Changelog of @hackage/hmatrix 0.16.0.4

0.16.0.0

* The modules Numeric.GSL.* have been moved to the new package hmatrix-gsl.

* The package "hmatrix" now depends only on BLAS and LAPACK and the
  license has been changed to BSD3.

* Added more organized reexport modules:
    Numeric.LinearAlgebra.HMatrix
    Numeric.LinearAlgebra.Data
    Numeric.LinearAlgebra.Devel

  The documentation is now hidden for Data.Packed.*, Numeric.Container, and
  the other Numeric.LinearAlgebra.* modules, but they continue to be exposed
  for backwards compatibility.

* Added support for empty arrays, extending automatic conformability
  (very useful for construction of block matrices).

* Added experimental support for sparse linear systems.

* Added experimental support for static dimension checking and inference
  using type-level literals.

* Added a different operator for the matrix-vector product.
  (available from the new reexport module).

* "join" deprecated (use "vjoin").

* "dot" now conjugates the first input vector.

* Added "udot" (unconjugated dot product).

* Added to/from ByteString

* Added "sortVector", "roundVector"

* Added Monoid instance for Matrix using matrix product.

* Added several pretty print functions

* Improved "build", "konst", "linspace", "LSDiv", loadMatrix', and other small changes.

* In hmatrix-glpk: (:=>:) change to (:>=:). Added L_1 linear system solvers.

* Improved error messages.

* Added many usage examples in the documentation.

0.15.2.0

* general pinvTol and improved pinv

0.15.1.0

* One-dimensional minimization

* Doubly-adaptive quadrature for difficult integrands

0.15.0.0

* Data.Packed.Foreign (additional FFI helpers)

* NFData instance of Matrix

* Unidimensional root finding

* In Numeric.LinearAlgebra.Util:
  pairwise2D, rowOuters, null1, null1sym, size, unitary, mt, (¦), (?), (¿)

* diagBlock

* meanCov moved to Container

0.14.1.0

* In Numeric.LinearAlgebra.Util:
  convolution: corr, conv, corr2, conv2, separable, corrMin
  kronecker: vec, vech, dup, vtrans

0.14.0.0

* integration over infinite intervals

* msadams and msbdf methods for ode

* Numeric.LinearAlgebra.Util

* (<\>) extended to multiple right-hand sides

* orth

0.13.0.0

* tests moved to new package hmatrix-tests

0.11.2.0

* geigSH' (symmetric generalized eigensystem)

* mapVectorWithIndex

0.11.1.0

* exported Mul

* mapMatrixWithIndex{,M,M_}

0.11.0.0

* flag -fvector default = True

* invlndet (inverse and log of determinant)

* step, cond

* find

* assoc, accum

0.10.0.0

* Module reorganization

* Support for Float and Complex Float elements (excluding LAPACK computations)

* Binary instances for Vector and Matrix

* optimiseMult

* mapVectorM, mapVectorWithIndexM, unzipVectorWith, and related functions.

* diagRect admits diagonal vectors of any length without producing an error,
  and takes an additional argument for the off-diagonal elements.

* different signatures in some functions

0.9.3.0

* flag -fvector to optionally use Data.Vector.Storable.Vector

without any conversion.

* Simpler module structure.

* toBlocks, toBlocksEvery

* cholSolve, mbCholSH

* GSL Nonlinear Least-Squares fitting using Levenberg-Marquardt.

* GSL special functions moved to separate package hmatrix-special.

* Added offset of Vector, allowing fast, noncopy subVector (slice).

Vector is now identical to Roman Leshchinskiy's Data.Vector.Storable.Vector, so we can convert from/to them in O(1).

* Removed Data.Packed.Convert, see examples/vector.hs

0.8.3.0

* odeSolve

* Matrix arithmetic automatically replicates matrix with single row/column

* latexFormat, dispcf

0.8.2.0

* fromRows/fromColumns now automatically expand vectors of dim 1
  to match the common dimension.
  fromBlocks also replicates single row/column matrices.
  Previously all dimensions had to be exactly the same.

* display utilities: dispf, disps, vecdisp

* scalar

* minimizeV, minimizeVD, using Vector instead of lists.

0.8.1.0

* runBenchmarks

0.8.0.0

* singularValues, fullSVD, thinSVD, compactSVD, leftSV, rightSV
  and complete interface to [d|z]gesdd.
  Algorithms based on the SVD of large matrices can now be
  significantly faster.

* eigenvalues, eigenvaluesSH

* linearSolveLS, rq

0.7.2.0

* ranksv

0.7.1.0

* buildVector/buildMatrix

* removed NFData instances

0.6.0.0

* added randomVector, gaussianSample, uniformSample, meanCov

* added rankSVD, nullspaceSVD

* rank, nullspacePrec, and economy svd defined in terms of ranksvd.

* economy svd now admits zero rank matrices and return a "degenerate
  rank 1" decomposition with zero singular value.

* added NFData instances for Matrix and Vector.

* liftVector, liftVector2 replaced by mapVector, zipVector.