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.