Seriously, no idea. Wild amount of changes. Good luck.

python/collect_inv_data_thresh-lp.py

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+import numpy as np
+from thunderhopper.filetools import search_files
+from thunderhopper.modeltools import load_data, save_data
+from IPython import embed
+
+# GENERAL SETTINGS:
+target_species = [
+    'Chorthippus_biguttulus',
+    'Chorthippus_mollis',
+    'Chrysochraon_dispar',
+    'Euchorthippus_declivus',
+    'Gomphocerippus_rufus',
+    'Omocestus_rufipes',
+    'Pseudochorthippus_parallelus',
+]
+search_path = '../data/inv/thresh_lp/'
+save_path = '../data/inv/thresh_lp/collected/'
+
+# ANALYSIS SETTINGS:
+with_noise = False
+
+# EXECUTION:
+for i, species in enumerate(target_species):
+    print(f'Processing {species}')
+
+    # Fetch all species-specific song files:
+    incl = 'noise' if with_noise else 'pure'
+    all_paths = search_files(species, incl=incl, ext='npz', dir=search_path)
+    
+    # Run through files:
+    for j, path in enumerate(all_paths):
+
+        # Load invariance data:
+        data, config = load_data(path, ['scales', 'measure_feat', 'thresh_rel'])
+        measure = data['measure_feat']
+
+        if j == 0:
+            # Prepare species-specific storage:
+            spec_data = np.zeros((measure.shape + (len(all_paths),)), dtype=float)
+
+        # Log file data:
+        spec_data[..., j] = measure
+
+    # Save collected file data:
+    save_name = save_path + species + f'_{incl}'
+    archive = dict(
+        scales=data['scales'],
+        measure_feat=spec_data,
+        thresh_rel=data['thresh_rel'])
+    save_data(save_name, archive, config)
+
+print('Done.')