Fix some typos in merged examples.

QuLogic · QuLogic · commit 701aba942615 · 2017-05-28T05:41:38.000-04:00
diff --git a/examples/images_contours_and_fields/image_demo.py b/examples/images_contours_and_fields/image_demo.py
@@ -138,9 +138,9 @@
 
 ###############################################################################
 # You can specify whether images should be plotted with the array origin
-# x[0,0] in the upper left or upper right by using the origin parameter.
+# x[0,0] in the upper left or lower right by using the origin parameter.
 # You can also control the default be setting image.origin in your
-# matplotlibrc file; see http://matplotlib.org/matplotlibrc
+# :ref:`matplotlibrc file <customizing-with-matplotlibrc-files>`
 
 x = np.arange(120).reshape((10, 12))
 
diff --git a/examples/pylab_examples/fancybox_demo.py b/examples/pylab_examples/fancybox_demo.py
@@ -93,7 +93,7 @@ def test2(ax):
     #p_fancy.set_boxstyle("round", pad=0.1, rounding_size=0.2)
 
     ax.text(0.1, 0.8,
-            ' boxstyle="round,pad=0.1\n rounding\\_size=0.2"',
+            ' boxstyle="round,pad=0.1\n rounding_size=0.2"',
             size=10, transform=ax.transAxes)
 
     # draws control points for the fancy box.
@@ -118,7 +118,7 @@ def test3(ax):
     ax.add_patch(p_fancy)
 
     ax.text(0.1, 0.8,
-            ' boxstyle="round,pad=0.1"\n mutation\\_scale=2',
+            ' boxstyle="round,pad=0.1"\n mutation_scale=2',
             size=10, transform=ax.transAxes)
 
     # draws control points for the fancy box.
@@ -152,7 +152,7 @@ def test4(ax):
     ax.add_patch(p_fancy)
 
     ax.text(0.1, 0.8,
-            ' boxstyle="round,pad=0.3"\n mutation\\_aspect=.5',
+            ' boxstyle="round,pad=0.3"\n mutation_aspect=.5',
             size=10, transform=ax.transAxes)
 
     draw_bbox(ax, bb)
diff --git a/examples/pylab_examples/psd_demo.py b/examples/pylab_examples/psd_demo.py
@@ -5,7 +5,7 @@
 
 Plotting Power Spectral Density (PSD) in Matplotlib.
 
-The PSD is a common plot in the field of signal processing. Numpy has
+The PSD is a common plot in the field of signal processing. NumPy has
 many useful libraries for computing a PSD. Below we demo a few examples
 of how this can be accomplished and visualized with Matplotlib.
 """
