computation_parallel.py

# This file is used to check individiual segment for the multiple nephron model
# runs the superficial and jux1 - jux5 nephrons
# type 'python3 computation_parallel.py' in the terminal to run
# requires outlet files from previous simulation

from driver import compute
from values import *
from defs import *
import os
import argparse
import multiprocessing
import output
from set_params import set_torq_params
import re

solute = ['Na','K','Cl','HCO3','H2CO3','CO2','HPO4','H2PO4','urea','NH3','NH4','H','HCO2','H2CO2','glu']
compart = ['Lumen','Cell','ICA','ICB','LIS','Bath']
cw=Vref*60e6

parser=argparse.ArgumentParser()
# required input
parser.add_argument('--sex',choices=['male','female'],required = True,type = str,help = 'Sex')
parser.add_argument('--species',choices=['human','rat', 'mouse'],required = True,type = str, help = 'human, rat or mouse model')
parser.add_argument('--segment', choices = ['PT','S3','SDL', 'LDL', 'LAL', 'mTAL','cTAL','DCT', 'CNT', 'CCD', 'OMCD', 'IMCD'], required=True, type=str, help = 'choose segment')
parser.add_argument('--savefile', required=True, type=str, help = 'where to save?')

# optional input
# obesity options
parser.add_argument('--obese', choices = ['Y', 'N'], default = 'N', type = str, help = 'obesity? (Y, N)')
# diabetic options
parser.add_argument('--diabetes',choices = ['Severe','Moderate'],default='Non',type=str,help='diabete status (Severe/Moderate)')
parser.add_argument('--inhibition',choices=['ACE','SGLT2','NHE3-50','NHE3-80','NKCC2-70','NKCC2-100','NCC-70','NCC-100','ENaC-70','ENaC-100','SNB-70','SNB-100', 'HKA-100', 'HKA-100preg'],default = None,type = str,help = 'any transporter inhibition?')
parser.add_argument('--unx',choices=['N','Y'],default = 'N',type = str,help = 'uninephrectomy status')
# pregnancy option
parser.add_argument('--pregnant', choices=['mid','late'], default='non', type=str, help='pregnant female? (mid/late)')
parser.add_argument('--HT',choices=['N','Y'],default = 'N',type = str,help = 'hypertension?')

args=parser.parse_args()

sex = args.sex
species = args.species
sup_or_multi = 'multiple'
segment = args.segment

if segment[-2:] == 'CD':
    print('segment: ' + segment)
    raise Exception('use computation.py for CD segments')

diabete = args.diabetes
inhib = args.inhibition
unx = args.unx
HT = args.HT
obese = args.obese
preg = args.pregnant

# error messages
if diabete != 'Non':
    if preg != 'non':
        raise Exception('pregnant diabetic not done')
elif preg != 'non':
    if sex == 'male':
        raise Exception('pregnant only for female')
    if species[0:3] == 'hum' or species[0:3] == 'mou':
        raise Exception('pregnant model not set up for human or mouse yet')
    if inhib != None:
        raise Exception('pregnant model does not have inhibition set up yet')


if segment == 'PT':
    N = 176
elif segment == 'S3':
    N = 25
else:
    N = 200

file_to_save = args.savefile

if os.path.isdir(file_to_save) == False:
    os.makedirs(file_to_save)

parts = ['sup','jux1','jux2','jux3','jux4','jux5']

def compute_one_segment(sup_or_jux, segment, sex,species,sup_or_multi,diabete,inhib,unx,preg, HT, obese, file_to_save):
    solute = ['Na','K','Cl','HCO3','H2CO3','CO2','HPO4','H2PO4','urea','NH3','NH4','H','HCO2','H2CO2','glu']
    compart = ['Lumen','Cell','ICA','ICB','LIS','Bath']
    cw=Vref*60e6
    #========================================================
    # Proximal convolute tubule
    #========================================================
    if segment == 'PT':
        print('%s PCT start' %(sup_or_jux))
        if species == 'human':
            NPT = 181
        elif species == 'rat':
            NPT = 176
        elif species == 'mouse':
            NPT = 176
        else:
            print(str(species))
            raise Exception('what is species?')

        if sex == 'male':
            filename = './datafiles/PTparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/PTparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/PTparams_F_'+species[0:3]+'.dat'

        pt=compute(NPT,filename,'Broyden',sup_or_jux,diabete,species,sup_or_multi=sup_or_multi,inhibition = inhib,unx = unx, preg = preg, HT = HT, obese = obese)

        Scaletorq = np.zeros(NPT)
        
        for j in range(NPT):
            if pt[j].segment == 'PT':
                TS = 1.3
                scaleT = 1.0
            elif pt[j].segment == 'S3':
                TS = 1.3
                scaleT = 0.5

            #torque-modulated effects                
            PM=pt[j].pres[0]                
            Radref,torqR,torqvm,PbloodPT,torqL,torqd = set_torq_params(pt[j].species,pt[j].sex,pt[j].preg)
                                        
            if pt[j].species == 'rat':
                fac1 = 8.0*visc*(pt[j].vol_init[0]*Vref)*torqL/(Radref**2)
            elif pt[j].species == 'mou':
                fac1 = 8.0*visc*(pt[j].vol_init[0]*Vref)*torqL/(Radref**2)
            elif pt[j].species == 'hum':
                fac1 = 8.0*visc*(pt[j].volref[0]*Vref)*torqL/(Radref**2)
            else:
                print('pt.species: ' + str(pt[j].species))
                raise Exception('what is species?')
            fac2 = 1.0 + (torqL+torqd)/Radref + 0.50*((torqL/Radref)**2)
            TM0= fac1*fac2
                
            RMtorq = torqR*(1.0e0+torqvm*(PM - PbloodPT))

            factor1 = 8.0*visc*(pt[j].vol[0]*Vref)*torqL/(RMtorq**2) 
            factor2 = 1.0 + (torqL+torqd)/RMtorq + 0.50*((torqL/RMtorq)**2)
            Torque = factor1*factor2
                
            Scaletorq[j] = 1.0 + TS*scaleT*(Torque/TM0-1.0)

        output.output_segment_results(pt,sup_or_jux,Scaletorq,file_to_save,NPT)

        print('%s PCT finished.' %(sup_or_jux))
        print('\n')
    
    #========================================================
    # S3
    #========================================================
    elif segment == 'S3':
        print('%s S3 start' %(sup_or_jux))
        if species == 'human':
            NS3 = 20
        elif species == 'rat':
            NS3 = 25
        elif species == 'mouse':
            NS3 = 25
        else:
            print('cell.species: ' + str(species))
            raise Exception('what is species?')
        
        if sex == 'male':
            filename = './datafiles/S3params_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/S3params_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/S3params_F_'+species[0:3]+'.dat'
        s3=compute(NS3,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi=sup_or_multi,inhibition = inhib,unx = unx,preg = preg, HT=HT, obese = obese)

        Scaletorq = np.zeros(NS3)
        
        for j in range(NS3):
            if s3[j].segment == 'PT':
                TS = 1.3
                scaleT = 1.0
            elif s3[j].segment == 'S3':
                TS = 1.3
                scaleT = 0.5

            #torque-modulated effects
                    
            PM=s3[j].pres[0]

            Radref,torqR,torqvm,PbloodPT,torqL,torqd = set_torq_params(s3[j].species,s3[j].sex,s3[j].preg)
                        
            if s3[j].species == 'rat':
                fac1 = 8.0*visc*(s3[j].vol_init[0]*Vref)*torqL/(Radref**2)
            elif s3[j].species == 'mou':
                fac1 = 8.0*visc*(s3[j].vol_init[0]*Vref)*torqL/(Radref**2)
            elif s3[j].species == 'hum':
                fac1 = 8.0*visc*(s3[j].volref[0]*Vref)*torqL/(Radref**2) 
            else:
                print('s3.species: ' + str(s3[j].species))
                raise Exception('what is species?')
            fac2 = 1.0 + (torqL+torqd)/Radref + 0.50*((torqL/Radref)**2)
            TM0= fac1*fac2
                
            RMtorq = torqR*(1.0e0+torqvm*(PM - PbloodPT))

            factor1 = 8.0*visc*(s3[j].vol[0]*Vref)*torqL/(RMtorq**2) 
            factor2 = 1.0 + (torqL+torqd)/RMtorq + 0.50*((torqL/RMtorq)**2)
            Torque = factor1*factor2
            
            Scaletorq[j] = 1.0 + TS*scaleT*(Torque/TM0-1.0)

        output.output_segment_results(s3,sup_or_jux,Scaletorq,file_to_save,NS3)

        print('%s S3 finished.' %(sup_or_jux))
        print('\n')
    
    #========================================================
    # Short descending limb
    #========================================================
    elif segment == 'SDL':
        print('%s SDL start' %(sup_or_jux))
        NSDL = 200
        if species == 'human':
            method = 'Newton'
        elif species == 'rat':
            method = 'Broyden'
        elif species == 'mouse':
            method = 'Broyden'
        else:
            print('species: ' + str(species))
            raise Exception('what is species?')
            
        if sex == 'male':
            filename = './datafiles/SDLparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/SDLparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/SDLparams_F_'+species[0:3]+'.dat'
        #sdl=compute(NSDL,filename,'Broyden',diabete)
        sdl=compute(NSDL,filename,method,sup_or_jux,diabete,species,sup_or_multi=sup_or_multi,inhibition = inhib,unx = unx, preg = preg, HT=HT, obese = obese)
        
        Scaletorq = np.ones(NSDL)
        output.output_segment_results(sdl,sup_or_jux,Scaletorq,file_to_save,NSDL)

        print('%s SDL finished.' %(sup_or_jux))
        print('\n')
    
    #========================================================
    # Long descending limb
    #========================================================
    elif segment == 'LDL':
        if sup_or_jux != 'sup':
            print('%s LDL start' %(sup_or_jux))
            NLDL = 200
            if sex == 'male':
                filename = './datafiles/LDLparams_M_'+species[0:3]+'.dat'
            elif sex == 'female':
                filename = './datafiles/LDLparams_F_'+species[0:3]+'.dat'
            else:
                filename ='./datafiles/LDLparams_F_'+species[0:3]+'.dat'
            ldl=compute(NLDL,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi=sup_or_multi,inhibition = inhib,unx = unx, preg = preg, HT=HT, obese = obese)

            Scaletorq = np.ones(NLDL)
            output.output_segment_results(ldl,sup_or_jux,Scaletorq,file_to_save,NLDL)
            
            print('%s LDL finished.' %(sup_or_jux))
            print('\n')
        
    #========================================================
    # Long ascending limb
    #========================================================
    elif segment == 'LAL':
        if sup_or_jux !='sup':
            print('%s LAL start' %(sup_or_jux))
            NLAL = 200
            if sex == 'male':
                filename = './datafiles/LALparams_M_rat.dat'
            elif sex == 'female':
                filename = './datafiles/LALparams_F_rat.dat'
            else:
                filename ='./datafiles/LALparams_F_rat.dat'
            lal=compute(NLAL,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi=sup_or_multi,inhibition = inhib,unx = unx, preg = preg, HT=HT, obese = obese)

            Scaletorq = np.ones(NLAL)
            output.output_segment_results(lal,sup_or_jux,Scaletorq,file_to_save,NLAL)

            print('%s LAL finished.' %(sup_or_jux))
            print('\n')

    #========================================================
    # Medulla thick ascending limb
    #========================================================
    elif segment == 'mTAL':
        print('%s mTAL start' %(sup_or_jux))
        NmTAL = 200
        if sex == 'male':
            filename = './datafiles/mTALparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/mTALparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/mTALparams_F_'+species[0:3]+'.dat'
        mtal=compute(NmTAL,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi,inhib,unx = unx, preg = preg, HT=HT, obese = obese)

        Scaletorq = np.ones(NmTAL)
        
        output.output_segment_results(mtal,sup_or_jux,Scaletorq,file_to_save,NmTAL)

        print('%s mTAL finished.' %(sup_or_jux))
        print('\n')

    #========================================================
    # Cortex thick ascending limb
    #========================================================
    elif segment == 'cTAL':
        print('%s cTAL start' %(sup_or_jux))
        NcTAL = 200
        if sex == 'male':
            filename = './datafiles/cTALparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/cTALparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/cTALparams_F_'+species[0:3]+'.dat'
        ctal=compute(NcTAL,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi,inhib,unx = unx, preg = preg, HT=HT, obese = obese)

        Scaletorq = np.ones(NcTAL)
        
        output.output_segment_results(ctal,sup_or_jux,Scaletorq,file_to_save,NcTAL)

        print('%s cTAL finished.' %(sup_or_jux))
        print('\n')
    
    #========================================================
    # Distal convoluted tubule
    #========================================================
    elif segment == 'DCT':
        print('%s DCT start' %(sup_or_jux))
        NDCT = 200
        if sex == 'male':
            filename = './datafiles/DCTparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/DCTparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/DCTparams_F_'+species[0:3]+'.dat'
        dct=compute(NDCT,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi,inhib,unx = unx, preg = preg, HT=HT, obese = obese)

        Scaletorq = np.ones(NDCT)
        
        output.output_segment_results(dct,sup_or_jux,Scaletorq,file_to_save,NDCT)

        print('%s DCT finished.'%(sup_or_jux))
        print('\n')
    
    #========================================================
    # Connecting tubule
    #========================================================
    elif segment == 'CNT':
        print('%s CNT start' %(sup_or_jux))
        NCNT = 200
        if sex == 'male':
            filename = './datafiles/CNTparams_M_'+species[0:3]+'.dat'
        elif sex == 'female':
            filename = './datafiles/CNTparams_F_'+species[0:3]+'.dat'
        else:
            filename ='./datafiles/CNTparams_F_'+species[0:3]+'.dat'
        cnt=compute(NCNT,filename,'Newton',sup_or_jux,diabete,species,sup_or_multi,inhib,unx = unx, preg = preg, HT=HT, obese = obese)

        Scaletorq = np.ones(NCNT)
        
        output.output_segment_results(cnt,sup_or_jux,Scaletorq,file_to_save,NCNT)

        print('%s CNT finished.'%(sup_or_jux))
        print(sup_or_jux+' finished.')
        print('\n')
    else:
        print('segment: ' + segment)
        raise Exception(segment + ' not characterized in computation_parallel.py')

def multiprocessing_func_segment(sup_or_jux):
    compute_one_segment(sup_or_jux, segment, sex, species, sup_or_multi, diabete, inhib, unx, preg, HT, obese, file_to_save)

if __name__ == '__main__':

    pool = multiprocessing.Pool()
    pool.map(multiprocessing_func_segment,parts)
    pool.close()