topsis-shubhaan-102203456 1.2.0

A Python package for the TOPSIS method

TOPSIS Package

The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) package is a Python library for multi-criteria decision-making. It helps users rank alternatives based on their proximity to the ideal solution and their distance from the worst-case solution.

Installation

You can install the package using pip:

pip install topsis

Usage

The package provides a simple interface for applying the TOPSIS method. Follow these steps:

Import the Package

from topsis import topsis

Prepare Input Data

You need the following inputs:

1. A decision matrix (a 2D list or NumPy array) where each row represents an alternative and each column represents a criterion.
2. A list of weights for each criterion.
3. A list of impacts for each criterion (either '+' for positive impact or '-' for negative impact).

Example Input:

decision_matrix = [
    [250, 16, 12, 5],
    [200, 20, 15, 6],
    [300, 18, 10, 8],
    [275, 25, 16, 7]
]
weights = [0.25, 0.25, 0.25, 0.25]
impacts = ['+', '+', '-', '+']

Run the TOPSIS Method

Call the topsis function with the prepared inputs:

rankings = topsis(decision_matrix, weights, impacts)

The rankings variable will contain the final rankings of the alternatives.

Full Example

from topsis import topsis

decision_matrix = [
    [250, 16, 12, 5],
    [200, 20, 15, 6],
    [300, 18, 10, 8],
    [275, 25, 16, 7]
]
weights = [0.25, 0.25, 0.25, 0.25]
impacts = ['+', '+', '-', '+']

rankings = topsis(decision_matrix, weights, impacts)
print("Rankings:", rankings)

Output

The output will be a list containing the rankings of the alternatives, with 1 representing the best alternative.

Example Output:

Rankings: [2, 3, 1, 4]

Features

• Simple interface for applying the TOPSIS method.
• Supports any number of alternatives and criteria.
• Customizable weights and impacts.

Testing

Run the unit tests to verify the functionality:

python -m unittest discover tests

License

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