from otree.api import (
    models,
    widgets,
    BaseConstants,
    BaseSubsession,
    BaseGroup,
    BasePlayer,
    Currency as c,
    currency_range,
)
import random
import itertools
import numpy as np
from django import forms
from django.forms import widgets as django_widgets
import math


author = 'Zheng Li'

doc = """
Intertemporal Choice
"""


class Constants(BaseConstants):
    name_in_url = 'inter_default_long'
    players_per_group = None

    decisions_low = [
        # pairs of tau2 and tau1#
        ['In 1 month', 'Today'],
        ['In 2 months', 'Today'],
        ['In 3 months', 'Today'],
    ]
    decisions_high = [
        # pairs of tau2 and tau1#
        ['In 6 months', 'Today'],
        ['In 9 months', 'Today'],
        ['In 12 months', 'Today'],
    ]
    decisions_target = [
        # pairs of tau2 and tau1#
        ['In 4 months', 'Today'],
        ['In 5 months', 'Today'],
    ]
    amounts = range(30,50,2)
    steps = 2
    num_rounds = 12

# to generate the certainty-uncertainty spectrum bar
    list1 = np.arange(1 * 20, - 1, -1)
    list2 = []
    list2.append(0)
    for x in range(20):
        list2.append((x+1)*5)

    example_set = [('In 30 days', 'Today', 25)]
    example_steps = 1

class Subsession(BaseSubsession):
    def creating_session(self):
        if self.round_number == 1:
            for p in self.get_players():
                # set treatment group: low default or high default
                p.participant.vars['default_identifier'] = random.choice([0, 1])

                # set default; only if failed check, becomes True
                p.participant.vars['failed_comprehension'] = False

                if p.participant.vars['default_identifier'] == 0:
                    decisions_default = Constants.decisions_low
                elif p.participant.vars['default_identifier'] == 1:
                    decisions_default = Constants.decisions_high

            # randomly assign ((tau2, tau1),pay_amount)'s
                dates_target = list()
                for _ in itertools.repeat(None, 3):
                    for date in Constants.decisions_target:
                        amount_tmp = random.choice(Constants.amounts)
                        date = (date, amount_tmp)
                        dates_target.append(date)

                dates_default = list()
                for _ in itertools.repeat(None, 2):
                    for date in decisions_default:
                        amount_tmp = random.choice(Constants.amounts)
                        date = (date, amount_tmp)
                        dates_default.append(date)

                p.participant.vars['dates'] = random.sample(dates_default + dates_target, 12)

        for p in self.get_players():
            p.default_identifier = p.participant.vars['default_identifier']
            p.set_current_task_number()


class Group(BaseGroup):
    pass


class Player(BasePlayer):

    prolific_id = models.StringField()

# indicator for low/high default group
    default_identifier = models.IntegerField(
        choices=[
            [0, 'low default'],
            [1, 'high default'],
        ],
        widget=widgets.RadioSelect,
        blank=False,
        label=""
    )

# parameters in the optimization problem
    pay_amount = models.IntegerField() # benchmark payment at tau2
    time_date_lhs = models.StringField() #tau2
    time_date_rhs = models.StringField() #tau1

#
    indicator_never_always_switcher = models.IntegerField()

# indifferent payment task:
    switching_point = models.FloatField()
    confidence = models.FloatField() # higher -> more confident; from 0 to 20 respectively corresponding to from 0% to 100%; step = $5%

# overall indicator of whether passed the comprehension check
    failed_comprehension = models.BooleanField(initial=False)

# indicators of whether correctly answered each question
    qn_lottery_got_wrong = models.BooleanField(initial=False)
    qn_confidence_got_wrong = models.BooleanField(initial=False)
    qn_hypo_got_wrong = models.BooleanField(initial=False)

# 4 comprehension questions
    qn_hypo = models.IntegerField(
        choices=[
            [1, 'In making my decisions, I am asked to assume that I will actually receive all payments indicated, regardless of whether they take place now or in the future.'],
            [0, 'In making my decisions, I am asked to assume that it is less likely that I will actually receive payments that are meant to take place in the future.'],
            [0, 'In making my decisions, I am asked to assume that it is less likely that I will actually receive payments that are meant to take place now.'],
        ],
        widget=widgets.RadioSelect,
        blank=False,
        label=""
    )
    qn_lottery = models.IntegerField(
        choices=[
            [0, 'It would be possible that I get paid both $15 and $20, i.e., I may receive a total amount of $35 from this decision.'],
            [1, 'I would receive EITHER $15 today OR $20 in 10 days.'],
            [0, 'It would be possible that I receive no money from this decision.'],
        ],
        widget=widgets.RadioSelect,
        blank=False,
        label=""
    )
    qn_confidence = models.FloatField(
        blank=False,
        label=""
    )

# to determine parameters in the current task
    def set_current_task_number(self):
        setattr(self, 'time_date_lhs', self.participant.vars['dates'][self.round_number - 1][0][0])
        setattr(self, 'time_date_rhs', self.participant.vars['dates'][self.round_number - 1][0][1])
        setattr(self, 'pay_amount', self.participant.vars['dates'][self.round_number - 1][1])

    def current_choice(self):
        iet_choice = [(self.time_date_lhs, self.time_date_rhs, self.pay_amount)]
        return iet_choice

# to generate the list of payments for option B in ListLoad.html
    def frange(self, start, stop, step):
        i = start + step
        while i < stop:
            if isinstance(i, int):
                yield i
            else:
                yield round(i, 2)
            i += step

# to display the list of payments for option B in List.html
    def right_side_amounts1(self):
        if self.pay_amount > 0:
            lst = self.frange(0, self.pay_amount + 1, Constants.steps)
        return list(enumerate(lst, 1)) # creating a list of tuples from looping "lst" with the starting index = 1

    def right_side_amounts2(self):
        lst = self.frange(0, Constants.example_set[0][2] + 1, Constants.example_steps)
        return list(enumerate(lst, 1))

# to display the confidence interval in Valuation.html
    def range_bounds(self):
        if self.pay_amount > 0:
            bounds = [0, self.pay_amount]
        return bounds

#
    def table_length1(self):
        return abs(self.pay_amount)/Constants.steps + 1

#
    def set_switching_point_and_indicator(self):
        if self.pay_amount > 0:
            if self.switching_point == 9999: # the template sets it to be 9999 when the player always chooses option A
                self.switching_point = self.pay_amount + Constants.steps
                self.indicator_never_always_switcher = 2
            elif self.switching_point == Constants.steps: # the template sets it to be 0 when the player always chooses option B
                self.indicator_never_always_switcher = 0
            else:
                self.indicator_never_always_switcher = 1 # when a middle point is chosen (what is desired)
        elif self.pay_amount < 0: ###how
            if self.switching_point == 9999:
                self.switching_point = 1
                self.indicator_never_always_switcher = 2
            elif self.switching_point == self.pay_amount:
                self.indicator_never_always_switcher = 0
            else:
                self.indicator_never_always_switcher = 1