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.
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).
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
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.
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 .
You may consult our online documentation for tutorials and API references.
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.
- Install pre-commit in your working environment by running
conda install pre-commit. - 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 contributing, please read our Code of Conduct.
For more information on diffpy.snmf please visit the project web-page or email Prof. Simon Billinge at [email protected].