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File Summary

Shane edited this page Aug 8, 2020 · 5 revisions

Utilities

  • config.py: Configuration file containing project directives for file and folder names, constants for the geometry and chemistry of the problem, plot customizations, and so forth.
  • utils.py: Utilities for logging and timing operations, loading and saving data, saving figures, and calculating ROM reconstruction errors.
  • chemistry_conversions.py: Chemistry-related data conversions.
  • data_processing.py: Tools for (un)lifting and (un)scaling data.

Main Routines

  • step1_unpack.py: Read raw .tar archives and compile snapshot data into a single HDF5 data set.
  • step2_preprocess.py: Lift, scale, and project GEMS training data. The process can also be decoupled into the following routines.
  • step3_train.py: Learn ROMs from projected data via regularized Operator Inference.

Other Files

  • log.log: Logging files (created as needed). For experiments with a specified number of training snapshots k, a separate log file is created (e.g., k = 10,000 activity is logged to config.BASE_FOLDER/k10000/log.log.
  • requirements.txt: Python package requirements for this repository. Use python3 -m pip install --user -r requirements.txt to install the prerequisites.

Problem Statement: computational domain, state variables, and description of the data.

Installation and Setup: how to download the source code and the data files.

File Summary: short descriptions of each file in the repository.

Documentation: how to use the repository for reduced-order model learning.

Results: plots and figures, including many additional results that are not in the publications.

References: short list of primary references.

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