ade52a2d1afe22bdff0ac28b65e5b5cfdd03dd44,pynets/utils.py,,collect_pandas_df,#Any#Any#Any#Any#Any#Any#,816

Before Change

    warnings.filterwarnings("ignore")
    from pynets.utils import collect_pandas_df_make, flatten

    func_models = ["corr", "sps", "cov", "partcorr", "QuicGraphicalLasso", "QuicGraphicalLassoCV",
                   "QuicGraphicalLassoEBIC", "AdaptiveQuicGraphicalLasso"]

    struct_models = ["csa", "tensor", "csd"]

    net_pickle_mt_list = list(flatten(net_pickle_mt_list))

After Change

    from pynets.utils import collect_pandas_df_make, flatten

    // Available functional and structural connectivity models
    with open("%s%s" % (str(Path(__file__).parent), "/runconfig.yaml"), "r") as stream:
        hardcoded_params = yaml.load(stream)
        try:
            func_models = hardcoded_params["available_models"]["func_models"]
        except KeyError:
            print("ERROR: available functional models not sucessfully extracted from runconfig.yaml")
        try:
            struct_models = hardcoded_params["available_models"]["struct_models"]
        except KeyError:
            print("ERROR: available structural models not sucessfully extracted from runconfig.yaml")
    net_pickle_mt_list = list(flatten(net_pickle_mt_list))

    if multi_nets is not None:
        net_pickle_mt_list_nets = net_pickle_mt_list

Instances