[statistics] backward compatibility of hist density - still buggy!

plotstyle.py

@@ -2,7 +2,7 @@ import matplotlib as mpl
 import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d import Axes3D
 
-xkcd_style = False
+xkcd_style = True
 
 # default size of figure:
 figure_width = 15.0  # cm, should be set according to \textwidth in the latex document

statistics/lecture/diehistograms.py

@@ -27,6 +27,9 @@ ax2.set_xlabel('x')
 ax2.set_ylim(0, 0.23)
 ax2.set_ylabel('Probability')
 ax2.plot([0.2, 6.8], [1.0/6.0, 1.0/6.0], zorder=-10, **lsAm)
-ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs)
+try:
+    ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs)
+except AttributeError:
+    ax2.hist([x2, x1], bins, normed=True, zorder=-5, **fs)
 fig.subplots_adjust(left=0.125)
 fig.savefig('diehistograms.pdf')

statistics/lecture/displayunivariatedata.py

@@ -4,7 +4,7 @@ import matplotlib.gridspec as gridspec
 from scipy.stats import gaussian_kde
 from plotstyle import *
 
-sketch_style()
+#sketch_style()
 #rng = np.random.RandomState(981)
 #data = rng.randn(40, 1) + 4.0
 rng = np.random.RandomState(1981)

statistics/lecture/kerneldensity.py

@@ -44,7 +44,10 @@ ax.set_ylabel('p(x)')
 ax.set_ylim(0.0, 0.49)
 ax.set_yticks(np.arange(0.0, 0.41, 0.1))
 #ax.plot(x, g, '-b', lw=2, zorder=-1)
-ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC)
+try:
+    ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC)
+except AttributeError:
+    ax.hist(r, np.arange(-4.1, 4, 0.4), normed=True, zorder=-5, **fsC)
 
 ax = fig.add_subplot(spec[1, 0])
 ax.set_xlabel('x')
@@ -54,7 +57,10 @@ ax.set_ylabel('p(x)')
 ax.set_ylim(0.0, 0.49)
 ax.set_yticks(np.arange(0.0, 0.41, 0.1))
 #ax.plot(x, g, '-b', lw=2, zorder=-1)
-ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC)
+try:
+    ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC)
+except AttributeError:
+    ax.hist(r, np.arange(-4.3, 4, 0.4), normed=True, zorder=-5, **fsC)
 
 ax = fig.add_subplot(spec[:, 1])
 ax.set_xlabel('x')

statistics/lecture/pdfhistogram.py

@@ -24,8 +24,12 @@ ax2.set_ylabel('Probab. density p(x)')
 ax2.set_ylim(0.0, 0.44)
 ax2.set_yticks(np.arange(0.0, 0.41, 0.1))
 ax2.plot(x, g, zorder=-1, **lsA)
-ax2.hist(r, 5, density=True, zorder=-10, **fsB)
-ax2.hist(r, 20, density=True, zorder=-5, **fsC)
+try:
+    ax2.hist(r, 5, density=True, zorder=-10, **fsB)
+    ax2.hist(r, 20, density=True, zorder=-5, **fsC)
+except AttributeError:
+    ax2.hist(r, 5, normed=True, zorder=-10, **fsB)
+    ax2.hist(r, 20, normed=True, zorder=-5, **fsC)
 
 fig.savefig('pdfhistogram.pdf')