import matplotlib.pyplot as plt

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()

# 将二维转换为三维的情况

axes = Axes3D(fig)

x = np.arange(-4, 4, 0.25)

y = np.arange(-4, 4, 0.25)

X, Y  = np.meshgrid(x, y)

Z = np.sin(np.sqrt(X**2 + Y**2))

# 画三维曲面图，rstride=1, cstride=1表示曲面的一个方格的位置

axes.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='rainbow')

# 画出投影， zm表示投影的方向，offset表示投影所处位置，cmap表示使用的colormap

axes.contour(X, Y, Z, zm='Z', offset=-2, cmap='rainbow')

# 扩大z轴的范围使得图看起来更加的压缩

axes.set_zlim(-2, 2)

plt.show()

# 构造坐标轴的方法1

fig = plt.figure()

# 构造了三维的坐标轴

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

plt.show()

# 构造坐标轴的方法2

figure =  plt.figure()

ax = figure.gca(projection='3d')

theta = np.linspace(-4 * np.pi, 4*np.pi, 100)

z = np.linspace(-2, 2, 100)

r = z**2 + 1

x = np.sin(theta) * r

y = np.cos(theta) * r

ax.plot(x, y, z, color='r')

plt.show()

np.random.seed(0)

# 用于生成随机点

def randrange(n, vmin, vmax):

    return (vmax-vmin)*np.random.randn(n) + vmin

fig = plt.figure()

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

n = 100

for c, m, zlow, zhigh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:

    xs = randrange(100, 23, 32)

    ys = randrange(100, 0, 100)

    zs = randrange(100, zlow, zhigh)

    ax.scatter(xs, ys, zs, marker=m, color=c)
# 进行视角的变化

ax.view_init(40, 20)

plt.show()

fig = plt.figure()

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

for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):

    xs = np.arange(20)

    ys = np.random.rand(20)
    cs = [c] * len(len(xs))

    ax.bar(xs, ys, zs=z, zdir='y', color=cs)

plt.show()