def prepare(args):
    overwriting = True

    load_config(args)
    load_key(args)
    output_dir = make_dir(args, "reference_set", None, overwriting)
    key = SecretDict.get_secrets()["key"]
    method_params_standardizer = ConfigDict.get_parameters()["standardization"]
    st = Standardizer.from_param_dict(
        method_param_dict=method_params_standardizer, verbosity=0)
    outcols_st = ["canonical_smiles", "success", "error_message"]
    out_types_st = ["object", "bool", "object"]
    dt_standarizer = DfTransformer(
        st,
        input_columns={"smiles": "smiles"},
        output_columns=outcols_st,
        output_types=out_types_st,
        success_column="success",
        nproc=1,
        verbosity=0,
    )

    method_params_folding = ConfigDict.get_parameters()["scaffold_folding"]
    sa = ScaffoldFoldAssign.from_param_dict(
        secret=key, method_param_dict=method_params_folding, verbosity=0)
    outcols_sa = [
        "murcko_smiles", "sn_smiles", "fold_id", "success", "error_message"
    ]
    out_types_sa = ["object", "object", "int", "bool", "object"]
    dt_fold = DfTransformer(
        sa,
        input_columns={"canonical_smiles": "smiles"},
        output_columns=outcols_sa,
        output_types=out_types_sa,
        success_column="success",
        nproc=1,
        verbosity=0,
    )

    method_params_descriptor = ConfigDict.get_parameters()["fingerprint"]
    dc = DescriptorCalculator.from_param_dict(
        secret=key, method_param_dict=method_params_descriptor, verbosity=0)
    outcols_dc = ["fp_feat", "fp_val", "success", "error_message"]
    out_types_dc = ["object", "object", "bool", "object"]
    dt_descriptor = DfTransformer(
        dc,
        input_columns={"canonical_smiles": "smiles"},
        output_columns=outcols_dc,
        output_types=out_types_dc,
        success_column="success",
        nproc=1,
        verbosity=0,
    )

    return output_dir, dt_standarizer, dt_fold, dt_descriptor
示例#2
0
def prepare(args):
    """
    Prepare output directories and instantiate df tansformer object for scaffold based folding

    Args:
        args (dict): argparser arguments

    Returns:
        Tuple(Path, DfTransformer): Path to output directory and instatitaed DfTranfomer for sccaffold folding


    """
    output_dir = make_dir(args, "results_tmp", "folding", args["non_interactive"])
    mapping_table_dir = make_dir(args, "mapping_table", None, args["non_interactive"])

    create_log_files(output_dir)
    create_log_files(mapping_table_dir)

    load_config(args)
    load_key(args)
    key = SecretDict.get_secrets()["key"]
    method_params = ConfigDict.get_parameters()["scaffold_folding"]
    sa = ScaffoldFoldAssign.from_param_dict(
        secret=key, method_param_dict=method_params, verbosity=0
    )
    outcols = ["murcko_smiles", "sn_smiles", "fold_id", "success", "error_message"]
    out_types = ["object", "object", "int", "bool", "object"]
    dt = DfTransformer(
        sa,
        input_columns={"canonical_smiles": "smiles"},
        output_columns=outcols,
        output_types=out_types,
        success_column="success",
        nproc=args["number_cpu"],
        verbosity=0,
    )
    return output_dir, mapping_table_dir, dt