import argparse
import gzip
from itertools import starmap
import logging
from multiprocessing import pool
import pathlib
import pickle

from cycler import cycler
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np
from scipy import interpolate

from .olaflow import OFModel

parser = argparse.ArgumentParser(description="Post-process olaflow results")
parser.add_argument("-v", "--verbose", action="count", default=0)
parser.add_argument(
    "-o",
    "--output",
    action="append",
    type=pathlib.Path,
    help="Post-processing directory",
    required=True,
)
args = parser.parse_args()

logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
log = logging.getLogger("ola_post")

log.info("Plotting comparison of model output")


def get_pickle(out):
    with (
        path.open("rb")
        if (path := out.joinpath("pickle")).exists()
        else gzip.open(path.with_suffix(".gz"), "rb")
    ) as f:
        return pickle.load(f)


models = list(map(get_pickle, args.output))

fig, ax = plt.subplots(len(models), constrained_layout=True)
for i, (_ax, _model) in enumerate(zip(ax, models)):
    _ax.contour(
        _model.t,
        _model.post_fields["graphUniform"]["x_alpha.water"],
        _model.post_fields["graphUniform"]["alpha.water"].T,
        (0.5,),
        colors="k",
    )

    _ax.set(xlabel="t (s)", ylabel="z (m)", title=f"Case {i}")
    _ax.grid()

fig.savefig(
    args.output[0].joinpath(f"diff_{'_'.join([o.name for o in args.output])}.pdf")
)