plot_spike_trains#

plot_spike_trains(
spike_trains__matrix,
timestep__ms,
axs,
pool_current__matrix=None,
cortical_input__matrix=None,
pool_to_plot=None,
apply_default_formatting=True,
**kwargs,
)[source]#

Plot spike trains for each motor neuron pool.

Parameters:

  • spike_trains__matrix (SPIKE_TRAIN__MATRIX) – The spike trains matrix to plot.

  • timestep__ms (float) – Simulation timestep in ms.

  • axs (beartype.cave.IterableType[matplotlib.axes.Axes]) – Matplotlib axes to plot on. This could be the same axis for all pools, or a separate axis for each pool.

  • pool_current__matrix (INPUT_CURRENT__MATRIX | None, optional) – The input current matrix to plot, by default None.

  • cortical_input__matrix (CORTICAL_INPUT__MATRIX | None, optional) – The cortical input matrix to plot, by default None.

  • pool_to_plot (list[int] | None, optional) – The pools to plot if not all pools should be plotted, by default None (all pools are plotted).

  • apply_default_formatting (bool, optional) – Whether to apply default formatting to the plot, by default True.

  • **kwargs (Any) – Additional keyword arguments to pass to the plot function. Only used if apply_default_formatting is False.

Returns:

The axes that were plotted on.

Return type:

beartype.cave.IterableType[matplotlib.axes.Axes]

Raises:

ValueError – If the number of axes does not match the number of pools to plot.