Wrote field data methods. Added some very general at the beginning of the methods section.

python/save_inv_data_short.py

@@ -27,7 +27,7 @@ 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=['DJN', '611ms'], dir='../data/processed/')
 noise_path = '../data/processed/white_noise_sd-1.npz'
 thresh_path = '../data/inv/short/thresholds.npz'
 pre_stages = ['filt', 'env']
@@ -42,8 +42,10 @@ thresh_rel = np.array([0, 0.5, 1, 1.5, 2, 2.5, 3])
 
 # SUBSET SETTINGS:
 kernels = None
-types = None
-sigmas = None
+types = np.array([1, -1, 2, -2, 3, -3, 4, -4])
+# types = [1, -1, 2, -2, 3, -3, 4, -4, 5, -5, 6, -6, 7, -7, 8, -8, 9, -9, 10, -10]
+sigmas = np.array([0.001, 0.002, 0.004, 0.008, 0.016])
+# sigmas = [0.001, 0.002, 0.004, 0.008, 0.016, 0.032]
 
 # PREPARATION:
 pure_noise = np.load(noise_path)['raw']
@@ -54,8 +56,6 @@ 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 "DJN" in name:
-        continue
 
     # Get song recording (prior to anything):
     data, config = load_data(data_path, files='raw')