Specifying the color Increments of heat-map in python

Question

Is there a way to specify in Seaborn or Matplotlib the color increments of heat-map color scale. For instance, for data-frame that contains normalized values between 0-1, to specify 100,discrete, color increments so each value is distinguished from other values?

Thank you in advance

Answer 1

There are two principle approaches to discetize a heatmap into n colors:

1. Supply the data rounded to the n values.
2. Use a discrete colormap.

The following code shows those two options.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

x, y = np.meshgrid(range(15),range(6))
v = np.random.rand(len(x.flatten()))
df = pd.DataFrame({"x":x.flatten(), "y":y.flatten(),"value":v})

df = df.pivot(index="y", columns="x", values="value")

n = 4.


fig, (ax0, ax, ax2) = plt.subplots(nrows=3)

### original
im0 = ax0.imshow(df.values, cmap="viridis", vmin=0, vmax=1)
ax0.set_title("original")

### Discretize array
arr = np.floor(df.values * n)/n
im = ax.imshow(arr, cmap="viridis", vmin=0, vmax=1)
ax.set_title("discretize values")

### Discretize colormap
cmap = plt.cm.get_cmap("viridis", n)
im2 = ax2.imshow(df.values, cmap=cmap, vmin=0, vmax=1 )
ax2.set_title("discretize colormap")


#colorbars
fig.colorbar(im0, ax=ax0)
fig.colorbar(im, ax=ax)
fig.colorbar(im2, ax=ax2, ticks=np.arange(0,1,1./n), )
plt.tight_layout()
plt.show()