Skip to main content

A python package implementing the stretched NMF algorithm.

Project description

PyPi Forge PythonVersion PR

CI Codecov Black Tracking

A python package implementing the stretched NMF algorithm.

diffpy.snmf implements the stretched non negative matrix factorization (sNMF) and sparse stretched NMF (ssNMF) algorithms.

This algorithm is designed to do an NMF factorization on a set of signals ignoring any uniform stretching of the signal on the independent variable axis. For example, for powder diffraction data taken from samples containing multiple chemical phases where the measurements were done at different temperatures and the materials were undergoing thermal expansion.

For more information about the diffpy.snmf library, please consult our online documentation.

Citation

If you use this program for a scientific research that leads to publication, we ask that you acknowledge use of the program by citing the following paper in your publication:

Ran Gu, Yevgeny Rakita, Ling Lan, Zach Thatcher, Gabrielle E. Kamm, Daniel O’Nolan, Brennan Mcbride, Allison Wustrow, James R. Neilson, Karena W. Chapman, Qiang Du, and Simon J. L. Billinge, Stretched Non-negative Matrix Factorization, npj Comput Mater 10, 193 (2024).

Installation

The preferred method is to use Miniconda Python and install from the “conda-forge” channel of Conda packages.

To add “conda-forge” to the conda channels, run the following in a terminal.

conda config --add channels conda-forge

We want to install our packages in a suitable conda environment. The following creates and activates a new environment named diffpy.snmf_env

conda create -n diffpy.snmf_env diffpy.snmf
conda activate diffpy.snmf_env

If the above does not work, you can use pip to download and install the latest release from Python Package Index. To install using pip into your diffpy.snmf_env environment, type

pip install diffpy.snmf

If you prefer to install from sources, after installing the dependencies, obtain the source archive from GitHub. Once installed, cd into your diffpy.snmf directory and run the following

pip install .

To confirm that the installation was successful, type

python -c "import diffpy.snmf; print(diffpy.snmf.__version__)"

The output should print the latest version displayed on the badges above.

Now, you may consult our online documentation for tutorials and API references.

Support and Contribute

Diffpy user group is the discussion forum for general questions and discussions about the use of diffpy.snmf. Please join the diffpy.snmf users community by joining the Google group. The diffpy.snmf project welcomes your expertise and enthusiasm!

If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR. You can also post it to the Diffpy user group.

Feel free to fork the project and contribute. To install diffpy.snmf in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory

pip install -e .

To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.

  1. Install pre-commit in your working environment by running conda install pre-commit.

  2. Initialize pre-commit (one time only) pre-commit install.

Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.

Improvements and fixes are always appreciated.

Before contribuing, please read our Code of Conduct.

Contact

For more information on diffpy.snmf please visit the project web-page or email Prof. Simon Billinge at sb2896@columbia.edu.

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

diffpy_snmf-0.1.3.tar.gz (22.4 kB view details)

Uploaded Source

Built Distribution

diffpy.snmf-0.1.3-py3-none-any.whl (17.0 kB view details)

Uploaded Python 3

File details

Details for the file diffpy_snmf-0.1.3.tar.gz.

File metadata

  • Download URL: diffpy_snmf-0.1.3.tar.gz
  • Upload date:
  • Size: 22.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for diffpy_snmf-0.1.3.tar.gz
Algorithm Hash digest
SHA256 02cf89aba4da3786d550950f31db51cb3dacd8973c5c0da465516d39272f9f41
MD5 1ef2eb3f50e99dd06a8d7d038863d2d8
BLAKE2b-256 e0a8b2222f6a209ed462f3e300bf3a74f52c0678a685e91b20c708a9486d71c9

See more details on using hashes here.

File details

Details for the file diffpy.snmf-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: diffpy.snmf-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 17.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for diffpy.snmf-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 11841799f7395807eb68759c05bc286665d76b1e253f208a781f15d7897c8e12
MD5 ee513db5aff0b1956011eb36a7292916
BLAKE2b-256 d8967f029eddd8554565463cc7058cfea6651514f8386484c3f6fbd5580ea8f2

See more details on using hashes here.

Supported by

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