Topsis-Jashan-102003206 1.0.0

Topsis package for Multiple Criteria Decision Making problems(MCDM) problems

TOPSIS SCORE EVALUATOR

Project-1 (UCS654)

Submitted by: Jashan Arora Roll no: 102003206 Group: 3COE9

Topsis-Jashan-102003206 is a Python library for dealing with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

Installation

Use the package manager pip to install Topsis-Jashan-102003206.

pip install Topsis-Jashan-102003206

Usage

Enter csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-), followed by name of output file to be generated. It generates output csv file in the present working directory.

Syntax

topsis <input_file> <weights> <impacts> <output_file>

topsis input.csv "1,1,1,1" "+,-,+,+" result.csv

Example

Data.csv

A csv file containing input showing data for different mobile handsets having varying features.

Model	Storage space	Camera	Price	Looks
M1	16	12	250	5
M2	16	8	200	3
M3	32	16	300	4
M4	32	8	275	4
M5	16	16	225	2

weights vector = [ 0.25 , 0.25 , 0.25 , 0.25 ]

impacts vector = [ + , + , - , + ]

Input:

topsis Data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" Result.csv

Output:

Result.csv

A csv file generated by program containing output showing original data with Topsis Score and Rank columns.

Model	Storage space	Camera	Price	Looks	Topsis Score	Rank
M1	16	12	250	5	0.534277	3
M2	16	8	200	3	0.308368	5
M3	32	16	300	4	0.691632	1
M4	32	8	275	4	0.534737	2
M5	16	16	225	2	0.401046	4

Other notes

• The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So make sure the csv follows the format as shown in sample.csv.
• Make sure the csv does not contain categorical values
• Impacts must be either + or -
• Weights must be numeric only
• Weights and Impacts must be seperated only by commas (' , ')

License

MIT