nirs4all.controllers.charts.targets module

YChartController - Y values histogram visualization with train/test split and folds.

class nirs4all.controllers.charts.targets.YChartController[source]

Bases: OperatorController

execute(step_info: ParsedStep, dataset: SpectroDataset, context: ExecutionContext, runtime_context: Any, source: int = -1, mode: str = 'train', loaded_binaries: Any = None, prediction_store: Any = None) Tuple[ExecutionContext, Any][source]

Execute y values histogram visualization.

If cross-validation folds exist (more than 1 fold), displays a grid showing: - One histogram per fold validation set - One histogram for the test partition (if available)

Otherwise, displays a simple train vs test histogram.

Supports optional parameters via dict syntax:

{“chart_y”: {“include_excluded”: True, “highlight_excluded”: True}}

Parameters:
  • include_excluded – If True, include excluded samples in visualization

  • highlight_excluded – If True, show excluded samples as separate histogram

Returns:

Tuple of (context, StepOutput)

classmethod matches(step: Any, operator: Any, keyword: str) bool[source]

Check if the operator matches the step and keyword.

priority: int = 10
classmethod supports_prediction_mode() bool[source]

Chart controllers should skip execution during prediction mode.

classmethod use_multi_source() bool[source]

Check if the operator supports multi-source datasets.