Skip to main content

Tools for processing x-ray powder diffraction data from laboratory sources.

Project description

PyPi Forge PythonVersion PR

CI Codecov Black Tracking

Tools for processing x-ray powder diffraction data from laboratory sources.

PDFgetX3 has revolutionized how PDF methods can be applied to solve nanostructure problems. However, the program was designed for use with Rapid Acquisition PDF (RAPDF) data from synchrotron sources. A key approximation inherent in the use of PDFgetX3 for RAPDF data is that absorption effects are negligible. This is typically not the case for laboratory x-ray diffractometers, where absorption effects can be significant.

This app is designed to preprocess data from laboratory x-ray diffractometers before using PDFgetX3 to obtain PDFs. The app currently carries out an absorption correction assuming a parallel beam capillary geometry which is the most common geometry for lab PDF measurements.

The theory is described in the following paper:

An ad hoc Absorption Correction for Reliable Pair-Distribution Functions from Low Energy x-ray Sources, Yucong Chen, Till Schertenleib, Andrew Yang, Pascal Schouwink, Wendy L. Queen and Simon J. L. Billinge, in preparation.

The related experimental data acquisition protocols are described in the following paper:

Protocols for Obtaining Reliable PDFs from Laboratory x-ray Sources Using PDFgetX3, Till Schertenleib, Daniel Schmuckler, Yucong Chen, Geng Bang Jin, Wendy L. Queen and Simon J. L. Billinge, in preparation.

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

Citation

If you use diffpy.labpdfproc in a scientific publication, we would like you to cite this package as

diffpy.labpdfproc Package, https://github.com/diffpy/diffpy.labpdfproc

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.labpdfproc_env

conda create -n diffpy.labpdfproc_env diffpy.labpdfproc
conda activate diffpy.labpdfproc_env

To confirm that the installation was successful, type

python -c "import diffpy.labpdfproc; print(diffpy.labpdfproc.__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.labpdfproc_env environment, type

pip install diffpy.labpdfproc

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

pip install .

Example

Navigate to the directory that contains 1D diffraction patterns that you would like to process. Activate the conda environment (conda activate diffpy.labpdfproc_env) that contains the package and run the following command

labpdfproc <muD> <path/to/inputfile.txt>

Here replace <muD> with the value of muD for your sample and <path/to/inputfile.txt> with the path and filename of your input file. For example, if the uncorrected data case is called zro2_mo.xy and is in the current directory and it has a muD of 2.5 then the command would be

labpdfproc 2.5 zro2_mo.xy

Please type

labpdfproc --help

for more information on the available options.

Getting Started

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.labpdfproc. Please join the diffpy.labpdfproc users community by joining the Google group. The diffpy.labpdfproc 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.labpdfproc 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 contributing, please read our Code of Conduct.

Contact

For more information on diffpy.labpdfproc 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_labpdfproc-0.1.3.tar.gz (47.2 kB view details)

Uploaded Source

Built Distribution

diffpy.labpdfproc-0.1.3-py3-none-any.whl (35.6 kB view details)

Uploaded Python 3

File details

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

File metadata

  • Download URL: diffpy_labpdfproc-0.1.3.tar.gz
  • Upload date:
  • Size: 47.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for diffpy_labpdfproc-0.1.3.tar.gz
Algorithm Hash digest
SHA256 be987107c75262f2da195b13db2f0ae42e488721a44a1d6d93034e680d0737d9
MD5 91d889be7b261da03628796dd2d23000
BLAKE2b-256 a093f732e1ff1cd5987cd468fdfefe50445b89a0580f1e748b8b1666a7d0b981

See more details on using hashes here.

File details

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

File metadata

File hashes

Hashes for diffpy.labpdfproc-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 80e21b15b2d3db55270846fde610ac553c68408134a62aa0d2c9d3750a15ae5b
MD5 3c367fa32adfc9dc8830d6529e44c7fb
BLAKE2b-256 a3a7a2ef168e3f98732ea5a21dd6ed042a458546e8cbf15b4bb7f01f4d232d09

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