- Author:
- nima <nafs080@aucklanduni.ac.nz>
- Date:
- 2020-09-30 10:07:25+13:00
- Desc:
- SEDML file
- Permanent Source URI:
- http://models.cellml.org/workspace/572/rawfile/59488c15178b09bcb5b11f795383b1435f7b7ef1/SEDML_files/Fig07(22.09).py
# To reproduce the data needed for Figure 4 in associated Physiome paper,
# execute this script in the Python console in OpenCOR. This can be done
# with the following commands at the prompt in the OpenCOR Python console:
#
# In [1]: cd path/to/folder_this_file_is_in
# In [2]: %run Fig05.py
#
import opencor as opencor
# import numpy as np
Na_m = [0.13, 0.1275, 0.125, 0.1175, 0.11, 0.105]
Cl_m = [0.131, 0.1285, 0.126, 0.1185, 0.111, 0.106]
glucose_m = [0.0, 0.005, 0.01, 0.025, 0.04, 0.05]
#######
#Glucose flux
glucose_flux = {}
simulation = opencor.open_simulation("test.sedml")
data = simulation.data()
data.set_ending_point(600)
for i, glu_m in enumerate(glucose_m):
# reset everything in case we are running interactively and have existing results
simulation.reset(True)
simulation.clear_results()
data.constants()["Apical_concentrations/Na_m"] = Na_m[i]
data.constants()["Apical_concentrations/Cl_m"] = Cl_m[i]
data.states()["Basolateral_concentrations/glucose_s"] = 0.001
# data.constants()["Cell_concentration/theta_26"] = 0 # Apical GLUT2 is turned off
data.constants()["Apical_concentrations/glucose_m"] = glu_m
simulation.run()
ds = simulation.results().data_store()
glucose_flux[glu_m] = abs(ds.voi_and_variables()["GLUT2/J_GLUT"].values())
# print((glucose_i))
# for key, value in glucose_i.items():
# print(key, value)
# cache results for plotting
outfile = open("J_GLUT.csv", 'w')
cols = []
for key, item in glucose_flux.items():
outfile.write(str(key) + ",")
cols.append(item)
outfile.write("\n")
for i in range(0, len(cols[0])):
for j in range(0, len(cols)):
outfile.write(str(cols[j][i]) + ",")
outfile.write("\n")
outfile.close()
#######
#Glucose flux n_SGLT*3
glucose_flux = {}
simulation = opencor.open_simulation("test.sedml")
data = simulation.data()
data.set_ending_point(600)
for i, glu_m in enumerate(glucose_m):
# reset everything in case we are running interactively and have existing results
simulation.reset(True)
simulation.clear_results()
data.constants()["Apical_concentrations/Na_m"] = Na_m[i]
data.constants()["Apical_concentrations/Cl_m"] = Cl_m[i]
data.states()["Basolateral_concentrations/glucose_s"] = 0.001
data.constants()["phenomonological_constants/n_SGLT"] = 12e7
# data.constants()["Cell_concentration/theta_26"] = 0 # Apical GLUT2 is turned off
data.constants()["Apical_concentrations/glucose_m"] = glu_m
simulation.run()
ds = simulation.results().data_store()
glucose_flux[glu_m] = abs(ds.voi_and_variables()["GLUT2/J_GLUT"].values())
# print((glucose_i))
# for key, value in glucose_i.items():
# print(key, value)
# cache results for plotting
outfile = open("J_GLUT_n_SGLT.csv", 'w')
cols = []
for key, item in glucose_flux.items():
outfile.write(str(key) + ",")
cols.append(item)
outfile.write("\n")
for i in range(0, len(cols[0])):
for j in range(0, len(cols)):
outfile.write(str(cols[j][i]) + ",")
outfile.write("\n")
outfile.close()
#######
#Glucose flux n_GLUT*3
glucose_flux = {}
simulation = opencor.open_simulation("test.sedml")
data = simulation.data()
data.set_ending_point(600)
for i, glu_m in enumerate(glucose_m):
# reset everything in case we are running interactively and have existing results
simulation.reset(True)
simulation.clear_results()
data.constants()["Apical_concentrations/Na_m"] = Na_m[i]
data.constants()["Apical_concentrations/Cl_m"] = Cl_m[i]
data.states()["Basolateral_concentrations/glucose_s"] = 0.001
data.constants()["A_GLUT2/n_GLUT"] = 126e7
data.constants()["GLUT2/n_GLUT"] = 42e7
# data.constants()["phenomonological_constants/n_SGLT"] = 12e7
# data.constants()["Cell_concentration/theta_26"] = 0 # Apical GLUT2 is turned off
data.constants()["Apical_concentrations/glucose_m"] = glu_m
simulation.run()
ds = simulation.results().data_store()
glucose_flux[glu_m] = abs(ds.voi_and_variables()["GLUT2/J_GLUT"].values())
# print((glucose_i))
# for key, value in glucose_i.items():
# print(key, value)
# cache results for plotting
outfile = open("J_GLUT_n_GLUT.csv", 'w')
cols = []
for key, item in glucose_flux.items():
outfile.write(str(key) + ",")
cols.append(item)
outfile.write("\n")
for i in range(0, len(cols[0])):
for j in range(0, len(cols)):
outfile.write(str(cols[j][i]) + ",")
outfile.write("\n")
outfile.close()
#######
#Glucose flux n_GLUT*3
glucose_flux = {}
simulation = opencor.open_simulation("test.sedml")
data = simulation.data()
data.set_ending_point(600)
for i, glu_m in enumerate(glucose_m):
# reset everything in case we are running interactively and have existing results
simulation.reset(True)
simulation.clear_results()
data.constants()["Apical_concentrations/Na_m"] = Na_m[i]
data.constants()["Apical_concentrations/Cl_m"] = Cl_m[i]
data.states()["Basolateral_concentrations/glucose_s"] = 0.001
data.constants()["A_GLUT2/n_GLUT"] = 126e7
data.constants()["GLUT2/n_GLUT"] = 42e7
data.constants()["phenomonological_constants/n_SGLT"] = 12e7
# data.constants()["Cell_concentration/theta_26"] = 0 # Apical GLUT2 is turned off
data.constants()["Apical_concentrations/glucose_m"] = glu_m
simulation.run()
ds = simulation.results().data_store()
glucose_flux[glu_m] = ds.voi_and_variables()["GLUT2/J_GLUT"].values()
# print((glucose_i))
# for key, value in glucose_i.items():
# print(key, value)
# cache results for plotting
outfile = open("J_GLUT_n_GLUT_SGLT.csv", 'w')
cols = []
for key, item in glucose_flux.items():
outfile.write(str(key) + ",")
cols.append(item)
outfile.write("\n")
for i in range(0, len(cols[0])):
for j in range(0, len(cols)):
outfile.write(str(cols[j][i]) + ",")
outfile.write("\n")
outfile.close()
