matplot_lib_examples.py

# -*- coding: utf-8 -*-
"""matplot3d_examples

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1Zy_tYU5LXxJuc44AG_4GO9-2ZfVhFMnK
"""

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt

# Commented out IPython magic to ensure Python compatibility.
# %matplotlib inline

from mpl_toolkits.mplot3d import axes3d

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

# load some test data for demonstration and plot a wireframe
X, Y, Z = axes3d.get_test_data(0.1)
ax.plot_wireframe(X, Y, Z, rstride=5, cstride=5)

angle = 30
ax.view_init(30, angle)
plt.draw()

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

x = [1, 2, 3]
y = [1, 1, 1]
z = [7, 8, 9]
ax.plot(x, y, z)

import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)


def randrange(n, vmin, vmax):
    '''
    Helper function to make an array of random numbers having shape (n, )
    with each number distributed Uniform(vmin, vmax).
    '''
    return (vmax - vmin)*np.random.rand(n) + vmin

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

n = 100

# For each set of style and range settings, plot n random points in the box
# defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].
for m, zlow, zhigh in [('o', -50, -25), ('^', -30, -5)]:
    xs = randrange(n, 23, 32)
    ys = randrange(n, 0, 100)
    zs = randrange(n, zlow, zhigh)
    ax.scatter(xs, ys, zs, marker=m)

angle = 0
ax.view_init(30, angle)

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

plt.show()

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

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure()
ax = fig.gca(projection='3d')
theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
z = np.linspace(-2, 2, 100)
r = z**2 + 1
x = r * np.sin(theta)
y = r * np.cos(theta)
ax.plot(x, y, z, label='parametric curve')
ax.legend()

plt.show()

# https://jakevdp.github.io/PythonDataScienceHandbook/04.12-three-dimensional-plotting.html

ax = plt.axes(projection='3d')

# Data for a three-dimensional line
zline = np.linspace(0, 15, 1000)
xline = np.sin(zline)
yline = np.cos(zline)
ax.plot3D(x, y, z, 'red',  marker = 'o')

# Data for three-dimensional scattered points
zdata = 15 * np.random.random(100)
xdata = np.sin(zdata) + 0.1 * np.random.randn(100)
ydata = np.cos(zdata) + 0.1 * np.random.randn(100)
ax.scatter3D(xdata, ydata, zdata, c=zdata, cmap='Greens', s = 300);