cleo.viz module#

Tools for visualizing models and simulations

class cleo.viz.VideoVisualizer(devices: collections.abc.Iterable[Union[cleo.base.InterfaceDevice, Tuple[cleo.base.InterfaceDevice, dict]]] = NOTHING, dt: brian2.units.fundamentalunits.Quantity = 1. * msecond, *, name: str = NOTHING, save_history: bool = True)[source]#

Bases: cleo.base.InterfaceDevice

Device for visualizing a simulation.

Must be injected after all other devices and before the simulation is run.

Method generated by attrs for class VideoVisualizer.

ax: matplotlib.axes._axes.Axes#
connect_to_neuron_group(neuron_group: brian2.groups.neurongroup.NeuronGroup, **kwparams) → None[source]#

Connect device to given neuron_group.

If your device introduces any objects which Brian must keep track of, such as a NeuronGroup, Synapses, or Monitor, make sure to add these to brian_objects.

Parameters

  • neuron_group (NeuronGroup) –

  • **kwparams (optional) – Passed from inject

devices: collections.abc.Iterable[Union[cleo.base.InterfaceDevice, Tuple[cleo.base.InterfaceDevice, dict]]]#

list of devices or (device, vis_kwargs) tuples to include in the plot, just as in the plot() function, by default “all”, which will include all recorders and stimulators currently injected when this visualizer is injected into the simulator.

dt: brian2.units.fundamentalunits.Quantity#

length of each frame—that is, every dt the visualizer takes a snapshot of the network, by default 1*ms

fig: matplotlib.figure.Figure#
generate_Animation(plotargs: dict, slowdown_factor: float = 10, **figargs: Any) → matplotlib.animation.Animation[source]#

Create a matplotlib Animation object from the recorded simulation

Parameters

  • plotargs (dict) – dictionary of arguments as taken by plot(). can include xlim, ylim, zlim, colors, axis_scale_unit, invert_z, and/or scatterargs. neuron groups and devices are automatically added and **figargs are specified separately.

  • slowdown_factor (float, optional) – how much slower the animation will be rendered, as a multiple of real-time, by default 10

  • **figargs (Any, optional) – keyword arguments passed to plt.figure(), such as figsize

Returns

An Animation object capturing the desired visualization. See matplotlib’s docs for saving and rendering options.

Return type

matplotlib.animation.Animation

init_for_simulator(simulator: cleo.base.CLSimulator)[source]#

Initialize device for simulator on initial injection.

This function is called only the first time a device is injected into a simulator and performs any operations that are independent of the individual neuron groups it is connected to.

Parameters

simulator (CLSimulator) – simulator being injected into

neuron_groups: list[brian2.groups.neurongroup.NeuronGroup]#
cleo.viz.plot(*neuron_groups: brian2.groups.neurongroup.NeuronGroup, xlim: Optional[Tuple[float, float]] = None, ylim: Optional[Tuple[float, float]] = None, zlim: Optional[Tuple[float, float]] = None, colors: Optional[collections.abc.Iterable] = None, axis_scale_unit: brian2.units.fundamentalunits.Unit = umetre, devices: collections.abc.Iterable[Union[cleo.base.InterfaceDevice, Tuple[cleo.base.InterfaceDevice, dict]]] = [], invert_z: bool = True, scatterargs: dict = {}, sim: Optional[cleo.base.CLSimulator] = None, **figargs: Any) → None[source]#

Visualize neurons and interface devices

Parameters

  • xlim (Tuple[float, float], optional) – xlim for plot, determined automatically by default

  • ylim (Tuple[float, float], optional) – ylim for plot, determined automatically by default

  • zlim (Tuple[float, float], optional) – zlim for plot, determined automatically by default

  • colors (Iterable, optional) – colors, one for each neuron group, automatically determined by default

  • axis_scale_unit (Unit, optional) – Brian unit to scale lim params, by default mm

  • devices (Iterable[Union[InterfaceDevice, Tuple[InterfaceDevice, dict]]], optional) – devices to add to the plot or (device, kwargs) tuples. add_self_to_plot() is called for each, using the kwargs dict if given. By default []

  • invert_z (bool, optional) – whether to invert z-axis, by default True to reflect the convention that +z represents depth from cortex surface

  • scatterargs (dict, optional) – arguments passed to plt.scatter() for each neuron group, such as marker

  • sim (CLSimulator, optional) – Optional shortcut to include all neuron groups and devices

  • **figargs (Any, optional) – keyword arguments passed to plt.figure(), such as figsize

Raises

ValueError – When neuron group doesn’t have x, y, and z already defined