To return the Norm of the matrix or vector in Linear Algebra, use the LA.norm() method in Python Numpy. The 1st parameter, x is an input array. If axis is None, x must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of x.ravel will be returned.
The 2nd parameter, ord is the order of the norm. The inf means numpy’s inf object. The default is None. The "nuc" set as a parameter is the Nuclear norm. Both the Frobenius and nuclear norm orders are only defined for matrices
Steps
At first, import the required library −
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 −
print("\nResult...\n",LA.norm(arr, 'nuc'))Example
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'))Output
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