v2.1.0

• New (additional) linear access data structure, explicitly storing coordinates in the sparse dimension, similar to Compressed Sparse Row.
• Block-based decomposition of the APR generation pipeline, allowing conversion of very large images.
• Expanded and improved functionality for image processing directly on the APR:
  • APR filtering (spatial convolutions and generic filters, e.g. rank filters).
  • APRNumerics module, including e.g. gradient computations and Richardson-Lucy deconvolution.
  • CUDA GPU-accelerated convolutions and RL deconvolution (currently only supports dense 3x3x3 and 5x5x5 stencils).
• Improved lazy access functionality (see e.g. Example_lazy_access and lazy reconstruction methods).
• Improved automatic parameter tuning

LibAPR (1.1)

First release of LibAPR:
*Basic Python wrappers.
*Pipeline clean-up and efficiencies.
*Additional testing.
*For creation of citable DOI