Monitor

core.Monitor.Monitor(
    self,
    obj,
    variables=[],
    period=None,
    period_offset=None,
    start=True,
    net_id=0,
)

Monitoring class allowing to record easily parameters or variables from Population, PopulationView, Dendrite or Projection objects.

Example:

m = Monitor(pop, ['g_exc', 'v', 'spike'], period=10.0)

It is also possible to record the sum of inputs to each neuron in a rate-coded population:

m = Monitor(pop, ['sum(exc)', 'r'])

Parameters

Name	Type	Description	Default
obj	Any	object to monitor. Must be a Population, PopulationView, Dendrite or Projection object.	required
variables	list	single variable name or list of variable names to record (default: []).	[]
period	float	delay in ms between two recording (default: dt). Not valid for the spike variable of a Population(View).	None
period_offset	float	determine the moment in ms of recording within the period (default 0). Must be smaller than period.	None
start	bool	defines if the recording should start immediately (default: True). If not, you should later start the recordings with the start() method.	True

Attributes

Name	Description
period	Period of recording in ms
period_offset	Shift of moment of time of recording in ms within a period
variables	Returns a copy of the current variable list.

Methods

Name	Description
coefficient_of_variation	Computes the coefficient of variation for the recorded spikes in the population.
get	Returns the recorded variables as a Numpy array (first dimension is time, second is neuron index).
histogram	Returns a histogram for the recorded spikes in the population.
inter_spike_interval	Computes the inter-spike interval for the recorded spikes in the population.
mean_fr	Computes the mean firing rate in the population during the recordings.
pause	Pauses the recordings.
population_rate	Takes the recorded spikes of a population and returns a smoothed firing rate for the population of recorded neurons.
raster_plot	Returns two numpy arrays representing for each recorded spike 1) the spike times and 2) the ranks of the neurons.
reset	Reset the monitor to its initial state.
resume	Resumes the recordings.
save	Saves the recorded variables as a Numpy array (first dimension is time, second is neuron index).
size_in_bytes	Get the size of allocated memory on C++ side. Please note, this is only valid if compile() was invoked.
smoothed_rate	Computes the smoothed firing rate of the recorded spiking neurons.
start	Starts recording the variables.
stop	Stops the recording.
times	Returns the start and stop times (in ms) of the recorded variables.

coefficient_of_variation

core.Monitor.Monitor.coefficient_of_variation(spikes=None, ranks=None)

Computes the coefficient of variation for the recorded spikes in the population.

:ranks: a list of neurons that should be evaluated. By default (None), all neurons are evaluated.

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None

get

core.Monitor.Monitor.get(
    variables=None,
    keep=False,
    reshape=False,
    force_dict=False,
)

Returns the recorded variables as a Numpy array (first dimension is time, second is neuron index).

If a single variable name is provided, the recorded values for this variable are directly returned. If a list is provided or the argument left empty, a dictionary with all recorded variables is returned.

The spike variable of a population will be returned as a dictionary of lists, where the spike times (in steps) for each recorded neurons are returned.

Parameters

Name	Type	Description	Default
variables	str | list[str]	(list of) variables. By default, a dictionary with all variables is returned.	None
keep	bool	defines if the content in memory for each variable should be kept (default: False).	False
reshape	bool	transforms the second axis of the array to match the population’s geometry (default: False).	False

Returns

Name	Type	Description
	dict	Recorded variables

histogram

core.Monitor.Monitor.histogram(
    spikes=None,
    bins=None,
    per_neuron=False,
    recording_window=None,
)

Returns a histogram for the recorded spikes in the population.

Example:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
histo = m.histogram()
plt.plot(histo)

or:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
spikes = m.get('spike')
histo = m.histogram(spikes)
plt.plot(histo)

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None
bins		the bin size in ms (default: dt).	None

inter_spike_interval

core.Monitor.Monitor.inter_spike_interval(
    spikes=None,
    ranks=None,
    per_neuron=False,
)

Computes the inter-spike interval for the recorded spikes in the population.

:ranks: a list of neurons that should be evaluated. By default (None), all neurons are evaluated. :per_neuron: if set to True, the computed inter-spike intervals are stored per neuron (analog to spikes), otherwise all values are stored in one huge vector (default: False).

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None

mean_fr

core.Monitor.Monitor.mean_fr(spikes=None)

Computes the mean firing rate in the population during the recordings.

Example:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
fr = m.mean_fr()

or:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
spikes = m.get('spike')
fr = m.mean_fr(spikes)

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None

pause

core.Monitor.Monitor.pause()

Pauses the recordings.

population_rate

core.Monitor.Monitor.population_rate(spikes=None, smooth=0.0)

Takes the recorded spikes of a population and returns a smoothed firing rate for the population of recorded neurons.

This method is faster than calling smoothed_rate and then averaging.

The first axis is the neuron index, the second is time.

If spikes is left empty, get('spike') will be called. Beware: this erases the data from memory.

Example:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
r = m.population_rate(smooth=100.)

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike').	None
smooth		smoothing time constant. Default: 0.0 (no smoothing).	0.0

raster_plot

core.Monitor.Monitor.raster_plot(spikes=None)

Returns two numpy arrays representing for each recorded spike 1) the spike times and 2) the ranks of the neurons.

Example:

m = Monitor(P[:1000], 'spike')
simulate(1000.0)
t, n = m.raster_plot()
plt.plot(t, n, '.')

or:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
spikes = m.get('spike')
t, n = m.raster_plot(spikes)
plt.plot(t, n, '.')

Parameters

Name	Type	Description	Default
spikes	dict	the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None

Returns

Name	Type	Description
	tuple	spike times and neuron indices as numpy arrays..

reset

core.Monitor.Monitor.reset()

Reset the monitor to its initial state.

resume

core.Monitor.Monitor.resume()

Resumes the recordings.

save

core.Monitor.Monitor.save(
    filename,
    variables=None,
    keep=False,
    reshape=False,
    force_dict=False,
)

Saves the recorded variables as a Numpy array (first dimension is time, second is neuron index).

If a single variable name is provided, the recorded values for this variable are directly saved. If a list is provided or the argument left empty, a dictionary with all recorded variables is saved.

The spike variable of a population will be returned as a dictionary of lists, where the spike times (in steps) for each recorded neurons are saved.

Parameters

Name	Type	Description	Default
filename	str	name of the save file.	required
variables	str | list[str]	(list of) variables. By default, a dictionary with all variables is returned.	None
keep	bool	defines if the content in memory for each variable should be kept (default: False).	False
reshape	bool	transforms the second axis of the array to match the population’s geometry (default: False).	False

Returns

Name	Type	Description
	None	Recorded variables

size_in_bytes

core.Monitor.Monitor.size_in_bytes()

Get the size of allocated memory on C++ side. Please note, this is only valid if compile() was invoked.

Returns

Name	Type	Description
	int	size in bytes of all allocated C++ data.

smoothed_rate

core.Monitor.Monitor.smoothed_rate(spikes=None, smooth=0.0)

Computes the smoothed firing rate of the recorded spiking neurons.

The first axis is the neuron index, the second is time.

Example:

m = ann.Monitor(P[:1000], 'spike')
ann.simulate(1000.0)
r = m.smoothed_rate(smooth=100.)

Parameters

Name	Type	Description	Default
spikes		the dictionary of spikes returned by get('spike'). If left empty, get('spike') will be called. Beware: this erases the data from memory.	None
smooth		smoothing time constant. Default: 0.0 (no smoothing).	0.0

start

core.Monitor.Monitor.start(variables=None, period=None)

Starts recording the variables.

It is called automatically after compile() if the flag start was not passed to the constructor.

Parameters

Name	Type	Description	Default
variables	list	single variable name or list of variable names to start recording (default: the variables argument passed to the constructor).	None
period	float	delay in ms between two recording (default: dt). Not valid for the spike variable of a Population(View).	None

stop

core.Monitor.Monitor.stop()

Stops the recording.

Warning: This will delete the content of the C++ object and all data not previously retrieved is lost.

times

core.Monitor.Monitor.times(variables=None)

Returns the start and stop times (in ms) of the recorded variables.

It should only be called after a call to get(), so that it describes when the variables have been recorded.

Parameters

Name	Type	Description	Default
variables	list[str]	(list of) variables. By default, the times for all variables is returned.	None

Returns

Name	Type	Description
	dict	dictionary of start and stop times.