def test_monitor_stereoeeg(self):
"""
This has to be verified.
"""
monitor = monitors.iEEG()
monitor.sensors = sensors.SensorsInternal(load_default=True)
assert monitor.period == self.default_period
def test_monitor_stereoeeg(self):
"""
This has to be verified.
"""
monitor = monitors.iEEG()
monitor.sensors = sensors.SensorsInternal(load_file="seeg_39.txt.bz2")
assert monitor.period == self.default_period
def test_sensorsinternal(self):
dt = sensors.SensorsInternal()
dt.configure()
self.assertFalse(dt.has_orientation)
self.assertEqual(dt.labels.shape, (103,))
self.assertEqual(dt.locations.shape, (103, 3))
self.assertEqual(dt.number_of_sensors, 103)
self.assertEqual(dt.orientations.shape, (0,))
self.assertEqual(dt.sensors_type, 'Internal')
def test_sensorsinternal(self):
dt = sensors.SensorsInternal(load_default=True)
dt.configure()
self.assertTrue(isinstance(dt, sensors.SensorsInternal))
self.assertFalse(dt.has_orientation)
self.assertEqual(dt.labels.shape, (103, ))
self.assertEqual(dt.locations.shape, (103, 3))
self.assertEqual(dt.number_of_sensors, 103)
self.assertEqual(dt.orientations.shape, (0, ))
self.assertEqual(dt.sensors_type, INTERNAL_POLYMORPHIC_IDENTITY)
def test_sensorsinternal(self):
dt = sensors.SensorsInternal(load_file="seeg_39.txt.bz2")
dt.configure()
assert isinstance(dt, sensors.SensorsInternal)
assert not dt.has_orientation
assert dt.labels.shape == (103,)
assert dt.locations.shape == (103, 3)
assert dt.number_of_sensors == 103
assert dt.orientations.shape == (0,)
assert dt.sensors_type == INTERNAL_POLYMORPHIC_IDENTITY
class iEEG(Projection):
"Forward solution for intracranial EEG (not ECoG!)."
_ui_name = "Intracerebral / Stereo EEG"
projection = ProjectionSurfaceSEEG(
default=None,
label='Projection matrix',
doc='Projection matrix to apply to sources.')
sigma = basic.Float(label="conductivity", default=1.0)
sensors = sensors_module.SensorsInternal(
label="Internal brain sensors",
default=None,
required=True,
doc=
"The set of SEEG sensors for which the forward solution will be calculated."
)
@classmethod
def from_file(cls,
sensors_fname='seeg_588.txt',
projection_fname='projection_seeg_588_surface_16k.npy',
**kwargs):
return Projection.from_file.im_func(cls, sensors_fname,
projection_fname, **kwargs)
def analytic(self, loc, ori):
"""Compute the projection matrix -- simple distance weight for now.
Equation 12 from sarvas1987basic (point dipole in homogeneous space):
V(r) = 1/(4*pi*\sigma)*Q*(r-r_0)/|r-r_0|^3
"""
r_0, Q = loc, ori
V_r = numpy.zeros((self.sensors.locations.shape[0], r_0.shape[0]))
for sensor_k in numpy.arange(self.sensors.locations.shape[0]):
a = self.sensors.locations[sensor_k, :] - r_0
na = numpy.sqrt(numpy.sum(a**2, axis=1))[:, numpy.newaxis]
V_r[sensor_k, :] = numpy.sum(
Q * (a / na**3), axis=1) / (4.0 * numpy.pi * self.sigma)
return V_r
def create_time_series(self,
storage_path,
connectivity=None,
surface=None,
region_map=None,
region_volume_map=None):
return TimeSeriesSEEG(storage_path=storage_path,
sensors=self.sensors,
sample_period=self.period,
title=' ' + self.__class__.__name__,
**self._transform_user_tags())
.. moduleauthor:: Stuart A. Knock <*****@*****.**>
"""
import numpy
from tvb.simulator.lab import *
import tvb.datatypes.sensors as sensors
##----------------------------------------------------------------------------##
##- Perform the simulation -##
##----------------------------------------------------------------------------##
LOG.info("Configuring...")
#Initialise a Model, Coupling, and Connectivity.
sens = sensors.SensorsInternal()
oscilator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity()
white_matter.speed = numpy.array([4.0])
white_matter_coupling = coupling.Linear(a=0.014)
#Initialise an Integrator
heunint = integrators.HeunDeterministic(dt=2**-4)
#Initialise some Monitors with period in physical time
mon_tavg = monitors.TemporalAverage(period=2**-2)
mon_savg = monitors.SpatialAverage(period=2**-2)
mon_eeg = monitors.EEG(period=2**-2)
mon_seeg = monitors.SEEG(period=2**-2)
