2.1.1.1.1. emicroml.modelling.cbed.distortion.estimation

For training machine learning models for distortion estimation in CBED.

Functions

combine_ml_dataset_files	Combine files storing machine learning datasets.
generate_and_save_ml_dataset	Generate a machine learning dataset.
load_ml_model_from_file	Load a machine learning model from a file.
load_ml_model_from_state_dict	Load a machine learning model from a dictionary
ml_data_dict_to_distortion_models	Convert a dictionary representation of ML data instances to a sequence of distortion models.
ml_data_dict_to_signals	Convert a dictionary representation of ML data instances to a sequence of Hyperspy signals.
normalize_normalizable_elems_in_ml_data_dict	Normalize in-place normalizable features of a dictionary representation of machine learning data instances.
split_ml_dataset_file	Split file storing a machine learning dataset.
unnormalize_normalizable_elems_in_ml_data_dict	Unnormalize in-place normalizable features of a dictionary representation of machine learning data instances.

Classes

DefaultCBEDPatternGenerator	The default class of random "fake" CBED pattern generators.
DefaultDistortionModelGenerator	The default class of random distortion model generators.
MLDataset	A wrapper to the PyTorch dataset class torch.utils.data.Dataset.
MLDatasetManager	A machine learning dataset manager.
MLModel	A machine learning model for distortion estimation in CBED.
MLModelTester	A machine learning model tester.
MLModelTrainer	A machine learning model trainer.