semvec/pypi-packages huggingface dataset:
TOPSIS-Prerit-102217030 1.0.2
A Python package for performing TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis.
License: MIT
Requires Python: >=3.7
Keywords: topsis mcdm multi-criteria decision-making ranking analysis

# TOPSIS Implementation

This package provides a Python implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for multi-criteria decision analysis.

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## Features
- **Ease of Use**: Simple and clear implementation of the TOPSIS algorithm.
- **Weighted Decision Making**: Allows users to define weights for each criterion.
- **Impact Analysis**: Accounts for both positive and negative impacts of criteria.
- **Command-Line Interface**: Execute TOPSIS directly from the terminal with input and output files.

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## Installation

To install the package, use:

pip install TOPSIS_Prerit_102217030


## Usage
Run the TOPSIS analysis using the command-line interface:

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>

Example
Suppose you have a CSV file data.csv containing a decision matrix where:

The first column is the identifier for alternatives.
The subsequent columns contain numeric data for each criterion.

If you want to apply TOPSIS with weights [1, 1, 1, 2] and impacts [+, +, -, +], use:
python topsis data.csv "1,1,1,2" "+,+,-,+" result.csv

This will generate a result file result.csv with the calculated TOPSIS scores and rankings.
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