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python-matplotlibHow to plot 3D heatmap


Instead of using imshow() we could use scatter() method to plot 3D heatmap:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from pylab import *
  
x = np.random.randint(low=100, high=500, size=(50,))
y = np.random.randint(low=300, high=500, size=(50,))
z = np.random.randint(low=200, high=500, size=(50,))

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

color_map = cm.ScalarMappable(cmap=cm.Reds_r)
clr = [x + y + z]
color_map.set_array(clr)

img = ax.scatter(x, y, z, s=200, color='red')
plt.colorbar(color_map)

plt.show()ctrl + c
import matplotlib.pyplot as plt

loads Matplotlib module to use plotting capabilities

import numpy as np

load Numpy module for Python

np.random.randint

generates random array based on specified paras (50 elements in our case)

.add_subplot

create sub chart

cm.ScalarMappable

create color map to use for points

.set_array(

apply our values (sum of x/y/z coordinates for each point) to color map

.scatter(

plots a point chart

.colorbar(

draw color bar based on our data

.show()

render chart in a separate window


How to plot 3D heatmap, python matplotlib

Usage example

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from pylab import *

x = np.random.randint(low=100, high=500, size=(50,))
y = np.random.randint(low=300, high=500, size=(50,))
z = np.random.randint(low=200, high=500, size=(50,))

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

color_map = cm.ScalarMappable(cmap=cm.Reds_r)
clr = [x + y + z]
color_map.set_array(clr)

img = ax.scatter(x, y, z, s=200, color='red')
plt.colorbar(color_map)

plt.show()