TOPSIS-ANUJ-101803638 0.5

THIS PACKAGE IS TO IMPLEMENT TOPSIS

TOPSIS_Anuj_101803638

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_Anuj_101803638

Using it

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

from TOPSIS_Anuj_101803638.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.