Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Compute the Moore-Penrose pseudoinverse of a stack of matrices in Python
To Compute the (Moore-Penrose) pseudo-inverse of a stack of matrices, use the numpy.linalg.pinv() method in Python. Calculate the generalized inverse of a matrix using its singular-value decomposition (SVD) and including all large singular values.
The 1st parameter, a is a Matrix or stack of matrices to be pseudo-inverted. The 2nd parameter, rcodn is cutoff for small singular values. Singular values less than or equal to rcond * largest_singular_value is set to zero. Broadcasts against the stack of matrices. The 3rd parameter, hermitian, if True, a is assumed to be Hermitian, enabling a more efficient method for finding singular values. Defaults to False.
Steps
At first, import the required libraries.
import numpy as np
Create an array using array().
arr = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
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 compute the (Moore-Penrose) pseudo-inverse of a stack of matrices, use the numpy.linalg.pinv() method in Python.
print("\nResult...\n",np.linalg.pinv(arr))Example
import numpy as np
# Create an array using array()
arr = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
# 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 Compute the (Moore-Penrose) pseudo-inverse of a stack of matrices, use the numpy.linalg.pinv() method in Python.
print("\nResult...\n",np.linalg.pinv(arr))Output
Our Array... [[[1 2] [3 4]] [[1 2] [2 1]] [[1 3] [3 1]]] Dimensions of our Array... 3 Datatype of our Array object... int64 Shape of our Array object... (3, 2, 2) Result... [[[-2. 1. ] [ 1.5 -0.5 ]] [[-0.33333333 0.66666667] [ 0.66666667 -0.33333333]] [[-0.125 0.375 ] [ 0.375 -0.125 ]]]
234 Views
