def from_file(cls, source_file="cortex_16384.zip",
region_mapping_file=os.path.join("regionMapping_16k_76.txt"),
local_connectivity_file=None, eeg_projection_file=None, instance=None):
result = super(Cortex, cls).from_file(source_file, instance)
if instance is not None:
# Called through constructor directly
if result.region_mapping is None:
result.region_mapping_data = RegionMapping.from_file()
if not result.eeg_projection:
result.eeg_projection = Cortex.from_file_projection_array()
if result.local_connectivity is None:
result.local_connectivity = LocalConnectivity.from_file()
if region_mapping_file is not None:
result.region_mapping_data = RegionMapping.from_file(region_mapping_file)
if local_connectivity_file is not None:
result.local_connectivity = LocalConnectivity.from_file(local_connectivity_file)
if eeg_projection_file is not None:
result.eeg_projection = Cortex.from_file_projection_array(eeg_projection_file)
return result
def configure(self,
dt=2**-3,
model=models.Generic2dOscillator,
speed=4.0,
coupling_strength=0.00042,
method="HeunDeterministic",
surface_sim=False,
default_connectivity=True):
"""
Create an instance of the Simulator class, by default use the
generic plane oscillator local dynamic model and the deterministic
version of Heun's method for the numerical integration.
"""
self.method = method
if default_connectivity:
white_matter = connectivity.Connectivity(load_default=True)
# NOTE: This is the default region mapping should consider changing the name.
region_mapping = RegionMapping.from_file(
source_file=
"cortex_reg13/region_mapping/o52r00_irp2008_hemisphere_both_subcortical_false_regions_74.txt.bz2"
)
else:
white_matter = connectivity.Connectivity.from_file(
source_file="connectivity_190.zip")
region_mapping = RegionMapping.from_file(
source_file=
"cortex_reg13/region_mapping/o52r00_irp2008_hemisphere_both_subcortical_true_regions_190.txt.bz2"
)
white_matter_coupling = coupling.Linear(a=coupling_strength)
white_matter.speed = speed
dynamics = model()
if method[-10:] == "Stochastic":
hisss = noise.Additive(nsig=numpy.array([2**-11]))
integrator = eval("integrators." + method + "(dt=dt, noise=hisss)")
else:
integrator = eval("integrators." + method + "(dt=dt)")
if surface_sim:
local_coupling_strength = numpy.array([2**-10])
default_cortex = Cortex(load_default=True,
region_mapping_data=region_mapping)
default_cortex.coupling_strength = local_coupling_strength
default_cortex.local_connectivity = LocalConnectivity(
load_default=default_connectivity, surface=default_cortex)
else:
default_cortex = None
# Order of monitors determines order of returned values.
self.sim = simulator.Simulator(model=dynamics,
connectivity=white_matter,
coupling=white_matter_coupling,
integrator=integrator,
monitors=self.monitors,
surface=default_cortex)
self.sim.configure()
def setup_method(self):
oscillator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity.from_file(
'connectivity_%d.zip' % (self.n_regions, ))
white_matter.speed = numpy.array([self.speed])
white_matter_coupling = coupling.Difference(a=self.coupling_a)
heunint = integrators.HeunStochastic(
dt=2**-4, noise=noise.Additive(nsig=numpy.array([
2**-10,
])))
mons = (
monitors.EEG.from_file(period=self.period),
monitors.MEG.from_file(period=self.period),
monitors.iEEG.from_file(period=self.period),
)
local_coupling_strength = numpy.array([2**-10])
region_mapping = RegionMapping.from_file('regionMapping_16k_%d.txt' %
(self.n_regions, ))
default_cortex = Cortex(region_mapping_data=region_mapping,
load_default=True)
default_cortex.coupling_strength = local_coupling_strength
self.sim = simulator.Simulator(model=oscillator,
connectivity=white_matter,
coupling=white_matter_coupling,
integrator=heunint,
monitors=mons,
surface=default_cortex)
self.sim.configure()
def setup_method(self):
self.sim = simulator.Simulator(
connectivity=connectivity.Connectivity.from_file(
'connectivity_192.zip'),
monitors=(monitors.iEEG(
sensors=SensorsInternal(load_default=True),
region_mapping=RegionMapping.from_file(
'regionMapping_16k_192.txt')))).configure()
def test_surface_sim_with_projections(self):
# Setup Simulator obj
oscillator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity.from_file('connectivity_%d.zip' % (self.n_regions,))
white_matter.speed = numpy.array([self.speed])
white_matter_coupling = coupling.Difference(a=self.coupling_a)
heunint = integrators.HeunStochastic(
dt=2 ** -4,
noise=noise.Additive(nsig=numpy.array([2 ** -10, ]))
)
mons = (
monitors.EEG.from_file(period=self.period),
monitors.MEG.from_file(period=self.period),
# monitors.iEEG.from_file(period=self.period),
# SEEG projection data is not part of tvb-data on Pypi, thus this can not work generic
)
local_coupling_strength = numpy.array([2 ** -10])
region_mapping = RegionMapping.from_file('regionMapping_16k_%d.txt' % (self.n_regions,))
region_mapping.surface = CorticalSurface.from_file()
default_cortex = Cortex.from_file()
default_cortex.region_mapping_data = region_mapping
default_cortex.coupling_strength = local_coupling_strength
sim = simulator.Simulator(model=oscillator, connectivity=white_matter, coupling=white_matter_coupling,
integrator=heunint, monitors=mons, surface=default_cortex)
sim.configure()
# check configured simulation connectivity attribute
conn = sim.connectivity
assert conn.number_of_regions == self.n_regions
assert conn.speed == self.speed
# test monitor properties
lc_n_node = sim.surface.local_connectivity.matrix.shape[0]
for mon in sim.monitors:
assert mon.period == self.period
n_sens, g_n_node = mon.gain.shape
assert g_n_node == sim.number_of_nodes
assert n_sens == mon.sensors.number_of_sensors
assert lc_n_node == g_n_node
# check output shape
ys = {}
mons = 'eeg meg seeg'.split()
for key in mons:
ys[key] = []
for data in sim(simulation_length=3.0):
for key, dat in zip(mons, data):
if dat:
_, y = dat
ys[key].append(y)
for mon, key in zip(sim.monitors, mons):
ys[key] = numpy.array(ys[key])
assert ys[key].shape[2] == mon.gain.shape[0]
def from_file(cls, sensors_fname, projection_fname, rm_f_name="regionMapping_16k_76.txt",
period=1e3/1024.0, **kwds):
"""
Build Projection-based monitor from sensors and projection files, and
any extra keyword arguments are passed to the monitor class constructor.
"""
result = cls(period=period, **kwds)
result.sensors = cls.sensors.field_type.from_file(sensors_fname)
result.projection = cls.projection_class().from_file(projection_fname)
result.region_mapping = RegionMapping.from_file(rm_f_name)
return result
def test_gain_size(self):
sim = simulator.Simulator(
connectivity=connectivity.Connectivity.from_file('connectivity_192.zip'),
monitors=(monitors.iEEG(
sensors=SensorsInternal.from_file(),
region_mapping=RegionMapping.from_file('regionMapping_16k_192.txt')
),)
).configure()
ieeg = sim.monitors[0] # type: SensorsInternal
n_sens, n_reg = ieeg.gain.shape
assert ieeg.sensors.locations.shape[0] == n_sens
assert sim.connectivity.number_of_regions == n_reg
def from_file(
cls,
source_file=os.path.join("cortex_reg13",
"surface_cortex_reg13.zip"),
region_mapping_file=os.path.
join(
"cortex_reg13", "region_mapping",
"o52r00_irp2008_hemisphere_both_subcortical_false_regions_74.txt.bz2"
),
local_connectivity_file=None,
eeg_projection_file=None,
instance=None):
result = super(Cortex, cls).from_file(source_file, instance)
if instance is not None:
# Called through constructor directly
if result.region_mapping is None:
result.region_mapping_data = RegionMapping.from_file()
if not result.eeg_projection:
result.eeg_projection = Cortex.from_file_projection_array()
if result.local_connectivity is None:
result.local_connectivity = LocalConnectivity.from_file()
if region_mapping_file is not None:
result.region_mapping_data = RegionMapping.from_file(
region_mapping_file)
if local_connectivity_file is not None:
result.local_connectivity = LocalConnectivity.from_file(
local_connectivity_file)
if eeg_projection_file is not None:
result.eeg_projection = Cortex.from_file_projection_array(
eeg_projection_file)
return result
def from_file(cls, sensors_fname, projection_fname, rm_f_name="regionMapping_16k_76.txt",
period=1e3/1024.0, instance=None, **kwds):
"""
Build Projection-based monitor from sensors and projection files, and
any extra keyword arguments are passed to the monitor class constructor.
"""
if instance is None:
result = cls(**kwds)
else:
result = instance
result.sensors = type(cls.sensors).from_file(sensors_fname)
result.projection = cls._projection_class().from_file(projection_fname)
result.region_mapping = RegionMapping.from_file(rm_f_name)
return result
def configure(self,
dt=2**-3,
model=ModelsEnum.GENERIC_2D_OSCILLATOR.get_class(),
speed=4.0,
coupling_strength=0.00042,
method=HeunDeterministic,
surface_sim=False,
default_connectivity=True,
with_stimulus=False):
"""
Create an instance of the Simulator class, by default use the
generic plane oscillator local dynamic model and the deterministic
version of Heun's method for the numerical integration.
"""
self.method = method
if default_connectivity:
white_matter = Connectivity.from_file()
region_mapping = RegionMapping.from_file(
source_file="regionMapping_16k_76.txt")
else:
white_matter = Connectivity.from_file(
source_file="connectivity_192.zip")
region_mapping = RegionMapping.from_file(
source_file="regionMapping_16k_192.txt")
region_mapping.surface = CorticalSurface.from_file()
white_matter_coupling = coupling.Linear(
a=numpy.array([coupling_strength]))
white_matter.speed = numpy.array(
[speed]) # no longer allow scalars to numpy array promotion
dynamics = model()
if issubclass(method, IntegratorStochastic):
hisss = noise.Additive(nsig=numpy.array([2**-11]))
integrator = method(dt=dt, noise=hisss)
else:
integrator = method(dt=dt)
if surface_sim:
local_coupling_strength = numpy.array([2**-10])
default_cortex = Cortex.from_file()
default_cortex.region_mapping_data = region_mapping
default_cortex.coupling_strength = local_coupling_strength
if default_connectivity:
default_cortex.local_connectivity = LocalConnectivity.from_file(
)
else:
default_cortex.local_connectivity = LocalConnectivity()
default_cortex.local_connectivity.surface = default_cortex.region_mapping_data.surface
# TODO stimulus
else:
default_cortex = None
if with_stimulus:
weights = StimuliRegion.get_default_weights(
white_matter.weights.shape[0])
weights[self.stim_nodes] = 1.
stimulus = StimuliRegion(temporal=Linear(parameters={
"a": 0.0,
"b": self.stim_value
}),
connectivity=white_matter,
weight=weights)
# Order of monitors determines order of returned values.
self.sim = simulator.Simulator()
self.sim.surface = default_cortex
self.sim.model = dynamics
self.sim.integrator = integrator
self.sim.connectivity = white_matter
self.sim.coupling = white_matter_coupling
self.sim.monitors = self.monitors
if with_stimulus:
self.sim.stimulus = stimulus
self.sim.configure()
def test_regionmapping(self):
dt = RegionMapping.from_file()
assert isinstance(dt, RegionMapping)
assert dt.array_data.shape == (16384, )
region_mapping_file=region_fname,
eeg_projection_file=eeg_fname)
ctx.configure()
print("cortex loaded")
pyplot.figure()
ax = pyplot.subplot(111, projection='3d')
x, y, z = ctx.vertices.T
ax.plot_trisurf(x, y, z, triangles=ctx.triangles, alpha=0.1, edgecolor='k')
# pyplot.show()
print("cortex plot ready")
# unit vectors that describe the location of eeg sensors
sensoreeg_fname = os.path.join(master_path, 'DH_20120806_EEGLocations.txt')
rm = RegionMapping.from_file(region_fname)
sensorsEEG = SensorsEEG.from_file(sensoreeg_fname)
prEEG = ProjectionSurfaceEEG.from_file(eeg_fname)
fsamp = 1e3 / 1024.0 # 1024 Hz
mon = monitors.EEG(sensors=sensorsEEG,
projection=prEEG,
region_mapping=rm,
period=fsamp)
sim = simulator.Simulator(
connectivity=conn,
# conduction speed: 3 mm/ms
# coupling: linear - rescales activity propagated
# stimulus: None - can be a spatiotemporal function
def __init__(self,Ps):
"""
Initialize simulation
----------------------
"""
sim_length = Ps['sim_params']['length']
outdir = Ps['sim_params']['outdir']
if not os.path.isdir(outdir): os.mkdir(outdir)
print '\nConfiguring sim...'
sim = simulator.Simulator()
_classes = [models, connectivity, coupling, integrators, monitors ]
_names = ['model', 'connectivity', 'coupling', 'integrator', 'monitors']
for _class,_name in zip(_classes,_names):
if _name is 'monitors':
thisattr = tuple([getattr(_class,m['type'])(**m['params']) for m in Ps['monitors'] ])
else:
if 'type' in Ps[_name]:
thisattr = getattr(_class,Ps[_name]['type'])(**Ps[_name]['params'])
setattr(sim,_name,thisattr)
# Additionals - parameters that are functions of other classes
# (example = larter_breakdspear demo)
if 'additionals' in Ps:
for a in Ps['additionals']:
setattr(eval(a[0]), a[1],eval(a[2]))
#sim,eval(a[0]),eval(a[1]))
# Stochastic integrator
if 'HeunStochastic' in Ps['integrator']:
from tvb.simulator.lab import noise
hiss = noise.Additive(nsig=np.array(Ps['integrator']['stochastic_nsig'])) # nsigm 0.015
sim.integrator.noise = hiss
# Non-default connectivity
# (to add here:
# - load from other data structures, e.g. .cff file
# - load weights, lengths, etc. directly from data matrices etc
if 'connectivity' in Ps:
if 'folder_path' in Ps['connectivity']: # (this is from the deterministic_stimulus demo)
sim.connectivity.default.reload(sim.connectivity, Ps['connectivity']['folder_path'])
sim.connectivity.configure()
# EEG projections
# (need to do this separately because don't seem to be able to do EEG(projection_matrix='<file>')
for m_it, m in enumerate(Ps['monitors']): # (yes I know enumerate isn't necessary here; but it's more transparent imho)
# assumption here is that the sim object doesn't re-order the list of monitors for any bizarre reason...
# (which would almost certainly cause an error anyway...)
#if m['type'] is 'EEG' and 'proj_mat_path' in m:
# proj_mat = loadmat(m['proj_mat_path'])['ProjectionMatrix']
# pr = projections.ProjectionRegionEEG(projection_data=proj_mat)
# sim.monitors[m_it].projection_matrix_data=pr
if m['type'] is 'EEG':
if m['proj_surf'] is 'default': pr = ProjectionSurfaceEEG(load_default=True)
else: pr = ProjectionSurfaceEEG.from_file(m['proj_surf'])
eeg_sens = SensorsEEG.from_file(source_file=m['source_file'])
if m['reg_map'] is 'default':
rm = RegionMapping(load_default=True)
else: rm = RegionMapping.from_file(m['reg_map'])
sim.monitors[m_it].projection = pr
sim.monitors[m_it].sensors = eeg_sens
sim.monitors[m_it].region_mapping = rm
# Surface
if 'surface' in Ps:
surf = getattr(surfaces,Ps['surface']['surface_type']).default()
if 'local_connectivity_params' in Ps['surface']:
localsurfconn = getattr(surfaces,'LocalConnectivity')(**Ps['surface']['local_connectivity_params'])
for ep in Ps['surface']['local_connectivity_equation_params'].items():
localsurfconn.equation.parameters[ep[0]] = ep[1]
surf.local_connectivity = localsurfconn
localcoupling = np.array( Ps['surface']['local_coupling_strength'] )
surf.coupling_strength = localcoupling
sim.surface = surf
# Stimulus
if 'stimulus' in Ps:
stim = getattr(patterns,Ps['stimulus']['type'])()
if 'equation' in Ps['stimulus']: # looks like need to do this to keep the other params as default; slightly different to above
stim_eqn_params = Ps['stimulus']['equation']['params']
# use this if need to evaluate text
# (stim_eqn_params = {p[0]: eval(p[1]) for p in Ps['stimulus']['equation']['params'].items() } (
stim_eqn_t = getattr(equations,Ps['stimulus']['equation']['type'])()
stim_eqn_t.parameters.update(**stim_eqn_params)
stim.temporal = stim_eqn_t
elif 'equation' not in Ps['stimulus']:
# (still need to do this...)
print 'something to do here'
sim.connectivity.configure()
stim_weighting = np.zeros((sim.connectivity.number_of_regions,))
stim_weighting[Ps['stimulus']['nodes']] = np.array(Ps['stimulus']['node_weightings'])
stim.connectivity = sim.connectivity
stim.weight = stim_weighting
sim.stimulus = stim
# Configure sim
sim.configure()
# Configure smooth parameter variation (if used)
spv = {}
if 'smooth_pvar' in Ps:
par_length = eval(Ps['smooth_pvar']['par_length_str'])
spv['mon_type'] = Ps['smooth_pvar']['monitor_type']
spv['mon_num'] = [m_it for m_it, m in enumerate(Ps['monitors']) if m == spv['mon_type'] ] # (yes, a bit clumsy..)
# a) as an equally spaced range
if 'equation' not in Ps['smooth_pvar']:
spv['a'] = eval(Ps['smooth_pvar']['spv_a_str'])
# b) using an Equation datadtype
else:
spv['params'] = {}
for p in Ps['smooth_pvar']['equation']['params'].items():
spv['params'][p[0]] = eval(p[1])
#sim_length = Ps['sim_params']['length'] # temporary fix]
#spv_a_params = {p[0]: eval(p[1]) for p in Ps['smooth_pvar']['equation']['params'].items() }
spv['eqn_t'] = getattr(equations,Ps['smooth_pvar']['equation']['type'])()
spv['eqn_t'].parameters.update(**spv['params'])
spv['pattern'] = eval(Ps['smooth_pvar']['equation']['pattern_str'])
spv['a'] = spv['pattern'] # omit above line? At moment this follows tutorial code
# recent additions....
self.sim = sim
self.Ps = Ps
self.sim_length = sim_length
self.spv = spv
def configure(self,
dt=2**-3,
model=models.Generic2dOscillator,
speed=4.0,
coupling_strength=0.00042,
method=HeunDeterministic,
surface_sim=False,
default_connectivity=True):
"""
Create an instance of the Simulator class, by default use the
generic plane oscillator local dynamic model and the deterministic
version of Heun's method for the numerical integration.
"""
self.method = method
if default_connectivity:
white_matter = Connectivity.from_file()
region_mapping = RegionMapping.from_file(
source_file="regionMapping_16k_76.txt")
else:
white_matter = Connectivity.from_file(
source_file="connectivity_192.zip")
region_mapping = RegionMapping.from_file(
source_file="regionMapping_16k_192.txt")
region_mapping.surface = CorticalSurface.from_file()
white_matter_coupling = coupling.Linear(
a=numpy.array([coupling_strength]))
white_matter.speed = numpy.array(
[speed]) # no longer allow scalars to numpy array promotion
dynamics = model()
if issubclass(method, IntegratorStochastic):
hisss = noise.Additive(nsig=numpy.array([2**-11]))
integrator = method(dt=dt, noise=hisss)
else:
integrator = method(dt=dt)
if surface_sim:
local_coupling_strength = numpy.array([2**-10])
default_cortex = Cortex.from_file()
default_cortex.region_mapping_data = region_mapping
default_cortex.coupling_strength = local_coupling_strength
if default_connectivity:
default_cortex.local_connectivity = LocalConnectivity.from_file(
)
else:
default_cortex.local_connectivity = LocalConnectivity()
default_cortex.local_connectivity.surface = default_cortex.region_mapping_data.surface
else:
default_cortex = None
# Order of monitors determines order of returned values.
self.sim = simulator.Simulator()
self.sim.surface = default_cortex
self.sim.model = dynamics
self.sim.integrator = integrator
self.sim.connectivity = white_matter
self.sim.coupling = white_matter_coupling
self.sim.monitors = self.monitors
self.sim.configure()
oscillator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity.from_file('connectivity_192.zip')
white_matter.speed = numpy.array([4.0])
white_matter_coupling = coupling.Difference(a=0.014)
heunint = integrators.HeunStochastic(
dt=2**-4,
noise=noise.Additive(nsig=numpy.array([2 ** -10, ]))
)
fsamp = 1e3/1024.0 # 1024 Hz
monitors = (
monitors.EEG.from_file('eeg-brainstorm-65.txt', 'projection_EEG_surface.npy', period=fsamp),
monitors.MEG.from_file('meg-brainstorm-276.txt', 'projection_MEG_surface.npy', period=fsamp),
monitors.iEEG.from_file('SEEG_588.txt', 'projection_SEEG_surface.npy', period=fsamp),
)
local_coupling_strength = numpy.array([2 ** -10])
default_cortex = Cortex(region_mapping_data=RegionMapping.from_file('regionMapping_16k_192.txt'),
load_default=True)
default_cortex.coupling_strength = local_coupling_strength
sim = simulator.Simulator(model=oscillator, connectivity=white_matter,
coupling=white_matter_coupling,
integrator=heunint, monitors=monitors,
surface=default_cortex)
sim.configure()
ts, ys = {}, {}
mons = 'eeg meg seeg'.split()
for key in mons:
ts[key] = []
ys[key] = []
for data in sim(simulation_length=2**2):
