topsis package for MCDM problems
Project description
Topsis-Sahil-102067006
| This library has been created as a part of the assignment for UCS654. This package implements Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) for solving Multiple Criteria Decision Making(MCDM) problems.
Installation
| This package can be installed using pip package manager
pip install Topsis-Sahil-102067006
Usage
| The library provides support for a 'topsis' command which can be invoked through the command line | Input Arguments:
-
file: a file with '.csv' extension, which should only have numeric values for all features, beyond the second column. This file should have minimum three columns, otherwise an error would occur
-
weights: A numeric array, with weights value for each feature column
-
impacts: A character array with '+' corresponding to features with positive impact and '-' corresponding to features with negative positive impact
-
output file name: name of the output csv file having TOPSIS score and rank columns appended to the input file
| Output: | The result table will be exported to a newly created csv file with given name
Example
| input.csv
| Fund Name | P1 | P2 | P3 | P4 | P5 |
|---|---|---|---|---|---|
| M1 | 0.67 | 0.45 | 5.1 | 66.4 | 18.16 |
| M2 | 0.8 | 0.64 | 4.9 | 46.7 | 13.26 |
| M3 | 0.68 | 0.46 | 3.6 | 34.9 | 9.91 |
| M4 | 0.84 | 0.71 | 4.7 | 36.8 | 10.76 |
| M5 | 0.68 | 0.46 | 4.7 | 51.1 | 14.24 |
| M6 | 0.63 | 0.4 | 5.3 | 54.5 | 15.21 |
| M7 | 0.8 | 0.64 | 3.7 | 67.3 | 18.11 |
| M8 | 0.79 | 0.62 | 3.3 | 66.6 | 17.83 |
| Weights = [1,1,1,1,1] | Impacts = ['+', '+', '+', '+', '-' ]
topsis input.csv 1,1,1,1,1 +,+,+,+,- output.csv
Output
| output.csv:
| Fund Name | P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank |
|---|---|---|---|---|---|---|---|
| M1 | 0.67 | 0.45 | 5.1 | 66.4 | 18.16 | 0.484607532 | 5 |
| M2 | 0.8 | 0.64 | 4.9 | 46.7 | 13.26 | 0.605914538 | 1 |
| M3 | 0.68 | 0.46 | 3.6 | 34.9 | 9.91 | 0.396910752 | 8 |
| M4 | 0.84 | 0.71 | 4.7 | 36.8 | 10.76 | 0.596374527 | 2 |
| M5 | 0.68 | 0.46 | 4.7 | 51.1 | 14.24 | 0.44053701 | 7 |
| M6 | 0.63 | 0.4 | 5.3 | 54.5 | 15.21 | 0.445909442 | 6 |
| M7 | 0.8 | 0.64 | 3.7 | 67.3 | 18.11 | 0.537060234 | 3 |
| M8 | 0.79 | 0.62 | 3.3 | 66.6 | 17.83 | 0.507571147 | 4 |
License
MIT License
Copyright (c) 2023 Sahil Singla
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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