- Author:
- nima <nafs080@aucklanduni.ac.nz>
- Date:
- 2022-04-05 19:04:25+12:00
- Desc:
- Updated Python Scripts
- Permanent Source URI:
- https://models.physiomeproject.org/workspace/840/rawfile/6e51b0b7b64171080f85f8fd67242c31b9044607/Figure02.py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# matplotlib.use('agg')
import opencor as opencor
# load the reference model
simulation = opencor.open_simulation("../res/model.sedml")
data = simulation.data()
results = dict()
def run_sim(Q_flow):
# reset everything in case we are running interactively and have existing results
simulation.reset(True)
simulation.clear_results()
data.constants()["Apical_concentrations/glucose_m"] = 0.1
data.constants()["Apical_concentrations/Na_m"] = 0.09
data.constants()["Apical_concentrations/Cl_m"] = 0.09
data.constants()["Apical_concentrations/K_m"] = 0.006
data.constants()["A_GLUT2/n_GLUT"] = 2e9
data.constants()["GLUT2/n_GLUT"] = 2e9
data.constants()["phenomonological_constants/n_SGLT"] = 10e7
data.constants()["ENaC/G_ENaC"] = 0.5
data.constants()["Cell_concentration/L_A"] = 6e-5
data.constants()["Cell_concentration/L_B"] = 6e-5
# data.constants()["Blood_concentrations/Q_in"] = 9e-18
data.constants()["Blood_concentrations/Q_in"] = Q_flow
data.set_starting_point(0)
data.set_ending_point(3000)
data.set_point_interval(10)
simulation.run()
ds = simulation.results().data_store()
J_GLUT = ds.voi_and_variables()["GLUT2/J_GLUT"].values()[-1]
J_A_Na = ds.voi_and_variables()["Cell_concentration/J_A_Na"].values()[-1]
J_W_A = ds.voi_and_variables()["Cell_concentration/J_w_A"].values()[-1]
return (J_GLUT, J_A_Na, J_W_A)
if __name__ == '__main__':
# different values for Q_flow
Q_flow = [6e-18, 1e-17, 3e-17, 1e-15]
results1 = run_sim(Q_flow[0])
results2 = run_sim(Q_flow[1])
results3 = run_sim(Q_flow[2])
results4 = run_sim(Q_flow[3])
plt.figure(figsize=(12, 8))
plt.subplot(131)
X1 = 0
X2 = 0.2
Y1 = results1[0]
Y2 = results2[0]
Y3 = results3[0]
Y4 = results4[0]
Y_A = ((Y1 + Y2 + Y3 + Y4) / 4) * 0.001 * 60
ymin, ymax = 0, 6e-11
Y_exp1 = [4.5e-11]
A1 = [5e-12]
A2 = [4.5e-12]
plt.bar(X1, Y_A, yerr=A1, align='center', color='b', alpha=0.5, ecolor='black', capsize=10, width=0.2,
label='Model')
plt.bar(X2, Y_exp1, yerr=A2, align='center', color='r', alpha=0.5, ecolor='black', capsize=10, width=0.2,
label='Experiment')
plt.ylim(ymin, ymax)
plt.tick_params(axis='x', which='major', labelsize=15)
plt.tick_params(axis='y', which='major', labelsize=15)
# plt.xticks(y_pos, objects)
plt.ylabel('Glucose Absorption Rate(mmol/min)', fontsize='14')
plt.xticks([])
plt.legend(loc='best', fontsize='14')
plt.title('A')
plt.subplot(132)
X1 = 0
X2 = 0.2
Y5 = results1[1]
Y6 = results2[1]
Y7 = results3[1]
Y8 = results4[1]
Y_A = ((Y1 + Y2 + Y3 + Y4) / 4) * 0.001 * 60
A3 = [2e-12]
A4 = [7e-12]
Y_B = ((Y5 + Y6 + Y7 + Y8) / 4) * 0.001 * 60
Y_exp2 = [4.2e-11]
ymin, ymax = 0, 8e-11
plt.bar(X1, Y_B, align='center', yerr=A3, color='b', ecolor='black', capsize=10, alpha=0.5, width=0.2,
label='Model')
plt.bar(X2, Y_exp2, align='center', yerr=A4, color='r', ecolor='black', capsize=10, alpha=0.5, width=0.2,
label='Experiment')
plt.ylim(ymin, ymax)
plt.tick_params(axis='x', which='major', labelsize=15)
plt.tick_params(axis='y', which='major', labelsize=15)
# ~ plt.xticks(y_pos, objects)
plt.ylabel('Sodium Absorption Rate(mmol/min)', fontsize='14')
plt.xticks([])
plt.legend(loc='best', fontsize='14')
plt.title('B')
plt.subplot(133)
ymin, ymax = 0, 4e-8
Y9 = -results1[2] * 0.001 * 60
Y10 = -results2[2] * 0.001 * 60
Y11 = -results3[2] * 0.001 * 60
Y12 = -results4[2] * 0.001 * 60
A5 = [3e-9]
A6 = [2e-9]
Y_C = ((Y9 + Y10 + Y11 + Y12) / 4)
print(Y_C)
Y_exp3 = [2e-8]
plt.bar(X1, Y_C, yerr=A5, align='center', color='b', alpha=0.5, ecolor='black', capsize=10, width=0.2,
label='Model')
plt.bar(X2, Y_exp3, yerr=A6, align='center', color='r', alpha=0.5, ecolor='black', capsize=10, width=0.2,
label='Experiment')
plt.ylim(ymin, ymax)
# plt.xticks(y_pos, objects)
plt.ylabel('Water Absorption Rate(mmol/min)', fontsize='14')
plt.tick_params(axis='x', which='major', labelsize=15)
plt.tick_params(axis='y', which='major', labelsize=15)
plt.xticks([])
plt.legend(loc='best', fontsize='14')
plt.title('C')
plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25,
wspace=0.35)
plt.savefig('Figure03.png')
plt.show()
