Topsis-Ayush-102203119 1.0.0

A Python package for implementing TOPSIS

Here’s a clear and concise example of a README.md for your TOPSIS package:

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Topsis-Ayush-102203119

A Python package for implementing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. This method is used for multi-criteria decision-making.

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Installation

Install the package using pip:

pip install Topsis-Ayush-102203119

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Usage

Command-Line Interface

After installation, you can use the topsis command to calculate rankings for your dataset.

Command Syntax

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>

• <InputDataFile>: Path to the input CSV file.
• <Weights>: Comma-separated list of weights for each criterion (e.g., 1,1,1,2).
• <Impacts>: Comma-separated list of impacts for each criterion (+ for positive, - for negative).
• <ResultFileName>: Path to save the output CSV file.

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Input File Format

• The input file must be a CSV with at least 3 columns.
• The first column should contain the names of the objects (e.g., M1, M2, ...).
• The remaining columns should contain numeric criteria values.

Example Input (data.csv):

Object,Criteria1,Criteria2,Criteria3,Criteria4
M1,250,16,12,5
M2,200,16,8,3
M3,300,32,16,4
M4,275,16,8,4
M5,225,32,16,2

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Example Usage

1. Prepare the input CSV file (e.g., data.csv).
2. Run the following command:

topsis data.csv 1,1,1,2 +,+,-,+ result.csv

3. The result will be saved in the specified output file (e.g., result.csv).

Example Output (result.csv):

Object,Criteria1,Criteria2,Criteria3,Criteria4,Topsis Score,Rank
M1,250,16,12,5,0.75,2
M2,200,16,8,3,0.45,4
M3,300,32,16,4,0.85,1
M4,275,16,8,4,0.55,3
M5,225,32,16,2,0.30,5

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Requirements

This package requires the following Python libraries:

• numpy
• pandas

These dependencies are automatically installed with the package.

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License

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

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