How to create a heat map in python that ranges from green to red?

Question

I am trying to display logarithmic relations from a range of -3 to 3 and want negative relations to be green and positive to be red, while the ratio of the logarithm of 0 (in the center) would be white. None of the pre-existing color schemes in matplotlib provide this feature, and I could not figure out how to manually draw a beautiful gradient.

Answer 1

You can create your own using LinearSegmentedColormap. I like to set the red and green channels to something less than 1.0 at the upper and lower limits, so the colors are not too bright (here I used 0.8). Adjust it to your taste.

See the custom_cmap example on the matplotlib website for more details.

Here is a working example:

import matplotlib.pyplot as plt
import matplotlib.colors as colors
import numpy as np

# This dictionary defines the colormap
cdict = {'red':  ((0.0, 0.0, 0.0),   # no red at 0
                  (0.5, 1.0, 1.0),   # all channels set to 1.0 at 0.5 to create white
                  (1.0, 0.8, 0.8)),  # set to 0.8 so its not too bright at 1

        'green': ((0.0, 0.8, 0.8),   # set to 0.8 so its not too bright at 0
                  (0.5, 1.0, 1.0),   # all channels set to 1.0 at 0.5 to create white
                  (1.0, 0.0, 0.0)),  # no green at 1

        'blue':  ((0.0, 0.0, 0.0),   # no blue at 0
                  (0.5, 1.0, 1.0),   # all channels set to 1.0 at 0.5 to create white
                  (1.0, 0.0, 0.0))   # no blue at 1
       }

# Create the colormap using the dictionary
GnRd = colors.LinearSegmentedColormap('GnRd', cdict)

# Make a figure and axes
fig,ax = plt.subplots(1)

# Some fake data in the range -3 to 3
dummydata = np.random.rand(5,5)*6.-3.

# Plot the fake data
p=ax.pcolormesh(dummydata,cmap=GnRd,vmin=-3,vmax=3)

# Make a colorbar
fig.colorbar(p,ax=ax)

plt.show()

Answer 2

How about the following use LinearSegmentedColormap:

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap


cmapGR = LinearSegmentedColormap(
    'GreenRed',
    {
        'red':  ((0.0, 0.0, 0.0),
                (0.5, 1.0, 1.0),
                (1.0, 1.0, 1.0)),
        'green':((0.0, 1.0, 1.0),
                (0.5, 1.0, 1.0),
                ( 1.0, 0.0, 0.0)),
        'blue': ((0.0, 0.0, 0.0),
                (0.5, 1.0, 1.0),
                (1.0, 0.0, 0.0))
    },)

plt.imshow(np.array([np.arange(200) for i in range(200)]), cmap=cmapGR)
plt.show()

He gives the following

See http://matplotlib.org/examples/pylab_examples/custom_cmap.html for more use and other examples.

Answer 3

matplotlib.colors.LinearSegmentedColormap from_list , .

from  matplotlib.colors import LinearSegmentedColormap
cmap=LinearSegmentedColormap.from_list('rg',["r", "w", "g"], N=256) 

:

from  matplotlib.colors import LinearSegmentedColormap
c = ["darkred","red","lightcoral","white", "palegreen","green","darkgreen"]
v = [0,.15,.4,.5,0.6,.9,1.]
l = list(zip(v,c))
cmap=LinearSegmentedColormap.from_list('rg',l, N=256)