import numpy as np
import os
import sys

# hours_per_time_step should be greater than 1
hours_per_step = 2

class PainModel():
    def __init__(self, seed):
        # pain -1 is bad
        # pain 1 is good
        self.pain = 0
        # initial start point for date -
        # TODO - make this random according to what weather data that you have
        self.datetime = 0
        # use random state so that it is repeatable
        self.random_state = np.random.RandomState(seed)

        self.precipitation_options = ['rain', 'sunny', 'snow', 'fog']
        self.activity_options = ['sleep', 'exercise', 'work', 'stressful', 'leisure']
        self.last_activities = []

    def step(activity):
        # activity is string matching one of 'activity_options'
        assert activity in self.activity_options
        recent_activities = self.activity_options[:max(self.hist_len, 24/hours_per_step)]
        hist_len = len(self.last_activities)
        if activity == 'sleep':
            self.pain-=.01
        if activity == 'exercise':
            self.pain-=.1
            # if you exercise too often, you may get hurt
            if 'exercise' in recent_activities:
                self.pain+=0.5
        if activity == 'work':
            self.pain+=.01
        if activity == 'stressful':
            self.pain+=0.5
        if activity == 'leisure':
            self.pain-=.01
        sleep_instances = [x if x=='sleep' for x in recent_activities]
        # reward getting 8 hours of sleep per night
        if 7/float(hours_per_step) < len(sleep_instances) < 12/float(hours_per_step):
            self.pain+=0.1

        # determine what the state was when this was experienced
        self.pain = np.clip(self.pain, -1, 1)
        self.state = [self.pain, self.datetime, self.get_precipitation()]
        # todo - turn datetime into day of week, workdayornot
        # state =  [self.datetim, self.get_precipitation(), self.get_temperature(), day_of_week, day_of_year, workday_or_holiday]

        # update datetime to prepare for next step
        self.datetime += hours_per_step
        self.last_activities.append(activity)
        # prevent pain from going outside bounds

        return self.state


    def get_day_of_week(self):
        # todo - find according to datetime in python
        return 0

    def get_precipitation(self):
        # todo - find according to datetime
        return self.random_state.randint(0,len(self.precipitation_options))


def generate_perfect_person():
    pain_model = PainModel(seed=103)
    stressful_random_state = np.random.RandomState(3949)
    sleep_random_state = np.random.RandomState(949)
    states = []
    for workday in [0, 1, 1, 1, 1, 1, 0]:
        if workday:
            # is time step is 2 and day restarts at midnight
            # 0-2
            if sleep_random_state.rand() < 0.95:
                states.append(pain_model('sleep'))
            else:
                states.append(pain_model('leisure'))
             # 2-4
            if sleep_random_state.rand() < 0.98:
                states.append(pain_model('sleep'))
            else:
                states.append(pain_model('stressful'))
            # 4-6
            if sleep_random_state.rand() < 0.98:
                states.append(pain_model('sleep'))
            else:
                states.append(pain_model('stressful'))
            # 6-8
            if sleep_random_state.rand() < 0.85:
                states.append(pain_model('sleep'))
            else:
                states.append(pain_model('exercise'))
            # 8-4
            for i in range(4):
                if stressful_random_state.rand()<0.95:
                    states.append(pain_model('work'))
                else:
                    states.append(pain_model('stressful'))
            # 4-12
            for i in range(4):
                afw = stressful_random_state.rand()
                if afw < 0.1:
                    states.append(pain_model('stressful'))
                if afw < 0.2:
                    states.append(pain_model('exercise'))
                elif < 0.95:
                    states.append(pain_model('leisure'))
                else:
                    states.append(pain_model('sleep'))
        else:
            # yay it is the weekend
            # is time step is 2 and day restarts at midnight
            for i in range(4):
                # sleep in on the weekend
                states.append(pain_model('sleep'))
            for i in range(7):
                states.append(pain_model('leisure'))
            states.append(pain_model('sleep'))