A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation

A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation - Published in JOSS (2024)

https://github.com/frederiklizakjohansen/debyecalculator

Science Score: 100.0%

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    Found CITATION.cff file
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    Found 10 DOI reference(s) in README and JOSS metadata
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    5 of 5 committers (100.0%) from academic institutions
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    Published in Journal of Open Source Software

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Chemistry Physical Sciences - 83% confidence
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Repository

A vectorised implementation of the Debye Scattering Equation on CPU and GPU

Basic Info
  • Host: GitHub
  • Owner: FrederikLizakJohansen
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 69.2 MB
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  • Stars: 33
  • Watchers: 2
  • Forks: 7
  • Open Issues: 4
  • Releases: 8
Created over 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

pypi Python License ChemRxiv ReadTheDocs DOI PyPI - Downloads

DebyeCalculator

Welcome to DebyeCalculator! This is a simple tool for calculating the scattering intensity $I(Q)$ through the Debye scattering equation, the Total Scattering Structure Function $S(Q)$, the Reduced Total Scattering Function $F(Q)$, and the Reduced Atomic Pair Distribution Function $G(r)$ from an atomic structure. The Debye scattering equation can be used to compute the scattering pattern of any atomic structure and is commonly used to study both crystalline and non-crystalline materials with a range of scattering techniques like powder diffraction, total scattering with pair distribution function and small-angle scattering. Although the Debye scattering equation is extremely versatile, the computation of the double sum, which scales O(N2), has limited the practical use of the equation. Here, we provide an optimised code for the calculation of the Debye scattering equation on Graphics processing units (GPUs) which accelerate the calculations with orders of magnitudes.

  1. Installation
    1. Prerequisites
    2. Install with pip
    3. Install locally
    4. GPU support
  2. Usage
    1. Interactive mode
    2. Example usage
  3. Demo
  4. Additional implementation details
  5. Authors
  6. Cite
  7. Contributing to the software
    1. Reporting issues
    2. Seeking support

Installation

Prerequisites

DebyeCalculator requires Python version >=3.7, <3.12. If needed, create an environment with any of these Python versions: bash conda create -n debyecalculator_env python=3.9 bash conda activate debyecalculator_env

Before installing the DebyeCalculator package, ensure that you have PyTorch installed. Follow the instructions on the official PyTorch website to install the appropriate version for your system: PyTorch Installation Guide.

NOTE: Installing an earlier version of PyTorch (<=1.13.1) will be necessary if you're running Python 3.7, since the latest PyTorch version requires Python 3.8 or higher.

Install with pip

Run the following command to install the DebyeCalculator package. (Requires: Python >=3.7, <3.12) pip install debyecalculator

Install locally

Clone the repo git clone https://github.com/FrederikLizakJohansen/DebyeCalculator.git

Run the following command to install the DebyeCalculator package. (Requires: Python >=3.7, <3.12) python -m pip install .

Testing the local installation

To ensure that the installation is set up correctly and your environment is ready to go, we recommend running the included unit tests.
First, make sure you have pytest installed. If not, you can install it using: bash pip install pytest After installing the package, open a terminal or command prompt and navigate to the root directory of the package. Then run the following command to execute the tests: bash pytest

GPU Support

The DebyeCalculator package supports GPU acceleration using PyTorch with CUDA. Follow these steps to enable GPU support:

1. Verify GPU Availability

After installing PyTorch with CUDA, you can check if your GPU is available by running the following code snippet in a Python environment:

python import torch print("CUDA available:", torch.cuda.is_available())

2. Specify GPU Device in DebyeCalculator

When creating an instance of DebyeCalculator, you can specify the device as 'cuda' to utilize GPU acceleration:

```python from debyecalculator import DebyeCalculator

calc = DebyeCalculator(device='cuda') ```

Usage

Interactive mode

IMPORTANT: CHANGES TO INTERACTIVE MODE AS OF JANUARY 2024 (DebyeCalculator version >=1.0.5) In the lastest version of DebyeCalculator, we are unfortunately experiences some issues with Google Colab that does not allow the package to display the interact() widget. If you experience any related issues, please refer to this statement for further clarification and workarounds.

Example Usage

This section provides quick examples on how to use the DebyeCalculator class for generating both total and partial scattering intensities from particle structures defined in .xyz files, .cif files, or directly from structure tuples.

Generating Scattering

To calculate the scattering intensity $I(Q)$ for a particle, you can use different structure sources:

```python from debyecalculator import DebyeCalculator import torch

Initialize the DebyeCalculator object

calc = DebyeCalculator(qmin=1.0, qmax=8.0, qstep=0.01)

Define structure sources

xyzfile = "somepath/somefile.xyz" ciffile = "somepath/somefile.cif" structure_tuple = ( ["Fe", "Fe", "O", "O"], torch.tensor( [[0.5377, 0.7068, 0.8589], [0.1576, 0.1456, 0.8799], [0.5932, 0.0204, 0.6759], [0.6946, 0.4114, 0.4869]] ) )

Calculate I(Q) from different sources

q, iqxyz = calc.iq(xyzfile) q, iqcif = calc.iq(ciffile) q, iqtuple = calc.iq(structuretuple) ```

Generating Partial Scattering

DebyeCalculator also allows users to extract the partial scattering for specific pairs of atomic species within a structure: ```python

Create an instance of DebyeCalculator with appropriate parameters

calc = DebyeCalculator(qmin=1.0, qmax=20.0)

Load a single particle from a .xyz file and calculate partial I(Q) for specific atom pairs

Replace 'X' and 'Y' with the atomic symbols present in your structure

q, iqXX = calc.iq("path/to/nanoparticle.xyz", partial="X-X") q, iqYY = calc.iq("path/to/nanoparticle.xyz", partial="Y-Y") q, iq_XY = calc.iq("path/to/nanoparticle.xyz", partial="X-Y") ``` Note: When combining signals from partial scattering, be cautious to avoid double-counting interactions between atoms.

Demo

For a more detailed demonstration on how DebyeCalulator works, including additional examples, please refer to the Demo.ipynb notebook available in the repository, or visit Colab-Demo

Additional implementation details

See the docs folder.

Authors

Frederik L. Johansen1, 2
Andy S. Anker1

1 Department of Chemistry & Nano-Science Center, University of Copenhagen, Denmark

2 Department of Computer Science, University of Copenhagen, Denmark

Should there be any questions, desired improvements or bugs please contact us on GitHub or through email: frjo@di.ku.dk and ansoan@dtu.dk.

Cite

If you use our code or our results, please consider citing our paper. Thanks in advance!

@article{Johansen_anker2024debye, title={A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation}, author={Frederik L. Johansen, Andy S. Anker, Ulrik Friis-Jensen, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan}, journal={Journal of Open Source Software}, year={2024}, issn={2475-9066}, issue={94}, url={"https://joss.theoj.org/papers/10.21105/joss.06024"}, doi={10.5281/zenodo.10659528}

Contributing to the software

We welcome contributions to our software! To contribute, please follow these steps:

  1. Fork the repository.
  2. Make your changes in a new branch.
  3. Submit a pull request.

We'll review your changes and merge them if they meet our quality standards, including passing all unit tests. To ensure that your changes pass the unit tests, please run the tests locally before submitting your pull request. You can also view the test results on our GitHub repository using GitHub Actions.

Reporting issues

If you encounter any issues or problems with our software, please report them by opening an issue on our GitHub repository. Please include as much detail as possible, including steps to reproduce the issue and any error messages you received.

Seeking support

If you need help using our software, please reach out to us on our GitHub repository. We'll do our best to assist you and answer any questions you have.

References

[1] Waasmaier, D., & Kirfel, A. (1995). New analytical scattering-factor functions for free atoms and ions. Acta Crystallographica Section A, 51(3), 416–431. https://doi.org/10.1107/S0108767394013292

Owner

  • Name: Frederik Lizak Johansen
  • Login: FrederikLizakJohansen
  • Kind: user
  • Location: Denmark
  • Company: @NanostructureUCPH

JOSS Publication

A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation
Published
February 20, 2024
Volume 9, Issue 94, Page 6024
Authors
Frederik L. Johansen ORCID
Department of Chemistry & Nano-Science Center, University of Copenhagen, Denmark, Department of Computer Science, University of Copenhagen, Denmark
Andy S. Anker ORCID
Department of Energy Conversation and Storage, Technical University of Denmark, Denmark, Department of Chemistry, University of Oxford, United Kingdom
Ulrik Friis-Jensen ORCID
Department of Chemistry & Nano-Science Center, University of Copenhagen, Denmark, Department of Computer Science, University of Copenhagen, Denmark
Erik B. Dam ORCID
Department of Computer Science, University of Copenhagen, Denmark
Kirsten M. ø. Jensen ORCID
Department of Chemistry & Nano-Science Center, University of Copenhagen, Denmark
Raghavendra Selvan ORCID
Department of Computer Science, University of Copenhagen, Denmark
Editor
Sophie Beck ORCID
Tags
Scattering Debye Scattering Equation GPU-accelerated Nanoparticles Pair Distribution Function Analysis

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Johansen
  given-names: Frederik L.
  orcid: "https://orcid.org/0000-0002-8049-8624"
- family-names: Anker
  given-names: Andy S.
  orcid: "https://orcid.org/0000-0002-7403-6642"
- family-names: Friis-Jensen
  given-names: Ulrik
  orcid: "https://orcid.org/0000-0001-6154-1167"
- family-names: Dam
  given-names: Erik B.
  orcid: "https://orcid.org/0000-0002-8888-2524"
- family-names: Jensen
  given-names: Kirsten M. Ø.
  orcid: "https://orcid.org/0000-0003-0291-217X"
- family-names: Selvan
  given-names: Raghavendra
  orcid: "https://orcid.org/0000-0003-4302-0207"
contact:
- family-names: Johansen
  given-names: Frederik L.
  orcid: "https://orcid.org/0000-0002-8049-8624"
- family-names: Anker
  given-names: Andy S.
  orcid: "https://orcid.org/0000-0002-7403-6642"
- family-names: Jensen
  given-names: Kirsten M. Ø.
  orcid: "https://orcid.org/0000-0003-0291-217X"
- family-names: Selvan
  given-names: Raghavendra
  orcid: "https://orcid.org/0000-0003-4302-0207"
doi: 10.5281/zenodo.10659528
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Johansen
    given-names: Frederik L.
    orcid: "https://orcid.org/0000-0002-8049-8624"
  - family-names: Anker
    given-names: Andy S.
    orcid: "https://orcid.org/0000-0002-7403-6642"
  - family-names: Friis-Jensen
    given-names: Ulrik
    orcid: "https://orcid.org/0000-0001-6154-1167"
  - family-names: Dam
    given-names: Erik B.
    orcid: "https://orcid.org/0000-0002-8888-2524"
  - family-names: Jensen
    given-names: Kirsten M. Ø.
    orcid: "https://orcid.org/0000-0003-0291-217X"
  - family-names: Selvan
    given-names: Raghavendra
    orcid: "https://orcid.org/0000-0003-4302-0207"
  date-published: 2024-02-20
  doi: 10.21105/joss.06024
  issn: 2475-9066
  issue: 94
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6024
  title: A GPU-Accelerated Open-Source Python Package for Calculating
    Powder Diffraction, Small-Angle-, and Total Scattering with the
    Debye Scattering Equation
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06024"
  volume: 9
title: A GPU-Accelerated Open-Source Python Package for Calculating
  Powder Diffraction, Small-Angle-, and Total Scattering with the Debye
  Scattering Equation

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pypi.org: debyecalculator

A vectorised implementation of the Debye Equation on CPU and GPU

  • Versions: 15
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 126 Last month
Rankings
Dependent packages count: 7.3%
Forks count: 30.0%
Stargazers count: 32.0%
Average: 34.5%
Dependent repos count: 68.6%
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Last synced: 4 months ago

Dependencies

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setup.py pypi
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