TOPSIS Application
Project description
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
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