Metadata-Version: 2.1
Name: scikit-mcda
Version: 0.0.8
Summary: Library for Multi-criteria Decision Aid Methods
Home-page: https://gitlab.com/cybercrafter/scikit-mcda
Author: Antonio Horta
Author-email: horta@cybercrafter.com.br
License: Apache License 2.0
Description: scikit-mcda
        ===========
        
        A python library made to provide multi-criteria decision aid for developers and operacional researchers.
        
        Module for Decision-making Under Uncertainty (DMUU)
        ---------------------------------------------------
        
        **dmuu**: Module for Decision-making Under Uncertainty
        
        **criteria**:
        
        - maximax
        - maximin
        - laplace
        - minimax-regret
        - hurwicz
        
        **functions**:
        
        - dataframe(alt_data, alt_labels=[], state_labels=[])
        - calc(dmuu_df, dmuu_criteria_list=[], hurwicz_coeficient=-1)
        - decision_making(dmuu_df, dmuu_criteria_list=[], hurwicz_coeficient=-1)
        
        Example
        -------
        
        ::
        
            from scikitmcda import dmuu 
        
            df = dmuu.dataframe([[5000, 2000, 100],
                                 [50, 50, 500]],
                                ["ALT_A", "ALT_B"],
                                ["STATE A", "STATE B", "STATE C"])
        
            df
            +----+----------------+-----------+-----------+-----------+
            |    | alternatives   |   STATE A |   STATE B |   STATE C |
            |----+----------------+-----------+-----------+-----------|
            |  0 | ALT_A          |      5000 |      2000 |       100 |
            |  1 | ALT_B          |        50 |        50 |       500 |
            +----+----------------+-----------+-----------+-----------+
        
            df_calc = dmuu.calc(df, ["minimax-regret", "hurwicz"], 0.7)
        
            df_calc
            +----+----------------+-----------+-----------+-----------+------------------+------------------+
            |    | alternatives   |   STATE A |   STATE B |   STATE C | minimax-regret   | hurwicz          |
            |----+----------------+-----------+-----------+-----------+------------------+------------------|
            |  0 | ALT_A          |      5000 |      2000 |       100 | (400, 1)         | (3530.0, 1, 0.7) |
            |  1 | ALT_B          |        50 |        50 |       500 | (4950, 0)        | (365.0, 0, 0.7)  |
            +----+----------------+-----------+-----------+-----------+------------------+------------------+
        
            result = dmuu.decision_making(df)
        
            result
        
            [{'alternative': 'ALT_A',
              'criteria': 'maximax',
              'hurwicz_coeficient': '',
              'index': 0,
              'result': {'ALT_A': 5000, 'ALT_B': 500},
              'type_dm': 'DMUU',
              'value': 5000},
            ...
            {'alternative': 'ALT_A',
              'criteria': 'hurwicz',
              'hurwicz_coeficient': 0.5,
              'index': 0,
              'result': {'ALT_A': 2550.0, 'ALT_B': 275.0},
              'type_dm': 'DMUU',
              'value': 2550.0}]
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
