bluepysnap.spike_report¶

Spike report access.

Classes

`FilteredSpikeReport`(spike_report[, group, ...])	Access to filtered SpikeReport data.
`PopulationSpikeReport`(spike_report, ...)	Access to PopulationSpikeReport data.
`SpikeReport`(simulation)	Access to SpikeReport data.

class bluepysnap.spike_report.FilteredSpikeReport(spike_report, group=None, t_start=None, t_stop=None)¶

Access to filtered SpikeReport data.

Initialize a FilteredSpikeReport.

A FilteredSpikeReport is a lazy and cached object which contains the filtered data from all the populations of a report.

Parameters:

spike_report (SpikeReport) – The SpikeReport to filter.
group (None/int/list/np.array/dict) – Get spikes filtered by group. See NodePopulation.
t_start (float) – Include only frames occurring at or after this time.
t_stop (float) – Include only frames occurring at or before this time.

Returns:

A FilteredSpikeReport object.

Return type:

FilteredSpikeReport

firing_animation(x_axis='x', y_axis='y', dt=20, ax=None)¶

Simple animation of simulation spikes.

Each frame of the animation represents the spiking nodes during a period of dt ms seconds in a coordinate system corresponding to the x, y or z axis of the circuit.

Parameters:

x_axis (str) – Node enum that will determine the animation x_axis
y_axis (str) – Node enum that will determine the animation y_axis
dt (int) – the time bin size of each frame in the video in ms
ax (matplotlib.Axis) – matplotlib Axis to draw on (if not specified, pyplot.gca() and plt.figure() are used).

Returns:

the matplotlib animation object and the corresponding axis.

Return type:

(matplotlib.animation.FuncAnimation, matplotlib.Axis)

Examples

From scripts:

>>> import matplotlib.pyplot as plt
>>> from bluepysnap import Simulation
>>> report = Simulation("config.json").spikes["my_population"]
>>> anim, ax = report.firing_animation()
>>> plt.show()
>>> # to save the animation : do not plt.show() and just anim.save('my_movie.mp4')

From notebooks:

>>> from IPython.display import HTML
>>> from bluepysnap import Simulation
>>> report = Simulation("config.json").spikes["my_population"]
>>> anim, ax = report.firing_animation()
>>> HTML(anim.to_html5_video())

firing_rate_histogram(time_binsize=None, ax=None)¶

Spike firing rate histogram.

This plot shows the number of nodes firing during a range of time.

Parameters:

time_binsize (None/int/float) – bin size (milliseconds). If None, a binning heuristic is used to create an histogram with ~100 spikes per bin in average.
ax (matplotlib.Axis) – matplotlib Axis to draw on (if not specified, pyplot.gca() is used).

Returns:

Axis containing firing rate histogram.

Return type:

matplotlib.Axis

Notes

If no axis is provided through the ax=ax keyword argument, then a default layout is set using pyplot.gca().

isi(use_frequency=False, binsize=None, ax=None)¶

Interspike interval histogram.

This plots show the binned time/frequency interval between to spikes for neurons.

Parameters:

use_frequency (bool) – use inverse interspike interval times (Hz)
binsize (None/int/float) – bin size in milliseconds or Hz. If None is used the binning is delegated to matplolib and is done automatically.
ax (matplotlib.Axis) – matplotlib Axis to draw on (if not specified, pyplot.gca() is used).

Returns:

axis containing the interspike interval histogram.

Return type:

matplotlib.Axis

Notes

If no axis is provided through the ax=ax keyword argument, then a default layout is set using pyplot.gca().

raster(y_axis=None, ax=None)¶

Spike raster plot.

Shows a global overview of the circuit’s firing nodes. The y axis can project either the node_ids or any properties present in the different node populations.

Parameters:

y_axis (None/str) – The property to display on the y axis. None is node_ids.
ax (matplotlib.Axis) – matplotlib Axis to draw on (if not specified, pyplot.gca() is used).

Returns:

Axis containing Spikes raster plot.

Return type:

matplotlib.Axis

Notes

If no axis is provided through the ax=ax keyword argument, then a default layout is set using pyplot.gca().

report¶

Access to the report data.

Returns:: A DataFrame containing the data from the report. Row’s indices are the different timestamps and the columns are ids and population names.
Return type:: pandas.DataFrame

class bluepysnap.spike_report.PopulationSpikeReport(spike_report, population_name)¶

Access to PopulationSpikeReport data.

Initializes a PopulationSpikeReport object from a SpikeReport.

Parameters:

spike_report (SpikeReport) – SpikeReport containing this spike report population.
population_name (str) – the population name corresponding to this report.

Returns:

A PopulationSpikeReport object.

Return type:

PopulationSpikeReport

get(group=None, t_start=None, t_stop=None)¶

Fetch spikes from the report.

Parameters:

group (None/int/list/np.array/dict) – Get spikes filtered by group. See NodePopulation.
t_start (float) – Include only spikes occurring at or after this time.
t_stop (float) – Include only spikes occurring at or before this time.

Returns:

return spiking node_ids indexed by sorted spike time.

Return type:

pandas.Series

property name¶: Return the name of the population.

node_ids¶

Returns the node ids present in the report.

Returns:: Numpy array containing the node_ids included in the report
Return type:: np.Array

nodes¶: Return the NodePopulation corresponding to this spike report.

resolve_nodes(group, raise_missing_property=True)¶: Transform a node group into a node_id array.

class bluepysnap.spike_report.SpikeReport(simulation)¶

Access to SpikeReport data.

Initializes a SpikeReport object from a simulation object.

Parameters:: simulation (Simulation) – Simulation containing this spike report.
Returns:: A SpikeReport object.
Return type:: SpikeReport

property config¶: Access to the spike ‘output’ config part.

property dt¶: Returns the frequency of reporting in milliseconds.

filter(group=None, t_start=None, t_stop=None)¶

Returns a FilteredSpikeReport.

A FilteredSpikeReport is a lazy and cached object which contains the filtered data from all the populations of a report.

Parameters:

group (None/int/list/np.array/dict) – Get spikes filtered by group. See NodePopulation.
t_start (float) – Include only frames occurring at or after this time.
t_stop (float) – Include only frames occurring at or before this time.

Returns:

A FilteredSpikeReport object.

Return type:

FilteredSpikeReport

log()¶: Context manager for the spike log file.

population_names¶: Returns the population names included in this report.

property simulation¶: Return the Simulation object related to this spike report.

property time_start¶: Returns the starting time of the simulation. Default is zero.

property time_stop¶: Returns the stopping time of the simulation.

property time_units¶: Returns the time unit of reporting.