Cleanup bullseye plot example.

Fix typo in filename.
Tighten axes layout, and use relative coordinates to position colorbars
instead of hardcoded absolute positions (which become wrong as soon as
the figure size changes).

Author: anntzer

examples/specialty_plots/leftventricle_bulleye.py renamed to examples/specialty_plots/leftventricle_bullseye.py

@@ -5,6 +5,8 @@
 
 This example demonstrates how to create the 17 segment model for the left
 ventricle recommended by the American Heart Association (AHA).
+
+.. redirect-from:: /gallery/specialty_plots/leftventricle_bulleye
 """
 
 import numpy as np
@@ -135,15 +137,11 @@ def bullseye_plot(ax, data, seg_bold=None, cmap=None, norm=None):
 
 
 # Make a figure and axes with dimensions as desired.
-fig, ax = plt.subplots(figsize=(12, 8), nrows=1, ncols=3,
-                       subplot_kw=dict(projection='polar'))
+fig = plt.figure(figsize=(10, 5), layout="constrained")
+fig.get_layout_engine().set(wspace=.1, w_pad=.2)
+axs = fig.subplots(1, 3, subplot_kw=dict(projection='polar'))
 fig.canvas.manager.set_window_title('Left Ventricle Bulls Eyes (AHA)')
 
-# Create the axis for the colorbars
-axl = fig.add_axes([0.14, 0.15, 0.2, 0.05])
-axl2 = fig.add_axes([0.41, 0.15, 0.2, 0.05])
-axl3 = fig.add_axes([0.69, 0.15, 0.2, 0.05])
-
 
 # Set the colormap and norm to correspond to the data for which
 # the colorbar will be used.
@@ -152,14 +150,16 @@ def bullseye_plot(ax, data, seg_bold=None, cmap=None, norm=None):
 # Create an empty ScalarMappable to set the colorbar's colormap and norm.
 # The following gives a basic continuous colorbar with ticks and labels.
 fig.colorbar(mpl.cm.ScalarMappable(cmap=cmap, norm=norm),
-             cax=axl, orientation='horizontal', label='Some Units')
+             cax=axs[0].inset_axes([0, -.15, 1, .1]),
+             orientation='horizontal', label='Some Units')
 
 
 # And again for the second colorbar.
 cmap2 = mpl.cm.cool
 norm2 = mpl.colors.Normalize(vmin=1, vmax=17)
 fig.colorbar(mpl.cm.ScalarMappable(cmap=cmap2, norm=norm2),
-             cax=axl2, orientation='horizontal', label='Some other units')
+             cax=axs[1].inset_axes([0, -.15, 1, .1]),
+             orientation='horizontal', label='Some other units')
 
 
 # The second example illustrates the use of a ListedColormap, a
@@ -173,7 +173,7 @@ def bullseye_plot(ax, data, seg_bold=None, cmap=None, norm=None):
 bounds = [2, 3, 7, 9, 15]
 norm3 = mpl.colors.BoundaryNorm(bounds, cmap3.N)
 fig.colorbar(mpl.cm.ScalarMappable(cmap=cmap3, norm=norm3),
-             cax=axl3,
+             cax=axs[2].inset_axes([0, -.15, 1, .1]),
              extend='both',
              ticks=bounds,  # optional
              spacing='proportional',
@@ -182,14 +182,14 @@ def bullseye_plot(ax, data, seg_bold=None, cmap=None, norm=None):
 
 
 # Create the 17 segment model
-bullseye_plot(ax[0], data, cmap=cmap, norm=norm)
-ax[0].set_title('Bulls Eye (AHA)')
+bullseye_plot(axs[0], data, cmap=cmap, norm=norm)
+axs[0].set_title('Bulls Eye (AHA)')
 
-bullseye_plot(ax[1], data, cmap=cmap2, norm=norm2)
-ax[1].set_title('Bulls Eye (AHA)')
+bullseye_plot(axs[1], data, cmap=cmap2, norm=norm2)
+axs[1].set_title('Bulls Eye (AHA)')
 
-bullseye_plot(ax[2], data, seg_bold=[3, 5, 6, 11, 12, 16],
+bullseye_plot(axs[2], data, seg_bold=[3, 5, 6, 11, 12, 16],
               cmap=cmap3, norm=norm3)
-ax[2].set_title('Segments [3, 5, 6, 11, 12, 16] in bold')
+axs[2].set_title('Segments [3, 5, 6, 11, 12, 16] in bold')
 
 plt.show()