CCP SyneRBI SIRF

New features PET Addition of sirf.STIR.ScatterEstimation and ScatterSimulation to allow (non-TOF) scatter estimation in PET GE Signa PET/MR reading of listmode data, sinograms, normalisation and randoms support added. If STIR is at least version 5 or built from the master branch, Georg Schramm's parallel (computing) projector is now made available from SIRF (use AcquisitionModelUsingParallelproj). This uses Joseph interpolation, but importantly can use your GPU (if CUDA was found during building). Implemented extraction of the operator representing the linear part of PET acquisition model and computation of its norm. When adding a shape to a sirf.STIR.ImageData, optionally give the number of times to sample a voxel. This is useful when the shape partially - but not completely - fills a voxel. If storage_scheme is set to memory, PETAcquisitionData allows direct modification, whereas before a copy would need to be created first. (Internally, it uses STIR ProjDataInMemory, instead of ProjDataFromStream). Registration Registration of 2d images is now supported with aladin and f3d. examples data: Installs examples, data and doc to the install directory, i.e. ${CMAKE_INSTALL_PREFIX}/share/SIRF-. directory. If the SIRF_DATA_PATH environment variable is set, examples_data_path will search for the examples data there, or in SIRF_INSTALL_PATH/share/SIRF-./data directory. In MATLAB, the example_data_path function has the version set by CMake at install time. Other Python features: Define __version__ in sirf python package. Added implementation of division and multiplication for NiftiImageData. Data validity checks return NotImplemented instead of throwing error, opening the door for future implementations of operations on data. Backwards incompatible changes STIR version 4.1.0 is now required. Python 2 is no longer supported. Most code might still work, but we do not check. A warning is written when the Python version found is 2. This will be changed to FATAL_ERROR at a later stage. Handling of coil images and sensitivities in C++ code simplified by inheriting CoilImagesVector from GadgetronImagesVector and replacing CoilSensitivitiesAsImages with CoilSensitivitiesVector, also inheriting from GadgetronImagesVector. All methods of CoilImagesVector and CoilSensitivitiesVector other than those inherited from GadgetronImagesVector are no longer supported except methods named compute(), which are renamed to calculate(). Deprecations (will be errors in SIRF 4.0) Registration: renamed Resample to Resampler and NiftyResample to NiftyResampler. Old names are now deprecated but should still work. STIR AcquisitionModel forward, direct, backward and adjoint signatures have changed in Python. Subset information should now be set via num_subsets and subset_num members. Theforwardandbackwardmembers can still be called with the previous syntax but this will be removed in a later version. Note that default values ofnum_subsetsandsubset_num` are 0 and 1 respectively, such that default behaviour is default behaviour (i.e. process all data) is unchanged. MR acquisition data storage scheme restricted to memory only (a message will be printed but no error thrown) Use CMake variable names from find_package(Python) which are available with CMake 3.12+. SIRF CMake files will accept both Python_EXECUTABLE or PYTHON_EXECUTABLE, for the latter it will send a deprecation warning. Other changes When registering, internally the forward displacement is no longer stored, replaced by the forward deformation. The inverse is no longer stored, and is calculated as needed. PETAcquisitionData.axpby now uses STIR's axpby and is therefore faster. Speed-up in stir::AcquisitionDataInMemory of as_array, fill, dot, norm, etc. (by using STIR iterators). Added common Python DataContainer algebra unit tests for all DataContainer inherited classes. Continuous Integration now uses Github Actions. Travis-CI has been dropped. New CMake option BUILD_DOCUMENTATION to use doxygen to build C++ documentation. It will be installed in the share/SIRF-version/doc/doxygen. Bug fixes Python fill method in MR DataContainer accepts numpy array, number or DataContainer. get_index_to_physical_point_matrix() returned a wrong matrix in MATLAB and Python. path manipulation of examples_data_path now should work for any platform, not just linux