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Getting started

  • Usage examples
  • Quick fault detection (CLI)
  • Configuration

Models and methods

  • ARCANA: Root cause analysis
  • CARE2Compare guide
  • CARE2Compare FAQ
  • Model overview
  • Sequence models
  • Sequence-to-one models
  • Sequence-to-sequence models
  • Anomaly scores

Advanced usage

  • Advanced usage and customization
  • Logging Configuration

API reference

  • The EnergyFaultDetector package
    • energy_fault_detector
      • Config
      • FaultDetector
      • anomaly_scores
      • autoencoders
      • config
      • core
      • data_preprocessing
      • data_splitting
        • data_splitting.data_gap_handler
        • data_splitting.data_splitter
        • data_splitting.sequence_dataset
      • evaluation
      • quick_fault_detection
      • root_cause_analysis
      • threshold_selectors
      • utils
      • registration
EnergyFaultDetector
  • energy_fault_detector
  • energy_fault_detector
  • data_splitting

data_splitting

Splitting and windowing of time-series data for training and validation.

  • data_splitting.data_gap_handler
    • DataGapHandler
      • DataGapHandler.freq
      • DataGapHandler.data_gaps
      • DataGapHandler.get_next_gap_after()
      • DataGapHandler.has_data_gaps()
      • DataGapHandler.is_in_gap()
    • shift_array()
  • data_splitting.data_splitter
    • BlockDataSplitter
      • BlockDataSplitter.train_selection
      • BlockDataSplitter.val_selection
      • BlockDataSplitter.split()
  • data_splitting.sequence_dataset
    • SequenceDatasetBuilder
      • SequenceDatasetBuilder.build_seq2one_dataset()
      • SequenceDatasetBuilder.build_sliding_dataset()
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