MEP12: Example clean-up for reference

examples/statistics/histogram_demo_cumulative.py

@@ -0,0 +1,30 @@
+"""
+Demo of the histogram (hist) function used to plot a cumulative distribution.
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib import mlab
+
+
+mu = 200
+sigma = 25
+n_bins = 50
+x = mu + sigma*np.random.randn(10000)
+
+n, bins, patches = plt.hist(x, n_bins, normed=1,
+                            histtype='step', cumulative=True)
+
+# Add a line showing the expected distribution.
+y = mlab.normpdf(bins, mu, sigma).cumsum()
+y /= y[-1]
+plt.plot(bins, y, 'k--', linewidth=1.5)
+
+# Overlay a reversed cumulative histogram.
+plt.hist(x, bins=bins, normed=1, histtype='step', cumulative=-1)
+
+plt.grid(True)
+plt.ylim(0, 1.05)
+plt.title('cumulative step')
+
+plt.show()

examples/statistics/histogram_demo_histtypes.py

@@ -0,0 +1,27 @@
+"""
+Demo of the histogram (hist) function with different ``histtype`` settings.
+
+* Histogram with step curve that has a color fill.
+* Histogram with with unequal bin widths.
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+mu = 200
+sigma = 25
+x = mu + sigma*np.random.randn(10000)
+
+fig, (ax0, ax1) = plt.subplots(ncols=2, figsize=(8, 4))
+
+ax0.hist(x, 20, normed=1, histtype='stepfilled', facecolor='g', alpha=0.75)
+ax0.set_title('stepfilled')
+
+# Create a histogram by providing the bin edges (unequally spaced).
+bins = [100, 150, 180, 195, 205, 220, 250, 300]
+ax1.hist(x, bins, normed=1, histtype='bar', rwidth=0.8)
+ax1.set_title('unequal bins')
+
+plt.tight_layout()
+plt.show()

examples/statistics/histogram_demo_multihist.py

@@ -0,0 +1,38 @@
+"""
+Demo of the histogram (hist) function with multiple data sets.
+
+Plot histogram with multiple sample sets and demonstrate:
+
+    * Use of legend with multiple sample sets
+    * Stacked bars
+    * Step curve with a color fill
+    * Data sets of different sample sizes
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+n_bins = 10
+x = np.random.randn(1000, 3)
+
+fig, axes = plt.subplots(nrows=2, ncols=2)
+ax0, ax1, ax2, ax3 = axes.flat
+
+colors = ['red', 'tan', 'lime']
+ax0.hist(x, n_bins, normed=1, histtype='bar', color=colors, label=colors)
+ax0.legend(prop={'size': 10})
+ax0.set_title('bars with legend')
+
+ax1.hist(x, n_bins, normed=1, histtype='bar', stacked=True)
+ax1.set_title('stacked bar')
+
+ax2.hist(x, n_bins, histtype='step', stacked=True, fill=True)
+ax2.set_title('stepfilled')
+
+# Make a multiple-histogram of data-sets with different length.
+x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
+ax3.hist(x_multi, n_bins, histtype='bar')
+ax3.set_title('different sample sizes')
+
+plt.tight_layout()
+plt.show()

examples/tests/backend_driver.py

@@ -74,7 +74,10 @@
 files['statistics'] = [
     'errorbar_demo.py',
     'errorbar_demo_features.py',
+    'histogram_demo_cumulative.py',
     'histogram_demo_features.py',
+    'histogram_demo_histtypes.py',
+    'histogram_demo_multihist.py',
     ]
 
 files['pie'] = [
@@ -172,7 +175,6 @@
     'hexbin_demo.py',
     'hexbin_demo2.py',
     'hist_colormapped.py',
-    'histogram_demo_extended.py',
     'vline_hline_demo.py',
 
     'image_clip_path.py',