Python 进行矩阵操作

我们可以使用Numpy库来轻松进行Python中的矩阵操作。NumPy是一个Python包。它代表’Numerical Python’。这是一个由多维数组对象和一组用于处理数组的例程组成的库。使用NumPy可以进行数组的数学和逻辑运算。

安装和导入Numpy

要安装Numpy，请使用pip −

pip install numpy

导入Numpy –

import numpy

添加、减去、除以和乘以矩阵

我们将使用以下的NumPy方法进行矩阵操作−

• numpy.add() − 添加两个矩阵

• numpy.subtract() − 减去两个矩阵

• numpy.divide() − 除以两个矩阵

• numpy.multiply() − 乘以两个矩阵

现在让我们看一下代码 −

示例

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]]

矩阵元素的求和

sum()方法用于找到求和结果-

示例

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

.T属性用于找到矩阵的转置-

示例

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]]