "\n", + "fig, ax = plt.subplots()\n", + "dr.project(label1, label2).draw(ax=ax)\n", + "ax.scatter(target[label1], target[label2], marker='*')\n", + "for e1 in dr.neighbors[label1]:\n", + " for e2 in dr.neighbors[label2]:\n", + " ax.scatter(e1, e2, c='r')\n", + "plt.show()" ] } ], From dc35034337f64a59a9ba1767d5056a54dc438250 Mon Sep 17 00:00:00 2001 From: avalluvan <62253557+avalluvan@users.noreply.github.com> Date: Sun, 10 Nov 2024 21:04:53 -0800 Subject: [PATCH 19/46] Tested new interpolation scheme on LMDR.ipynb --- cosipy/response/FullDetectorResponse.py | 17 +- cosipy/spacecraftfile/SpacecraftFile.py | 6 +- docs/tutorials/response/LMDR.ipynb | 634 ++++++++-------- docs/tutorials/response/SpacecraftFile.ipynb | 729 +++++++++++++++++-- 4 files changed, 1016 insertions(+), 370 deletions(-) diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py index 297bb8c5..b93bb867 100644 --- a/cosipy/response/FullDetectorResponse.py +++ b/cosipy/response/FullDetectorResponse.py @@ -912,26 +912,27 @@ def get_point_source_response(self, psr.axes[axis_label].coordsys = coord.frame # Set coordinate system of PsiChi axis to input coordinate frame. Axis coordsys was set when response file was opened and initialized using HealpixBase.__init__ - for i,(pixels, exposure) in \ - enumerate(zip(scatt_map.contents.coords.transpose(), - scatt_map.contents.data)): + for pixels, exposure in \ + zip(scatt_map.contents.coords.transpose(), # Arrays of [[x's], [y's]] --> [[x,y]'s] + scatt_map.contents.data): #gc.collect() # HDF5 cache issues + # Calculate attitude of coordinates in scatt_map att = Attitude.from_axes(x = scatt_map.axes['x'].pix2skycoord(pixels[0]), y = scatt_map.axes['y'].pix2skycoord(pixels[1])) - coord.attitude = att + coord.attitude = att # Set attitude to given input coordinate. It is used to transform Spacecraft coordinates (scoords) from ICRS to mhealpy pixel #TODO: Change this to interpolation - loc_nulambda_pixels = np.array(self.axes['NuLambda'].find_bin(coord), + loc_nulambda_pixels = np.array(self.axes['NuLambda'].find_bin(coord), # Pixel corresponding to coord ndmin = 1) - dr_pix = Histogram.concatenate(coords_axis, [self[i] for i in loc_nulambda_pixels]) + dr_pix = Histogram.concatenate(coords_axis, [self[pixel] for pixel in loc_nulambda_pixels]) # Concatenate Axis object with DetectorResponse Histogram (Histograms if multiple target_coords are provided) - dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = att) + dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = att) # Update the attitude of the PsiChi axis from `None` to `att` - self._sum_rot_hist(dr_pix, psr, exposure) + self._sum_rot_hist(dr_pix, psr, exposure) # Rotate PsiChi from local SC to galactic coordinates. (Function only affects Healpix Axis of psr Histogram) # Convert to PSR psr = tuple([PointSourceResponse(psr.axes[1:], diff --git a/cosipy/spacecraftfile/SpacecraftFile.py b/cosipy/spacecraftfile/SpacecraftFile.py index 6aa0d634..9ffd9a09 100644 --- a/cosipy/spacecraftfile/SpacecraftFile.py +++ b/cosipy/spacecraftfile/SpacecraftFile.py @@ -108,7 +108,7 @@ def parse_from_file(cls, file): orientation_file = np.loadtxt(file, usecols=(1, 2, 3, 4, 5), delimiter=' ', skiprows=1, comments=("#", "EN")) time_stamps = orientation_file[:, 0] axis_1 = orientation_file[:, [2, 1]] - axis_2 = orientation_file[:, [4, 3]] + axis_2 = orientation_file[:, [4, 3]] # MEGAlib saves in (b,l) format. Need to feed (l,b) to SkyCoord(). time = Time(time_stamps, format = "unix") xpointings = SkyCoord(l = axis_1[:,0]*u.deg, b = axis_1[:,1]*u.deg, frame = "galactic") @@ -1009,3 +1009,7 @@ def plot_rmf(self, file_name = None, save_name = None, dpi = 300): #plt.show() return + + # len() functionality for SpacecraftFile / ori objects + def __len__(self): + return len(self._time) \ No newline at end of file diff --git a/docs/tutorials/response/LMDR.ipynb b/docs/tutorials/response/LMDR.ipynb index 97c6392c..29457bab 100644 --- a/docs/tutorials/response/LMDR.ipynb +++ b/docs/tutorials/response/LMDR.ipynb @@ -2,265 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 73, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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-       "                  performances in 3ML                                                                              \n",
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-       "                  performances in 3ML                                                                              \n",
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-       "                  performances in 3ML                                                                              \n",
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cosipy.spacecraftfile import SpacecraftFile\n", "from cosipy import test_data\n", "\n", @@ -1284,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1038,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -1306,7 +1050,7 @@ "" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -1318,7 +1062,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -1330,7 +1074,7 @@ "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -1341,7 +1085,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -1361,7 +1105,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -1370,7 +1114,29 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pixel 0 centered at \n" + ] + } + ], + "source": [ + "with FullDetectorResponse.open(response_path) as response:\n", + " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", + " data = response._file['DRM']['CONTENTS'][0, ...]\n", + " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit)\n", + " dr = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1380,10 +1146,17 @@ "\n", "# Read the full oritation\n", "ori = SpacecraftFile.parse_from_file(ori_path)\n", - "scatt_map = ori.get_scatt_map(nside = 16, coordsys = 'galactic')\n", - "\n", + "scatt_map = ori.get_scatt_map(nside = 16, coordsys = 'galactic')" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [], + "source": [ "# define the target coordinates (Crab)\n", - "target_coord = SkyCoord(184.5551, -05.7877, unit = \"deg\", frame = \"galactic\")" + "target_coord = SkyCoord([184.5551, 173], -05.7877, unit = \"deg\", frame = \"galactic\")" ] }, { @@ -1414,70 +1187,347 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(210, 2)" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scatt_map.contents.coords.transpose().shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Pixel 0 centered at \n" + "2077374\n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", - " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", - " dr = response[0]\n", - " data = response._file['DRM']['CONTENTS'][0]\n", - " dr = ListModeResponse(response.axes[1:], contents=data, unit=response.unit) \n", - " dr = response.get_interp_response(SkyCoord(lon=0, lat=0, frame=SpacecraftFrame(), unit=u.deg), unbinned=True)" + " coords_axis = Axis(np.arange(target_coord.size+1), label = 'coords')\n", + " psr = Histogram([Axis(np.arange(target_coord.size+1))] + list(response.axes[1:]), \n", + " unit = response.unit * scatt_map.unit)\n", + " psr.axes['PsiChi'].coordsys = target_coord.frame\n", + "\n", + " limit = 1\n", + " for pixels, exposure in zip(scatt_map.contents.coords.transpose()[:limit], # Arrays of [[x's], [y's]] --> [[x,y]'s]\n", + " scatt_map.contents.data[:limit]):\n", + " \n", + " target_coord.attitude = Attitude.from_axes(scatt_map.axes['x'].pix2skycoord(pixels[0]), \n", + " scatt_map.axes['y'].pix2skycoord(pixels[1]))\n", + " loc_nulambda_pixels = np.array(response.axes['NuLambda'].find_bin(target_coord), ndmin=1)\n", + " print(loc_nulambda_pixels)\n", + " dr_list = []\n", + " for coord in target_coord:\n", + "\n", + " pixels, weights = response.axes['NuLambda'].get_interp_weights(coord)\n", + " dr = ListModeResponse(response.axes[1:],\n", + " sparse=response._sparse,\n", + " unit=response.unit)\n", + " # for p, w in zip(pixels, weights):\n", + " # dr += response[p] * w\n", + " print(pixels, weights)\n", + " idx = 0# weights.argmax()\n", + " print(pixels[idx])\n", + " dr += response[pixels[idx]]\n", + " dr_list.append(dr)\n", + " print(np.sum((response[loc_nulambda_pixels[0]].contents - dr_list[0].contents).value < 1e-15))\n", + " dr_pix = Histogram.concatenate(coords_axis, [response[pixel] for pixel in loc_nulambda_pixels])\n", + " dr_pix_2 = Histogram.concatenate(coords_axis, dr_list)\n", + " dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = target_coord.attitude)\n", + " dr_pix_2.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = target_coord.attitude)\n", + " # response._sum_rot_hist(dr_pix, psr, scatt_map.contents.data[0])\n", + " " ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 216, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,\n", + " 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,\n", + " 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,\n", + " 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n", + " 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,\n", + " 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,\n", + " 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,\n", + " 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103,\n", + " 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116,\n", + " 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129,\n", + " 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142,\n", + " 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155,\n", + " 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168,\n", + " 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,\n", + " 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194,\n", + " 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207,\n", + " 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220,\n", + " 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233,\n", + " 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246,\n", + " 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259,\n", + " 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272,\n", + " 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285,\n", + " 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298,\n", + " 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311,\n", + " 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324,\n", + " 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337,\n", + " 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350,\n", + " 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363,\n", + " 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376,\n", + " 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389,\n", + " 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402,\n", + " 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415,\n", + " 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428,\n", + " 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441,\n", + " 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454,\n", + " 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467,\n", + " 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480,\n", + " 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493,\n", + " 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506,\n", + " 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519,\n", + " 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532,\n", + " 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545,\n", + " 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558,\n", + " 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571,\n", + " 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584,\n", + " 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597,\n", + " 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610,\n", + " 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623,\n", + " 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636,\n", + " 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649,\n", + " 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662,\n", + " 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675,\n", + " 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688,\n", + " 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701,\n", + " 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714,\n", + " 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727,\n", + " 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740,\n", + " 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753,\n", + " 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766,\n", + " 767, 768])" + ] + }, + "execution_count": 216, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dr_pix.project('PsiChi').axis.edges" + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 219, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(dr_pix.project('Ei', 'Em') - dr_pix_2.project('Ei', 'Em')).draw(vmax=1e-5, vmin=-1e-5)" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + ", obstime=None, location=None)>" + ] + }, + "execution_count": 129, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dr_pix.axes['PsiChi'].coordsys" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_unit': None,\n", + " '_edges': array([0, 1]),\n", + " '_label': 'coords',\n", + " '_scale': 'linear'}" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coords_axis.__dict__" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [], + "source": [ + "with FullDetectorResponse.open(response_path) as response:\n", + " h = Histogram.concatenate(coords_axis, [response[i] for i in loc_nulambda_pixels])" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "h.axes['PsiChi'].coordsys" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "psr_obj = tuple([PointSourceResponse(psr.axes[1:],\n", + " contents = data,\n", + " sparse = psr.is_sparse,\n", + " unit = psr.unit)\n", + " for data in psr[:]])" + ] + }, + { + "cell_type": "code", + "execution_count": 117, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\n", - "\n", - "\n" + "\n", + "\n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", - " print(Histogram([Axis(np.arange(target_coord.size+1))] + list(response.axes[1:]), \n", - " unit = response.unit * scatt_map.unit))\n", - " print(response.axes['PsiChi'].coordsys)\n", - " response.axes['PsiChi'].coordsys = target_coord.frame\n", - " print(response.axes['PsiChi'].coordsys)" + " print(type(response[1].axes['PsiChi'].coordsys))\n", + " print(response[1].axes['PsiChi'].coordsys)" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "array(['coords', 'Ei', 'Em', 'Phi', 'PsiChi'], dtype='11:31:35 WARNING The naima package is not available. Models that depend on it will not be functions.py:48\n", + " available \n", + "\n" + ], + "text/plain": [ + "\u001b[38;5;46m11:31:35\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The naima package is not available. Models that depend on it will not be \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=493255;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py\u001b\\\u001b[2mfunctions.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=495046;file:///Users/penguin/miniconda3/envs/cosipy/lib/python3.10/site-packages/astromodels/functions/functions_1D/functions.py#48\u001b\\\u001b[2m48\u001b[0m\u001b]8;;\u001b\\\n", + "\u001b[38;5;46m \u001b[0m \u001b[1;38;5;251mavailable \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m \u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
         WARNING   The GSL library or the pygsl wrapper cannot be loaded. Models that depend on it  functions.py:69\n",
+       "                  will not be available.                                                                           \n",
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+       "                  require the C/C++ interface (currently HAWC)                                                     \n",
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+       "                  software installed and configured?                                                               \n",
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+       "                  software installed and configured?                                                               \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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