matplotlib
diff --git a/‎examples/pylab_examples/axes_demo.py
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+23-22Lines changed: 23 additions & 22 deletions b/‎examples/pylab_examples/axes_demo.py
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+23-22Lines changed: 23 additions & 22 deletions
diff --git a/‎examples/pylab_examples/broken_axis.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎examples/pylab_examples/broken_axis.py
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎lib/matplotlib/backend_bases.py
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+6-7Lines changed: 6 additions & 7 deletions b/‎lib/matplotlib/backend_bases.py
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+6-7Lines changed: 6 additions & 7 deletions
diff --git a/‎lib/matplotlib/transforms.py
Copy file name to clipboardExpand all lines: lib/matplotlib/transforms.py
+3-2Lines changed: 3 additions & 2 deletions b/‎lib/matplotlib/transforms.py
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+3-2Lines changed: 3 additions & 2 deletions
@@ -1,32 +1,33 @@
-#!/usr/bin/env python
-
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np
 
 # create some data to use for the plot
 dt = 0.001
-t = arange(0.0, 10.0, dt)
-r = exp(-t[:1000]/0.05)               # impulse response
-x = randn(len(t))
-s = convolve(x, r)[:len(x)]*dt  # colored noise
+t = np.arange(0.0, 10.0, dt)
+r = np.exp(-t[:1000]/0.05)               # impulse response
+x = np.random.randn(len(t))
+s = np.convolve(x, r)[:len(x)]*dt  # colored noise
 
 # the main axes is subplot(111) by default
-plot(t, s)
-axis([0, 1, 1.1*amin(s), 2*amax(s)])
-xlabel('time (s)')
-ylabel('current (nA)')
-title('Gaussian colored noise')
+plt.plot(t, s)
+plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
+plt.xlabel('time (s)')
+plt.ylabel('current (nA)')
+plt.title('Gaussian colored noise')
 
 # this is an inset axes over the main axes
-a = axes([.65, .6, .2, .2], axisbg='y')
-n, bins, patches = hist(s, 400, normed=1)
-title('Probability')
-setp(a, xticks=[], yticks=[])
+a = plt.axes([.65, .6, .2, .2], axisbg='y')
+n, bins, patches = plt.hist(s, 400, normed=1)
+plt.title('Probability')
+plt.xticks([])
+plt.yticks([])
 
 # this is another inset axes over the main axes
-a = axes([0.2, 0.6, .2, .2], axisbg='y')
-plot(t[:len(r)], r)
-title('Impulse response')
-setp(a, xlim=(0, .2), xticks=[], yticks=[])
-
+a = plt.axes([0.2, 0.6, .2, .2], axisbg='y')
+plt.plot(t[:len(r)], r)
+plt.title('Impulse response')
+plt.xlim(0, 0.2)
+plt.xticks([])
+plt.yticks([])
 
-show()
+plt.show()
@@ -1,7 +1,7 @@
 """
 Broken axis example, where the y-axis will have a portion cut out.
 """
-import matplotlib.pylab as plt
+import matplotlib.pyplot as plt
 import numpy as np
 
 
 
@@ -2813,15 +2813,14 @@ def mouse_move(self, event):
                 pass
             else:
                 artists = event.inaxes.hitlist(event)
-                if event.inaxes.patch in artists:
-                    artists.remove(event.inaxes.patch)
 
                 if artists:
-                    artists.sort(key=lambda x: x.zorder)
-                    a = artists[-1]
-                    data = a.get_cursor_data(event)
-                    if data is not None:
-                        s += ' [%s]' % a.format_cursor_data(data)
+                    a = max(enumerate(artists), key=lambda x: x[1].zorder)[1]
+                    if a is not event.inaxes.patch:
+                        data = a.get_cursor_data(event)
+                        if data is not None:
+                            s += ' [%s]' % a.format_cursor_data(data)
+
                 if len(self.mode):
                     self.set_message('%s, %s' % (self.mode, s))
                 else:
 
@@ -50,7 +50,8 @@
 from .path import Path
 
 DEBUG = False
-
+# we need this later, but this is very expensive to set up
+MINFLOAT = np.MachAr(float).xmin
 MaskedArray = ma.MaskedArray
 
 
@@ -2738,7 +2739,7 @@ def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=True):
         swapped = True
 
     maxabsvalue = max(abs(vmin), abs(vmax))
-    if maxabsvalue < (1e6 / tiny) * np.MachAr(float).xmin:
+    if maxabsvalue < (1e6 / tiny) * MINFLOAT:
         vmin = -expander
         vmax = expander