Skip to main content

A Python package for Matrix Operations

Project description

pymatops - A Python package for Matrix Operations

Package Status Package Status

Package Details

The pymatops package is available on the official Python Package Index (PyPi) repository. It can be installed and used in your projects by running the following command using pip

pip install pymatops

Package Operations

1. visualize - visualize a matrix

import pymatops as pmo
mat = [[1,2,3], [4,5,6], [7,8,9]]
pmo.visualize(mat)

image

2. dim - returns a tuple with the dimensions of the matrix

import pymatops as pmo
mat = [[1,2,3], [4,5,6], [7,8,9]]
print("The dimension of the matrix is ", pmo.dim(mat))

image

3. randomMatrix - returns a matrix of random dimensions with random values if the function is called with no arguments

import pymatops as pmo
print("The randomly generated matrix: ")
pmo.randomMatrix()

image

4. randomMatrix - you can pass dimensions to get a matrix of specified dimensions with random values. Both row and col dimensions are required

import pymatops as pmo
print("The random matrix of dimension 6*8 generated: ")
pmo.randomMatrix(6,8)

image

5. matSum - returns the sum of all elements in the matrix passed

import pymatops as pmo
print("The random matrix generated: ")
mat = pmo.randomMatrix(6,8) # retuns a 6*8 matrix with random values
print("The sum of the matrix: ", pmo.matSum(mat))

image

6. matAdd - returns the resultant matrix of the sum of matrix A and B

import pymatops as pmo
mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
mat1 =[[1, 2, 3], [4, 5, 6], [7, 8, 9]] # returns a 6*8 matrix with random values
print("Matrix 1:")
pmo.visualize(mat)
print("Matrix 2:")
pmo.visualize(mat1)
print("The resultant matrix of the matrix addition operation: ")
pmo.matAdd(mat, mat1)

image

7. matMul - returns the resultant matrix of the multiplication of matrix A and B

import pymatops as pmo
mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]] # matrix of dimensions 4*3
mat1 =[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] # matrix of dimensions 3*4
print("Matrix 1:")
pmo.visualize(mat)
print("Matrix 2:")
pmo.visualize(mat1)
print("The resultant matrix of the matrix multiplication operation: ")
pmo.matMul(mat, mat1)

image

8. scalarMul - returns the resultant matrix of the multiplication of matrix A with scalar c

import pymatops as pmo
mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
print("Original Matrix: ")
pmo.visualize(mat)
print("Matrix after scalar multiplication operation: ")
pmo.scalarMul(mat, 3)

image

9. transpose - returns transpose of matrix

import pymatops as pmo
mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
print("Original Matrix: ")
pmo.visualize(mat)
print("Matrix after transpose operation: ")
pmo.transpose(mat)

image

10. zeroElements - returns the number of zero elements in the matrix

import pymatops as pmo
mat = [[1, 0, 3], [0, 5, 6], [7, 8, 0], [10, 11, 12]]
print("Original Matrix: ")
pmo.visualize(mat)
print("Number of zeros in the matrix: ", end = " ")
print(pmo.zeroElements(mat))

image

11. evenCheck - returns a tuple with the first element as the number of even numbers in the matrix and the second element being the number of odd numbers in the matrix

import pymatops as pmo
mat = [[1, 0, 3], [0, 5, 6], [7, 8, 0], [10, 11, 12]]
print("Original Matrix: ")
pmo.visualize(mat)
print("Number of even numbers in the matrix: ", end = " ")
print(pmo.evenCheck(mat)[0])
print("Number of odd numbers in the matrix: ", end = " ")
print(pmo.evenCheck(mat)[1])

image

Developed by Yash Seth (c) 2022

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pymatops-1.3.0.tar.gz (4.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pymatops-1.3.0-py3-none-any.whl (4.9 kB view details)

Uploaded Python 3

File details

Details for the file pymatops-1.3.0.tar.gz.

File metadata

  • Download URL: pymatops-1.3.0.tar.gz
  • Upload date:
  • Size: 4.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.2

File hashes

Hashes for pymatops-1.3.0.tar.gz
Algorithm Hash digest
SHA256 a5dd65cb07c90aeb06f51ccd89d821dd34de23e6cca476043821223a49ca1014
MD5 8c15c45c86f1df00697e6f157471005f
BLAKE2b-256 7a510700fdb6590057302e84c6d7a955cf91df987e9f7e84d57794f622bb07fb

See more details on using hashes here.

File details

Details for the file pymatops-1.3.0-py3-none-any.whl.

File metadata

  • Download URL: pymatops-1.3.0-py3-none-any.whl
  • Upload date:
  • Size: 4.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.2

File hashes

Hashes for pymatops-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 75f1eefa772e4596d3369abc59f59cd8fc28bbba240157d68c45d5972941abe1
MD5 fe89a21c966e2716ebd6f4033c17b1d4
BLAKE2b-256 7e4a1d041cd73169b4be6adad85457397e8f5088932439f30c49719d4804f8f9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page