Location: Funny current channel knowledge page @ 3750deed6e38 / parameter_finder / find_BG_parameters.py

Author:
Shelley Fong <sfon036@UoA.auckland.ac.nz>
Date:
2024-08-19 14:20:55+12:00
Desc:
Changing rdf link
Permanent Source URI:
https://models.physiomeproject.org/workspace/b8b/rawfile/3750deed6e3853e3a563bf0b3833bbe59a16de5e/parameter_finder/find_BG_parameters.py

# This script calculates the bond graph parameters for all reactions of the
# a given module. Specify the directory.
# based on SERCA model of Pan et al, which is based on Tran et al. (2009).
# Parameters calculated in module's directory, by using the kinetic
# parameters and stoichiometric matrix.

# return W from kinetic_parameters

import os
import csv
import json
import math
import numpy as np
import sympy
from sympy import Matrix, S, nsimplify
from scipy.linalg import null_space
from fractions import Fraction


def read_IDs(path):
    data = []
    with open(path, 'r') as f:
        reader = csv.reader(f)
        for row in reader:
            data.append(row[0])
        f.close()
    return data


def load_matrix(stoich_path):
    matrix = []
    with open(stoich_path, 'r') as f:
        reader = csv.reader(f, delimiter=',')
        for row in reader:
            matrix.append([float(r) for r in row])
        f.close()
    return matrix


# def rational_nullspace(A, max_denom = 10):
#     v = null_space(A)
#     vFrac = [[Fraction(num).limit_denominator(max_denominator=max_denom) for num in row] for row in v]
#
#     vRat = [] #np.zeros([len(vFrac),len(vFrac[0])])
#     if not v.any():
#         return []
#     all_denom = [[res.denominator for res in row] for row in vFrac]
#     if all_denom.count(all_denom[0]) == len(all_denom):# identical
#         for row in vFrac:
#             largest_denom = max([res.denominator for res in row])
#             vRat.append( [vi.numerator for vi in row] )
#         return vRat
#     else:
#         print('denominators for fractions of rational nullspace are not identical')
#         return []

if __name__ == "__main__":

    ## booleans
    write_parameters_file = True
    include_constraints = True
    include_type2_reactions = True

    ## Set directories
    current_dir = os.getcwd()
    data_dir = current_dir + '\data'
    output_dir = current_dir + '\output'
    modname = os.path.dirname(current_dir).split('\\')[-1].split('BG_')[-1]
    if not os.path.exists(output_dir):
        os.mkdir(output_dir)

    if ('beta1' in current_dir) and False:
        matstr = '_withR_LR_scheme4'
    else:
        matstr = ''

    ## Define constants
    R = 8.314 # unit    J / mol / K
    T = 310
    F = 96485
    
    cNao = 140 # unit    mM
    cNai = 10 # unit    mM
    cKo = 5.4
    cKi = 145
    N_A = 6.022e23
    A_cap = 1.534e-4 # Unit    cm ^ 2
    SA = 1100 # um2, Kernik iPSC
    Cm = 60e-6 # [=] uF

    funny_density = 6 # GUESS from Pan [=] 1/um2
    numChannels = funny_density*SA # number of channels per cell

    V_myo = 3.71  # pL, for Kernik iPSCell
    V_o = 0.12*V_myo/0.88 # Using cleft volume calc from LRd
    V = dict()
    V['V_myo'] = V_myo
    V['V_o'] = V_o
    V['F'] = F
    V['R'] = R
    V['T'] = T
    V['Cm'] = Cm
    V['N_A'] = N_A
    V['A_cap'] = A_cap
    V['cNao'] = cNao
    V['cNai'] = cNai
    V['cKi'] = cKi
    V['cKo'] = cKo
    V['numChannels'] = numChannels

    ## Load forward matrix
    if include_type2_reactions:
        stoich_path = data_dir + '\\all_forward_matrix%s.txt' % matstr
    else:
        stoich_path = data_dir + '\\all_noType2_forward_matrix.txt'

    N_f = load_matrix(stoich_path)

    ## Load reverse matrix
    if include_type2_reactions:
        stoich_path = data_dir + '\\all_reverse_matrix%s.txt' % matstr
    else:
        stoich_path = data_dir + '\\all_noType2_reverse_matrix.txt'

    N_r = load_matrix(stoich_path)

    N_fT = np.transpose(N_f)
    N_rT = np.transpose(N_r)

    ## Calculate stoichiometric matrix
    # I matrix to align with placement of kappa down the column.
    # x-axis of stoich matrix (R1a, R1b etc) coincides with the kp km of that kinetic reaction
    N = [[N_r[j][i] - N_f[j][i] for i in range(len(N_f[0]))] for j in range(len(N_f))]
    N_T = [[N_rT[j][i] - N_fT[j][i] for i in range(len(N_fT[0]))] for j in range(len(N_fT))]

    num_rows = len(N)
    num_cols = len(N[0])
    dims = dict()
    dims['num_rows'] = num_rows
    dims['num_cols'] = num_cols

    I = np.identity(num_cols)

    M = np.append(np.append(I, N_fT, 1), np.append(I, N_rT, 1), 0)

    func = __import__('kinetic_parameters_%s' % modname)
    [k_kinetic, N_cT, K_C, W] = func.kinetic_parameters(M, include_type2_reactions, dims, V)
    if not include_constraints:
        N_cT = []

    try:
        M = np.append(M, N_cT, 0)
        k = np.append(k_kinetic, K_C, 0)
    except:
        k = k_kinetic

    # Calculate bond graph constants from kinetic parameters
    # Note: units of kappa are fmol/s, units of K are fmol^-1
    lambda_expo = np.matmul(np.linalg.pinv(M), [math.log(ik) for ik in k])
    lambdaW = [math.exp(l) for l in lambda_expo]

    # Check that kinetic parameters are reproduced by bond graph parameters
    k_est = np.matmul(M, [math.log(k) for k in lambdaW])
    k_est = [math.exp(k) for k in k_est]
    diff = [(k[i] - k_est[i]) / k[i] for i in range(len(k))]

    error = np.sum([abs(d) for d in diff])

    # Checks
    N_rref = sympy.Matrix(N).rref()
    R = nsimplify(Matrix(N), rational=True).nullspace()  # rational_nullspace(N, max_denom=len(N[0]))
    if R:
        R = np.transpose(np.array(R).astype(np.float64))[0]
    # Check that there is a detailed balance constraint
    Z = nsimplify(Matrix(M), rational=True).nullspace()  # rational_nullspace(M, 2)
    if Z:
        Z = np.transpose(np.array(Z).astype(np.float64))[0]

    kf = k_kinetic[:num_cols]
    kr = k_kinetic[num_cols:]
    K_eq = [kf[i] / kr[i] for i in range(len(kr))]
    try:
        zero_est = np.matmul(np.transpose(R), K_eq)
        zero_est_log = np.matmul(np.transpose(R), [math.log(k) for k in K_eq])
    except:
        print('undefined R nullspace')

    # if not R_mat:
    #     warning('R_mat is empty: matrix is full rank')

    lambdak = [lambdaW[i] / W[i] for i in range(len(W))]
    kappa = lambdak[:len(N[0])]
    K = lambdak[len(N[0]):]

    rxnID = read_IDs('data\\rxnID.txt')
    Kname = read_IDs('data\\Kname.txt')
    zname = read_IDs('data\\zname.txt')
    zval = read_IDs('data\\z_value.txt')

    # ### print outputs ###
    for ik in range(len(kappa)):
        print('var kappa_%s: fmol_per_sec {init: %g, pub: out};' % (rxnID[ik], kappa[ik]))
    for ik in range(len(Kname)):
        print('var K_%s: per_fmol {init: %g, pub: out};' % (Kname[ik], K[ik]))
    for ik in range(len(zname)):
        print('var %s: dimensionless {init: %s, pub: out};' % (zname[ik], zval[ik]))

    file = open(output_dir + '/all_parameters_out.json', 'w')
    data = {"K": K, "kappa": kappa, "k_kinetic": k_kinetic}
    json.dump(data, file)

    cellmlfilepath = os.getcwd() + '\\output\\TEMP.cellml.txt'
    with open(cellmlfilepath, 'w') as cid:
        cid.write('def model individual_%s as\n def import using "units_and_constants/units_BG.cellml" for\n\
        unit mM using unit mM;\nunit fmol using unit fmol;\nunit per_fmol using unit per_fmol;\n\
        unit J_per_mol using unit J_per_mol;\nunit fmol_per_sec using unit fmol_per_sec;\n\
        unit C_per_mol using unit C_per_mol;\n  unit J_per_C using unit J_per_C;\n\
        unit microm3 using unit microm3;\n  unit fF using unit fF;\n\
        unit fC using unit fC;\n  unit fA using unit fA;\n\
        unit per_second using unit per_second;\n  unit millivolt using unit millivolt;\n\
        unit per_sec using unit per_sec;\n  unit J_per_K_per_mol using unit J_per_K_per_mol;\n\
        unit fmol_per_L using unit fmol_per_L;\n  unit fmol_per_L_per_sec using unit fmol_per_L_per_sec;\n\
        unit per_sec_per_fmol_per_L using unit per_sec_per_fmol_per_L;\n  unit uM using unit uM;\n\
        unit mM_per_sec using unit mM_per_sec;\n  unit uM_per_sec using unit uM_per_sec;\n\
        unit pL using unit pL;\n  unit m_to_u using unit m_to_u;\n enddef;\n' % (modname))
        cid.write('def import using "units_and_constants/constants_BG.cellml" for\n\
            comp constants using comp constants;\nenddef;\n\n')
        cid.write("    def comp environment as\n\
    var time: second {pub: out};\n\
    // initial values\n")
        for Kn in Kname:
            cid.write('var q_%s: fmol {init: 1e-888, pub: out};\n' % (Kn))
        # cid.write('// Global value\n')
        # for Kn in Kname:
        #     cid.write('var q_%s: fmol {pub: out};\n'%Kn)
        cid.write('// From submodule\n')
        for rx in rxnID:
            cid.write('var v_%s: fmol_per_sec {pub: in};\n' % (rx))
        for Kn in Kname:
            cid.write('ode(q_%s, time) = vvv;\n' % (Kn))
        cid.write('enddef;\n\n')
        cid.write('def comp %s_parameters as\n' % (modname))
        for ik in range(len(kappa)):
            cid.write('var kappa_%s: fmol_per_sec {init: %g, pub: out};\n' % (rxnID[ik], kappa[ik]))
        for ik in range(len(Kname)):
            cid.write('var K_%s: per_fmol {init: %g, pub: out};\n' % (Kname[ik], K[ik]))
        cid.write('enddef;\n')

        cid.write('def comp %s as\n' % (modname))
        cid.write('        var time: second {pub: in};\n\
        var R: J_per_K_per_mol {pub: in};\n\
        var T: kelvin {pub: in};\n\
        // parameters\n')
        for ik in range(len(kappa)):
            cid.write('var kappa_%s: fmol_per_sec {pub: in};\n' % (rxnID[ik]))
        for ik in range(len(Kname)):
            cid.write('var K_%s: per_fmol {pub: in};\n' % (Kname[ik]))

        cid.write('// Input from global environment\n')
        for Kn in Kname:
            cid.write('var q_%s: fmol {pub: in};\n' % Kn)
        # cid.write('// Output to global environment\n')
        # for Kn in Kname:
        #     # cid.write('var q_%s: fmol {init: 1e-16, pub: out};\n'%(Kn))
        #     cid.write('var v_%s: fmol_per_sec {pub: out};\n'%(Kn))
        cid.write('// Constitutive parameters\n')
        for Kn in Kname:
            cid.write('var mu_%s: J_per_mol;\n' % (Kn))
        for rx in rxnID:
            cid.write('var v_%s: fmol_per_sec {pub: out};\n' % (rx))
        for Kn in Kname:
            cid.write('mu_%s = R*T*ln(K_%s*q_%s);\n' % (Kn, Kn, Kn))
        for rx in rxnID:
            cid.write('v_%s = ppp;\n' % (rx))
        # for Kn in Kname:
        #     cid.write('v_%s = rrr;\n' %Kn)
        # for Kn in Kname:
        #     cid.write('ode(q_%s, time) = qqq;\n'%Kn)
        cid.write('enddef;\n')

        cid.write('def map between environment and %s for\n' % modname)
        cid.write('vars time and time;\n')
        for Kn in Kname:
            cid.write('vars q_%s and q_%s;\n' % (Kn, Kn))
        for rx in rxnID:
            cid.write('vars v_%s and v_%s;\n' % (rx, rx))
        cid.write('enddef;\n')
        cid.write('def map between %s and %s_parameters for\n' % (modname, modname))
        for ik in rxnID:
            cid.write('vars kappa_%s and kappa_%s;\n' % (ik, ik))
        for mod in Kname:
            cid.write('vars K_%s and K_%s;\n' % (mod, mod))
        cid.write('enddef;\n')
        cid.write('def map between constants and %s for\n' % modname)
        cid.write('vars R and R;\n vars T and T;\n')
        cid.write('enddef;\n')
        cid.write('enddef;\n')
        cid.close()

    print('error =', (error))