Simulator history implementations.
Bases: tvb.simulator.descriptors.StaticAttr
Abstract base class for history implementations.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Set initial conditions for the simulation using either the provided initial_conditions or, if none are provided, the model’s initial() method. This method is called durin the Simulator’s __init__().
Any initial_conditions that are provided as an argument are expected to have dimensions 1, 2, and 3 with shapse corresponding to the number of state_variables, nodes and modes, respectively. If the provided inital_conditions are shorter in time (dim=0) than the required history the model’s initial() method is called to make up the difference.
Specialization of Final to int/long type.
Specialization of Final to int/long type.
Specialization of Final to int/long type.
Specialization of Final to int/long type.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Bases: tvb.simulator.history.BaseHistory
TVB’s traditional history implementation.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Bases: tvb.simulator.history.DenseHistory
History implementation which stores data only for non-zero weights.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Specialization of Final to int/long type.
Specialization of Final to int/long type.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Data descriptor for a NumPy array, with type, mutability and shape checking.
Specialization of Final to int/long type.
A module of classes and functions of common use.
Bases: builtins.dict
the Struct class is a dictionary with matlab/C struct-like access to its fields:
>>> parameters = Struct(x=23.4345, alpha=1.522e-4)
>>> parameters.x + 1
24.4345
>>> parameters.x_init = 6
>>> parameters.x_init + 1
7
>>> print(parameters.y)
None
note that this class returns None if the field does not exist!
Helper for generating a sequence of astr representation of attributes on self
at(a, indices, b=None)
Performs unbuffered in place operation on operand ‘a’ for elements specified by ‘indices’. For addition ufunc, this method is equivalent to a[indices] += b, except that results are accumulated for elements that are indexed more than once. For example, a[[0,0]] += 1 will only increment the first element once because of buffering, whereas add.at(a, [0,0], 1) will increment the first element twice.
New in version 1.8.0.
Set items 0 and 1 to their negative values:
>>> a = np.array([1, 2, 3, 4])
>>> np.negative.at(a, [0, 1])
>>> a
array([-1, -2, 3, 4])
Increment items 0 and 1, and increment item 2 twice:
>>> a = np.array([1, 2, 3, 4])
>>> np.add.at(a, [0, 1, 2, 2], 1)
>>> a
array([2, 3, 5, 4])
Add items 0 and 1 in first array to second array, and store results in first array:
>>> a = np.array([1, 2, 3, 4])
>>> b = np.array([1, 2])
>>> np.add.at(a, [0, 1], b)
>>> a
array([2, 4, 3, 4])
Data descriptors for declaring workspace for algorithms and checking usage.
Bases: tvb.simulator.descriptors.Final
Specialization of Final to int/long type.
Bases: builtins.object
A descriptor for an attribute, possibly type-checked, that once initialized, cannot be changed.
Bases: builtins.AttributeError
Error due to modifying an immutable attribute.
Bases: builtins.AttributeError
Error due to using incorrect type to set attribute value.
Bases: tvb.simulator.descriptors.StaticAttr
Data descriptor for a NumPy array, with type, mutability and shape checking.
Bases: builtins.tuple
State(array, initialized)
Alias for field number 0
Alias for field number 1
Bases: builtins.object
Base class which requires all attributes to be declared at class level.