- Author:
- WeiweiAi <wai484@aucklanduni.ac.nz>
- Date:
- 2021-09-30 13:14:32+13:00
- Desc:
- fix the typos and tables in doc
- Permanent Source URI:
- https://models.cellml.org/workspace/6bb/rawfile/5766fc294ca1fb80e47e776c78d754cad7f5fc7f/Simulation/src/Fig11A_sim.py
# To reproduce the data needed for Figure 11A in associated original 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 Fig11A_sim.py
import opencor as oc
import numpy as np
# Load the simulation file
simfile='../Single_stim_experiment.sedml'
simulation = oc.open_simulation(simfile)
# The data object houses all the relevant information
# and pointers to the OpenCOR internal data representations
data = simulation.data()
# Set the experiments
Vholding, t_ss = -80, 0
duration = 1
Nai=[16.55]
Cai_init = 130e-6
inhPump = 1
Vtest = 0
# Define the interval of interest for this simulation experiment
start, pointInterval = 0, 0.001
data.set_starting_point(start)
data.set_point_interval(pointInterval)
# Data to save
varName = np.array(["time", "Cai", "stress"])
vars = np.reshape(varName, (1, len(varName)))
# start to save when the test voltage returns to holding
rows=int((duration+19)/pointInterval+1)
r = np.zeros((rows,len(varName)))
# The prefix of the saved output file name
prefilenames = ['simFig11A']
for j, prefilename in enumerate(prefilenames):
data.set_ending_point(t_ss+duration+19)
for k, iNai in enumerate(Nai):
# Reset states and parameters
simulation.reset(True)
# Set constant parameter values
data.constants()['Vstim_para/V_actHolding'] = Vholding
data.constants()['Vstim_para/V_actTest'] = Vtest
data.constants()['Vstim_para/t_act'] = duration
data.constants()['Vstim_para/t_ss'] = t_ss
data.constants()['control_para/Nai'] = iNai
data.constants()['control_para/inhPump'] = inhPump
data.states()['outputs/Cai'] = Cai_init
simulation.run()
# Access simulation results
results = simulation.results()
# Grab a specific algebraic variable results
r[:,0] = results.voi().values()[-rows:]
r[:,1] = results.states()['outputs/Cai'].values()[-rows:]
r[:,2] = results.algebraic()['outputs/stress'].values()[-rows:]
# clear the results except the last run
simulation.clear_results()
# Save the simulation result of the last run
filename='../simulatedData/%s.csv' % (prefilename)
np.savetxt(filename, vars, fmt='%s',delimiter=",")
with open(filename, "ab") as f:
np.savetxt(f, r, delimiter=",")
f.close
