Skip to main content

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

Project description

ml4pd

Process design with Machine Learning.

How to Install for Users

pip install ml4pd git+https://github.com/NREL/ml4pd_models.git@v1

How to Set Up for Development

git clone https://github.com/NREL/ml4pd.git
git clone https://github.com/NREL/ml4pd_models.git
mamba env create -f ml4pd/environment.yml
conda develop ml4pd
conda develop ml4pd_models

Additional GitHub repositories for docs, tests and training

  • ml4pd_utils: code base for generating & preparing data for training.
  • 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 apply change to workflow .yml files, this README and index.md in docs.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ml4pd-2022.11.9.tar.gz (24.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ml4pd-2022.11.9-py3-none-any.whl (29.9 kB view details)

Uploaded Python 3

File details

Details for the file ml4pd-2022.11.9.tar.gz.

File metadata

  • Download URL: ml4pd-2022.11.9.tar.gz
  • Upload date:
  • Size: 24.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for ml4pd-2022.11.9.tar.gz
Algorithm Hash digest
SHA256 828281de00417773e008dda53e77368a3377588472e64c9426ff0522551ccb14
MD5 e4a51d3ee5f8ad0719a7140bb63c7770
BLAKE2b-256 a4065ae9c4b6e3a17441ab789f496abbc91554ced8e96ab34cd54e55175b2637

See more details on using hashes here.

File details

Details for the file ml4pd-2022.11.9-py3-none-any.whl.

File metadata

  • Download URL: ml4pd-2022.11.9-py3-none-any.whl
  • Upload date:
  • Size: 29.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for ml4pd-2022.11.9-py3-none-any.whl
Algorithm Hash digest
SHA256 f240d0ab6cf6a3977d3cfd59273970909daf528e5a6d660410ec1e07e5fc5c84
MD5 28424d84250b7bf4441fee874b761b52
BLAKE2b-256 90130002966efd3d11003ea6395decb0fa50cc7518f324d28196c0293066a150

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page