📜  使用 NumPy 计算给定矩阵的条件数

📅  最后修改于: 2022-05-13 01:55:38.825000             🧑  作者: Mango

使用 NumPy 计算给定矩阵的条件数

在本文中,我们将使用 NumPy 包的 cond()函数来计算给定矩阵的条件数。 cond() 是 NumPy 包中线性代数模块的函数。

句法:

numpy.linalg.cond(x, p=None)

示例 1: 2X2 矩阵的条件数

Python3
# Importing library
import numpy as np
  
# Creating a 2X2 matrix
matrix = np.array([[4, 2], [3, 1]])
  
print("Original matrix:")
print(matrix)
  
# Output
result =  np.linalg.cond(matrix)
  
print("Condition number of the matrix:")
print(result)


Python3
# Importing library
import numpy as np
  
# Creating a 3X3 matrix
matrix = np.array([[4, 2, 0], [3, 1, 2], [1, 6, 4]])
  
print("Original matrix:")
print(matrix)
  
# Output
result =  np.linalg.cond(matrix)
  
print("Condition number of the matrix:")
print(result)


Python3
# Importing library
import numpy as np
  
# Creating a 4X4 matrix
matrix = np.array([[4, 1, 4, 2], [3, 1, 2, 0], 
                   [3, 5, 7 ,1], [0, 6, 8, 4]])
  
print("Original matrix:")
print(matrix)
  
# Output
result =  np.linalg.cond(matrix)
  
print("Condition number of the matrix:")
print(result)


输出:

Original matrix:
[[4 2]
 [3 1]]
Condition number of the matrix:
14.933034373659256

示例 2: 3X3 矩阵的条件数

Python3

# Importing library
import numpy as np
  
# Creating a 3X3 matrix
matrix = np.array([[4, 2, 0], [3, 1, 2], [1, 6, 4]])
  
print("Original matrix:")
print(matrix)
  
# Output
result =  np.linalg.cond(matrix)
  
print("Condition number of the matrix:")
print(result)

输出:

Original matrix:
[[4 2 0]
 [3 1 2]
 [1 6 4]]
Condition number of the matrix:
5.347703616656448

示例 3: 4X4 矩阵的条件数

Python3

# Importing library
import numpy as np
  
# Creating a 4X4 matrix
matrix = np.array([[4, 1, 4, 2], [3, 1, 2, 0], 
                   [3, 5, 7 ,1], [0, 6, 8, 4]])
  
print("Original matrix:")
print(matrix)
  
# Output
result =  np.linalg.cond(matrix)
  
print("Condition number of the matrix:")
print(result)

输出:

Original matrix:
[[4 1 4 2]
 [3 1 2 0]
 [3 5 7 1]
 [0 6 8 4]]
Condition number of the matrix:
57.34043866386226