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Python library for Multi-Criteria Decision Analysis.

Project description

pyrepo-mcda

The Python 3 library for Multi-Criteria Decision Analysis.

Installation

pip install pyrepo-mcda

Usage

pyrepo-mcda can be used to rank alternatives after providing their performance values in two-dimensional decision matrix with alternatives in rows and criteria in columns, and criteria weights and types in vectors. Here is example of using the TOPSIS method:

from pyrepo_mcda.mcda_methods import TOPSIS
from pyrepo_mcda import distance_metrics as dists
from pyrepo_mcda import normalizations as norms
from pyrepo_mcda.additions import rank_preferences

import numpy as np

matrix = np.array([[256, 8, 41, 1.6, 1.77, 7347.16],
[256, 8, 32, 1.0, 1.8, 6919.99],
[256, 8, 53, 1.6, 1.9, 8400],
[256, 8, 41, 1.0, 1.75, 6808.9],
[512, 8, 35, 1.6, 1.7, 8479.99],
[256, 4, 35, 1.6, 1.7, 7499.99]])

weights = np.array([0.405, 0.221, 0.134, 0.199, 0.007, 0.034])
types = np.array([1, 1, 1, 1, -1, -1])

topsis = TOPSIS(normalization_method=norms.vector_normalization, distance_metric=dists.euclidean)
pref = topsis(matrix, weights, types)
rank = rank_preferences(pref, reverse = True)
print(rank)

License

pyrepo-mcda was created by Aleksandra Bączkiewicz. It is licensed under the terms of the MIT license.

Documentation

Documentation of this library with instruction of installation and usage is provided here

Project details


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