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run_Cm_lookups.py
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Wed, May 22, 12:35

run_Cm_lookups.py
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# -*- coding: utf-8 -*-
# @Author: Theo Lemaire
# @Email: theo.lemaire@epfl.ch
# @Date: 2020-08-05 17:42:12
# @Last Modified by: Theo Lemaire
# @Last Modified time: 2020-08-05 20:31:11
''' Create Cm lookup table. '''
import os
import logging
import numpy as np
from PySONIC.utils import logger, isIterable, alert
from PySONIC.core import BilayerSonophore, Batch, Lookup, AcousticDrive
from PySONIC.parsers import MechSimParser
@alert
def computeCmLookup(bls, fref, Aref, mpi=False, loglevel=logging.INFO):
descs = {'f': 'US frequencies', 'A': 'US amplitudes'}
# Populate reference vectors dictionary
refs = {
'f': fref, # Hz
'A': Aref # Pa
}
# Check validity of all reference vectors
for key, values in refs.items():
if not isIterable(values):
raise TypeError(f'Invalid {descs[key]} (must be provided as list or numpy array)')
if not all(isinstance(x, float) for x in values):
raise TypeError(f'Invalid {descs[key]} (must all be float typed)')
if len(values) == 0:
raise ValueError(f'Empty {key} array')
if key == 'f' and min(values) <= 0:
raise ValueError(f'Invalid {descs[key]} (must all be strictly positive)')
if key == 'A' and min(values) < 0:
raise ValueError(f'Invalid {descs[key]} (must all be positive or null)')
# Get references dimensions
dims = np.array([x.size for x in refs.values()])
# Create simulation queue
drives = AcousticDrive.createQueue(fref, Aref)
queue = [[drive, 0.] for drive in drives]
# Run simulations and populate outputs
logger.info(f'Starting Cm simulation batch for {bls}')
batch = Batch(bls.getRelCmCycle, queue)
rel_Cm_cycles = batch(mpi=mpi, loglevel=loglevel)
# Make sure outputs size matches inputs dimensions product
nout, nsamples = len(rel_Cm_cycles), rel_Cm_cycles[0].size
assert nout == dims.prod(), 'Number of outputs does not match number of combinations'
dims = np.hstack([dims, nsamples])
refs['t'] = np.linspace(0., 1., nsamples)
# Reshape effvars into nD arrays and add them to lookups dictionary
logger.info('Reshaping output into lookup table')
rel_Cm_cycles = np.array(rel_Cm_cycles).reshape(dims)
# Construct and return lookup object
return Lookup(refs, {'Cm_rel': rel_Cm_cycles})
def main():
parser = MechSimParser(outputdir='.')
parser.addTest()
parser.defaults['radius'] = 32.0 # nm
parser.defaults['freq'] = np.array([20., 100., 500., 1e3, 2e3, 3e3, 4e3]) # kHz
parser.defaults['amp'] = np.insert(
np.logspace(np.log10(0.1), np.log10(600), num=50), 0, 0.0) # kPa
args = parser.parse()
logger.setLevel(args['loglevel'])
# Model
a = args['radius'][0] # m
Cm0 = 1e-2 # F/m2
Qm0 = 0.0 # C/m2
bls = BilayerSonophore(a, Cm0, Qm0)
lookup_fpath = bls.Cm_lkp_filepath
# Batch inputs
inputs = [args[x] for x in ['freq', 'amp']]
# Adapt inputs and output filename if test case
if args['test']:
for i, x in enumerate(inputs):
if x is not None and x.size > 1:
inputs[i] = np.array([x.min(), x.max()])
fcode, fext = os.path.splitext(lookup_fpath)
lookup_fpath = f'{fcode}_test{fext}'
# Check if lookup file already exists
if os.path.isfile(lookup_fpath):
logger.warning(
f'"{lookup_fpath}" file already exists and will be overwritten. Continue? (y/n)')
user_str = input()
if user_str not in ['y', 'Y']:
logger.error('Cm-lookup creation canceled')
return
# Compute lookup
lkp = computeCmLookup(bls, *inputs, mpi=args['mpi'], loglevel=args['loglevel'])
logger.info(f'Generated Cm-lookup: {lkp}')
# Save lookup in PKL file
logger.info(f'Saving {bls} Cm-lookup in file: "{lookup_fpath}"')
lkp.toPickle(lookup_fpath)
if __name__ == '__main__':
main()

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