Updating the unit tests with the ciritcal change to the feature space…

… code
Gravity-Spy · Nov 14, 2018 · b08c0a5 · b08c0a5
1 parent 0443e48
commit b08c0a5
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Showing 3 changed files with 16 additions and 23 deletions.
diff --git a/bin/wscan b/bin/wscan
@@ -148,7 +148,7 @@ def main(channel_name, frametype, event_time, gid, plot_directory,
     elif hdf5:
         results.convert_unicode_to_bytestring()
         results.write(os.path.join(final_path, 'classification.hdf5'),
-                      path='/{0}'.format(idstring), format='hdf5', append=True))
+                      path='/{0}'.format(idstring), format='hdf5', append=True)
         if path_to_similarity_search is not None:
             features.convert_unicode_to_bytestring()
             features.write(os.path.join(final_path, 'features.hdf5'),

diff --git a/gravityspy/ml/labelling_test_glitches.py b/gravityspy/ml/labelling_test_glitches.py
@@ -3,6 +3,7 @@
 K.set_image_dim_ordering('th')
 from keras.models import load_model
 from scipy.misc import imresize
+from keras.applications.vgg16 import preprocess_input
 
 import numpy
 import os
@@ -182,30 +183,22 @@ def get_multiview_feature_space(image_data, semantic_model_name,
             a 200 dimensional feature space vector
     """
     img_rows, img_cols = image_size[0], image_size[1]
-    test_set_unlabelled_x_1 = image_data.filter(regex=("1.0.png")).iloc[0].iloc[0]
-    test_set_unlabelled_x_2 = image_data.filter(regex=("2.0.png")).iloc[0].iloc[0]
-    test_set_unlabelled_x_3 = image_data.filter(regex=("4.0.png")).iloc[0].iloc[0]
-    test_set_unlabelled_x_4 = image_data.filter(regex=("0.5.png")).iloc[0].iloc[0]
-    test_set_unlabelled_x_1 = numpy.concatenate((test_set_unlabelled_x_1[0].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_1[1].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_1[2].reshape(-1, 1, img_rows, img_cols)),
-                                             axis=1)
-    test_set_unlabelled_x_2 = numpy.concatenate((test_set_unlabelled_x_2[0].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_2[1].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_2[2].reshape(-1, 1, img_rows, img_cols)),
-                                             axis=1)
-    test_set_unlabelled_x_3 = numpy.concatenate((test_set_unlabelled_x_3[0].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_3[1].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_3[2].reshape(-1, 1, img_rows, img_cols)),
-                                             axis=1)
-    test_set_unlabelled_x_4 = numpy.concatenate((test_set_unlabelled_x_4[0].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_4[1].reshape(-1, 1, img_rows, img_cols),
-                                              test_set_unlabelled_x_4[2].reshape(-1, 1, img_rows, img_cols)),
-                                             axis=1)
+    half_second_images = sorted(image_data.filter(regex=("0.5.png")).keys())
+    one_second_images = sorted(image_data.filter(regex=("1.0.png")).keys())
+    two_second_images = sorted(image_data.filter(regex=("2.0.png")).keys())
+    four_second_images = sorted(image_data.filter(regex=("4.0.png")).keys())
+
+    test_set_unlabelled_x_1 = numpy.vstack(image_data[one_second_images].iloc[0]).reshape(-1, 3, img_rows, img_cols)
+    test_set_unlabelled_x_2 = numpy.vstack(image_data[two_second_images].iloc[0]).reshape(-1, 3, img_rows, img_cols)
+    test_set_unlabelled_x_3 = numpy.vstack(image_data[four_second_images].iloc[0]).reshape(-1, 3, img_rows, img_cols)
+    test_set_unlabelled_x_4 = numpy.vstack(image_data[half_second_images].iloc[0]).reshape(-1, 3, img_rows, img_cols)
+
     semantic_idx_model = load_model(semantic_model_name)
     concat_test_unlabelled = concatenate_views(test_set_unlabelled_x_1,
                             test_set_unlabelled_x_2, test_set_unlabelled_x_3, test_set_unlabelled_x_4, [img_rows, img_cols], True)
 
+    concat_test_unlabelled = preprocess_input(concat_test_unlabelled)
+
     half_second_images = sorted(image_data.filter(regex=("0.5.png")).keys())
 
     ids = []

diff --git a/gravityspy/ml/read_image.py b/gravityspy/ml/read_image.py
@@ -58,7 +58,7 @@ def read_grayscale(filename, resolution=0.3, x=[66, 532], y=[105, 671],
 
     image_data = rgb2gray(image_data)
     image_data = rescale(image_data, resolution, mode='constant',
-                         preserve_range='True')
+                         preserve_range='True',multichannel=False)
 
     dim = np.int(reduce(lambda x, y: x * y, image_data.shape))
     image_data = np.reshape(image_data, (dim))
@@ -90,7 +90,7 @@ def read_rgb(filename, resolution=0.3, x=[66, 532], y=[105, 671],
 
     image_data = read_and_crop_image(filename, x=x, y=y)
     image_data = rescale(image_data, resolution, mode='constant',
-                         preserve_range='True')
+                         preserve_range='True', multichannel=True)
     dim = np.int(reduce(lambda x, y: x * y, image_data[:,:,0].shape))
     image_data_r = np.reshape(image_data[:,:,0], (dim))
     image_data_g = np.reshape(image_data[:,:,1], (dim))