NumPy中数组和矩阵的基本运算

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数组运算

数组的加减乘除:

import numpy as np

# 一维数组的加减乘除:
a1 = np.array([1,2,3,4])
b1 = np.array([4,3,2,1])

s1 = a1 + b1   # s1的值为array([5, 5, 5, 5])
d1 = a1 - b1   # d1的值为array([-3, -1,  1,  3])
p1 = a1 * b1   # p1的值为array([4, 6, 6, 4])
q1 = a1 / b1   # q1的值为array([0.25,0.66666667,1.5 ,4.])


# 二维数组的加减乘除:
a2 = np.array([[2,3,4],[1,2,5]])
b2 = np.array([[1,2,3],[2,3,4]])

s2 = a2 + b2   # s2的值为array([[3, 5, 7],[3, 5, 9]])
d2 = a2 - b2   # d2的值为array([[ 1,  1,  1],[-1, -1,  1]])
p2 = a2 * b2   # p2的值为array([[ 2,  6, 12],[ 2,  6, 20]])
q2 = a2 / b2   # q2的值为array([[2.,1.5,1.33333333],[0.5 ,0.66666667,1.25]])

数组的点积:

# 一维数组的点积:
a3 = np.array([1,2,3,4])
b3 = np.array([2,3,4,5])
dp1 = np.dot(a3,b3)   # dp1的值为40
dp2 = a3 @ b3         # dp2的值为40
# 运算符@等价于点积运算函数np.dot


# 二维数组的点积:
a4 = np.array([[1,2,3],[2,3,4]])
b4 = np.array([[1,2],[2,5],[0,1]])
dp3 = np.dot(a4,b4)   # dp3的值为array([[ 5, 15],[ 8, 23]])
dp4 = a4 @ b4         # dp4的值为array([[ 5, 15],[ 8, 23]])
# 运算符@等价于点积运算函数np.dot

# 二维数组与一维数组的点积:
a5 = np.array([[1,2,3],[2,3,4]])
b5 = np.array([1,2,3])
dp5 = np.dot(a5,b5)   # dp5的值为array([14, 20])
dp6 = a5 @ b5         # dp6的值为array([14, 20])
# 运算符@等价于点积运算函数np.dot

矩阵运算

矩阵的乘法:

a6 = np.matrix([[1,2,3],[1,2,1]])
b6 = np.matrix([[1,2],[3,4],[2,3]])
p3 = a6 * b6         # p3的值为matrix([[13, 19],[ 9, 13]])
p4 = np.dot(a6,b6)   # p4的值为matrix([[13, 19],[ 9, 13]])
p5 = a6 @ b6         # p5的值为matrix([[13, 19],[ 9, 13]])
# 两个矩阵A(m×n)和B(n×k)相乘时,矩阵A的列数必须与矩阵B的行数相同,此时运算符*、@和点乘函数np.dot()三者是等价的

PS:本文为博主原创文章,转载请注明出处。

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