Reverse colormap in matplotlib

More ways to reverse a colormap

Beyond the fast answer, there are more nuances to reversing a colormap in matplotlib. Let's have a look at some additional methods that can come in handy in different situations!

Reversal method for built-in colormaps

Every built-in colormap in matplotlib has a twin sibling who just likes to do everything backwards, identifiable by the _r suffix. For instance, when using plot_surface, the reversed colormap can be implemented this way:

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
surface = ax.plot_surface(X, Y, Z, cmap='coolwarm_r')  # Suddenly, cool things are getting warmer!
plt.show()
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Dynamic reversing in codes

Sometimes, you might want to reverse a colormap on the fly. Fear not, matplotlib's reversed method can allow you to create a "rewind" button for your colormaps. Available from matplotlib 2.0 onward:

from matplotlib.pyplot import get_cmap

original_cmap = get_cmap('cividis')
reversed_cmap = original_cmap.reversed()  # Reverse, reverse! 🎵
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Reversing your custom colormaps

For those who love building their own ListedColormap or LinearSegmentedColormap, even these colormaps can learn to walk backwards:

from matplotlib.colors import ListedColormap, LinearSegmentedColormap

# A ListedColormap that learned to bend its stride
listed_cmap = ListedColormap(['red', 'green', 'blue'])
listed_cmap_reversed = ListedColormap(listed_cmap.colors[::-1])  # Walking on the color moonwalk

# Same for the LinearSegmentedColormap
linear_cmap = LinearSegmentedColormap.from_list('my_cmap', ['red', 'green', 'blue'])
linear_cmap_reversed = LinearSegmentedColormap.from_list('my_cmap_r', linear_cmap.colors[::-1])  # Turning the time-turner like Hermione
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A visual comparison of original and reversed colormaps

If you're a fan of comparisons and enjoy seeing your progress, ColorbarBase from matplotlib.colorbar can be your buddy:

from matplotlib.colorbar import ColorbarBase
from matplotlib.colors import Normalize

norm = Normalize(vmin=0, vmax=1)
fig, ax = plt.subplots(2)

cb1 = ColorbarBase(ax[0], cmap=listed_cmap, norm=norm, orientation='horizontal')  # 😎 Here's how you looked before reversal
cb2 = ColorbarBase(ax[1], cmap=listed_cmap_reversed, norm=norm, orientation='horizontal')  # 🔄 And voilà, the new you!

plt.tight_layout()
plt.show()
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Ensuring quality visualization with reversed colormaps

Reversing a colormap is not just about aesthetics, it's about maintaining data representation. Always confirm if the reversal aids or hinders comprehension of the data. Be a responsible data scientist!

In some special situations, you may need to handcraft a reversed colormap. Here's how:

from matplotlib.colors import ListedColormap

custom_colors = ['#000000', '#123456', '#654321', '#ffffff']  # It's okay to be picky about your colors
custom_cmap = ListedColormap(custom_colors)
reverse_colors = custom_cmap.colors[::-1]  # Colors, fall in line... from the back!
custom_cmap_r = ListedColormap(reverse_colors)
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Then plug this custom_cmap_r into your plots for a tailored reversed visual.