- Author:
- nima <nafs080@aucklanduni.ac.nz>
- Date:
- 2021-05-05 10:08:43+12:00
- Desc:
- Run the model for longer time and capture the results at different time in order to make sure the simulation gets to steady state.
- Permanent Source URI:
- https://staging.physiomeproject.org/workspace/648/rawfile/cce2f4422134edf6acdb765a9cdd9ff5e69b3006/Figure06.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 Figure04.py
#
import opencor as opencor
import numpy as np
#different values for gf to decrease the If
K_NaCa = [1.6715, 0.3343]
# Time = {}
# load the reference model
simulation = opencor.open_simulation("HumanSAN_Fabbri_Fantini_Wilders_Severi_2017.sedml")
data = simulation.data()
data.set_ending_point(1.8)
data.set_point_interval(0.001)
simulation.reset(True)
#
#
# simulation.run()
results = np.zeros((13, 1801))
for value in range(len(K_NaCa)):
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = K_NaCa[value]
for i in range (8):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[value] = ds.voi_and_variables()["Membrane/V"].values()
# print(results)
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 0.83575
for i in range(3):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[3] = ds.voi_and_variables()["Membrane/V"].values()
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 3.343
for i in range(42):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[2] = ds.voi_and_variables()["Membrane/V"].values()
for i in range(0,1):
for i in range (3):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[4] = ds.voi_and_variables()["environment/time"].values()
for value in range(len(K_NaCa)):
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = K_NaCa[value]
for i in range (8):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[value+5] = ds.voi_and_variables()["Ca_dynamics/Cai"].values()
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 0.83575
for i in range(3):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[8] = ds.voi_and_variables()["Ca_dynamics/Cai"].values()
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 3.343
for i in range(42):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[7] = ds.voi_and_variables()["Ca_dynamics/Cai"].values()
for value in range(len(K_NaCa)):
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = K_NaCa[value]
for i in range(8):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[value+9] = ds.voi_and_variables()["i_NaCa/i_NaCa"].values()
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 0.83575
for i in range(3):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[12] = ds.voi_and_variables()["i_NaCa/i_NaCa"].values()
simulation.reset(True)
simulation.clear_results()
data.constants()["i_NaCa/K_NaCa"] = 3.343
for i in range(42):
simulation.run()
simulation.clear_results()
simulation.run()
ds = simulation.results().data_store()
results[11] = ds.voi_and_variables()["i_NaCa/i_NaCa"].values()
# print(type(Time))
# print(type(V_m))
# print(V_m)
np.savetxt("Fig06.csv", results[:13].T, fmt='%.4e', delimiter=',')
#
# for k in K_NaCa:
# # reset everything in case we are running interactively and have existing results
# simulation.reset(True)
# simulation.clear_results()
#
# data.constants()["i_NaCa/K_NaCa"] = k
# simulation.run()
# ds = simulation.results().data_store()
# # Time = ds.voi_and_variables()["environment/time"].values()
# V_m[k] = ds.voi_and_variables()["Membrane/V"].values()
#
# # print((V_m))
# # for key, value in glucose_i.items():
# # print(key, value)
#
# simulation.reset(True)
# simulation.clear_results()
#
# Time = {}
# for i in range(0,1):
# simulation.run()
# ds = simulation.results().data_store()
# Time[t[0]] = ds.voi_and_variables()["environment/time"].values()
# print(Time)
#
# # print(type(Time))
# # print(type(V_m))
#
# V_m.update(Time)
# # print(V_m)
#
# Cai={}
# for k in K_NaCa:
# # reset everything in case we are running interactively and have existing results
# simulation.reset(True)
# simulation.clear_results()
#
# data.constants()["i_NaCa/K_NaCa"] = k
# simulation.run()
# ds = simulation.results().data_store()
# # Time = ds.voi_and_variables()["environment/time"].values()
# Cai[k] = ds.voi_and_variables()["Membrane/V"].values()
#
# # print((V_m))
# # for key, value in glucose_i.items():
# # print(key, value)
#
# simulation.reset(True)
# simulation.clear_results()
#
# # cache results for plotting
# outfile = open("Fig06.csv", 'w')
# cols = []
# for key, item in V_m.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()
#
#
#
#
