RawDataView

class RawDataView()

Bases: MetaEventTabView

Subclass of MetaEventTabView for visualizing raw signal data and PSD plots.

Handles plot rendering, signal responses, and interactions with readers, filters, and event finders.

Public Methods

RawDataView.get_current_view() → str

Abstract method to get the name of the current view.

Subclasses must override this to return the current view name.

Returns:

The name of the view currently displayed.

Return type:

str

Raises:

NotImplementedError – Always, unless overridden by a subclass.

RawDataView.get_save_filename() → str

Open a dialog to save a CSV file.

Returns:

Selected file path, or an empty string if cancelled.

Return type:

str

RawDataView.get_walkthrough_steps() → List[Tuple[str, str, str, Callable[[], QWidget | List[QWidget]]]]

Abstract method to retrieve the walkthrough steps for the current view.

Subclasses must override this to return a list of walkthrough steps, each a (title, description, view name, widget getter) tuple.

Returns:

The ordered walkthrough steps for this view.

Return type:

List[WalkthroughStep]

Raises:

NotImplementedError – Always, unless overridden by a subclass.

RawDataView.handle_parameter_change(submodel_name: str, action_name: str, args: tuple) → None

Handle parameter changes triggered by RawDataControls and dispatch the corresponding action.

Parameters:

  • submodel_name (str) – Name of the submodel triggering the action.

  • action_name (str) – Action identifier string.

  • args (tuple) – Tuple of arguments passed with the signal.

RawDataView.register_eventfinder_channels(channels_by_finder: Mapping[str, Sequence[int]]) → None

Give each event finder not seen before a default time range for every channel.

The channel lookup is RawDataController’s: it resolves every finder up front and hands the answers down. A finder absent from channels_by_finder, or present with no channels, is left unregistered so the next push retries it. Registering one whose lookup failed would leave it with empty time limits permanently, since nothing asks again for a finder it already knows.

A finder already in analysis_time_limits keeps the ranges the user set on it; only genuinely new finders get defaults.

Parameters:

channels_by_finder (Mapping[str, Sequence[int]]) – channels per event finder, for finders that answered

Returns:

None

Return type:

None

RawDataView.set_commit_statuses(writer: str, statuses: List[Tuple[int, str | None]], experiment_name: str, output_file: str) → None

Confirm replacing any channel the output already holds, then ask for the commit.

One prompt per held channel, as the event-finding prompt does, so declining one keeps that channel’s events and skips only it. A stored experiment name that differs from experiment_name is named in the prompt for the user to decide on: the events file keys on channel alone, so a Yes replaces the other experiment’s events.

Parameters:

  • writer (str) – the writer plugin’s key

  • statuses (List[Tuple[int, Optional[str]]]) – (channel, stored experiment name or None) for each channel that answered

  • experiment_name (str) – the experiment name this commit would store

  • output_file (str) – the writer’s output file, for the prompt

Returns:

None

Return type:

None

RawDataView.set_event_plot_data(event_data: Sequence[ndarray[tuple[int, ...], dtype[float64]]], time_bases: Sequence[ndarray[tuple[int, ...], dtype[float64]]], event_indices: Sequence[int]) → None

Plot the events the Controller loaded, or report that there were none.

event_indices is the surviving list: an event the finder could not supply is dropped by the Controller, so the traces and the indices labelling them stay aligned without this method having to prune anything.

Parameters:

  • event_data (Sequence[npt.NDArray[np.float64]]) – one array of samples per surviving event

  • time_bases (Sequence[npt.NDArray[np.float64]]) – one time axis per event in microseconds, index-aligned with event_data and built by MetaModel.time_bases

  • event_indices (Sequence[int]) – the event indices that produced data, index-aligned with event_data

Returns:

None

Return type:

None

RawDataView.set_eventfinding_statuses(eventfinder: str, statuses: List[Tuple[int, bool]], data_filter: str) → None

Confirm any already-finished channels, then ask for the approved ones to run.

The per-channel prompt is kept exactly as it was, including that declining one channel skips only that channel - a coarser guard that abandoned the batch would be a behaviour change.

A channel with no configured time limits stops the whole launch, as before. What changed is how it stops: it used to raise KeyError out of this tab, which was survivable while the call chain started at a Qt signal on the View. It now runs inside a call from the Controller’s slot, where an escaping exception would reach Qt, so it is reported instead. Nothing launches either way.

Parameters:

  • eventfinder (str) – the event finder plugin’s key

  • statuses (List[Tuple[int, bool]]) – (channel, already_finished) for each channel that answered

  • data_filter (str) – the filter plugin’s key, or “” for no filtering

Returns:

None

Return type:

None

RawDataView.set_psd(Pxx_list: List[ndarray[tuple[int, ...], dtype[float64]]], rms_list: List[ndarray[tuple[int, ...], dtype[float64]]], frequency: ndarray[tuple[int, ...], dtype[float64]] | None, kept_indices: List[int]) → None

Set the PSD and RMS lists for visualization.

Parameters:

  • Pxx_list (List[npt.NDArray[np.float64]]) – Power spectral density data, one array per kept channel.

  • rms_list (List[npt.NDArray[np.float64]]) – RMS noise data, one array per kept channel.

  • frequency (Optional[npt.NDArray[np.float64]]) – Frequency axis data, or None if no channel was processed.

  • kept_indices (List[int]) – Indices into the channel list passed to calculate_psd that were successfully processed, since some channels may have been skipped.

RawDataView.set_trace_data(data_list: Sequence[ndarray[tuple[int, ...], dtype[float64]]], time_bases: Sequence[ndarray[tuple[int, ...], dtype[float64]]], channels: Sequence[int], start: float, baseline: bool) → None

Plot the trace the Controller loaded, or report that there was none.

The tail of _handle_load_data_and_update_plot. channels is the surviving list - a channel the reader could not supply is dropped by the Controller - so it and data_list stay index-aligned without this method having to prune anything.

Parameters:

  • data_list (Sequence[npt.NDArray[np.float64]]) – one array per surviving channel

  • time_bases (Sequence[npt.NDArray[np.float64]]) – one time axis per channel, index-aligned with data_list

  • channels (Sequence[int]) – the channels that produced data, index-aligned with data_list

  • start (float) – the start time being plotted from

  • baseline (bool) – whether the user asked for the baseline band

Returns:

None

Return type:

None

RawDataView.set_trace_for_psd(data_list: Sequence[ndarray[tuple[int, ...], dtype[float64]]], channels: Sequence[int]) → None

Compute and draw the PSD of the trace the Controller loaded.

Only the loading happens elsewhere; the PSD computation below asks this tab’s own Controller through calculate_psd and reads the answer back off psd_kept_indices and friends on the next statement. That read is safe because the connection is direct, so set_psd has already run by the time it returns - an invariant worth knowing before anyone makes the connection queued.

Parameters:

  • data_list (Sequence[npt.NDArray[np.float64]]) – one array per surviving channel

  • channels (Sequence[int]) – the channels that produced data, index-aligned with data_list

Returns:

None

Return type:

None

RawDataView.update_available_plugins(available_plugins: Dict[str, List[str]]) → None

Called whenever a new plugin is instantiated elsewhere in the app, to keep an up-to-date list of possible data sources for use by this plugin.

Parameters:

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

RawDataView.update_channels(channels: Sequence[int]) → None

Update the channel combo box with available channels.

Parameters:

channels (Sequence[int]) – Available channel identifiers.

RawDataView.update_plot(data: Sequence[ndarray[tuple[int, ...], dtype[float64]]], time_bases: Sequence[ndarray[tuple[int, ...], dtype[float64]]], channels: Sequence[int], start: float = 0, baseline_stats: List[Tuple[float, float, float] | None] | None = None) → None

Update the plot area with the provided data across multiple channels in a grid layout.

Parameters:

  • data (Sequence[npt.NDArray[np.float64]]) – One array of current samples per channel.

  • time_bases (Sequence[npt.NDArray[np.float64]]) – One time axis per channel in seconds from the start of the recording, index-aligned with data. Built by MetaModel.time_bases, since the axis is a property of the samples and the rate they were taken at rather than of the drawing.

  • channels (Sequence[int]) – List of channel identifiers corresponding to the data.

  • start (float) – Time offset added to the plotted time axis, in seconds.

  • baseline_stats (Optional[List[Optional[Tuple[float, float, float]]]]) – Per-channel (amplitude, mean, stdev) from the Model, index-aligned with data, or None to draw no baseline overlay at all. An individual entry may be None where that channel’s fit failed.

RawDataView.update_plot_samplerate(samplerate: float) → None

Update the sampling rate used for plotting.

Parameters:

samplerate (float) – Sampling frequency in Hz.

RawDataView.update_psd(psd_data: Sequence[ndarray[tuple[int, ...], dtype[float64]]], rms_data: Sequence[ndarray[tuple[int, ...], dtype[float64]]], frequency: ndarray[tuple[int, ...], dtype[float64]], channels: Sequence[int]) → None

Update the plot area with the provided psd and frequency data across multiple channels in a grid layout.

Parameters:

  • psd_data (Sequence[npt.NDArray[np.float64]]) – Power spectral density values, one array for each channel.

  • rms_data (Sequence[npt.NDArray[np.float64]]) – Integrated RMS noise values corresponding to psd_data, one array for each channel.

  • frequency (npt.NDArray[np.float64]) – Frequency axis shared across all channels.

  • channels (Sequence[int]) – List of channel identifiers corresponding to the data.

Private Methods

RawDataView._init() → None

Initialize the RawDataView-specific attributes.