How to display a 3D plot in Python?

Question

I have the following code segment, but when I run it I only get a blank white screen and the plot is not displayed. I'm using Python 3.10.9. Any ideas about the issue?:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
def np_bivariate_normal_pdf(domain, mean, variance):
 X = np.arange(-domain+mean, domain+mean, variance)
 Y = np.arange(-domain+mean, domain+mean, variance)
 X, Y = np.meshgrid(X, Y)
 R = np.sqrt(X**2 + Y**2)
 Z = ((1. / np.sqrt(2 * np.pi)) * np.exp(-.5*R**2))
 return X+mean, Y+mean, Z
def plt_plot_bivariate_normal_pdf(x, y, z):
 fig = plt.figure(figsize=(12, 6))
 ax = Axes3D(fig)
 ax.plot_surface(x, y, z,
 cmap=cm.coolwarm,
 linewidth=0,
 antialiased=True)
 ax.set_xlabel('x')
 ax.set_ylabel('y')
 ax.set_zlabel('z')
 plt.show()
def main():
 plt_plot_bivariate_normal_pdf(*np_bivariate_normal_pdf(4, 0, .25))
if __name__ == '__main__':
 main()

Answer 1

ax = Axes3D(fig) was how to create 3D axes in Matplotlib prior to version 1.0.0. Since then, use fig.add_subplot(111, projection='3d'). See here.

Full code:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
def np_bivariate_normal_pdf(domain, mean, variance):
 X = np.arange(-domain+mean, domain+mean, variance)
 Y = np.arange(-domain+mean, domain+mean, variance)
 X, Y = np.meshgrid(X, Y)
 R = np.sqrt(X**2 + Y**2)
 Z = ((1. / np.sqrt(2 * np.pi)) * np.exp(-.5*R**2))
 return X+mean, Y+mean, Z
def plt_plot_bivariate_normal_pdf(x, y, z):
 fig = plt.figure(figsize=(12, 6))
 ax = fig.add_subplot(111, projection='3d')
 ax.plot_surface(x, y, z,
 cmap=cm.coolwarm,
 linewidth=0,
 antialiased=True)
 ax.set_xlabel('x')
 ax.set_ylabel('y')
 ax.set_zlabel('z')
 plt.show()
def main():
 plt_plot_bivariate_normal_pdf(*np_bivariate_normal_pdf(4, 0, .25))
if __name__ == '__main__':
 main()

gives

enter image description here