Seaborn offers a function called color_palette, which allows you to easily create new color_palettes for plots.
colors = ["#67E568","#257F27","#08420D","#FFF000","#FFB62B","#E56124","#E53E30","#7F2353","#F911FF","#9F8CA6"]
color_palette = sns.color_palette(colors)
I want to transform color_palette to a cmap, which I can use in matplotlib, but I don't see how I can do this.
Sadly just functions like "cubehelix_palette","light_palette",… have an "as_cmap" paramater. "color_palette" doesn't, unfortunately.
You have to convert a list of colors from seaborn palette to color map of matplolib (thx to @RafaelLopes for proposed changes):
import seaborn as sns
import matplotlib.pylab as plt
import numpy as np
from matplotlib.colors import ListedColormap
# construct cmap
flatui = ["#9b59b6", "#3498db", "#95a5a6", "#e74c3c", "#34495e", "#2ecc71"]
my_cmap = ListedColormap(sns.color_palette(flatui).as_hex())
N = 500
data1 = np.random.randn(N)
data2 = np.random.randn(N)
colors = np.linspace(0,1,N)
plt.scatter(data1, data2, c=colors, cmap=my_cmap)
plt.colorbar()
plt.show()
Most seaborn methods to generate color palettes have an optional argument as_cmap
which by default is False
. You can use to directly get a Matplotlib colormap:
import seaborn as sns
import matplotlib.pylab as plt
import numpy as np
# construct cmap
my_cmap = sns.light_palette("Navy", as_cmap=True)
N = 500
data1 = np.random.randn(N)
data2 = np.random.randn(N)
colors = np.linspace(0,1,N)
plt.scatter(data1, data2, c=colors, cmap=my_cmap)
plt.colorbar()
plt.show()
The first answer is somehow correct but way too long with a lot of unnecessary information. The correct and short answer is:
To convert any sns.color_palette()
to a matplotlib compatible cmap you need two lines of code
from matplotlib.colors import ListedColormap
cmap = ListedColormap(sns.color_palette())
Just an additional tip - if one wants a continuous colorbar/colormap, adding 256 as the number of colors required from Seaborn colorscheme helps a lot.
cmap = ListedColormap(sns.color_palette("Spectral",256))