import cppcolormap as cm
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
cmap = cm.Reds()
m_cmap = mpl.colors.ListedColormap(cmap, name="Reds", N=cmap.shape[0])
xterm = cm.xterm()
idx = cm.match(cmap, xterm, cm.metric.perceptual)
m_xterm = mpl.colors.ListedColormap(xterm[idx, :],
name="xterm",
N=cmap.shape[0])
fig, axes = plt.subplots(figsize=(16, 8), ncols=2)
x, y = np.meshgrid(np.linspace(0, 99, 100), np.linspace(0, 99, 100))
z = (x - 50)**2.0 + (y - 50)**2.0
im = axes[0].imshow(z, cmap=m_cmap, clim=(0, 5000))
im = axes[1].imshow(z, cmap=m_xterm, clim=(0, 5000))
plt.savefig("match.pdf")
plt.close()
import cppcolormap as cmap
import matplotlib.pyplot as plt
import numpy as np
colormapNames = 'Accent,Dark2,Paired,Spectral,Pastel1,Pastel2,Set1,Set2,Set3,Blues,Greens,Greys,Oranges,Purples,Reds,BuPu,GnBu,PuBu,PuBuGn,PuRd,RdPu,OrRd,RdOrYl,YlGn,YlGnBu,YlOrRd,BrBG,PuOr,RdBu,RdGy,RdYlBu,RdYlGn,PiYG,PRGn'
# number of colors in the colormap (optional, may be omitted)
N = 128
# specify the colormap as string
cr = cmap.colormap("Reds", N)
cc = cmap.colorcycle("tue")
# or call the functions directly
c = cmap.Reds(N)
c = cmap.tue()
plt.imshow(
np.reshape(
cmap.colormap(colormapNames.split(',')[6], N * N) / 255., (N, N, 3)))
plt.show()