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Editing a Fitted Model

The SuperGLM editor is a compact analyst workspace for reviewing and adjusting fitted one-dimensional effects. Python owns the fitted model, edit history, summaries, and evidence; the browser provides a fast visual preview and sends completed actions back to Python.

Open the Editor

Create an editor session from a fitted model and display its widget in Jupyter or VS Code:

from superglm.editor import EditorSession

session = EditorSession.from_model(
    model,
    terms=["age", "territory"],
    validation_data=(X_validation, y_validation, validation_weight),
)
session.widget()

The standard iframe is 1180 by 720 pixels. At narrower notebook widths the inspector becomes a drawer; in a short window the workspace scrolls instead of shrinking the plot into an unusable strip.

Select, Move, Zoom, and Handles

  • Select brushes points or levels. Shift-click toggles a point or level; Select all selects the complete active term.
  • Move drags selected relativities. The curve previews immediately and Python confirms the edit when the pointer is released.
  • Zoom drags a box. The mouse wheel zooms around the pointer and Home restores the fitted extent.
  • Handles edits a spline through fixed-x control handles. Basis contributions and the Build animation are available from Advanced when the fitted term exposes them.

The active mode is always visible in the left tool rail. Hover briefly over an icon, or focus it with the keyboard, to see its name and shortcut.

Curve Selection Operations

The floating palette acts on the current selection:

  • Increase or decrease moves the selected relativities by five percent.
  • Smooth reduces local variation while respecting adjacent unselected values.
  • Straighten selection interpolates the selected relativities between their first and last points.
  • Increasing and Decreasing apply anchored monotonic constraints.
  • Level left, Average, and Level right flatten the selection to the named reference value.
  • Snap highest and Snap lowest flatten to the selected extreme.

The icons remain compact so the plot stays large. Their delayed hover and immediate focus explanations describe the action before it is run.

Group and Ungroup Categorical Levels

Expanded and Collapsed display modes change only how an existing fitted grouping is drawn. They do not rename levels or change the fitted model.

Collapse selected levels, Ungroup selected levels, and Restore previous collapse are structural actions: SuperGLM refits the model and clears incompatible manual edit history. A confirmation is shown only when history would actually be discarded; it names the term or levels and the number of history entries. The refit overlay reports elapsed time. When the fit returns, the plot and summary change together; metrics may remain marked Updating briefly.

Long category names may appear shortened with an end ellipsis on the x-axis. This is display-only. Hover or focus the tick (or inspect the point tooltip) for the complete value; selection, grouping, history, exports, and saved models retain the exact original string.

Undo, Redo, and Recovery

Undo and Redo are visible in the application bar and expose their keyboard shortcuts. They operate on confirmed Python history, not on an uncommitted pointer preview.

If an edit request fails, the browser restores the last confirmed Python state and shows a persistent message. Choose Retry to repeat that action after recovery or Dismiss to keep the restored state. A failed metric, summary, or report refresh does not undo a valid model edit; only that evidence panel becomes Stale and offers Retry.

Evidence Freshness

The metric strip, summary, and reports distinguish these states:

  • Current describes the displayed model revision.
  • Updating retains the last confirmed values while Python computes the new revision.
  • Stale retains those values after a failed refresh and must not be read as current evidence.
  • Error means that panel has no confirmed value to retain.

Late responses for an older model revision or request sequence are ignored. Validation and test rows remain in Python; the browser receives aggregate metrics rather than a copy of the evaluation data.

Inspector and Help

Summary shows the current in-force model, History shows confirmed edits, Advanced contains infrequent curve and diagnostic controls, and Help lists modes, gestures, operations, and shortcuts. On a narrow screen these panes share a dismissible drawer. Escape closes a popover or drawer and returns focus to its launcher.

Export

Choose Export > Python model to download a fitted .joblib artifact or write it to a kernel path. SuperGLM loads the serialized artifact back before releasing it and, when evaluation rows are available, compares predictions on a bounded sample. The export always uses Python's current authoritative edit revision; display-only zoom, mode, grouping view, and truncated tick text are not written into the model.

Choose Export > Excel rating workbook for deployment-oriented rating tables. This export needs explicit training data or fit data retained by the model. Its Model Summary sheet contains typed ModelOverview and TermInference tables, so numbers remain numeric Excel cells rather than one large formatted text block.

Keyboard Shortcuts

  • Use Tab to reach application tabs, the tool rail, context controls, the SVG action palette, and the inspector.
  • Use arrow keys inside tab lists and the mode rail; Home and End jump to the first and last item.
  • Use Enter or Space to activate a focused control.
  • Use Escape to close the current popover, Help drawer, inspector drawer, or dialog.
  • Use the displayed Undo/Redo shortcut for confirmed curve edits.

Pointer editing remains the primary high-density curve workflow. Full per-point keyboard editing and an alternate editable data table are separate future accessibility enhancements.