CODEWITHSUNDEEP
pythonmatplotlibheatmap
A. Gup
A. Gup

Reputation: 313

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

I'm trying to plot log ratios from the range -3 to 3 and want negative ratios to be green and positive to be red, with a log ratio of 0 (center) to be white in color. None of the pre-existing color schemes in matplotlib provide this option, and I haven't been able to figure out how to output a nice gradient manually.

Upvotes: 30

Views: 54316

Answers (5)

T1mor
T1mor

Reputation: 153

I don't want to use g or r because these are different than the default Greens and Reds Colormaps https://matplotlib.org/stable/users/explain/colors/colormaps.html

So I concatenate Greens and Reds.

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

sample = 15
colors = np.vstack(
    (
        # Default is White -> Green but I want Green -> White -> Red so reverse the order
        plt.get_cmap("Greens", sample)(np.linspace(0, 1, sample))[::-1],
        # np.ones((1, 4)),  # Explicit White optional
        plt.get_cmap("Reds", sample)(np.linspace(0, 1, sample)),
    )
)
cmap = LinearSegmentedColormap.from_list("green_to_red", colors)

fig, ax = plt.subplots(figsize=(5, 1), tight_layout=True)
ax.imshow(np.array([np.arange(256) for i in range(256)]), cmap="Greens", aspect="auto")
fig.show()

enter image description here

And a Scatter Plot

fig, ax = plt.subplots(figsize=(6, 3), tight_layout=True)
x = np.linspace(-7, 7, 1000)
map = ax.scatter(x, np.cos(x), c=y, cmap=cmap)
fig.colorbar(mappable=map, ax=ax)
fig.show()

enter image description here

Upvotes: 0

Rubayet Alam
Rubayet Alam

Reputation: 61

Not exactly red to green, but there's a diverging colormap: RdYlGn, red-yellow-green.

plot = sns.heatmap(df.corr().round(2),cmap='RdYlGn',annot=True)

Upvotes: 5

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339092

Using matplotlib.colors.LinearSegmentedColormap's from_list method seems more intuitive than some of the other answers here.

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

enter image description here

Or for more sophisticated tuning:

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)

enter image description here

Upvotes: 53

tmdavison
tmdavison

Reputation: 69076

you can create your own using a LinearSegmentedColormap. I like to set the red and green channels to something less than 1.0 at the upper and lower limits so the colours aren't too bright (here I used 0.8). Adjust that to suit your taste.

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

Here's an 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()

enter image description here

Upvotes: 8

jmetz
jmetz

Reputation: 12773

How about the following that uses 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()

It produces the following enter image description here

See e.g. http://matplotlib.org/examples/pylab_examples/custom_cmap.html for more uses and other examples.

Upvotes: 5

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