v1.0

Restructured files and added new installation instructions.
Created setup files.

CHANGELOG.rst

@@ -0,0 +1,4 @@
+v1.0
+----
+- Generated setup files to install package.
+- Bumped version to 1.0 as it's completely operational.

README.rst

@@ -5,7 +5,7 @@ pc2graph
 General Information
 ~~~~~~~~~~~~~~~~~~~
 
-This is a Python script that converts a numpy.ndarray containing a point cloud
+This is a Python (2.7x) script that converts a numpy.ndarray containing a point cloud
 (x, y, z) into a NetworkX graph.
 
 The code also includes a function to extract shortest path information from a
@@ -19,3 +19,27 @@ and Scientific Development (10.13039/501100003593) – Brazil (Process number 23
 
 Any questions or suggestions, feel free to contact me using one of the
 following e-mails: [email protected] or [email protected]
+
+
+Installation
+~~~~~~~~~~~~
+
+To install this package use the command:
+
+    .. code-block:: python
+
+        python setup.py install
+
+or:
+
+    .. code-block:: python
+
+        pip install pc2graph
+
+
+
+
+
+
+
+

data/batch/files.txt

@@ -1 +1 @@
-../data/point_cloud_example.txt
+../../data/point_cloud_example.txt

pc2graph/__init__.py

@@ -0,0 +1,32 @@
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
+# All rights reserved.
+#
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+__author__ = "Matheus Boni Vicari"
+__copyright__ = "Copyright 2018-2019"
+__credits__ = ["Matheus Boni Vicari"]
+__license__ = "GPL3"
+__version__ = "1.0"
+__maintainer__ = "Matheus Boni Vicari"
+__email__ = "[email protected]"
+__status__ = "Development"
+
+
+__all__ = ['downsampling', 'shortpath']
+
+import downsampling
+import shortpath
+

pc2graph/downsampling.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2017, Matheus Boni Vicari, TLSeparation Project
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
 # All rights reserved.
 #
 #
@@ -16,10 +16,10 @@
 #    along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 __author__ = "Matheus Boni Vicari"
-__copyright__ = "Copyright 2017"
+__copyright__ = "Copyright 2018-2019"
 __credits__ = ["Matheus Boni Vicari"]
 __license__ = "GPL3"
-__version__ = "0.1"
+__version__ = "1.0"
 __maintainer__ = "Matheus Boni Vicari"
 __email__ = "[email protected]"
 __status__ = "Development"

pc2graph/example_batch.py → pc2graph/examples/example_batch.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2017, Matheus Boni Vicari, TLSeparation Project
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
 # All rights reserved.
 #
 #
@@ -16,10 +16,10 @@
 #    along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 __author__ = "Matheus Boni Vicari"
-__copyright__ = "Copyright 2017"
+__copyright__ = "Copyright 2018-2019"
 __credits__ = ["Matheus Boni Vicari"]
 __license__ = "GPL3"
-__version__ = "0.1"
+__version__ = "1.0"
 __maintainer__ = "Matheus Boni Vicari"
 __email__ = "[email protected]"
 __status__ = "Development"
@@ -32,9 +32,9 @@
 
 if __name__ == '__main__':
 
-    # Declaring list of files to process and output folder.
-    filelist = '../data/batch/files.txt'
-    out_folder = '../data/batch/'
+    # Declaring list of files to process and output directory.
+    filelist = '../../data/batch/files.txt'
+    out_dir = '../../data/batch/'
 
     # Declaring downsample size of 10 cm.
     downsample_size = 0.1
@@ -112,4 +112,4 @@
         # Stacking all variables and exporting.
         out_cloud = np.hstack((upscale_cloud, upscale_distance.reshape(-1, 1),
                                diff.reshape(-1, 1)))
-        np.savetxt('%s%s.txt' % (out_folder, fname), out_cloud, fmt='%1.3f')
+        np.savetxt('%s%s.txt' % (out_dir, fname), out_cloud, fmt='%1.3f')

pc2graph/examples/example_plot_gif.py

@@ -0,0 +1,99 @@
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
+# All rights reserved.
+#
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+__author__ = "Matheus Boni Vicari"
+__copyright__ = "Copyright 2018-2019"
+__credits__ = ["Matheus Boni Vicari"]
+__license__ = "GPL3"
+__version__ = "1.0"
+__maintainer__ = "Matheus Boni Vicari"
+__email__ = "[email protected]"
+__status__ = "Development"
+
+from downsampling import downsample_cloud
+from shortpath import array_to_graph
+import numpy as np
+import glob
+import os
+
+
+
+
+if __name__ == '__main__':
+
+    try:
+        import mayavi.mlab as mlab
+
+        # Setting up where to save the data.
+        out_dir = '../../data/test_gif/'
+        out_file = 'test'
+        layer_delay = 2
+
+        # Setting up parameters to generate the graph.
+        point_cloud = np.loadtxt('../../data/point_cloud_example.txt')
+        downsample_dist = 0.05
+        kpairs = 3
+        knn = 100
+        nbr_dist_threshold = downsample_dist * 1.5
+        nbr_dist_threshold_step = 0.03
+        downsample_cloud = downsample_cloud(point_cloud, downsample_dist)
+
+        # Obtaining base id (lowest point in the cloud).
+        base_id = np.argmin(downsample_cloud[:, 2])
+
+        # Generating graph with option to return the step_register as True.
+        G, step_register = array_to_graph(downsample_cloud, base_id, kpairs,
+                                          knn, nbr_dist_threshold,
+                                          nbr_dist_threshold_step,
+                                          return_step=True)
+
+
+        # Starts the iterative plotting. This will require the Mayavi package.
+        iteration = 0
+        mlab.figure(bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
+        mlab.points3d(downsample_cloud[:, 0], downsample_cloud[:, 1],
+                      downsample_cloud[:, 2], color=(0.3, 0.3, 0.3), mode='point')
+        for s in np.unique(step_register):
+            mask = step_register == s
+            mlab.points3d(downsample_cloud[mask, 0], downsample_cloud[mask, 1],
+                          downsample_cloud[mask, 2], color=(1, 0, 0), mode='point')
+            mlab.savefig(out_dir + '%s.png' % iteration)
+            iteration += 1
+        mlab.close()
+
+        # Generating the list of step images to join in a gif later.
+        file_list = glob.glob('%s*.png' % out_dir)
+        file_list = [os.path.basename(f) for f in file_list]
+        list.sort(file_list, key=lambda x: int(os.path.basename(x).split('.png')[0]))
+        with open('%simage_list.txt' % out_dir, 'w') as file:
+            for item in file_list:
+                file.write("%s\n" % item)
+
+        # Changing directory and using ImageMagik to join all images into a gif.
+        # Then, delets all unnecessary files.In the end, returns to initial
+        # directory.
+        cwd = os.getcwd()
+        os.chdir(out_dir)
+        os.system('convert -loop 0 -delay %s @image_list.txt %s.gif' % (layer_delay, out_file))
+        os.remove('image_list.txt')
+        for f in file_list:
+            os.remove(f)
+        os.chdir(cwd)
+
+    except:
+        print('Mayavi not installed, this example cannot run!')
+

pc2graph/example_single.py → pc2graph/examples/example_single.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2017, Matheus Boni Vicari, TLSeparation Project
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
 # All rights reserved.
 #
 #
@@ -16,10 +16,10 @@
 #    along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 __author__ = "Matheus Boni Vicari"
-__copyright__ = "Copyright 2017"
+__copyright__ = "Copyright 2018-2019"
 __credits__ = ["Matheus Boni Vicari"]
 __license__ = "GPL3"
-__version__ = "0.1"
+__version__ = "1.0"
 __maintainer__ = "Matheus Boni Vicari"
 __email__ = "[email protected]"
 __status__ = "Development"
@@ -31,7 +31,7 @@
 if __name__ == "__main__":
 
     # Loads point cloud into a numpy.ndarray (n_points x dimensions).
-    point_cloud = np.loadtxt('../data/point_cloud_example.txt')
+    point_cloud = np.loadtxt('../../data/point_cloud_example.txt')
 
     # Growth factor. Each point adds 3 new points to graph.
     kpairs = 3
@@ -64,4 +64,4 @@
     # Preparing output point cloud.
     distance = np.asarray(distance).reshape(-1, 1)
     out_cloud = np.hstack((nodes, distance))
-    np.savetxt('../data/output_point_cloud.txt', out_cloud, fmt='%1.3f')
+    np.savetxt('../../data/output_point_cloud.txt', out_cloud, fmt='%1.3f')

pc2graph/shortpath.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2017, Matheus Boni Vicari, TLSeparation Project
+# Copyright (c) 2018-2019, Matheus Boni Vicari, pc2graph
 # All rights reserved.
 #
 #
@@ -16,10 +16,10 @@
 #    along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 __author__ = "Matheus Boni Vicari"
-__copyright__ = "Copyright 2017"
+__copyright__ = "Copyright 2018-2019"
 __credits__ = ["Matheus Boni Vicari"]
 __license__ = "GPL3"
-__version__ = "0.1"
+__version__ = "1.0"
 __maintainer__ = "Matheus Boni Vicari"
 __email__ = "[email protected]"
 __status__ = "Development"