Changelog for hmatrix-0.12.0.1
0.11.2.0
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- geigSH' (symmetric generalized eigensystem)
- mapVectorWithIndex
0.11.1.0
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- exported Mul
- mapMatrixWithIndex{,M,M_}
0.11.0.0
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- flag -fvector default = True
- invlndet (inverse and log of determinant)
- step, cond
- find
- assoc, accum
0.10.0.0
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- 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
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- 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
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- odeSolve
- Matrix arithmetic automatically replicates matrix with single row/column
- latexFormat, dispcf
0.8.2.0
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- 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
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- runBenchmarks
0.8.0.0
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- 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
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- ranksv
0.7.1.0
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- buildVector/buildMatrix
- removed NFData instances
0.6.0.0
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- 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.