SpikeGeneratorGroup class¶
(Shortest import: from brian2 import SpikeGeneratorGroup)

class
brian2.input.spikegeneratorgroup.
SpikeGeneratorGroup
(N, indices, times, dt=None, clock=None, period=1e100*second, when='thresholds', order=0, sorted=False, name='spikegeneratorgroup*', codeobj_class=None)[source]¶ Bases:
brian2.groups.group.Group
,brian2.groups.group.CodeRunner
,brian2.core.spikesource.SpikeSource
A group emitting spikes at given times.
Parameters: N : int
The number of “neurons” in this group
indices : array of integers
The indices of the spiking cells
times :
Quantity
The spike times for the cells given in
indices
. Has to have the same length asindices
.period :
Quantity
, optionalIf this is specified, it will repeat spikes with this period.
dt :
Quantity
, optionalThe time step to be used for the simulation. Cannot be combined with the
clock
argument.clock :
Clock
, optionalThe update clock to be used. If neither a clock, nor the
dt
argument is specified, thedefaultclock
will be used.when : str, optional
When to run within a time step, defaults to the
'thresholds'
slot.order : int, optional
The priority of of this group for operations occurring at the same time step and in the same scheduling slot. Defaults to 0.
sorted : bool, optional
Whether the given indices and times are already sorted. Set to
True
if your events are already sorted (first by spike time, then by index), this can save significant time at construction if your arrays contain large numbers of spikes. Defaults toFalse
.Notes
 In a time step,
SpikeGeneratorGroup
emits all spikes that happened at \(tdt < t_{spike} \leq t\). This might lead to unexpected or missing spikes if you change the time step dt between runs. SpikeGeneratorGroup
does not currently raise any warning if a neuron spikes more that once during a time step, but other code (e.g. for synaptic propagation) might assume that neurons only spike once per time step and will therefore not work properly. If
sorted
is set toTrue
, the given arrays will not be copied (only affects runtime mode)..
Attributes
_previous_dt
Remember the dt we used the last time when we checked the spike bins _spikes_changed
“Dirty flag” that will be set when spikes are changed after the spikes
The spikes returned by the most recent thresholding operation. Methods
before_run
(run_namespace)set_spikes
(indices, times[, period, sorted])Change the spikes that this group will generate. Details

_previous_dt
¶ Remember the dt we used the last time when we checked the spike bins to not repeat the work for multiple runs with the same dt

_spikes_changed
¶ “Dirty flag” that will be set when spikes are changed after the
before_run
check

spikes
¶ The spikes returned by the most recent thresholding operation.

set_spikes
(indices, times, period=1e100*second, sorted=False)¶ Change the spikes that this group will generate.
This can be used to set the input for a second run of a model based on the output of a first run (if the input for the second run is already known before the first run, then all the information should simply be included in the initial
SpikeGeneratorGroup
initializer call, instead).Parameters: indices : array of integers
The indices of the spiking cells
times :
Quantity
The spike times for the cells given in
indices
. Has to have the same length asindices
.period :
Quantity
, optionalIf this is specified, it will repeat spikes with this period.
sorted : bool, optional
Whether the given indices and times are already sorted. Set to
True
if your events are already sorted (first by spike time, then by index), this can save significant time at construction if your arrays contain large numbers of spikes. Defaults toFalse
.
 In a time step,
Tutorials and examples using this¶
 Example frompapers/Diesmann_et_al_1999