- 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/Fig9_sim.py
# To reproduce the data needed for Figure 9 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 Fig9_sim.py
import opencor as oc
import numpy as np
# Load the simulation file
simfile='../Cai_experiment1.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
end = 11
# 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", "phosphorylation", "stress","Cai"])
vars = np.reshape(varName, (1, len(varName)))
rows=[int((end)/pointInterval+1)]
# The prefix of the saved output file name
prefilenames = ['simFig9']
for j, prefilename in enumerate(prefilenames):
data.set_ending_point(end)
# Reset states and parameters
simulation.reset(True)
simulation.run()
# Access simulation results
results = simulation.results()
# Grab a specific algebraic variable results
r = np.zeros((rows[j],len(varName)))
r[:,0] = results.voi().values()[-rows[j]:]
r[:,1] = results.algebraic()['outputs/phosphorylation'].values()[-rows[j]:]
r[:,2] = results.algebraic()['outputs/stress'].values()[-rows[j]:]
r[:,3] = results.algebraic()['Cai/Cai'].values()[-rows[j]:]
# 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
