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Package for analysis of scanning far field x-ray diffraction data with support for intragranular strain reconstruction and ImageD11 peak files. For documentation see link below.

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Welcome to the s3dxrd package

This is a scientific code originally developed to adress scanning-3d-xray-diffraction (s3dxrd) strain measurements of polycrystalline materials.

Intragranular strain is computed based on a series of line integral measurements. The s3dxrd package supports regression either by a simple weighted least squares approach or alternatively by a Gaussian Proccess. The later statistical model uses spatial correlation assumptions and an equlibrium prior to find good fits to data.

If you want to use this code, it is strongly recomended that you have a look at the underlying publication: describing the weighted least squares approach (named "ASR" in the paper)

Reconstructing intragranular strain fields in polycrystalline materials from scanning 3DXRD data, Henningsson, N. A., Hall, S. A., Wright, J. P. & Hektor, J. (2020). J. Appl. Cryst. 53, 314-325.

The paper describing the Gaussian Process regression procedure is also available here:

Intragranular Strain Estimation in Far-Field Scanning X-ray Diffraction using a Gaussian Processes, Henningsson, A. & Hendriks, J. (2021). J. Appl. Cryst. 54.

This paper may also help the user to understand some of the mathematical notation hinted at in the code.

Installation

Installation via pip is available as

pip3 install s3dxrd

For manuall installation, first get the code to your local machine by:

git clone https://github.com/AxelHenningsson/scanning-xray-diffraction.git

Next go to the repository and try to install

cd scanning-xray-diffraction
python setup.py build install

You will now recieve messages about dependecies that need be installed first. Go through these untill the build succeeds.

Documentation

Documentation is hosted seperately at github pages:

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Package for analysis of scanning far field x-ray diffraction data with support for intragranular strain reconstruction and ImageD11 peak files. For documentation see link below.

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