evaluation code

09_plot_ws_hist.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn
+from config import conf
+import os
+
+hist_sum = np.zeros((len(conf.all_window_sizes)), dtype=int)
+for trait in xrange(0, conf.n_traits):
+  for si in xrange(0, 100):
+    filename = conf.get_result_filename(conf.annotation_all, trait, False, si, add_suffix=True)
+    if os.path.exists(filename):
+      data = np.load(filename)
+      chosen_window_indices = data['chosen_window_indices']
+      hist, _ = np.histogram(chosen_window_indices, bins=np.arange(-0.5, len(conf.all_window_sizes), 1))
+      hist_sum += hist
+    else:
+      print 'did not find', filename
+
+hist_sum_sum = np.sum(hist_sum)
+
+plt.figure()
+ax = plt.subplot(111)
+bars = ax.bar(conf.all_window_sizes, hist_sum/float(hist_sum_sum)*100, width=8, tick_label=[str(x) for x in conf.all_window_sizes])
+
+for rect in bars:
+        height = rect.get_height()
+        ax.text(rect.get_x() + rect.get_width()/2., 1.01*height,
+                '%d' % (height/100.*hist_sum_sum),
+                ha='center', va='bottom')
+
+# Hide the right and top spines
+ax.spines['right'].set_visible(False)
+ax.spines['top'].set_visible(False)
+plt.xlabel('window size in s')
+plt.ylabel('percentage')
+plt.savefig('figures/ws_hist.pdf')
+plt.close()