Tool for visualizing 3D diffraction and PDF Images.
Diffpy.fourigui is a tool to visualize and process 3D data sets written with the Python programming language. Diffpy.fourigui always displays one slice perpendicular to one axis and allows scrolling through the 3D data set along the given axis with a slider. It shows feedback values such as global and local maxima, minima or NAN ratios. The matplotlib panel e.g. for zooming and saving figures is featured. Diffpy.fourigui is designed for the processing of 3D atomic pair distribution functions (PDFs). One can load a 3D reciprocal space scattering volume which can be Fourier transformed to the 3D PDF. Thereby, one can apply cut off frequencies beyond and below given Q values, compare the results and switch between the scattering volume in reciprocal space and 3D PDF in real space.
For more information about the diffpy.fourigui library, please consult our online documentation.
If you use diffpy.fourigui in a scientific publication, we would like you to cite this package as
S. Y. Harouna-Mayer, S. Tao, Z. Gong, M. V. Zimmermann, D. Koziej, A.-C. Dippel, and S. J. L. Billinge, Real-Space Texture and Pole-Figure Analysis Using the 3D Pair Distribution Function on a Platinum Thin Film. IUCrJ 9 (5), 594–603 (2022).
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.fourigui_env
conda create -n diffpy.fourigui_env diffpy.fourigui conda activate diffpy.fourigui_env
To confirm that the installation was successful, type
python -c "import diffpy.fourigui; print(diffpy.fourigui.__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.fourigui_env environment, type
pip install diffpy.fourigui
If you prefer to install from sources, after installing the dependencies, obtain the source archive from
GitHub. Once installed, cd into your diffpy.fourigui 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.fourigui. Please join the diffpy.fourigui users community by joining the Google group. The diffpy.fourigui 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.fourigui 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.fourigui please visit the project web-page or email Prof. Simon Billinge at [email protected].