Metadata-Version: 1.1
Name: Topsis_Drishti_102016102
Version: 0.2
Summary: topsis
Home-page: UNKNOWN
Author: Drishti bhatia
Author-email: drishtibhatia2020@gmail.com
License: MIT
Description: Project description
        TOPSIS
        Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
        Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) came in the 1980s as a multi-criteria-based decision-making method. TOPSIS chooses the alternative of shortest the Euclidean distance from the ideal solution and greatest distance from the negative ideal solution.
        
        TOPSIS is a way to allocate the ranks on basis of the weights and impact of the given factors:.
        
        Weights mean how much a given factor should be taken into consideration
        Impact means that a given factor has a positive or negative impact.
        This tool allows you to calculate the topsis ranking and save the results in the form of a csv (Comma Seperated Value) file.
        
        Installing Package
        pip install Topsis-Drishti-102016102
        Using the TOPSIS tool
        Create a script by importing the package and just calling the TOPSIS function.
        import importlib
        topsis=importlib.import_module("Topsis_Drishti_1016102")
        topsis.TOPSIS()
        Run the Script through command line as shown below:
        C:/Users/admin> python myscript.py <Data_File_csv> <Weights(Comma_seperated)> <Impacts(Comma_seperated)> <Result_file_csv>
        
Keywords: topsis
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
