#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Created by schaffer at 11/6/19

Collection of utility functions specific to GRIS
"""

import datetime
import re
from collections import namedtuple
from glob import glob
from itertools import chain
from os.path import basename
from pathlib import Path

import numpy as np
import pandas as pd
from astropy.io.fits.hdu.hdulist import fitsopen as fitsopen

from kis_tools.util.util import gris_run_number


def get_observers(logfile):
    return extract_names(get_candidates(logfile))


def get_candidates(logfile):
    with open(logfile, "r") as f:
        text = f.read().strip()
    text = "\n".join(text.split("\n")[:5])

    observer_parts = []
    patterns = [
        r"[a-zA-Z\-]*[ \t\r\f\v]*(?:observer|remote)+\w*[ \t\r\f\v]*:?\s+(.+)\n",
        r"(?:\n|^)*\s*([a-z ,\.]+)\n",
    ]

    for p in patterns:
        res = re.findall(p, text, re.IGNORECASE)
        if res:
            for r in res:
                observer_parts.append(r)
            break

    return ",".join(observer_parts)


def extract_names(obs_candidates):
    # check for Capitalized names
    obs_candidates.replace(" and ", ",")
    observers = [c for c in obs_candidates.split(",") if re.search(r"[A-Z][a-z]", c)]
    return observers


def observer_data_frame():
    files = glob("/dat/sdc/gris/*/*.txt")
    logfiles = list(filter(lambda x: re.match(r"\d{8}\.txt", basename(x)), files))

    observers = []
    dates = []

    for f in logfiles:
        observers.append(",".join(get_observers(f)))
        date = datetime.datetime.strptime(basename(f), "%Y%m%d.txt")
        dates.append(date)

    df = pd.DataFrame(dict(date=dates, observers=observers))
    df = df.set_index("date")

    print(df.head())


def extract_position_kws_from_manolo(raw_gris_file):
    """
    Extract coordinate information from an observation, possibly spliced into multiple gris files.
    Extracts date and run information from the filename, searches for files of the same observation
    and determines coordinate info. Coordinate info is collected for every step of the first map found.
    The keywords are averaged across the map, resulting in the coordinates of the map center.

    Args:
        raw_gris_file: path or stub of gris file name like 14apr20.001[-01][cc|r]

    Returns:
        pos: dictionary with member access to position values
    """
    # get coord info and bounding box
    folder = Path(raw_gris_file).parent
    assert folder.exists(), f"Input folder {folder} not found!"

    runnumber = gris_run_number(raw_gris_file)

    pattern = f"*.{runnumber:03d}*"
    files = [f for f in folder.glob(pattern) if not str(f).endswith('m')]
    print(files)

    headers = []
    for f in sorted(files):
        with fitsopen(f) as hdu:
            hdu[0].verify("silentfix")
            headers.append(hdu[0].header)

    assert headers, f"Empty list of headers, are there files in {str(folder)}? Pattern was: '{pattern}'."

    pos_kws = [
        "IFILE",
        "SLITORIE",
        "SLITPOSX",
        "SLITPOSY",
        "SLITLATI",
        "SLITLONG",
        "B0ANGLE",
        "P0ANGLE",
        "PARAANGL",
        "AZIMUT",
        "ELEVATIO",
        "L0ANGLE",
        "ROTANGLE",
        "ROTCODE",
        "FILENAME",
        "RA",
        "DEC",
    ]
    PositionInfo = namedtuple("PositionInfo", field_names=pos_kws)

    def info_from_env(env):
        # default for rotcode and angle, they were added in 2016
        defaults = dict(
            ROTCODE=1,
            ROTANGLE=0,
        )

        kwargs = {**defaults, **{k: env[k] for k in pos_kws if k in env}}
        return PositionInfo(**kwargs)

    env = {}
    pos_infos = None
    trigger_kw = "ISTEP"
    for key, value in chain(*[h.items() for h in headers]):
        if str(value).strip() == '' and key in env.keys():
            value = env[key]
        env[key] = value
        next_map = key == 'ISERIE' and value == 2
        if next_map:
            # Stop iteration after first map
            break
        if key == trigger_kw and value != 1:
            if pos_infos is None:
                pos_infos = [None] * env["STEPS"]
            pos_infos[env["ISTEP"] - 1] = info_from_env(env)
    pos_infos[env["ISTEP"] - 1] = info_from_env(env)
    pos_infos = np.array(pos_infos)
    # coords map 1
    indexes = {k: i for i, k in enumerate(pos_kws)}
    pos = dict(
        slitposx=pos_infos[:, indexes["SLITPOSX"]].astype(float).mean(),
        slitposy=pos_infos[:, indexes["SLITPOSY"]].astype(float).mean(),

        slitlati=pos_infos[:, indexes["SLITLATI"]].astype(float).mean(),
        slitlong=pos_infos[:, indexes["SLITLONG"]].astype(float).mean(),

        slitorie=pos_infos[:, indexes["SLITORIE"]].astype(float).mean(),

        l0_angle=pos_infos[:, indexes["L0ANGLE"]].astype(float).mean(),
        b0_angle=pos_infos[:, indexes["B0ANGLE"]].astype(float).mean(),
        p0_angle=pos_infos[:, indexes["P0ANGLE"]].astype(float).mean(),

        parallax_angle=pos_infos[:, indexes["PARAANGL"]].astype(float).mean(),
        azimuth=pos_infos[:, indexes["AZIMUT"]].astype(float).mean(),
        elevation=pos_infos[:, indexes["ELEVATIO"]].astype(float).mean(),
        date_beg=headers[0]["DATE-OBS"] + " " + headers[0]["UT"]
    )

    return pos