rerun autopep8

twmr · twmr · commit 5b0de04989ff · 2014-09-13T20:09:11.000+02:00
diff --git a/examples/event_handling/poly_editor.py b/examples/event_handling/poly_editor.py
@@ -121,7 +121,7 @@ def key_press_callback(self, event):
             p = event.x, event.y  # display coords
             for i in range(len(xys) - 1):
                 s0 = xys[i]
-                s1 = xys[i+1]
+                s1 = xys[i + 1]
                 d = dist_point_to_segment(p, s0, s1)
                 if d <= self.epsilon:
                     self.poly.xy = np.array(
diff --git a/examples/images_contours_and_fields/interpolation_none_vs_nearest.py b/examples/images_contours_and_fields/interpolation_none_vs_nearest.py
@@ -15,14 +15,14 @@
 import matplotlib.pyplot as plt
 import matplotlib.cbook as cbook
 
-#Load big image
+# Load big image
 big_im_path = cbook.get_sample_data('necked_tensile_specimen.png')
 big_im = plt.imread(big_im_path)
-#Define small image
+# Define small image
 small_im = np.array([[0.25, 0.75, 1.0, 0.75], [0.1, 0.65, 0.5, 0.4],
-    [0.6, 0.3, 0.0, 0.2], [0.7, 0.9, 0.4, 0.6]])
+                     [0.6, 0.3, 0.0, 0.2], [0.7, 0.9, 0.4, 0.6]])
 
-#Create a 2x2 table of plots
+# Create a 2x2 table of plots
 fig = plt.figure(figsize=[8.0, 7.5])
 ax = plt.subplot(2, 2, 1)
 ax.imshow(big_im, interpolation='none')
@@ -33,27 +33,27 @@
 ax = plt.subplot(2, 2, 4)
 ax.imshow(small_im, interpolation='nearest')
 plt.subplots_adjust(left=0.24, wspace=0.2, hspace=0.1,
-    bottom=0.05, top=0.86)
+                    bottom=0.05, top=0.86)
 
-#Label the rows and columns of the table
+# Label the rows and columns of the table
 fig.text(0.03, 0.645, 'Big Image\nScaled Down', ha='left')
 fig.text(0.03, 0.225, 'Small Image\nBlown Up', ha='left')
 fig.text(0.383, 0.90, "Interpolation = 'none'", ha='center')
 fig.text(0.75, 0.90, "Interpolation = 'nearest'", ha='center')
 
-#If you were going to run this example on your local machine, you
-#would save the figure as a PNG, save the same figure as a PDF, and
-#then compare them.  The following code would suffice.
+# If you were going to run this example on your local machine, you
+# would save the figure as a PNG, save the same figure as a PDF, and
+# then compare them.  The following code would suffice.
 txt = fig.text(0.452, 0.95, 'Saved as a PNG', fontsize=18)
-# plt.savefig('None_vs_nearest-png.png')
-# txt.set_text('Saved as a PDF')
-# plt.savefig('None_vs_nearest-pdf.pdf')
-
-#Here, however, we need to display the PDF on a webpage, which means
-#the PDF must be converted into an image.  For the purposes of this
-#example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into
-#'Nearest_vs_none-pdf.png' at 80 dpi.  We simply need to load and
-#display it.
+#plt.savefig('None_vs_nearest-png.png')
+#txt.set_text('Saved as a PDF')
+#plt.savefig('None_vs_nearest-pdf.pdf')
+
+# Here, however, we need to display the PDF on a webpage, which means
+# the PDF must be converted into an image.  For the purposes of this
+# example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into
+# 'Nearest_vs_none-pdf.png' at 80 dpi.  We simply need to load and
+# display it.
 pdf_im_path = cbook.get_sample_data('None_vs_nearest-pdf.png')
 pdf_im = plt.imread(pdf_im_path)
 fig2 = plt.figure(figsize=[8.0, 7.5])
diff --git a/examples/mplot3d/hist3d_demo.py b/examples/mplot3d/hist3d_demo.py
@@ -8,7 +8,7 @@
 hist, xedges, yedges = np.histogram2d(x, y, bins=4)
 
 elements = (len(xedges) - 1) * (len(yedges) - 1)
-xpos, ypos = np.meshgrid(xedges[:-1]+0.25, yedges[:-1]+0.25)
+xpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25)
 
 xpos = xpos.flatten()
 ypos = ypos.flatten()
diff --git a/examples/mplot3d/mixed_subplots_demo.py b/examples/mplot3d/mixed_subplots_demo.py
@@ -42,7 +42,7 @@ def f(t):
 Z = np.sin(R)
 
 surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1,
-        linewidth=0, antialiased=False)
+                       linewidth=0, antialiased=False)
 
 ax.set_zlim3d(-1, 1)
 
diff --git a/examples/mplot3d/scatter3d_demo.py b/examples/mplot3d/scatter3d_demo.py
@@ -4,7 +4,7 @@
 
 
 def randrange(n, vmin, vmax):
-    return (vmax-vmin)*np.random.rand(n) + vmin
+    return (vmax - vmin)*np.random.rand(n) + vmin
 
 fig = plt.figure()
 ax = fig.add_subplot(111, projection='3d')
diff --git a/examples/mplot3d/subplot3d_demo.py b/examples/mplot3d/subplot3d_demo.py
@@ -18,7 +18,7 @@
 R = np.sqrt(X**2 + Y**2)
 Z = np.sin(R)
 surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
-        linewidth=0, antialiased=False)
+                       linewidth=0, antialiased=False)
 ax.set_zlim3d(-1.01, 1.01)
 
 fig.colorbar(surf, shrink=0.5, aspect=10)
diff --git a/examples/mplot3d/surface3d_demo.py b/examples/mplot3d/surface3d_demo.py
@@ -12,7 +12,7 @@
 R = np.sqrt(X**2 + Y**2)
 Z = np.sin(R)
 surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
-        linewidth=0, antialiased=False)
+                       linewidth=0, antialiased=False)
 ax.set_zlim(-1.01, 1.01)
 
 ax.zaxis.set_major_locator(LinearLocator(10))
diff --git a/examples/mplot3d/surface3d_demo3.py b/examples/mplot3d/surface3d_demo3.py
@@ -21,7 +21,7 @@
         colors[x, y] = colortuple[(x + y) % len(colortuple)]
 
 surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, facecolors=colors,
-        linewidth=0, antialiased=False)
+                       linewidth=0, antialiased=False)
 
 ax.set_zlim3d(-1, 1)
 ax.w_zaxis.set_major_locator(LinearLocator(6))
