hookeai.model_architectures.procedures.convergence_plots

Plots for convergence analysis based on RNN-based models.

Functions

plot_prediction_loss_convergence

Plot average prediction loss against training data set size.

plot_best_parameters_convergence

Plot best state parameters versus training data set size.

plot_time_series_convergence

Plot time series predictions versus ground-truth.

plot_prediction_loss_convergence_uq

Plot average prediction loss versus training data set size.

plot_best_parameters_convergence_uq

Plot best state parameters versus training data set size.

plot_time_series_convergence_uq

Plot time series predictions versus ground-truth.

Functions

build_prediction_data_arrays(...[, samples_ids])	Build samples predictions data arrays with predictions and ground-truth.
build_time_series_predictions_data(...[, ...])	Build times series prediction and ground-truth data arrays.
find_unique_file_with_regex(directory, regex)	Find file in directory based on regular expression.
load_dataset(dataset_file_path)	Load PyTorch time series data set.
make_directory(directory[, is_overwrite])	Create a directory.
plot_best_parameters_convergence(...[, ...])	Plot best state parameters versus training data set size.
plot_best_parameters_convergence_uq(...[, ...])	Plot best state parameters versus training data set size.
plot_boxplots(data_boxplots[, data_labels, ...])	Plot set of box plots.
plot_prediction_loss_convergence(...[, ...])	Plot average prediction loss versus training data set size.
plot_prediction_loss_convergence_uq(...[, ...])	Plot average prediction loss versus training data set size.
plot_time_series_convergence(...[, ...])	Plot time series predictions versus ground-truth.
plot_time_series_convergence_uq(...[, ...])	Plot time series predictions versus ground-truth.
plot_time_series_prediction(prediction_sets)	Plot time series predictions.
plot_truth_vs_prediction(prediction_sets[, ...])	Plot ground-truth versus predictions.
read_best_parameters_from_file(...)	Read best performance state model parameters from file.
save_figure(figure, filename[, height, ...])	Save Matplotlib figure.
scatter_xy_data(data_xy[, data_labels, ...])	Scatter data in xy axes.