Again, numerous changes.

Mostly figure polishing and fixing.
Crucial fix to "short" invariance analysis.

python/condense_inv_data_short.py

@@ -26,7 +26,11 @@ search_path = '../data/inv/short/'
 save_path = '../data/inv/short/condensed/'
 
 # ANALYSIS SETTINGS:
-compute_ratios = False
+normalization = [
+    'none',
+    'base',
+    'range'
+    ][1]
 
 # EXECUTION:
 for i, species in enumerate(target_species):
@@ -64,8 +68,16 @@ for i, species in enumerate(target_species):
             # Log song file data:
             for stage in stages:
                 mkey = f'measure_{stage}'
-                if compute_ratios:
+
+                if normalization == 'base':
+                    # Noise baseline normalization:
                     data[mkey] /= data[mkey][0]
+                elif normalization == 'range':
+                    # Min-max normalization:
+                    min_measure = data[mkey].min(axis=0, keepdims=True)
+                    max_measure = data[mkey].max(axis=0, keepdims=True)
+                    data[mkey] = (data[mkey] - min_measure) / (max_measure - min_measure)
+
                 file_data[stage][..., k] = data[mkey]
 
         # Get recording statistics:
@@ -75,10 +87,12 @@ for i, species in enumerate(target_species):
 
     # Save condensed recording data:
     save_name = save_path + species
-    if compute_ratios:
-        save_name += '_normed'
-    else:
-        save_name += '_raw'
+    if normalization == 'none':
+        save_name += '_unnormed'
+    elif normalization == 'base':
+        save_name += '_norm-base'
+    elif normalization == 'range':
+        save_name += '_norm-range'
     archive = dict(scales=data['scales'])
     archive.update(rec_mean)
     archive.update(rec_sd)