from django.core.exceptions import PermissionDenied
from rowers.models import C2WorldClassAgePerformance
from rowers.utils import myqueue

# The interactions with the Concept2 logbook API
# All C2 related functions should be defined here
# (There is still some stuff defined directly in views.py. Need to
# move that here.)

from rowers.imports import *
import datetime
from requests import Request, Session
import rowers.mytypes as mytypes
from rowers.mytypes import otwtypes
from rowers.rower_rules import is_workout_user, ispromember
from iso8601 import ParseError

import numpy
import json
from scipy import optimize
from json.decoder import JSONDecodeError

from pytz.exceptions import UnknownTimeZoneError
from rowers.utils import dologging

from rowsandall_app.settings import (
    C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET,
    UPLOAD_SERVICE_URL, UPLOAD_SERVICE_SECRET
)

from rowers.tasks import (
    handle_c2_import_stroke_data, handle_c2_sync, handle_c2_async_workout,
    handle_c2_getworkout
)
import django_rq
queue = django_rq.get_queue('default')
queuelow = django_rq.get_queue('low')
queuehigh = django_rq.get_queue('high')


def getagegrouprecord(age, sex='male', weightcategory='hwt',
                      distance=2000, duration=None, indf=pd.DataFrame()):

    if not indf.empty:  # pragma: no cover
        if not duration:
            df = indf[indf['distance'] == distance]
        else:
            duration = 60*int(duration)
            df = indf[indf['duration'] == duration]
    else:
        if not duration:
            df = pd.DataFrame(
                list(
                    C2WorldClassAgePerformance.objects.filter(
                        distance=distance,
                        sex=sex,
                        weightcategory=weightcategory
                    ).values()
                )
            )
        else:
            duration = 60*int(duration)
            df = pd.DataFrame(
                list(
                    C2WorldClassAgePerformance.objects.filter(
                        duration=duration,
                        sex=sex,
                        weightcategory=weightcategory
                    ).values()
                )
            )

    if not df.empty:
        ages = df['age']
        powers = df['power']

        def fitfunc(pars, x):
            return np.abs(pars[0])*(1-x/max(120, pars[1]))-np.abs(
                pars[2])*np.exp(-x/np.abs(pars[3]))+np.abs(pars[4])*(np.sin(np.pi*x/max(50, pars[5])))

        def errfunc(pars, x, y):
            return fitfunc(pars, x)-y

        p0 = [700, 120, 700, 10, 100, 100]

        try:
            p1, success = optimize.leastsq(errfunc, p0[:],
                                           args=(ages, powers))
        except:  # pragma: no cover
            p1 = p0
            success = 0

        if success:
            power = fitfunc(p1, float(age))

            power = 0.5*(np.abs(power)+power)
        else:  # pragma: no cover
            power = 0
    else:
        power = 0

    return power