NumPy中两个数组的矩阵乘积


要找到两个数组的矩阵乘积,请在Python NumPy中使用**numpy.matmul()**方法。如果两个参数都是二维的,则它们像传统的矩阵一样相乘。返回输入的矩阵乘积。只有当x1、x2都是一维向量时,这才是标量。

out是一个将结果存储其中的位置。如果提供,则其形状必须与签名(n,k),(k,m)->(n,m)匹配。如果没有提供或为None,则返回一个新分配的数组。

步骤

首先,导入所需的库:

import numpy as np

创建两个二维数组:

arr1 = np.array([[5, 7], [10, 15]])
arr2 = np.array([[11, 12], [19, 20]])

显示数组:

print("Array 1...
", arr1) print("
Array 2...
", arr2)

获取数组的类型:

print("
Our Array 1 type...
", arr1.dtype) print("
Our Array 2 type...
", arr2.dtype)

获取数组的维度:

print("
Our Array 1 Dimensions...
",arr1.ndim) print("
Our Array 2 Dimensions...
",arr2.ndim)

获取数组的形状:

print("
Our Array 1 Shape...
",arr1.shape) print("
Our Array 2 Shape...
",arr2.shape)

要找到两个数组的矩阵乘积,请在Python NumPy中使用numpy.matmul()方法。如果两个参数都是二维的,则它们像传统的矩阵一样相乘:

print("
Result (matrix product)...
",np.matmul(arr1, arr2))

示例

import numpy as np

# Create two 2D arrays
arr1 = np.array([[5, 7], [10, 15]])
arr2 = np.array([[11, 12], [19, 20]])

# Display the arrays
print("Array 1...
", arr1) print("
Array 2...
", arr2) # Get the type of the arrays print("
Our Array 1 type...
", arr1.dtype) print("
Our Array 2 type...
", arr2.dtype) # Get the dimensions of the Arrays print("
Our Array 1 Dimensions...
",arr1.ndim) print("
Our Array 2 Dimensions...
",arr2.ndim) # Get the shape of the Arrays print("
Our Array 1 Shape...
",arr1.shape) print("
Our Array 2 Shape...
",arr2.shape) # To find the matrix product of two arrays, use the numpy.matmul() method in Python Numpy # If both arguments are 2-D they are multiplied like conventional matrices. print("
Result (matrix product)...
",np.matmul(arr1, arr2))

输出

Array 1...
[[ 5 7]
[10 15]]

Array 2...
[[11 12]
[19 20]]

Our Array 1 type...
int64

Our Array 2 type...
int64

Our Array 1 Dimensions...
2

Our Array 2 Dimensions...
2

Our Array 1 Shape...
(2, 2)

Our Array 2 Shape...
(2, 2)

Result (matrix product)...
[[188 200]
[395 420]]

更新于:2022年2月7日

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