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 + cgithub

`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()

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python-matplotlibHow to plot 3D heatmap

Usage example

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