diff --git a/source/model_utils.py b/source/model_utils.py index 3709983aabd9fa6d5d4e1f3b4b41658faad4447c..cfbfa0ccda1396f906dcb47fe74d8ea3d237f4ae 100644 --- a/source/model_utils.py +++ b/source/model_utils.py @@ -171,7 +171,7 @@ class Latent_space_control(Layer): # Adds Silhouette score controling overlap between clusters hard_labels = tf.math.argmax(z_cat, axis=1) silhouette = tf.numpy_function(silhouette_score, [z, hard_labels], tf.float32) - self.add_loss(- K.mean(silhouette), inputs=[z, hard_labels]) + self.add_loss(-K.mean(silhouette), inputs=[z, hard_labels]) self.add_metric(silhouette, aggregation="mean", name="silhouette") return z diff --git a/visualizations/train_viz_data_generator.py b/visualizations/train_viz_data_generator.py index df60d5ac3dcc52aa6558837549ca89c459a3f105..a57ac82dcf2a9ebe95b80dfb43587b6b953019d1 100644 --- a/visualizations/train_viz_data_generator.py +++ b/visualizations/train_viz_data_generator.py @@ -219,22 +219,58 @@ coords_dist_angles1 = merge_tables(coords1, distances1, angles1) input_dict = { "coords": coords1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), "dists": distances1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), "angles": angles1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), "coords+dist": coords_distances1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), "coords+angle": coords_angles1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), "coords+dist+angle": coords_dist_angles1.preprocess( - window_size=11, window_step=1, scale=True, random_state=42, filter="gauss" + window_size=11, + window_step=1, + scale=True, + random_state=42, + filter="gaussian", + sigma=55, + shuffle=True, ), }