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test_basic.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Author: Theo Lemaire
# @Date: 2017-06-14 18:37:45
# @Email: theo.lemaire@epfl.ch
# @Last Modified by: Theo Lemaire
# @Last Modified time: 2017-08-28 14:18:56
''' Test the basic functionalities of the package. '''
import logging
import inspect
import numpy as np
from PointNICE.utils import load_BLS_params
from PointNICE import BilayerSonophore, channels, SolverElec, SolverUS
from PointNICE.solvers import detectSpikes, titrateEStim, titrateAStim
from PointNICE.constants import *
# Set logging options
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%d/%m/%Y %H:%M:%S:')
logger = logging.getLogger('PointNICE')
logger.setLevel(logging.DEBUG)
# List of implemented neurons
neurons = []
for _, obj in inspect.getmembers(channels):
if inspect.isclass(obj) and isinstance(obj.name, str):
if obj.name != 'LeechT':
neurons.append(obj)
def test_MECH():
''' Maximal negative and positive deflections of the BLS structure for a specific
sonophore size, resting membrane properties and stimulation parameters. '''
logger.info('Starting test: Mechanical simulation')
# BLS geometry and parameters
geom = {"a": 32e-9, "d": 0.0e-6}
params = load_BLS_params()
# Create BLS instance
Fdrive = 350e3 # Hz
Cm0 = 1e-2 # membrane resting capacitance (F/m2)
Qm0 = -80e-5 # membrane resting charge density (C/m2)
bls = BilayerSonophore(geom, params, Fdrive, Cm0, Qm0)
# Run mechanical simulation
Adrive = 100e3 # Pa
Qm = 50e-5 # C/m2
bls.runMech(Fdrive, Adrive, Qm)
_, y, _ = bls.runMech(Fdrive, Adrive, Qm)
# Check validity of deflection extrema
Z, _ = y
Zlast = Z[-NPC_FULL:]
Zmin, Zmax = (Zlast.min(), Zlast.max())
logger.info('Zmin = %.2f nm, Zmax = %.2f nm', Zmin * 1e9, Zmax * 1e9)
Zmin_ref, Zmax_ref = (-0.116e-9, 5.741e-9)
assert np.abs(Zmin - Zmin_ref) < 1e-12, 'Unexpected BLS compression amplitude'
assert np.abs(Zmax - Zmax_ref) < 1e-12, 'Unexpected BLS expansion amplitude'
logger.info('Passed test: Mechanical simulation')
def test_resting_potential():
''' Neurons membrane potential in free conditions should stabilize to their
specified resting potential value. '''
conv_err_msg = ('{} neuron membrane potential in free conditions does not converge to '
'stable value (gap after 20s: {:.2e} mV)')
value_err_msg = ('{} neuron steady-state membrane potential in free conditions differs '
'significantly from specified resting potential (gap = {:.2f} mV)')
logger.info('Starting test: neurons in free conditions')
# Initialize solver
solver = SolverElec()
for neuron_class in neurons:
# Simulate each neuron in free conditions
neuron = neuron_class()
_, y, _ = solver.run(neuron, Astim=0.0, tstim=20.0, toffset=0.0)
Vm_free, *_ = y
# Check membrane potential convergence
Vm_free_last, Vm_free_beforelast = (Vm_free[-1], Vm_free[-2])
Vm_free_conv = Vm_free_last - Vm_free_beforelast
assert np.abs(Vm_free_conv) < 1e-5, conv_err_msg.format(neuron.name, Vm_free_conv)
# Check membrane potential convergence to resting potential
Vm_free_diff = Vm_free_last - neuron.Vm0
assert np.abs(Vm_free_diff) < 0.1, value_err_msg.format(neuron.name, Vm_free_diff)
logger.info('Passed test: neurons in free conditions')
def test_ESTIM():
''' Threshold E-STIM amplitude and needed to obtain an action potential and response latency
should match reference values. '''
Athr_err_msg = ('{} neuron threshold amplitude for excitation does not match reference value'
'(gap = {:.2f} mA/m2)')
latency_err_msg = ('{} neuron latency for excitation at threshold amplitude does not match '
'reference value (gap = {:.2f} ms)')
logger.info('Starting test: E-STIM titration')
# Initialize solver
solver = SolverElec()
Arange = (0.0, 2 * TITRATION_ESTIM_A_MAX) # mA/m2
# Stimulation parameters
tstim = 100e-3 # s
toffset = 50e-3 # s
# Reference values
Athr_refs = {'FS': 6.91, 'LTS': 1.54, 'RS': 5.03, 'LeechT': 5.54, 'RE': 3.61, 'TC': 4.05}
latency_refs = {'FS': 101.00e-3, 'LTS': 128.56e-3, 'RS': 103.81e-3, 'LeechT': 20.22e-3,
'RE': 148.50e-3, 'TC': 63.46e-3}
for neuron_class in neurons:
# Perform titration for each neuron
neuron = neuron_class()
print(neuron.name, 'neuron titration')
(Athr, t, y, _, latency) = titrateEStim(solver, neuron, Arange, tstim, toffset,
PRF=None, DF=1.0)
Vm = y[0, :]
# Check that final number of spikes is 1
n_spikes, _, _ = detectSpikes(t, Vm, SPIKE_MIN_VAMP, SPIKE_MIN_DT)
assert n_spikes == 1, 'Number of spikes after titration should be exactly 1'
# Check threshold amplitude
Athr_diff = Athr - Athr_refs[neuron.name]
assert np.abs(Athr_diff) < 0.1, Athr_err_msg.format(neuron.name, Athr_diff)
# Check response latency
lat_diff = (latency - latency_refs[neuron.name]) * 1e3
assert np.abs(lat_diff) < 1.0, latency_err_msg.format(neuron.name, lat_diff)
logger.info('Passed test: E-STIM titration')
def test_ASTIM():
''' Threshold A-STIM amplitude and needed to obtain an action potential and response latency
should match reference values. '''
Athr_err_msg = ('{} neuron threshold amplitude for excitation does not match reference value'
'(gap = {:.2f} kPa)')
latency_err_msg = ('{} neuron latency for excitation at threshold amplitude does not match '
'reference value (gap = {:.2f} ms)')
logger.info('Starting test: A-STIM titration')
# BLS geometry and parameters
geom = {"a": 32e-9, "d": 0.0e-6}
params = load_BLS_params()
# Stimulation parameters
Fdrive = 350e3 # Hz
tstim = 50e-3 # s
toffset = 30e-3 # s
Arange = (0.0, 2 * TITRATION_ASTIM_A_MAX) # Pa
# Reference values
Athr_refs = {'FS': 38.67e3, 'LTS': 24.80e3, 'RS': 51.17e3, 'RE': 46.36e3, 'TC': 23.24e3,
'LeechT': None}
latency_refs = {'FS': 63.72e-3, 'LTS': 61.92e-3, 'RS': 62.52e-3, 'RE': 79.20e-3, 'TC': 68.53e-3,
'LeechT': None}
# Titration for each neuron
for neuron_class in neurons:
# Initialize neuron
neuron = neuron_class()
print(neuron.name, 'neuron titration')
# Initialize solver
solver = SolverUS(geom, params, neuron, Fdrive)
# Perform titration
(Athr, t, y, _, latency) = titrateAStim(solver, neuron, Fdrive, Arange, tstim, toffset,
PRF=None, DF=1.0)
Qm = y[2]
# Check that final number of spikes is 1
n_spikes, _, _ = detectSpikes(t, Qm, SPIKE_MIN_QAMP, SPIKE_MIN_DT)
assert n_spikes == 1, 'Number of spikes after titration should be exactly 1'
# Check threshold amplitude
Athr_diff = (Athr - Athr_refs[neuron.name]) * 1e-3
assert np.abs(Athr_diff) < 0.1, Athr_err_msg.format(neuron.name, Athr_diff)
# Check response latency
lat_diff = (latency - latency_refs[neuron.name]) * 1e3
assert np.abs(lat_diff) < 1.0, latency_err_msg.format(neuron.name, lat_diff)
logger.info('Passed test: A-STIM titration')
def test_ASTIM_classic():
''' Short classic A-STIM simulation should not raise any errors. '''
logger.info('Starting test: A-STIM classic simulation')
# BLS geometry and parameters
geom = {"a": 32e-9, "d": 0.0e-6}
params = load_BLS_params()
# Stimulation parameters
Fdrive = 350e3 # Hz
Adrive = 100e3 # Pa
tstim = 1e-3 # s
toffset = 1e-3 # s
# Initialize RS neuron
rs_neuron = channels.CorticalRS()
# Initialize solver
solver = SolverUS(geom, params, rs_neuron, Fdrive)
# Run short classic simulation of the system
solver.run(rs_neuron, Fdrive, Adrive, tstim, toffset, sim_type='classic')
# If no error is raised, test is passed successfully
logger.info('Passed test: A-STIM classic simulation')
def test_ASTIM_hybrid():
''' Short hybrid A-STIM simulation should not raise any errors. '''
logger.info('Starting test: A-STIM hybrid simulation')
# BLS geometry and parameters
geom = {"a": 32e-9, "d": 0.0e-6}
params = load_BLS_params()
# Stimulation parameters
Fdrive = 350e3 # Hz
Adrive = 100e3 # Pa
tstim = 10e-3 # s
toffset = 1e-3 # s
# Initialize RS neuron
rs_neuron = channels.CorticalRS()
# Initialize solver
solver = SolverUS(geom, params, rs_neuron, Fdrive)
# Run short classic simulation of the system
solver.run(rs_neuron, Fdrive, Adrive, tstim, toffset, sim_type='hybrid')
# If no error is raised, test is passed successfully
logger.info('Passed test: A-STIM hybrid simulation')
if __name__ == '__main__':
logger.info('Starting tests')
test_MECH()
test_resting_potential()
test_ESTIM()
test_ASTIM()
test_ASTIM_classic()
test_ASTIM_hybrid()
logger.info('All tests successfully passed')

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