matplotlib · mdboom · Aug 6, 2013 · Aug 6, 2013 · Aug 6, 2013 · Aug 7, 2013
diff --git a/doc/conf.py b/doc/conf.py
@@ -11,6 +11,7 @@
 # All configuration values have a default value; values that are commented out
 # serve to show the default value.
 
+from distutils import version
 import os
 import sys
 import sphinx
@@ -44,7 +45,7 @@
 
 autosummary_generate = True
 
-if sphinx.__version__ >= 1.1:
+if version.LooseVersion(sphinx.__version__) >= version.LooseVersion('1.1'):
     autodoc_docstring_signature = True
 
 # Add any paths that contain templates here, relative to this directory.

diff --git a/doc/pyplots/text_commands.py b/doc/pyplots/text_commands.py
@@ -1,6 +1,11 @@
 # -*- coding: utf-8 -*-
 import matplotlib.pyplot as plt
 
+# Make this example compatible with Python 2 and 3
+import sys
+if sys.version_info[0] == 3:
+    unicode = str
+
 fig = plt.figure()
 fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')
 

diff --git a/doc/pyplots/whats_new_99_spines.py b/doc/pyplots/whats_new_99_spines.py
@@ -4,7 +4,7 @@
 
 
 def adjust_spines(ax,spines):
-    for loc, spine in ax.spines.iteritems():
+    for loc, spine in ax.spines.items():
         if loc in spines:
             spine.set_position(('outward',10)) # outward by 10 points
         else:

diff --git a/doc/users/image_tutorial.rst b/doc/users/image_tutorial.rst
@@ -40,7 +40,7 @@ examples, if you use the -pylab method, you can skip the "mpimg." and
 Importing image data into Numpy arrays
 ===============================================
 
-Plotting image data is supported by the Python Image Library (`PIL 
+Plotting image data is supported by the Python Image Library (`PIL
 <http://www.pythonware.com/products/pil/>`_).  Natively, matplotlib
 only supports PNG images.  The commands shown below fall back on PIL
 if the native read fails.
@@ -122,7 +122,7 @@ reading/writing for any format other than PNG is limited to uint8
 data.  Why 8 bits? Most displays can only render 8 bits per channel
 worth of color gradation.  Why can they only render 8 bits/channel?
 Because that's about all the human eye can see.  More here (from a
-photography standpoint): `Luminous Landscape bit depth tutorial 
+photography standpoint): `Luminous Landscape bit depth tutorial
 <http://www.luminous-landscape.com/tutorials/bit-depth.shtml>`_.
 
 Each inner list represents a pixel.  Here, with an RGB image, there
@@ -179,7 +179,7 @@ channel of our data:
 
     In [6]: lum_img = img[:,:,0]
 
-This is array slicing.  You can read more in the `Numpy tutorial 
+This is array slicing.  You can read more in the `Numpy tutorial
 <http://www.scipy.org/Tentative_NumPy_Tutorial>`_.
 
 .. sourcecode:: ipython
@@ -336,7 +336,7 @@ and the computer has to draw in pixels to fill that space.
 
 .. sourcecode:: ipython
 
-    In [8]: import Image
+    In [8]: from PIL import Image
     In [9]: img = Image.open('stinkbug.png')    # Open image as PIL image object
     In [10]: rsize = img.resize((img.size[0]/10,img.size[1]/10)) # Use PIL to resize
     In [11]: rsizeArr = np.asarray(rsize)  # Get array back
@@ -347,7 +347,7 @@ and the computer has to draw in pixels to fill that space.
     import matplotlib.pyplot as plt
     import matplotlib.image as mpimg
     import numpy as np
-    import Image
+    from PIL import Image
     img = Image.open('../_static/stinkbug.png')  # opens the file using PIL - it's not an array yet
     rsize = img.resize((img.size[0]/10,img.size[1]/10))  # resize the image
     rsizeArr = np.asarray(rsize)
@@ -368,7 +368,7 @@ Let's try some others:
         import matplotlib.pyplot as plt
         import matplotlib.image as mpimg
         import numpy as np
-        import Image
+        from PIL import Image
         img = Image.open('../_static/stinkbug.png')  # opens the file using PIL - it's not an array yet
         rsize = img.resize((img.size[0]/10,img.size[1]/10))  # resize the image
         rsizeArr = np.asarray(rsize)
@@ -385,7 +385,7 @@ Let's try some others:
         import matplotlib.pyplot as plt
         import matplotlib.image as mpimg
         import numpy as np
-        import Image
+        from PIL import Image
         img = Image.open('../_static/stinkbug.png')  # opens the file using PIL - it's not an array yet
         rsize = img.resize((img.size[0]/10,img.size[1]/10))  # resize the image
         rsizeArr = np.asarray(rsize)

diff --git a/examples/pylab_examples/animation_demo.py b/examples/pylab_examples/animation_demo.py
@@ -13,7 +13,7 @@
 y = np.arange(5)
 z = x * y[:,np.newaxis]
 
-for i in xrange(5):
+for i in range(5):
     if i==0:
         p = plt.imshow(z)
         fig = plt.gcf()

diff --git a/examples/pylab_examples/boxplot_demo2.py b/examples/pylab_examples/boxplot_demo2.py
@@ -57,15 +57,15 @@
 # Now fill the boxes with desired colors
 boxColors = ['darkkhaki','royalblue']
 numBoxes = numDists*2
-medians = range(numBoxes)
-for i in range(numBoxes):
+medians = list(range(numBoxes))
+for i in medians:
   box = bp['boxes'][i]
   boxX = []
   boxY = []
   for j in range(5):
       boxX.append(box.get_xdata()[j])
       boxY.append(box.get_ydata()[j])
-  boxCoords = zip(boxX,boxY)
+  boxCoords = list(zip(boxX,boxY))
   # Alternate between Dark Khaki and Royal Blue
   k = i % 2
   boxPolygon = Polygon(boxCoords, facecolor=boxColors[k])

diff --git a/examples/pylab_examples/filledmarker_demo.py b/examples/pylab_examples/filledmarker_demo.py
@@ -14,13 +14,13 @@
     f = plt.figure()
     f.text(.5,.95, "marker = %r" % marker, ha='center')
     for i,fs in enumerate(mlines.Line2D.fillStyles):
-        color = colors.next()
+        color = next(colors)
 
         ax = f.add_subplot(121)
         ax.plot(2*(4-i)+y, c=color,
                        marker=marker,
-                       markersize=20, 
-                       fillstyle=fs, 
+                       markersize=20,
+                       fillstyle=fs,
                        label=fs)
         ax.legend(loc=2)
         ax.set_title('fillstyle')

diff --git a/examples/pylab_examples/logo.py b/examples/pylab_examples/logo.py
@@ -9,7 +9,7 @@
 datafile = cbook.get_sample_data('membrane.dat', asfileobj=False)
 print('loading', datafile)
 
-x = 1000*0.1*fromstring(file(datafile, 'rb').read(), float32)
+x = 1000*0.1*fromstring(open(datafile, 'rb').read(), float32)
 # 0.0005 is the sample interval
 t = 0.0005*arange(len(x))
 figure(1, figsize=(7,1), dpi=100)

diff --git a/examples/pylab_examples/multiple_yaxis_with_spines.py b/examples/pylab_examples/multiple_yaxis_with_spines.py
@@ -3,7 +3,7 @@
 def make_patch_spines_invisible(ax):
     ax.set_frame_on(True)
     ax.patch.set_visible(False)
-    for sp in ax.spines.itervalues():
+    for sp in ax.spines.values():
         sp.set_visible(False)
 
 fig, host = plt.subplots()
@@ -15,8 +15,8 @@ def make_patch_spines_invisible(ax):
 # Offset the right spine of par2.  The ticks and label have already been
 # placed on the right by twinx above.
 par2.spines["right"].set_position(("axes", 1.2))
-# Having been created by twinx, par2 has its frame off, so the line of its 
-# detached spine is invisible.  First, activate the frame but make the patch 
+# Having been created by twinx, par2 has its frame off, so the line of its
+# detached spine is invisible.  First, activate the frame but make the patch
 # and spines invisible.
 make_patch_spines_invisible(par2)
 # Second, show the right spine.

diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -773,13 +773,13 @@ def get_sample_data(fname, asfileobj=True):
     path = os.path.join(root, fname)
 
     if asfileobj:
-        if (os.path.splitext(fname)[-1].lower() in
-                ('.csv', '.xrc', '.txt')):
+        base, ext = os.path.splitext(fname)
+        ext = ext.lower()
+        if (ext in ('.csv', '.xrc', '.txt')):
             mode = 'r'
         else:
             mode = 'rb'
 
-        base, ext = os.path.splitext(fname)
         if ext == '.gz':
             return gzip.open(path, mode)
         else: