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| author | Tomas Kulhanek <tomas.kulhanek@stfc.ac.uk> | 2019-01-21 17:16:52 +0000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-01-21 17:16:52 +0000 |
| commit | 39dc8ebc5e4bbb3b4138156d21d2e970ece2fbc5 (patch) | |
| tree | 8b59253d9e35ee5eab0b165ca7cc0126be8b6b43 | |
| parent | b9ee6fad5b3119e738f6999eb4dd78bafb98a7cd (diff) | |
| parent | 60b4d51ce1cf19be2a3483232448ae227253614c (diff) | |
| download | regularization-39dc8ebc5e4bbb3b4138156d21d2e970ece2fbc5.tar.gz regularization-39dc8ebc5e4bbb3b4138156d21d2e970ece2fbc5.tar.bz2 regularization-39dc8ebc5e4bbb3b4138156d21d2e970ece2fbc5.tar.xz regularization-39dc8ebc5e4bbb3b4138156d21d2e970ece2fbc5.zip | |
Merge pull request #1 from TomasKulhanek/pr-test
Pr test
| -rw-r--r-- | Readme.md | 1 | ||||
| -rwxr-xr-x | build/jenkins-build.sh | 9 |
2 files changed, 4 insertions, 6 deletions
@@ -1,3 +1,4 @@ +[](https://anvil.softeng-support.ac.uk/jenkins/job/CILsingle/job/CCPi-Regularisation-Toolkit/) # CCPi-Regularisation Toolkit (CCPi-RGL) **Iterative image reconstruction (IIR) methods normally require regularisation to stabilise the convergence and make the reconstruction problem (inverse problem) more well-posed. The CCPi-RGL software provides 2D/3D and multi-channel regularisation strategies to ensure better performance of IIR methods. The regularisation modules are well-suited to use with [splitting algorithms](https://en.wikipedia.org/wiki/Augmented_Lagrangian_method#Alternating_direction_method_of_multipliers), such as, [ADMM](https://github.com/dkazanc/ADMM-tomo) and [FISTA](https://github.com/dkazanc/FISTA-tomo). Furthermore, the toolkit can be used for simpler inversion tasks, such as, image denoising, inpaiting, deconvolution etc. The core modules are written in C-OMP and CUDA languages and wrappers for Matlab and Python are provided.** diff --git a/build/jenkins-build.sh b/build/jenkins-build.sh index 8c10484..4225db3 100755 --- a/build/jenkins-build.sh +++ b/build/jenkins-build.sh @@ -1,11 +1,10 @@ #!/usr/bin/env bash -# TODO put git tag recognition + if [[ -n ${CIL_VERSION} ]] then echo Using defined version: $CIL_VERSION else -# TODO put git tag recognition, or default - #export CIL_VERSION=0.10.4 + #get tag, remove first char ('v') and leave rest export CIL_VERSION=`git describe --tags | tail -c +2` if [[ ${CIL_VERSION} == *"-"* ]]; then @@ -33,11 +32,9 @@ else ./Miniconda3-latest-Linux-x86_64.sh -u -b -p . PATH=$PATH:./bin fi - # presume that git clone is done before this script is launched, if not, uncomment #git clone https://github.com/vais-ral/CCPi-Regularisation-Toolkit conda install -y conda-build -#export CIL_VERSION=0.10.2 #cd CCPi-Regularisation-Toolkit # already there by jenkins # need to call first build conda build Wrappers/Python/conda-recipe @@ -52,7 +49,7 @@ if [[ -n ${CCPI_CONDA_TOKEN} ]] then conda install anaconda-client while read -r outfile; do - #TODO if git tag is defined than call anaconda without --label dev + #if 0 commit after tag then call anaconda without --label dev #TODO if pull request??? do not upload if [[ $CIL_VERSION == *"_"* ]]; then # upload with dev label |