- Author:
- Shelley Fong <sfon036@UoA.auckland.ac.nz>
- Date:
- 2025-07-01 13:36:57+12:00
- Desc:
- Adding files
- Permanent Source URI:
- https://staging.physiomeproject.org/workspace/d41/rawfile/9f2143606a679f2aff90f95e31dc428c77eb46d0/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
# this is for the SOC of the ICC interstitial cell of Cajal
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([int(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 = ''
V = dict()
N_A = 6.022140857e23
SA = 1100 # um2, Kernik iPSC
LCC_density = 6.5 # from Pan [=] 1/um2
numChannels = LCC_density*SA # number of channels per cell
## Define volumes
V_myo = 0.7 # pL, for ICC interstitial cell of Cajal
V_o = 5.182/34.4 # pL, scaled by Luo Rudy cardiomyocyte where ICC vol is 1 pL
V_ER = 0.1
## Define constants
R = 8.314 # unit J / mol / K
T = 310
F = 96485
# dict
V['V_myo'] = V_myo
V['V_o'] = V_o
V['V_ER'] = V_ER
V['N_A'] = N_A
V['F'] = F
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')
# ### 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]))
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.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.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))
