NeSy4PPM package

Subpackages

• NeSy4PPM.Data_preprocessing package
  • Submodules
  • NeSy4PPM.Data_preprocessing.data_preprocessing module
    • encode_prefixes()
    • end_to_end_process()
    • extract_encode_prefixes()
    • extract_trace_prefixes()
  • NeSy4PPM.Data_preprocessing.log_utils module
    • LogData
      • LogData.act_enc_mapping
      • LogData.act_name_key
      • LogData.case_name_key
      • LogData.encode_log()
      • LogData.evaluation_prefix_end
      • LogData.evaluation_prefix_start
      • LogData.evaluation_trace_ids
      • LogData.feedback_trace_ids
      • LogData.log
      • LogData.log_name
      • LogData.max_len
      • LogData.median
      • LogData.read_log()
      • LogData.remove_variant_outliers()
      • LogData.res_enc_mapping
      • LogData.res_name_key
      • LogData.timestamp_key
      • LogData.training_trace_ids
  • NeSy4PPM.Data_preprocessing.shared_variables module
  • NeSy4PPM.Data_preprocessing.utils module
    • BK_type
      • BK_type.Declare
      • BK_type.Declare_End
      • BK_type.ProbDeclare
      • BK_type.Procedural
      • BK_type.Procedural_End
    • Encodings
      • Encodings.Index_based
      • Encodings.Multi_encoders
      • Encodings.One_hot
      • Encodings.Shrunk_Index_based
    • NN_model
      • NN_model.LSTM
      • NN_model.Transformer
    • discover_Petri_nets()
    • extract_last_model_checkpoint()
    • load_bk()
    • prepare_encoded_data()
  • Module contents
• NeSy4PPM.Prediction package
  • Submodules
  • NeSy4PPM.Prediction.Checkers module
    • Constraint_checker
      • Constraint_checker.check_trace_conformance()
    • TraceDeclareAnalyzer
      • TraceDeclareAnalyzer.run()
  • NeSy4PPM.Prediction.create_event_log module
    • convert_to_log()
    • convert_trace()
  • NeSy4PPM.Prediction.inference_algorithm module
    • run_experiments()
  • NeSy4PPM.Prediction.predict_suffix module
    • predict_evaluate()
  • NeSy4PPM.Prediction.prepare_data module
    • ConstraintChecker
      • ConstraintChecker.POSSIBLY_SATISFIED
      • ConstraintChecker.POSSIBLY_VIOLATED
      • ConstraintChecker.SATISFIED
      • ConstraintChecker.VIOLATED
    • declare_compliance_checking()
    • encode()
    • fitness_checking()
    • get_beam_size()
    • get_pn_fitness()
  • Module contents
• NeSy4PPM.ProbDeclmonitor package
  • Submodules
  • NeSy4PPM.ProbDeclmonitor.autUtils module
    • TruthValue
      • TruthValue.PERM_SAT
      • TruthValue.PERM_VIOL
      • TruthValue.POSS_SAT
      • TruthValue.POSS_VIOL
    • get_state_for_prefix()
    • get_state_truth_value()
    • prefix_to_word()
  • NeSy4PPM.ProbDeclmonitor.ltlUtils module
    • get_constraint_formula()
  • NeSy4PPM.ProbDeclmonitor.probDeclPredictor module
    • AggregationMethod
      • AggregationMethod.AVG
      • AggregationMethod.MAX
      • AggregationMethod.MIN
      • AggregationMethod.SUM
    • ProbDeclarePredictor
      • ProbDeclarePredictor.loadProbDeclModel()
      • ProbDeclarePredictor.processPrefix()
    • createMonafile()
    • get_aggregate_score()
    • invoke_mona()
    • to_dfa()
  • Module contents
• NeSy4PPM.Training package
  • Submodules
  • NeSy4PPM.Training.Modulator module
    • Modulator
      • Modulator.build()
      • Modulator.call()
      • Modulator.compute_output_shape()
      • Modulator.get_config()
  • NeSy4PPM.Training.train_common module
    • CustomTransformer
      • CustomTransformer.call()
      • CustomTransformer.get_config()
    • create_checkpoints_path()
    • plot_loss()
  • NeSy4PPM.Training.train_model module
    • train()
  • Module contents

Submodules

NeSy4PPM.Evaluation module

NeSy4PPM.Evaluation.discover_bpmn(log_path)

NeSy4PPM.Evaluation.discover_petri_net(log_path)

NeSy4PPM.Evaluation.evaluate_all(output_folder, filename, metrics, log_data: LogData | None = None, resource: bool = False, declare_model=None, petri_net_model=None, fitness_method=None, weight=None, prefix_len=None, traces_ids=[], results_fold='results')

NeSy4PPM.Evaluation.get_fitness(event_log, bk_model, method_fitness='fitness_token_based_replay')

NeSy4PPM.Evaluation.log_conformance(log, bk_model)

Module contents