DOC: standardize plural Axes as axs

phobson · phobson · commit fd41c9da99df · 2018-03-26T11:22:29.000-07:00
diff --git a/examples/images_contours_and_fields/barb_demo.py b/examples/images_contours_and_fields/barb_demo.py
@@ -22,23 +22,23 @@
 data = np.array(data, dtype=[('x', np.float32), ('y', np.float32),
                              ('u', np.float32), ('v', np.float32)])
 
-fig, axes1 = plt.subplots(nrows=2, ncols=2)
+fig1, axs1 = plt.subplots(nrows=2, ncols=2)
 # Default parameters, uniform grid
-axes1[0, 0].barbs(X, Y, U, V)
+axs1[0, 0].barbs(X, Y, U, V)
 
 # Arbitrary set of vectors, make them longer and change the pivot point
 # (point around which they're rotated) to be the middle
-axes1[0, 1].barbs(data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle')
+axs1[0, 1].barbs(data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle')
 
 # Showing colormapping with uniform grid.  Fill the circle for an empty barb,
 # don't round the values, and change some of the size parameters
-axes1[1, 0].barbs(X, Y, U, V, np.sqrt(U * U + V * V), fill_empty=True, rounding=False,
-         sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))
+axs1[1, 0].barbs(X, Y, U, V, np.sqrt(U * U + V * V), fill_empty=True, rounding=False,
+                 sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))
 
 # Change colors as well as the increments for parts of the barbs
-axes1[1, 1].barbs(data['x'], data['y'], data['u'], data['v'], flagcolor='r',
-         barbcolor=['b', 'g'],
-         barb_increments=dict(half=10, full=20, flag=100), flip_barb=True)
+axs1[1, 1].barbs(data['x'], data['y'], data['u'], data['v'], flagcolor='r',
+                 barbcolor=['b', 'g'], flip_barb=True,
+                 barb_increments=dict(half=10, full=20, flag=100))
 
 # Masked arrays are also supported
 masked_u = np.ma.masked_array(data['u'])
diff --git a/examples/images_contours_and_fields/contour_corner_mask.py b/examples/images_contours_and_fields/contour_corner_mask.py
@@ -23,8 +23,8 @@
 z = np.ma.array(z, mask=mask)
 
 corner_masks = [False, True]
-fig, axes = plt.subplots(ncols=2)
-for ax, corner_mask in zip(axes, corner_masks):
+fig, axs = plt.subplots(ncols=2)
+for ax, corner_mask in zip(axs, corner_masks):
     cs = ax.contourf(x, y, z, corner_mask=corner_mask)
     ax.contour(cs, colors='k')
     ax.set_title('corner_mask = {0}'.format(corner_mask))
diff --git a/examples/images_contours_and_fields/figimage_demo.py b/examples/images_contours_and_fields/figimage_demo.py
@@ -3,7 +3,7 @@
 Figimage Demo
 =============
 
-This illustrates placing images directly in the figure, with no axes.
+This illustrates placing images directly in the figure, with no Axes objects.
 
 """
 import numpy as np
diff --git a/examples/images_contours_and_fields/image_demo.py b/examples/images_contours_and_fields/image_demo.py
@@ -45,7 +45,7 @@
 
 fig, ax = plt.subplots()
 ax.imshow(image)
-ax.axis('off')  # clear x- and y-axes
+ax.axis('off')  # clear x-axis and y-axis
 
 
 # And another image
diff --git a/examples/images_contours_and_fields/image_masked.py b/examples/images_contours_and_fields/image_masked.py
@@ -42,7 +42,7 @@
 # range to which the regular palette color scale is applied.
 # Anything above that range is colored based on palette.set_over, etc.
 
-# set up the axes
+# set up the Axes objets
 fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 5.4))
 
 # plot using 'continuous' color map
diff --git a/examples/images_contours_and_fields/interpolation_methods.py b/examples/images_contours_and_fields/interpolation_methods.py
@@ -27,12 +27,12 @@
 
 grid = np.random.rand(4, 4)
 
-fig, axes = plt.subplots(3, 6, figsize=(12, 6),
-                         subplot_kw={'xticks': [], 'yticks': []})
+fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(12, 6),
+                        subplot_kw={'xticks': [], 'yticks': []})
 
 fig.subplots_adjust(hspace=0.3, wspace=0.05)
 
-for ax, interp_method in zip(axes.flat, methods):
+for ax, interp_method in zip(axs.flat, methods):
     ax.imshow(grid, interpolation=interp_method, cmap='viridis')
     ax.set_title(str(interp_method))
 
diff --git a/examples/images_contours_and_fields/quiver_demo.py b/examples/images_contours_and_fields/quiver_demo.py
@@ -6,7 +6,7 @@
 Known problem: the plot autoscaling does not take into account
 the arrows, so those on the boundaries are often out of the picture.
 This is *not* an easy problem to solve in a perfectly general way.
-The workaround is to manually expand the axes.
+The workaround is to manually expand the Axes objects.
 """
 import matplotlib.pyplot as plt
 import numpy as np
diff --git a/examples/images_contours_and_fields/shading_example.py b/examples/images_contours_and_fields/shading_example.py
@@ -35,26 +35,26 @@ def main():
 
 def compare(z, cmap, ve=1):
     # Create subplots and hide ticks
-    fig, axes = plt.subplots(ncols=2, nrows=2)
-    for ax in axes.flat:
+    fig, axs = plt.subplots(ncols=2, nrows=2)
+    for ax in axs.flat:
         ax.set(xticks=[], yticks=[])
 
     # Illuminate the scene from the northwest
     ls = LightSource(azdeg=315, altdeg=45)
 
-    axes[0, 0].imshow(z, cmap=cmap)
-    axes[0, 0].set(xlabel='Colormapped Data')
+    axs[0, 0].imshow(z, cmap=cmap)
+    axs[0, 0].set(xlabel='Colormapped Data')
 
-    axes[0, 1].imshow(ls.hillshade(z, vert_exag=ve), cmap='gray')
-    axes[0, 1].set(xlabel='Illumination Intensity')
+    axs[0, 1].imshow(ls.hillshade(z, vert_exag=ve), cmap='gray')
+    axs[0, 1].set(xlabel='Illumination Intensity')
 
     rgb = ls.shade(z, cmap=cmap, vert_exag=ve, blend_mode='hsv')
-    axes[1, 0].imshow(rgb)
-    axes[1, 0].set(xlabel='Blend Mode: "hsv" (default)')
+    axs[1, 0].imshow(rgb)
+    axs[1, 0].set(xlabel='Blend Mode: "hsv" (default)')
 
     rgb = ls.shade(z, cmap=cmap, vert_exag=ve, blend_mode='overlay')
-    axes[1, 1].imshow(rgb)
-    axes[1, 1].set(xlabel='Blend Mode: "overlay"')
+    axs[1, 1].imshow(rgb)
+    axs[1, 1].set(xlabel='Blend Mode: "overlay"')
 
     return fig
 
