pyrepo_mcda.compromise_rankings

Functions

copeland(matrix)	Calculate the compromise ranking considering several rankings obtained using different
dominance_directed_graph(matrix)	Calculate the compromise ranking considering several rankings obtained using different
rank_position_method(matrix)	Calculate the compromise ranking considering several rankings obtained using different
improved_borda_rule(prefs, ranks)	Calculate the compromise ranking considering several rankings obtained using different

Module Contents

pyrepo_mcda.compromise_rankings.copeland(matrix)

Calculate the compromise ranking considering several rankings obtained using different methods using the Copeland compromise ranking methodology.

Parameters

matrixndarray

Two-dimensional matrix containing different rankings in columns.

Returns

ndarray

Vector including compromise ranking.

Examples

>>> rank = copeland(matrix)

pyrepo_mcda.compromise_rankings.dominance_directed_graph(matrix)

Calculate the compromise ranking considering several rankings obtained using different methods using Dominance Directed Graph methodology

Parameters

matrixndarray

Two-dimensional matrix containing different rankings in columns.

Returns

ndarray

Vector including compromise ranking.

Examples

>>> rank = dominance_directed_graph(matrix)

pyrepo_mcda.compromise_rankings.rank_position_method(matrix)

Calculate the compromise ranking considering several rankings obtained using different methods using Rank Position Method

Parameters

matrixndarray

Two-dimensional matrix containing different rankings in columns.

Returns

ndarray

Vector including compromise ranking.

Examples

>>> rank = rank_position_method(matrix)

pyrepo_mcda.compromise_rankings.improved_borda_rule(prefs, ranks)

Calculate the compromise ranking considering several rankings obtained using different methods using Improved Borda rule methodology

Parameters

prefsndarray

Two-dimensional matrix containing preferences calculated by different methods in columns.

ranksndarray

Two-dimensional matrix containing rankings determined by different methods in columns.

Returns

ndarray

Vector including compromise ranking.

Examples

>>> rank = improved_borda_rule(prefs, ranks)