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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

Metadata

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