Metadata-Version: 2.1
Name: TOPSIS-Vikram-101803368
Version: 1.0.2
Summary: Apply topsis to a dataset in a csv file
Home-page: https://github.com/sixthkrum/topsis
Author: Vikram Alagh
Author-email: valagh_be18@thapar.edu
License: MIT
Description: Apply TOPSIS to a dataset in csv format.
        
        <h1> Usage: </h1>
        
        <h3> For use in code: </h3>
        
        from topsis import csvTopsis
        
        <h3> From the command line: </h3>
        
        csvTopsis (filename) (weights) (impacts) {options: delimiter(,)}
        
            filename is the name of the csv file which has the dataset
                
                The dataset must have a minimum of three columns and all the parameter columns must have numeric values. The first row is assumed to contain the column names and the first column is assumed to contain the row names
            
            weights is a comma seperated list of weights ex: 1.0,1,1,1
                
                weights must be numeric and the number of weights equal to number of parameter in the dataset
            
            impacts is a comma seperated list of impacts ex: +,+,+,+
                
                impacts must be either - or + and the number of impacts must be equal to number of parameters in the dataset
            
            delimiter is the delimiter to be used to read the csv file
                
                default ','
        
        
        Sample output:
        
            scores [0.5633920465033206, 0.3929781508166451, 0.8668523706767487, 0.14869542262467947, 0.5693097043728271]
        
            ranks [3, 4, 1, 5, 2]
        
        
        <h1> Functions: </h1>
        
        csvTopsis.topsis(inputCSV, weights, impacts, delimiter = ',')
        
            arguments:
        
                inputCSV is a stream containing the dataset, it must have at least 3 columns and the parameter columns must have only numeric values. The first column is assumed to contain row names and the first row is assumed to contain column names
                
                weights is a list with weights for the parameters in the dataset. The list must be numeric and have a size equal to the number of parameters in the dataset
                
                impacts is a list with impacts for the parameters in the dataset. The list must have only '-' or '+' as values and the size must be equal to number of parameters in the dataset
                
                delimiter is the delimiter to be used to read the inputCSV file object (default: ',')
        
            returns:
        
                resultCSV is a stream which contains the original dataset with 2 added columns namely 'Topsis Score' and 'Rank' the former contains the topsis score for the rows and the latter the topsis ranks
                
                similarityList is a list containing the topsis scores of all the rows
                
                rankList is a list containing the topsis ranks
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
