Python中的矩阵操作-yiteyi-C++库

在python中，矩阵可以实现为2D 列表或二维阵列。从后者形成矩阵，提供了在矩阵中执行各种操作的附加功能。这些行动和大堆是“模块中的定义” 努比 “.

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矩阵运算：

1.添加（）：- 此功能用于执行以下操作： 元素矩阵加法 .

2.减法（）：- 此功能用于执行以下操作： 元素矩阵减法 .

3.除法（）：- 此功能用于执行以下操作： 元素矩阵除法 .

                     # Python code to demonstrate matrix operations                   
                     # add(), subtract() and divide()                   
                             
                     # importing numpy for matrix operations                   
                     import                               numpy                   
                             
                     # initializing matrices                   
                     x                               =                               numpy.array([[                               1                               ,                               2                               ], [                               4                               ,                               5                               ]])                   
                     y                               =                               numpy.array([[                               7                               ,                               8                               ], [                               9                               ,                               10                               ]])                   
                             
                     # using add() to add matrices                   
                     print                               (                               "The element wise addition of matrix is : "                               )                   
                     print                               (numpy.add(x,y))                   
                             
                     # using subtract() to subtract matrices                   
                     print                               (                               "The element wise subtraction of matrix is : "                               )                   
                     print                               (numpy.subtract(x,y))                   
                             
                     # using divide() to divide matrices                   
                     print                               (                               "The element wise division of matrix is : "                               )                   
                     print                               (numpy.divide(x,y))                   

输出：

The element wise addition of matrix is : 
[[ 8 10]
 [13 15]]
The element wise subtraction of matrix is : 
[[-6 -6]
 [-5 -5]]
The element wise division of matrix is : 
[[ 0.14285714  0.25      ]
 [ 0.44444444  0.5       ]]

4.乘法（）：- 此功能用于执行以下操作： 元素矩阵乘法 .

5.点（）：- 此函数用于计算 矩阵乘法，而不是元素乘法 .

                     # Python code to demonstrate matrix operations                   
                     # multiply() and dot()                   
                             
                     # importing numpy for matrix operations                   
                     import                               numpy                   
                             
                     # initializing matrices                   
                     x                               =                               numpy.array([[                               1                               ,                               2                               ], [                               4                               ,                               5                               ]])                   
                     y                               =                               numpy.array([[                               7                               ,                               8                               ], [                               9                               ,                               10                               ]])                   
                             
                     # using multiply() to multiply matrices element wise                   
                     print                               (                               "The element wise multiplication of matrix is : "                               )                   
                     print                               (numpy.multiply(x,y))                   
                             
                     # using dot() to multiply matrices                   
                     print                               (                               "The product of matrices is : "                               )                   
                     print                               (numpy.dot(x,y))                   

输出：

The element wise multiplication of matrix is : 
[[ 7 16]
 [36 50]]
The product of matrices is : 
[[25 28]
 [73 82]]

6.sqrt（）：- 此函数用于计算 每个元素的平方根 《黑客帝国》。

7.总和（x轴）：- 此函数用于 将矩阵中的所有元素相加 .可选的“axis”参数计算 轴为0时的列和 和 行和如果轴是1 .

8.“T”：- 这个论点被用来转置指定的矩阵。

                     # Python code to demonstrate matrix operations                   
                     # sqrt(), sum() and "T"                   
                             
                     # importing numpy for matrix operations                   
                     import                               numpy                   
                             
                     # initializing matrices                   
                     x                               =                               numpy.array([[                               1                               ,                               2                               ], [                               4                               ,                               5                               ]])                   
                     y                               =                               numpy.array([[                               7                               ,                               8                               ], [                               9                               ,                               10                               ]])                   
                             
                     # using sqrt() to print the square root of matrix                   
                     print                               (                               "The element wise square root is : "                               )                   
                     print                               (numpy.sqrt(x))                   
                             
                     # using sum() to print summation of all elements of matrix                   
                     print                               (                               "The summation of all matrix element is : "                               )                   
                     print                               (numpy.                               sum                               (y))                   
                             
                     # using sum(axis=0) to print summation of all columns of matrix                   
                     print                               (                               "The column wise summation of all matrix  is : "                               )                   
                     print                               (numpy.                               sum                               (y,axis                               =                               0                               ))                   
                             
                     # using sum(axis=1) to print summation of all columns of matrix                   
                     print                               (                               "The row wise summation of all matrix  is : "                               )                   
                     print                               (numpy.                               sum                               (y,axis                               =                               1                               ))                   
                             
                     # using "T" to transpose the matrix                   
                     print                               (                               "The transpose of given matrix is : "                               )                   
                     print                               (x.T)                   

输出：

The element wise square root is : 
[[ 1.          1.41421356]
 [ 2.          2.23606798]]
The summation of all matrix element is : 
34
The column wise summation of all matrix  is : 
[16 18]
The row wise summation of all matrix  is : 
[15 19]
The transpose of given matrix is : 
[[1 4]
 [2 5]]

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