EventAnalysisController

class EventAnalysisController(available_subclasses: Optional[Mapping[str, List[str]]] = None, **kwargs)

Bases: MetaController

Subclass of MetaController for for managing event analysis view-model logic.

Connects the EventAnalysisModel and EventAnalysisView.

Public Methods

EventAnalysisController.relay_eventfitting_status(status: bool) → None

Relay event fitting status to the view.

Parameters:

status (bool) – Boolean indicating the success of event fitting.

EventAnalysisController.set_event_filter(data_filter: Callable) → None

Set the callable function used to filter event data.

Parameters:

data_filter (Callable) – A function that applies filtering logic to event data.

EventAnalysisController.set_eventfitting_status(status: bool) → None

Set the current status of the event fitting process in the view.

Parameters:

status (bool) – Boolean indicating if event fitting was successful.

EventAnalysisController.set_num_events_allowed(num_events: int) → None

Set the maximum number of events allowed for processing or display.

Parameters:

num_events (int) – Maximum number of events to handle.

EventAnalysisController.update_available_plugins(available_plugins: dict) → None

Relay an updated dict of available plugin keys, keyed by metaclass, to both the model and the view.

Parameters:

available_plugins (dict) – dict of lists keyed by MetaClass, listing the identifiers of all instantiated plugins throughout the app.

EventAnalysisController.update_channels(channels: List[int]) → None

Update the view with the current number of channels available or selected.

Parameters:

channels (List[int]) – List of channel identifiers.

EventAnalysisController.update_features(vertical: List[float] | None = None, horizontal: List[float] | None = None, points: List[Tuple[float, float]] | None = None, vlabels: List[str] | None = None, hlabels: List[str] | None = None, plabels: List[str] | None = None) → None

Update the plot with visual annotations including vertical lines, horizontal lines, and point markers.

Validates that each visual feature has a corresponding label (or explicit None) if labels are provided.

Parameters:

  • vertical (Optional[List[float]]) – Vertical line positions for the event being plotted.

  • horizontal (Optional[List[float]]) – Horizontal line positions for the event being plotted.

  • points (Optional[List[Tuple[float, float]]]) – (x, y) point coordinates for the event being plotted.

  • vlabels (Optional[List[str]]) – Labels for the vertical lines.

  • hlabels (Optional[List[str]]) – Labels for the horizontal lines.

  • plabels (Optional[List[str]]) – Labels for the point markers.

Raises:

ValueError – If a label list is provided and its length does not match the corresponding feature list.

EventAnalysisController.update_plot_data(data: Any | None = None) → None

Update the view with new plot data.

Parameters:

data (Optional[Any]) – Optional data to be plotted (e.g., event traces or fitted results).

EventAnalysisController.update_plot_samplerate(samplerate: float) → None

Set the sampling rate to be used for time axis conversion in the plot.

Parameters:

samplerate (float) – Sampling rate in Hz.

Private Methods

EventAnalysisController._init() → None

Perform additional initialization specific to the algorithm being implemented. Must be implemented by subclasses.

This function is called at the end of the class constructor to perform additional initialization specific to the algorithm being implemented. kwargs provided to the base class constructor are available as class attributes.

EventAnalysisController._setup_connections() → None

Set up any local connections between the subordinate view and model