numpy的生成网格矩阵 meshgrid()

numpy模块中的meshgrid函数用来生成网格矩阵，最简单的网格矩阵为二维矩阵

meshgrid函数可以接受 x1, x2,..., xn 等 n 个一维向量，生成 N-D 矩阵。

1 基本语法

meshgrid(*xi, **kwargs)

参数：

xi - x1, x2,..., xn : array_like

返回值：

X1, X2,..., XN : ndarray

2 示例(二维网格)

2.1 一个参数时

import numpy as np
a = [1,2,3]
b = np.meshgrid(a)
print(b) # [array([1, 2, 3])]

当只有一个参数时，返回值也只有一个 b ，若写两个返回值  b, c = np.meshgrid(a) 则会报错。

2.2 两个参数时

2.2.1 两个参数长度一致时

示例1 

import numpy as np

a = [1,2,3]
b = [9,8,7]

c, d = np.meshgrid(a,b)

print(c)
print('-'*10)
print(d)

运行

[[1 2 3]
[1 2 3]
[1 2 3]]
----------
[[9 9 9]
[8 8 8]
[7 7 7]]

当两个参数长度一致时（如长度为 N ），则生成 N * N 维矩阵

示例2 

交换两参数的顺序

import numpy as np

a = [1,2,3]
b = [9,8,7]

c, d = np.meshgrid(b,a)

print(c)
# [[9 8 7]
#  [9 8 7]
#  [9 8 7]]
print(d)
# [[1 1 1]
#  [2 2 2]
#  [3 3 3]]

交换两个参数顺序后，输出结果发生了变化。

示例3

当返回值值是两个或两个以上参数时，也可用一个参数来接受。

import numpy as np
a = [1,2,3]
b = [9,8,7]
c = np.meshgrid(a,b)
print(c)
# 下面是打印出的结果+
# [array([[1, 2, 3],
#        [1, 2, 3],
#        [1, 2, 3]]), array([[9, 9, 9],
#        [8, 8, 8],
#        [7, 7, 7]])]

2.2.2 两个参数长度不一致时

import numpy as np
a = [1,2,3]
b = [9,8]
c, d = np.meshgrid(a,b)
print(c)
# [[1 2 3]
#  [1 2 3]]
print(d)
# [[9 9 9]
#  [8 8 8]]

这是一个 2 * 3（2 行 3 列）

相当于 b 由 行向量 变成了 列向量。

import numpy as np
a = [1,2,3]
b = [9,8]
c, d = np.meshgrid(b, a)
print(c)
# [[9 8]
#  [9 8]
#  [9 8]]
print(d)
# [[1 1]
#  [2 2]
#  [3 3]]

3 示例（三维网格）

import numpy as np

a = [1,2,3]
b = [4,5,6]
c = [7,8,9]

x, y, z = np.meshgrid(a, b, c)

print(x)
# [[[1 1 1]
#   [2 2 2]
#   [3 3 3]]
#
#  [[1 1 1]
#   [2 2 2]
#   [3 3 3]]
#
#  [[1 1 1]
#   [2 2 2]
#   [3 3 3]]]
print(y)
# [[[4 4 4]
#   [4 4 4]
#   [4 4 4]]
#
#  [[5 5 5]
#   [5 5 5]
#   [5 5 5]]
#
#  [[6 6 6]
#   [6 6 6]
#   [6 6 6]]]
print(z)
# [[[7 8 9]
#   [7 8 9]
#   [7 8 9]]
#
#  [[7 8 9]
#   [7 8 9]
#   [7 8 9]]
#
#  [[7 8 9]
#   [7 8 9]
#   [7 8 9]]]