semvec/pypi-packages huggingface dataset:
Topsis-Nipun-Garg-102003674 0.0.2
A small example package
Requires Python: >=3.6

# Topsis implemented by Nipun Garg 102003674

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)  
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

## Functionality of the Package

- Outputs the result(topsis score) and ranking of items in output.csv file you will mention in terminal or command promt
- Inputs the file path of input csv file in terminal

## Example

```
#test.py
##
type:
from Topsis_Nipun_Garg_102003674 import main
n=len(sys.argv)
inputFile= sys.argv[1]
weight=sys.argv[2]
impact=sys.argv[3]
outputFile=sys.argv[4]
# main.get_score(inputFile, weight, impact, outputFile)
```

## Usage

- Make sure you have Python installed in your system.
- Run Following command in the CMD.

```
 pip install Topsis_Nipun_Garg_102003674
```

## Run the following Script.

```
 python <Filename.py> <inputfile.csv> weight impact <outputfile.csv>
```

## Note

- I have tried to implement all the functionality, it might have some bugs also. Ignore that or please try to solve that bug.
- Rank 1 corresponds to minimum performance score and so on.
CADETMatch 0.8.16
CADETMatch is a parameter estimation and error modeling library for CADET
Requires Python: >=3.7

# CADET-Match
CADET Parameter estimation engine

This software is a work in progress. The file formats will break as changes as made.

This software is designed to do parameter estimation for CADET. The required libraries are in the README.txt file
in the CADETMatch directory.

The documentation is also a work in progress.

If you use this software in your research please give credit.
Topsis-Bandhan-102003440 1.3
Doing Evaluation of alternatives based on multiple criteria using TOPSIS method.

## Topsis:-MULTIPLE-CRITERIA DECISION MAKING

# TOPSIS

Submitted By: **BANDHAN SHER SINGH 102003440**.

Date: **23-JAN-2023**.

Description: **Evaluation of alternatives based on multiple criteria using TOPSIS method.**.

---

## What is TOPSIS?

**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution
TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution,
and greatest distance from the negative-ideal solution.

<br>

## How to install this package:

```
>>pip install Topsis_Bandhan_102003440
```

### In Command Prompt

```
>> topsis data.csv "1,1,1,2,1" "+,+,-,+,-" result.csv
```

## Input file (data.csv)

The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Attribute, Price or cost, Storage Space ,Camera,Looks.

| Fund Name | P1   | P2   | P3  | P4   | P5    |
| --------- | ---- | ---- | --- | ---- | ----- |
| M1        | 0.67 | 0.45 | 6.4 | 64.2 | 17.93 |
| M2        | 0.78 | 0.61 | 5.1 | 42.5 | 12.25 |
| M3        | 0.66 | 0.44 | 6.7 | 58.5 | 16.58 |
| M4        | 0.68 | 0.46 | 3.6 | 40.7 | 11.36 |
| M5        | 0.83 | 0.69 | 6.8 | 33   | 10.33 |
| M6        | 0.95 | 0.9  | 5.7 | 36.9 | 11.11 |
| M7        | 0.95 | 0.9  | 3.5 | 51.2 | 14.14 |
| M8        | 0.89 | 0.79 | 4.1 | 60.1 | 16.47 |

Weights (`weights`) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in `impacts`.

<br>

## Output file (result.csv)

| Fund Name | P1   | P2   | P3  | P4   | P5    | Topsis Score | Rank |
| --------- | ---- | ---- | --- | ---- | ----- | ------------ | ---- |
| M1        | 0.67 | 0.45 | 6.4 | 64.2 | 17.93 | 0.541        | 3    |
| M2        | 0.78 | 0.61 | 5.1 | 42.5 | 12.25 | 0.401        | 7    |
| M3        | 0.66 | 0.44 | 6.7 | 58.5 | 16.58 | 0.486        | 4    |
| M4        | 0.68 | 0.46 | 3.6 | 40.7 | 11.36 | 0.405        | 6    |
| M5        | 0.83 | 0.69 | 6.8 | 33   | 10.33 | 0.323        | 8    |
| M6        | 0.95 | 0.9  | 5.7 | 36.9 | 11.11 | 0.445        | 5    |
| M7        | 0.95 | 0.9  | 3.5 | 51.2 | 14.14 | 0.679        | 2    |
| M8        | 0.89 | 0.79 | 4.1 | 60.1 | 16.47 | 0.723        | 1    |

<br>
The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**