#coding: UTF-8

# Code for model comparison

import ckdsimulation_ln as ckdsim
# you have to import another source code provided as additional file
import random
import math
import numpy as np
from multiprocessing import Process, Queue
import csv
import codecs
import time
import gc

SIM_INT = 4 # Simulation interval (times per year)

#-----------------------------------
# Model comparison
def modelcomp(simtimes, nsize, dec1, dec2, years, bootsize = 10000, initAge = 40,
initeGFR = 70, female = 0.5):

    lifeyear_FTM_total = [] #Fixed Transition probability Model
    lifeyear_eDM_total = [] #eGFR dependent model
    Dialen_FTM_total = [] #Dialysis length
    Dialen_eDM_total = []
    CumDialen_FTM_total = [] #Cumulative dialysis length
    CumDialen_eDM_total = []

    for j in range(0, simtimes): # Simulation carried out multiple times

        # Transition probabilities acquired from input eGFR decline speed
        p, msim = ckdsim.eGFR2tp(nsize = nsize, splesize = bootsize, x1 = dec1, \
        x2 = dec2, years = years, initAge = initAge, initeGFR = initeGFR, \
        female = female)

        # Fixed model virtual cohort using aforementioned transition probailities
        FTMsim = ckdsim.Fixed_Model_sim(coh = nsize, years = years, initAge = initAge,
        initStatus = ckdsim.ckdconv(initeGFR), female = female, \
        x1 = p[0], x2 = p[1], x3 = p[2], x4 = p[3], x5 = p[4], x6 = p[5])

        lifeyear_FTM = []
        lifeyear_eDM = []
        diapt_FTM = 0
        diapt_eDM = 0
        Dialen_FTM = []
        Dialen_eDM = []
        Cumdia_FTM = 0
        Cumdia_eDM = 0

        for i in range(0, nsize):
            # Calculate mean life year
            lifeyear_FTM.append(FTMsim[i][years * SIM_INT - 1][0])
            lifeyear_eDM.append(msim[i][years * SIM_INT - 1][0])

            hdtmp_FTM = []
            hdtmp_eDM = []

            for k in range(0, years * SIM_INT):
                hdtmp_FTM.append(FTMsim[i][k][2] * FTMsim[i][k][3])
                hdtmp_eDM.append(ckdsim.ckdconv(msim[i][k][2]) * msim[i][k][3])

            # Calculate cumulative dialysis period
            Cumdia_FTM = Cumdia_FTM + hdtmp_FTM.count(7) / SIM_INT
            Cumdia_eDM = Cumdia_eDM + hdtmp_eDM.count(7) / SIM_INT

            # Count patients who initiated dialysis
            diapt_FTM = diapt_FTM + int(7 in hdtmp_FTM)
            diapt_eDM = diapt_eDM + int(7 in hdtmp_eDM)

            # Calculate mean dialysis length of each patient
            if diapt_FTM != 0:
                Dialen_FTM.append(Cumdia_FTM / diapt_FTM)
            else:
                Dialen_FTM.append(0)

            if diapt_eDM != 0:
                Dialen_eDM.append(Cumdia_eDM / diapt_eDM)
            else:
                Dialen_eDM.append(0)

        lifeyear_FTM_total.append(np.mean(lifeyear_FTM))
        lifeyear_eDM_total.append(np.mean(lifeyear_eDM))
        Dialen_FTM_total.append(np.mean(Dialen_FTM))
        Dialen_eDM_total.append(np.mean(Dialen_eDM))
        CumDialen_FTM_total.append(Cumdia_FTM)
        CumDialen_eDM_total.append(Cumdia_eDM)

        del msim
        del FTMsim
        gc.collect()

    res = [np.mean(lifeyear_FTM_total), np.std(lifeyear_FTM_total), \
    np.mean(lifeyear_eDM_total), np.std(lifeyear_eDM_total), \
    np.mean(Dialen_FTM_total), np.std(Dialen_FTM_total), \
    np.mean(Dialen_eDM_total), np.std(Dialen_eDM_total), \
    np.mean(CumDialen_FTM_total), np.std(CumDialen_FTM_total), \
    np.mean(CumDialen_eDM_total), np.std(CumDialen_eDM_total)]

    return res

#-----------------------------------
if __name__ == "__main__":

    time1 = time.time()

    re = modelcomp(20, nsize = 10000, dec1 = 4.8, dec2 = 7.5, years = 60, \
    bootsize = 10000, initAge = 35, initeGFR = 75, female = 0.5)
    # input parameters of 1st base case

    time2 = time.time()
    elapsedtime = time2 - time1

    print(re)
    print(elapsedtime)