Releases: dkazanc/ToMoBAR
Releases · dkazanc/ToMoBAR
ToMoBAR v.2024.08
ToMoBAR 23.03
Removes the unnecessary C code from the source and enables pyproject.toml packaging
ToMoBAR v22.06
ToMoBAR v21.03
Merge pull request #61 from dkazanc/artefacts demos updates to new artefacts module tomophantom
ToMoBAR 20.08 release
[2020.06]
Added
Stripe-Weighted Least squares penalty to remove ring artifacts
Mask initialisation to apply circular masking to the reconstructed image/VOLUME
An option to provide variable CoRs values in order to fix the problem of misalignment for 2D and 3D case
Additional real data demo to reconstruct macrocrystallographic data
Various bug fixes
[2020.01]
Added
Kullback-Leibler term has been added according to C.Vogel p.174
Demos has been updated to use KL term
[2019.12]
Changed
Due to model-based structure of algorithms, the amount of parameters constantly increases. It has been decided to re-structure class function and make it simpler to operate. See demos for examples.
Added extensive HELP, one can use - help(RecToolsIR) or help(RecToolsDIR) to get information about parameters
Demos modified to adapt a new structure
ToMoBAR 19.11 version
Changes since 19.05
[2019.11]
Added
RING_WEIGHTS module in C which calculates a better ring model to use in non-quadratic data penalties
Cmake and Cython wrappers
run.sh to run Cmake based installation of Python wrappers
Changed
Installation process to use Cmake and Cython to wrap Python modules
Demos and conda-build files moved to the main directory
[2019.08]
Added
Autocropper to automatically crop the 3D projection data to reduce its size
Changed
normalisation script has been optimised
[2019.06]
Added
Vector geometry added to 3D case replacing the scalar aproach
Center of Rotation (CenterRotOffset variable) can be defined in the class as a scalar to avoid direct data manupulations (cropping, padding)
Changed
Demos for 2D/3D reconstruction updated with a new class
Removed
Section about "changelog" vs "CHANGELOG".
ToMoBAR
fista-tomo
Fista-tomo reconstruction package includes Matlab and Python versions. Python version doesn't have Group-Huber and Students t data fidelities yet.