Matrix package:lapack

QC.forAll genDD $ \(xs, (ys0,ys1)) -> approxArray (dividedDifferencesMatrix xs (ys0|+|ys1)) (dividedDifferencesMatrix xs ys0 #+# dividedDifferencesMatrix xs ys1)

QC.forAll genDD $ \(xs, (ys0,ys1)) -> approxArray (dividedDifferencesMatrix xs (Vector.mul ys0 ys1)) (dividedDifferencesMatrix xs ys0 <> dividedDifferencesMatrix xs ys1)

parameterDifferencesMatrix :: Vector ShapeInt Float -> Upper ShapeInt Float

lapack Numeric.LAPACK.Example.DividedDifference

QC.forAll (QC.choose (0,10)) $ \n -> let sh = shapeInt n in QC.forAll (Util.genDistinct [-10..10] [-10..10] sh) $ \xs -> approxArray (DD.parameterDifferencesMatrix xs) (DD.upperFromPyramid sh (Vector.zero sh : DD.parameterDifferences xs))

type SquareMatrix size = Square size Double

lapack Numeric.LAPACK.Example.EconomicAllocation

fromMatrix :: (Measure meas, C vert, C horiz, C height, C width, Floating a) => Full meas vert horiz height width a -> LowerUpper meas vert horiz height width a

lapack Numeric.LAPACK.Linear.LowerUpper

LowerUpper.fromMatrix a computes the LU decomposition of matrix a with row pivotisation. You can reconstruct a from lu depending on whether a is tall or wide.

LU.multiplyP NonInverted lu $ LU.extractL lu ##*# LU.tallExtractU lu
LU.multiplyP NonInverted lu $ LU.wideExtractL lu #*## LU.extractU lu

toMatrix :: (Measure meas, C vert, C horiz, C height, Eq height, C width, Eq width, Floating a) => LowerUpper meas vert horiz height width a -> Full meas vert horiz height width a

lapack Numeric.LAPACK.Linear.LowerUpper

type ArrayMatrix pack property = Matrix (Array pack property) () ()

lapack Numeric.LAPACK.Matrix.Array

fromMatrix :: (Measure meas, C vert, C horiz, C height, C width, Floating a) => Full meas vert horiz height width a -> Householder meas vert horiz height width a

lapack Numeric.LAPACK.Orthogonal.Householder

toMatrix :: (C sh, Floating a) => Permutation sh -> Square sh a

lapack Numeric.LAPACK.Permutation