Added newly processed species to fig_features_cross_species.pdf.

Wrote more of the results.

python/save_inv_data_full.py

@@ -18,7 +18,7 @@ target_species = [
     # 'Gomphocerippus_rufus',
     # 'Omocestus_rufipes',
     # 'Pseudochorthippus_parallelus',
-][0]
+][1]
 example_file = {
     'Chorthippus_biguttulus': 'Chorthippus_biguttulus_GBC_94-17s73.1ms-19s977ms',
     'Chorthippus_mollis': 'Chorthippus_mollis_DJN_41_T28C-46s4.58ms-1m15s697ms',
@@ -28,7 +28,7 @@ example_file = {
     'Omocestus_rufipes': 'Omocestus_rufipes_DJN_32-40s724ms-48s779ms',
     'Pseudochorthippus_parallelus': 'Pseudochorthippus_parallelus_GBC_88-6s678ms-9s32.3ms'
 }[target_species]
-data_paths = search_files(target_species, dir='../data/processed/')
+data_paths = search_files(target_species, incl='GBC', dir='../data/processed/')
 noise_path = '../data/processed/white_noise_sd-1.npz'
 thresh_path = '../data/inv/full/thresholds.npz'
 stages = ['filt', 'env', 'log', 'inv', 'conv', 'feat']
@@ -55,10 +55,13 @@ thresh_abs = thresh_rel[:, None] * thresh_data['sds'][None, :]
 for data_path, name in zip(data_paths, crop_paths(data_paths)):
     save_detailed = example_file in name
     print(f'Processing {name}')
+    if 'BM04' in name:
+        continue
 
     # Get song recording (prior to anything):
     data, config = load_data(data_path, files='raw')
     song, rate = data['raw'], config['rate']
+    print(song.shape, song.size)
 
     # Reduce to kernel subset:
     if any(var is not None for var in [kernels, types, sigmas]):