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How to view all colormaps available in Matplotlib?
To view all colormaps available in Matplotlib, we can take the following steps −
- Set the figure size and adjust the padding between and around the subplots.
- Create a new figure or activate an existing figure.
- Add an '~.axes.Axes' to the figure as part of a subplot arrangement
- Make an axis that is divider on the existing axes.
- Create random data using numpy.
- Display the data as an image, i.e., on a 2D regular raster.
- Create a colorbar for a ScalarMappable instance, im.
- Set a title for the current figure.
- Animate the image with all colormaps available in matplotlib.
- Make an animation by repeatedly calling a function.
- To display the figure, use show() method.
Example
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.axes_grid1 import make_axes_locatable
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
fig = plt.figure()
ax = fig.add_subplot(111)
div = make_axes_locatable(ax)
cax = div.append_axes('right', '5%', '5%')
data = np.random.rand(5, 5)
im = ax.imshow(data)
cb = fig.colorbar(im, cax=cax)
cmap = plt.colormaps()
tx = ax.set_title('Color map: {0}'.format(cmap[0]))
def animate(i):
cax.cla()
data = np.random.rand(5, 5)
im = ax.imshow(data, cmap=cmap[i])
fig.colorbar(im, cax=cax)
tx.set_text('Color map: {0}'.format(cmap[i]))
ani = animation.FuncAnimation(fig, animate, frames=166)
plt.show()Output
Updated on: 15-Jun-2021
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