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lax/src/lib.rs

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//! Linear Algebra eXtension (LAX)
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//! ===============================
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//!
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//! ndarray-free safe Rust wrapper for LAPACK FFI
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//!
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//! Linear equation, Inverse matrix, Condition number
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//! --------------------------------------------------
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//!
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//! As the property of $A$, several types of triangular factorization are used:
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//!
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//! - LU-decomposition for general matrix
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//! - $PA = LU$, where $L$ is lower matrix, $U$ is upper matrix, and $P$ is permutation matrix
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//! - Bunch-Kaufman diagonal pivoting method for nonpositive-definite Hermitian matrix
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//! - $A = U D U^\dagger$, where $U$ is upper matrix,
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//! $D$ is Hermitian and block diagonal with 1-by-1 and 2-by-2 diagonal blocks.
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//!
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//! | matrix type | Triangler factorization (TRF) | Solve (TRS) | Inverse matrix (TRI) | Reciprocal condition number (CON) |
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//! |:--------------------------------|:------------------------------|:------------|:---------------------|:----------------------------------|
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//! | General (GE) | [lu] | [solve] | [inv] | [rcond] |
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//! | Symmetric (SY) / Hermitian (HE) | [bk] | [solveh] | [invh] | - |
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//!
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//! [lu]: solve/trait.Solve_.html#tymethod.lu
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//! [solve]: solve/trait.Solve_.html#tymethod.solve
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//! [inv]: solve/trait.Solve_.html#tymethod.inv
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//! [rcond]: solve/trait.Solve_.html#tymethod.rcond
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//!
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//! [bk]: solveh/trait.Solveh_.html#tymethod.bk
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//! [solveh]: solveh/trait.Solveh_.html#tymethod.solveh
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//! [invh]: solveh/trait.Solveh_.html#tymethod.invh
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//!
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//! Eigenvalue Problem
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//! -------------------
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//!
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//! Solve eigenvalue problem for a matrix $A$
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//!
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//! $$ Av_i = \lambda_i v_i $$
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//!
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//! or generalized eigenvalue problem
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//!
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//! $$ Av_i = \lambda_i B v_i $$
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//!
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//! | matrix type | Eigenvalue (EV) | Generalized Eigenvalue Problem (EG) |
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//! |:--------------------------------|:----------------|:------------------------------------|
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//! | General (GE) |[eig] | - |
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//! | Symmetric (SY) / Hermitian (HE) |[eigh] |[eigh_generalized] |
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//!
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//! [eig]: eig/trait.Eig_.html#tymethod.eig
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//! [eigh]: eigh/trait.Eigh_.html#tymethod.eigh
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//! [eigh_generalized]: eigh/trait.Eigh_.html#tymethod.eigh_generalized
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//!
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//! Singular Value Decomposition (SVD), Least square problem
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//! ----------------------------------------------------------
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//!
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//! | matrix type | Singular Value Decomposition (SVD) | SVD with divided-and-conquer (SDD) | Least square problem (LSD) |
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//! |:-------------|:-----------------------------------|:-----------------------------------|:---------------------------|
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//! | General (GE) | [svd] | [svddc] | [least_squares] |
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//!
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//! [svd]: svd/trait.SVD_.html#tymethod.svd
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//! [svddc]: svddck/trait.SVDDC_.html#tymethod.svddc
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//! [least_squares]: least_squares/trait.LeastSquaresSvdDivideConquer_.html#tymethod.least_squares
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extern crate blas_src;
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extern crate lapack_src;

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