Made variable names more meaningful

DrNightmare · DrNightmare · commit 14cd6cfd72a1 · 2016-10-30T12:24:50.000+05:30
diff --git a/examples/statistics/customized_violin_demo.py b/examples/statistics/customized_violin_demo.py
@@ -20,15 +20,14 @@
 
 def adjacent_values(vals):
     q1, q3 = np.percentile(vals, [25, 75])
-    # inter-quartile range iqr
-    iqr = q3 - q1
-    # upper adjacent values
-    uav = q3 + iqr * 1.5
-    uav = np.clip(uav, q3, vals[-1])
-    # lower adjacent values
-    lav = q1 - iqr * 1.5
-    lav = np.clip(lav, vals[0], q1)
-    return [lav, uav]
+    inter_quartile_range = q3 - q1
+
+    upper_adjacent_value = q3 + inter_quartile_range * 1.5
+    upper_adjacent_value = np.clip(upper_adjacent_value, q3, vals[-1])
+
+    lower_adjacent_value = q1 - inter_quartile_range * 1.5
+    lower_adjacent_value = np.clip(lower_adjacent_value, vals[0], q1)
+    return [lower_adjacent_value, upper_adjacent_value]
 
 
 def set_axis_style(ax, labels):
@@ -42,19 +41,19 @@ def set_axis_style(ax, labels):
 
 # create test data
 np.random.seed(123)
-dat = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)]
+data = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)]
 
 fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4), sharey=True)
 
 # plot the default violin
 ax1.set_title('Default violin plot')
 ax1.set_ylabel('Observed values')
-ax1.violinplot(dat)
+ax1.violinplot(data)
 
 # customized violin
 ax2.set_title('Customized violin plot')
 parts = ax2.violinplot(
-        dat, showmeans=False, showmedians=False,
+        data, showmeans=False, showmedians=False,
         showextrema=False)
 
 # customize colors
@@ -63,21 +62,17 @@ def set_axis_style(ax, labels):
     pc.set_edgecolor('black')
     pc.set_alpha(1)
 
-# medians
-med = [np.percentile(sarr, 50) for sarr in dat]
-# inter-quartile ranges
-iqr = [[np.percentile(sarr, 25), np.percentile(sarr, 75)] for sarr in dat]
-# upper and lower adjacent values
-avs = [adjacent_values(sarr) for sarr in dat]
+medians = np.percentile(data, 50, axis=1)
+inter_quartile_ranges = list(zip(*(np.percentile(data, [25, 75], axis=1))))
+whiskers = [adjacent_values(sorted_array) for sorted_array in data]
 
 # plot whiskers as thin lines, quartiles as fat lines,
 # and medians as points
-for i, median in enumerate(med):
-    # whiskers
-    ax2.plot([i + 1, i + 1], avs[i], '-', color='black', linewidth=1)
-    # quartiles
-    ax2.plot([i + 1, i + 1], iqr[i], '-', color='black', linewidth=5)
-    # medians
+for i, median in enumerate(medians):
+    ax2.plot([i + 1, i + 1], whiskers[i], '-', color='black', linewidth=1)
+    ax2.plot(
+        [i + 1, i + 1], inter_quartile_ranges[i], '-', color='black',
+        linewidth=5)
     ax2.plot(
         i + 1, median, 'o', color='white',
         markersize=6, markeredgecolor='none')
