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tacaswell merged 1 commit into from
Jun 29, 2016
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adding from_list to custom cmap tutorial #6662

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78 changes: 52 additions & 26 deletions examples/pylab_examples/custom_cmap.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,18 @@
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
Expand Down Expand Up @@ -55,7 +67,32 @@
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),
Expand Down Expand Up @@ -130,39 +167,29 @@
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*
Expand All @@ -171,19 +198,18 @@
# 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()
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