返回线性代数中矩阵的核范数（Nuclear Norm）的Python代码

要返回线性代数中矩阵或向量的范数，请使用Python的LA.norm()方法。第一个参数x是一个输入数组。如果axis为None，则x必须是1-D或2-D，除非ord为None。如果axis和ord都是None，则返回x.ravel的2范数。

第二个参数ord是范数的阶数。inf表示numpy的inf对象。默认值为None。将参数设置为”nuc”表示核范数。Frobenius和核范数只对矩阵定义。

步骤

首先，导入所需的库-

import numpy as np
from numpy import linalg as LA

创建一个数组 –

arr = np.array([[ -4, -3, -2], [-1, 0, 1], [2, 3, 4] ])

显示数组-

print("Our Array...\n",arr)

检查尺寸 −

print("\nDimensions of our Array...\n",arr.ndim)

获取数据类型 –

print("\nDatatype of our Array object...\n",arr.dtype)

获取形状 –

print("\nShape of our Array object...\n",arr.shape)

要在线性代数中计算矩阵或向量的范数，请使用LA.norm()方法−

print("\nResult...\n",LA.norm(arr, 'nuc'))

示例

import numpy as np
from numpy import linalg as LA

# Create an array
arr = np.array([[ -4, -3, -2],[-1, 0, 1],[2, 3, 4] ])

# Display the array
print("Our Array...\n",arr)

# Check the Dimensions
print("\nDimensions of our Array...\n",arr.ndim)

# Get the Datatype
print("\nDatatype of our Array object...\n",arr.dtype)

# Get the Shape
print("\nShape of our Array object...\n",arr.shape)

# To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy
print("\nResult...\n",LA.norm(arr, 'nuc'))

输出

Our Array...
   [[-4 -3 -2]
   [-1 0 1]
   [ 2 3 4]]

Dimensions of our Array...
2

Datatype of our Array object...
int64

Shape of our Array object...
(3, 3)

Result...
9.797958971132713