Wrote results for pipeline_full, pipeline_short, and feat_cross_species.

python/fig_features_cross_species.py

@@ -2,7 +2,7 @@ import plotstyle_plt
 import numpy as np
 import matplotlib.pyplot as plt
 from itertools import product
-from scipy.stats import ttest_ind
+from scipy.stats import ttest_ind, mannwhitneyu
 from thunderhopper.modeltools import load_data
 from thunderhopper.filetools import search_files
 from thunderhopper.filtertools import find_kern_specs
@@ -15,7 +15,7 @@ from IPython import embed
 # GENERAL SETTINGS:
 cross_species = [
     'Chorthippus_biguttulus',
-    # 'Chorthippus_mollis',
+    'Chorthippus_mollis',
     'Chrysochraon_dispar',
     # 'Euchorthippus_declivus',
     'Gomphocerippus_rufus',
@@ -410,11 +410,17 @@ for x, y in product(range(n_song), range(n_song)):
     # print('\nAxis position: ', (y, x))
     # print(f'Song {song_labels[x]} (x) vs. Song {song_labels[y]} (y)')
 
+print('\nMedian correlation coefficients:')
+print(f'Intraspecies: {np.median(song_regs)}')
+print(f'Interspecies: {np.median(spec_regs)}')
+
 if test_regression:
+    song_regs, spec_regs = np.array(song_regs), np.array(spec_regs)
+
     # Add test result subplot:
     test_ax = fig.add_subplot(test_ax_bounds)
     test_ax.set_xlim(-0.6, 1.6)
-    test_ax.set_ylim(0, 1)
+    test_ax.set_ylim(-0.15, 1)
     test_ax.yaxis.set_major_locator(plt.MultipleLocator(yloc_test))
     ylabel(test_ax, ylab_test, **ylab_test_kwargs)
 
@@ -425,15 +431,22 @@ if test_regression:
     test_ax.plot(np.zeros(len(spec_regs)), spec_regs, **boxplot_dot_kwargs)
     test_ax.plot(np.ones(len(song_regs)), song_regs, **boxplot_dot_kwargs)
 
+    # CAREFUL - PSEUDO-REPLICATION:
+
     # Perform t-test:
     test = ttest_ind(spec_regs, song_regs, equal_var=False)
-    t, p = test.pvalue, test.statistic
+    p, t = test.pvalue, test.statistic
     print(f'\nT-test result: t={t}, p={p}')
 
+    # Perform Wilcoxon rank-sum test:
+    test = mannwhitneyu(spec_regs, song_regs, alternative='two-sided')
+    p, u = test.pvalue, test.statistic
+    print(f'\nMWU rank test result: U={u}, p={p}')
+
 if save_path is not None:
     fig.savefig(save_path)
 plt.show()
-
+embed()