Arcana package

Subpackages

• Arcana Logger
  • Submodules
  • arcana.logger.logger module
    • get_logger()
    • setup_applevel_logger()
  • Module contents
• Arcana Losses
  • Submodules
  • arcana.losses.loss module
    • CombinedHPLoss
      • CombinedHPLoss.forward()
    • CombinedLPLoss
      • CombinedLPLoss.forward()
    • HuberLoss
    • LogCoshLoss
      • LogCoshLoss.forward()
    • LossFactory
      • LossFactory.create_loss()
    • MSELoss
    • PinballLoss
      • PinballLoss.forward()
      • PinballLoss.pinball_loss_numpy()
    • QuantileLoss
      • QuantileLoss.forward()
    • is_numpy()
    • is_tensor()
    • to_numpy()
    • to_tensor()
  • arcana.losses.loss_trace module
    • LossTrace
      • LossTrace.calculate_batch_loss_train()
      • LossTrace.calculate_batch_loss_validation()
      • LossTrace.calculate_epoch_loss()
      • LossTrace.reset_temp_loss_trace()
  • Module contents
• Arcana Models
  • Subpackages
    • Arcana Models: Decoders
      • Submodules
      • arcana.models.decoders.additive_decoder module
      • arcana.models.decoders.base_decoder module
      • arcana.models.decoders.multihead_decoder module
      • Module contents
    • Arcana models: encoders
      • Submodules
      • arcana.models.encoders.additive_encoder module
      • arcana.models.encoders.base_encoder module
      • arcana.models.encoders.multihead_encoder module
      • Module contents
    • Arcana Models: sequence_to_sequence
      • Submodules
      • arcana.models.sequence_to_sequence.seq2seq_factory module
      • arcana.models.sequence_to_sequence.sequence_to_sequence module
      • Module contents
  • Module contents
• Arcana Plots
  • Submodules
  • arcana.plots.analysis_plot_utils module
    • AnalysisPlotUtils
      • AnalysisPlotUtils.plot_additive_attention()
      • AnalysisPlotUtils.plot_all_multihead_attention()
      • AnalysisPlotUtils.plot_sensitivity_analyis()
    • ScalarFormatterForceFormat
  • arcana.plots.plot_utils module
    • plot_model_learning_rate()
    • plot_sample_prediction()
    • plot_train_val_loss()
    • plot_train_val_loss_individual()
  • arcana.plots.plots module
    • Plots
      • Plots.plot_line()
      • Plots.plot_scatter()
      • Plots.set_labels()
  • Module contents
• Arcana Prediction
  • Submodules
  • arcana.prediction.quantile_prediction module
    • QuantilePredictor
      • QuantilePredictor.apply_correct_exogenous()
      • QuantilePredictor.calculate_metrics()
      • QuantilePredictor.metrics_preparation()
      • QuantilePredictor.plot_analysis()
      • QuantilePredictor.plot_predictions()
      • QuantilePredictor.predict_data_preparation()
      • QuantilePredictor.predict_quantiles()
      • QuantilePredictor.save_attention()
      • QuantilePredictor.save_metrics()
      • QuantilePredictor.save_predictions()
      • QuantilePredictor.save_sensitivity()
      • QuantilePredictor.save_transformed_predictions()
      • QuantilePredictor.transform_predictions_to_numpy()
    • metrics_helper()
  • Module contents
• Arcana Procedure
  • Submodules
  • arcana.procedures.config_handler module
    • ConfigHandler
      • ConfigHandler.get_data_config()
      • ConfigHandler.get_general_config()
      • ConfigHandler.get_model_config()
      • ConfigHandler.get_procedure_config()
    • DataConfig
      • DataConfig.data_headers
      • DataConfig.maximum_available_cycles
      • DataConfig.number_of_samples
      • DataConfig.path_to_config
      • DataConfig.test_sample
      • DataConfig.train_ratio
      • DataConfig.val_test_ratio
    • GeneralConfig
      • GeneralConfig.data_name
      • GeneralConfig.input_data_folder
      • GeneralConfig.path_to_config
      • GeneralConfig.pretrained_model
      • GeneralConfig.scaler_model
      • GeneralConfig.test_id
    • ModelConfig
      • ModelConfig.read_tuning_conf()
    • ProcedureConfig
      • ProcedureConfig.attention_type
      • ProcedureConfig.learning_rate_type
      • ProcedureConfig.naive_training
      • ProcedureConfig.number_of_trials
      • ProcedureConfig.optuna_tuning
      • ProcedureConfig.path_to_config
      • ProcedureConfig.predicting
      • ProcedureConfig.preprocess_data
      • ProcedureConfig.transfer_learning
  • arcana.procedures.finetuning module
    • FineTuning
      • FineTuning.load_model()
      • FineTuning.training()
      • FineTuning.unfreeze_decoder()
      • FineTuning.unfreeze_fc_and_attention()
      • FineTuning.unfreeze_fully_connected()
  • arcana.procedures.predicting module
    • PredictProcedure
      • PredictProcedure.all_preparation()
      • PredictProcedure.get_pretrained_model()
      • PredictProcedure.get_test_data()
      • PredictProcedure.predicting()
      • PredictProcedure.predicting_all()
      • PredictProcedure.preparation()
  • arcana.procedures.training module
    • TrainProcedure
      • TrainProcedure.data_splits()
      • TrainProcedure.loader_initialization()
      • TrainProcedure.model_parameter_initialization()
      • TrainProcedure.save_data_splits()
      • TrainProcedure.save_model_parameters()
      • TrainProcedure.set_device()
      • TrainProcedure.train_element_initialization()
      • TrainProcedure.training()
  • arcana.procedures.tuning module
    • TuneProcedure
      • TuneProcedure.rename_trials()
      • TuneProcedure.save_tuning_params()
      • TuneProcedure.tuning()
  • Module contents
• Arcana Processing
  • Submodules
  • arcana.processing.data_processing module
    • DataPreparation
      • DataPreparation.data_splits()
      • DataPreparation.get_data_for_model()
      • DataPreparation.get_max_available_scaled_cycle()
      • DataPreparation.pad_the_splits()
      • DataPreparation.prepare_data_for_model()
      • DataPreparation.prepare_test_data_for_pretrained_model()
      • DataPreparation.standardize_data()
      • DataPreparation.tensorized_and_pad()
  • Module contents
• Arcana Regularizations
  • Submodules
  • arcana.regularizations.optimizer_scheduler module
    • SchedulerFactory
      • SchedulerFactory.get_scheduler()
  • arcana.regularizations.stopping_criteria module
    • EarlyStopping
      • EarlyStopping.step()
  • arcana.regularizations.teacher_forcing module
    • TeacherForcingScheduler
      • TeacherForcingScheduler.get_ratio()
  • Module contents
• Arcana Training
  • Submodules
  • arcana.training.train_model module
    • Seq2SeqTrainer
      • Seq2SeqTrainer.calculate_overall_combined_loss()
      • Seq2SeqTrainer.calculate_overall_loss()
      • Seq2SeqTrainer.compute_loss()
      • Seq2SeqTrainer.count_parameters()
      • Seq2SeqTrainer.early_stopping_check()
      • Seq2SeqTrainer.initialize_training()
      • Seq2SeqTrainer.plot_training_params()
      • Seq2SeqTrainer.save_training_results_and_plots()
      • Seq2SeqTrainer.train_epoch()
      • Seq2SeqTrainer.train_model()
      • Seq2SeqTrainer.update_training_params()
      • Seq2SeqTrainer.validation_epoch()
  • Module contents
• Arcana Utils
  • Submodules
  • arcana.utils.utils module
    • align_and_truncate_samples()
    • create_dir()
    • handle_tensor()
    • pad_array_to_length()
    • prepare_folder_structure()
    • prepare_optuna_folder_structure()
    • save_optuna_fig()
    • save_plots()
    • save_test_data()
    • standardize_dataset()
  • Module contents

Module contents

Top-level package for Arcana.