JuliaCF64LinearAlgebra

jla64.spad line 399 [edit on github]

Linear Algebra functions computed using Julia and its algorithms. 64 bits version.

conditionNumber: (JuliaComplexF64Matrix, JuliaFloat64) -> JuliaFloat64

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

conditionNumber: JuliaComplexF64Matrix -> JuliaFloat64

conditionNumber(m) computes the condition number of m.

condSkeel: JuliaComplexF64Matrix -> JuliaFloat64

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

eigen!: JuliaComplexF64Matrix -> Record(values: JuliaComplexF64Vector, vectors: JuliaComplexF64Matrix)

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

eigen: JuliaComplexF64Matrix -> Record(values: JuliaComplexF64Vector, vectors: JuliaComplexF64Matrix)

eigen(m) computes the spectral decomposition of m.

eigenSystem!: JuliaComplexF64Matrix -> Record(values: JuliaComplexF64Vector, leftVectors: JuliaComplexF64Matrix, rightVectors: JuliaComplexF64Matrix)

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

eigenSystem: JuliaComplexF64Matrix -> Record(values: JuliaComplexF64Vector, leftVectors: JuliaComplexF64Matrix, rightVectors: JuliaComplexF64Matrix)

eigenSystem(m) computes the spectral decomposition of m.

eigvals!: JuliaComplexF64Matrix -> JuliaComplexF64Vector

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

eigvals: JuliaComplexF64Matrix -> JuliaComplexF64Vector

eigvals(m) returns the eigen values of m.

eigvecs: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

eigvecs(m) returns the eigen vectors of m.

exp: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

exp(m) returns the matrix exponential of m.

log: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

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

mpInverse: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

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

norm: (JuliaComplexF64Matrix, JuliaFloat64) -> JuliaFloat64

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

norm: (JuliaComplexF64Vector, JuliaFloat64) -> JuliaFloat64

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

norm: JuliaComplexF64Matrix -> JuliaFloat64

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

norm: JuliaComplexF64Vector -> JuliaFloat64

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

normalize!: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

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

normalize!: JuliaComplexF64Vector -> JuliaComplexF64Vector

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

normalize: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

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

normalize: JuliaComplexF64Vector -> JuliaComplexF64Vector

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

operatorNorm: (JuliaComplexF64Matrix, JuliaFloat64) -> JuliaFloat64

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

operatorNorm: JuliaComplexF64Matrix -> JuliaFloat64

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

rank!: (JuliaComplexF64Matrix, JuliaFloat64) -> NonNegativeInteger

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

rank: (JuliaComplexF64Matrix, JuliaFloat64) -> NonNegativeInteger

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

solve!: (JuliaComplexF64Matrix, JuliaComplexF64Matrix) -> JuliaComplexF64Matrix

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

solve: (JuliaComplexF64Matrix, JuliaComplexF64Matrix) -> JuliaComplexF64Matrix

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

sqrt: JuliaComplexF64Matrix -> JuliaComplexF64Matrix

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

svd!: JuliaComplexF64Matrix -> Record(U: JuliaComplexF64Matrix, sv: JuliaFloat64Vector, Vt: JuliaComplexF64Matrix)

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

svd: JuliaComplexF64Matrix -> Record(U: JuliaComplexF64Matrix, sv: JuliaFloat64Vector, Vt: JuliaComplexF64Matrix)

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

svdvals!: JuliaComplexF64Matrix -> JuliaFloat64Vector

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

svdvals: JuliaComplexF64Matrix -> JuliaFloat64Vector

svdvals(m) returns the singular values of m.