Topsis-Aayushi-102103676 1.2.0

A Python package to calculate TOPSIS scores and rank models.

TOPSIS Package

A lightweight and easy-to-use Python package for the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method.

Introduction

TOPSIS is a multi-criteria decision analysis method, which is used to find the best alternative from a set of feasible alternatives. This package provides a command-line tool to perform TOPSIS analysis on a given dataset.

Installation

Install the package from PyPI using pip:

pip install Topsis-Aayushi-102103676

Usage

This package provides a command-line interface topsis that you can use directly from your terminal.

Syntax

topsis <input_file> <weights> <impacts> <result_file>

Arguments

• <input_file>: The path to your input data file (must be a .csv or .xlsx file). The file must contain only numeric values, with the first column being the model name and the rest being the numeric criteria.
• <weights>: A comma-separated string of weights for each criterion (e.g., "1,1,1,1").
• <impacts>: A comma-separated string of impacts for each criterion, where + denotes a beneficial criterion and - denotes a non-beneficial (cost) criterion (e.g., "+,+,-,+").
• <result_file>: The name of the output file (e.g., result.csv) where the results with TOPSIS scores and ranks will be saved.

Example

Suppose you have an input file data.csv:

Model	Price	Storage	Camera	Performance
M1	250	16	12	8
M2	200	16	8	7
M3	300	32	16	9
M4	275	32	8	8

To run the TOPSIS analysis on this data, you would use the following command:

topsis data.csv "1,1,1,1" "-,+,+,+" result.csv

This will generate a result.csv file with the TOPSIS scores and ranks for each model.

License

This project is licensed under the MIT License. See the LICENSE file for details.