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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
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