Metadata-Version: 2.1
Name: TOPSIS_ANMOL_101803669
Version: 0.2
Summary: THIS PACKAGE IS TO IMPLEMENT TOPSIS
Home-page: UNKNOWN
Author: ANMOL JINDAL
Author-email: ajindal4_be18@thapar.edu
License: MIT
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](https://choosealicense.com/licenses/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.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
