core package
Essential Brian modules, in particular base classes for all kinds of brian
objects.
Built-in preferences
Core Brian preferences
core.default_float_dtype
= float64
Default dtype for all arrays of scalars (state variables, weights, etc.).
core.default_integer_dtype
= int32
Default dtype for all arrays of integer scalars.
core.outdated_dependency_error
= True
Whether to raise an error for outdated dependencies (True
) or just
a warning (False
).
base
module
All Brian objects should derive from BrianObject
.
Exported members:
BrianObject
, BrianObjectException
Classes
BrianObject (**kwds) |
All Brian objects derive from this class, defines magic tracking and update. |
BrianObjectException (message, brianobj, …) |
High level exception that adds extra Brian-specific information to exceptions |
Functions
device_override (name) |
Decorates a function/method to allow it to be overridden by the current Device . |
weakproxy_with_fallback (obj) |
Attempts to create a weakproxy to the object, but falls back to the object if not possible. |
clocks
module
Clocks for the simulator.
Exported members:
Clock
, defaultclock
Classes
Clock (dt[, name]) |
An object that holds the simulation time and the time step. |
DefaultClockProxy |
Method proxy to access the defaultclock of the currently active device |
Functions
check_dt (new_dt, old_dt, target_t) |
Check that the target time can be represented equally well with the new dt. |
Objects
defaultclock |
The standard clock, used for objects that do not specify any clock or dt |
core_preferences
module
Definitions, documentation, default values and validation functions for core
Brian preferences.
Functions
functions
module
Exported members:
DEFAULT_FUNCTIONS
, Function
, implementation()
, declare_types()
Classes
Function (pyfunc[, sympy_func, arg_units, …]) |
An abstract specification of a function that can be used as part of model equations, etc. |
FunctionImplementationContainer (function) |
Helper object to store implementations and give access in a dictionary-like fashion, using CodeGenerator implementations as a fallback for CodeObject implementations. |
Functions
declare_types (**types) |
Decorator to declare argument and result types for a function |
implementation (target[, code, namespace, …]) |
A simple decorator to extend user-written Python functions to work with code generation in other languages. |
timestep (t, dt) |
Converts a given time to an integer time step. |
magic
module
Exported members:
MagicNetwork
, magic_network
, MagicError
, run()
, stop()
, collect()
, store()
, restore()
, start_scope()
Classes
Functions
restore ([name, filename]) |
Restore the state of the network and all included objects. |
run (duration[, report, report_period, …]) |
Runs a simulation with all “visible” Brian objects for the given duration. |
stop () |
Stops all running simulations. |
store ([name, filename]) |
Store the state of the network and all included objects. |
Objects
names
module
Exported members:
Nameable
Classes
Nameable (name) |
Base class to find a unique name for an object |
Functions
namespace
module
Implementation of the namespace system, used to resolve the identifiers in
model equations of NeuronGroup
and Synapses
Exported members:
get_local_namespace()
, DEFAULT_FUNCTIONS
, DEFAULT_UNITS
, DEFAULT_CONSTANTS
Functions
network
module
Module defining the Network
object, the basis of all simulation runs.
Preferences
Network preferences
core.network.default_schedule
= ['start', 'groups', 'thresholds', 'synapses', 'resets', 'end']
Default schedule used for networks that
don’t specify a schedule.
Exported members:
Network
, profiling_summary()
, scheduling_summary()
Classes
Network (*objs[, name]) |
The main simulation controller in Brian |
SchedulingSummary (objects) |
Object representing the schedule that is used to simulate the objects in a network. |
Functions
spikesource
module
Exported members:
SpikeSource
Classes
tracking
module
Exported members:
Trackable
Classes
Trackable |
Classes derived from this will have their instances tracked. |
variables
module
Classes used to specify the type of a function, variable or common
sub-expression.
Exported members:
Variable
, Constant
, ArrayVariable
, DynamicArrayVariable
, Subexpression
, AuxiliaryVariable
, VariableView
, Variables
, LinkedVariable
, linked_var()
Classes
ArrayVariable (name, owner, size, device[, …]) |
An object providing information about a model variable stored in an array (for example, all state variables). |
AuxiliaryVariable (name[, dimensions, dtype, …]) |
Variable description for an auxiliary variable (most likely one that is added automatically to abstract code, e.g. |
Constant (name, value[, dimensions, owner]) |
A scalar constant (e.g. |
DynamicArrayVariable (name, owner, size, device) |
An object providing information about a model variable stored in a dynamic array (used in Synapses ). |
LinkedVariable (group, name, variable[, index]) |
A simple helper class to make linking variables explicit. |
Subexpression (name, owner, expr, device[, …]) |
An object providing information about a named subexpression in a model. |
Variable (name[, dimensions, owner, dtype, …]) |
An object providing information about model variables (including implicit variables such as t or xi ). |
VariableView (name, variable, group[, dimensions]) |
A view on a variable that allows to treat it as an numpy array while allowing special indexing (e.g. |
Functions
get_dtype_str (val) |
Returns canonical string representation of the dtype of a value or dtype |
linked_var (group_or_variable[, name, index]) |
Represents a link target for setting a linked variable. |