Matplotlib-使用for循环绘制3D

Question

I want to plot several 3D points with matplotlib. My coordinates are stored in 2D arrays because i got multiple cases and so i would like to plot all the cases in a same 3D plot with a "for loop" but when i do that, the results appeared on different plots...

As example :

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

X = np.array([[3,2,1],[4,5,6]])
Y = np.array([[1,2,1],[2,3,4]])
Z = np.array([[10,11,12],[13,12,16]])

for i in range(0,X.shape[0]):

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

    ax.scatter(X[i,:], Y[i,:], Z[i,:], c='r', marker='o')

    ax.set_xlabel('Z')
    ax.set_ylabel('X')
    ax.set_zlabel('Y')

    plt.show()

Answer 1

You create a new figure each iteration and plot it each iteration. Also you always create the first suplot of a 1x1 subplot-grid.

You probably want a x.shape[0] x 1 grid or 1 x x.shape[0] grid:

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

X = np.array([[3,2,1],[4,5,6]])
Y = np.array([[1,2,1],[2,3,4]])
Z = np.array([[10,11,12],[13,12,16]])

# Create figure outside the loop
fig = plt.figure()

for i in range(0,X.shape[0]):

    # Add the i+1 subplot of the x.shape[0] x 1 grid
    ax = fig.add_subplot(X.shape[0], 1, i+1, projection='3d')

    ax.scatter(X[i,:], Y[i,:], Z[i,:], c='r', marker='o')

    ax.set_xlabel('Z')
    ax.set_ylabel('X')
    ax.set_zlabel('Y')
# Show it outside the loop
plt.show()

---

EDIT:

If you want to plot them all into the same plot use:

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.set_xlabel('Z')
ax.set_ylabel('X')
ax.set_zlabel('Y')

for i in range(0,X.shape[0]):
    # Only do the scatter inside the loop
    ax.scatter(X[i,:], Y[i,:], Z[i,:], c='r', marker='o')

plt.show()