## org.netlib.lapack Class Sgesvx

```java.lang.Object
org.netlib.lapack.Sgesvx
```

`public class Sgesvxextends java.lang.Object`

```Following is the description from the original
Fortran source.  For each array argument, the Java
version will include an integer offset parameter, so
the arguments may not match the description exactly.
Contact seymour@cs.utk.edu with any questions.

*     ..
*
*  Purpose
*  =======
*
*  SGESVX uses the LU factorization to compute the solution to a real
*  system of linear equations
*     A * X = B,
*  where A is an N-by-N matrix and X and B are N-by-NRHS matrices.
*
*  Error bounds on the solution and a condition estimate are also
*  provided.
*
*  Description
*  ===========
*
*  The following steps are performed:
*
*  1. If FACT = 'E', real scaling factors are computed to equilibrate
*     the system:
*        TRANS = 'N':  diag(R)*A*diag(C)     *inv(diag(C))*X = diag(R)*B
*        TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B
*        TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B
*     Whether or not the system will be equilibrated depends on the
*     scaling of the matrix A, but if equilibration is used, A is
*     overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N')
*     or diag(C)*B (if TRANS = 'T' or 'C').
*
*  2. If FACT = 'N' or 'E', the LU decomposition is used to factor the
*     matrix A (after equilibration if FACT = 'E') as
*        A = P * L * U,
*     where P is a permutation matrix, L is a unit lower triangular
*     matrix, and U is upper triangular.
*
*  3. If some U(i,i)=0, so that U is exactly singular, then the routine

*     returns with INFO = i. Otherwise, the factored form of A is used
*     to estimate the condition number of the matrix A.  If the
*     reciprocal of the condition number is less than machine precision,
*     INFO = N+1 is returned as a warning, but the routine still goes on
*     to solve for X and compute error bounds as described below.
*
*  4. The system of equations is solved for X using the factored form
*     of A.
*
*  5. Iterative refinement is applied to improve the computed solution
*     matrix and calculate error bounds and backward error estimates
*     for it.
*
*  6. If equilibration was used, the matrix X is premultiplied by
*     diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so
*     that it solves the original system before equilibration.
*
*  Arguments
*  =========
*
*  FACT    (input) CHARACTER*1
*          Specifies whether or not the factored form of the matrix A is
*          supplied on entry, and if not, whether the matrix A should be
*          equilibrated before it is factored.
*          = 'F':  On entry, AF and IPIV contain the factored form of A.
*                  If EQUED is not 'N', the matrix A has been
*                  equilibrated with scaling factors given by R and C.
*                  A, AF, and IPIV are not modified.
*          = 'N':  The matrix A will be copied to AF and factored.
*          = 'E':  The matrix A will be equilibrated if necessary, then

*                  copied to AF and factored.
*
*  TRANS   (input) CHARACTER*1
*          Specifies the form of the system of equations:
*          = 'N':  A * X = B     (No transpose)
*          = 'T':  A**T * X = B  (Transpose)
*          = 'C':  A**H * X = B  (Transpose)
*
*  N       (input) INTEGER
*          The number of linear equations, i.e., the order of the
*          matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrices B and X.  NRHS >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the N-by-N matrix A.  If FACT = 'F' and EQUED is
*          not 'N', then A must have been equilibrated by the scaling
*          factors in R and/or C.  A is not modified if FACT = 'F' or
*          'N', or if FACT = 'E' and EQUED = 'N' on exit.
*
*          On exit, if EQUED .ne. 'N', A is scaled as follows:
*          EQUED = 'R':  A := diag(R) * A
*          EQUED = 'C':  A := A * diag(C)
*          EQUED = 'B':  A := diag(R) * A * diag(C).
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  AF      (input or output) REAL array, dimension (LDAF,N)
*          If FACT = 'F', then AF is an input argument and on entry
*          contains the factors L and U from the factorization
*          A = P*L*U as computed by SGETRF.  If EQUED .ne. 'N', then
*          AF is the factored form of the equilibrated matrix A.
*
*          If FACT = 'N', then AF is an output argument and on exit
*          returns the factors L and U from the factorization A = P*L*U

*          of the original matrix A.
*
*          If FACT = 'E', then AF is an output argument and on exit
*          returns the factors L and U from the factorization A = P*L*U

*          of the equilibrated matrix A (see the description of A for
*          the form of the equilibrated matrix).
*
*  LDAF    (input) INTEGER
*          The leading dimension of the array AF.  LDAF >= max(1,N).
*
*  IPIV    (input or output) INTEGER array, dimension (N)
*          If FACT = 'F', then IPIV is an input argument and on entry
*          contains the pivot indices from the factorization A = P*L*U
*          as computed by SGETRF; row i of the matrix was interchanged
*          with row IPIV(i).
*
*          If FACT = 'N', then IPIV is an output argument and on exit
*          contains the pivot indices from the factorization A = P*L*U
*          of the original matrix A.
*
*          If FACT = 'E', then IPIV is an output argument and on exit
*          contains the pivot indices from the factorization A = P*L*U
*          of the equilibrated matrix A.
*
*  EQUED   (input or output) CHARACTER*1
*          Specifies the form of equilibration that was done.
*          = 'N':  No equilibration (always true if FACT = 'N').
*          = 'R':  Row equilibration, i.e., A has been premultiplied by

*                  diag(R).
*          = 'C':  Column equilibration, i.e., A has been postmultiplied
*                  by diag(C).
*          = 'B':  Both row and column equilibration, i.e., A has been
*                  replaced by diag(R) * A * diag(C).
*          EQUED is an input argument if FACT = 'F'; otherwise, it is an
*          output argument.
*
*  R       (input or output) REAL array, dimension (N)
*          The row scale factors for A.  If EQUED = 'R' or 'B', A is
*          multiplied on the left by diag(R); if EQUED = 'N' or 'C', R
*          is not accessed.  R is an input argument if FACT = 'F';
*          otherwise, R is an output argument.  If FACT = 'F' and
*          EQUED = 'R' or 'B', each element of R must be positive.
*
*  C       (input or output) REAL array, dimension (N)
*          The column scale factors for A.  If EQUED = 'C' or 'B', A is

*          multiplied on the right by diag(C); if EQUED = 'N' or 'R', C

*          is not accessed.  C is an input argument if FACT = 'F';
*          otherwise, C is an output argument.  If FACT = 'F' and
*          EQUED = 'C' or 'B', each element of C must be positive.
*
*  B       (input/output) REAL array, dimension (LDB,NRHS)
*          On entry, the N-by-NRHS right hand side matrix B.
*          On exit,
*          if EQUED = 'N', B is not modified;
*          if TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by
*          diag(R)*B;
*          if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is
*          overwritten by diag(C)*B.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  X       (output) REAL array, dimension (LDX,NRHS)
*          If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X
*          to the original system of equations.  Note that A and B are
*          modified on exit if EQUED .ne. 'N', and the solution to the
*          equilibrated system is inv(diag(C))*X if TRANS = 'N' and
*          EQUED = 'C' or 'B', or inv(diag(R))*X if TRANS = 'T' or 'C'
*          and EQUED = 'R' or 'B'.
*
*  LDX     (input) INTEGER
*          The leading dimension of the array X.  LDX >= max(1,N).
*
*  RCOND   (output) REAL
*          The estimate of the reciprocal condition number of the matrix
*          A after equilibration (if done).  If RCOND is less than the
*          machine precision (in particular, if RCOND = 0), the matrix
*          is singular to working precision.  This condition is
*          indicated by a return code of INFO > 0.
*
*  FERR    (output) REAL array, dimension (NRHS)
*          The estimated forward error bound for each solution vector
*          X(j) (the j-th column of the solution matrix X).
*          If XTRUE is the true solution corresponding to X(j), FERR(j)

*          is an estimated upper bound for the magnitude of the largest

*          element in (X(j) - XTRUE) divided by the magnitude of the
*          largest element in X(j).  The estimate is as reliable as
*          the estimate for RCOND, and is almost always a slight
*          overestimate of the true error.
*
*  BERR    (output) REAL array, dimension (NRHS)
*          The componentwise relative backward error of each solution
*          vector X(j) (i.e., the smallest relative change in
*          any element of A or B that makes X(j) an exact solution).
*
*  WORK    (workspace/output) REAL array, dimension (4*N)
*          On exit, WORK(1) contains the reciprocal pivot growth
*          factor norm(A)/norm(U). The "max absolute element" norm is
*          used. If WORK(1) is much less than 1, then the stability
*          of the LU factorization of the (equilibrated) matrix A
*          could be poor. This also means that the solution X, condition
*          estimator RCOND, and forward error bound FERR could be
*          unreliable. If factorization fails with 0 0:  if INFO = i, and i is
*                <= N:  U(i,i) is exactly zero.  The factorization has
*                       been completed, but the factor U is exactly
*                       singular, so the solution and error bounds
*                       could not be computed. RCOND = 0 is returned.
*                = N+1: U is nonsingular, but RCOND is less than machine
*                       precision, meaning that the matrix is singular
*                       to working precision.  Nevertheless, the
*                       solution and error bounds are computed because
*                       there are a number of situations where the
*                       computed solution can be more accurate than the

*                       value of RCOND would suggest.
*
*  =====================================================================
*
*     .. Parameters ..
```

Constructor Summary
`Sgesvx()`

Method Summary
`static void` ```sgesvx(java.lang.String fact, java.lang.String trans, int n, int nrhs, float[] a, int _a_offset, int lda, float[] af, int _af_offset, int ldaf, int[] ipiv, int _ipiv_offset, StringW equed, float[] r, int _r_offset, float[] c, int _c_offset, float[] b, int _b_offset, int ldb, float[] x, int _x_offset, int ldx, floatW rcond, float[] ferr, int _ferr_offset, float[] berr, int _berr_offset, float[] work, int _work_offset, int[] iwork, int _iwork_offset, intW info)```

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### Sgesvx

`public Sgesvx()`
Method Detail

### sgesvx

```public static void sgesvx(java.lang.String fact,
java.lang.String trans,
int n,
int nrhs,
float[] a,
int _a_offset,
int lda,
float[] af,
int _af_offset,
int ldaf,
int[] ipiv,
int _ipiv_offset,
StringW equed,
float[] r,
int _r_offset,
float[] c,
int _c_offset,
float[] b,
int _b_offset,
int ldb,
float[] x,
int _x_offset,
int ldx,
floatW rcond,
float[] ferr,
int _ferr_offset,
float[] berr,
int _berr_offset,
float[] work,
int _work_offset,
int[] iwork,
int _iwork_offset,
intW info)```