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CHANGELOG.md

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Version 0.6

  • Support for Mathematica 12.0
  • Support for NumericArray
  • Incompatible change: ByteArrays are now mapped to NumericArrayRef instead of RawArrayRef
  • Added LTemplatePrivateNoCompile.m as an alternative to LTemplatePrivate.m. It is to be used when embedding LTemplate in another package and only loading support is needed (not compilation support). It does not load CCompilerDriver, which would be slow on Windows in some Mathematica versions.
  • Minor non-critical bug fixes and performance improvements
  • Documentation fixes

Version 0.5.4

  • Bug fix for SparseArrayRef::iterator
  • Fix getting integral vectors with mlstream
  • Documentation fixes

Version 0.5.3

  • Bug fix: in some cases, the row index was not correctly computed when using SparseArrayRef::iterator

Version 0.5.2

  • Bug fixes
  • Support for ByteArray type specification

Version 0.5.1

  • GenericImageRef split into GenericImageRef / GenericImage3DRef
  • Bug fixes
  • Expanded documentation and examples

Version 0.5

  • Expanded SparseArray support, added SparseMatrixRef.
  • Added experimental RawArray support.
  • Added experimental Image and Image3D support.
  • Uniform type specifications through LType, e.g. LType[List, Real] or LType[SparseArray, Integer, 2]. Added NormalizeTemplate which converts to this form. The usual LibraryLink compatible type specifications also work.
  • More functions for creating Tensors.
  • Class instances can now be retrieved by ID; access to the class-collection.
  • Greatly expanded documentation with many examples.
  • Several other small improvements.

Incompatible changes:

  • A compiler with C++11 support is now required. GCC 4.8 and MSVC 2015 both work.
  • CompileTempate automatically selects C++11 using a compiler flag. If you need a newer standard, such as C++14, you must now select this explicitly using a flag similar to -std=c++14, even if C++14 is the default for your compiler.
  • CubeRef is now indexed as (slices, rows, columns) for consistency with Image. In practice, this means that operator () has not changed, but slices(), rows() and cols() now return the tensor size along the 1st, 2nd and 3rd index, respectively.