from otree.api import (
    models, widgets, BaseConstants, BaseSubsession, BaseGroup, BasePlayer,
    Currency as c, currency_range
)
from django.forms import widgets as d_widgets
import random
import numpy as np
from scipy.optimize import curve_fit

doc = '''
    This app is the investment decision with two assets.
'''

class Constants(BaseConstants):
    name_in_url = 'TwoAssets'
    players_per_group = None
    num_rounds = 15


class Subsession(BaseSubsession):
    pass


class Group(BaseGroup):
    pass


class Player(BasePlayer):


    def func_model(self,x,a,b):
        return a*x[0]+b*x[1]

    gamma=models.FloatField(initial=.001)
    eta=models.FloatField(initial=1)
    def calc_hara(self):
        val=[]
        f=[]
        pi=[]
        for x in self.in_all_rounds()[-9:]:
            val.append(x.mert_value/100)
            pi.append(x.mert_B/100)
            f.append(np.exp(-self.rf_rate*(5-x.round_number)))
        xdata=np.array([val,f],dtype="float")
        pi = np.array(pi,dtype="float")
        # print(xdata.shape)
        estimates, vcov=curve_fit(self.func_model,xdata,pi)
        # print(estimates)
        self.gamma=1-(.235-.03)/(.734**2)/estimates[0]
        self.eta=estimates[1]*(.734)**2/(.235-.03)

        # print(self.gamma)
        # print(self.eta)

        self.participant.vars['gamma']=self.gamma
        self.participant.vars['eta']=self.eta

######################################################################################################

###################### MERTON TASK ##################################################################

    mert_value=models.FloatField(initial=100)
    rf_rate=models.FloatField(initial=.03)

    mert_A=models.IntegerField(max=100,min=0,initial=50,
        label='''Risk Free''',
        widget=d_widgets.NumberInput(attrs={"step":5,'class':'spinner','type':'hidden'}))
    mert_B=models.IntegerField(max=100,min=0,initial=50,
        label='''Risky''',
        widget=d_widgets.NumberInput(attrs={"step":5,'class':'spinner','type':'hidden'}))

    def mert_return(self):
        ret=np.exp(np.random.normal(.06,.55))
        if self.round_number not in [1,6,11]:
            prev_val=self.in_previous_rounds()[-1].mert_value
        else:
            prev_val=self.mert_value
        self.mert_value=round((self.mert_A*prev_val*(1+self.rf_rate) + self.mert_B*prev_val*ret)/100,2)
        # print(self.mert_value)
#####################################################################################################3