Topsis Package
Project description
For: Assignment-1 (UCS654)
Submitted by: Sanjana Sinha
Roll No: 102103040
Group: 3COE2
Topsis_Sanjana_102103040
Topsis_Sanjana_102103040 is a Python library for dealing with Multiple Criteria Decision Making (MCDM) problems by applying Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).
Installation
Install Topsis_Sanjana_102103040 using Pypi via pip.
$ pip install topsis_sanjana_102103040
Usage
You can use this package in python as :
from topsis_sanjana_102103040 import topsis
inputFile="sample.csv"
weights="1,1,1,1"
impacts="-,+,+,+"
resultFile="result.csv"
topsis(inputFile, weights, impacts, resultFile)
OR
You can use this package via commandline as :
$ topsis [InputDataFile as .csv] [Weights as a string] [Impacts as a string] [ResultFileName as .csv]
For Example :
$ topsis sample.csv "1,1,1,1" "-,+,+,+" result.csv
Please Note That :
- The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So the csv MUST follow the format as shown in sample.csv shown in the Example section.
- The input data file MUST contain three or more columns.
- The second to last columns of the data file MUST contain NUMERIC values.
- The number of weights, impacts and columns (second to last) MUST be SAME.
- Impacts MUST either be '+' or '-'.
- Impacts and Weights MUST be separated by ‘,’ (comma).
Example
sample.csv
A csv file that contains data for mobile models and their features.
Model | Price (in $) | Storage Space (in GB) | Camera (in MP) | Looks (1 to 5) |
---|---|---|---|---|
M1 | 250 | 16 | 12 | 5 |
M2 | 200 | 16 | 8 | 3 |
M3 | 300 | 32 | 16 | 4 |
M4 | 275 | 32 | 8 | 4 |
M5 | 225 | 16 | 16 | 2 |
Weights : 0.25,0.25,0.25,0.25
Impacts : -,+,+,+
input :
$ topsis sample.csv "0.25,0.25,0.25,0.25" "-,+,+,+" result.csv
result.csv
A csv file that contains the same data as sample.csv with two additional columns 'Topsis Score' and 'Rank'.
Model | Price (in $) | Storage Space (in GB) | Camera (in MP) | Looks (1 to 5) | Topsis Score | Rank |
---|---|---|---|---|---|---|
M1 | 250 | 16 | 12 | 5 | 53.43 | 3 |
M2 | 200 | 16 | 8 | 3 | 30.84 | 5 |
M3 | 300 | 32 | 16 | 4 | 69.16 | 1 |
M4 | 275 | 32 | 8 | 4 | 53.47 | 2 |
M5 | 225 | 16 | 16 | 2 | 40.1 | 4 |
License
MIT License
Copyright (c) 2024 Sanjana Sinha
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.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for topsis_sanjana_102103040-0.6.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 47b98349370eb2ea07b84d48599ffcc5f5ccddef5c6d356e6ae0145b4816cac8 |
|
MD5 | 1bde942143485be1ee24b934a08018e8 |
|
BLAKE2b-256 | 29c4b10215d06309e409ea19e3f1e5b6c908ef60a45dfa3507706d30a626e2ac |