lubeck

Members

Enums

fastmath

anonymousenum fastmath

Undocumented in source.

Functions

choleskyDecomp

auto choleskyDecomp(Slice!(kind, [2], Iterator) a, char uplo)

Computs Cholesky decomposition of symmetric positive definite matrix 'A'. The factorization has the form: \A = U**T * U, if UPLO = Upper, or \A = L * L**T, if UPLO = Lower Where U is an upper triangular matrix and L is lower triangular.

choleskySolve

auto choleskySolve(Slice!(Canonical, [2], IteratorC) c, Slice!(kindB, n, IteratorB) b, char uplo)

Solves a system of linear equations A * X = B with a symmetric matrix A using the Cholesky factorization: \A = U**T * U or \A = L * L**T computed by choleskyDecomp.

cov

Slice!(Contiguous, [2], BlasType!Iterator*) cov(Slice!(kind, [2], Iterator) matrix)

Covariance matrix.

det

auto det(Slice!(kind, [2], Iterator) a)

Matrix determinant.

detSymmetric

auto detSymmetric(Slice!(kind, [2], Iterator) a, char store)

Matrix determinant.

eigSymmetric

auto eigSymmetric(Slice!(kind, [2], Iterator) a, char store)

Eigenvalues and eigenvectors of symmetric matrix.

inv

auto inv(Slice!(kind, [2], Iterator) a)

Calculates the inverse of a matrix.

ldlDecomp

auto ldlDecomp(Slice!(kind, [2], Iterator) a, char uplo)

Computes the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method. The for of the factorization is: \A = L*D*L**T Where L is product if permutation and unit lower triangular matrices, and D is symmetric and block diagonal with '1 x 1' and '2 x 2' diagonal blocks.

ldlSolve

auto ldlSolve(Slice!(Canonical, [2], IteratorA) a, Slice!(Contiguous, [1], lapackint*) ipiv, Slice!(kindB, n, IteratorB) b, char uplo)

Solves a system of linear equations \A * X = B with symmetric matrix 'A' using the factorization \A = U * D * U**T, or \A = L * D * L**T computed by ldlDecomp.

luDecomp

auto luDecomp(Slice!(kind, [2], Iterator) a)

Computes LU factorization of a general 'M x N' matrix 'A' using partial pivoting with row interchanges. The factorization has the form: \A = P * L * U Where P is a permutation matrix, L is lower triangular with unit diagonal elements (lower trapezoidal if m > n), and U is upper triangular (upper trapezoidal if m < n).

luSolve

auto luSolve(Slice!(Canonical, [2], IteratorLU) lut, Slice!(Contiguous, [1], lapackint*) ipiv, Slice!(kindB, n, IteratorB) b, char trans)

Solves a system of linear equations \A * X = B, or \A**T * X = B with a general 'N x N' matrix 'A' using the LU factorization computed by luDecomp.

mldivide

Slice!(Contiguous, [2], BlasType!(IteratorA, IteratorB)*) mldivide(Slice!(kindA, [2], IteratorA) a, Slice!(kindB, [2], IteratorB) b)

Slice!(Contiguous, [1], BlasType!(IteratorA, IteratorB)*) mldivide(Slice!(kindA, [2], IteratorA) a, Slice!(kindB, [1], IteratorB) b)

Solve systems of linear equations AX = B for X. Computes minimum-norm solution to a linear least squares problem if A is not a square matrix.

mtimes

Slice!(Contiguous, [2], BlasType!(IteratorA, IteratorB)*) mtimes(Slice!(kindA, [2], IteratorA) a, Slice!(kindB, [2], IteratorB) b)

General matrix-matrix multiplication. Allocates result to an uninitialized slice using GC.

mtimes

Slice!(Contiguous, [1], BlasType!(IteratorA, IteratorB)*) mtimes(Slice!(kindA, [2], IteratorA) a, Slice!(kindB, [1], IteratorB) b)

General matrix-matrix multiplication. Allocates result to an uninitialized slice using GC.

mtimes

Slice!(Contiguous, [1], BlasType!(IteratorA, IteratorB)*) mtimes(Slice!(kindB, [1], IteratorB) a, Slice!(kindA, [2], IteratorA) b)

General matrix-matrix multiplication.

mtimes

CommonType!(BlasType!IteratorA, BlasType!IteratorB) mtimes(Slice!(kindB, [1], IteratorB) a, Slice!(kindA, [1], IteratorA) b)

Vector-vector multiplication (dot product).

pca

auto pca(Slice!(kind, [2], Iterator) matrix, Flag!"centerColumns" cc)

Principal component analysis of raw data.

pinv

Slice!(Contiguous, [2], BlasType!Iterator*) pinv(Slice!(kind, [2], Iterator) matrix, BlasType!Iterator tolerance)

Computes Moore-Penrose pseudoinverse of matrix.

qrDecomp

auto qrDecomp(Slice!(kind, [2], Iterator) a)

Computes a QR factorization of matrix 'a'.

qrSolve

auto qrSolve(Slice!(Canonical, [2], IteratorA) a, Slice!(Contiguous, [1], IteratorT) tau, Slice!(kindB, n, IteratorB) b)

Solve the least squares problem: \min ||A * X - B|| Using the QR factorization: \A = Q * R computed by qrDecomp.

svd

auto svd(Slice!(kind, [2], Iterator) matrix, Flag!"slim" slim)

Computes the singular value decomposition.

Structs

EigSymmetricResult

struct EigSymmetricResult(T)

Eigenvalues and eigenvectors POD.

LDLResult

struct LDLResult(T)

Consist LDL factorization;

LUResult

struct LUResult(T)

LUResult consist lu factorization.

PcaResult

struct PcaResult(T)

Principal component analises result.

QRResult

struct QRResult(T)

SvdResult

struct SvdResult(T)

choleskyResult

struct choleskyResult(T)

Undocumented in source.

• lubeck