Topsis-Anjani-102303480 1.0.0

TOPSIS implementation in Python

Topsis-Anjani-102303480

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) implementation in Python for multi-criteria decision analysis.

Description

TOPSIS is a multi-criteria decision analysis method that ranks alternatives based on their similarity to the ideal solution. This package provides a simple command-line tool to perform TOPSIS analysis on CSV data files.

Installation

Install the package using pip:

pip install Topsis-Anjani-102303480

Usage

After installation, you can use the topsis command from anywhere in your terminal:

topsis <InputDataFile> <Weights> <Impacts> <OutputResultFileName>

Parameters

• InputDataFile: Path to the input CSV file
• Weights: Comma-separated weights for each criterion (e.g., "1,1,1,2")
• Impacts: Comma-separated impacts for each criterion ('+' for maximize, '-' for minimize)
• OutputResultFileName: Path for the output CSV file

Example

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

Input File Format

The input CSV file must follow this structure:

• First column: Names of alternatives/options
• Remaining columns: Numeric values for each criterion
• Minimum: 3 columns (1 name column + at least 2 criteria)

Example Input (data.csv)

Model,Price,Storage,Camera,Battery
P1,250,64,12,4000
P2,200,32,8,3500
P3,300,128,16,4500
P4,275,64,12,4200
P5,225,32,16,3800

Output Format

The output CSV includes all original columns plus:

• Topsis Score: Score between 0 and 1 (higher is better)
• Rank: Ranking based on TOPSIS score (1 is best)

Example Output (result.csv)

Model,Price,Storage,Camera,Battery,Topsis Score,Rank
P3,300,128,16,4500,0.691,1
P4,275,64,12,4200,0.535,2
P1,250,64,12,4000,0.534,3
P5,225,32,16,3800,0.401,4
P2,200,32,8,3500,0.308,5