Changelog for hmatrix-0.16.1.3
0.16.1.0
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* Added (|||) and (===) for "besides" and "above"
* rowOuters
0.16.0.0
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* 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
For normal usage we only need to import Numeric.LinearAlgebra.HMatrix.
(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
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* general pinvTol and improved pinv
0.15.1.0
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* One-dimensional minimization
* Doubly-adaptive quadrature for difficult integrands
0.15.0.0
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* 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
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* In Numeric.LinearAlgebra.Util:
convolution: corr, conv, corr2, conv2, separable, corrMin
kronecker: vec, vech, dup, vtrans
0.14.0.0
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* integration over infinite intervals
* msadams and msbdf methods for ode
* Numeric.LinearAlgebra.Util
* (<\>) extended to multiple right-hand sides
* orth
0.13.0.0
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* tests moved to new package hmatrix-tests
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.