#! /usr/bin/env python3
"""
|------------------------------------------------------------------|
|---------------------  Instructions  -----------------------------|
|------------------------------------------------------------------|
This script is a simple wrapper for neon sites that performs the
following:
    1) For neon sites, subset surface dataset from global dataset
        (i.e. ./subset_data.py )
    2) Download neon and update the created surface dataset
       based on the downloaded neon data.
       (i.e. modify_singlept_site_neon.py)

Instructions for running using conda python environments:

../../py_env_create
conda activate ctsm_py

"""
#  Import libraries
from __future__ import print_function

import argparse
import logging
import os
import subprocess
import tqdm

import pandas as pd


def get_parser():
    """
    Get parser object for this script.
    """
    parser = argparse.ArgumentParser(
        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
    )

    parser.print_usage = parser.print_help

    parser.add_argument(
        "-v",
        "--verbose",
        help="Verbose mode will print more information. ",
        action="store_true",
        dest="verbose",
        default=False,
    )

    parser.add_argument(
        "--16pft",
        help="Create and/or modify 16-PFT surface datasets (e.g. for a FATES run) ",
        action="store_true",
        dest="pft_16",
        default=True,
    )

    return parser


def execute(command):
    """
    Function for running a command on shell.
    Args:
        command (str):
            command that we want to run.
    Raises:
        Error with the return code from shell.
    """
    print("\n", " >>  ", *command, "\n")

    try:
        subprocess.check_call(command, stdout=open(os.devnull, "w"), stderr=subprocess.STDOUT)

    except subprocess.CalledProcessError as err:
        # raise RuntimeError("command '{}' return with error
        # (code {}): {}".format(e.cmd, e.returncode, e.output))
        # print (e.ouput)
        print(err)


def main():
    """
    Read plumber2_sites from csv, iterate through sites, and add dominant PFT
    """

    args = get_parser().parse_args()

    if args.verbose:
        logging.basicConfig(level=logging.DEBUG)

    plumber2_sites = pd.read_csv("PLUMBER2_sites.csv", skiprows=4)

    for _, row in tqdm.tqdm(plumber2_sites.iterrows()):
        lat = row["Lat"]
        lon = row["Lon"]
        site = row["Site"]
        pft1 = row["pft1"]
        pctpft1 = row["pft1-%"]
        cth1 = row["pft1-cth"]
        cbh1 = row["pft1-cbh"]
        pft2 = row["pft2"]
        pctpft2 = row["pft2-%"]
        cth2 = row["pft2-cth"]
        cbh2 = row["pft2-cbh"]
        # overwrite missing values from .csv file
        if pft1 == -999:
            pft1 = 0
            pctpft1 = 0
            cth1 = 0
            cbh1 = 0
        if pft2 == -999:
            pft2 = 0
            pctpft2 = 0
            cth2 = 0
            cbh2 = 0
        clmsite = "1x1_PLUMBER2_" + site
        print("Now processing site :", site)

        if args.pft_16:
            # use surface dataset with 16 pfts, but overwrite to 100% 1 dominant PFT
            # don't set crop flag
            # set dominant pft
            subset_command = [
                "./subset_data",
                "point",
                "--lat",
                str(lat),
                "--lon",
                str(lon),
                "--site",
                clmsite,
                "--dompft",
                str(pft1),
                str(pft2),
                "--pctpft",
                str(pctpft1),
                str(pctpft2),
                "--cth",
                str(cth1),
                str(cth2),
                "--cbh",
                str(cbh1),
                str(cbh2),
                "--create-surface",
                "--uniform-snowpack",
                "--cap-saturation",
                "--verbose",
                "--overwrite",
            ]
        else:
            # use surface dataset with 78 pfts, and overwrite to 100% 1 dominant PFT
            # NOTE: FATES will currently not run with a 78-PFT surface dataset
            # set crop flag
            # set dominant pft
            subset_command = [
                "./subset_data",
                "point",
                "--lat",
                str(lat),
                "--lon",
                str(lon),
                "--site",
                clmsite,
                "--crop",
                "--dompft",
                str(pft1),
                str(pft2),
                "--pctpft",
                str(pctpft1),
                str(pctpft2),
                "--create-surface",
                "--uniform-snowpack",
                "--cap-saturation",
                "--verbose",
                "--overwrite",
            ]
        execute(subset_command)


if __name__ == "__main__":
    main()