.. odftt documentation master file, created by sphinx-quickstart on Wed Jul 23 15:18:51 2025. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to odftomo's documentation! ================================= Introduction ************ Texture tomography is a way of reconstructing data from scanning synchrotron x-ray diffraction computed tomography (XRD-CT) experiments. The goal is to spatially map the microstructure of a polycrystalline sample by reconstructing an orientation distribution function in each voxel of a 3D sample. This python package was developed at the Paul Scherrer Institut for the publication `Texture tomography with high angular resolution utilizing sparsity `_ as a set of plugins for `mumott `_ but has since grown a bit in scope. The main workflow in texture tomography consists of three steps: .. toctree:: :maxdepth: 2 ./azimuthal_integration ./reconstruction ./analysis A few specialized workflows are documented in separate jupyter notebook: .. toctree:: :maxdepth: 1 ./notebooks/demonstration_single_grain_reconstructions.ipynb ./notebooks/demonstration_clustering_algorithms.ipynb The code is hosted on `gitlab `_. Installation ************ The package is not on pypi, so you have to download it from git. This can eg. look like: :: cd folder_where_I_want_the_python_code git clone https://gitlab.com/liebi-group/software/odf-mumott.git python -m pip install ./odf-mumott The dependencies are all the dependencies of `mumott`: mainly `numpy`, `scipy`, `matplotlib` and `numba`. The use of `numba` means you might have to downgrade `numpy`, for which reason you might want to use a fresh virtual environment. The notebooks have been tested with python 3.9 and 3.11. Furthermore, to run some of the jupyter-notebooks, you will need `jupyter` and `pyFAI`. Miscellaneous ************* .. toctree:: :maxdepth: 1 ./conventions