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2dcollections3d.py
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48 lines (38 loc) · 1.22 KB
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"""
=======================
Plot 2D data on 3D plot
=======================
Demonstrates using ax.plot's zdir keyword to plot 2D data on
selective axes of a 3D plot.
"""
import numpy as np
import matplotlib.pyplot as plt
ax = plt.figure().add_subplot(projection='3d')
# Plot a sin curve using the x and y axes.
x = np.linspace(0, 1, 100)
y = np.sin(x * 2 * np.pi) / 2 + 0.5
ax.plot(x, y, zs=0, zdir='z', label='curve in (x, y)')
# Plot scatterplot data (20 2D points per colour) on the x and z axes.
colors = ('r', 'g', 'b', 'k')
# Fixing random state for reproducibility
np.random.seed(19680801)
x = np.random.sample(20 * len(colors))
y = np.random.sample(20 * len(colors))
c_list = []
for c in colors:
c_list.extend([c] * 20)
# By using zdir='y', the y value of these points is fixed to the zs value 0
# and the (x, y) points are plotted on the x and z axes.
ax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x, z)')
# Make legend, set axes limits and labels
ax.legend()
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
ax.set_zlim(0, 1)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
# Customize the view angle so it's easier to see that the scatter points lie
# on the plane y=0
ax.view_init(elev=20., azim=-35)
plt.show()