| """RunResult container for spike data and analysis access."""
|
|
|
| from .exceptions import NeurocoreError
|
|
|
|
|
| class RunResult:
|
| """Encapsulates results from a run() call."""
|
|
|
| def __init__(self, total_spikes, timesteps, spike_trains, placement, backend):
|
| self.total_spikes = total_spikes
|
| self.timesteps = timesteps
|
| self.spike_trains = spike_trains
|
| self.placement = placement
|
| self.backend = backend
|
|
|
| def raster_plot(self, filename=None, show=True, populations=None):
|
| """Generate a matplotlib spike raster plot.
|
|
|
| Only available with Simulator backend (hardware doesn't report
|
| per-neuron spike data).
|
| """
|
| if not self.spike_trains:
|
| raise NeurocoreError(
|
| "Per-neuron spike data not available. "
|
| "Hardware only returns total spike count. "
|
| "Use Simulator backend for raster plots.")
|
| from . import analysis
|
| return analysis.raster_plot(self, filename, show, populations)
|
|
|
| def firing_rates(self, population=None):
|
| """Compute mean firing rate (spikes/timestep) per neuron."""
|
| from . import analysis
|
| return analysis.firing_rates(self, population)
|
|
|
| def spike_count_timeseries(self, bin_size=1):
|
| """Total spikes per time bin across all neurons."""
|
| from . import analysis
|
| return analysis.spike_count_timeseries(self, bin_size)
|
|
|
| def isi_histogram(self, bins=50):
|
| """Inter-spike interval distribution."""
|
| from . import analysis
|
| return analysis.isi_histogram(self, bins)
|
|
|
| def to_dataframe(self):
|
| """Export spike data as a pandas DataFrame."""
|
| from . import analysis
|
| return analysis.to_dataframe(self)
|
|
|
| def __repr__(self):
|
| return (f"RunResult(total_spikes={self.total_spikes}, "
|
| f"timesteps={self.timesteps}, backend='{self.backend}')")
|
|
|
