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from tvb.datatypes.cortex import Cortex
from tvb.simulator.lab import *
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LOG.info("Configuring...")
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#Initialise a Model, Coupling, and Connectivity.
oscillator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity(load_default=True)
white_matter.speed = numpy.array([4.0])
white_matter_coupling = coupling.Linear(a=2 ** -7)
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#Initialise an Integrator
heunint = integrators.HeunDeterministic(dt=2 ** -4)
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#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)
#Bundle them
what_to_watch = (mon_tavg, mon_savg, mon_eeg)
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#Initialise a surface
local_coupling_strength = numpy.array([2 ** -6])
default_cortex = Cortex(load_default=True)
default_cortex.coupling_strength = local_coupling_strength
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##NOTE: THIS IS AN EXAMPLE OF DESCRIBING A SURFACE STIMULUS AT REGIONS LEVEL.
# SURFACES ALSO SUPPORT STIMULUS SPECIFICATION BY A SPATIAL FUNCTION
# CENTRED AT A VERTEX (OR VERTICES).
#Define the stimulus
#Specify a weighting for regions to receive stimuli...
white_matter.configure() # Because we want access to number_of_regions
nodes = [0, 7, 13, 33, 42]
#NOTE: here, we specify space at region level simulator will map to surface
#Specify a weighting for regions to receive stimuli...
weighting = numpy.zeros((white_matter.number_of_regions, 1))
weighting[nodes] = numpy.array([2.0 ** -2, 2.0 ** -3, 2.0 ** -4, 2.0 ** -5, 2.0 ** -6])[:, numpy.newaxis]
eqn_t = equations.Gaussian()
eqn_t.parameters["midpoint"] = 8.0
stimulus = patterns.StimuliRegion(temporal=eqn_t,
connectivity=white_matter,
weight=weighting)
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#Initialise Simulator -- Model, Connectivity, Integrator, Monitors, and surface.
sim = simulator.Simulator(model=oscillator,
connectivity=white_matter,
coupling=white_matter_coupling,
integrator=heunint,
monitors=what_to_watch,
surface=default_cortex, stimulus=stimulus)
sim.configure()
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#Clear the initial transient, so that the effect of the stimulus is clearer.
#NOTE: this is ignored, stimuli are defined relative to each simulation call.
LOG.info("Initial integration to clear transient...")
for _, _, _ in sim(simulation_length=128):
pass
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LOG.info("Starting simulation...")
#Perform the simulation
tavg_data = []
tavg_time = []
savg_data = []
savg_time = []
eeg_data = []
eeg_time = []
for tavg, savg, eeg in sim(simulation_length=2 ** 5):
if not tavg is None:
tavg_time.append(tavg[0])
tavg_data.append(tavg[1])
if not savg is None:
savg_time.append(savg[0])
savg_data.append(savg[1])
if not eeg is None:
eeg_time.append(eeg[0])
eeg_data.append(eeg[1])
LOG.info("finished simulation.")
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#Plot the stimulus
plot_pattern(sim.stimulus)
if IMPORTED_MAYAVI:
surface_pattern(sim.surface, sim.stimulus.spatial_pattern)
#Make the lists numpy.arrays for easier use.
TAVG = numpy.array(tavg_data)
SAVG = numpy.array(savg_data)
EEG = numpy.array(eeg_data)
#Plot region averaged time series
figure(3)
plot(savg_time, SAVG[:, 0, :, 0])
title("Region average")
#Plot EEG time series
figure(4)
plot(eeg_time, EEG[:, 0, :, 0])
title("EEG")
#Show them
show()
#Surface movie, requires mayavi.malb
if IMPORTED_MAYAVI:
st = surface_timeseries(sim.surface, TAVG[:, 0, :, 0])