from otree.api import (
    models,
    widgets,
    BaseConstants,
    BaseSubsession,
    BaseGroup,
    BasePlayer,
    Currency as c,
    currency_range,
)
import numpy as np


author = 'Alexander Schneeberger'

doc = """
Moral Foundations Questionaire
"""


class Constants(BaseConstants):
    name_in_url = 'MFQ'
    players_per_group = None
    num_rounds = 1
    # Choice Set
    choices_1 = [
        [5, 'Extremely relevant'],
        [4, 'Very relevant'],
        [3, 'Somewhat relevant'],
        [2, 'Slightly relevant'],
        [1, 'Not very relevant'],
        [0, 'Not at all relevant'],
    ]
    choices_2 = [
        [5, 'Strongly agree'],
        [4, 'Moderately agree'],
        [3, 'Slightly agree'],
        [2, 'Slightly disagree'],
        [1, 'Moderately disagree'],
        [0, 'Strongly disagree'],
    ]


class Subsession(BaseSubsession):
    pass


class Group(BaseGroup):
    pass


class Player(BasePlayer):
    # Input - Indicate how relevant to morality
    Q1 = models.IntegerField(choices=Constants.choices_1)
    Q2 = models.IntegerField(choices=Constants.choices_1)
    Q3 = models.IntegerField(choices=Constants.choices_1)
    Q5 = models.IntegerField(choices=Constants.choices_1)
    Q6 = models.IntegerField(choices=Constants.choices_1)
    Q7 = models.IntegerField(choices=Constants.choices_1)
    Q8 = models.IntegerField(choices=Constants.choices_1)
    Q9 = models.IntegerField(choices=Constants.choices_1)
    Q11 = models.IntegerField(choices=Constants.choices_1)
    Q12 = models.IntegerField(choices=Constants.choices_1)
    Q13 = models.IntegerField(choices=Constants.choices_1)
    Q14 = models.IntegerField(choices=Constants.choices_1)
    Q16 = models.IntegerField(choices=Constants.choices_1)
    # Input - Indicate agreement or disagreement
    Q17 = models.IntegerField(choices=Constants.choices_2)
    Q18 = models.IntegerField(choices=Constants.choices_2)
    Q19 = models.IntegerField(choices=Constants.choices_2)
    Q21 = models.IntegerField(choices=Constants.choices_2)
    Q22 = models.IntegerField(choices=Constants.choices_2)
    Q23 = models.IntegerField(choices=Constants.choices_2)
    Q24 = models.IntegerField(choices=Constants.choices_2)
    Q25 = models.IntegerField(choices=Constants.choices_2)
    Q27 = models.IntegerField(choices=Constants.choices_2)
    Q28 = models.IntegerField(choices=Constants.choices_2)
    Q29 = models.IntegerField(choices=Constants.choices_2)
    Q30 = models.IntegerField(choices=Constants.choices_2)
    Q32 = models.IntegerField(choices=Constants.choices_2)
    # Background
    Harm = models.FloatField()
    Fairness = models.FloatField()
    Ingroup = models.FloatField()
    Purity = models.FloatField()
    Individualism = models.FloatField()
    Communalism = models.FloatField()
    Progressivism = models.FloatField()
    # Functions
    def calculate_scores(self):
        self.Harm = np.mean([self.Q1, self.Q7, self.Q12, self.Q17, self.Q23, self.Q28])
        self.Fairness = np.mean([self.Q2, self.Q8, self.Q13, self.Q18, self.Q24, self.Q29])
        self.Ingroup = np.mean([self.Q3, self.Q9, self.Q14, self.Q19, self.Q25, self.Q30])
        self.Purity = np.mean([self.Q5, self.Q11, self.Q16, self.Q21, self.Q27, self.Q32])
        self.Individualism = np.mean([self.Harm, self.Fairness])
        self.Communalism = np.mean([self.Ingroup, self.Purity])
        self.Progressivism = self.Individualism - self.Communalism