semvec/pypi-packages huggingface dataset:
Topsis-Aayushi-102103676 1.2.0
A Python package to calculate TOPSIS scores and rank models.
License: MIT

# 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:

```bash
pip install Topsis-Aayushi-102103676
```

## Usage

This package provides a command-line interface `topsis` that you can use directly from your terminal.

### Syntax

```bash
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:

```bash
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](LICENSE) file for details.