for: Project-1 (UCS654) submitted by: Chhavi Dhankhar Roll no: 102103605 Group: 3CO22
Topsis-Chhavi-102103605 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).
Use the package manager pip to install topsis.
pip install Topsis-Chhavi-102103605Enter 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 (+,-), and followed by path of the output csv file.
Topsis sample.csv "1,1,1,1" "+,-,+,+" output.csv
or vectors can be entered without " "
Topsis sample.csv 1,1,1,1 +,-,+,+ output.csv
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
A csv file showing data for different mobile handsets having varying features.
| Model | Storage (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 = [ + , + , - , + ]
Topsis sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output.csv
TOPSIS RESULTS
| Model | Storage (in gb) | Camera (in MP) | Price (in $) | Looks (out of 5) | P-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 |
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. All the categorical column are encoded to numerical values for processing.