percolate/percolate.py
def statistics(
    graph, ps, spanning_cluster=True, model='bond', alpha=alpha_1sigma, runs=40
):
    """
    Helper function to compute percolation statistics

    See Also
    --------

    canonical_averages

    microcanonical_averages

    sample_states

    """

    my_microcanonical_averages = microcanonical_averages(
        graph=graph, runs=runs, spanning_cluster=spanning_cluster, model=model,
        alpha=alpha
    )

    my_microcanonical_averages_arrays = microcanonical_averages_arrays(
        my_microcanonical_averages
    )

    return canonical_averages(ps, my_microcanonical_averages_arrays)
def statistics(
    graph, ps, spanning_cluster=True, model='bond', alpha=alpha_1sigma, runs=40
):
    """
    Helper function to compute percolation statistics

    See Also
    --------

    canonical_averages

    microcanonical_averages

    sample_states

    """

    my_microcanonical_averages = microcanonical_averages(
        graph=graph, runs=runs, spanning_cluster=spanning_cluster, model=model,
        alpha=alpha
    )

    my_microcanonical_averages_arrays = microcanonical_averages_arrays(
        my_microcanonical_averages
    )

    return canonical_averages(ps, my_microcanonical_averages_arrays)
def statistics ( graph , ps , spanning_cluster = True , model = 'bond' , alpha = alpha_1sigma , runs = 40 ) : my_microcanonical_averages = microcanonical_averages ( graph = graph , runs = runs , spanning_cluster = spanning_cluster , model = model , alpha = alpha ) my_microcanonical_averages_arrays = microcanonical_averages_arrays ( my_microcanonical_averages ) return canonical_averages ( ps , my_microcanonical_averages_arrays )
Helper function to compute percolation statistics

    See Also
    --------

    canonical_averages

    microcanonical_averages

    sample_states
Helper function to compute percolation statistics