# -*- coding: utf-8 -*-
"""
Created on Fri Oct 15 16:52:39 2021

@author: mvessen
"""

import pandas as pd
import biogeme.database as db
import biogeme.biogeme as bio
import biogeme.models as models
import biogeme.expressions as ex
import numpy as np
import time
import warnings
import random



            if run_biogeme:               
                #maak biogeme database
                subdf["CHOICE"] = subdf["I"]
                subdf["WEIGHT"] = subdf[weegfactor] / subdf[weegfactor].mean()
                subdf.drop(columns=["H","I","J"],inplace=True) #verwijder kolommen die niet worden gebruikt in de schatting
                database = db.Database("octavius_"+keten_str,subdf)
                globals().update(database.variables)

                #maak benodigde parameters aan
                locatie_vars = zone_variabelen + trip_variabelen
                tot_vars = locatie_vars + pers_variabelen
                parameter_dic = {}
                for var in tot_vars: 
                    if var in {"ARB_TOT"}: 
                        parameter_dic[var] = ex.Beta("B_"+var,1,None,None,1)
                    elif var in {"INW","LLP_TOT"}: parameter_dic[var] = ex.exp(ex.Beta("B_"+var,0,None,None,0))
                    else: parameter_dic[var] = ex.Beta("B_"+var,0,None,None,0)
                    

                print("aantal kolommen:",len(subdf.columns))
                print("aantal variabelen:",len(parameter_dic))
                print(list(parameter_dic.keys()))

                #maak kostenfuncties
                u_functions = {}
                av = {}
                for i in pc4_zones:
                    terms1 = []
                    terms2 = []
                    for var in tot_vars: 
                        if var in {"LLP_BAS","LLP_MID","LLP_MBO","LLP_HO","LLP_TOT","ARB_OND","ARB_IND","ARB_KAN","ARB_WIN","ARB_OVE","ARB_TOT","INW"}:   
                            terms2.append(parameter_dic[var] * db.Variable(var+str(i)))
                        else: terms1.append(parameter_dic[var] * db.Variable(var+str(i)))

                    u_functions[i] = sum(terms1) + ex.log(sum(terms2))
                    av[i] = db.Variable("AV"+str(i))
               
                #maak logprob model
                print("start biogeme...")    
                logprob = models.loglogit(u_functions,av,CHOICE)
                formulas = {'loglike':logprob,'weight':WEIGHT}
                biogeme = bio.BIOGEME(database,formulas)
                biogeme.modelName = "octavius_"+keten_str+"_"+str(max_waarnemingen)+"_"+str(grenswaarde_reistijd)

                # Schat parameters
                results = biogeme.estimate(saveIterations=True)
                biogeme.createLogFile()

                #Schrijf parameters weg naar tekst bestand
                pandasResults = results.getEstimatedParameters()