Again, numerous changes.

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

python/fig_saturation_log-hp_appendix.py

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+import plotstyle_plt
+import numpy as np
+import matplotlib.pyplot as plt
+from thunderhopper.filetools import search_files
+from plot_functions import xlabel, super_ylabel
+from color_functions import load_colors
+from misc_functions import shorten_species
+from IPython import embed
+
+# GENERAL SETTINGS:
+target_species = [
+    'Chorthippus_biguttulus',
+    'Chorthippus_mollis',
+    'Chrysochraon_dispar',
+    # 'Euchorthippus_declivus',
+    'Gomphocerippus_rufus',
+    'Omocestus_rufipes',
+    'Pseudochorthippus_parallelus',
+]
+data_path = '../data/inv/log_hp/saturation/'
+save_path = '../figures/fig_saturation_log-hp_appendix.pdf'
+
+# GRAPH SETTINGS:
+fig_kwargs = dict(
+    figsize=(32/2.54, 16/2.54),
+    nrows=len(target_species),
+    ncols=1,
+    sharex=True,
+    sharey=False,
+    gridspec_kw=dict(
+        wspace=0,
+        hspace=0.3,
+        left=0.09,
+        right=0.99,
+        bottom=0.1,
+        top=0.95,
+    )
+)
+
+# PLOT SETTINGS:
+colors = load_colors('../data/species_colors.npz')
+bar_kwargs = dict(
+    ec='w',
+)
+mean_kwargs = dict(
+    c='k',
+    lw=3,
+    ls='--'
+)
+xlab = 'scale $\\alpha$'
+ylab = '$\\text{PDF}_{\\alpha}$'
+xlab_kwargs = dict(
+    y=0,
+    fontsize=16,
+    ha='center',
+    va='bottom',
+)
+ylab_kwargs = dict(
+    x=0.005,
+    fontsize=16,
+    ha='left',
+    va='center',
+)
+leg_x = fig_kwargs['gridspec_kw']['left']
+leg_y = fig_kwargs['gridspec_kw']['top']
+leg_box = [
+    leg_x,
+    leg_y,
+    fig_kwargs['gridspec_kw']['right'] - leg_x,
+    1 - leg_y
+]
+leg_kwargs = dict(
+    ncols=len(target_species),
+    loc='upper center',
+    bbox_to_anchor=leg_box,
+    frameon=False,
+    prop=dict(
+        size=15,
+        style='italic',
+    ),
+    borderpad=0,
+    borderaxespad=0,
+    handlelength=1,
+    columnspacing=1,
+)
+text_kwargs = dict(
+    x=1,
+    y=1,
+    fontsize=14,
+    ha='right',
+    va='top',
+)
+
+# Prepare graph:
+fig, axes = plt.subplots(**fig_kwargs)
+xlabel(axes[-1], xlab, **xlab_kwargs, transform=fig.transFigure)
+super_ylabel(ylab, fig, axes[0], axes[-1], **ylab_kwargs)
+
+# Run through species:
+handles = []
+for species, ax in zip(target_species, axes):
+    color = colors[species]
+    
+    # Load species data:
+    path = search_files(species, dir=data_path)[0]
+    data = dict(np.load(path))
+    hist = data['hist']
+    bins = data['bins']
+    n_songs = data['crit_scales'].size
+
+    # Plot distribution of saturation points:
+    handles.append(ax.bar(bins, hist, width=bins[1] - bins[0], fc=color, **bar_kwargs))
+    ax.set_ylim(0, hist.max() * 1.05)
+
+    # Indicate mean of distribution:
+    ax.axvline(data['crit_scales'].mean(), **mean_kwargs)
+
+    # Indicate number of songs:
+    ax.text(**text_kwargs, s=f'n = {n_songs}', transform=ax.transAxes)
+
+# Posthocs:
+labels = [shorten_species(species) for species in target_species]
+fig.legend(handles, labels, **leg_kwargs)
+ax.set_xlim(0, bins[-1])
+
+# Save graph:
+fig.savefig(save_path)
+plt.show()  
+
+