python - Combining two matplotlib colormaps -

i merge 2 colormaps one, such can use 1 cmap negative values , other 1 positive values.

at moment masked arrays , plotting 1 image 1 cmap , other image other, resulting in:

with following data

dat = np.random.rand(10,10) * 2 - 1 pos = np.ma.masked_array(dat, dat<0) neg = np.ma.masked_array(dat, dat>=0) 

i plotted pos gist_heat_r , neg binary.

i have single colorbar combined cmap's, not correct approach me.

so, how take 2 existing cmaps's , merge them one?

edit: admit, duplicate, answer that's given more clear here. example images make more clear.

colormaps interpolation functions can call. map values interval [0,1] colors. can sample colors both maps , combine them:

import numpy np import matplotlib.pyplot plt import matplotlib.colors mcolors  data = np.random.rand(10,10) * 2 - 1  # sample colormaps want use. use 128 each 256 # colors in total colors1 = plt.cm.binary(np.linspace(0., 1, 128)) colors2 = plt.cm.gist_heat_r(np.linspace(0, 1, 128))  # combine them , build new colormap colors = np.vstack((colors1, colors2)) mymap = mcolors.linearsegmentedcolormap.from_list('my_colormap', colors)  plt.pcolor(data, cmap=mymap) plt.colorbar() plt.show() 

result:

note: understand might have specific needs this, in opinion not approach: how distinguish -0.1 0.9? -0.9 0.1?

one way prevent sample maps ~0.2 ~0.8 (e.g.: colors1 = plt.cm.binary(np.linspace(0.2, 0.8, 128))) wont go way black: