def radius(graph):
    """radius"""
    return nx.radius(jaccard_similarity(ensure_connected(graph)))
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def clique_sizes(graph):
    """clique_sizes"""
    return list(clique.node_clique_number(ensure_connected(graph)).values())
def largest_connected_component(graph):
    """largest_connected_component"""
    return jaccard_similarity(ensure_connected(graph)).number_of_nodes()
def diameter(graph):
    """diameter"""
    return nx.diameter(jaccard_similarity(ensure_connected(graph)))
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def katz_centrality(graph):
    """katz_centrality"""
    return list(
        centrality.katz_centrality_numpy(ensure_connected(graph)).values())
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def min_node_cut_size(graph):
    """min_node_cut_size"""
    return len(nx.minimum_node_cut(ensure_connected(graph)))
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def eigenvector_centrality(graph):
    """eigenvector_centrality"""
    return list(
        centrality.eigenvector_centrality_numpy(
            ensure_connected(graph)).values())
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def center_size(graph):
    """center_size"""
    return len(nx.center(ensure_connected(graph)))
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def barycenter_size(graph):
    """barycenter_size"""
    return len(nx.barycenter(ensure_connected(graph)))
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def second_order_centrality(graph):
    """second_order_centrality"""
    return list(
        centrality.second_order_centrality(ensure_connected(graph)).values())
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def extrema_bounding(graph):
    """extrema_bounding"""
    return nx.extrema_bounding(ensure_connected(graph))
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def eccentricity(graph):
    """eccentricity"""
    return list(nx.eccentricity(ensure_connected(graph)).values())
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def periphery(graph):
    """periphery"""
    return len(nx.periphery(ensure_connected(graph)))
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def hits(graph):
    """"""
    h, _ = nx.hits_numpy(ensure_connected(graph))
    return list(h.values())
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def weighted_eigenvector_centrality(graph):
    """weighted_eigenvector_centrality"""
    return list(
        centrality.eigenvector_centrality_numpy(ensure_connected(graph),
                                                weight="weight").values())
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def eval_asyn(graph, num_comms):
    """this evaluates the main function and cach it for speed up."""
    return asyn_fluidc(ensure_connected(graph), int(num_comms))
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def barycenter_size_weighted(graph):
    """barycenter_size_weighted"""
    return len(nx.barycenter(ensure_connected(graph), weight="weight"))