def test_scc(graph):
    sc = scc.KosarajuSCC(graph)
    assert scc.connectedComponents(sc) == 1
    assert scc.stronglyConnected(sc, 'A1', 'A4') is True
    assert scc.stronglyConnected(sc, 'A1', 'B3') is True
Example #2
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def numSCC(citibike):

    citibike['components'] = scc.KosarajuSCC(citibike['connections'])
    return scc.connectedComponents(citibike['components'])
def connectedComponents(analyzer):
    """
    Calcula los componentes conectados del grafo
    Se utiliza el algoritmo de Kosaraju
    """
    return scc.connectedComponents(analyzer['components'])
Example #4
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def Calcular_clusters(catalog):
    info_kosaraju = catalog['Kosaraju']
    cantidad = scc.connectedComponents(info_kosaraju)
    return cantidad
Example #5
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def numSCC(graph):
    sc = scc.KosarajuSCC(graph["graph"])
    return scc.connectedComponents(sc)
Example #6
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def numSCC(analyzer):
    sc = scc.KosarajuSCC(analyzer["connections"])
    return scc.connectedComponents(sc)
Example #7
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def connectedComponents(analyzer):
  
    analyzer['components'] = scc.KosarajuSCC(analyzer['connections'])

    return scc.connectedComponents(analyzer['components'])
def numSCC(graph):
    """
    Informa cuántos componentes fuertemente conectados se encontraron
    """
    sc = scc.KosarajuSCC(graph)
    return scc.connectedComponents(sc)
Example #9
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def numSCC(graph, sc):
    sc = scc.KosarajuSCC(graph['grafo'])
    return (scc.connectedComponents(sc), sc)
 def req_1_optimization(self):
     self.clusters = scc.KosarajuSCC(self.connections_map)
     self.cluster_number = scc.connectedComponents(self.clusters)
def numClusters(dataBase):
    clusters = scc.KosarajuSCC(dataBase['graph'])
    return scc.connectedComponents(clusters)
Example #12
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def test_scc(graph):
    sc = scc.KosarajuSCC(graph)
    assert scc.connectedComponents(sc) == 4
    assert scc.stronglyConnected(sc, 'Pedro', 'Carol') is True
    assert scc.stronglyConnected(sc, 'Pedro', 'Luz') is False