semvec/pypi-packages huggingface dataset:
Topsis-Prianshu-102017159 0.0.1
### Package Description

## Package to calculate TOPSIS score on a given data in csv format
This package is an implementation to calculate the topsis score on a given data. It only takes command line arguments


## Installation through PIP
```bash
pip install Topsis_Prianshu_102017159
```
## Running through Command line or terminal

```bash
python topsis <weights> <impacts> <output_file>
```
The weights has to be entered in separated by a comma
```bash
'1,1,1,1,1'
'+,+,-,+,-'
```
## Parameters/Arguments
```bash
topsis <input_file> <weights> <impacts> <output_file>
```

## Returns
Returns a pandas data frame saved in csv format in the given output file


Home-page: UNKNOWN
Author: Prianshu Jha
Author-email: pjha1_be20@thapar.edu
License: MIT
Description: UNKNOWN
Keywords: SOME,MEANINGFULL,KEYWORDS
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
matSN 0.0.1
Basic Operations For Matrices
Requires Python: >=3.7

## SNMATRICES
-------------------------------------------------------------------------------
- These Operations will work only ,if both the matrices are of same order
-----------------------------------------------------------------------------------

## Matrix_Operations: 
## MODULE NAME:operations.py

1)Getting input matrix:
Function:input_matrix(Number of rows,Number of columns)

2)Matrix Addition:
Function:matrix_addition(matrixA,matrixB)

3)Matrix Subraction
Function:matrix_subraction(matrixA,matrixB)

-4)Matrix Multiplication:
-Function:matrix_multiplication(matrixA,matrixB)

## SOURCE CODE

## MATRIX ADDITION
def matrix_addition(A,B):
    mat_addition=[]
    for i in range(len(A)):
        c=[]
        for j in range(len(B[0])):
            c.append(A[i][j]+B[i][j])
        mat_addition.append(c)
    print('Matrix Addition=')
    print(mat_addition)

## MATRIX SUBRACTION
def matrix_subraction(A,B):
    mat_subraction=[]
    for i in range(len(A)):
        c=[]
        for j in range(len(B)):
            c.append(A[i][j]-B[i][j])
        mat_subraction.append(c)
    print('Matrix Subraction=')
    print(mat_subraction)

## MATRIX MULTIPLICATION
def matrix_multiplication(A,B):
    mul_result=[]
    for i in range(len(A)):
        c=[]
        for j in range(len(B[0])):
            result=0
            for k in range(len(B)):
                result+=A[i][k]*B[k][j]
            c.append(result)
        mul_result.append(c)
    print('Matrix Multiplication=')
    print(mul_result)

## INPUT MATRIX
def input_matrix(rows,columns): 
    A=[]
    print('Enter the entries row wise:')
    a=[]
    for i in range(rows):
        a=[]
        for j in range(columns):
            a.append(int(input()))
        A.append(a)
    print('Input Matrix=')
    print(A)

##LICENSE
MIT