Building SIRF and CIL with conda - SyneRBI/SIRF GitHub Wiki

These are instructions to build SIRF, CIL and all prerequisites using conda for dependencies. It is recommended to do this if you use conda for your normal python development. The instructions are for a Linux system although minor variations should work on other systems (see also below).

These instructions might currently fail due to a problem with the CCPi-Regularisation-Toolkit. Fixes coming soon.***

First, install miniconda.

Then follow these steps (see below for modifications if you encounter problems).

First create the Conda environment:

mkdir ~/devel
cd ~/devel
git clone https://github.com/SyneRBI/SIRF-SuperBuild
mkdir buildConda
cd buildConda

conda create --name cilsirfbuild python=3 cxx-compiler cmake=3.* ninja swig setuptools pip wheel \
  scipy python-wget cython six pillow nose h5py numpy matplotlib pytest pytest-cov \
  boost pugixml libitk-devel libitk nlohmann_json libparallelproj fftw docopt deprecation niftyreg \
  tqdm pywavelets numba zenodo_get -c conda-forge

Extra packages: (It is generally recommended to install all conda packages when you create the environment, to give conda the opportunity to find matching versions.)

  • If you have CUDA >= 12.0, add cuda-driver-dev cuda-cudart-dev cuda-nvcc to the above list.
  • When using clang (e.g. on MacOS), add llvm-openmp. On other systems, if OpenMP support is not found, you could try to add libgomp.
  • For some CIL functionality (including its tests), you will need to add olefile dxchange.
  • You might want to add other packages as well, such as pytorch or whatever.

Now proceed with building. The instructions here are for Linux (and MacOS?). See below for modifications for Windows.

conda activate cilsirfbuild

cmake -G Ninja -S ../SIRF-SuperBuild/ -B . -DCMAKE_INSTALL_PREFIX:PATH="$CONDA_PREFIX" -DCMAKE_PREFIX_PATH:PATH="$CONDA_PREFIX" -DUSE_SYSTEM_ACE=OFF -DUSE_SYSTEM_Boost=ON -DUSE_SYSTEM_ITK=ON -DUSE_SYSTEM_parallelproj=ON -DUSE_SYSTEM_FFTW3=ON -DUSE_SYSTEM_SWIG=ON -DUSE_SYSTEM_HDF5=ON -DUSE_SYSTEM_JSON=ON -DUSE_SYSTEM_NIFTYREG=ON -DUSE_ITK=ON -DBUILD_Gadgetron=OFF -DBUILD_CIL=ON -DCCPi-Regularisation-Toolkit_USE_CUDA=OFF

cmake --build . --config Release

Note: See https://github.com/SyneRBI/SIRF-SuperBuild/issues/948 for why we do -DCCPi-Regularisation-Toolkit_USE_CUDA=OFF at the moment.

Usual CMake build instructions apply. For instance, if you prefer to use a build tool such as make over Ninja, you will have to install it, and use that for the -G option of cmake above.

This will download, build, & install all CIL & SIRF dependencies in $CONDA_PREFIX, however without Gadgetron toolbox support (see below).

To run SIRF+CIL you need to create a shell script like the following and source it:

# activate conda environment
conda activate cilsirfbuild
# source the SIRF environment file
source "$CONDA_PREFIX"/bin/env_sirf.sh

Note that ideally we'd have a requirements.yml to specify all of the above. Work in progress...

Building Gadgetron

The above lines don't have all dependencies for Gadgetron. You have 2 options

Build Gadgetron via the SIRF-SuperBuild

This is likely hard, as the Gadgetron version we are using currently (8 Mar 2025) supports g++-11, while conda uses g++-13. You would need to use a very recent version of Gadgetron. The following lines could work (to be executed after the above):

conda install armadillo=12.8.4 dcmtk howardhinnant_date eigen libcurl mkl mkl-include range-v3 libblas=*=*mkl gtest gmock plplot go
export CGO_ENABLED=1 # make sure the C interface for "go" is enabled.
cmake -DBUILD_Gadgetron=ON -DGadgetron_TAG=avoid_test_compilation_error -DGadgetron_URL=https://github.com/SyneRBI/gadgetron.git -DISMRMRD_TAG=origin/master -DUSE_SYSTEM_Armadillo=ON -DUSE_SYSTEM_GTest=ON -DUSE_SYSTEM_range-v3=ON -DUSE_SYSTEM_Date=ON -DGadgetron_USE_MKL=ON -B .
cmake --build . --config Release

Install Gadgetron via conda.

You could try to use conda to install Gadgetron as well. Please check the Gadgetron conda instructions. Essentially, you'd have to add gadgetron and its channel to the original conda install line, and hope that versions can be resolved... We haven't tried this ourselves yet.

Building on non-Linux systems

Windows

WARNING: Do not use the Ninja generator nor the clang compiler with conda builds, as conda libraries are compiled with Visual Studio.

You will need some obvious changes from the above to accommodate for the shell syntax of course. Surprisingly, you also have to substitute $CONDA_PREFIX with $Env:CONDA_PREFIX/Library (when using Powershell).

It is highly recommended to use -DCMAKE_INSTALL_PREFIX:PATH=$Env:CONDA_PREFIX/Library -DPYTHON_DEST_DIR:PATH=$Env:CONDA_PREFIX/lib/site-packages to avoid problems with Python permissions, see https://github.com/SyneRBI/SIRF-SuperBuild/issues/729#issuecomment-1173548769

cmake -S ../SIRF-SuperBuild/ -B . -DCMAKE_INSTALL_PREFIX:PATH=$Env:CONDA_PREFIX/Library -DPYTHON_DEST_DIR:PATH=$Env:CONDA_PREFIX/lib/site-packages` -DCMAKE_PREFIX_PATH:PATH=$Env:CONDA_PREFIX <copy options from above>

At the time of writing, you will still need to do

Move-Item $Env:CONDA_PREFIX/Library/Library/bin/*.* $Env:CONDA_PREFIX/Library/bin

check https://github.com/TomographicImaging/CIL/issues/2141 for latest updates on this problem.

Problems and potential solutions:

On older Linux, e.g. Ubuntu 20.04, you might have some linking problems. You can try the following work-arounds:

  • add sysroot_linux-64 to the list of conda packages. This could resolve linking problems with the system GLIBC being older than what was used to build certain conda packages. An example error is undefined reference to memcpy@GLIBC_2.14 (arguably, this should have been solved by conda or the relevant packages, but adding the dependency yourself could work around this problem).
  • add the envs lib folder directly to the path of the run-time loader of shared libraries. This could resolve linking problems finding the correct openmp library for instance: 
    export LD_LIBRARY_PATH="$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH"
  • If you still have problems building the ISMRMRD examples, you could just switch them off: 
    cmake -DISMRMRD_EXTRA_CMAKE_ARGS:STRING="-DBUILD_EXAMPLES:BOOL=OFF" -B .
cmake --build . --config Release
  • If you have problems with a conda package that we can build ourselves, you can do that as opposed to the above, e.g. when experiencing problems with parallelproj: 
    # first remove the package that we installed
conda remove --force libparallelproj
# now reconfigure telling the SuperBuild to build it
cmake -DUSE_SYSTEM_parallelproj:BOOL=OFF -B .
cmake --build . --config Release