visualization

Visualization components for LOS Estimator.

class los_estimator.visualization.DeconvolutionAnimator(all_fit_results: MultiSeriesFitResults, series_data: SeriesData, model_config: ModelConfig, visualization_config: VisualizationConfig, visualization_context: VisualizationContext, output_folder_config: OutputFolderConfig, animation_config: AnimationConfig)

Bases: DeconvolutionPlots

Animation functionality for deconvolution analysis.

animate_fit_deconvolution(): Create animation of fit deconvolution process.

save_n_show_animation_frame(fig: matplotlib.pyplot.Figure, num: int): Save the current figure as an animation frame.

class los_estimator.visualization.DeconvolutionPlots(all_fit_results: MultiSeriesFitResults, series_data: SeriesData, model_config: ModelConfig, visualization_config: VisualizationConfig, visualization_context: VisualizationContext, output_config: OutputFolderConfig)

Bases: VisualizerBase

Plotting functionality for deconvolution analysis.

Provides comprehensive visualization capabilities for analyzing and presenting the results of length of stay deconvolution models, including fit comparisons, kernel visualizations, and error analysis plots.

all_fit_results

Container with all fitting results.

Type:: MultiSeriesFitResults

series_data

Time series data used for fitting.

Type:: SeriesData

model_config

Configuration for model parameters.

Type:: ModelConfig

visualization_context

Shared visualization context.

Type:: VisualizationContext

output_config

Output directory configuration.

Type:: OutputFolderConfig

boxplot_errors(errors, title, ylabel, file, show_outliers): Create boxplot of errors.

generate_plots_for_run(): Generate all plots for a run.

plot_error_comparison(): Plot error comparison across models.

show_all_error_windows_superimposed(): Show all error windows superimposed.

show_all_predictions(): Show all predictions together.

show_error_windows(distro: str | List[str] | None = None): Show error windows for specified distributions.

superimpose_kernels(distro: str | List[str] | None = None): Show superimposed kernels for distributions.

los_estimator.visualization.get_color_palette() → List[str]

Get extended color palette for plotting.

Returns a comprehensive color palette combining matplotlib’s default color cycle with additional colors for extensive plotting needs.

Returns:: List of color codes in hexadecimal format.
Return type:: List[str]