Python 中的矩阵操作

我们可以使用 Numpy 库轻松地在 Python 中执行矩阵操作。NumPy 是一个 Python 包。它代表“数值 Python”。它是一个由多维数组对象和一系列用于处理数组的例程组成的库。使用 NumPy，可以对数组执行数学和逻辑运算。

安装和导入 Numpy

要安装 Numpy，请使用 pip −

pip install numpy

导入 Numpy −

import numpy

加、减、乘、除矩阵

我们将使用以下 Numpy 方法来进行矩阵操作 −

  • numpy.add() − 加两个矩阵

  • numpy.subtract() − 减去两个矩阵

  • numpy.divide() − 除以两个矩阵

  • numpy.multiply() − 乘以两个矩阵

我们现在来看看代码 −

示例

Open Compiler
import numpy as np

# Two matrices
mx1 = np.array([[5, 10], [15, 20]])
mx2 = np.array([[25, 30], [35, 40]])

print("Matrix1 =\n",mx1)
print("\nMatrix2 =\n",mx2)

# The addition() is used to add matrices
print ("\nAddition of two matrices: ")
print (np.add(mx1,mx2))

# The subtract() is used to subtract matrices
print ("\nSubtraction of two matrices: ")
print (np.subtract(mx1,mx2))

# The divide() is used to divide matrices
print ("\nMatrix Division: ")
print (np.divide(mx1,mx2))

# The multiply()is used to multiply matrices
print ("\nMultiplication of two matrices: ")
print (np.multiply(mx1,mx2))

输出

Matrix1 =
 [[ 5 10]
 [15 20]]

Matrix2 =
[[25 30]
 [35 40]]

Addition of two matrices:
[[30 40]
 [50 60]]

Subtraction of two matrices:
[[-20 -20]
 [-20 -20]]

Matrix Division:
[[0.2 0.33333333]
 [0.42857143 0.5 ]]

Multiplication of two matrices:
[[125 300]
 [525 800]]

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矩阵元素求和

使用 sum() 方法来求和 −

示例

Open Compiler
import numpy as np

# A matrix
mx = np.array([[5, 10], [15, 20]])

print("Matrix =\n",mx)

print ("\nThe summation of elements=")
print (np.sum(mx))

print ("\nThe column wise summation=")
print (np.sum(mx,axis=0))

print ("\nThe row wise summation=")
print (np.sum(mx,axis=1))

输出

Matrix =
 [[ 5 10]
 [15 20]]

The summation of elements=
50

The column wise summation=
[20 30]

The row wise summation=
[15 35]

转置矩阵

使用 .T 属性来求矩阵的转置 −

示例

Open Compiler
import numpy as np

# A matrix
mx = np.array([[5, 10], [15, 20]])

print("Matrix =\n",mx)

print ("\nThe Transpose =")
print (mx.T)

输出

Matrix =
 [[ 5 10]
 [15 20]]

The Transpose =
[[ 5 15]
 [10 20]]

更新于： 2022 年 8 月 11 日

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