I have an image that I\'m showing with matplotlib.
The image is gener
This sounds like the seismic colormap
You might want to force the minimum and maximum to get the middle to be white.
There's more than one way to do this. In your case, it's easiest to use LinearSegmentedColormap.from_list
and specify relative positions of colors as well as the colornames. (If you had evenly-spaced changes, you could skip the tuples and just do from_list('my cmap', ['blue', 'white', 'red'])
.) You'll then need to specify a manual min and max to the data (the vmin
and vmax
kwargs to imshow
/pcolor
/etc).
As an example:
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
data = np.array(
[[ 0.000, 0.120, 0.043, 0.094, 0.037, 0.045],
[ 0.120, 0.000, 0.108, 0.107, 0.105, 0.108],
[ 0.043, 0.108, 0.000, 0.083, 0.043, 0.042],
[ 0.094, 0.107, 0.083, 0.000, 0.083, 0.089],
[ 0.037, 0.105, 0.043, 0.083, 0.000, 2.440],
[ 0.045, 0.108, 0.042, 0.089, 2.440, 0.000]])
mask = np.tri(data.shape[0], k=-1)
data = np.ma.masked_where(mask, data)
vmax = 3.0
cmap = LinearSegmentedColormap.from_list('mycmap', [(0 / vmax, 'blue'),
(1 / vmax, 'white'),
(3 / vmax, 'red')]
)
fig, ax = plt.subplots()
im = ax.pcolor(data, cmap=cmap, vmin=0, vmax=vmax, edgecolors='black')
cbar = fig.colorbar(im)
cbar.set_ticks(range(4)) # Integer colorbar tick locations
ax.set(frame_on=False, aspect=1, xticks=[], yticks=[])
ax.invert_yaxis()
plt.show()