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THIS PACKAGE IS TO IMPLEMENT TOPSIS

Project description

TOPSIS_ANMOL_101803669

With this you can calculate the TOPSIS score and RANK of the data provided in '.csv' format.

  • Input file:
    • contain three or more columns
    • First column is the object/variable name.
    • From 2nd to last column contain numeric values only

Overview

  • You can check intermediate steps as well as the final score i.e it provides functions to calculate normalized matrix, weight normalized decision matrix , ideal best , ideal worst lists and so on.

Usage

In the following paragraphs, I am going to describe how you can get and use TOPSIS for your own projects.

Getting it

To download TOPSIS, either fork this github repo or simply use Pypi via pip.

$ pip install TOPSIS_ANMOL_101803669

Using it

TOPSIS was programmed with ease-of-use in mind. Just, import topsis from TOPSIS-Aditi-101803650

from TOPSIS_ANMOL_101803669.topsis1 import topsis
topsis('inputfilename','Weights','Impacts','Outputfilename')

And you are ready to go!

topsis

There are 5 steps in this:

  • normalized_matrix
  • weight_normalized
  • ideal_best_worst
  • euclidean_distance
  • topsis_score

License

MIT

Pre-requisite

The data should be enclosed in the csv file. There must be more than 2 columns

Result

the output(outputfilename) is saved in the project folder with extra 2 columns with topsis score and rank.

Project details


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