Creating Custom Colormaps¶

Colormaps provide a way to translate from numbers to colors. The matplotlib colormaps are lovely, but sometimes we just want to say "I'd like a colormap that goes from this color to that color." The one2another colormap generator does just that.

In [1]:

from chromatic import one2another, version

from chromatic import one2another, version

In [2]:

version()

version()

Out[2]:

'0.4.12'

How do we make a new colormap?¶

All we need to specify is the color at the bottom and the color at the top. If we want to get really fancy, we can specify different alpha (= opacity) values for either of these limits.

In [3]:

one2another("orchid", "black")

one2another("orchid", "black")

Out[3]:

orchid2black

under

bad

over

In [4]:

one2another("black", "orchid")

one2another("black", "orchid")

Out[4]:

black2orchid

under

bad

over

In [5]:

one2another(bottom="orchid", top="orchid", alpha_bottom=0)

one2another(bottom="orchid", top="orchid", alpha_bottom=0)

Out[5]:

orchid2orchid

under

bad

over

That's it! You can use these colormaps anywhere you'd set cmap= in a matplotlib function.

In [6]:

import numpy as np, matplotlib.pyplot as plt

# make a custom cmap
my_fancy_cmap = one2another("orchid", "black")

# make some fake data
x, y = np.random.uniform(-1, 1, [2, 1000])
z = np.random.normal(0, 1, [10, 10])

# use the cmap
fi, ax = plt.subplots(1, 2, constrained_layout=True)
ax[0].scatter(x, y, c=x**2 + y**2, cmap=my_fancy_cmap)
ax[0].axis("scaled")
ax[1].imshow(z, cmap=my_fancy_cmap)
ax[1].axis("scaled");

import numpy as np, matplotlib.pyplot as plt # make a custom cmap my_fancy_cmap = one2another("orchid", "black") # make some fake data x, y = np.random.uniform(-1, 1, [2, 1000]) z = np.random.normal(0, 1, [10, 10]) # use the cmap fi, ax = plt.subplots(1, 2, constrained_layout=True) ax[0].scatter(x, y, c=x**2 + y**2, cmap=my_fancy_cmap) ax[0].axis("scaled") ax[1].imshow(z, cmap=my_fancy_cmap) ax[1].axis("scaled");