Topsis-Smarth-102497023 1.0.0

A command-line Python package to implement the TOPSIS method.

Topsis-Smarth-102497023

A Python package implementing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for Multi-Criteria Decision Making (MCDM). This package works as a Command Line Tool and generates an output CSV file containing the TOPSIS Score and Rank.

Installation

Install the package from PyPI using:

pip install Topsis-Smarth-102497023

Quick Start

Command Syntax

Once installed, you can use the topsis command directly from your terminal, following the syntax given below.

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

Parameters

The command accepts exactly 4 parameters:

Parameter	Format	Example	Description
Input file	Path string	"data.csv"	Path to your CSV file
Weights	Comma-separated string	"1,1,1,1"	Weight for each criterion
Impacts	Comma-separated string	"+,+,-,+"	+ for benefit, - for cost
Output file	Path string	"result.csv"	Where to save results

Example Execution

Grab an input csv or excel file strictly adheres to the following structure:

1. The file must have at least 3 columns- Candidate Identifier column followed by min. 2 criteria.
2. The first column must contain the names/IDs of the alternatives.
3. Criteria columns must contain only numeric values.

A sample dataset file (data1.csv) is shown below:

Model	Corr	Rseq	RMSE	Accuracy
M1	0.79	0.62	1.25	60.89
M2	0.66	0.44	2.89	63.07
M3	0.56	0.31	1.57	62.87
M4	0.82	0.67	2.68	70.19
M5	0.75	0.56	1.30	80.39

Run the following command through the terminal.

topsis data1.csv "1,1,1,1" "+,+,-,+" output_data1.csv

The output file (output_data1.csv) generated will look like this:

Model	Corr	Rseq	RMSE	Accuracy	Topsis Score	Rank
M1	0.79	0.62	1.25	60.89	0.7722	2
M2	0.66	0.44	2.89	63.07	0.2256	5
M3	0.56	0.31	1.57	62.87	0.4389	4
M4	0.82	0.67	2.68	70.19	0.5239	3
M5	0.75	0.56	1.30	80.39	0.8114	1

Sample input and output files are available in the sample_data/ folder.

Important Notes

• The command accepts exactly four parameters.
• Number of weights and impacts must match number of criteria columns.
• Impacts must be only + or -.
• Make sure the criteria columns must be numeric as mentioned earlier.
• No cell should be empty.

License

This project is licensed under the MIT License. See LICENSE for more information.

Author

Smarth Kaushal
Penultimate-Year Student, BE-CSE
Thapar Institute of Engineering and Technology, Patiala

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