Data

Tools

Indexes

Applications

Experiments

Open Source Science

cdiutils

A python package to help Coherent Diffraction Imaging (CDI) practitioners in their analysis.

https://github.com/clatlan/cdiutils

Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

A python package to help Coherent Diffraction Imaging (CDI) practitioners in their analysis.

Basic Info
  • Host: GitHub
  • Owner: clatlan
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 36.8 MB
Statistics
  • Stars: 14
  • Watchers: 6
  • Forks: 10
  • Open Issues: 31
  • Releases: 3
Created almost 5 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Citation

README.md

CDIutils

DOI PyPI version License

CDIutils is a Python package to help X-ray Bragg Coherent Diffraction Imaging (BCDI) practitioners in their analysis and visualisation workflows. I developed the package during my PhD.

The package is designed to handle the three primary stages of a BCDI data processing workflow:

  • Pre-processing (data centering and cropping)
  • Phase retrieval: utilises PyNX for accurate phasing (refer to PyNX documentation).
  • Post-processing (orthogonalisation, phase manipulation, strain computation etc.)

It is assumed that the phase retrieval is conducted using the PyNX package. The BcdiPipeline class runs all three stages and can manage connections to different machines, especially for GPU-based phase retrieval.

Some features of this package include:

  • Flexibility in Hardware: While the phase retrieval stage may leverage GPUs, pre- and post-processing can be executed without GPU support.
  • Utility Functions: The package provides utility functions to analyse processed data and generate plots suitable for potential publications.

For a visual wrap-up, see the associated poster presented at XTOP24: xtop_poster

Documentation

Read the full documentation on Read the Docs

The documentation includes: - Tutorials: Step-by-step guides for common workflows - API Reference: Complete function and class documentation - Examples: Jupyter notebook examples - Installation Guide: Detailed setup instructions

Installation

Using pip (from PyPI - simplest way)

Install directly from PyPI:

bash pip install cdiutils

Using conda (recommended for dependency management)

Option 1: Create a new conda environment with all dependencies

```bash

create conda environment directly from GitHub

conda env create -f https://raw.githubusercontent.com/clatlan/cdiutils/master/environment.yml

activate the environment

conda activate cdiutils-env

install cdiutils from PyPI

pip install cdiutils ```

Option 2: Install dependencies in your existing conda environment

```bash

download and install dependencies using conda solver

conda env update -f https://raw.githubusercontent.com/clatlan/cdiutils/master/environment.yml

install cdiutils from PyPI

pip install cdiutils ```

For development (includes documentation and testing tools):

```bash

create development environment directly from GitHub

conda env create -f https://raw.githubusercontent.com/clatlan/cdiutils/master/environment-dev.yml

activate the environment

conda activate cdiutils-dev-env

install cdiutils in development mode (requires cloning)

git clone https://github.com/clatlan/cdiutils.git cd cdiutils pip install -e . ```

Directly from GitHub (development version)

You can also install the latest development version directly from GitHub:

You can install the package directly from GitHub:

bash pip install git+https://github.com/clatlan/cdiutils.git

To update your environment with the latest commits:

bash pip install -I --no-deps git+https://github.com/clatlan/cdiutils.git

Note: Check out the dev branch for the latest features and bug fixes. The dev branch is not guaranteed to be stable.

Getting started

Once the package is installed, you can try it right away using the notebook template directly accessible with the command:

bash prepare_bcdi_notebooks

This will generate a notebook templates in your current directory.

Processing BCDI data

Once data are processed, the BcdiPipeline instance saves the data in .npz, .cxi and .vti files following the CXI file format convention (see https://www.cxidb.org/cxi.html). It also plots summary and debug figures such as:

  • Summary Slice Plot summary
  • Isosurface determination isosurface
  • Different strain computation methods strain

BCDI reconstruction analysis

If want to analyse and compare your reconstructions, check out the example notebook bcdireconstructionanalysis.ipynb in the examples folder. This notebook provides a comprehensive overview of the analysis process, including: * Slice plots of any quantity you like (here phase) across different conditions:

  • Reciprocal space plots in the orthogonal frame (lab frame)

  • Histogram plots of any quantity you like across different conditions:

Cross section quiver

The cross section quiver is nice tool for visualising the strain and displacement fields and their relationship in BCDI data.

  • The cross section quiver allows to plot cross section of strain and displacement field on the same plot. Cross Section Quiver
  • For different conditions Quivers

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

If you encounter any issues or have questions:

  1. Check the documentation for tutorials and API reference
  2. Open an issue on the GitHub repository
  3. Browse existing issues to see if your question has been answered

Owner

  • Name: Clément Atlan
  • Login: clatlan
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this package for scientific work, please consider including a citation as below."
type: software
authors:
  - family-names: Atlan
    given-names: Clement
    orcid: https://orcid.org/0000-0001-8531-7864

doi: 10.5281/zenodo.7656853
version: 0.2.0
date-released: 2025-02
title: "Cdiutils: A python package for Bragg Coherent Diffraction Imaging processing, analysis and visualisation workflows"

abstract: "A python package to help Bragg Coherent Diffraction Imaging (BCDI) practitioners in their analysis and visualisation workflows.

The package is designed to handle the three primary stages of a BCDI data processing workflow:

* **Proprocessing** (data centering and cropping)
* **Phase retrieval**: utilises  PyNX for phasing (refer to [PyNX documentation](http://ftp.esrf.fr/pub/scisoft/PyNX/doc/)).
* **Post processing** (orthogonalisation, phase manipulation, strain computation etc.)

It is assumed that the phase retrieval is conducted using the PyNX package. The `BcdiPipeline` class runs all three stages and can manage connections to different machines, especially for GPU-based phase retrieval."
repository-code: https://github.com/clatlan/cdiutils
url: https://github.com/clatlan/cdiutils
license: MIT

GitHub Events

Total
  • Fork event: 3
  • Create event: 7
  • Commit comment event: 1
  • Release event: 1
  • Issues event: 15
  • Watch event: 3
  • Delete event: 5
  • Member event: 1
  • Issue comment event: 19
  • Push event: 142
  • Pull request review comment event: 8
  • Pull request review event: 13
  • Pull request event: 23
Last Year
  • Fork event: 3
  • Create event: 7
  • Commit comment event: 1
  • Release event: 1
  • Issues event: 15
  • Watch event: 3
  • Delete event: 5
  • Member event: 1
  • Issue comment event: 19
  • Push event: 142
  • Pull request review comment event: 8
  • Pull request review event: 13
  • Pull request event: 23

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 14
  • Average time to close issues: 9 months
  • Average time to close pull requests: 23 days
  • Total issue authors: 4
  • Total pull request authors: 3
  • Average comments per issue: 1.14
  • Average comments per pull request: 0.0
  • Merged pull requests: 8
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 3
  • Pull requests: 13
  • Average time to close issues: N/A
  • Average time to close pull requests: about 17 hours
  • Issue authors: 2
  • Pull request authors: 3
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • clatlan (12)
  • Abd-zak (6)
  • ewbellec (4)
  • kyolson (3)
  • mirichard-S (2)
  • DSimonne (2)
  • sjleake (1)
  • Manalorca (1)
  • ccechatelier (1)
Pull Request Authors
  • clatlan (17)
  • DSimonne (12)
  • Manalorca (1)
  • Abd-zak (1)
Top Labels
Issue Labels
enhancement (10)
Pull Request Labels
enhancement (9) bug (2) help wanted (1)

Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
pypi.org: cdiutils

A Python package for (Bragg) Coherent X-ray Diffraction Imaging processing, analysis and visualisation workflows.

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 8.7%
Average: 29.0%
Dependent repos count: 49.2%
Maintainers (1)
Clatlan
Last synced: 6 months ago

Dependencies

requirements.txt pypi
  • PyYAML >=6.0
  • colorcet >=3.0.0
  • h5py >=3.6.0
  • hdf5plugin >=3.2.0
  • matplotlib >=3.5.2
  • numpy >=1.22.3
  • pandas >=1.4.2
  • paramiko >=2.12.0
  • ruamel.yaml >=0.17.21
  • ruamel.yaml.clib >=0.2.7
  • scikit-image >=0.19.2
  • scikit-learn >=1.1.3
  • scipy >=1.8.0
  • seaborn >=0.12.1
  • silx >=1.0.0
  • sklearn >=0.0.post1
  • vtk ==9.1.0
  • xrayutilities >=1.7.3
setup.py pypi
  • PyYAML >=6.0
  • bcdi *
  • colorcet >=3.0.0
  • h5py >=3.6.0
  • hdf5plugin >=3.2.0
  • matplotlib >=3.5.2
  • numpy >=1.22.3
  • pandas >=1.4.2
  • paramiko >=2.12.0
  • ruamel.yaml >=0.17.21
  • ruamel.yaml.clib >=0.2.7
  • scikit-image >=0.19.2
  • scikit-learn >=1.1.3
  • scipy >=1.8.0
  • seaborn >=0.12.1
  • silx >=1.0.0
  • sklearn >=0.0.post1
  • vtk ==9.1.0
  • xrayutilities >=1.7.3