Add labels to all tqdm progress bars

avocado/augment.py

@@ -449,7 +449,7 @@ def augment_dataset(self, augment_name, dataset, num_augments,
         """
         augmented_objects = []
 
-        for reference_object in tqdm(dataset.objects):
+        for reference_object in tqdm(dataset.objects, desc='Object'):
             if include_reference:
                 augmented_objects.append(reference_object)
 

avocado/classifier.py

@@ -283,7 +283,7 @@ def predict(self, dataset):
 
         predictions = 0
 
-        for classifier in tqdm(self.classifiers):
+        for classifier in tqdm(self.classifiers, desc='Classifier'):
             fold_scores = classifier.predict_proba(
                 features, raw_score=True,
                 num_iteration=classifier.best_iteration_

avocado/dataset.py

@@ -407,7 +407,7 @@ def extract_raw_features(self, featurizer):
         """
         list_raw_features = []
         object_ids = []
-        for obj in tqdm(self.objects):
+        for obj in tqdm(self.objects, desc='Object'):
             obj_features = featurizer.extract_raw_features(obj)
             list_raw_features.append(obj_features.values())
             object_ids.append(obj.metadata['object_id'])

avocado_settings.json

@@ -12,46 +12,5 @@
 
     "classifier_directory": "./classifiers",
 
-    "predictions_directory": "./predictions",
-
-    "RAW_DATA_DIR": "./data",
-    "RAW_TRAINING_PATH": "./data/training_set.csv",
-    "RAW_TRAINING_METADATA_PATH": "./data/training_set_metadata.csv",
-    "RAW_TEST_PATH": "./data/test_set.csv",
-    "RAW_TEST_METADATA_PATH": "./data/test_set_metadata.csv",
-    "UNBLIND_TEST_METADATA_PATH": "./data/unblind_test_set_metadata.csv",
-
-    "SPLIT_TEST_DIR": "./data_split",
-    "SPLIT_TEST_PATH_FORMAT": "./data_split/plasticc_split_%04d.h5",
-
-    "FEATURES_DIR": "./features",
-    "FEATURES_PATH_FORMAT": "./features/features_v%d_%s.h5",
-    "GP_FITS_PATH_FORMAT": "./features/gp_fits_v%d_%s.h5",
-    "FEATURES_VERSION": 5,
-
-    "SALT_FITS_DIR": "./salt_fits",
-    "SALT_FITS_PATH_FORMAT": "./salt_fits/salt_fits_%s.h5",
-
-    "AUGMENT_DIR": "./augment",
-    "AUGMENT_PATH_FORMAT": "./augment/%s.h5",
-    "NUM_AUGMENTS": 2,
-    "AUGMENT_VERSION": 23,
-
-    "MODEL_DIR": "./model",
-    "MODEL_PATH_FORMAT": "./model/model_%d.pkl",
-
-    "FLAT_WEIGHT": false,
-    "REDSHIFT_WEIGHT": false,
-    "RATES_WEIGHT": false,
-    "NO_UNKNOWN_WEIGHT": false,
-
-    "SCORES_DIR": "./scores",
-    "SCORES_PATH_FORMAT": "./scores/scores_%d.npz",
-
-    "SUBMISSIONS_DIR": "./submissions/",
-    "SUBMISSIONS_PATH_FORMAT": "./submissions/submission_%d.csv",
-    "SUBMISSIONS_RATES_PATH_FORMAT": "./submissions/submission_rates_%d.csv",
-    "SUBMISSIONS_PROBE99_PATH_FORMAT": "./submissions/submission_probe99_%d.csv",
-
-    "RATES_PATH_FORMAT": "./scores/rates_aug%s.csv"
+    "predictions_directory": "./predictions"
 }

scripts/avocado_augment

@@ -79,7 +79,7 @@ if __name__ == "__main__":
     else:
         # Process all chunks
         print("Processing the dataset in %d chunks..." % args.num_chunks)
-        for chunk in tqdm(range(args.num_chunks)):
+        for chunk in tqdm(range(args.num_chunks), desc='Chunk'):
             process_chunk(augmentor, chunk, args, verbose=False)
 
     print("Done!")

scripts/avocado_featurize

@@ -69,7 +69,7 @@ if __name__ == "__main__":
     else:
         # Process all chunks
         print("Processing the dataset in %d chunks..." % args.num_chunks)
-        for chunk in tqdm(range(args.num_chunks)):
+        for chunk in tqdm(range(args.num_chunks), desc='Chunk'):
             process_chunk(featurizer, chunk, args, verbose=False)
 
     print("Done!")

scripts/avocado_predict

@@ -63,7 +63,7 @@ if __name__ == "__main__":
     else:
         # Process all chunks
         print("Processing the dataset in %d chunks..." % args.num_chunks)
-        for chunk in tqdm(range(args.num_chunks)):
+        for chunk in tqdm(range(args.num_chunks), desc='Chunk'):
             process_chunk(classifier, chunk, args, verbose=False)
 
     print("Done!")