# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
#
# SPDX-License-Identifier: AGPL-3.0-or-later

import pandas as pd

REF_OBJ_DF = pd.read_csv("test/utils/obj_ref.csv", comment="#")

SCALE = 1_000_000


def extract_obj_for_path(dir, fl, ref_df=REF_OBJ_DF):
    """
    Parameters
    ----------
    dir : string
        name of the folder containing outputs of a modeling run
    fl : string
        name of a log file for a modeling run
    ref_df : pd.DataFrame
        dataframe which contains reference objective values for test runs
    baseyear : int

    Examples
    ----------
    .. code-block:: python

        # calling an existing log outputs a respective objective value
        obj_found = extract_obj_for_path(
            "custom", "elec_s_6_ec_lcopt_Co2L-4H_python.log", ref_df=REF_OBJ_DF
        )
        print(obj_found)

        # calling a non-existing log results in NA value
        obj_na = extract_obj_for_path(
            "custom2", "elec_s_6_ec_lcopt_Co2L-4H_python.log", ref_df=REF_OBJ_DF
        )
        print(obj_na)
    """
    mask = (ref_df["folder"] == dir) & (ref_df["file"] == fl)

    obj_value = ref_df["objective"][mask]

    if obj_value.empty:
        obj_value = "NA"
    else:
        obj_value = round(obj_value.values[0] / SCALE, 2)

    return obj_value