mlcg-tk
/

Contents:

  • Data pipeline user guide
    • About the Training Data Generation Pipeline
    • 0) Create a directory to output all the intermediate files
    • 1) Loading and processing all-atom simulation data
    • 2) Computing statistics and fitting priors
    • 3) Producing delta forces
    • 4) Package training data
    • 5) Generate simulation input
  • API documentation
    • Core API
      • input_generator package
        • prior_fit package
          • dihedral module
          • fit_potentials module
          • harmonic module
          • histogram module
          • polynomial module
          • repulsion module
          • restricted_bending module
          • utils module
        • embedding_maps module
        • prior_gen module
        • prior_nls module
        • raw_data_loader module
        • raw_dataset module
        • utils module
      • prior_tools package
        • utils module
    • Scripts
      • gen_input_data.py
      • fit_priors.py
      • merge_statistics.py
      • produce_delta_forces.py
      • package_training_data.py
      • add_decoys.py
      • gen_sim_input.py
  1. mlcg-tk /
  2. API documentation /
  3. Scripts

Scripts¶

All of the scripts and their methods can be accessed directly on the command line by appending the mlcg-tk- prefix and removing the .py. You can call the methods inside each script and pass all the arguments via a yaml file that is parsed using jsonargparse.

For example

::

mlcg-tk-gen_input_data process_raw_dataset –config ./trpcage.yaml

  • gen_input_data.py
  • fit_priors.py
  • merge_statistics.py
  • produce_delta_forces.py
  • package_training_data.py
  • add_decoys.py
  • gen_sim_input.py
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