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simulator Package

burst_configuration_h5

class tvb.core.entities.file.simulator.burst_configuration_h5.BurstConfigurationH5(path)[source]

Bases: tvb.core.neotraits._h5core.H5File

load_into(burst_config)[source]
store(burst_config, scalars_only=False, store_references=True)[source]

datatype_measure_h5

class tvb.core.entities.file.simulator.datatype_measure_h5.DatatypeMeasure(**kwargs)[source]

Bases: tvb.basic.neotraits._core.HasTraits

metrics : tvb.core.entities.file.simulator.datatype_measure_h5.DatatypeMeasure.metrics = Attr(field_type=<class ‘dict’>, default=None, required=True)

analyzed_datatype : tvb.core.entities.file.simulator.datatype_measure_h5.DatatypeMeasure.analyzed_datatype = Attr(field_type=<class ‘tvb.datatypes.time_series.TimeSeries’>, default=None, required=True)
Links to the time-series on which the metrics are computed.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

analyzed_datatype

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

metrics

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

class tvb.core.entities.file.simulator.datatype_measure_h5.DatatypeMeasureH5(path)[source]

Bases: tvb.core.neotraits._h5core.H5File

simulation_history_h5

class tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory(**kwargs)[source]

Bases: tvb.basic.neotraits._core.HasTraits

Simulation State, prepared for H5 file storage.

history : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.history = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

current_state : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.current_state = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

current_step : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.current_step = Int(field_type=<class ‘int’>, default=0, required=True)

monitor_stock_1 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_1 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_2 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_2 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_3 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_3 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_4 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_4 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_5 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_5 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_6 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_6 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_7 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_7 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_8 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_8 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_9 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_9 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_10 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_10 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_11 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_11 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_12 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_12 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_13 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_13 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_14 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_14 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_stock_15 : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_stock_15 = NArray(label=’‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

monitor_names : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.monitor_names = List(of=<class ‘str’>, default=(), required=True)

integrator_noise_rng_state_algo : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.integrator_noise_rng_state_algo = Attr(field_type=<class ‘str’>, default=None, required=False)

integrator_noise_rng_state_keys : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.integrator_noise_rng_state_keys = NArray(label=’‘, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

integrator_noise_rng_state_pos : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.integrator_noise_rng_state_pos = Int(field_type=<class ‘int’>, default=0, required=False)

integrator_noise_rng_state_has_gauss : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.integrator_noise_rng_state_has_gauss = Int(field_type=<class ‘int’>, default=0, required=False)

integrator_noise_rng_state_cached_gauss : tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistory.integrator_noise_rng_state_cached_gauss = Float(field_type=<class ‘float’>, default=0, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

current_state

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

current_step

Declares an integer This is different from Attr(field_type=int). The former enforces int subtypes This allows all integer types, including numpy ones that can be safely cast to the declared type according to numpy rules

fill_into(simulator_algorithm)[source]

Populate a Simulator object from current stored-state.

history

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

integrator_noise_rng_state_algo

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

integrator_noise_rng_state_cached_gauss

Declares a float. This is different from Attr(field_type=float). The former enforces float subtypes. This allows any type that can be safely cast to the declared float type according to numpy rules.

Reading and writing this attribute is slower than a plain python attribute. In performance sensitive code you might want to use plain python attributes or even better local variables.

integrator_noise_rng_state_has_gauss

Declares an integer This is different from Attr(field_type=int). The former enforces int subtypes This allows all integer types, including numpy ones that can be safely cast to the declared type according to numpy rules

integrator_noise_rng_state_keys

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

integrator_noise_rng_state_pos

Declares an integer This is different from Attr(field_type=int). The former enforces int subtypes This allows all integer types, including numpy ones that can be safely cast to the declared type according to numpy rules

monitor_names

The attribute is a list of values. Choices and type are reinterpreted as applying not to the list but to the elements of it

monitor_stock_1

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_10

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_11

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_12

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_13

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_14

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_15

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_2

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_3

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_4

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_5

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_6

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_7

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_8

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

monitor_stock_9

Declares a numpy array. dtype enforces the dtype. The default dtype is float32. An optional symbolic shape can be given, as a tuple of Dim attributes from the owning class. The shape will be enforced, but no broadcasting will be done. domain declares what values are allowed in this array. It can be any object that can be checked for membership Defaults are checked if they are in the declared domain. For performance reasons this does not happen on every attribute set.

populate_from(simulator_algorithm)[source]

Prepare a state for storage from a Simulator object.

class tvb.core.entities.file.simulator.simulation_history_h5.SimulationHistoryH5(path)[source]

Bases: tvb.core.neotraits._h5core.H5File

view_model

class tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.NoiseViewModel, tvb.simulator.noise.Additive

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

nsig : tvb.simulator.noise.Additive.nsig = NArray(label=’\(D\)‘, dtype=float64, default=array([1.]), dim_names=(), ndim=None, required=True)
The noise dispersion, it is the standard deviation of the distribution from which the Gaussian random variates are drawn. NOTE: Sensible values are typically ~<< 1% of the dynamic range of a Model’s state variables.
ntau : tvb.simulator.noise.Noise.ntau = Float(field_type=<class ‘float’>, default=0.0, required=True)
The noise correlation time
noise_seed : tvb.simulator.noise.Noise.noise_seed = Int(field_type=<class ‘int’>, default=42, required=True)
A random seed used to initialise the random_stream if it is missing.
random_stream : tvb.simulator.noise.Noise.random_stream = Attr(field_type=<class ‘numpy.random.mtrand.RandomState’>, default=None, required=False)
An instance of numpy’s RandomState associated with thisspecific Noise object. Used when you need to resume a simulation from a state saved to disk

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.BoldRegionROIViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.BoldViewModel, tvb.simulator.monitors.BoldRegionROI

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Bold.period = Float(field_type=<class ‘float’>, default=2000.0, required=True)
For the BOLD monitor, sampling period in milliseconds must be an integral multiple of 500. Typical measurment interval (repetition time TR) is between 1-3 s. If TR is 2s, then Bold period is 2000ms.
hrf_kernel : tvb.simulator.monitors.Bold.hrf_kernel = Attr(field_type=<class ‘tvb.datatypes.equations.HRFKernelEquation’>, default=<tvb.datatypes.equations.FirstOrderVolterra object at 0x7f008f4af310>, required=True)
A tvb.datatypes.equation object which describe the haemodynamic response function used to compute the BOLD signal.
hrf_length : tvb.simulator.monitors.Bold.hrf_length = Float(field_type=<class ‘float’>, default=20000.0, required=True)
Duration of the hrf kernel
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.BoldViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.Bold

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Bold.period = Float(field_type=<class ‘float’>, default=2000.0, required=True)
For the BOLD monitor, sampling period in milliseconds must be an integral multiple of 500. Typical measurment interval (repetition time TR) is between 1-3 s. If TR is 2s, then Bold period is 2000ms.
hrf_kernel : tvb.simulator.monitors.Bold.hrf_kernel = Attr(field_type=<class ‘tvb.datatypes.equations.HRFKernelEquation’>, default=<tvb.datatypes.equations.FirstOrderVolterra object at 0x7f008f4af310>, required=True)
A tvb.datatypes.equation object which describe the haemodynamic response function used to compute the BOLD signal.
hrf_length : tvb.simulator.monitors.Bold.hrf_length = Float(field_type=<class ‘float’>, default=20000.0, required=True)
Duration of the hrf kernel
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.CortexViewModel(**kwargs)[source]

Bases: tvb.core.neotraits.view_model.ViewModel, tvb.datatypes.cortex.Cortex

surface_gid : tvb.core.entities.file.simulator.view_model.CortexViewModel.surface_gid = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=False)
By default, a Cortex object which represents the cortical surface defined by points in the 3D physical space and their neighborhood relationship. In the current TVB version, when setting up a surface-based simulation, the option to configure the spatial spread of the Local Connectivity is available.
local_connectivity : tvb.core.entities.file.simulator.view_model.CortexViewModel.local_connectivity = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=False)
Define the interaction between neighboring network nodes. This is implicitly integrated in the definition of a given surface as an excitatory mean coupling of directly adjacent neighbors to the first state variable of each population model (since these typically represent the mean-neural membrane voltage). This coupling is instantaneous (no time delays).
region_mapping_data : tvb.core.entities.file.simulator.view_model.CortexViewModel.region_mapping_data = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
An index vector of length equal to the number_of_vertices + the number of non-cortical regions, with values that index into an associated connectivity matrix.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

coupling_strength : tvb.datatypes.cortex.Cortex.coupling_strength = NArray(label=’Local coupling strength’, dtype=float64, default=array([1.]), dim_names=(), ndim=None, required=True)
A factor that rescales local connectivity strengths.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
local_connectivity

Keep a GID but also link the type of DataType it should point to

region_mapping_data

Keep a GID but also link the type of DataType it should point to

surface_gid

Keep a GID but also link the type of DataType it should point to

class tvb.core.entities.file.simulator.view_model.Dop853StochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel, tvb.simulator.integrators.Dop853Stochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.Dop853ViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.Dop853

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.Dopri5StochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel, tvb.simulator.integrators.Dopri5Stochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.Dopri5ViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.Dopri5

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.EEGViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.ProjectionViewModel, tvb.simulator.monitors.EEG

projection : tvb.core.entities.file.simulator.view_model.EEGViewModel.projection = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
Projection matrix to apply to sources.
sensors : tvb.core.entities.file.simulator.view_model.EEGViewModel.sensors = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
Sensors to use for this EEG monitor
region_mapping : tvb.core.entities.file.simulator.view_model.ProjectionViewModel.region_mapping = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
A region mapping specifies how vertices of a surface correspond to given regions in the connectivity. For iEEG/EEG/MEG monitors, this must be specified when performing a region simulation but is optional for a surface simulation.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

reference : tvb.simulator.monitors.EEG.reference = Attr(field_type=<class ‘str’>, default=None, required=False)
EEG Electrode to be used as reference, or “average” to apply an average reference. If none is provided, the produced time-series are the idealized or reference-free.
sigma : tvb.simulator.monitors.EEG.sigma = Float(field_type=<class ‘float’>, default=1.0, required=True)
When a projection matrix is not used, this provides the value of conductivity in the formula for the single sphere approximation of the head (Sarvas 1987).
obsnoise : tvb.simulator.monitors.Projection.obsnoise = Attr(field_type=<class ‘tvb.simulator.noise.Noise’>, default=<tvb.simulator.noise.Additive object at 0x7f008f511dd0>, required=False)
The monitor’s noise source. It incorporates its own instance of Numpy’s RandomState.
period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
projection

Keep a GID but also link the type of DataType it should point to

sensors

Keep a GID but also link the type of DataType it should point to

class tvb.core.entities.file.simulator.view_model.EulerDeterministicViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.EulerDeterministic

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.EulerStochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel, tvb.simulator.integrators.EulerStochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.GlobalAverageViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.GlobalAverage

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.HeunDeterministicViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.HeunDeterministic

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.HeunStochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel, tvb.simulator.integrators.HeunStochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.IdentityViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.Identity

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.IntegratorStochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
noise

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

class tvb.core.entities.file.simulator.view_model.IntegratorViewModel(**kwargs)[source]

Bases: tvb.core.neotraits.view_model.ViewModel, tvb.simulator.integrators.Integrator

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.MEGViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.ProjectionViewModel, tvb.simulator.monitors.MEG

projection : tvb.core.entities.file.simulator.view_model.MEGViewModel.projection = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
Projection matrix to apply to sources.
sensors : tvb.core.entities.file.simulator.view_model.MEGViewModel.sensors = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
The set of MEG sensors for which the forward solution will be calculated.
region_mapping : tvb.core.entities.file.simulator.view_model.ProjectionViewModel.region_mapping = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
A region mapping specifies how vertices of a surface correspond to given regions in the connectivity. For iEEG/EEG/MEG monitors, this must be specified when performing a region simulation but is optional for a surface simulation.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

obsnoise : tvb.simulator.monitors.Projection.obsnoise = Attr(field_type=<class ‘tvb.simulator.noise.Noise’>, default=<tvb.simulator.noise.Additive object at 0x7f008f511dd0>, required=False)
The monitor’s noise source. It incorporates its own instance of Numpy’s RandomState.
period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
projection

Keep a GID but also link the type of DataType it should point to

sensors

Keep a GID but also link the type of DataType it should point to

class tvb.core.entities.file.simulator.view_model.MonitorViewModel(**kwargs)[source]

Bases: tvb.core.neotraits.view_model.ViewModel, tvb.simulator.monitors.Monitor

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.MultiplicativeNoiseViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.NoiseViewModel, tvb.simulator.noise.Multiplicative

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

nsig : tvb.simulator.noise.Multiplicative.nsig = NArray(label=’\(D\)‘, dtype=float64, default=array([1.]), dim_names=(), ndim=None, required=True)
The noise dispersion, it is the standard deviation of the distribution from which the Gaussian random variates are drawn. NOTE: Sensible values are typically ~<< 1% of the dynamic range of a Model’s state variables.
b : tvb.simulator.noise.Multiplicative.b = Attr(field_type=<class ‘tvb.datatypes.equations.TemporalApplicableEquation’>, default=<tvb.datatypes.equations.Linear object at 0x7f013e22cc50>, required=True)
A function evaluated on the state-variables, the result of which enters as the diffusion coefficient.
ntau : tvb.simulator.noise.Noise.ntau = Float(field_type=<class ‘float’>, default=0.0, required=True)
The noise correlation time
noise_seed : tvb.simulator.noise.Noise.noise_seed = Int(field_type=<class ‘int’>, default=42, required=True)
A random seed used to initialise the random_stream if it is missing.
random_stream : tvb.simulator.noise.Noise.random_stream = Attr(field_type=<class ‘numpy.random.mtrand.RandomState’>, default=None, required=False)
An instance of numpy’s RandomState associated with thisspecific Noise object. Used when you need to resume a simulation from a state saved to disk

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.NoiseViewModel(**kwargs)[source]

Bases: tvb.core.neotraits.view_model.ViewModel, tvb.simulator.noise.Noise

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

ntau : tvb.simulator.noise.Noise.ntau = Float(field_type=<class ‘float’>, default=0.0, required=True)
The noise correlation time
noise_seed : tvb.simulator.noise.Noise.noise_seed = Int(field_type=<class ‘int’>, default=42, required=True)
A random seed used to initialise the random_stream if it is missing.
random_stream : tvb.simulator.noise.Noise.random_stream = Attr(field_type=<class ‘numpy.random.mtrand.RandomState’>, default=None, required=False)
An instance of numpy’s RandomState associated with thisspecific Noise object. Used when you need to resume a simulation from a state saved to disk

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.ProjectionViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.Projection

region_mapping : tvb.core.entities.file.simulator.view_model.ProjectionViewModel.region_mapping = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
A region mapping specifies how vertices of a surface correspond to given regions in the connectivity. For iEEG/EEG/MEG monitors, this must be specified when performing a region simulation but is optional for a surface simulation.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

obsnoise : tvb.simulator.monitors.Projection.obsnoise = Attr(field_type=<class ‘tvb.simulator.noise.Noise’>, default=<tvb.simulator.noise.Additive object at 0x7f008f511dd0>, required=False)
The monitor’s noise source. It incorporates its own instance of Numpy’s RandomState.
period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
region_mapping

Keep a GID but also link the type of DataType it should point to

class tvb.core.entities.file.simulator.view_model.RawViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.Raw

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Raw.period = Float(field_type=<class ‘float’>, default=0.0, required=True)

variables_of_interest : tvb.simulator.monitors.Raw.variables_of_interest = NArray(label=’Raw Monitor sees all!!! Resistance is futile...’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.RungeKutta4thOrderDeterministicViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.RungeKutta4thOrderDeterministic

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel[source]

Bases: tvb.core.neotraits.view_model.ViewModel, tvb.simulator.simulator.Simulator

connectivity : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.connectivity = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
A tvb.datatypes.Connectivity object which contains the structural long-range connectivity data (i.e., white-matter tracts). In combination with the Long-range coupling function it defines the inter-regional connections. These couplings undergo a time delay via signal propagation with a propagation speed of Conduction Speed
surface : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.surface = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.CortexViewModel’>, default=None, required=False)
By default, a Cortex object which represents the cortical surface defined by points in the 3D physical space and their neighborhood relationship. In the current TVB version, when setting up a surface-based simulation, the option to configure the spatial spread of the Local Connectivity is available.
stimulus : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.stimulus = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=False)
A Spatiotemporal stimulus can be defined at the region or surface level. It’s composed of spatial and temporal components. For region defined stimuli the spatial component is just the strength with which the temporal component is applied to each region. For surface defined stimuli, a (spatial) function, with finite-support, is used to define the strength of the stimuli on the surface centred around one or more focal points. In the current version of TVB, stimuli are applied to the first state variable of the Local dynamic model.

history_gid : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.history_gid = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

integrator : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.integrator = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.IntegratorViewModel’>, default=<tvb.core.entities.file.simulator.view_model.HeunDeterministicViewModel object at 0x7f0088e79750>, required=True)
A tvb.simulator.Integrator object which is an integration scheme with supporting attributes such as integration step size and noise specification for stochastic methods. It is used to compute the time courses of the model state variables.
monitors : tvb.core.entities.file.simulator.view_model.SimulatorAdapterModel.monitors = List(of=<class ‘tvb.core.entities.file.simulator.view_model.MonitorViewModel’>, default=(<tvb.core.entities.file.simulator.view_model.TemporalAverageViewModel object at 0x7f0088e79950>,), required=True)
A tvb.simulator.Monitor or a list of tvb.simulator.Monitor objects that ‘know’ how to record relevant data from the simulation. Two main types exist: 1) simple, spatial and temporal, reductions (subsets or averages); 2) physiological measurements, such as EEG, MEG and fMRI. By default the Model’s specified variables_of_interest are returned, temporally downsampled from the raw integration rate to a sample rate of 1024Hz.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

conduction_speed : tvb.simulator.simulator.Simulator.conduction_speed = Float(field_type=<class ‘float’>, default=3.0, required=False)
Conduction speed for Long-range connectivity (mm/ms)
coupling : tvb.simulator.simulator.Simulator.coupling = Attr(field_type=<class ‘tvb.simulator.coupling.Coupling’>, default=<tvb.simulator.coupling.Linear object at 0x7f008f3a54d0>, required=True)
The coupling function is applied to the activity propagated between regions by the Long-range connectivity before it enters the local dynamic equations of the Model. Its primary purpose is to ‘rescale’ the incoming activity to a level appropriate to Model.
model : tvb.simulator.simulator.Simulator.model = Attr(field_type=<class ‘tvb.simulator.models.base.Model’>, default=<tvb.simulator.models.oscillator.Generic2dOscillator object at 0x7f008f3cb110>, required=True)
A tvb.simulator.Model object which describe the local dynamic equations, their parameters, and, to some extent, where connectivity (local and long-range) enters and which state-variables the Monitors monitor. By default the ‘Generic2dOscillator’ model is used. Read the Scientific documentation to learn more about this model.
initial_conditions : tvb.simulator.simulator.Simulator.initial_conditions = NArray(label=’Initial Conditions’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)
Initial conditions from which the simulation will begin. By default, random initial conditions are provided. Needs to be the same shape as simulator ‘history’, ie, initial history function which defines the minimal initial state of the network with time delays before time t=0. If the number of time points in the provided array is insufficient the array will be padded with random values based on the ‘state_variables_range’ attribute.
simulation_length : tvb.simulator.simulator.Simulator.simulation_length = Float(field_type=<class ‘float’>, default=1000.0, required=True)
The length of a simulation (default in milliseconds).

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

connectivity

Keep a GID but also link the type of DataType it should point to

determine_indexes_for_chosen_vars_of_interest()[source]
first_monitor[source]
static get_variables_of_interest_indexes(all_variables, chosen_variables)[source]
history_gid

Keep a GID but also link the type of DataType it should point to

integrator

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

linked_has_traits[source]
monitors

The attribute is a list of values. Choices and type are reinterpreted as applying not to the list but to the elements of it

stimulus

Keep a GID but also link the type of DataType it should point to

surface

An Attr declares the following about the attribute it describes: * the type * a default value shared by all instances * if the value might be missing * documentation It will resolve to attributes on the instance.

class tvb.core.entities.file.simulator.view_model.SpatialAverageViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.SpatialAverage

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

spatial_mask : tvb.simulator.monitors.SpatialAverage.spatial_mask = NArray(label=’Spatial Mask’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
A vector of length==nodes that assigns an index to each node specifying the “region” to which it belongs. The default usage is for mapping a surface based simulation back to the regions used in its Long-range Connectivity.
default_mask : tvb.simulator.monitors.SpatialAverage.default_mask = Attr(field_type=<class ‘str’>, default=’hemispheres’, required=False)
Fallback in case spatial mask is none and no surface providedto use either connectivity hemispheres or cortical attributes.
period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.SubSampleViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.SubSample

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.TemporalAverageViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.MonitorViewModel, tvb.simulator.monitors.TemporalAverage

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.VODEStochasticViewModel[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel, tvb.simulator.integrators.VODEStochastic

noise : tvb.core.entities.file.simulator.view_model.IntegratorStochasticViewModel.noise = Attr(field_type=<class ‘tvb.core.entities.file.simulator.view_model.NoiseViewModel’>, default=<tvb.core.entities.file.simulator.view_model.AdditiveNoiseViewModel object at 0x7f008f3a5410>, required=True)
The stochastic integrator’s noise source. It incorporates its own instance of Numpy’s RandomState.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.VODEViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.IntegratorViewModel, tvb.simulator.integrators.VODE

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

dt : tvb.simulator.integrators.Integrator.dt = Float(field_type=<class ‘float’>, default=0.01220703125, required=True)
The step size used by the integration routine in ms. This should be chosen to be small enough for the integration to be numerically stable. It is also necessary to consider the desired sample period of the Monitors, as they are restricted to being integral multiples of this value. The default value is set such that all built-in models are numerically stable with there default parameters and because it is consitent with Monitors using sample periods corresponding to powers of 2 from 128 to 4096Hz.

bounded_state_variable_indices : tvb.simulator.integrators.Integrator.bounded_state_variable_indices = NArray(label=”indices of the state variables to be bounded by the integrators within the boundaries in the boundaries’ values array”, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

state_variable_boundaries : tvb.simulator.integrators.Integrator.state_variable_boundaries = NArray(label=’The boundary values of the state variables’, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_indices : tvb.simulator.integrators.Integrator.clamped_state_variable_indices = NArray(label=’indices of the state variables to be clamped by the integrators to the values in the clamped_values array’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)

clamped_state_variable_values : tvb.simulator.integrators.Integrator.clamped_state_variable_values = NArray(label=’The values of the state variables which are clamped ‘, dtype=float64, default=None, dim_names=(), ndim=None, required=False)

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
class tvb.core.entities.file.simulator.view_model.iEEGViewModel(**kwargs)[source]

Bases: tvb.core.entities.file.simulator.view_model.ProjectionViewModel, tvb.simulator.monitors.iEEG

projection : tvb.core.entities.file.simulator.view_model.iEEGViewModel.projection = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
Projection matrix to apply to sources.
sensors : tvb.core.entities.file.simulator.view_model.iEEGViewModel.sensors = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
The set of SEEG sensors for which the forward solution will be calculated.
region_mapping : tvb.core.entities.file.simulator.view_model.ProjectionViewModel.region_mapping = DataTypeGidAttr(field_type=<class ‘uuid.UUID’>, default=None, required=True)
A region mapping specifies how vertices of a surface correspond to given regions in the connectivity. For iEEG/EEG/MEG monitors, this must be specified when performing a region simulation but is optional for a surface simulation.

operation_group_gid : tvb.core.neotraits.view_model.ViewModel.operation_group_gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=False)

ranges : tvb.core.neotraits.view_model.ViewModel.ranges = Attr(field_type=<class ‘str’>, default=None, required=False)

range_values : tvb.core.neotraits.view_model.ViewModel.range_values = Attr(field_type=<class ‘str’>, default=None, required=False)

is_metric_operation : tvb.core.neotraits.view_model.ViewModel.is_metric_operation = Attr(field_type=<class ‘bool’>, default=False, required=True)

sigma : tvb.simulator.monitors.iEEG.sigma = Float(field_type=<class ‘float’>, default=1.0, required=True)

obsnoise : tvb.simulator.monitors.Projection.obsnoise = Attr(field_type=<class ‘tvb.simulator.noise.Noise’>, default=<tvb.simulator.noise.Additive object at 0x7f008f511dd0>, required=False)
The monitor’s noise source. It incorporates its own instance of Numpy’s RandomState.
period : tvb.simulator.monitors.Monitor.period = Float(field_type=<class ‘float’>, default=0.9765625, required=True)
Sampling period in milliseconds, must be an integral multiple of integration-step size. As a guide: 2048 Hz => 0.48828125 ms ; 1024 Hz => 0.9765625 ms ; 512 Hz => 1.953125 ms.
variables_of_interest : tvb.simulator.monitors.Monitor.variables_of_interest = NArray(label=’Model variables to watch’, dtype=int64, default=None, dim_names=(), ndim=None, required=False)
Indices of model’s variables of interest (VOI) that this monitor should record. Note that the indices should start at zero, so that if a model offers VOIs V, W and V+W, and W is selected, and this monitor should record W, then the correct index is 0.

gid : tvb.basic.neotraits._core.HasTraits.gid = Attr(field_type=<class ‘uuid.UUID’>, default=None, required=True)

linked_has_traits[source]
projection

Keep a GID but also link the type of DataType it should point to

sensors

Keep a GID but also link the type of DataType it should point to