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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 14:07:37
''' Test the basic functionalities of the package. '''
import logging
import inspect
import numpy as np
from PointNICE.utils import LoadParams
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 = LoadParams()
# 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 = LoadParams()
# 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 = LoadParams()
# 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 = LoadParams()
# 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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