nirs4all.visualization.chart_utils.matrix_builder module

MatrixBuilder - Build matrices for heatmap visualizations.

class nirs4all.visualization.chart_utils.matrix_builder.MatrixBuilder

Bases: object

Build matrices for heatmap visualizations.

Handles grouping scores by variables and creating 2D matrices with support for different aggregation strategies.

Optimized to work with PredictionResultsList from predictions.top().

static build_matrices(score_dict: Dict, aggregation: str, higher_better: bool, natural_sort: bool = True) → Tuple[List, List, ndarray, ndarray]

Build matrices from score dictionary.

Parameters:

• score_dict – Dict of scores grouped by x and y variables. Can be {y: {x: [scores]}} or {y: {x: (score, count)}}.

• aggregation – Aggregation method (‘best’, ‘mean’, ‘median’, ‘identity’). Use ‘identity’ if scores are already aggregated tuples.

• higher_better – Whether higher values are better.

• natural_sort – Whether to use natural sorting for labels.

Returns:

Tuple of (y_labels, x_labels, score_matrix, count_matrix).

static build_score_dict(predictions_list, x_var: str, y_var: str, display_score_field: str, rank_field: str | None = None) → Dict

Group scores by x and y variables from PredictionResultsList.

Parameters:

• predictions_list – List of prediction results.

• x_var – Variable name for x-axis grouping.

• y_var – Variable name for y-axis grouping.

• display_score_field – Field name for display scores.

• rank_field – Optional field name for ranking scores.

Returns:

{y_val: {x_val: [(display_score, rank_score), …]}} or {y_val: {x_val: [score1, score2, …]}} if no rank_field.

Return type:

Dict structure

static build_score_dict_with_dynamic_partition(predictions_list, x_var: str, y_var: str, metric: str, use_rank_scores: bool = False) → Dict

Group scores by x and y variables when partition is one of the grouping variables.

This method handles the special case where ‘partition’ is used as x_var or y_var. It extracts the score from the appropriate partition field based on the partition value.

Parameters:

• predictions_list – List of prediction results.

• x_var – Variable name for x-axis grouping.

• y_var – Variable name for y-axis grouping.

• metric – Metric name to extract scores for.

• use_rank_scores – If True, include rank scores for proper aggregation.

Returns:

{y_val: {x_val: [score1, score2, …]}} or

{y_val: {x_val: [(display_score, rank_score), …]}}

Return type:

Dict structure