Topsis-Prisha-102116052 0.0.1

TOPSIS Application

Topsis-Prisha-102116052

for: Project-1 (UCS654)

submitted by: Prisha Sawhney

Roll no: 102116052

Group: 3CS10

Topsis-Prisha-102116052 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-Prisha-102116052.

pip install Topsis-Prisha-102116052

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 (+,-)

topsis sample.csv "1,1,1,1" "+,-,+,+"

or vectors can be entered without " "

topsis sample.csv 1,1,1,1 +,-,+,+

But the second representation does not provide for inadvertent spaces between vector values. So, if the input string contains spaces, make sure to enclose it between double quotes (" ").

To view usage help, use

topsis /h

Example

sample.csv

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

| Model | Storage space(in gb) | Camera(in MP)| Price(in $) | Looks(out of 5) |

| :----: |:--------------------:|:------------:|:------------:|:---------------:|

| 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 sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+"

output:

      TOPSIS RESULTS

-----------------------------



    P-Score  Rank

1  0.534277     3

2  0.308368     5

3  0.691632     1

4  0.534737     2

5  0.401046     4