Added some cmap functions.

Selected species-specific  colors.
Quite some progress on fig_invariance_thresh_lp_species.pdf.

python/fig_invariance_log-hp.py

@@ -30,6 +30,7 @@ def plot_snippets(axes, time, snippets, ymin=None, ymax=None, **kwargs):
 # GENERAL SETTINGS:
 target = 'Omocestus_rufipes'
 data_paths = search_files(target, excl='noise', dir='../data/inv/log_hp/')
+species_paths = search_files('*', incl='noise', dir='../data/inv/log_hp/')
 stages = ['env', 'log', 'inv']
 load_kwargs = dict(
     files=stages,
@@ -39,10 +40,6 @@ save_path = '../figures/fig_invariance_log_hp.pdf'
 compute_ratios = True
 show_diag = True
 show_noise = True
-if compute_ratios:
-    ref_data = load_data('../data/processed/white_noise_sd-1.npz', files=stages)[0]
-    ref_measures = {k: v.std() for k, v in ref_data.items() if not k.endswith('rate')}
-
 
 # GRAPH SETTINGS:
 fig_kwargs = dict(
@@ -221,6 +218,20 @@ noise_kwargs = dict(
     zorder=1.5,
 )
 
+# PREPARATION:
+if compute_ratios:
+    ref_data = load_data('../data/processed/white_noise_sd-1.npz', files=stages)[0]
+    ref_measures = {k: v.std() for k, v in ref_data.items() if not k.endswith('rate')}
+
+species_measures = []
+for species_path in species_paths:
+    species_data, _ = load_data(species_path, **load_kwargs)
+    species_measure = species_data['measure_inv']
+    if compute_ratios:
+        species_measure /= ref_measures['inv']
+    species_measures.append(species_measure)
+species_measures = np.array(species_measures).T
+
 # EXECUTION:
 for data_path in data_paths:
     print(f'Processing {data_path}')
@@ -340,6 +351,9 @@ for data_path in data_paths:
     big_axes[1].plot(noise_scales, noise_data['measure_log'], c=colors['log'], lw=lw_big)
     big_axes[1].plot(noise_scales, noise_data['measure_inv'], c=colors['inv'], lw=lw_big)
 
+    # Plot species measures:
+    big_axes[1].plot(noise_scales, species_measures, 'k', lw=lw_big, zorder=2.1)
+
     if show_diag:
         # Indicate diagonal:
         big_axes[0].plot(pure_scales, pure_scales, **diag_kwargs)