ANNMINERvA3

This is a Python3 TF framework.

• eager_hadmult_simple.py - Run classification in Eager mode. This is not meant for "production," but rather for debugging model code.
• estimator_hadmult_simple.py - Run classification using the Estimator API.
• mnvtf/
  • data_readers.py - collection of functions for ingesting data using the tf.data.Dataset API.
  • estimator_fns.py - collection of functions supporting the Estimators.
  • evtid_utils.py - utility functions for event ids (built from runs, subruns, gates, and physics event numbers).
  • hdf5_readers.py - collection of classes for reading HDF5 (used by data_readers.py).
  • model_classes.py - collection of (Keras) models used here (Eager code relies on Keras API).
  • recorder_text.py - classes for text-based predictions persistency.
• run_eager_hadmult_simple.sh - Runner script for eager_hadmult_simple.py meant for short, interactive tests.
• run_estimator_hadmult_simple.sh - Runner script for estimator_hadmult_simple.py meant for short, interactive tests.
• test_data_readers.py - Exercise the data reader classes.
• test_evtid_utils.py - Exercise eventid utility functions.
• test_models.py - Exercise model creation code.
• test_recorder_text.py - Exercise text-based predictions persistency.