wilcoxon test

code/plot_chirp_bodylegth.py

@@ -1,4 +1,5 @@
 import numpy as np
+from extract_chirps import get_valid_datasets
 
 import os
 
@@ -116,6 +117,8 @@ def main(datapath: str):
 
     foldernames = [
         datapath + x + '/' for x in os.listdir(datapath) if os.path.isdir(datapath+x)]
+
+    foldernames, _ = get_valid_datasets(datapath)
     path_order_meta = (
         '/').join(foldernames[0].split('/')[:-2]) + '/order_meta.csv'
     order_meta_df = read_csv(path_order_meta)
@@ -223,7 +226,8 @@ def main(datapath: str):
         size_chirps_diffs.append(chirp_winner - chirp_loser)
         freq_diffs.append(freq_winner - freq_loser)
 
-    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(22*ps.cm, 12*ps.cm), width_ratios=[1.5, 1,1])
+    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(
+        22*ps.cm, 12*ps.cm), width_ratios=[1.5, 1, 1])
     plt.subplots_adjust(left=0.098, right=0.945, top=0.94, wspace=0.343)
     scatterwinner = 1.15
     scatterloser = 1.85

code/plot_chirp_size.py

@@ -1,10 +1,11 @@
 import numpy as np
+from extract_chirps import get_valid_datasets
 
 import os
 
 import numpy as np
 import matplotlib.pyplot as plt
-from scipy.stats import pearsonr, spearmanr
+from scipy.stats import pearsonr, spearmanr, wilcoxon
 from thunderfish.powerspectrum import decibel
 
 from IPython import embed
@@ -182,6 +183,7 @@ def main(datapath: str):
 
     foldernames = [
         datapath + x + '/' for x in os.listdir(datapath) if os.path.isdir(datapath+x)]
+    foldernames, _ = get_valid_datasets(datapath)
     path_order_meta = (
         '/').join(foldernames[0].split('/')[:-2]) + '/order_meta.csv'
     order_meta_df = read_csv(path_order_meta)
@@ -242,24 +244,25 @@ def main(datapath: str):
         size_chirps_winner.append(chirp_winner)
         size_chirps_loser.append(chirp_loser)
 
-
     size_winner_pearsonr = pearsonr(size_diffs_winner, size_chirps_winner)
     size_loser_pearsonr = pearsonr(size_diffs_loser, size_chirps_loser)
 
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(
-        22*ps.cm, 12*ps.cm), sharey=True)
+        13*ps.cm, 10*ps.cm), sharey=True)
     plt.subplots_adjust(left=0.098, right=0.945, top=0.94, wspace=0.343)
     scatterwinner = 1.15
     scatterloser = 1.85
     chirps_winner = np.asarray(chirps_winner)[~np.isnan(chirps_winner)]
     chirps_loser = np.asarray(chirps_loser)[~np.isnan(chirps_loser)]
 
+    stat = wilcoxon(chirps_winner, chirps_loser)
+    print(stat)
 
     bplot1 = ax1.boxplot(chirps_winner, positions=[
-        1], showfliers=False, patch_artist=True)
+        0.9], showfliers=False, patch_artist=True)
 
     bplot2 = ax1.boxplot(chirps_loser,  positions=[
-        2], showfliers=False, patch_artist=True)
+        2.1], showfliers=False, patch_artist=True)
     ax1.scatter(np.ones(len(chirps_winner)) *
                 scatterwinner, chirps_winner, color=ps.red)
     ax1.scatter(np.ones(len(chirps_loser)) *
@@ -270,19 +273,27 @@ def main(datapath: str):
 
     for w, l in zip(chirps_winner, chirps_loser):
         ax1.plot([scatterwinner, scatterloser], [w, l],
-                 color='r', alpha=0.5, linewidth=0.5)
+                 color=ps.white, alpha=1, linewidth=0.5)
-    ax1.set_ylabel('Chirps [n]', color=ps.white)
+    ax1.set_ylabel('chirps [n]', color=ps.white)
+    ax1.set_xlabel('outcome', color=ps.white)
 
     colors1 = ps.red
     ps.set_boxplot_color(bplot1, colors1)
     colors1 = ps.orange
     ps.set_boxplot_color(bplot2, colors1)
 
-    ax2.scatter(size_diffs_winner, size_chirps_winner, color=ps.red)
+    ax2.scatter(size_diffs_winner, size_chirps_winner,
-    ax2.scatter(size_diffs_loser, size_chirps_loser, color=ps.orange)
+                color=ps.red, label='winner')
+    ax2.scatter(size_diffs_loser, size_chirps_loser,
+                color=ps.orange, label='loser')
+
+    ax2.set_xlabel('size difference [cm]')
+    # ax2.set_xticks(np.arange(-10, 10.1, 2))
+
+    handles, labels = ax2.get_legend_handles_labels()
+    fig.legend(handles, labels, loc='upper center', ncol=2)
+    plt.subplots_adjust(left=0.162, right=0.97, top=0.85, bottom=0.176)
 
-    ax2.set_xlabel('Size difference [cm]')
-    ax2.set_xticks(np.arange(-10, 10.1, 2))
     # pearson r
     plt.savefig('../poster/figs/chirps_winner_loser.pdf')
     plt.show()

code/plot_event_timeline.py

@@ -12,6 +12,7 @@ from modules.logger import makeLogger
 from modules.plotstyle import PlotStyle
 from modules.behaviour_handling import Behavior, correct_chasing_events
 
+from extract_chirps import get_valid_datasets
 ps = PlotStyle()
 
 logger = makeLogger(__name__)
@@ -19,7 +20,9 @@ logger = makeLogger(__name__)
 
 def main(datapath: str):
 
-    foldernames = [datapath + x + '/'  for x in os.listdir(datapath) if os.path.isdir(datapath+x)]
+    foldernames = [
+        datapath + x + '/' for x in os.listdir(datapath) if os.path.isdir(datapath+x)]
+    foldernames, _ = get_valid_datasets(datapath)
     for foldername in foldernames:
         #foldername = foldernames[0]
         if foldername == '../data/mount_data/2020-05-12-10_00/':
@@ -47,14 +50,18 @@ def main(datapath: str):
         fish1_color = ps.red
         fish2_color = ps.orange
 
-        fig, ax = plt.subplots(4, 1, figsize=(21*ps.cm, 13*ps.cm), height_ratios=[0.5, 0.5, 0.5, 6], sharex=True)
+        fig, ax = plt.subplots(4, 1, figsize=(
+            21*ps.cm, 13*ps.cm), height_ratios=[0.5, 0.5, 0.5, 6], sharex=True)
         # marker size
         s = 200
-        ax[0].scatter(physical_contact, np.ones(len(physical_contact)), color='firebrick', marker='|', s=s)
+        ax[0].scatter(physical_contact, np.ones(
-        ax[1].scatter(chasing_onset, np.ones(len(chasing_onset)), color='green', marker='|', s=s )
+            len(physical_contact)), color='firebrick', marker='|', s=s)
-        ax[2].scatter(fish1, np.ones(len(fish1))-0.25, color=fish1_color, marker='|', s=s)
+        ax[1].scatter(chasing_onset, np.ones(len(chasing_onset)),
-        ax[2].scatter(fish2, np.zeros(len(fish2))+0.25, color=fish2_color, marker='|', s=s)
+                      color='green', marker='|', s=s)
-
+        ax[2].scatter(fish1, np.ones(len(fish1))-0.25,
+                      color=fish1_color, marker='|', s=s)
+        ax[2].scatter(fish2, np.zeros(len(fish2))+0.25,
+                      color=fish2_color, marker='|', s=s)
 
         freq_temp = bh.freq[bh.ident == fish1_id]
         time_temp = bh.time[bh.idx[bh.ident == fish1_id]]
@@ -73,7 +80,6 @@ def main(datapath: str):
         ax[0].set_yticks([])
         ps.hide_ax(ax[0])
 
-
         ax[1].grid(False)
         ax[1].set_frame_on(False)
         ax[1].set_xticks([])
@@ -86,16 +92,17 @@ def main(datapath: str):
         ax[2].set_xticks([])
         ps.hide_ax(ax[2])
 
-
-
         ax[3].axvspan(3, 6, 0, 5, facecolor='grey', alpha=0.5)
         ax[3].set_xticks(np.arange(0, 6.1, 0.5))
 
         labelpad = 40
         fsize = 12
-        ax[0].set_ylabel('Physical contact', rotation=0, labelpad=labelpad, fontsize=fsize)
+        ax[0].set_ylabel('Physical contact', rotation=0,
-        ax[1].set_ylabel('Chasing events', rotation=0, labelpad=labelpad, fontsize=fsize)
+                         labelpad=labelpad, fontsize=fsize)
-        ax[2].set_ylabel('Chirps', rotation=0, labelpad=labelpad, fontsize=fsize)
+        ax[1].set_ylabel('Chasing events', rotation=0,
+                         labelpad=labelpad, fontsize=fsize)
+        ax[2].set_ylabel('Chirps', rotation=0,
+                         labelpad=labelpad, fontsize=fsize)
         ax[3].set_ylabel('EODf')
 
         ax[3].set_xlabel('Time [h]')
@@ -105,7 +112,6 @@ def main(datapath: str):
         # plt.savefig('../poster/figs/timeline.pdf')
         plt.show()
 
-
     # plot chirps