Merge pull request #6662 from choldgraf/tutorial_fromlist_cmap

tacaswell · tacaswell · commit 9e5b18a930f7 · 2016-06-29T18:44:29.000-04:00
DOC: adding from_list to custom cmap tutorial
diff --git a/examples/pylab_examples/custom_cmap.py b/examples/pylab_examples/custom_cmap.py
@@ -5,6 +5,18 @@
 from matplotlib.colors import LinearSegmentedColormap
 
 """
+Creating a colormap from a list of colors
+-----------------------------------------
+Creating a colormap from a list of colors can be done with the `from_list`
+method of `LinearSegmentedColormap`. You must pass a list of RGB tuples that
+define the mixture of colors from 0 to 1.
+
+
+Creating custom colormaps
+-------------------------
+It is also possible to create a custom mapping for a colormap. This is
+accomplished by creating dictionary that specifies how the RGB channels
+change from one end of the cmap to the other.
 
 Example: suppose you want red to increase from 0 to 1 over the bottom
 half, green to do the same over the middle half, and blue over the top
@@ -57,7 +69,32 @@
 never used.
 
 """
+# Make some illustrative fake data:
+
+x = np.arange(0, np.pi, 0.1)
+y = np.arange(0, 2*np.pi, 0.1)
+X, Y = np.meshgrid(x, y)
+Z = np.cos(X) * np.sin(Y) * 10
+
+
+# --- Colormaps from a list ---
 
+colors = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]  # R -> G -> B
+n_bins = [3, 6, 10, 100]  # Discretizes the interpolation into bins
+cmap_name = 'my_list'
+fig, axs = plt.subplots(2, 2, figsize=(6, 9))
+fig.subplots_adjust(left=0.02, bottom=0.06, right=0.95, top=0.94, wspace=0.05)
+for n_bin, ax in zip(n_bins, axs.ravel()):
+    # Create the colormap
+    cm = LinearSegmentedColormap.from_list(
+        cmap_name, colors, N=n_bin)
+    # Fewer bins will result in "coarser" colomap interpolation
+    im = ax.imshow(Z, interpolation='nearest', origin='lower', cmap=cm)
+    ax.set_title("N bins: %s" % n_bin)
+    fig.colorbar(im, ax=ax)
+
+
+# --- Custom colormaps ---
 
 cdict1 = {'red':   ((0.0, 0.0, 0.0),
                    (0.5, 0.0, 0.1),
@@ -132,39 +169,29 @@
 plt.register_cmap(name='BlueRed3', data=cdict3)  # optional lut kwarg
 plt.register_cmap(name='BlueRedAlpha', data=cdict4)
 
-# Make some illustrative fake data:
-
-x = np.arange(0, np.pi, 0.1)
-y = np.arange(0, 2*np.pi, 0.1)
-X, Y = np.meshgrid(x, y)
-Z = np.cos(X) * np.sin(Y) * 10
-
 # Make the figure:
 
-plt.figure(figsize=(6, 9))
-plt.subplots_adjust(left=0.02, bottom=0.06, right=0.95, top=0.94, wspace=0.05)
+fig, axs = plt.subplots(2, 2, figsize=(6, 9))
+fig.subplots_adjust(left=0.02, bottom=0.06, right=0.95, top=0.94, wspace=0.05)
 
 # Make 4 subplots:
 
-plt.subplot(2, 2, 1)
-plt.imshow(Z, interpolation='nearest', cmap=blue_red1)
-plt.colorbar()
+im1 = axs[0, 0].imshow(Z, interpolation='nearest', cmap=blue_red1)
+fig.colorbar(im1, ax=axs[0, 0])
 
-plt.subplot(2, 2, 2)
 cmap = plt.get_cmap('BlueRed2')
-plt.imshow(Z, interpolation='nearest', cmap=cmap)
-plt.colorbar()
+im2 = axs[1, 0].imshow(Z, interpolation='nearest', cmap=cmap)
+fig.colorbar(im2, ax=axs[1, 0])
 
 # Now we will set the third cmap as the default.  One would
 # not normally do this in the middle of a script like this;
 # it is done here just to illustrate the method.
 
 plt.rcParams['image.cmap'] = 'BlueRed3'
 
-plt.subplot(2, 2, 3)
-plt.imshow(Z, interpolation='nearest')
-plt.colorbar()
-plt.title("Alpha = 1")
+im3 = axs[0, 1].imshow(Z, interpolation='nearest')
+fig.colorbar(im3, ax=axs[0, 1])
+axs[0, 1].set_title("Alpha = 1")
 
 # Or as yet another variation, we can replace the rcParams
 # specification *before* the imshow with the following *after*
@@ -173,19 +200,18 @@
 # image-like item plotted via pyplot, if any.
 #
 
-plt.subplot(2, 2, 4)
 # Draw a line with low zorder so it will be behind the image.
-plt.plot([0, 10*np.pi], [0, 20*np.pi], color='c', lw=20, zorder=-1)
+axs[1, 1].plot([0, 10*np.pi], [0, 20*np.pi], color='c', lw=20, zorder=-1)
 
-plt.imshow(Z, interpolation='nearest')
-plt.colorbar()
+im4 = axs[1, 1].imshow(Z, interpolation='nearest')
+fig.colorbar(im4, ax=axs[1, 1])
 
 # Here it is: changing the colormap for the current image and its
 # colorbar after they have been plotted.
-plt.set_cmap('BlueRedAlpha')
-plt.title("Varying alpha")
+im4.set_cmap('BlueRedAlpha')
+axs[1, 1].set_title("Varying alpha")
 #
 
-plt.suptitle('Custom Blue-Red colormaps', fontsize=16)
+fig.suptitle('Custom Blue-Red colormaps', fontsize=16)
 
 plt.show()
