import datetime
from datetime import timezone
import re
import numpy as np

from icing.pirep_goes import get_goes_datasource

NO_ICE = '\s*NEG\s*|\s*NONE\s*|\s*NEGATIVE\s*|\s*NO\s*'
ICE_LVL = '\d+-\d+|FL\d+-FL\d+'
FLT_LVL = '/FL\s{0,1}\d+\s*'
ICE_RPT = '/IC'
ATYPE = '/TP'
RMK = '/RM'


# Returns icing/non-icing
def pirep_icing(filename, lon_range=[-180, 180], lat_range=[-55, 55]):
    no_ice_reports = []
    ice_reports = []

    # HEADER: VALID,URGENT,AIRCRAFT,REPORT,LAT,LON

    ice_dict = {}
    no_ice_dict = {}

    with open(filename) as file:
        for idx, line in enumerate(file):
            toks = line.split(',')
            if toks[0] == 'VALID':  # Skip headers (concatenated files)
                continue
            if len(toks) != 6:  # Check for line format error
                continue

            report = toks[3]
            lat = float(toks[4])
            lon = float(toks[5])

            if lon < lon_range[0] or lon > lon_range[1]:
                continue
            if lat < lat_range[0] or lat > lat_range[1]:
                continue

            # Flight level
            so = re.search(FLT_LVL, report)
            if so is None:
                continue
            else:
                fl = so.group()
                fl = (fl[3:].rstrip()).lstrip()
                if fl.isnumeric():
                    fl = float(fl) * 100 * 0.3048  # conv flight level to meters
                else:
                    continue

            # Icing
            ii = report.find('/IC')
            if ii >= 0:
                ice_str = report[ii+3:]
                ri = ice_str.find('/RM')

                if ri >= 0:
                    ice_str = ice_str[:ri]
                else:
                    ri = ice_str.find(',')
                    if ri >= 0:
                        ice_str = ice_str[:ri]
                ice_str = ice_str.lstrip()
                if ice_str.find('N/A') >= 0:
                    continue

                dto = datetime.datetime.strptime(toks[0], '%Y%m%d%H%M').replace(tzinfo=timezone.utc)
                timestmp = dto.timestamp()

                if len(re.findall(NO_ICE, ice_str)) != 0:
                    no_ice_reports.append(ice_str)
                    rpts = no_ice_dict.get(timestmp)
                    tup = (lat, lon, fl, ice_str)
                    if rpts is None:
                        rpts = []
                        rpts.append(tup)
                        no_ice_dict[timestmp] = rpts
                    else:
                        rpts.append(tup)
                else:
                    ice_reports.append(ice_str)
                    so = re.search(ICE_LVL, ice_str)
                    if so is not None:
                        lvl_a, lvl_b = so.group().split('-')
                        if lvl_a.find('FL') >= 0:
                            lvl_a = float(lvl_a[2:]) * 100 * 0.3048
                            lvl_b = float(lvl_b[2:]) * 100 * 0.3048
                        else:
                            lvl_a = float(lvl_a) * 100 * 0.3048
                            lvl_b = float(lvl_b) * 100 * 0.3048

                        fl = max(lvl_a, lvl_b)

                    if fl > 15000.0:
                        continue

                    rpts = ice_dict.get(timestmp)
                    tup = (lat, lon, fl, ice_str)
                    if rpts is None:
                        rpts = []
                        rpts.append(tup)
                        ice_dict[timestmp] = rpts
                    else:
                        rpts.append(tup)

    return ice_dict, no_ice_dict


def analyze(ice_dct, no_ice_dct):
    ice_times = np.array(list(ice_dct.keys()))
    no_ice_times = np.array(list(no_ice_dct.keys()))

    dt_str = '201601010000'
    dto = datetime.datetime.strptime(dt_str, '%Y%m%d%H%M').replace(tzinfo=timezone.utc)
    t0 = dto.timestamp()

    dt_str = '201906300000'
    dto = datetime.datetime.strptime(dt_str, '%Y%m%d%H%M').replace(tzinfo=timezone.utc)
    t1 = dto.timestamp()

    tline = np.arange(t0, t1, 600)
    hist_a, edges = np.histogram(no_ice_times, bins=tline)
    print(len(np.nonzero(hist_a)[0]))

    hist_b, edges = np.histogram(ice_times, bins=tline)
    print(len(np.nonzero(hist_b)[0]))

    print(np.sum(np.logical_and(hist_a > 0, hist_b > 0)))

    for ts in list(no_ice_dct.keys()):
        ds = get_goes_datasource(ts)
        goes_file = ds.get_file(ts)[0]
        print(goes_file)