JuliaCF32LinearAlgebra

jla32.spad line 390 [edit on github]

Linear Algebra functions computed using Julia and its algorithms. 32 bits version.

conditionNumber: (JuliaComplexF32Matrix, JuliaFloat32) -> JuliaFloat32

conditionNumber(m) computes the p-condition number of m.

conditionNumber: JuliaComplexF32Matrix -> JuliaFloat32

conditionNumber(m) computes the condition number of m.

condSkeel: JuliaComplexF32Matrix -> JuliaFloat32

condsKeel(m) computes the Skeel condition number of m.

eigen!: JuliaComplexF32Matrix -> Record(values: JuliaComplexF32Vector, vectors: JuliaComplexF32Matrix)

eigen!(m) computes the spectral decomposition of m but overwrites m to save memory space.

eigen: JuliaComplexF32Matrix -> Record(values: JuliaComplexF32Vector, vectors: JuliaComplexF32Matrix)

eigen(m) computes the spectral decomposition of m.

eigenSystem!: JuliaComplexF32Matrix -> Record(values: JuliaComplexF32Vector, leftVectors: JuliaComplexF32Matrix, rightVectors: JuliaComplexF32Matrix)

eigenSystem!(m) computes the spectral decomposition of m but overwrites m to save memory space.

eigenSystem: JuliaComplexF32Matrix -> Record(values: JuliaComplexF32Vector, leftVectors: JuliaComplexF32Matrix, rightVectors: JuliaComplexF32Matrix)

eigenSystem(m) computes the spectral decomposition of m.

eigvals!: JuliaComplexF32Matrix -> JuliaComplexF32Vector

eigvals!(m) returns the eigen values of m but overwrites m to save memory space.

eigvals: JuliaComplexF32Matrix -> JuliaComplexF32Vector

eigvals(m) returns the eigen values of m.

eigvecs: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

eigvecs(m) returns the eigen vectors of m.

exp: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

exp(m) returns the matrix exponential of m.

log: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

log(m) tries to compute the principal matrix logarithm of m. Otherwise, returns a non pricipal matrix logarithm of m if possible.

mpInverse: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

mpInverse(m) returns the Moore-Penrose pseudo inverse of m.

norm: (JuliaComplexF32Matrix, JuliaFloat32) -> JuliaFloat32

norm(m,p) computes the p-norm of m.

norm: (JuliaComplexF32Vector, JuliaFloat32) -> JuliaFloat32

norm(v,p) computes th p-norm of v.

norm: JuliaComplexF32Matrix -> JuliaFloat32

norm(m) computes the 2-norm of m, also known as the Frobenius norm.

norm: JuliaComplexF32Vector -> JuliaFloat32

norm(v) computes the 2-norm of v.

normalize!: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

normalize!(m) destructively normalize m such that its norm equals to 1.

normalize!: JuliaComplexF32Vector -> JuliaComplexF32Vector

normalize!(v) destructively normalize v such that norm(v) equals to 1.

normalize: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

normalize(m) returns normalized m such that its norm equals to 1.

normalize: JuliaComplexF32Vector -> JuliaComplexF32Vector

normalize(v) returns normalized v such that its norm equals to 1.

operatorNorm: (JuliaComplexF32Matrix, JuliaFloat32) -> JuliaFloat32

operatorNorm(m,p) computes the operator norm of m induced by the vector p-norm.

operatorNorm: JuliaComplexF32Matrix -> JuliaFloat32

operatorNorm(m) computes the operator norm of m induced by the vector 2-norm.

rank!: (JuliaComplexF32Matrix, JuliaFloat32) -> NonNegativeInteger

rank!(m, tol) computes rank of m. Counts singular value with magnitude greater than tol but overwrites m to save memory space.

rank: (JuliaComplexF32Matrix, JuliaFloat32) -> NonNegativeInteger

rank(m, tol) computes rank of m. Counts singular value with magnitude greater than tol.

solve!: (JuliaComplexF32Matrix, JuliaComplexF32Matrix) -> JuliaComplexF32Matrix

solve!(A,B) solves the matrix equation A*X=B. Overwrites B with matrix X and returns X.

solve: (JuliaComplexF32Matrix, JuliaComplexF32Matrix) -> JuliaComplexF32Matrix

solve(A,B) solves the matrix equation A*X=B, and returns X.

sqrt: JuliaComplexF32Matrix -> JuliaComplexF32Matrix

sqrt(m) returns the principal square root of m.

svd!: JuliaComplexF32Matrix -> Record(U: JuliaComplexF32Matrix, sv: JuliaFloat32Vector, Vt: JuliaComplexF32Matrix)

svd!(m) is the same as svd(m) but overwites a to save memory space.

svd: JuliaComplexF32Matrix -> Record(U: JuliaComplexF32Matrix, sv: JuliaFloat32Vector, Vt: JuliaComplexF32Matrix)

svd(m) computes the singular value decomposition SVD of m such that SVD.U * diagonalMatrix(sv) * SVD.Vt = m.

svdvals!: JuliaComplexF32Matrix -> JuliaFloat32Vector

svdvals!(m) returns the singular values of m but overwrites m to save memory space.

svdvals: JuliaComplexF32Matrix -> JuliaFloat32Vector

svdvals(m) returns the singular values of m.