Create a scatter plot. Argument Description xs, ys Positions of data points. zs Either an array of the same length as xs and ys or a single value to place all points in the same plane. Default is 0. zdir Which direction to use as z (‘x’, ‘y’ or ‘z’) when plotting a 2D set. s size in points^2. It is a scalar or an array of the same length as x and y. c a color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however.
markdown matplotlib绘制三维曲面和散点图
更多例子https://matplotlib.org/gallery.html
曲面图
```
# -*- coding: utf-8 -*-
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
# 具体函数方法可用 help(function) 查看，如：help(ax.plot_surface)
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='rainbow')
plt.show()
```
散点图
```
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
data = np.random.randint(0, 255, size=[40, 40, 40])
x, y, z = data[0], data[1], data[2]
ax = plt.subplot(111, projection='3d') # 创建一个三维的绘图工程
# 将数据点分成三部分画，在颜色上有区分度
ax.scatter(x[:10], y[:10], z[:10], c='y') # 绘制数据点
ax.scatter(x[10:20], y[10:20], z[10:20], c='r')
ax.scatter(x[30:40], y[30:40], z[30:40], c='g')
ax.set_zlabel('Z') # 坐标轴
ax.set_ylabel('Y')
ax.set_xlabel('X')
plt.show()
```
```
# -*- coding: utf-8 -*-
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-100, 100, 1)
Y = np.arange(-100, 100, 1)
X, Y = np.meshgrid(X, Y)
Z = 50
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='rainbow')
data = np.random.randint(-100, 100, size=[20, 20, 20])
data1 = np.random.randint(-100, 0, size=[20, 20, 20])
data2 = np.random.randint(0, 100, size=[20, 20, 20])
x1, y1 = data[0], data[1]
z1 = data1[2]
x2, y2 = data[0], data[1]
z2 = data2[2]
ax.scatter(x1[:10], y1[:10], z1[:10], c='y')
ax.scatter(x2[10:20], y2[10:20], z2[10:20], c='r')
plt.show()
```