bead package

Subpackages

• bead.src package
  • Subpackages
    • bead.src.models package
      • Submodules
      • bead.src.models.flows module
      • bead.src.models.layers module
      • bead.src.models.models module
      • Module contents
    • bead.src.trainers package
      • Submodules
      • bead.src.trainers.inference module
      • bead.src.trainers.training module
      • Module contents
    • bead.src.utils package
      • Submodules
      • bead.src.utils.conversion module
      • bead.src.utils.data_processing module
      • bead.src.utils.diagnostics module
      • bead.src.utils.ggl module
      • bead.src.utils.helper module
      • bead.src.utils.loss module
      • bead.src.utils.normalization module
      • bead.src.utils.plotting module
      • Module contents
  • Module contents

Submodules

bead.bead module

BEAD (Behavior and Anomaly Detection) main module.

This module serves as the entry point for the BEAD framework, providing command-line interface functionality for anomaly detection workflows. It orchestrates the complete pipeline from data preparation to model training, inference, and result visualization.

bead.bead.main()

Process command-line arguments to execute BEAD functionality.

Parses command-line arguments and executes the appropriate functionality based on the specified mode. The available modes are:

Parameters:

• line (Arguments are parsed from command)

• function. (not passed directly to this)

Modes:

new_project: Create a new project with default configuration. convert_csv: Convert CSV data to HDF5 or NPY format. prepare_inputs: Process data files into PyTorch tensors for training. train: Train a model using the prepared data. detect: Run inference on data to detect anomalies. plot: Generate visualization plots for results. diagnostics: Run performance profiling and diagnostics. chain: Execute the full pipeline from data conversion to visualization.

Raises:

NameError – If the specified mode is not recognized.

Module contents