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 "fro" set as a parameter is the Frobenius 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 in Python Numpy −
print("\nResult...\n",LA.norm(arr, 'fro'))
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, 'fro'))
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... 7.745966692414834