diff --git a/.gitignore b/.gitignore index 83f378b8..7d14fdee 100644 --- a/.gitignore +++ b/.gitignore @@ -19,6 +19,7 @@ # Project **/*.json +**/.bin *.npy input.txt output.txt diff --git a/Cargo.lock b/Cargo.lock index 0c233939..53344687 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -660,6 +660,7 @@ version = "0.23.0" dependencies = [ "approx", "argmin_testfunctions", + "bincode", "bitflags", "criterion", "csv", diff --git a/doc/Gpx_Tutorial.ipynb b/doc/Gpx_Tutorial.ipynb index 359f1544..6e6d7332 100644 --- a/doc/Gpx_Tutorial.ipynb +++ b/doc/Gpx_Tutorial.ipynb @@ -1,1052 +1,1067 @@ { - "cells": [ - { - "attachments": {}, - "cell_type": "markdown", - "id": "4bd147b8", - "metadata": {}, - "source": [ - "# Using _egobox_ surrogate model _Gpx_" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "3141794e", - "metadata": {}, - "source": [ - "## Installation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "33b7dcca", - "metadata": {}, - "outputs": [], - "source": [ - "%pip install egobox" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "0fa96b71", - "metadata": {}, - "source": [ - "We import _egobox_ as _egx_ for short" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "d502466d-906e-4b64-9968-ea5b642fbadf", - "metadata": {}, - "outputs": [], - "source": [ - "import egobox as egx" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "c8e65173-d594-4a1d-8bfb-f5e3a480ce47", - "metadata": { - "tags": [] - }, - "source": [ - "# Example 1 : Gpx basics" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "358adf9c-0447-4b16-b3dc-02eb881a7d96", - "metadata": { - "tags": [] - }, - "source": [ - "### Training " - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "d72fd25e-803b-435e-ae81-9aa7175494bc", - "metadata": {}, - "source": [ - "#### Training data definition" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "f4de436a-8319-47f5-bb5a-e68d02419752", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "xt = np.array([[0.0, 1.0, 2.0, 3.0, 4.0]]).T\n", - "yt = np.array([[0.0, 1.0, 1.5, 0.9, 1.0]]).T" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "465167dc-424b-4b73-8e1d-28dc6e5e3044", - "metadata": {}, - "source": [ - "#### Building the surrogate" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "41bca9a8-bc79-4122-a650-64dd4c37203c", - "metadata": {}, - "outputs": [], - "source": [ - "gpx = egx.Gpx.builder().fit(xt, yt)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "a302fb72-aff9-4d92-949f-f77832ab78d6", - "metadata": { - "tags": [] - }, - "source": [ - "### Prediction" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "b4419c24-cb8e-4dd0-893b-8b6b23ad3218", - "metadata": {}, - "source": [ - "#### Using the surrogate for estimation" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "47d51b54-41df-4b78-b10f-f996ec8bf5a2", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimal theta = [1.67830276]\n", - "GP variance = 0.30493880450870275\n", - "Reduced likelihood = 0.5781740714671411\n" - ] - } - ], - "source": [ - "# number of x locations to estimate\n", - "num = 100\n", - "\n", - "# x should have 2D shape (nsamples, nx)\n", - "x = np.linspace(0.0, 4.0, num).reshape((-1, 1))\n", - "\n", - "# estimated values\n", - "y = gpx.predict(x)\n", - "# estimated variances\n", - "s2 = gpx.predict_var(x)\n", - "\n", - "# Print hyperparameters\n", - "print(f\"Optimal theta = {gpx.thetas()[0]}\")\n", - "print(f\"GP variance = {gpx.variances()[0]}\")\n", - "print(f\"Reduced likelihood = {gpx.likelihoods()[0]}\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "4c44d3ba-4540-4e3f-8eb8-35eac1a6c3df", - "metadata": {}, - "source": [ - "#### Plotting results" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "782b0849-ef74-4267-999b-d714065323e7", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "def plot_gp(xt, yt, x, y, s2):\n", - " fig, axs = plt.subplots(1)\n", - " \n", - " # training data\n", - " axs.plot(xt, yt, \"o\")\n", - " \n", - " # gp mean\n", - " axs.plot(x, y)\n", - " \n", - " # 99% confidence interval\n", - " axs.fill_between(\n", - " np.ravel(x),\n", - " np.ravel(y - 3 * np.sqrt(s2)),\n", - " np.ravel(y + 3 * np.sqrt(s2)),\n", - " color=\"lightgrey\",\n", - " )\n", - " \n", - " # legend\n", - " axs.set_xlabel(\"x\")\n", - " axs.set_ylabel(\"y\")\n", - " axs.legend(\n", - " [\"Training data\", \"Prediction\", \"Confidence Interval 99%\"],\n", - " loc=\"lower right\",\n", - " )\n", - " return axs\n", - "\n", - "plot_gp(xt, yt, x, y, s2)\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "81c877a9-85b0-43f0-89d3-a9bd78940e80", - "metadata": { - "tags": [] - }, - "source": [ - "### Sampling" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "e9771aff-1fdb-4cc0-b6c4-620abd209513", - "metadata": {}, - "source": [ - "#### Sampling the conditionned Gaussian process" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c6b11bc9-777d-45c7-ba9b-6fac8cc0f33e", - "metadata": {}, - "outputs": [], - "source": [ - "# number fo trajectories to sample\n", - "n_traj = 30\n", - "\n", - "trajs = gpx.sample(x, n_traj)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "432580a5-e386-4fb2-900c-eb557c39aa73", - "metadata": {}, - "source": [ - "#### Plotting trajectories" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "7f7475e5-2653-47d5-8cfe-adf1178a44fa", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "axs = plot_gp(xt, yt, x, y, s2)\n", - "\n", - "for i in range(n_traj):\n", - " axs.plot(x, trajs[:, i])\n", - "\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "a7f6a424-1da4-4816-b95f-47d46fa418c2", - "metadata": {}, - "source": [ - "## Example 2 : Gpx trend and correlation models customization, saving and loading" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "8a910ef7-33b0-4033-998b-6317760e3ac7", - "metadata": {}, - "source": [ - "### Test function\n", - "\n", - "$$f : \\left\\{ \\begin{array}{c} [-10, 10] \\rightarrow \\mathbb{R} \\\\ x \\mapsto x^2 \\sin(x) \\ \\end{array} \\right.$$" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "ad996348-9dd9-4068-8a45-8455520ad859", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "def f(x):\n", - " return x**2 * np.sin(x)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "2fe7b4b2-6ac9-465c-8436-3e7429aa4747", - "metadata": { - "tags": [] - }, - "source": [ - "### Training" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "87fe0c9f-cd81-4494-be24-a3aab057a69e", - "metadata": {}, - "source": [ - "$f$ is approximated with _Gpx_ at points $-8.5$, $-4.0$, $-3.0$, $-1.0$, $4.0$ and $7.5$. " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "9ef79902-15e1-4ef3-a671-3f14a89d470e", - "metadata": {}, - "outputs": [], - "source": [ - "xt = np.array([[-8.5, -4.0, -3.0, -1.0, 4.0, 7.5]]).T\n", - "yt = f(xt)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "8a2f08c8-1c1d-4e10-a157-012a46eafe17", - "metadata": {}, - "source": [ - "To show features of _Gpx_, below, we build the surrogate asking for best GP regression by testing constant, linear or quadratic trend with either squared_exponential or matern52. The quality of the surrogate is assessed by cross validation." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "99e498c1-9ce5-4f07-a92b-c7bb0cb679f9", - "metadata": {}, - "outputs": [], - "source": [ - "gpx_builder = egx.Gpx.builder(regr_spec=egx.RegressionSpec.ALL, \n", - " corr_spec=egx.CorrelationSpec.SQUARED_EXPONENTIAL | egx.CorrelationSpec.MATERN52)\n", - "gpx = gpx_builder.fit(xt, yt)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "77456008-7572-4138-b307-b6d77522bd8d", - "metadata": {}, - "source": [ - "We can get string representations of the trained GP" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "7f58b435-8c3d-4d8a-844f-79c829f10983", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Gpx string: Mixture[Smooth](Linear_SquaredExponentialGP(mean=LinearMean, corr=SquaredExponential, theta=[14.452882749810662], variance=441.2141000495963, likelihood=3.031768565015306))\n", - "Gpx stringified JSON serialization {\"recombination\":{\"Smooth\":null},\"experts\":[{\"type\":\"GpLinearSquaredExponentialSurrogate\",\"theta\":{\"v\":1,\"dim\":[1],\"data\":[14.452882749810662]},\"likelihood\":3.031768565015306,\"mean\":\"LinearMean\",\"corr\":\"SquaredExponential\",\"inner_params\":{\"sigma2\":441.2141000495963,\"beta\":{\"v\":1,\"dim\":[2,1],\"data\":[-0.07757166517069636,0.7944037509309693]},\"gamma\":{\"v\":1,\"dim\":[6,1],\"data\":[-0.44643171321364306,1.1331405283903964,-0.3878788861969931,0.1553420259776689,-0.8959678802322967,0.4417959252748667]},\"r_chol\":{\"v\":1,\"dim\":[6,6],\"data\":[1.000000000000011,0.0,0.0,0.0,0.0,0.0,0.00015107687965342333,0.9999999885878993,0.0,0.0,0.0,0.0,1.960569341106461e-6,0.647617274864888,0.7619657901065864,0.0,0.0,0.0,2.4359093850121372e-11,0.020038526606141666,0.21382309005204245,0.9766668539538308,0.0,0.0,3.299917901018181e-30,8.401926714807942e-13,7.451627142017255e-10,0.00001964311890039922,0.999999999807085,0.0,4.983282830665148e-49,1.1139381004845755e-25,2.069666987829042e-21,2.387862924959664e-14,0.004882594368483155,0.9999880800650851]},\"ft\":{\"v\":1,\"dim\":[6,2],\"data\":[0.9999999999999889,-1.3292355199392736,0.9998489345307233,-0.5488312520922597,0.462591105466827,-0.02653440727656832,0.9021006879988441,-0.012517047814952423,0.9999822797762914,0.8379965521044357,0.9951293540292918,1.4407467936872096]},\"ft_qr_r\":{\"v\":1,\"dim\":[2,2],\"data\":[2.2400270233067623,0.16524847426703282,0.0,2.1953646732623318]}},\"w_star\":{\"v\":1,\"dim\":[1,1],\"data\":[1.0]},\"xtrain\":{\"data\":{\"v\":1,\"dim\":[6,1],\"data\":[-1.3292355199392882,-0.549032062583619,-0.3756535165045814,-0.028896424346506258,0.8379963060486816,1.4448212173253132]},\"mean\":{\"v\":1,\"dim\":[1],\"data\":[-0.8333333333333334]},\"std\":{\"v\":1,\"dim\":[1],\"data\":[5.767726299562651]}},\"ytrain\":{\"data\":{\"v\":1,\"dim\":[6,1],\"data\":[-1.5797826304192275,0.3712640485913234,-0.002705461006250771,0.009275082294565307,-0.3056720463069517,1.5076210068465417]},\"mean\":{\"v\":1,\"dim\":[1],\"data\":[-1.1732910418024691]},\"std\":{\"v\":1,\"dim\":[1],\"data\":[35.77542995914992]}}}],\"gmx\":{\"weights\":{\"v\":1,\"dim\":[1],\"data\":[1.0]},\"means\":{\"v\":1,\"dim\":[1,1],\"data\":[-0.8333333333333334]},\"covariances\":{\"v\":1,\"dim\":[1,1,1],\"data\":[27.722223222222226]},\"precisions\":{\"v\":1,\"dim\":[1,1,1],\"data\":[0.0360721429873776]},\"precisions_chol\":{\"v\":1,\"dim\":[1,1,1],\"data\":[0.18992667792434426]},\"heaviside_factor\":1.0,\"log_det\":{\"v\":1,\"dim\":[1],\"data\":[-1.6611171869637489]}},\"output_dim\":1}\n" - ] - } - ], - "source": [ - "print(f\"Gpx string: {gpx}\")\n", - "print(f\"Gpx stringified JSON serialization {repr(gpx)}\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "b143465a-1a0f-4cd4-a214-cf436212fd47", - "metadata": {}, - "source": [ - "... and save it in a json file." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "c7aa44a9-d9d9-4e41-851c-80ca9aa0ebc5", - "metadata": {}, - "outputs": [], - "source": [ - "gpx.save(\"gp.json\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "7319042a-ab3d-43b7-8a12-1bebb0e44a60", - "metadata": { - "tags": [] - }, - "source": [ - "We can reload it with" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "f0ffeda5-1939-44af-9754-d523842bc15d", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "gpx = egx.Gpx.load(\"gp.json\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "aa750f99-8508-4405-b79d-10b868c5d6be", - "metadata": { - "tags": [] - }, - "source": [ - "### Prediction" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "cd4b168f-79f5-4153-a8f8-1d3ff7fab14a", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "x_min, x_max = -10, 10\n", - "n_plot = 500\n", - "\n", - "# x must have (nsamples, nx) shape\n", - "x = np.linspace(x_min, x_max, n_plot).reshape(-1, 1)\n", - "\n", - "y = gpx.predict(x)\n", - "s2 = gpx.predict_var(x)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "dd5d170f-c274-4acc-be25-4fe8faba3722", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_gp(xt, yt, x, y, s2)\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "4eaf76ed-5a6b-4b11-8944-f622a47a2264", - "metadata": { - "tags": [] - }, - "source": [ - "### Sampling" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "1e5ce606-a320-470e-a1e9-d5e75866b6fd", - "metadata": {}, - "source": [ - "#### Sampling the conditionned Gaussian process" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "2cde3d09-2e38-414b-901f-0c92cb4ed08f", - "metadata": {}, - "outputs": [], - "source": [ - "# number fo trajectories to sample\n", - "n_traj = 10\n", - "\n", - "trajs = gpx.sample(x, n_traj)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "960f9d9c-b5cb-4db3-80a3-f4d7b48810e3", - "metadata": {}, - "source": [ - "#### Plotting trajectories" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "42ebdbc8-b9d7-48c8-abf8-49825139ce07", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "axs = plot_gp(xt, yt, x, y, s2)\n", - "\n", - "for i in range(n_traj):\n", - " axs.plot(x, trajs[:, i])\n", - "\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "0781134f-ccae-4fd0-a0de-835f2cc30ead", - "metadata": {}, - "source": [ - "## Example 3 : Clustering" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "3015e350-d8b5-4f89-872e-f0e5eb094d7b", - "metadata": {}, - "source": [ - "### Test function\n", - "\n", - "We are going to use a test function with three modes to show clustering feature" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "33133e72-262e-445d-ab97-525c693e66e3", - "metadata": {}, - "outputs": [], - "source": [ - "def function_3modes(x):\n", - " y = np.zeros(x.shape)\n", - " y[x < 0.4] = x[x < 0.4] ** 2\n", - " y[(x >= 0.4) & (x < 0.8)] = 3 * x[(x >= 0.4) & (x < 0.8)] + 1\n", - " y[x >= 0.8] = np.sin(10 * x[x >= 0.8])\n", - " return y" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "b39b12aa-c2c6-4f64-8e27-5078ae5c9ee5", - "metadata": { - "tags": [] - }, - "source": [ - "### Training " - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "1c597ff9-bfa8-433e-8800-d5f20533f140", - "metadata": {}, - "source": [ - "#### Training data definition" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "b31cb879-19ae-4054-b18d-39ffda55a24b", - "metadata": {}, - "outputs": [], - "source": [ - "np.random.seed(42) # results may differ depending on training data, set seed here for reproducibility\n", - "xt = np.random.sample(60).reshape((-1, 1))\n", - "yt = function_3modes(xt)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "c4dbc652-7bf1-4bd1-a348-bcf0c19df50f", - "metadata": {}, - "source": [ - "#### Building the surrogate" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "412e4c38-7361-4ce2-88bb-533797b048dd", - "metadata": {}, - "outputs": [], - "source": [ - "gpx = egx.Gpx.builder(n_clusters=3).fit(xt, yt)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "ce2d2c7c-bf96-468c-bb4f-f358e477825d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Mixture[Smooth(0.1)](Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.02798142256558686], variance=0.02638828606423465, likelihood=278.2517956877343), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.007994050570374143], variance=1.3952667945423496, likelihood=192.53772467321363), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.030545446402999624], variance=0.9814282111121166, likelihood=89.03789739740697))\n" - ] - } - ], - "source": [ - "print(gpx)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "caf365bb-f2b5-4dfd-98b2-7f78b4d2b854", - "metadata": {}, - "source": [ - "We see that 3 experts are smoothly recombined with an heasviside factor of 0.1 automatically adjusted to improve the overall surrogate quality." - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "fb9cb31d-2b01-41f3-b4cb-acf625635db5", - "metadata": {}, - "source": [ - "### Plotting" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "e5e4db6f-d0a2-43fb-9095-6ad6ee56d7c6", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "x_min, x_max = 0, 1\n", - "n_plot = 500\n", - "\n", - "# x must have (nsamples, nx) shape\n", - "x = np.linspace(x_min, x_max, n_plot).reshape(-1, 1)\n", - "\n", - "y = gpx.predict(x)\n", - "s2 = gpx.predict_var(x)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "933f231a-71eb-4728-9245-ce4331a8abd9", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_gp(xt, yt, x, y, s2)\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "7a3f976c-6260-41a3-97b7-7513abf2beb0", - "metadata": {}, - "source": [ - "We can check it is better than one cluster (the default)." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "531c5590-3504-48ab-a53e-1eb004f62330", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "gpx = egx.Gpx.builder().fit(xt, yt)\n", - "y = gpx.predict(x)\n", - "s2 = gpx.predict_var(x)\n", - "plot_gp(xt, yt, x, y, s2)\n", - "plt.show()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "7920a0e3-37f6-4ff0-bdf0-bb9cbf550962", - "metadata": {}, - "source": [ - "We can also let _Gpx_ find the best number of clusters" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "6c0f2a73-03d8-482a-8824-c46c8ef51aee", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Mixture[Hard](Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.02798142256558686], variance=0.02638828606423465, likelihood=278.2517956877343), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.007994050570374143], variance=1.3952667945423496, likelihood=192.53772467321363), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.030545446402999624], variance=0.9814282111121166, likelihood=89.03789739740697))\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "gpx = egx.Gpx.builder(n_clusters=0).fit(xt, yt)\n", - "print(gpx)\n", - "y = gpx.predict(x)\n", - "s2 = gpx.predict_var(x)\n", - "plot_gp(xt, yt, x, y, s2)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "4e550286", - "metadata": {}, - "source": [ - "## Gpx API" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "c3db4c30", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Help on GpMix in module builtins object:\n", - "\n", - "class GpMix(object)\n", - " | GpMix(n_clusters=1, regr_spec=Ellipsis, corr_spec=Ellipsis, recombination=Ellipsis, theta_init=None, theta_bounds=None, kpls_dim=None, n_start=10, seed=None)\n", - " | \n", - " | Gaussian processes mixture builder\n", - " | \n", - " | n_clusters (int >= 0)\n", - " | Number of clusters used by the mixture of surrogate experts.\n", - " | When set to 0, the number of cluster is determined automatically and refreshed every\n", - " | 10-points addition (should say 'tentative addition' because addition may fail for some points\n", - " | but failures are counted anyway).\n", - " | \n", - " | regr_spec (RegressionSpec flags, an int in [1, 7]):\n", - " | Specification of regression models used in mixture.\n", - " | Can be RegressionSpec.CONSTANT (1), RegressionSpec.LINEAR (2), RegressionSpec.QUADRATIC (4) or\n", - " | any bit-wise union of these values (e.g. RegressionSpec.CONSTANT | RegressionSpec.LINEAR)\n", - " | \n", - " | corr_spec (CorrelationSpec flags, an int in [1, 15]):\n", - " | Specification of correlation models used in mixture.\n", - " | Can be CorrelationSpec.SQUARED_EXPONENTIAL (1), CorrelationSpec.ABSOLUTE_EXPONENTIAL (2),\n", - " | CorrelationSpec.MATERN32 (4), CorrelationSpec.MATERN52 (8) or\n", - " | any bit-wise union of these values (e.g. CorrelationSpec.MATERN32 | CorrelationSpec.MATERN52)\n", - " | \n", - " | recombination (Recombination.Smooth or Recombination.Hard)\n", - " | Specify how the various experts predictions are recombined\n", - " | * Smooth: prediction is a combination of experts prediction wrt their responsabilities,\n", - " | the heaviside factor which controls steepness of the change between experts regions is optimized\n", - " | to get best mixture quality.\n", - " | * Hard: prediction is taken from the expert with highest responsability\n", - " | resulting in a model with discontinuities.\n", - " | \n", - " | theta_init ([nx] where nx is the dimension of inputs x)\n", - " | Initial guess for GP theta hyperparameters.\n", - " | When None the default is 1e-2 for all components\n", - " | \n", - " | theta_bounds ([[lower_1, upper_1], ..., [lower_nx, upper_nx]] where nx is the dimension of inputs x)\n", - " | Space search when optimizing theta GP hyperparameters\n", - " | When None the default is [1e-6, 1e2] for all components\n", - " | \n", - " | kpls_dim (0 < int < nx where nx is the dimension of inputs x)\n", - " | Number of components to be used when PLS projection is used (a.k.a KPLS method).\n", - " | This is used to address high-dimensional problems typically when nx > 9.\n", - " | \n", - " | n_start (int >= 0)\n", - " | Number of internal GP hyperpameters optimization restart (multistart)\n", - " | \n", - " | seed (int >= 0)\n", - " | Random generator seed to allow computation reproducibility.\n", - " | \n", - " | Methods defined here:\n", - " | \n", - " | fit(self, /, xt, yt)\n", - " | Fit the parameters of the model using the training dataset to build a trained model\n", - " | \n", - " | Parameters\n", - " | xt (array[nsamples, nx]): input samples\n", - " | yt (array[nsamples, 1]): output samples\n", - " | \n", - " | Returns Gpx object\n", - " | the fitted Gaussian process mixture\n", - " | \n", - " | ----------------------------------------------------------------------\n", - " | Static methods defined here:\n", - " | \n", - " | __new__(*args, **kwargs) from builtins.type\n", - " | Create and return a new object. See help(type) for accurate signature.\n", - "\n" - ] - } - ], - "source": [ - "help(egx.Gpx.builder())" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "284f975e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Help on class Gpx in module builtins:\n", - "\n", - "class Gpx(object)\n", - " | A trained Gaussian processes mixture\n", - " | \n", - " | Methods defined here:\n", - " | \n", - " | __repr__(self, /)\n", - " | Return repr(self).\n", - " | \n", - " | __str__(self, /)\n", - " | Return str(self).\n", - " | \n", - " | likelihoods(self, /)\n", - " | Get reduced likelihood values gotten when fitting the GP experts\n", - " | \n", - " | Maybe used to compare various parameterization\n", - " | \n", - " | Returns\n", - " | likelihood as an array[n_clusters]\n", - " | \n", - " | predict(self, /, x)\n", - " | Predict output values at nsamples points.\n", - " | \n", - " | Parameters\n", - " | x (array[nsamples, nx])\n", - " | input values\n", - " | \n", - " | Returns\n", - " | the output values at nsamples x points (array[nsamples, 1])\n", - " | \n", - " | predict_gradients(self, /, x)\n", - " | Predict surrogate output derivatives at nsamples points.\n", - " | \n", - " | Parameters\n", - " | x (array[nsamples, nx])\n", - " | input values\n", - " | \n", - " | Returns\n", - " | the output derivatives at nsamples x points (array[nsamples, nx]) wrt inputs\n", - " | The ith column is the partial derivative value wrt to the ith component of x at the given samples.\n", - " | \n", - " | predict_var(self, /, x)\n", - " | Predict variances at nsample points.\n", - " | \n", - " | Parameters\n", - " | x (array[nsamples, nx])\n", - " | input values\n", - " | \n", - " | Returns\n", - " | the variances of the output values at nsamples input points (array[nsamples, 1])\n", - " | \n", - " | predict_var_gradients(self, /, x)\n", - " | Predict variance derivatives at nsamples points.\n", - " | \n", - " | Parameters\n", - " | x (array[nsamples, nx])\n", - " | input values\n", - " | \n", - " | Returns\n", - " | the variance derivatives at nsamples x points (array[nsamples, nx]) wrt inputs\n", - " | The ith column is the partial derivative value wrt to the ith component of x at the given samples.\n", - " | \n", - " | sample(self, /, x, n_traj)\n", - " | Sample gaussian process trajectories.\n", - " | \n", - " | Parameters\n", - " | x (array[nsamples, nx])\n", - " | locations of the sampled trajectories\n", - " | n_traj number of trajectories to generate\n", - " | \n", - " | Returns\n", - " | the trajectories as an array[nsamples, n_traj]\n", - " | \n", - " | save(self, /, filename)\n", - " | Save Gaussian processes mixture in a json file.\n", - " | \n", - " | Parameters\n", - " | filename (string)\n", - " | json file generated in the current directory\n", - " | \n", - " | thetas(self, /)\n", - " | Get optimized thetas hyperparameters (ie once GP experts are fitted)\n", - " | \n", - " | Returns\n", - " | thetas as an array[n_clusters, nx or kpls_dim]\n", - " | \n", - " | variances(self, /)\n", - " | Get GP expert variance (ie posterior GP variance)\n", - " | \n", - " | Returns\n", - " | variances as an array[n_clusters]\n", - " | \n", - " | ----------------------------------------------------------------------\n", - " | Static methods defined here:\n", - " | \n", - " | __new__(*args, **kwargs) from builtins.type\n", - " | Create and return a new object. See help(type) for accurate signature.\n", - " | \n", - " | builder(n_clusters=1, regr_spec=Ellipsis, corr_spec=Ellipsis, recombination=Ellipsis, theta_init=None, theta_bounds=None, kpls_dim=None, n_start=10, seed=None)\n", - " | Get Gaussian processes mixture builder aka `GpMix`\n", - " | \n", - " | See `GpMix` constructor\n", - " | \n", - " | load(filename)\n", - " | Load Gaussian processes mixture from a json file.\n", - " | \n", - " | Parameters\n", - " | filename (string)\n", - " | json filepath generated by saving a trained Gaussian processes mixture\n", - "\n" - ] - } - ], - "source": [ - "help(egx.Gpx)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} \ No newline at end of file + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "4bd147b8", + "metadata": {}, + "source": [ + "# Using _egobox_ surrogate model _Gpx_" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "3141794e", + "metadata": {}, + "source": [ + "## Installation" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "33b7dcca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: egobox in d:\\rlafage\\miniconda3\\lib\\site-packages (0.23.0)\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install egobox" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "0fa96b71", + "metadata": {}, + "source": [ + "We import _egobox_ as _egx_ for short" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d502466d-906e-4b64-9968-ea5b642fbadf", + "metadata": {}, + "outputs": [], + "source": [ + "import egobox as egx" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "c8e65173-d594-4a1d-8bfb-f5e3a480ce47", + "metadata": { + "tags": [] + }, + "source": [ + "# Example 1 : Gpx basics" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "358adf9c-0447-4b16-b3dc-02eb881a7d96", + "metadata": { + "tags": [] + }, + "source": [ + "### Training " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "d72fd25e-803b-435e-ae81-9aa7175494bc", + "metadata": {}, + "source": [ + "#### Training data definition" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f4de436a-8319-47f5-bb5a-e68d02419752", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "xt = np.array([[0.0, 1.0, 2.0, 3.0, 4.0]]).T\n", + "yt = np.array([[0.0, 1.0, 1.5, 0.9, 1.0]]).T" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "465167dc-424b-4b73-8e1d-28dc6e5e3044", + "metadata": {}, + "source": [ + "#### Building the surrogate" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "41bca9a8-bc79-4122-a650-64dd4c37203c", + "metadata": {}, + "outputs": [], + "source": [ + "gpx = egx.Gpx.builder().fit(xt, yt)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "a302fb72-aff9-4d92-949f-f77832ab78d6", + "metadata": { + "tags": [] + }, + "source": [ + "### Prediction" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b4419c24-cb8e-4dd0-893b-8b6b23ad3218", + "metadata": {}, + "source": [ + "#### Using the surrogate for estimation" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "47d51b54-41df-4b78-b10f-f996ec8bf5a2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Optimal theta = [1.67828994]\n", + "GP variance = 0.3049400437701594\n", + "Reduced likelihood = 0.5781740714718056\n" + ] + } + ], + "source": [ + "# number of x locations to estimate\n", + "num = 100\n", + "\n", + "# x should have 2D shape (nsamples, nx)\n", + "x = np.linspace(0.0, 4.0, num).reshape((-1, 1))\n", + "\n", + "# estimated values\n", + "y = gpx.predict(x)\n", + "# estimated variances\n", + "s2 = gpx.predict_var(x)\n", + "\n", + "# Print hyperparameters\n", + "print(f\"Optimal theta = {gpx.thetas()[0]}\")\n", + "print(f\"GP variance = {gpx.variances()[0]}\")\n", + "print(f\"Reduced likelihood = {gpx.likelihoods()[0]}\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "4c44d3ba-4540-4e3f-8eb8-35eac1a6c3df", + "metadata": {}, + "source": [ + "#### Plotting results" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "782b0849-ef74-4267-999b-d714065323e7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "def plot_gp(xt, yt, x, y, s2):\n", + " fig, axs = plt.subplots(1)\n", + " \n", + " # training data\n", + " axs.plot(xt, yt, \"o\")\n", + " \n", + " # gp mean\n", + " axs.plot(x, y)\n", + " \n", + " # 99% confidence interval\n", + " axs.fill_between(\n", + " np.ravel(x),\n", + " np.ravel(y - 3 * np.sqrt(s2)),\n", + " np.ravel(y + 3 * np.sqrt(s2)),\n", + " color=\"lightgrey\",\n", + " )\n", + " \n", + " # legend\n", + " axs.set_xlabel(\"x\")\n", + " axs.set_ylabel(\"y\")\n", + " axs.legend(\n", + " [\"Training data\", \"Prediction\", \"Confidence Interval 99%\"],\n", + " loc=\"lower right\",\n", + " )\n", + " return axs\n", + "\n", + "plot_gp(xt, yt, x, y, s2)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "81c877a9-85b0-43f0-89d3-a9bd78940e80", + "metadata": { + "tags": [] + }, + "source": [ + "### Sampling" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "e9771aff-1fdb-4cc0-b6c4-620abd209513", + "metadata": {}, + "source": [ + "#### Sampling the conditionned Gaussian process" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c6b11bc9-777d-45c7-ba9b-6fac8cc0f33e", + "metadata": {}, + "outputs": [], + "source": [ + "# number fo trajectories to sample\n", + "n_traj = 30\n", + "\n", + "trajs = gpx.sample(x, n_traj)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "432580a5-e386-4fb2-900c-eb557c39aa73", + "metadata": {}, + "source": [ + "#### Plotting trajectories" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7f7475e5-2653-47d5-8cfe-adf1178a44fa", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "axs = plot_gp(xt, yt, x, y, s2)\n", + "\n", + "for i in range(n_traj):\n", + " axs.plot(x, trajs[:, i])\n", + "\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "a7f6a424-1da4-4816-b95f-47d46fa418c2", + "metadata": {}, + "source": [ + "## Example 2 : Gpx trend and correlation models customization, saving and loading" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "8a910ef7-33b0-4033-998b-6317760e3ac7", + "metadata": {}, + "source": [ + "### Test function\n", + "\n", + "$$f : \\left\\{ \\begin{array}{c} [-10, 10] \\rightarrow \\mathbb{R} \\\\ x \\mapsto x^2 \\sin(x) \\ \\end{array} \\right.$$" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "ad996348-9dd9-4068-8a45-8455520ad859", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "def f(x):\n", + " return x**2 * np.sin(x)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "2fe7b4b2-6ac9-465c-8436-3e7429aa4747", + "metadata": { + "tags": [] + }, + "source": [ + "### Training" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "87fe0c9f-cd81-4494-be24-a3aab057a69e", + "metadata": {}, + "source": [ + "$f$ is approximated with _Gpx_ at points $-8.5$, $-4.0$, $-3.0$, $-1.0$, $4.0$ and $7.5$. " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9ef79902-15e1-4ef3-a671-3f14a89d470e", + "metadata": {}, + "outputs": [], + "source": [ + "xt = np.array([[-8.5, -4.0, -3.0, -1.0, 4.0, 7.5]]).T\n", + "yt = f(xt)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "8a2f08c8-1c1d-4e10-a157-012a46eafe17", + "metadata": {}, + "source": [ + "To show features of _Gpx_, below, we build the surrogate asking for best GP regression by testing constant, linear or quadratic trend with either squared_exponential or matern52. The quality of the surrogate is assessed by cross validation." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "99e498c1-9ce5-4f07-a92b-c7bb0cb679f9", + "metadata": {}, + "outputs": [], + "source": [ + "gpx_builder = egx.Gpx.builder(regr_spec=egx.RegressionSpec.ALL, \n", + " corr_spec=egx.CorrelationSpec.SQUARED_EXPONENTIAL | egx.CorrelationSpec.MATERN52)\n", + "gpx = gpx_builder.fit(xt, yt)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "77456008-7572-4138-b307-b6d77522bd8d", + "metadata": {}, + "source": [ + "We can get string representations of the trained GP" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "7f58b435-8c3d-4d8a-844f-79c829f10983", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Gpx string: Mixture[Smooth](Linear_SquaredExponentialGP(mean=LinearMean, corr=SquaredExponential, theta=[14.453108310585526], variance=441.2131727575699, likelihood=3.0317685650605943))\n", + "Gpx stringified JSON serialization {\"recombination\":{\"Smooth\":null},\"experts\":[{\"type\":\"GpLinearSquaredExponentialSurrogate\",\"theta\":{\"v\":1,\"dim\":[1],\"data\":[14.453108310585526]},\"likelihood\":3.0317685650605943,\"inner_params\":{\"sigma2\":441.2131727575699,\"beta\":{\"v\":1,\"dim\":[2,1],\"data\":[-0.07757161926025721,0.7944037941949736]},\"gamma\":{\"v\":1,\"dim\":[6,1],\"data\":[-0.44643167687202573,1.133131124809854,-0.3878666745284213,0.15533955394250828,-0.8959677803782301,0.4417954530263136]},\"r_chol\":{\"v\":1,\"dim\":[6,6],\"data\":[1.000000000000011,0.0,0.0,0.0,0.0,0.0,0.0001510561378024045,0.9999999885910327,0.0,0.0,0.0,0.0,1.9601672565991523e-6,0.6476128837840273,0.7619695221943696,0.0,0.0,0.0,2.434980514598138e-11,0.020037303823239316,0.21381693649172018,0.9766682262287502,0.0,0.0,3.296423703753802e-30,8.398281535208459e-13,7.44911612228923e-10,0.00001963976192234679,0.9999999998071509,0.0,4.974640459217575e-49,1.1129396734558612e-25,2.068110297817145e-21,2.386690085166188e-14,0.0048821888384808325,0.999988082045065]},\"ft\":{\"v\":1,\"dim\":[6,2],\"data\":[0.9999999999999889,-1.3292355199392736,0.9998489552694416,-0.5488312796613454,0.4625945845539201,-0.026537417389141983,0.902102824801257,-0.012517224989006932,0.9999822827627053,0.8379965520658361,0.9951297575720011,1.4407471306715083]},\"ft_qr_r\":{\"v\":1,\"dim\":[2,2],\"data\":[2.240028792174559,0.16524799061580708,0.0,2.195364975090908]}},\"w_star\":{\"v\":1,\"dim\":[1,1],\"data\":[1.0]},\"xt_norm\":{\"data\":{\"v\":1,\"dim\":[6,1],\"data\":[-1.3292355199392882,-0.549032062583619,-0.3756535165045814,-0.028896424346506258,0.8379963060486816,1.4448212173253132]},\"mean\":{\"v\":1,\"dim\":[1],\"data\":[-0.8333333333333334]},\"std\":{\"v\":1,\"dim\":[1],\"data\":[5.767726299562651]}},\"yt_norm\":{\"data\":{\"v\":1,\"dim\":[6,1],\"data\":[-1.5797826304192275,0.3712640485913234,-0.002705461006250771,0.009275082294565307,-0.3056720463069517,1.5076210068465417]},\"mean\":{\"v\":1,\"dim\":[1],\"data\":[-1.1732910418024691]},\"std\":{\"v\":1,\"dim\":[1],\"data\":[35.77542995914992]}},\"training_data\":[{\"v\":1,\"dim\":[6,1],\"data\":[-8.5,-4.0,-3.0,-1.0,4.0,7.5]},{\"v\":1,\"dim\":[6,1],\"data\":[-57.69069388704717,12.108839924926851,-1.2700800725388048,-0.8414709848078965,-12.108839924926851,52.76249869357906]}],\"params\":{\"theta_tuning\":{\"Optimized\":{\"init\":[0.01],\"bounds\":[[1e-8,100.0]]}},\"mean\":\"LinearMean\",\"corr\":\"SquaredExponential\",\"kpls_dim\":null,\"n_start\":10,\"nugget\":2.220446049250313e-14}}],\"gmx\":{\"weights\":{\"v\":1,\"dim\":[1],\"data\":[1.0]},\"means\":{\"v\":1,\"dim\":[1,1],\"data\":[-0.8333333333333334]},\"covariances\":{\"v\":1,\"dim\":[1,1,1],\"data\":[27.722223222222226]},\"precisions\":{\"v\":1,\"dim\":[1,1,1],\"data\":[0.0360721429873776]},\"precisions_chol\":{\"v\":1,\"dim\":[1,1,1],\"data\":[0.18992667792434426]},\"heaviside_factor\":1.0,\"log_det\":{\"v\":1,\"dim\":[1],\"data\":[-1.6611171869637489]}},\"gp_type\":\"FullGp\",\"training_data\":[{\"v\":1,\"dim\":[6,1],\"data\":[-8.5,-4.0,-3.0,-1.0,4.0,7.5]},{\"v\":1,\"dim\":[6,1],\"data\":[-57.69069388704717,12.108839924926851,-1.2700800725388048,-0.8414709848078965,-12.108839924926851,52.76249869357906]}],\"params\":{\"gp_type\":\"FullGp\",\"n_clusters\":1,\"recombination\":{\"Smooth\":null},\"regression_spec\":\"CONSTANT | LINEAR | QUADRATIC\",\"correlation_spec\":\"SQUAREDEXPONENTIAL | MATERN52\",\"theta_tunings\":[{\"Optimized\":{\"init\":[0.01],\"bounds\":[[1e-8,100.0]]}}],\"kpls_dim\":null,\"n_start\":10,\"gmm\":null,\"gmx\":null,\"rng\":{\"s\":[11018582338624544618,6886584510669971503,10234006225050304258,10303931937502703328]}}}\n" + ] + } + ], + "source": [ + "print(f\"Gpx string: {gpx}\")\n", + "print(f\"Gpx stringified JSON serialization {repr(gpx)}\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b143465a-1a0f-4cd4-a214-cf436212fd47", + "metadata": {}, + "source": [ + "... and save it in a json file (for a human readable format) or in binary file (for optimizing performances)." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "c7aa44a9-d9d9-4e41-851c-80ca9aa0ebc5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gpx.save(\"gp.json\") # json extension is automatically detected hence json file format\n", + "gpx.save(\"gp.bin\") # otherwise binary (you can compare here the size on disk)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7319042a-ab3d-43b7-8a12-1bebb0e44a60", + "metadata": { + "tags": [] + }, + "source": [ + "We can reload it with" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "f0ffeda5-1939-44af-9754-d523842bc15d", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "gpx = egx.Gpx.load(\"gp.json\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "aa750f99-8508-4405-b79d-10b868c5d6be", + "metadata": { + "tags": [] + }, + "source": [ + "### Prediction" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "cd4b168f-79f5-4153-a8f8-1d3ff7fab14a", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "x_min, x_max = -10, 10\n", + "n_plot = 500\n", + "\n", + "# x must have (nsamples, nx) shape\n", + "x = np.linspace(x_min, x_max, n_plot).reshape(-1, 1)\n", + "\n", + "y = gpx.predict(x)\n", + "s2 = gpx.predict_var(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "dd5d170f-c274-4acc-be25-4fe8faba3722", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_gp(xt, yt, x, y, s2)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "4eaf76ed-5a6b-4b11-8944-f622a47a2264", + "metadata": { + "tags": [] + }, + "source": [ + "### Sampling" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "1e5ce606-a320-470e-a1e9-d5e75866b6fd", + "metadata": {}, + "source": [ + "#### Sampling the conditionned Gaussian process" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "2cde3d09-2e38-414b-901f-0c92cb4ed08f", + "metadata": {}, + "outputs": [], + "source": [ + "# number fo trajectories to sample\n", + "n_traj = 10\n", + "\n", + "trajs = gpx.sample(x, n_traj)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "960f9d9c-b5cb-4db3-80a3-f4d7b48810e3", + "metadata": {}, + "source": [ + "#### Plotting trajectories" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "42ebdbc8-b9d7-48c8-abf8-49825139ce07", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "axs = plot_gp(xt, yt, x, y, s2)\n", + "\n", + "for i in range(n_traj):\n", + " axs.plot(x, trajs[:, i])\n", + "\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "0781134f-ccae-4fd0-a0de-835f2cc30ead", + "metadata": {}, + "source": [ + "## Example 3 : Clustering" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "3015e350-d8b5-4f89-872e-f0e5eb094d7b", + "metadata": {}, + "source": [ + "### Test function\n", + "\n", + "We are going to use a test function with three modes to show clustering feature" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "33133e72-262e-445d-ab97-525c693e66e3", + "metadata": {}, + "outputs": [], + "source": [ + "def function_3modes(x):\n", + " y = np.zeros(x.shape)\n", + " y[x < 0.4] = x[x < 0.4] ** 2\n", + " y[(x >= 0.4) & (x < 0.8)] = 3 * x[(x >= 0.4) & (x < 0.8)] + 1\n", + " y[x >= 0.8] = np.sin(10 * x[x >= 0.8])\n", + " return y" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b39b12aa-c2c6-4f64-8e27-5078ae5c9ee5", + "metadata": { + "tags": [] + }, + "source": [ + "### Training " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "1c597ff9-bfa8-433e-8800-d5f20533f140", + "metadata": {}, + "source": [ + "#### Training data definition" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "b31cb879-19ae-4054-b18d-39ffda55a24b", + "metadata": {}, + "outputs": [], + "source": [ + "np.random.seed(42) # results may differ depending on training data, set seed here for reproducibility\n", + "xt = np.random.sample(60).reshape((-1, 1))\n", + "yt = function_3modes(xt)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "c4dbc652-7bf1-4bd1-a348-bcf0c19df50f", + "metadata": {}, + "source": [ + "#### Building the surrogate" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "412e4c38-7361-4ce2-88bb-533797b048dd", + "metadata": {}, + "outputs": [], + "source": [ + "gpx = egx.Gpx.builder(n_clusters=3).fit(xt, yt)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "ce2d2c7c-bf96-468c-bb4f-f358e477825d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mixture[Smooth(0.1)](Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.030558468159793944], variance=0.9805836846291843, likelihood=89.03681533053401), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.027856606714033984], variance=0.026494441460099966, likelihood=278.25736821645546), Constant_SquaredExponentialGP(mean=ConstantMean, corr=SquaredExponential, theta=[0.007858695608853907], variance=1.4186216960244649, likelihood=192.5430848398401))\n" + ] + } + ], + "source": [ + "print(gpx)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "caf365bb-f2b5-4dfd-98b2-7f78b4d2b854", + "metadata": {}, + "source": [ + "We see that 3 experts are smoothly recombined with an heasviside factor of 0.1 automatically adjusted to improve the overall surrogate quality." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "fb9cb31d-2b01-41f3-b4cb-acf625635db5", + "metadata": {}, + "source": [ + "### Plotting" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "e5e4db6f-d0a2-43fb-9095-6ad6ee56d7c6", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "x_min, x_max = 0, 1\n", + "n_plot = 500\n", + "\n", + "# x must have (nsamples, nx) shape\n", + "x = np.linspace(x_min, x_max, n_plot).reshape(-1, 1)\n", + "\n", + "y = gpx.predict(x)\n", + "s2 = gpx.predict_var(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "933f231a-71eb-4728-9245-ce4331a8abd9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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gqen3d8C0CImIyFHI/h0+uw/+NxsArz2MPd3H4h50Le06dK101eSgnQ1WU6VjhACMu9iPhUhDUhASEQlmxfmw7FnMN09hufIBONBhBPv6TaBTv5Ow2+1+LrAJs9kxWFgYdY0FMQUhEZEAVmX3ldcL697DfHYvVvYuLCCvxbGk9/sbbQeNpGtYM5j+frQsq2TAtKcI41GLULBSEBIRCUAer+G5z3/ltW+2klng8h1Pjg3jiSHFpP7yGOz6AQsojkgive/1xKZeTpe4OL/VHJBsjpIgpBahoKUgJCISYBasS+POOWvJzHeVO96GvdyRP5vUL5YB4HGEs6fHOLyDriMlpaN2T68Leyi48tQiFMQUhEREAkCx28vry7Yy/3+7+HFn+c2gIyjkr47/8lf7fMIsF15j8V/rVHqdextd+qVq1/SjUTqF3rjVIhSsFIRERJq4aR+v56WvtnD4YicWXs63fc3tIbNpbWUC8K23Jw+4LuMn05G3YnrQTSHo6JQuqqhZY8FLQUhEpInyeA03zl7N/P+lVXjseOtn7gmZybG2LQBs8ybykPsSFnpPoGwN6EM3RpU6Kt1vTEEoeCkIiYg0QQvWpTH1g5/YnVO+S6adlcGdjrf4o/07AHJMOM+6RzPDM4JiQsqd2yw2Rm1opS1CaIxQ0FIQEhFpYhasS+O6N1ZxaE9YJAVMcHzAVfZPcFouPMZitud0nnD/mX3EVniOZrMxagOzShdVNB7XEc6UQKUgJCLShHi8hvv+u94Xgmx4+bP9S25zvEMrKwuArz29ecB9GRtN+yqfp9lsjNrQSrvGUNdY0FIQEhFpQlZs2e/b6PRE23rudsykt20bAL95k3jQfSmLvQM4uBd8eXERITx8ft/mszFqQysbLK2usaClICQi0oRk5BTS3trNXY5ZjLB/D0C2ieBp9/n8x3MWrip+bMeFh3DlSZ2YeHpXtQTVp7LB0gpCQUtBSESkqSjM4oRfnuSz0FcJtTy4jY03PWfwlPtPHKDq3bNvHtaNiad3UwBqCGVdYxojFLQUhERE/M3jhlWvY754iDb5e8GCLz3H8oB7LJtMuyoviwy18/iF/dQN1pBKB0tbXgWhYKUgJCLiT5u/gIV3QcZ6LKAwugNfJF/D9f/rVOUlgzrGc8Pp3RjStaVagRpa6Rghy+v2cyHSUBSERET8Ye8m+HQK/PIJAO7QGDJ6XYVj8HjOTm7L9GPTuO+/630Dp6FkSvzUkb3UAtSYSrfYUBAKXgpCIiKNqeAAfPkIZsVLWF43xrKzr8v55A6cQIce/X0bo47ok8yZvZJYsWU/GTmFJEaXrAukFqBG5msRUtdYsFIQEhFpDB4X/PAaZslDWAUHsIDs5JNIP3YCnY4/i5YhIRUusdssUru0aPxa5aCyMULG4+dCpKEoCImI1BOP11TegvPrZyXjgPZuLBkHFNOJ9GNvoFXqRRwTGenvsqU6dg2WDnYKQiIi9WDBuopjelKj9/BMwnu02v0VAO7QOHb3vprQE6+mY2uN8wkIGiwd9BSERESO0uF7g8WRw02O9xlb/BmO3V48loMDXS8g7/jraH/Msb5xQBIA1CIU9BSERESOwqF7g4Xg5jL7Im50vE+slQ/AQs/xTHdcxtsXXErL0IrjgKSJ8wUhjREKVgpCIiJHoWRvsAJOt63m74436WJLA2C9twMPuMey3NsbXLBqR7YGPgci32BptQgFKwUhEZEjqHIQNFCw83/MDJnGH+zrANhjYnjMPYZ3PUPxYvM9R0ZOYaXPLU1c6RghNEYoaCkIiYhUweM1PPf5r7z2zVYyCw62CCTHhvGPs5I4I+0VTls5A8vupcg4eNVzNs+7R5FLRIXnSowOa8zSpb6ULqhoUxAKWgpCIiKVWLAujTvnrCUzv3yXSCguRubO54QP54JVgAV8xmDuK76IHaZ1heexgKTYklYkCUClXWMYBaFgpSAkInKIklagTTz52S+HPWIYbvuByY5ZdLTtBmADnQg55RbyYk9h57vrsMA3cwxKQhDA1JG9tCJ0oLKVbbGhwdLBSkFIRKTUgnVp3PvhT6RnF5U73svayt2ON0i1rwdgt4njUfcY3vf8gVkdhjCqSwucztAK6wglaW+wwFcWhLSydNBSEBIRoeJaQACtyGSS413G2JdgswyFJoSXPOfygvv/yKdkzE/ZIGjtDRakbKUD3hWEgpaCkIg0e4euBQTgpJi/2BcwwTGPKKsk6HzoSeWfrovYRaty1x46CFp7gwUhdY0FPQUhEWn2StYCKgQM59i+Y7LjLVJsewBY4+3C/a7LWGWOqXBdsgZBB7/SIITx+rcOaTC2I5/SNEybNo0TTjiB6OhoEhMTGT16NBs3bqz2mhkzZmBZVrlbWJimsIo0Zx6vYfnmfXywZhfLN+/D4zVk5BTSx/qNd0Lv51+hz5Bi20OaSeCm4us5r/i+SkMQaBB0s6AxQkEvYFqEvvzySyZMmMAJJ5yA2+3mrrvu4qyzzmL9+vVEVrN7c0xMTLnApD1+RJqvyjZG7RuTzz/j5jHfOR+AAhPKC+6RvOQ5lwIq/8UpLiKEh8/vq0HQzYGCUNALmCC0YMGCcvdnzJhBYmIiK1eu5JRTTqnyOsuySEpKaujyRKSJO3wwdBhFjLd/xHVF/yUio2SW2Puek3nUNYZ0Kh/nExcewpUndWLi6V3VEtRcWCUdJxojFLwCJggdLisrC4CEhOr753Nzc+nQoQNer5cBAwbw0EMP0bt37yrPLyoqoqjo4NTZ7Ozs+ilYRPym/GBow//ZlnNHyFu0tfYBsNLbjcety1nm6kxV8ebmYd2YeHo3BaDmxjdGSEEoWAXMGKFDeb1ebrrpJk466ST69OlT5Xndu3fn1Vdf5YMPPuCNN97A6/UyZMgQdu7cWeU106ZNIzY21ndLSUlpiLcgIo2obDB0f2sT74feyzOhz9HW2sdO05KJxTfwp+J7WVbUmZuHdSMptnx3WHJsGC+MHcCNw45RCGqOfF1jWlk6WFnGGHPk05qW6667jk8++YSvv/6adu3a1fg6l8tFz549ufjii3nggQcqPaeyFqGUlBSysrKIiYk56tpFpPEtXPYD+Z/cw3n2bwDIM07+5R7FK55zKCLUd97TF/Xnj8e20VpActAvn8KsC8iP70HEjd/5uxqphezsbGJjY4/4/R1wXWMTJ05k/vz5LF26tFYhCCAkJITjjjuOTZs2VXmO0+nE6XQebZki0hQU58E3TzPs66ex2wvxGov3PKfwmPtCMoivcHpidJjWApLybHZAg6WDWcAEIWMMN9xwA3PnzmXJkiV06tSp1s/h8XhYu3Yt55xzTgNUKCJNhtcLa9/BfHYvVk4admAVPbineCzrTOcKp2tjVKmSFlQMegEThCZMmMCsWbP44IMPiI6OJj09HYDY2FjCw8MBGDduHG3btmXatGkA3H///Zx44ol07dqVzMxMHn30UbZt28bVV1/tt/chIg1s+7ew4E74fTUWUBzZhvS+17Ml/mx+mrtRG6NK7ZS2CGmwdPAKmCA0ffp0AE499dRyx1977TWuuOIKALZv347NdnD894EDBxg/fjzp6enEx8czcOBAli1bRq9evRqrbBFpLJnbYdFU+GkOAB5HBHt6XI4ZfC3tUzrSHoiMjNTGqFI7h6wjZIzRWnRBKCAHSzemmg62EpGG5fGaygcxF+XA109ilj2H5SnCYHGg00gyj5tAxz6Dyv1yVO3ziFRm5w/wyhkURyTjuHV9hb9P0nQF7WBpEWl+KlsRuk1MKC8eu5E+Pz+DlbsbC8htNYD0fn+j/aBzSQgNrfS5NBhaasXXNeZF7QbBSUFIRJq0w1eEBhhsbeDuwpn0+WErAEWRbUnvdwPxgy+ha2ysX+qUIHXIOkIKQsFJQUhEmqzyK0JDirWbyY63OMe+AoBsE8G/bedz4UW30yGlg/8KleB1yBghr1c70AcjBSERaTIOH7/j9RrSsgqJIp+Jjg+40v4JTsuNx1jM8pzBk+4/s58YTiyOoq2/i5fgZJV2jXk9ahEKUgpCItIkVDYOKCHMxsX2xdzieJeWVsm+f0s9ffmHeyy/mIPb32TkFFZ4PpF6cciCigpCwUlBSET8pqwFaNH6dF79Zmu5x1JtP3GPdyY9Q7YDsNmbzD/cY/nC2x8O2xo1Mbr8/mAi9UZdY0FPQUhE/KKyFiCAjlYadzlmcZZ9JQCZJpKn3H/iDc8w3If9yNKK0NLgynafV9dY0FIQEpFGV9lMsBjyuMExl8vtCwm1PLiNjZmeM3nafT6ZRFd4Dq0ILY3C1yKk6fPBSkFIRBrV4TPB7Hi42P45kxzvkmDlAvC5pz8Pui9lszk4BDouPITMApfvvlaElkZRNkYIL16P28/FSENQEBKRRrViy35fd9gpth+Z4niDY2y7APjF25Z/uMey1NuvwnXPXzoAm2VpRWhpXGULKgJGQSgoKQiJSKPKyCmki7WLvzve5HT7GgD2myiecF/AW57T8WAvd37ZOKATO7dQ8JHGZzv4NWm8CkLBSEFIRBpPwQEG/fwIC0P/g8Py4jJ2ZniG86x7NNlEVThd44DE7w4JQl53sR8LkYaiICQiDc/rgVWvYxY/QHLBfrBgkWcgD7kvYYupeoyPxgGJ3x0ShFDXWFBSEBKRhrVtOXxyG6SvxQIKYzqxOPlaJv6YUuUlV53UkWG9kjQOSPzPOmSMkLrGgpKCkIg0jKJcWHgXrHodAE9INLt7XUXokGs5t3Uy9r4V1xFKVguQNDU2GwYLC4PxuI58vgQcBSERqX97foG3LoL9mzFYHOg0kuwTbqRDz4FYVkkLz4g+yZzZK6nc3mJqAZImyeYAr0uzxoKUgpCI1K8DWzGvnY2VvxdXeCI7T5hCm5MuIsHprHCq3WaR2qWFH4oUqQWbHbwuUItQUFIQEpH643HD+1dj5e+lIK4bv58xnS59T/B3VSJHp3TAtFdBKCjZ/F2AiASRn/8LO7/H44hke+rDCkESHHz7jalrLBgpCIlI/fn2BQD2dbuAbiec7udiROpJ6cwx4/X4uRBpCApCIlI/DmyFHd9iLDu5PcZgs+nHiwSJsm021DUWlPSTSkTqx7ZlABTE96Bdz+P9XIxIPSrtGtOsseCkICQi9aM0COW17E9oaKifixGpR/bSIORVi1AwUhASkfqxfTkA+S0r7hwvEtDUIhTUFIRE5OgV58G+TQA4OqX6uRiReqZZY0FNQUhEjl7mDgA8IVHEJHXyczEi9csq229MQSgoKQiJyNHL3AZAcWQyERERfi5GpJ75WoQ0fT4YKQiJyNE7UBqEIpKx2+1HOFkkwJROn9emq8FJQUhEjl5pi5ArUrvGSxDSGKGgpiAkIkfvkK4xkaCjIBTUFIRE5OiVdo25Itr4uRCRBqDp80FNQUhEjprJ/h0Ae0J7P1ci0gDKtovRYOmgFDBBaNq0aZxwwglER0eTmJjI6NGj2bhx4xGve/fdd+nRowdhYWH07duXjz/+uBGqFWlGjIGCAwA4YpP8XIxIAyhtEbKMglAwCpgg9OWXXzJhwgS+/fZbFi1ahMvl4qyzziIvL6/Ka5YtW8bFF1/MVVddxerVqxk9ejSjR49m3bp1jVi5SJAryvF9QTiiW/m5GJEGUDZGSEEoKDn8XUBNLViwoNz9GTNmkJiYyMqVKznllFMqvebpp59mxIgR3HbbbQA88MADLFq0iOeee44XXnih0muKioooKiry3c/Ozq6ndyASpEpbg7y2UEIjYvxcjEgDKGsRUtdYUAqYFqHDZWVlAZCQkFDlOcuXL2fYsGHljg0fPpzly5dXec20adOIjY313VJSUuqnYJFgVRqEPKExOJ1OPxcj0gBK1xFS11hwCsgg5PV6uemmmzjppJPo06dPleelp6fTunXrcsdat25Nenp6lddMnjyZrKws323Hjh31VrdIUDokCIWEhPi5GJEGULbFhtGssWAUMF1jh5owYQLr1q3j66+/rvfndjqd+q1WpDYOCUI2W0D+biVSPd9gaa+fC5GGEHBBaOLEicyfP5+lS5fSrl27as9NSkpi9+7d5Y7t3r2bpCTNbBGpN4cEIZGgpL3GglrA/PpmjGHixInMnTuXzz//nE6djrzDdWpqKosXLy53bNGiRaSmpjZUmSLNj4KQBDtNnw9qAdMiNGHCBGbNmsUHH3xAdHS0b5xPbGws4eHhAIwbN462bdsybdo0AG688UaGDh3K448/zrnnnsvs2bP54YcfeOmll/z2PkSCTmkQcodG+7kQkQaiwdJBLWBahKZPn05WVhannnoqycnJvtvbb7/tO2f79u2kpaX57g8ZMoRZs2bx0ksv0a9fP9577z3mzZtX7QBrEamlgkxALUISxDR9PqgFTIuQMeaI5yxZsqTCsQsuuIALLrigASoSEUBdYxL8bGWzxhSEglHAtAiJSBOlICTBTmOEgpqCkIgcncKSxU1xKghJkPJ1jWkdoWCkICQiR8W48gGwOaP8XIlIA7GXLBRqaUHFoKQgJCJHR0FIgp2tdMV0tQgFJQUhETk6xXkA2MI0fV6ClF1dY8FMQUhE6s4YX4uQ5Yz0czEiDcSmrrFgpiAkInXnLvLtv2QP02BpCVJlY4S0jlBQUhASkborbQ0CsIdpjJAEqbIWIXWNBSUFIRGpu9Ig5LUcOJzhfi5GpIGUjRFS11hQUhASkborLglCxhGO3W73czEiDUQtQkFNQUhE6s5VMmPM6wjD4QiYHXtEaqd0jJC22AhOCkIiUneuAgC8dgUhCWJaWTqoKQiJSN2Vdo15HWHYbPpxIkFKQSio6SeXiNRdWdeYXQOlJYhpi42gpiAkInV3SIuQSNCyaR2hYKYgJCJ1VzZ93q4gJEFM0+eDmoKQiNSdq2z6vIKQBDFtuhrUFIREpO7KusY0RkiCmf3gOkLGGD8XI/VNQUhE6u6QdYREgtYhm64qCAUfBSERqbtD1hESCVr2g9PnvV6vn4uR+qYgJCJ1p1lj0hwcMmtMQSj4KAiJSN1pHSFpDuzqGgtmCkIiUnelXWOaNSZBzaausWCmICQidecuBMBrD/VzISINyH5w+ryCUPBREBKRunMXAWDsTj8XItKAfLPGPOoaC0IKQiJSd6VByHIoCEkQKxsjhMHrdvm5GKlvCkIiUne+IKQxQhLESscIAXhL/85L8FAQEpE6M57SL4UQBSEJYmVjhACvu9iPhUhDUBASkbpT15g0B7aDQQiPusaCjYKQiNRdaRCyhWodIQliNrvvj2oRCj4KQiJSdxojJM2BZWFKW4WMglDQCaggtHTpUkaOHEmbNm2wLIt58+ZVe/6SJUuwLKvCLT09vXEKFgl2nrIWIQUhCXJlrUIeBaFgE1BBKC8vj379+vH888/X6rqNGzeSlpbmuyUmJjZQhSLNiDGHdI1F+LkYkQZW2iKkrrHg4zjyKU3H2Wefzdlnn13r6xITE4mLi6v/gkSaM68bi5LF5dQ1JkGvdOaY0WDpoBNQLUJ11b9/f5KTkznzzDP55ptvqj23qKiI7OzscjcRqUTp9hoANqdahCTIla0lpCAUdII6CCUnJ/PCCy/w/vvv8/7775OSksKpp57KqlWrqrxm2rRpxMbG+m4pKSmNWLFIADmki8CuWWMS7OwaLB2sAqprrLa6d+9O9+7dffeHDBnC5s2befLJJ5k5c2al10yePJlJkyb57mdnZysMiVSmdKC0sezY7EH9o0TkkK4xBaFg0+x+eg0aNIivv/66ysedTidOpxaHEzmiQ3aet9vtRzhZJMCVLaqorrGgE9RdY5VZs2YNycnJ/i5DJPCVdhEYm4KQBD9Lg6WDVkC1COXm5rJp0ybf/S1btrBmzRoSEhJo3749kydPZteuXfznP/8B4KmnnqJTp0707t2bwsJCXnnlFT7//HM+/fRTf70FkeBR2iJkbCHYbM3udyppbkoHSysIBZ9a//S6/PLLWbp0aUPUckQ//PADxx13HMcddxwAkyZN4rjjjuOee+4BIC0tje3bt/vOLy4u5pZbbqFv374MHTqUH3/8kc8++4wzzjjDL/WLBJXSsRJGXWPSHNjVNRasat0ilJWVxbBhw+jQoQNXXnkll19+OW3btm2I2io49dRTMcZU+fiMGTPK3b/99tu5/fbbG7gqkWaqdDFFry0Uy7L8XIxIAysbI+RVEAo2tW4RmjdvHrt27eK6667j7bffpmPHjpx99tm89957uFz6CyLSbJQGIWMP9XMhIo1AY4SCVp069lu1asWkSZP48ccf+e677+jatSuXXXYZbdq04eabb+bXX3+t7zpFpKkpmz5f9puySDDzLajo9m8dUu+OaoRjWloaixYtYtGiRdjtds455xzWrl1Lr169ePLJJ+urRhFpinyDpdUiJM1AaYuQZRSEgk2tg5DL5eL999/nj3/8Ix06dODdd9/lpptu4vfff+f111/ns88+45133uH+++9viHpFpKkonT7vVdeYNAelLZ+WV0Eo2NR6sHRycjJer5eLL76YFStW0L9//wrnnHbaadrkVCTYqWtMmpPS1dMVhIJPrYPQk08+yQUXXEBYWNW7TcfFxbFly5ajKkxEmjgNlpbmxF6y44ClWWNBp9ZB6LLLLmuIOkQk0BwyfV4k6IWUbCxs8xT6uRCpb1oOVkTqxtcipK4xaQZCIwGwuQv8XIjUNwUhEakb3xghtQhJM1DaImSV/r2X4KEgJCJ141YQkmYkJAJQi1AwUhASkbopGyOkwdLSHJQFIbUIBR0FIRGpG02fl+YkVC1CwUpBSETqxn1w93mRoOdrEdKssWCjICQidVO6xYamz0uz4BsjpCAUbBSERKRuPGUtQuoak2bAN2tMQSjYKAiJSN1o01VpTsrWEfIUYozxczFSnxSERKRutMWGNCdlK0u7C/F6vX4uRuqTgpCI1E1p15gVUvW+gyJBI+Rgi5DH4/FzMVKfFIREpG7KBo06nP6tQ6QxlI0RchfidmsH+mCiICQidWJKp8/bHGoRkmagbB0h48ZdpLWEgomCkIjUTVmLkLrGpDkonT4P4CnK9WMhUt8UhESkbkoHS2uMkDQL9lCMVfKV6S3M8XMxUp8UhESkbkq32LDUNSbNgWX5WoW8RXl+Lkbqk4KQiNRNaYuQLTTcz4WINJLSAdNqEQouCkIiUjeaPi/NTekUerUIBRcFIRGpPa8XqywIqWtMmovSmWOmWEEomCgIiUjtlYYgUNeYNB+WxggFJQUhEam90oHSADZ1jUlzERYDgFV4wM+FSH1SEBKR2nMfDEJ2tQhJcxHdBgBH/h4/FyL1SUFIRGqvNAh5baHY7HY/FyPSSGJKg1CBglAwURASkdor23neFoJdQUiai9IgFFKQ4edCpD4pCIlI7ZWOETL2UGw2/RiRZiKmLQAhahEKKgH1E2zp0qWMHDmSNm3aYFkW8+bNO+I1S5YsYcCAATidTrp27cqMGTMavE6RoHdI15hahKTZOKRFyOv1+rkYqS8BFYTy8vLo168fzz//fI3O37JlC+eeey6nnXYaa9as4aabbuLqq69m4cKFDVypSJBzq0VImg+P17B88z4+3m4B4CjKpCBHM8eChcPfBdTG2Wefzdlnn13j81944QU6derE448/DkDPnj35+uuvefLJJxk+fHhDlSkS/DwHxwhZluXnYkQazoJ1adz33/WkZRUChg3OUMKtYr74/kf+OOx0f5cn9SCof5Vbvnw5w4YNK3ds+PDhLF++vMprioqKyM7OLncTkcO4SxZUNPYQPxci0nAWrEvjujdWlYYgAIvfTQsA5nz+DQvWpfmvOKk3QR2E0tPTad26dbljrVu3Jjs7m4KCgkqvmTZtGrGxsb5bSkpKY5QqEljcJV8MXpvTz4WINAyP13Dff9djDju+3NsLgFNtP3Lff9fj8R5+hgSaoA5CdTF58mSysrJ8tx07dvi7JJGmp3SLDWNTi5AEpxVb9h/SEnTQYu8AAE63ryYtq4AVW/Y3dmlSzwJqjFBtJSUlsXv37nLHdu/eTUxMDOHhla+G63Q6cTr1W65ItUpbhIw91M+FiDSMjJyKIQhgmbc3BSaUdtZe/mj7loyc4xq5MqlvQd0ilJqayuLFi8sdW7RoEampqX6qSCRI+KbPq0VIglNidOV76BURykuePwLwUMi/6Zr7Q2OWJQ0goIJQbm4ua9asYc2aNUDJ9Pg1a9awfft2oKRba9y4cb7zr732Wn777Tduv/12fv75Z/71r3/xzjvvcPPNN/ujfJHgUdY1phYhCVKDOiWQHBtGZXMin3OPZoW3OzFWPr0WX4ln+b/AlIwVKptq/8GaXSzfvE9jiAJAQHWN/fDDD5x22mm++5MmTQLg8ssvZ8aMGaSlpflCEUCnTp346KOPuPnmm3n66adp164dr7zyiqbOixytsq4xm4KQBCe7zWLqyF5c98YqLCg3aNqNg8uKJ/NJh7fovHsh9oWTKd7yDV/2vJd7FmwvN7YoOTaMqSN7MaJPcqO/B6kZyxijuFqN7OxsYmNjycrKIiYmxt/liDQNS/4JSx5if+dRJIz7j7+rEWkw5dcRKuELN72TKPjiccK+egjLePjNm8RE199Ybzr6zi1rUZo+doDCUCOr6fd3QLUIiUgT4Zs+rxYhCW4j+iRzZq8kVmzZT0ZOIYnRYQzqlIDdVhJxwk+/leJOJ7Hv9bF0tqUzN3Qqt7vG84H3ZKCkJckC7vvves7sleS7TpqOgBojJCJNhG+LDc2wlOBnt1mkdmnBqP5tSe3SokKYWek9hhGFD/GZ5ziclounQ//FDfY5lHWoGSAtq1BT7ZsoBSERqT13yYKkXgUhETJyCskiivGuW3jBXTKj7JaQ93jU8SIO3OXOk6ZHQUhEaq+sRUhdYyK+qfYGGw+7L+Eu11W4jY0LHEt5LuRZQkrDUFVT8sW/FIREpPZcahESKXP4VPtZnjP4q+tmioyDEfbveTHkCTrE2BjUKcGvdUrlFIREpPZ8Y4TUIiRSNtUeDs4SW+wdyFWu2ygwoZxuX8PsyMexe4r8V6RUSUFIRGqvdIyQBkuLlBjRJ5npYweQFHuw++trb18mhd6NyxZG8oHvKXjjEvC4/FilVEbT50Wk9sq22FCLkIhP5VPtz8Ha0g/vm38mfNtiCmb/hfCLXweb2iGaCv2fEJHaKx0jZIVUvnmxSHNV2VR7W5ehmAtex1h2wn/9kMIPtM1TU6IgJCK1V9oihEOzYERqwt7zHLyjpgMQ9uMMCpc+4+eKpIyCkIjUmnGrRUiktuz9x+A+dQoAzs+n4vppvp8rElAQEpG6KN1iwwpVEBKpDcfQW3H1vRgLL7Y5V+PZtcbfJTV7CkIiUnuu0iAUEuHnQkQCjGURMvpZitsNwe4pwPvGnzE56f6uqllTEBKR2ittEbKpRUik9uwhhF76FsWxnQkp2EPBfy7StHo/UhASkdox5pAgpBYhkToJjyP0snfwOCKI2LOavA9uw+M1LN+8jw/W7GL55n14vMbfVTYLWkdIRGrH68YyXkBBSOSotOyGdf6L8M5lRP7vNSb/lMBbeQN9DyfHhjF1ZC9G9En2Y5HBTy1CIlI7pWsIAdicCkIiR8PW6//Y1PUvAExxP0cXa5fvsfSsQq57YxUL1qX5q7xmQUFIRGrHfXC/JLtahESOisdruGL72Szz9CLSKmJ6yFOEUbqXX+k59/13vbrJGpCCkIjUTukaQl5bKHaHetdFjsaKLfvZme3iBtcNZJg4jrHt4u+ON32PGyAtq5AVW/b7r8ggpyAkIrXj23neid1u93MxIoEtI6dk4sE+Ypnkug6Ayxyfcabth0rPk/qnICQitVM6RshrD8WmjSNFjkpidPnd6l90nwvAIyEv0Zr9lZ4n9Us/xUSkdtQiJFJvBnVKIDk2DKv0/mPuMaz1diTeyuWJkOnY8JIcG8agTgl+rTOYKQiJSO0cOkZIQUjkqNhtFlNH9gLAAlw4uNE1kXzj5CT7T1xl/4SpI3tht1nVP5HUmYKQiNTOIS1ClqUfziJHa0SfZKaPHUBSbEn312+mDQ+4xwJwR+i7DGt5wJ/lBT1N+RCR2ildVdprD/VzISLBY0SfZM7slcSKLfvJyCkkMWowrqW/ErJ9KfnvXIVj4tdgUwtsQ1CLkIjUTumGq8bu9HMhIsHFbrNI7dKCUf3bktq1JSF/mo4nJJKI/evJXTTN3+UFLQUhEamdshYhm1qERBpUbDtsZ/8TgIjvnsKdts7PBQUnBSERqR23WoREGot13FjcnU7H5nVR/M5V4HH7u6SgoyAkIrVTlAOA1xHu50JEmgHLwnHev/CERBNx4Gdyv3jC3xUFHQUhEamd4lwAvCHaZ0ykUcQkYxv+DwDClz+BZ/82PxcUXBSERKR2ikqCkMehICTSWKwB43C3OQG7p4C8d68Do01Y64uCkIjUTlmLkIKQSOOx2XCc9zxey0FM2jfk/fCWvysKGgEXhJ5//nk6duxIWFgYgwcPZsWKFVWeO2PGDCzLKncLC9N+LSJHRUFIxD9adYeTbwIgdPEUTEGmX8sJFgEVhN5++20mTZrE1KlTWbVqFf369WP48OFkZGRUeU1MTAxpaWm+27Zt6lsVOSpFZUFIg6VFGpvtlNtwx3YipHAf2XNv9Xc5QSGggtATTzzB+PHjufLKK+nVqxcvvPACERERvPrqq1VeY1kWSUlJvlvr1q0bsWKRIKTB0iL+ExKGY/QzAMT88h4Fv37F8s37+GDNLpZv3ofHq7FDtRUwW2wUFxezcuVKJk+e7Dtms9kYNmwYy5cvr/K63NxcOnTogNfrZcCAATz00EP07t27yvOLioooKiry3c/Ozq6fNyASLEpbhHBG+7cOkeaq0ym4+16EY+1str85gUsLH8Rb2q6RHBvG1JG9GNEn2c9FBo6AaRHau3cvHo+nQotO69atSU9Pr/Sa7t278+qrr/LBBx/wxhtv4PV6GTJkCDt37qzydaZNm0ZsbKzvlpKSUq/vQyTQmeKSdYRsYTF+rkSk+fqy49/IMhF0ZxuX2Bf7jqdnFXLdG6tYsC7Nj9UFloAJQnWRmprKuHHj6N+/P0OHDmXOnDm0atWKF198scprJk+eTFZWlu+2Y8eORqxYJACUtggpCIn4h8drmPJpOo+5LwTgNsfbJFDSe1HWMXbff9erm6yGAiYItWzZErvdzu7du8sd3717N0lJSTV6jpCQEI477jg2bdpU5TlOp5OYmJhyNxE5RHEeAPaIWD8XItI8rdiyn7SsQmZ5zmC9twOxVj63Ot72PW6AtKxCVmzZ778iA0jABKHQ0FAGDhzI4sUHmwC9Xi+LFy8mNTW1Rs/h8XhYu3YtycnqOxWpE48Ly1Myhk4tQiL+kZFTst+fBzv3uC4H4CL7Evpav1V6nlQvYIIQwKRJk3j55Zd5/fXX2bBhA9dddx15eXlceeWVAIwbN67cYOr777+fTz/9lN9++41Vq1YxduxYtm3bxtVXX+2vtyAS2Er3GQOwh6tFSMQfEqMProf3g+nBHM/J2CzD/SEzsPBWep5ULWBmjQGMGTOGPXv2cM8995Cenk7//v1ZsGCBbwD19u3bsdkOZrsDBw4wfvx40tPTiY+PZ+DAgSxbtoxevXr56y2IBLayqfO2UELCNH1exB8GdUogOTaM9KxCDDDNdTFn2X7gONsm/mxfynueU0mKDWNQpwR/lxoQLGO0YUl1srOziY2NJSsrS+OFRHavh+mpuEPjcN38M+HhWlRRxB8WrEvjujdWASVjgq62f8SUkDfZa2I4vegJHhl7crOfQl/T7++A6hoTET87ZDHFkJAQPxcj0nyN6JPM9LEDSIot6f6a4RnOJm8bWlrZzOq6uNmHoNoIqK4xEfGz4oM7z4fY7X4uRqR5G9EnmTN7JbFiy34ycgpxZd0PX1xNr9/fw5VxCyGJ3fxdYkBQi5CI1FzpYGmvIwLLsvxcjIjYbRapXVowqn9bep7yZ9wdTsHmdZH/wW3+Li1gKAiJSM3l7QHA44zzbx0iUpFl4TjnYQw2Ynd9waolH2gPshpQ15iI1FxuSRByh8X7uRARqVTr3mzv+Cc6bH0Xx+dTuan4AQw27UFWDbUIiUjNlbYIuZ0KQiJN0YJ1afz559PJMeEca9vCaNs3gPYgq46CkIjUXF4GAG6n1icRaWo8XsN9/13PHmJ53j0KgNtD3iacQu1BVg0FIRGpOV/XmIKQSFNTtgcZwGueEezwtiLZ2s819o8A7UFWFQUhEakxU9o1RmRL/xYiIhUcurdYEaE87L4YgL865tOa/ZWeJwpCIlIbpV1j9lgNuBRpag7fW+wj72C+9x5DhFXELY53qzyvuVMQEpGacRVila4jFBLX1s/FiMjhyvYgO7jCl8WDrrEA/Mm+lO7WDpK1B1kFCkIiUjOl3WJeWwjOmFZ+LkZEDme3WUwdWbKpeFkYWmO68rFnEHbLcLtjNlNH9sJu02Koh1IQEpGayS3pFvM443GGqWldpCk6fA8ygEfdY3Bj4wz7ak6xr/NjdU2TFlQUkZrZ+wsARVFtiXQ6/VyMiFTl8D3IEqNPxPppHax6DfPpPSwPOY6M3CISo0u6yZp7C5GCkIjUzJ4NABTFdCJK+4yJNGlle5D5tL4L15rZRB5Yz39efYZPvIMBtOI06hoTkZrKKAlChTGd/VyIiNTWgq0eni8+G4DbHG/jwA1oxWlQEBKRGjIZ6wEojuvq50pEpDbKVpx+2X0ue0wMnW3pXGT/AkArTqMgJCI1UZiNlbUTAGdKPz8XIyK1UbbidB7hPO3+EwA3Ot4nkgJAK04rCIlIBR6vYfnmfXywZhfLN+/D++siAIoi2xKT2N7P1YlIbRy6kvRsz2n85k2ilZXNeMdHVZ7XnGiwtIgAJeFnxZb9fLY+nblrdrE/z+V7bEbEi5wKZLc7jVZRUX6rUURq79CVpN04eNQ9humhTzPe/hFvuoexh7gK5zUnahESERasS+Pkf37OxS9/y7+/2VouBHW00kj1rAJgachJ/ipRROro8BWnP/EOYrW3K5FWEX9zzMGCZr3itIKQSAA7vAurLoMdF6xL47o3Vvl2rT5UW/bwfMgzOC0XX3t68+jGVs12QKVIoKq44rTFNFfJhqwX2b+gg5XerFecVteYSBNV7PYyc/lWtu3PJyU+nB5JMezPL/YtgrZofTr3/Xd9uQBT2zVBymaTGCCCQrpYv9PV2kUX2+/0tbYwxPYTIZaHAyaKO1zXkO4qZsWW/eXXJxGRJq9sxemynxkrTE8+9/TndPsa/p38IV36XOXvEv1GQUjEzw4NPB0SIrgstSOPf/ozL3+1haoaX+IiQsjMd1U4XrYmyPSxAyqGIWMgby9kboMDWyFzG3u3beTR/HV0cqbT1tpX6Wst8/TiDvd4dlGyv1hzHVApEugOX3G6hftBzPw/0mX/Eoq2foez42B/l+gXCkIifjTt4/UVAs8DH2044nWVhSCAMAppb+1h8bz/cVZOLLbM7b7QYw5sw3LllTu/NdDafvD+HhPDZtOWTd42/Gra8bW3D5tN+Z3mm+uAytryeDy4XJX/fxLxp+PaRgKRQAvyd16FfdNC8j5/EnPJDD9XVjshISHY7fYjn3gECkIi9aBsxlXJvj41279n2sfreXHpllq8iiGOXNpY+0pve2lj7aeNtZcUaw8pVgYtreySU93AwvJXW4DBwh3ekuKIZIqj2rDTm8iMzRFsNa3ZZNqSRdUzwiwgqRkPqKwpYwzp6elkZmb6uxSRI+t2Bab1cCwM5pf1WCHh/q6oVuLi4khKSsI6im1/FIREjtKCdWm1HqtT7Pby8lflQ5CTYpJ9IWcfbSgLOwePRVhFR6wn00Syw7QiPCGF2MQUXJFtKI5MxtaiM87W3YiMiSciIoJIm40Yr2HZPz8nPauQmgyBbs4DKmuqLAQlJiYSERFxVD+gRRqDyYnGKtiP1+bE1qIjBMDfWWMM+fn5ZGRkAJCcXPe90hSEJOBV1hoD8O1v+1i+eR9gSO3ckhO7tMBus+rUelOVshlXh4eIcmN1eidBwQHISYPsNMhJY+269dxn/4Uk6wCtrf0kW/toVdaacwR7TAy/m5b8blqQZlrwu2nBDtOKnSaRHaYV2UQC8NbIE+l6hEHNZbNJrntjVWmLUeW0MWPNeDweXwhq0UIDyiVAhLTF7M7CohiPNx97ZGD83Q0PL2m9ysjIIDExsc7dZApC0qRUNnA41GGrMuw8u/hXXvn6N3KLPL7niIsIweX2kld88NhzX2wmLiKEMce348Mf045qplUZj8fLYx9+TydrN62tAyRygNbWAZKsAyRaJX9u+14mZm4mlqe43LUDgYGV/OvLN05+Lw03JbeW/E4LdpUGn3STQBGh1dZV2y6sw2eTlGkRGcqo/m04s1fSUYXF5qRsTFBERISfKxGpBXsIRCVCbjpWThq59hjcXoPDZiPSaW/SrZpl/9ZcLledg5BljNGiINXIzs4mNjaWrKwsYmJi/F1Ok3ek1pbqHq9s4LDNgjN6JrJuV3a5L+m4iBDyiz0Uu71HXXNZddPHDmBEr9YlrTd5eyAvA3IzSv6cm1FyP28v5GZg8jIwORnYvMXVPveh3KGxuMJb4Q5ryeaiGJbujWC3SWC3iSfNtGCXaUEmUYdUdJTvpbbBrh5bypqrwsJCtmzZQqdOnQgL06ByCSBeD97dP2EzHnaZluwz0QCE2G20iQsjNrz6X8D8pbp/czX9/laLUBNW1RdTZcc9XnPElpSWkU6wYG9uUbVfdIc//8AO8azcduCIX5BHGitT3eOrtx+odOCw18Ci9RkVjlc1a+pwToqJJ4d4K5c4K5cEcoi3cogjl3grl3grhxZk09LKIvG9bIwtB8vrPuLzWhwMHbkmjN0mnnSTwG7iyTDx7DZxJfdNPGOG9OTUgb0Jj4olIiKCcIeDXm4v59/9SZXT42vy+oaK0+iTjqILy26ztD6QSDOVVeQh1xtHW2sfiRzgAFF4sXB5vGzbl0+HFjTZMHS0FISaqKpCw//1S67QtRMRaqfA5eHQtr0HP95QaUvKoSrrEqrsdW0W5b6wq7quurEy15zSiZeWbqny8epYeImmgBgrn2jyiSGfGCvP9984K5d4cn0BJ8HK8R2ryeDickobmNwh0bjDEvA4E3CHxeMOS8DtjMddep/IRDYWxfG3T7MoxFntU97W6wRatykfMEIdNsb/oVO1s8aqG7NTFngOXRNErTjBIxha5zp27MhNN93ETTfdVKPzlyxZwmmnncaBAweIi4tr0NoON2PGDG666aZmO9PPGMPvmYW4TQwtycJpuWlJFhkmznfO75mFxISFNOlusroKuCD0/PPP8+ijj5Kenk6/fv149tlnGTRoUJXnv/vuu9x9991s3bqVbt268c9//pNzzjmnESuuvapCRVpWYaVfnPmHjIUpU1VLyqEOX3yvqtc9vNXi8OsOXZ34UHY8RFJIJIUs/noXfa1CIq1CIigkkiIirEKiKCDaOjTcFPhCTtnxKAqwWXXvwXUZO5lEccBEcYBoDphoDpgo37H9xLDXxLLHxDLuDz05fUAPwiJjcDqdOEOq/offzmuI/67qGVdHGqsz+ZySJe8r6w4c/4dO3HJWj2pXli77YlQrTnCpyyzEo3GkL7apU6dy77331vp5v//+eyIjI2t8/pAhQ0hLSyM2NrbWr+UPtQ16TVlekQeXp+S3wN0mnvbWHlqRxT5i8JTuxOXyeMkr8hAVFnCx4YgC6h29/fbbTJo0iRdeeIHBgwfz1FNPMXz4cDZu3EhiYmKF85ctW8bFF1/MtGnT+OMf/8isWbMYPXo0q1atok+fPn54B0dWVag4egY7Xhx4CMWNAzcOPIRZLl7/YCFnxPZj7gffMMSWixMXYRSX3CwXTooJw0WYVYyTYpy4CKcY5ngw62LIycrkuYLdRIaWhJ4Iq+S/YVb9LiZXaELIJpJsE0EOEb7/lgScqNKAE00mUew30RwgikwTTQ7h1HTcTfvu/WmVVLNgUd2Mq7JXO9J088nn9CoXeA7t1gS46g+da1SLBIcazUKs5zCUlpbm+/Pbb7/NPffcw8aNG33HoqIOri1ljMHj8eBwHPmro1WrVrWqIzQ0lKSkpFpdI/XD7T041jKTKFqZLMKtYhLJJM0kVHpeMAmowdKDBw/mhBNO4LnnngPA6/WSkpLCDTfcwJ133lnh/DFjxpCXl8f8+fN9x0488UT69+/PCy+8UOlrFBUVUVR0sDslOzublJSU+h8svfQx2L2uZNsD4y29GfbnFbFq2z5sGGwYrNKbDW/pfbBZ3tJjBgduQvDgwENI2Z+tsj+XhB0HHpzWkce9NBSXsZNHGLmEk2+c5BNGrgkjnzDyCCPbRJBNJDkm3Bd0Dr+fQwTFhDRYjWWtN1/fcXqtuyAa+zd4abqOZrC0x2s4+Z+fV9mVfTR/R2vq8C6isu6qjz/+mClTprB27Vo+/fRTUlJSmDRpEt9++y15eXn07NmTadOmMWzYMN9zHd5iYlkWL7/8Mh999BELFy6kbdu2PP744/zf//1fudcq6xorq+Xtt9/mpptuYseOHZx88sm89tprvjVj3G43kyZN4j//+Q92u52rr76a9PR0srKymDdvXrXv85577mHv3r0MHz6ck08+mQceeMD3vjdv3lzt+zv11FP58ssvyz2nMYZ9+/YxceJEli5dyoEDB+jSpQt33XUXF198cT3832k4uYVuftub67sfTQGdbOl4jcVG0w5XaZtJ55ZRTa5FqFkNli4uLmblypVMnjzZd8xmszFs2DCWL19e6TXLly9n0qRJ5Y4NHz682n8g06ZN47777quXmqu1bRlsXlzhcAIw7OhXDK8Rr7EoIoQiQsDhJNMVQiGhFFH6X1Py38P/XEgohabkvJO7JBAaFsmMdUXkEUaeCSePMPKNsyT4EOb7R9RU1bT1piqH798TqGM6xL9WbNlfZQiCkhbHtKxCv2x6e+edd/LYY4/RuXNn4uPj2bFjB+eccw4PPvggTqeT//znP4wcOZKNGzfSvn37Kp/nvvvu45FHHuHRRx/l2Wef5dJLL2Xbtm0kJFTefZyfn89jjz3GzJkzsdlsjB07lltvvZU333wTgH/+85+8+eabvPbaa/Ts2ZOnn36aefPmcdppp1VZw3fffcdVV13FtGnTGD16NAsWLGDq1KnlzsnNza32/c2ZM4d+/fpxzTXXMH78eN91hYWFDBw4kDvuuIOYmBg++ugjLrvsMrp06VLtEA5/i3TaCbHbfN1jOYSTa8KIsgppzQF2mlaE2Eum0gejpv0NdYi9e/fi8Xho3bp1ueOtW7fm559/rvSa9PT0Ss9PT0+v8nUmT55cLjyVtQjVuxOuIq/dyWRl5YBlw1gl85B2Zrt5b0NuSTuQsfBScitp/wEvttL7JTcXdtzYceHAbUr+W3bMjZ1iHLiNo/Scg+e6cOAt7fsFmHxqN6Yt/LXWb+OMoScyqFMCt1SzOrFFyUKlVc2QsoAIp528oopjnerK6bBRdNjU+qrWETqamVZlNONKjlZNN7P1x6a3999/P2eeeabvfkJCAv369fPdf+CBB5g7dy4ffvghEydOrPJ5rrjiCl/ryEMPPcQzzzzDihUrGDFiRKXnu1wuXnjhBbp06QLAxIkTuf/++32PP/vss0yePJnzzjsPgOeee46PP/642vfy9NNPM2LECG6//XYAjjnmGJYtW8aCBQt85/Tr16/a95eQkIDdbic6Orpcd17btm259dZbffdvuOEGFi5cyDvvvNOkg5BlWbSJC2PbvnzfsXSTQFfrd+LJZS9xRIVHkVfkafLrCtVFwAShxuJ0OnE6q58FVC96nEtkj3M5fChhktdwUy22PDhaZc3tV/6hKzO+3VHj1z10IHBNxsqM/0PJrDGqePzxC/qxevuBGq8jFB8RQpHbW2GgeJTTziN/OpbhfZKrXFn69hE91XojTU5NN7P1x6a3xx9/fLn7ubm53HvvvXz00UekpaXhdrspKChg+/bt1T7Pscce6/tzZGQkMTExvi0SKhMREeELQVCyjULZ+VlZWezevbtcwLDb7QwcOBBvNWNZNmzY4AtOZVJTU8sFobq+P4/Hw0MPPcQ777zDrl27KC4upqioKCAW2IwND6VDi5LZYS6Pl3ycZJlIYq08ktjP1twQ9uYW4bDZaBsXRmxE8EylD5gg1LJlS+x2O7t37y53fPfu3VUOsEtKSqrV+U1BTbc8qA+HdgmFOmw1ft3KupKqWp340NaW49rHV/v4iD7JVQ4crnIbjc37WP7bXqCkRebEzi18NZ3UtSUndW1ZoX613khTNKhTAsmxYXWehdiQDp/9deutt7Jo0SIee+wxunbtSnh4OH/+858pLq5+gdGQkPLj/CzLqja0VHZ+Ywxrrev7e/TRR3n66ad56qmn6Nu3L5GRkdx0001HvK6piA0PJSYshLwiD9mFLtJz44khjxgrnwhTSD5huL1etu3Pp5XLQ3JsYG3QWpWACUKhoaEMHDiQxYsXM3r0aKBksPTixYurbIpNTU1l8eLF5aY3Llq0iNTU1EaouO6qChVVrSMUGWon/7B1hKpqSTnU4V1CVb3u4esIVdWVdKSxMjUZSxPqsFU6U6qq8HJSt5ac1K1i2BEJNPUxC7GxfPPNN1xxxRW+lpXc3Fy2bt3aqDXExsbSunVrvv/+e0455RSgpEVm1apV9O/fv8rrevbsyXfffVfu2Lffflvufk3eX2hoKB6Pp8J1o0aNYuzYsUDJd9Qvv/xCr1696vIW/cKyLCKddnYcyMdFCPuJpgU5JFsH2GwO/szfk1NERIg9KFqGAiYIAUyaNInLL7+c448/nkGDBvHUU0+Rl5fHlVdeCcC4ceNo27Yt06ZNA+DGG29k6NChPP7445x77rnMnj2bH374gZdeesmfb6NGqgsNlXXt1NfK0pW9bk1XloYjt7aoNUakajVpWW0KunXrxpw5cxg5ciSWZXH33XdX27LTUG644QamTZtG165d6dGjB88++ywHDhyodgzL3/72N0466SQee+wxRo0axcKFC8t1i0HN3l/Hjh1ZunQpF110EU6nk5YtW9KtWzfee+89li1bRnx8PE888QS7d+8OqCAE5dcVyjDxxJNLpFVIjMknm4PdfLsyC4gJD/xFFgMqCI0ZM4Y9e/Zwzz33kJ6eTv/+/VmwYIFvQPT27dux2Q4OAB4yZAizZs1iypQp3HXXXXTr1o158+Y12TWEDldVaKjsuN1m1aolpbavq/Ai0jgCYRbiE088wV/+8heGDBlCy5YtueOOO8jOzm70Ou644w7S09MZN24cdruda665huHDh1e7+eaJJ57Iyy+/zNSpU7nnnnsYNmwYU6ZM4YEHHvCdU5P3d//99/PXv/6VLl26UFRUhDGGKVOm8NtvvzF8+HAiIiK45pprGD16NFlZWQ32GTSEQ9cLcmFnLzEkkkWStZ8cE+FrrXR7TVAsshhQ6wj5gzZdFZGa0qar/uX1eunZsycXXnhhuWAjtXP4ukJ2vHS3duCwvOzwtuIABxfZbJ8QQZwfu8ea1TpCIiIih9q2bRuffvopQ4cOpaioiOeee44tW7ZwySWX+Lu0gBbptOOw2XwtQx5s7CGOZPbT2jpAlonEWzpyzXFIL0ygCvx3ICIizZLNZmPGjBmccMIJnHTSSaxdu5bPPvuMnj17+ru0gGZZFm3jyreu7DMxFBs7oZabBKukmzBYFllUi5CIiASklJQUvvnmG3+XEZRiI0Jp5fKwJ6dkyykvFhnE0469JJLJAaJpExcR8AOlQS1CIiIiUonk2HA6JETgKB2of8BEU2hCcFheOofnERse+FPnQS1CIiIiUoXYiFBiwksWWXR7vRh3MuRuJ6xoH3iSwN5wm2E3FrUIiYiISJUsyyIqzEFcRCjh0Ql4HeFYGDxZv/u7tHqhICQiIiI1Y1lYsW0BsBXux7gbfxPg+qYgJCIiIjVmOaPxhkZhAd7MXeQWusnMLya30N0oe8HVN40REhERkVqxxbbF7NmIvTibtL37KMAJlEypbxMXFlADqdUiJCIijeaKK67wbZwNcOqpp5bbGLsu6uM5pHay3A4yTckK00nWAd9xl8fLtn35ZBUU+6u0WlMQEhERrrjiCizLwrIsQkND6dq1K/fffz9ut7tBX3fOnDk13g5jyZIlWJZFZmZmnZ9Djp4xht8zC9lt4vEaiLYKiKKg3Dm/ZxYGTDeZgpCIiAAwYsQI0tLS+PXXX7nlllu49957efTRRyucV1xcf7/tJyQkEB0d7ffnkJor252+GAf7KdnD69BWIShpGcooXYyxqVMQEhFpKMZAcZ5/bnX4bdzpdJKUlESHDh247rrrGDZsGB9++KGvO+vBBx+kTZs2dO/eHYAdO3Zw4YUXEhcXR0JCAqNGjWLr1q2+5/N4PEyaNIm4uDhatGjB7bffXqGV4PBuraKiIu644w5SUlJwOp107dqVf//732zdupXTTjsNgPj4eCzL4oorrqj0OQ4cOMC4ceOIj48nIiKCs88+m19//dX3+IwZM4iLi2PhwoX07NmTqKgoXwiUIzt0d/oME4fHWERYRcSSV+683dmFAdFFpsHSIiINxZUPD7Xxz2vf9TuERh7VU4SHh7Nv3z4AFi9eTExMDIsWLQLA5XIxfPhwUlNT+eqrr3A4HPzjH/9gxIgR/O9//yM0NJTHH3+cGTNm8Oqrr9KzZ08ef/xx5s6dy+mnn17la44bN47ly5fzzDPP0K9fP7Zs2cLevXtJSUnh/fff509/+hMbN24kJiaG8PDwSp/jiiuu4Ndff+XDDz8kJiaGO+64g3POOYf169cTElKyAGB+fj6PPfYYM2fOxGazMXbsWG699VbefPPNo/rMmoNDN1p1Y2cvcbTmAEnWAbJNJIdG3V0HCogJC2nSW3EoCImISDnGGBYvXszChQu54YYb2LNnD5GRkbzyyiuEhpbMBnrjjTfwer288sorvi+51157jbi4OJYsWcJZZ53FU089xeTJkzn//PMBeOGFF1i4cGGVr/vLL7/wzjvvsGjRIoYNGwZA586dfY8nJCQAkJiYSFxcXKXPURaAvvnmG4YMGQLAm2++SUpKCvPmzeOCCy4ASoLcCy+8QJcuXQCYOHEi999/f10/smYl0mknxG7D5SlpGdpjYkggG6flIp4c9puD3ZRuryGvyE1UWNNdgVpBSESkoYRElLTM+Ou1a2n+/PlERUXhcrnwer1ccskl3HvvvUyYMIG+ffv6QhDAjz/+yKZNmyqMzSksLGTz5s1kZWWRlpbG4MGDfY85HA6OP/74KgfRrlmzBrvdztChQ2tde5kNGzbgcDjKvW6LFi3o3r07GzZs8B2LiIjwhSCA5ORkMjIy6vy6zYllWbSJC2PbvnwAvNjIII627KM1B8gkCi8HW4ByizwKQiIizZJlHXX3VGM67bTTmD59OqGhobRp0waH4+BXRGRk+feRm5vLwIEDK+1KatWqVZ1ev6quroZQ1kVWxrKsgJnl1BTEhocSG+4iq8AFwH4TQ0uycFpuWpJFhok75Oym/blqsLSIiAAlYadr1660b9++XAiqzIABA/j1119JTEyka9eu5W6xsbHExsaSnJzMd99957vG7XazcuXKKp+zb9++eL1evvzyy0ofL2uR8ng8VT5Hz549cbvd5V533759bNy4kV69elX7nqR2WkQebCE0wG4TD0ArsrBzcEB1lLNpt7koCImISK1deumltGzZklGjRvHVV1+xZcsWlixZwt/+9jd27twJwI033sjDDz/MvHnz+Pnnn7n++usrrAF0qI4dO3L55Zfzl7/8hXnz5vme85133gGgQ4cOWJbF/Pnz2bNnD7m5uRWeo1u3bowaNYrx48fz9ddf8+OPPzJ27Fjatm3LqFGjGuSzaK4inQ7stoNdYJlEUWBCsVteEq1MAOw2i0gFIRERCTYREREsXbqU9u3bc/7559OzZ0+uuuoqCgsLiYkpWVvmlltu4bLLLuPyyy8nNTWV6OhozjvvvGqfd/r06fz5z3/m+uuvp0ePHowfP568vJJp2W3btuW+++7jzjvvpHXr1kycOLHS53jttdcYOHAgf/zjH0lNTcUYw8cff1yhO0yOjmVZtIsv352ZbkoGtLcgmxDctIsPb9IzxgAso07RamVnZxMbG0tWVpbvH7eISGUKCwvZsmULnTp1IiwszN/liDSKrIJifs8s9M0i62ylEWUVUuiIISyxyxGuPjrV/Zur6fd3026vEhERkSYtNjyUmLAQ8oo8uL1ebN62kL0Zpzsbb3E+ttDaz2BsTOoaExERkaNiWRZRYQ7iIkKJiIrBOGOxAJO5o06rnDcmBSERERGpV1ZsWwwWdnc+3oJMf5dTLQUhERERqV8OJ0SWrieVvQuMt/rz/UhBSEREROqdFZ2EsRzYvC482bv9XU6VFIRERESk/tnsEFuy6bAtLwPjcfm5oMopCImIiEiDsMIT8DrCsfDizdzp73IqpSAkIiIiDcOysMW2A8BWlIm3KM/PBVWkICQiIiINxxmFCYsrmU6f1fSm0ysIiYg0sOLiYgoKChrtVlxc7O+3XCVjDNdccw0JCQlYlsWaNWs49dRTuemmm6q9rmPHjjz11FONUmNz1xCftRVTNp2+AE/+/np97qOllaVFRBpQcXExv/76K425m5FlWXTr1s23W3tNpKen8+CDD/LRRx+xa9cuEhMT6d+/PzfddBNnnHFGvdW2YMECZsyYwZIlS+jcuTMtW7Zkzpw5QbEP2NatW+nUqROrV6+mf//+Nbrm3nvvZd68eaxZs6ZBa6tPLpeLadOm8frrr7Nr1y66d+/OP//5T0aMGOE7Jycnh7vvvpu5c+eSkZHBcccdx1MP3s2g7klY2b9jwuN4/IkneeSRRwC44447uOWWW3zXf/fdd1x//fV89913OBwNG1UCpkVo//79XHrppcTExBAXF8dVV11V6c7Dhzr11FOxLKvc7dprr22kikVEwOPxNGoIgpJWF4/HU+Pzt27dysCBA/n888959NFHWbt2LQsWLOC0005jwoQJ9Vrb5s2bSU5OZsiQISQlJeFwOEhISCA6OrpeX6e5acxWwClTpvDiiy/y7LPPsn79eq699lrOO+88Vq9e7Tvn6quvZtGiRcycOZO1a9dy1llnceboi9i5ez8242bNss+45557mD17Nm+99RZTpkxh7dq1ALjdbq699lpeeOGFBg9BEEBB6NJLL+Wnn35i0aJFzJ8/n6VLl3LNNdcc8brx48eTlpbmu5WlTxERKXH99ddjWRYrVqzgT3/6E8cccwy9e/dm0qRJfPvtt77ztm/fzqhRo4iKiiImJoYLL7yQ3bsPrg9z77330r9/f2bOnEnHjh2JjY3loosuIicnB4ArrriCG264ge3bt2NZFh07dgSo0DWWkZHByJEjCQ8Pp1OnTrz55psVas7MzOTqq6+mVatWxMTEcPrpp/Pjjz/WuBYAr9fLI488QteuXXE6nbRv354HH3zQ9/iOHTu48MILiYuLIyEhgVGjRrF169Yaf65LlizBsiwWL17M8ccfT0REBEOGDGHjxo0AzJgxg/vuu48ff/zR98v6jBkzavX+XnnlFd+Goy+99BJt2rTB6y2/eOGoUaP4y1/+ApQE0VGjRtG6dWuioqI44YQT+Oyzz2r8ngBmzpzJXXfdxTnnnEPnzp257rrrOOecc3j88ccBKCgo4P333+eRRx7hlFNOoWvXrtx777107dqV6W8vAOCXdWs4tm8fTj/9dM444wyOPfZYfv75ZwAeffRRTjnlFE444YRa1VVXARGENmzYwIIFC3jllVcYPHgwJ598Ms8++yyzZ8/m999/r/baiIgIkpKSfLcj7SBfVFREdnZ2uZuISLDav38/CxYsYMKECURGRlZ4PC4uDigJDaNGjWL//v18+eWXLFq0iN9++40xY8aUO3/z5s3MmzeP+fPnM3/+fL788ksefvhhAJ5++mnuv/9+2rVrR1paGt9//32lNV1xxRXs2LGDL774gvfee49//etfZGRklDvnggsuICMjg08++YSVK1cyYMAAzjjjDPbvPzj+pLpaACZPnszDDz/M3Xffzfr165k1axatW7cGSrp/hg8fTnR0NF999RXffPMNUVFRjBgxotatL3//+995/PHH+eGHH3A4HL5QMmbMGG655RZ69+7t+2W97POsyfvbtGkT77//PnPmzGHNmjVccMEF7Nu3jy+++MJ3Ttn/30svvRSA3NxczjnnHBYvXszq1asZMWIEI0eOZPv27TV+P0VFRRV2eg8PD+frr78GSlp0PB5Pped88+33eJ0xHNuzK7/88gvbt21j27Zt/PLLL/Tp04fNmzfz2muv8Y9//KMWn/BRMgHg3//+t4mLiyt3zOVyGbvdbubMmVPldUOHDjUtW7Y0LVq0ML179zZ33nmnycvLq/a1pk6daoAKt6ysrHp5LyISvAoKCsz69etNQUGB71h+fr5Zu3Zto9/y8/NrVPN3331ngGp/lhpjzKeffmrsdrvZvn2779hPP/1kALNixQpjTMnPz4iICJOdne0757bbbjODBw/23X/yySdNhw4dyj330KFDzY033miMMWbjxo3lntMYYzZs2GAA8+STTxpjjPnqq69MTEyMKSwsLPc8Xbp0MS+++GKNasnOzjZOp9O8/PLLlb7fmTNnmu7duxuv1+s7VlRUZMLDw83ChQsrvWbLli0GMKtXrzbGGPPFF18YwHz22We+cz766CMD+P6OTJ061fTr16/c89T0/YWEhJiMjIxy54waNcr85S9/8d1/8cUXTZs2bYzH46m0ZmOM6d27t3n22Wd99zt06OD7rCtz8cUXm169eplffvnFeDwe8+mnn5rw8HATGhrqOyc1NdUMHTrU7Nq1y7jdbjNz5kxjs9nMMcccY4yr0Hh3rTbTp91ljunaxRxzzDFm+vTpxhhjzjjjDDN37lzz7rvvmt69e5v+/fubL7/8sspaKvs3VyYrK6tG398BMVg6PT2dxMTEcsfK+pXT09OrvO6SSy6hQ4cOtGnThv/973/ccccdbNy4kTlz5lR5zeTJk5k0aZLvfnZ2NikpKUf/JkREmiBTw/FLGzZsICUlpdzPw169ehEXF8eGDRt83RgdO3YsN94nOTm5QmvOkV7H4XAwcOBA37EePXr4WqYAfvzxR3Jzc2nRokW5awsKCti8ebPvfnW1bNiwgaKioioHgv/4449s2rSpwtilwsLCcq9RE8cee2y5GqCk+699+/ZVvnZN3l+HDh1o1apVuXMuvfRSxo8fz7/+9S+cTidvvvkmF110ETZbSQdQbm4u9957Lx999BFpaWm43W4KCgpq1SL09NNPM378eHr06IFlWXTp0oUrr7ySV1991XfOzJkz+ctf/kLbtm2x2+0MGDCAiy++mJUrV5bsQxadxLXj/sxfLx8Dib2w7A5ef/11oqOjSU1NpXv37nz//ffs3LmTiy66iC1btuB0OmtcY234NQjdeeed/POf/6z2nA0bNtT5+Q8dQ9S3b1+Sk5M544wz2Lx5M126dKn0GqfT2WAftohIU9OtWzcsy/KNzzhah8/+siyrwpiVo5Wbm0tycjJLliyp8Nihgam6WsLDw4/4GgMHDqx0fNLh4eNIDq3DsiyAaj+Tmr6/yroyR44ciTGGjz76iBNOOIGvvvqKJ5980vf4rbfeyqJFi3jsscfo2rUr4eHh/PnPf65Vd1+rVq2YN28ehYWF7Nu3jzZt2nDnnXfSuXNn3zldunThyy+/JC8vj+zsbJKTkxkzZozvHCsqEW/+fmyeIjyZOzlgorjvvvtYunQp3333HccccwzdunWjW7duuFwufvnlF/r27VvjGmvDr0Holltu4Yorrqj2nM6dO5OUlFThNwq3283+/ftJSkqq8esNHjwYKOlXrSoIiYg0JwkJCQwfPpznn3+ev/3tbxW+XDMzM4mLi6Nnz57s2LGDHTt2+FqF1q9fT2ZmJr169aq3enr06IHb7WblypW+VqaNGzeSmZnpO2fAgAGkp6fjcDh8A65rq1u3boSHh7N48WKuvvrqCo8PGDCAt99+m8TExCOOLT0aoaGhFWb4Hc37CwsL4/zzz+fNN99k06ZNdO/enQEDBvge/+abb7jiiis477zzgJLQVZsB4Ie/Vtu2bXG5XLz//vtceOGFFc6JjIwkMjKSAwcOsHDhwoMTliwbtrgU2LcJW9EBbrp1MjfffDPt2rXj+++/x+U6uC9Z2ZijhuLXwdKtWrWiR48e1d5CQ0NJTU0lMzOzpEmt1Oeff47X6/WFm5ooW6ehrGlSRETg+eefx+PxMGjQIN5//31+/fVXNmzYwDPPPENqaioAw4YNo2/fvlx66aWsWrWKFStWMG7cOIYOHcrxxx9fb7V0796dESNG8Ne//pXvvvuOlStXcvXVV5drwRk2bBipqamMHj2aTz/9lK1bt7Js2TL+/ve/88MPP9TodcLCwrjjjju4/fbb+c9//sPmzZv59ttv+fe//w2UdDG1bNmSUaNG8dVXX7FlyxaWLFnC3/72N3burL89szp27MiWLVtYs2YNe/fupaio6Kjf36WXXspHH33Eq6++6hskXaZbt26+wdU//vgjl1xySa1b7L777jvmzJnDb7/9xldffcWIESPwer3cfvvtvnMWLlzIggUL2LJlC4sWLeK0006jR48eXHnllQefyBmNCYtn0dIV/PLrL76lGk444QR+/vlnPvnkE1566SXsdjvdu3evVY21ERCzxnr27MmIESMYP348K1as4JtvvmHixIlcdNFFtGlTsrPtrl276NGjBytWrABKZgs88MADrFy5kq1bt/Lhhx8ybtw4TjnllHL9tSIiDclut/u6QxqLZVnY7fYan9+5c2dWrVrFaaedxi233EKfPn0488wzWbx4MdOnT/c95wcffEB8fDynnHIKw4YNo3Pnzrz99tv1Xv9rr71GmzZtGDp0KOeffz7XXHNNuXGilmXx8ccfc8opp3DllVdyzDHHcNFFF7Ft2zbfrK+auPvuu7nlllu455576NmzJ2PGjPH1PkRERLB06VLat2/P+eefT8+ePbnqqqsoLCys1xaiP/3pT4wYMYLTTjuNVq1a8dZbbx31+zv99NNJSEhg48aNXHLJJeUee+KJJ4iPj2fIkCGMHDmS4cOHl2sxqonCwkKmTJlCr169OO+882jbti1ff/11uW67rKwsJkyYQI8ePRg3bhwnn3wyCxcurNBdWRjaghumPsFLL//bN46pXbt2PPvss1x55ZU8+OCDvP7660fsyjwalqnpSDk/279/PxMnTuS///0vNpuNP/3pTzzzzDNERUUBB1f0/OKLLzj11FPZsWMHY8eOZd26deTl5ZGSksJ5553HlClTavWXODs7m9jYWLKyshq0eVREAl9hYSFbtmzxretSpri4uEGb9g9nt9trtaq0SKCq6t8c1Pz7OyBmjUFJP/asWbOqfLxjx47lZj+kpKTw5ZdfNkZpIiLVUigRaboComtMREREpCEoCImIiEizpSAkIiIizZaCkIhIPQuQOSgiAa8+/q0pCImI1JOyqcH5+fl+rkSkeSj7t3b4tPzaCJhZYyIiTZ3dbicuLq7cWjSNvYaQSHNgjCE/P5+MjAzi4uJqtW7W4RSERETqUdm2P7XZaFRE6iYuLq5WW21VRkFIRKQeWZZFcnIyiYmJ5fZLEpH6FRISclQtQWUUhEREGoDdbq+XH9Ii0rA0WFpERESaLQUhERERabYUhERERKTZ0hihIyhbrCk7O9vPlYiIiEhNlX1vH2nRRQWhI8jJyQFKdrMXERGRwJKTk0NsbGyVj1tGa8FXy+v18vvvvxMdHV2vC6NlZ2eTkpLCjh07iImJqbfnlYr0WTcOfc6NQ59z49Dn3Dga8nM2xpCTk0ObNm2w2aoeCaQWoSOw2Wy0a9euwZ4/JiZG/8gaiT7rxqHPuXHoc24c+pwbR0N9ztW1BJXRYGkRERFpthSEREREpNlSEPITp9PJ1KlTcTqd/i4l6Omzbhz6nBuHPufGoc+5cTSFz1mDpUVERKTZUouQiIiINFsKQiIiItJsKQiJiIhIs6UgJCIiIs2WglADev755+nYsSNhYWEMHjyYFStWVHv+u+++S48ePQgLC6Nv3758/PHHjVRpYKvN5/zyyy/zhz/8gfj4eOLj4xk2bNgR/7/IQbX9O11m9uzZWJbF6NGjG7bAIFHbzzkzM5MJEyaQnJyM0+nkmGOO0c+PGqjt5/zUU0/RvXt3wsPDSUlJ4eabb6awsLCRqg1MS5cuZeTIkbRp0wbLspg3b94Rr1myZAkDBgzA6XTStWtXZsyY0bBFGmkQs2fPNqGhoebVV181P/30kxk/fryJi4szu3fvrvT8b775xtjtdvPII4+Y9evXmylTppiQkBCzdu3aRq48sNT2c77kkkvM888/b1avXm02bNhgrrjiChMbG2t27tzZyJUHntp+1mW2bNli2rZta/7whz+YUaNGNU6xAay2n3NRUZE5/vjjzTnnnGO+/vprs2XLFrNkyRKzZs2aRq48sNT2c37zzTeN0+k0b775ptmyZYtZuHChSU5ONjfffHMjVx5YPv74Y/P3v//dzJkzxwBm7ty51Z7/22+/mYiICDNp0iSzfv168+yzzxq73W4WLFjQYDUqCDWQQYMGmQkTJvjuezwe06ZNGzNt2rRKz7/wwgvNueeeW+7Y4MGDzV//+tcGrTPQ1fZzPpzb7TbR0dHm9ddfb6gSg0ZdPmu3222GDBliXnnlFXP55ZcrCNVAbT/n6dOnm86dO5vi4uLGKjEo1PZznjBhgjn99NPLHZs0aZI56aSTGrTOYFKTIHT77beb3r17lzs2ZswYM3z48AarS11jDaC4uJiVK1cybNgw3zGbzcawYcNYvnx5pdcsX7683PkAw4cPr/J8qdvnfLj8/HxcLhcJCQkNVWZQqOtnff/995OYmMhVV13VGGUGvLp8zh9++CGpqalMmDCB1q1b06dPHx566CE8Hk9jlR1w6vI5DxkyhJUrV/q6z3777Tc+/vhjzjnnnEapubnwx3ehNl1tAHv37sXj8dC6detyx1u3bs3PP/9c6TXp6emVnp+ent5gdQa6unzOh7vjjjto06ZNhX94Ul5dPuuvv/6af//736xZs6YRKgwOdfmcf/vtNz7//HMuvfRSPv74YzZt2sT111+Py+Vi6tSpjVF2wKnL53zJJZewd+9eTj75ZIwxuN1urr32Wu66667GKLnZqOq7MDs7m4KCAsLDw+v9NdUiJM3Www8/zOzZs5k7dy5hYWH+Lieo5OTkcNlll/Hyyy/TsmVLf5cT1LxeL4mJibz00ksMHDiQMWPG8Pe//50XXnjB36UFlSVLlvDQQw/xr3/9i1WrVjFnzhw++ugjHnjgAX+XJkdJLUINoGXLltjtdnbv3l3u+O7du0lKSqr0mqSkpFqdL3X7nMs89thjPPzww3z22Wcce+yxDVlmUKjtZ71582a2bt3KyJEjfce8Xi8ADoeDjRs30qVLl4YtOgDV5e90cnIyISEh2O1237GePXuSnp5OcXExoaGhDVpzIKrL53z33Xdz2WWXcfXVVwPQt29f8vLyuOaaa/j73/+OzaZ2hfpQ1XdhTExMg7QGgVqEGkRoaCgDBw5k8eLFvmNer5fFixeTmppa6TWpqanlzgdYtGhRledL3T5ngEceeYQHHniABQsWcPzxxzdGqQGvtp91jx49WLt2LWvWrPHd/u///o/TTjuNNWvWkJKS0pjlB4y6/J0+6aST2LRpky9oAvzyyy8kJycrBFWhLp9zfn5+hbBTFj6NtuysN375LmywYdjN3OzZs43T6TQzZsww69evN9dcc42Ji4sz6enpxhhjLrvsMnPnnXf6zv/mm2+Mw+Ewjz32mNmwYYOZOnWqps/XQG0/54cfftiEhoaa9957z6SlpfluOTk5/noLAaO2n/XhNGusZmr7OW/fvt1ER0ebiRMnmo0bN5r58+ebxMRE849//MNfbyEg1PZznjp1qomOjjZvvfWW+e2338ynn35qunTpYi688EJ/vYWAkJOTY1avXm1Wr15tAPPEE0+Y1atXm23bthljjLnzzjvNZZdd5ju/bPr8bbfdZjZs2GCef/55TZ8PZM8++6xp3769CQ0NNYMGDTLffvut77GhQ4eayy+/vNz577zzjjnmmGNMaGio6d27t/noo48aueLAVJvPuUOHDgaocJs6dWrjFx6Aavt3+lAKQjVX28952bJlZvDgwcbpdJrOnTubBx980Ljd7kauOvDU5nN2uVzm3nvvNV26dDFhYWEmJSXFXH/99ebAgQONX3gA+eKLLyr9mVv22V5++eVm6NChFa7p37+/CQ0NNZ07dzavvfZag9ZoGaM2PREREWmeNEZIREREmi0FIREREWm2FIRERESk2VIQEhERkWZLQUhERESaLQUhERERabYUhERERKTZUhASERGRZktBSERERJotBSERERFpthSEREREpNlSEBKRZmXPnj0kJSXx0EMP+Y4tW7aM0NBQFi9e7MfKRMQftOmqiDQ7H3/8MaNHj2bZsmV0796d/v37M2rUKJ544gl/lyYijUxBSESapQkTJvDZZ59x/PHHs3btWr7//nucTqe/yxKRRqYgJCLNUkFBAX369GHHjh2sXLmSvn37+rskEfEDjRESkWZp8+bN/P7773i9XrZu3ervckTET9QiJCLNTnFxMYMGDaJ///50796dp556irVr15KYmOjv0kSkkSkIiUizc9ttt/Hee+/x448/EhUVxdChQ4mNjWX+/Pn+Lk1EGpm6xkSkWVmyZAlPPfUUM2fOJCYmBpvNxsyZM/nqq6+YPn26v8sTkUamFiERERFpttQiJCIiIs2WgpCIiIg0WwpCIiIi0mwpCImIiEizpSAkIiIizZaCkIiIiDRbCkIiIiLSbCkIiYiISLOlICQiIiLNloKQiIiINFsKQiIiItJs/T86lqs8TYA4swAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_gp(xt, yt, x, y, s2)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7a3f976c-6260-41a3-97b7-7513abf2beb0", + "metadata": {}, + "source": [ + "We can check it is better than one cluster (the default)." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "531c5590-3504-48ab-a53e-1eb004f62330", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gpx = egx.Gpx.builder().fit(xt, yt)\n", + "y = gpx.predict(x)\n", + "s2 = gpx.predict_var(x)\n", + "plot_gp(xt, yt, x, y, s2)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7920a0e3-37f6-4ff0-bdf0-bb9cbf550962", + "metadata": {}, + "source": [ + "We can also let _Gpx_ find the best number of clusters" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "6c0f2a73-03d8-482a-8824-c46c8ef51aee", + "metadata": {}, + "outputs": [ + { + "ename": "PanicException", + "evalue": "index out of bounds: the len is 0 but the index is 0", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mPanicException\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[26], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m gpx \u001b[38;5;241m=\u001b[39m \u001b[43megx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mGpx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuilder\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_clusters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mxt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43myt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(gpx)\n\u001b[0;32m 3\u001b[0m y \u001b[38;5;241m=\u001b[39m gpx\u001b[38;5;241m.\u001b[39mpredict(x)\n", + "\u001b[1;31mPanicException\u001b[0m: index out of bounds: the len is 0 but the index is 0" + ] + } + ], + "source": [ + "gpx = egx.Gpx.builder(n_clusters=0).fit(xt, yt)\n", + "print(gpx)\n", + "y = gpx.predict(x)\n", + "s2 = gpx.predict_var(x)\n", + "plot_gp(xt, yt, x, y, s2)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "4e550286", + "metadata": {}, + "source": [ + "## Gpx API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c3db4c30", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on GpMix in module builtins object:\n", + "\n", + "class GpMix(object)\n", + " | GpMix(n_clusters=1, regr_spec=Ellipsis, corr_spec=Ellipsis, recombination=Ellipsis, theta_init=None, theta_bounds=None, kpls_dim=None, n_start=10, seed=None)\n", + " | \n", + " | Gaussian processes mixture builder\n", + " | \n", + " | n_clusters (int >= 0)\n", + " | Number of clusters used by the mixture of surrogate experts.\n", + " | When set to 0, the number of cluster is determined automatically and refreshed every\n", + " | 10-points addition (should say 'tentative addition' because addition may fail for some points\n", + " | but failures are counted anyway).\n", + " | \n", + " | regr_spec (RegressionSpec flags, an int in [1, 7]):\n", + " | Specification of regression models used in mixture.\n", + " | Can be RegressionSpec.CONSTANT (1), RegressionSpec.LINEAR (2), RegressionSpec.QUADRATIC (4) or\n", + " | any bit-wise union of these values (e.g. RegressionSpec.CONSTANT | RegressionSpec.LINEAR)\n", + " | \n", + " | corr_spec (CorrelationSpec flags, an int in [1, 15]):\n", + " | Specification of correlation models used in mixture.\n", + " | Can be CorrelationSpec.SQUARED_EXPONENTIAL (1), CorrelationSpec.ABSOLUTE_EXPONENTIAL (2),\n", + " | CorrelationSpec.MATERN32 (4), CorrelationSpec.MATERN52 (8) or\n", + " | any bit-wise union of these values (e.g. CorrelationSpec.MATERN32 | CorrelationSpec.MATERN52)\n", + " | \n", + " | recombination (Recombination.Smooth or Recombination.Hard)\n", + " | Specify how the various experts predictions are recombined\n", + " | * Smooth: prediction is a combination of experts prediction wrt their responsabilities,\n", + " | the heaviside factor which controls steepness of the change between experts regions is optimized\n", + " | to get best mixture quality.\n", + " | * Hard: prediction is taken from the expert with highest responsability\n", + " | resulting in a model with discontinuities.\n", + " | \n", + " | theta_init ([nx] where nx is the dimension of inputs x)\n", + " | Initial guess for GP theta hyperparameters.\n", + " | When None the default is 1e-2 for all components\n", + " | \n", + " | theta_bounds ([[lower_1, upper_1], ..., [lower_nx, upper_nx]] where nx is the dimension of inputs x)\n", + " | Space search when optimizing theta GP hyperparameters\n", + " | When None the default is [1e-6, 1e2] for all components\n", + " | \n", + " | kpls_dim (0 < int < nx where nx is the dimension of inputs x)\n", + " | Number of components to be used when PLS projection is used (a.k.a KPLS method).\n", + " | This is used to address high-dimensional problems typically when nx > 9.\n", + " | \n", + " | n_start (int >= 0)\n", + " | Number of internal GP hyperpameters optimization restart (multistart)\n", + " | \n", + " | seed (int >= 0)\n", + " | Random generator seed to allow computation reproducibility.\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | fit(self, /, xt, yt)\n", + " | Fit the parameters of the model using the training dataset to build a trained model\n", + " | \n", + " | Parameters\n", + " | xt (array[nsamples, nx]): input samples\n", + " | yt (array[nsamples, 1]): output samples\n", + " | \n", + " | Returns Gpx object\n", + " | the fitted Gaussian process mixture\n", + " | \n", + " | ----------------------------------------------------------------------\n", + " | Static methods defined here:\n", + " | \n", + " | __new__(*args, **kwargs) from builtins.type\n", + " | Create and return a new object. See help(type) for accurate signature.\n", + "\n" + ] + } + ], + "source": [ + "help(egx.Gpx.builder())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "284f975e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on class Gpx in module builtins:\n", + "\n", + "class Gpx(object)\n", + " | A trained Gaussian processes mixture\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | __repr__(self, /)\n", + " | Return repr(self).\n", + " | \n", + " | __str__(self, /)\n", + " | Return str(self).\n", + " | \n", + " | likelihoods(self, /)\n", + " | Get reduced likelihood values gotten when fitting the GP experts\n", + " | \n", + " | Maybe used to compare various parameterization\n", + " | \n", + " | Returns\n", + " | likelihood as an array[n_clusters]\n", + " | \n", + " | predict(self, /, x)\n", + " | Predict output values at nsamples points.\n", + " | \n", + " | Parameters\n", + " | x (array[nsamples, nx])\n", + " | input values\n", + " | \n", + " | Returns\n", + " | the output values at nsamples x points (array[nsamples, 1])\n", + " | \n", + " | predict_gradients(self, /, x)\n", + " | Predict surrogate output derivatives at nsamples points.\n", + " | \n", + " | Parameters\n", + " | x (array[nsamples, nx])\n", + " | input values\n", + " | \n", + " | Returns\n", + " | the output derivatives at nsamples x points (array[nsamples, nx]) wrt inputs\n", + " | The ith column is the partial derivative value wrt to the ith component of x at the given samples.\n", + " | \n", + " | predict_var(self, /, x)\n", + " | Predict variances at nsample points.\n", + " | \n", + " | Parameters\n", + " | x (array[nsamples, nx])\n", + " | input values\n", + " | \n", + " | Returns\n", + " | the variances of the output values at nsamples input points (array[nsamples, 1])\n", + " | \n", + " | predict_var_gradients(self, /, x)\n", + " | Predict variance derivatives at nsamples points.\n", + " | \n", + " | Parameters\n", + " | x (array[nsamples, nx])\n", + " | input values\n", + " | \n", + " | Returns\n", + " | the variance derivatives at nsamples x points (array[nsamples, nx]) wrt inputs\n", + " | The ith column is the partial derivative value wrt to the ith component of x at the given samples.\n", + " | \n", + " | sample(self, /, x, n_traj)\n", + " | Sample gaussian process trajectories.\n", + " | \n", + " | Parameters\n", + " | x (array[nsamples, nx])\n", + " | locations of the sampled trajectories\n", + " | n_traj number of trajectories to generate\n", + " | \n", + " | Returns\n", + " | the trajectories as an array[nsamples, n_traj]\n", + " | \n", + " | save(self, /, filename)\n", + " | Save Gaussian processes mixture in a json file.\n", + " | \n", + " | Parameters\n", + " | filename (string)\n", + " | json file generated in the current directory\n", + " | \n", + " | thetas(self, /)\n", + " | Get optimized thetas hyperparameters (ie once GP experts are fitted)\n", + " | \n", + " | Returns\n", + " | thetas as an array[n_clusters, nx or kpls_dim]\n", + " | \n", + " | variances(self, /)\n", + " | Get GP expert variance (ie posterior GP variance)\n", + " | \n", + " | Returns\n", + " | variances as an array[n_clusters]\n", + " | \n", + " | ----------------------------------------------------------------------\n", + " | Static methods defined here:\n", + " | \n", + " | __new__(*args, **kwargs) from builtins.type\n", + " | Create and return a new object. See help(type) for accurate signature.\n", + " | \n", + " | builder(n_clusters=1, regr_spec=Ellipsis, corr_spec=Ellipsis, recombination=Ellipsis, theta_init=None, theta_bounds=None, kpls_dim=None, n_start=10, seed=None)\n", + " | Get Gaussian processes mixture builder aka `GpMix`\n", + " | \n", + " | See `GpMix` constructor\n", + " | \n", + " | load(filename)\n", + " | Load Gaussian processes mixture from a json file.\n", + " | \n", + " | Parameters\n", + " | filename (string)\n", + " | json filepath generated by saving a trained Gaussian processes mixture\n", + "\n" + ] + } + ], + "source": [ + "help(egx.Gpx)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "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": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/ego/src/gpmix/mixint.rs b/ego/src/gpmix/mixint.rs index 7331263c..ec713028 100644 --- a/ego/src/gpmix/mixint.rs +++ b/ego/src/gpmix/mixint.rs @@ -9,8 +9,8 @@ use egobox_doe::{FullFactorial, Lhs, LhsKind, Random}; use egobox_gp::metrics::CrossValScore; use egobox_gp::ThetaTuning; use egobox_moe::{ - Clustered, Clustering, CorrelationSpec, FullGpSurrogate, GpMixture, GpMixtureParams, - GpSurrogate, GpSurrogateExt, MixtureGpSurrogate, RegressionSpec, + Clustered, Clustering, CorrelationSpec, FullGpSurrogate, GpFileFormat, GpMixture, + GpMixtureParams, GpSurrogate, GpSurrogateExt, MixtureGpSurrogate, RegressionSpec, }; use linfa::traits::{Fit, PredictInplace}; use linfa::{DatasetBase, Float, ParamGuard}; @@ -581,13 +581,15 @@ impl GpSurrogate for MixintGpMixture { /// Save Moe model in given file. #[cfg(feature = "persistent")] - fn save(&self, path: &str) -> egobox_moe::Result<()> { + fn save(&self, path: &str, format: GpFileFormat) -> egobox_moe::Result<()> { + use egobox_moe::GpFileFormat; + let mut file = fs::File::create(path).unwrap(); - let bytes = match serde_json::to_string(self) { - Ok(b) => b, - Err(err) => return Err(MoeError::SaveError(err)), + let bytes = match format { + GpFileFormat::Json => serde_json::to_vec(self).map_err(MoeError::SaveJsonError)?, + GpFileFormat::Binary => bincode::serialize(self).map_err(MoeError::SaveBinaryError)?, }; - file.write_all(bytes.as_bytes())?; + file.write_all(&bytes)?; Ok(()) } } diff --git a/gp/Cargo.toml b/gp/Cargo.toml index bff703f1..fe5a1ec1 100644 --- a/gp/Cargo.toml +++ b/gp/Cargo.toml @@ -13,7 +13,7 @@ categories = ["algorithms", "mathematics", "science"] default = [] -serializable = ["serde", "typetag", "linfa/serde"] +serializable = ["serde", "typetag", "linfa/serde", "rand_xoshiro/serde1"] persistent = ["serializable", "serde_json"] blas = ["ndarray-linalg", "linfa/ndarray-linalg", "linfa-pls/blas"] diff --git a/moe/Cargo.toml b/moe/Cargo.toml index 9984c160..d4e13730 100644 --- a/moe/Cargo.toml +++ b/moe/Cargo.toml @@ -18,7 +18,7 @@ categories = ["algorithms", "mathematics", "science"] [features] default = [] -persistent = ["serializable", "serde_json"] +persistent = ["serializable", "serde_json", "bincode"] serializable = [ "serde", "typetag", @@ -51,6 +51,8 @@ thiserror = "1" serde = { version = "1", features = ["derive"], optional = true } serde_json = { version = "1", optional = true } +bincode = { version = "1.3.3", optional = true } + typetag = { version = "0.2", optional = true } [dev-dependencies] diff --git a/moe/src/algorithm.rs b/moe/src/algorithm.rs index f710a174..eb1e1110 100644 --- a/moe/src/algorithm.rs +++ b/moe/src/algorithm.rs @@ -483,13 +483,15 @@ impl GpSurrogate for GpMixture { } /// Save Moe model in given file. #[cfg(feature = "persistent")] - fn save(&self, path: &str) -> Result<()> { + fn save(&self, path: &str, format: GpFileFormat) -> Result<()> { let mut file = fs::File::create(path).unwrap(); - let bytes = match serde_json::to_string(self) { - Ok(b) => b, - Err(err) => return Err(MoeError::SaveError(err)), + + let bytes = match format { + GpFileFormat::Json => serde_json::to_vec(self).map_err(MoeError::SaveJsonError)?, + GpFileFormat::Binary => bincode::serialize(self).map_err(MoeError::SaveBinaryError)?, }; - file.write_all(bytes.as_bytes())?; + file.write_all(&bytes)?; + Ok(()) } } @@ -878,9 +880,12 @@ impl GpMixture { #[cfg(feature = "persistent")] /// Load Moe from given json file. - pub fn load(path: &str) -> Result> { - let data = fs::read_to_string(path)?; - let moe: GpMixture = serde_json::from_str(&data).unwrap(); + pub fn load(path: &str, format: GpFileFormat) -> Result> { + let data = fs::read(path)?; + let moe = match format { + GpFileFormat::Json => serde_json::from_slice(&data).unwrap(), + GpFileFormat::Binary => bincode::deserialize(&data).unwrap(), + }; Ok(Box::new(moe)) } } @@ -1150,8 +1155,8 @@ mod tests { let xtest = array![[0.6]]; let y_expected = moe.predict(&xtest).unwrap(); let filename = format!("{test_dir}/saved_moe.json"); - moe.save(&filename).expect("MoE saving"); - let new_moe = GpMixture::load(&filename).expect("MoE loading"); + moe.save(&filename, GpFileFormat::Json).expect("MoE saving"); + let new_moe = GpMixture::load(&filename, GpFileFormat::Json).expect("MoE loading"); assert_abs_diff_eq!(y_expected, new_moe.predict(&xtest).unwrap(), epsilon = 1e-6); } @@ -1358,6 +1363,10 @@ mod tests { .fit(&Dataset::new(xt, yt)) .expect("GP fit error"); + // To see file size : 100D => json ~ 1.2Mo, bin ~ 0.6Mo + // gp.save("griewank.json", GpFileFormat::Json).unwrap(); + // gp.save("griewank.bin", GpFileFormat::Binary).unwrap(); + let rng = Xoshiro256Plus::seed_from_u64(0); let xtest = Lhs::new(&xlimits).with_rng(rng).sample(100); let ytest = gp.predict(&xtest).expect("prediction error"); diff --git a/moe/src/errors.rs b/moe/src/errors.rs index c6dbc6f0..1aad2bb6 100644 --- a/moe/src/errors.rs +++ b/moe/src/errors.rs @@ -30,7 +30,11 @@ pub enum MoeError { /// When error during saving #[cfg(feature = "persistent")] #[error("Save error: {0}")] - SaveError(#[from] serde_json::Error), + SaveJsonError(#[from] serde_json::Error), + /// When error during saving + #[cfg(feature = "persistent")] + #[error("Save error: {0}")] + SaveBinaryError(#[from] bincode::Error), /// When error during loading #[error("Load IO error")] LoadIoError(#[from] std::io::Error), diff --git a/moe/src/surrogates.rs b/moe/src/surrogates.rs index 232376c6..64301f36 100644 --- a/moe/src/surrogates.rs +++ b/moe/src/surrogates.rs @@ -1,4 +1,5 @@ use crate::errors::Result; +use crate::types::GpFileFormat; use egobox_gp::{ correlation_models::*, mean_models::*, GaussianProcess, GpParams, SgpParams, SparseGaussianProcess, SparseMethod, ThetaTuning, @@ -54,7 +55,7 @@ pub trait GpSurrogate: std::fmt::Display + Sync + Send { fn predict_var(&self, x: &ArrayView2) -> Result>; /// Save model in given file. #[cfg(feature = "persistent")] - fn save(&self, path: &str) -> Result<()>; + fn save(&self, path: &str, format: GpFileFormat) -> Result<()>; } /// A trait for a GP surrogate with derivatives predictions and sampling @@ -157,13 +158,17 @@ macro_rules! declare_surrogate { } #[cfg(feature = "persistent")] - fn save(&self, path: &str) -> Result<()> { + fn save(&self, path: &str, format: GpFileFormat) -> Result<()> { let mut file = fs::File::create(path).unwrap(); - let bytes = match serde_json::to_string(self as &dyn GpSurrogate) { - Ok(b) => b, - Err(err) => return Err(MoeError::SaveError(err)) + let bytes = match format { + GpFileFormat::Json => serde_json::to_vec(self as &dyn GpSurrogate) + .map_err(MoeError::SaveJsonError)?, + GpFileFormat::Binary => { + bincode::serialize(self as &dyn GpSurrogate).map_err(MoeError::SaveBinaryError)? + } }; - file.write_all(bytes.as_bytes())?; + file.write_all(&bytes)?; + Ok(()) } @@ -311,13 +316,16 @@ macro_rules! declare_sgp_surrogate { } #[cfg(feature = "persistent")] - fn save(&self, path: &str) -> Result<()> { + fn save(&self, path: &str, format: GpFileFormat) -> Result<()> { let mut file = fs::File::create(path).unwrap(); - let bytes = match serde_json::to_string(self as &dyn SgpSurrogate) { - Ok(b) => b, - Err(err) => return Err(MoeError::SaveError(err)) + let bytes = match format { + GpFileFormat::Json => serde_json::to_vec(self as &dyn SgpSurrogate) + .map_err(MoeError::SaveJsonError)?, + GpFileFormat::Binary => { + bincode::serialize(self as &dyn SgpSurrogate).map_err(MoeError::SaveBinaryError)? + } }; - file.write_all(bytes.as_bytes())?; + file.write_all(&bytes)?; Ok(()) } } @@ -382,10 +390,17 @@ declare_sgp_surrogate!(Matern52); #[cfg(feature = "persistent")] /// Load GP surrogate from given json file. -pub fn load(path: &str) -> Result> { - let data = fs::read_to_string(path)?; - let gp: Box = serde_json::from_str(&data).unwrap(); - Ok(gp) +pub fn load(path: &str, format: GpFileFormat) -> Result> { + let data = fs::read(path)?; + match format { + GpFileFormat::Json => { + serde_json::from_slice::>(&data).map_err(|err| { + MoeError::LoadError(format!("Error while loading from {path}: ({err})")) + }) + } + GpFileFormat::Binary => bincode::deserialize(&data) + .map_err(|err| MoeError::LoadError(format!("Error while loading from {path} ({err})"))), + } } #[doc(hidden)] @@ -448,8 +463,9 @@ mod tests { let gp = make_surrogate_params!(Constant, SquaredExponential) .train(&xt.view(), &yt.view()) .expect("GP fit error"); - gp.save("target/tests/save_gp.json").expect("GP not saved"); - let gp = load("target/tests/save_gp.json").expect("GP not loaded"); + gp.save("target/tests/save_gp.json", GpFileFormat::Json) + .expect("GP not saved"); + let gp = load("target/tests/save_gp.json", GpFileFormat::Json).expect("GP not loaded"); let xv = Lhs::new(&xlimits).sample(20); let yv = xsinx(&xv); let ytest = gp.predict(&xv.view()).unwrap(); @@ -459,7 +475,7 @@ mod tests { #[test] fn test_load_fail() { - let gp = load("notfound.json"); + let gp = load("notfound.json", GpFileFormat::Json); assert!(gp.is_err()); } } diff --git a/moe/src/types.rs b/moe/src/types.rs index 215609ec..cf84ff75 100644 --- a/moe/src/types.rs +++ b/moe/src/types.rs @@ -125,3 +125,13 @@ impl Clustering { pub trait MixtureGpSurrogate: Clustered + GpSurrogate + GpSurrogateExt { fn experts(&self) -> &Vec>; } + +#[derive(Default, Debug)] +/// An enumeration of Gpx available file format +pub enum GpFileFormat { + /// Human readable format + #[default] + Json, + /// Binary format + Binary, +} diff --git a/python/egobox/tests/test_gpmix.py b/python/egobox/tests/test_gpmix.py index eec9bed8..3ae3ea7a 100644 --- a/python/egobox/tests/test_gpmix.py +++ b/python/egobox/tests/test_gpmix.py @@ -55,26 +55,29 @@ def test_gpx_kriging(self): def test_gpx_save_load(self): filename = "gpdump.json" - + filename_bin = "gpdump.bin" gpx = self.gpx - if os.path.exists(filename): - os.remove(filename) - gpx.save(filename) - gpx2 = egx.Gpx.load(filename) - os.remove(filename) + for file in [filename, filename_bin]: + if os.path.exists(file): + os.remove(file) + gpx.save(file) - # should interpolate - self.assertAlmostEqual(1.0, gpx2.predict(np.array([[1.0]])).item()) - self.assertAlmostEqual(0.0, gpx2.predict_var(np.array([[1.0]])).item()) + gpx2 = egx.Gpx.load(file) - # check a point not too far from a training point - self.assertAlmostEqual( - 1.1163, gpx2.predict(np.array([[1.1]])).item(), delta=1e-3 - ) - self.assertAlmostEqual( - 0.0, gpx2.predict_var(np.array([[1.1]])).item(), delta=1e-3 - ) + os.remove(file) + + # should interpolate + self.assertAlmostEqual(1.0, gpx2.predict(np.array([[1.0]])).item()) + self.assertAlmostEqual(0.0, gpx2.predict_var(np.array([[1.0]])).item()) + + # check a point not too far from a training point + self.assertAlmostEqual( + 1.1163, gpx2.predict(np.array([[1.1]])).item(), delta=1e-3 + ) + self.assertAlmostEqual( + 0.0, gpx2.predict_var(np.array([[1.1]])).item(), delta=1e-3 + ) def test_training_params(self): self.assertEqual(self.gpx.dims(), (1, 1)) diff --git a/src/gp_mix.rs b/src/gp_mix.rs index 03806afd..c84e403e 100644 --- a/src/gp_mix.rs +++ b/src/gp_mix.rs @@ -9,6 +9,8 @@ //! //! See the [tutorial notebook](https://github.com/relf/egobox/doc/Gpx_Tutorial.ipynb) for usage. //! +use std::path::Path; + use crate::types::*; use egobox_gp::metrics::CrossValScore; use egobox_moe::{Clustered, MixtureGpSurrogate, ThetaTuning}; @@ -236,17 +238,25 @@ impl Gpx { self.0.to_string() } - /// Save Gaussian processes mixture in a json file. + /// Save Gaussian processes mixture in a file. + /// If the filename has .json JSON human readable format is used + /// otherwise an optimized binary format is used. /// /// Parameters - /// filename (string) - /// json file generated in the current directory + /// filename with .json or .bin extension (string) + /// file generated in the current directory + /// + /// Returns True if save succeeds otherwise False /// - fn save(&self, filename: String) { - self.0.save(&filename).ok(); + fn save(&self, filename: String) -> bool { + let format = match Path::new(&filename).extension().unwrap().to_str().unwrap() { + "json" => egobox_moe::GpFileFormat::Json, + _ => egobox_moe::GpFileFormat::Binary, + }; + self.0.save(&filename, format).is_ok() } - /// Load Gaussian processes mixture from a json file. + /// Load Gaussian processes mixture from file. /// /// Parameters /// filename (string) @@ -254,7 +264,11 @@ impl Gpx { /// #[staticmethod] fn load(filename: String) -> Gpx { - Gpx(GpMixture::load(&filename).unwrap()) + let format = match Path::new(&filename).extension().unwrap().to_str().unwrap() { + "json" => egobox_moe::GpFileFormat::Json, + _ => egobox_moe::GpFileFormat::Binary, + }; + Gpx(GpMixture::load(&filename, format).unwrap()) } /// Predict output values at nsamples points. diff --git a/src/sparse_gp_mix.rs b/src/sparse_gp_mix.rs index 068da717..5fca3e9a 100644 --- a/src/sparse_gp_mix.rs +++ b/src/sparse_gp_mix.rs @@ -9,6 +9,8 @@ //! //! See the [tutorial notebook](https://github.com/relf/egobox/doc/Sgp_Tutorial.ipynb) for usage. //! +use std::path::Path; + use crate::types::*; use egobox_moe::{ Clustered, GpMixture, GpSurrogate, GpType, Inducings, MixtureGpSurrogate, ThetaTuning, @@ -237,14 +239,22 @@ impl SparseGpx { self.0.to_string() } - /// Save Gaussian processes mixture in a json file. + /// Save Gaussian processes mixture in a file. + /// If the filename has .json JSON human readable format is used + /// otherwise an optimized binary format is used. /// /// Parameters - /// filename (string) - /// json file generated in the current directory + /// filename with .json or .bin extension (string) + /// file generated in the current directory + /// + /// Returns True if save succeeds otherwise False /// - fn save(&self, filename: String) { - self.0.save(&filename).ok(); + fn save(&self, filename: String) -> bool { + let format = match Path::new(&filename).extension().unwrap().to_str().unwrap() { + "json" => egobox_moe::GpFileFormat::Json, + _ => egobox_moe::GpFileFormat::Binary, + }; + self.0.save(&filename, format).is_ok() } /// Load Gaussian processes mixture from a json file. @@ -255,7 +265,11 @@ impl SparseGpx { /// #[staticmethod] fn load(filename: String) -> SparseGpx { - SparseGpx(GpMixture::load(&filename).unwrap()) + let format = match Path::new(&filename).extension().unwrap().to_str().unwrap() { + "json" => egobox_moe::GpFileFormat::Json, + _ => egobox_moe::GpFileFormat::Binary, + }; + SparseGpx(GpMixture::load(&filename, format).unwrap()) } /// Predict output values at nsamples points.