Exemplo n.º 1
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def load_ht09_flockwork_params(scaled=False):
    """Load the standard parameters to generate SocioPatterns HT09 
    surrogate networks using the Flockwork-P model with varying rates.

    Parameters
    ----------
    scaled : bool, optional
        If this is `True`, load the rewiring rate `gamma(t)` and proba-
        bility to reconnect `P(t)` rescaled with a corrective factor.
        This factor emerges because in the original network the mean degree
        is overestimated due to binning of edges. This overestimation
        typically leads to an underestimation of `gamma(t)` and an 
        overestimation of `P(t)`.
        
    Returns
    -------
    :obj:`dict`
        The `kwargs` to pass to :func:`tacoma.flockwork_P_varying_rates`.
    """

    if scaled:
        fn = os.path.join(path, 'ht09_fwP_params_scaled.json')
    else:
        fn = os.path.join(path, 'ht09_fwP_params_unscaled.json')

    return tc.load_json_dict(fn)
Exemplo n.º 2
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def load_hs13_dyn_RGG_params():
    """Load the standard parameters to generate SocioPatterns HS13
    surrogate networks using the dynamic RGG model.

    Returns
    -------
    :obj:`dict`
        The `kwargs` to pass to :func:`tacoma.dynamic_RGG`.
    """

    fn = os.path.join(path, 'ht09_dyn_RGG_params.json')
    return tc.load_json_dict(fn)
Exemplo n.º 3
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def load_ht09_ZSBB_params():
    """Load the standard parameters to generate SocioPatterns HT09 
    surrogate networks using the ZSBB model.

    Returns
    -------
    :obj:`dict`
        The `kwargs` to pass to :func:`tacoma.ZSBB_model`.
    """

    fn = os.path.join(path, 'ht09_zsbb_params.json')
    return tc.load_json_dict(fn)
Exemplo n.º 4
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def load_dtu_ZSBB_params():
    """Load the standard parameters to generate surrogate networks 
    for one week of DTU data using the ZSBB model.

    Returns
    -------
    :obj:`dict`
        The `kwargs` to pass to :func:`tacoma.ZSBB_model`.
    """

    fn = os.path.join(path, 'dtu_zsbb_params.json')
    return tc.load_json_dict(fn)