To install, in the top level directory of a local copy of this repository:

• run pip install -e . to install a symlinked copy that can be updated with a git pull
• or run pip install . to install a local copy that isn't symlinked. I recommend the former as this model is in heavy flux and so you'll probably want recent changes directly from the repo.

The simplest run would be:

import multifil
sarc = multifil.hs.hs()
axial_force = sarc.run()

More complicated runs (workloops, length-velocity calculations) require the modification of sarcomere parameters such as z-line-to-m-line distance and Calcium activation during the run. This is managed by the aws.run.py module through the reading of JSON formatted meta files. The metafiles are specified in aws.metas.py module.

Creating a meta file for a workloop would look like:

# Imports
import numpy as np 
import multifil as mf
# Set run parameters
z_line_rest, z_line_amp, poisson_ratio = 1250, 50, 0.5 
freq, phase = 12, 0.8
act_time, act_rise, act_fall = 20, 3, 3
local_path, s3_path = './', None
# Create time, length, activation traces
time = np.arange(0,200,0.05) #in ms
z_line = mf.aws.metas.zline_workloop(z_line_rest, z_line_amp, freq, time)
activation = mf.aws.metas.actin_permissiveness_workloop(freq, phase, act_time, act_rise, act_fall, time)
# Emit metafile
meta = mf.aws.metas.emit(local_path, s3_path, time, poisson_ratio, z_line=z_line, actin_permissiveness=activation, comment="Example workloop run", phase=phase, frequency=freq)