v2.6.0

v2.6.0 (2020-01-13)

Diff since v2.5.2

Closed issues:

• Matrix-free iterative method examples? (#81)
• mul! with LinearCombination and matrices not working (#79)
• Allocation-free 5-arg mul! for custom maps (#75)
• InexactError when using LinearMap of complex matrix (#73)
• use LinearAlgebra's new generic in-place 5-arg mul! (requires Julia 1.3)? (#56)

Merged pull requests:

• Keep the FunctionMap promise (#82) (dkarrasch)
• select intermediate destination of CompositionMap based on input (#80) (kose-y)
• Minor updates in README.md (#78) (wsshin)
• stop testing Julia v1.2, start testing on windows (#77) (dkarrasch)
• add mulstyle feature (#76) (dkarrasch)
• BlockMap enhancements (#72) (dkarrasch)
• Use 5-arg mul! for matrices (#68) (dkarrasch)
• miscellaneous updates (#66) (dkarrasch)
• add Kronecker products for LinearMaps (#61) (dkarrasch)

v2.5.2

v2.5.2 (2019-09-19)

Diff since v2.5.1

Merged pull requests:

• Return correct size of BlockMap involving zero-size blocks (#70) (perrutquist)
• refactor tests (#67) (dkarrasch)

v2.5.1

v2.5.1 (2019-08-30)

Diff since v2.5.0

Closed issues:

• hvcat indexing issue with misaligned blocks (#58)
• Tag LinearMaps v2.5 (#55)
• Stashing user variable(s) in a LinearMap struct? (#53)

Merged pull requests:

• bump version in Project.toml (#62) (dkarrasch)
• minor code polish, use unicode (#60) (dkarrasch)
• Fix index in BlockMap adjoint/transpose multiply (#59) (JeffFessler)

v2.5.0

v2.5.0 (2019-08-09)

Diff since v2.4.0

Closed issues:

• Transition to new registration and package management (#46)
• hcat of LinearMaps (#45)

Merged pull requests:

• Optimize block map construction and multiplication (#52) (dkarrasch)
• Simplify multiplication code (#51) (dkarrasch)
• Add block maps (#50) (dkarrasch)
• UniformScalingMap improvements (#49) (dkarrasch)
• disallow test failures on Julia v1.2 (#48) (dkarrasch)

v2.4.0

v2.4.0 (2019-06-11)

Diff since v2.3.0

Closed issues:

• Potential reasons why Quaternion and Octonion tests fail (#42)
• Why no getindex() ? (#38)

Merged pull requests:

• update to new registration process (#47) (dkarrasch)
• Testings on Octonions and more testings on quaternions (#41) (yikait2)

Add support for noncommutative number types

v2.3.0

fix link in README

Fix CompositeMap-mul with shared data vectors

Thanks to work by @cako, this allows to work with composite (function) maps of differing sizes, where the functions share the vector data (e.g., by reshaping).

minor fixes, more tests

Minor fixes and cleaned up/more tests (#30)

* fix typo in identitymap

* generate undef Vectors

* tests: clean up and add new

full Julia 1.0 compatibility, sparse matrix convert with mutating matmul

Julia 1.0 tests, sparse convert, mutating matmul in sparse (#28)

* minor Julia 1.0 edits

* travis test also against Julia v1.0
* removed obsolete precompilation statement
* added sparse matrix convert
* sparse matrix construction uses mutating multiplication

* expanded README and tests

* consistent code style

v2.1.0

• A 5-argument version for mul!(y, A::LinearMap, x, α=1, β=0), which computes y := α * A * x + β * y and implements the usual 3-argument mul!(y, A, x) for the default α and β.
• Synonymous convert(Matrix, A::LinearMap) and convert(Array, A::LinearMap) functions, that call the Matrix constructor and return the matrix representation of A.
• Multiplication with matrices, interpreted as a block row vector of vectors:
  • mul!(Y::AbstractArray, A::LinearMap, X::AbstractArray, α=1, β=0): applies A to each column of X and stores the result in-place in the corresponding column of Y;
  • for the out-of-place multiplication, the approach is to compute convert(Matrix, A * X); this is equivalent to applying A to each column of X. In generic code which handles both A::AbstractMatrix and A::LinearMap, the additional call to convert is a noop when A is a matrix.
• Full compatibility with Arpack.jl's eigs and svds.