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ML4PD - an open-source libray for building Aspen-like process models via machine learning.

Project description

ml4pd

Process design with Machine Learning.

How to Set Up for Development

via Conda

  1. Clone repository with git clone.
  2. Create new env. & install dependencies: mamba env create -f ml4pd/environment.yml -n [env-name]
  3. Add repo to path with conda develop ml4pd.
  4. Optional: register conda environment with jupyter notebook python -m ipykernel install --user --name=ml4pd

Additional GitHub repositories for docs, tests and training

  • ml4pd_utils: code base for generating & preparing data for training.
  • ml4pd_models: to store model files.
  • autoaspen: database for data obtained by aspen & python.

To debug docs

  • Use mkdocs serve within ml4pd directory, then go to localhost:8000.
  • generate_site.py gets docstrings (written in makrdown) from classes and put them in the right directory.
  • To make changes to notebooks, add ml4pd to path with sys.path.append() or conda develop.

Relationship with ml4pd_models

To minimize manual work, ml4pd dependends on a specific ml4pd_models github branch. When changes are made to either ml4pd or ml4pd_models that will break compatibility, create new branch in ml4pd_models, and link requirements.txt with the new branch.

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