initial conditions demo

In this demo we show how to use different initial conditions

import pprint
from pathlib import Path

import simcardems

# Create configurations with custom output directory
here = Path(__file__).absolute().parent
outdir = here / "results_IC_demo"

# Specify paths to the geometry that we will use
geometry_path = here / "geometries/slab.h5"
geometry_schema_path = here / "geometries/slab.json"

Please see https://computationalphysiology.github.io/cardiac_geometries/ for more info about the geometries

# Specify path to the initial conditions for the cell model
initial_conditions_path = here / "initial_conditions/fully_coupled_ORdmm_Land/init_5000beats.json"

config = simcardems.Config(
    outdir=outdir,
    geometry_path=geometry_path,
    geometry_schema_path=geometry_schema_path,
    T=1000,
    cell_init_file=initial_conditions_path,
)

# Print current configuration
pprint.pprint(config.as_dict())

runner = simcardems.Runner(config)
runner.solve(T=config.T, save_freq=config.save_freq, show_progress_bar=True)

This will create the output directory results_IC_demo with the following output

results_IC_demo
├── results.h5
├── state.h5

The file state.h5 contains the final state which can be used if you want use the final state as a starting point for the next simulation. The file results.h5 contains the Displacement (\(u\)), active tension (\(T_a\)), voltage (\(V\)) and calcium (\(Ca\)) for each time step. We can also plot the traces using the postprocess module

The final state of this model can be used as the starting point of a new simulation, but is limited to changes in time, pacing rate, disease model and drug effects.

config = simcardems.Config(
    outdir=outdir,
    T=2000,
    load_state=True,
)
runner = simcardems.Runner(config)
runner.solve(T=config.T, save_freq=config.save_freq, show_progress_bar=True)

Analysis and visualization of the results is performed in the same way as described above

simcardems.postprocess.plot_state_traces(outdir.joinpath("results.h5"), "center")