/*
 *  linsol II: Ascend Linear Equation Solver
 *  by Karl Westerberg
 *  Created: 2/6/90
 *  Version: $Revision: 1.13 $
 *  Version control file: $RCSfile: linsolqr.h,v $
 *  Date last modified: $Date: 1997/07/25 17:23:49 $
 *  Last modified by: $Author: ballan $
 *
 *  This file is part of the SLV solver.
 *
 *  Copyright (C) 1990 Karl Michael Westerberg
 *  Copyright (C) 1993 Joseph Zaher
 *  Copyright (C) 1994 Joseph Zaher, Benjamin Andrew Allan
 *  Copyright (C) 1995 Benjamin Andrew Allan, Kirk Andre' Abbott
 *
 *  QR options by Ben Allan
 *  based on sqr.pas v1.5: Copyright (C) 1994 Boyd Safrit
 *
 *  The SLV solver is free software; you can redistribute
 *  it and/or modify it under the terms of the GNU General Public License as
 *  published by the Free Software Foundation; either version 2 of the
 *  License, or (at your option) any later version.
 *
 *  The SLV solver is distributed in hope that it will be
 *  useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 *  General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License along with
 *  the program; if not, write to the Free Software Foundation, Inc., 675
 *  Mass Ave, Cambridge, MA 02139 USA.  Check the file named COPYING.
 *  COPYING is found in ../compiler.
 */

/*************************************************************************
 ***  Contents:     ASCEND generalized linear equation solver module
 ***
 ***  Authors:      Numerous. See copyrights above and methods below.
 ***
 ***  Dates:        06/90 - original version (KW)
 ***                04/91 - removed output assignment and partitioning
 ***                        (belong in structural analysis) (JZ)
 ***                08/92 - added transpose ability (JZ)
 ***                01/94 - broke out linsol_invert() and linsol_solve() (JZ)
 ***                10/94 - reorganized for multiple methods and QR (BA)
 ***                        moved drag operator to mtx (BA,JZ)
 ***                11/94 - added linsolqr_get_factors/inverse for debugging.BA
 ***                09/95 - added factor_class to better manage families. BA
 ***                09/95 - added ranki_*2 methods (BA)
 ***                09/95 - added gauss (broken) (KA)
 ***                11/96 - added ranki_ba2 method (BA)
 ***
 ***  Description:  A linear system consists of a coefficient matrix (A)
 ***                and possibly several right-hand-sides (rhs).  The
 ***                solution vector x sought can be that of either
 ***
 ***                                         T
 ***                   A x = rhs      or    A x = rhs
 ***
 ***                depending on a specification inherent with rhs which
 ***                dictates whether or not A should be transposed.  If a
 ***                rhs specifies transpose, then the vector itself is
 ***                expected to be indexed by the original column numbers
 ***                of the coefficient matrix and the solution vector shall
 ***                be indexed by original row numbers.  Otherwise, rhs
 ***                is expected to be indexed by original row numbers while
 ***                the solution can be referenced using original column
 ***                numbers.  The coefficient matrix and each rhs will be
 ***                preserved throughout solving, except that the
 ***                coefficient matrix may be permuted during reordering
 ***                or (depending on the method) solving. 
 ***
 ***                The method of linear solution is an option new to
 ***                linsolqr. Also, some of the data structures have been
 ***                expanded as required. The factoring methods are
 ***                enumerated and summarized below.
 ***
 ***                Linsol is a general sparse solver. It uses mtx, though any
 ***                proper sparse matrix package can be substituted. By
 ***                proper, of course, we mean one with at least the
 ***                functionality of mtx. If you find something with all
 ***                the features of mtx that is faster than mtx, let us
 ***                know, please. If you do any comparisons of linsol with
 ***                other sparse codes (on sequential processors) also
 ***                please let us know how you find its performance.
 ***                You probably won't find algorithms for banded or
 ***                symmetric matrices here. Why?
 ***                The efficiency of most banded algorithms comes from
 ***                the way they access memory with three assumptions: 
 ***                that all possible coefficient locations are known before
 ***                a solution is attempted, that they are accessible
 ***                in some ORDERED fashion, and that the matrix will not
 ***                be reordered (except perhaps in very limited ways)
 ***                during solution. Linsol is predicated on just
 ***                the opposite assumptions at the moment.
 ***                These assumptions would relieve the solver of
 ***                memory allocation and a great deal of range checking.
 ***                While we would do our flops efficiently with linsol/mtx
 ***                on a banded matrix, the cost of accessing linear
 ***                coefficients in an UNORDERED fashion is such that a good
 ***                band, variable band, or symmetric skyline code making the
 ***                ORDERED assumption will always beat linsol in speed,
 ***                though perhaps not in robustness.
 *************************************************************************/

#ifndef linsolqr__already_included
#define linsolqr__already_included

/* requires #include <string.h> */
/* requires #include "base.h" */
/* requires #include "mtx.h" */

#define LINSOLMTX_DEBUG FALSE
/* */
#define LINQR_DROP_TOLERANCE 1.0e-16
/* This is the default for drop tolerances in methods which use a drop tol */

typedef struct linsolqr_header *linsolqr_system_t;
/**
 ***  linsolqr_system_t is the linear system handle.
 **/

enum factor_class {
  unknown_c,  /* error handling class */
  ranki = 100,     /* all ranki (and gauss until broken out) methods */
  s_qr = 200       /* all sparse qr methods */
};

enum reorder_method {
  unknown_r,       /* error handling method */
  natural = 1000,  /* do nothing reorder */
  spk1 = 2000,     /* Stadtherr's SPK1 reordering */
  tspk1 = 3000     /* transpose of Stadtherr's SPK1 reordering good for gauss */
  /* future work:
  invspk1,      spk1 then diagonally inverted
  invtspk1,     tspk1 then diagonally inverted
  widespk1,     spk1 of an MxN region, N > M
  */
};

enum factor_method {
  unknown_f = 0,    /* error handling method */
  ranki_kw = 1,     /* original linsol method */
  ranki_jz = 2,     /* original linsol method with pseudo-complete pivoting */
  ranki_kw2 = 3,    /* better data structure version of ranki_kw, w/drop tol */ 
  ranki_jz2 = 4,    /* better data structure version of ranki_jz, w/drop tol */ 
  ranki_ka = 12,    /* kirks hacked verion of the basic method. */
  plain_qr = 5,     /* rectangular col pivoted qr variants */
  cond_qr = 6,      /* stewart-based sparse QR method new Coke */
  ranki_ba2 = 7,    /* proper linked list implementation of ranki (dragfree) */
  opt_qr = 8,       /* coming soon */
  ls_qr = 9,        /* anticipated */
  gauss_ba2 = 10,   /* anticipated */
  symmetric_lu = 11 /* anticipated */
};

extern int g_linsolqr_timing;
/*
 * If nonzero and certain internal defines are set, factorization
 * generates a fill and timing message.
 */


/* KAA_DEBUG */
extern boolean linsolqr_col_is_a_spike (/* mtx_matrix_t mtx,
					   int32 col*/);
/*********************************************************************\
  Returns true if the column in question is a spike.
\*********************************************************************/

/*********************************************************************\
 Each method is described here, including the unimplemented ones,
 however vaguely. By convention all methods assign unpivotable variables
 the value of 0.0 in the linear solution vector. This makes sense because
 the linear system usually arises from a nonlinear scheme wherein
 stepping in the unpivoted variables is left for a future iteration.

 The currently recommended methods are ranki_*2, in particular ba2.

 ranki_kw:
   Reordering method: SPK1, Stadtherr & Wood (1984), and like.
     The region used is confined to the main diagonal.
     The square region is reordered to lower triangular with spikes.
     Each spike is higher than or equal to all spikes to the left of it
     if the matrix is partitioned.
   Solution method: RANKI, Stadtherr & Wood 
     Ref: Computers and Chemical Engineering (8)1 pp. 9-33  (1984)
     The square region is U/L factored with spikes dragged in to replace
     unacceptable pivots. Fill is in spike columns and
     dragged rows where it usually does take place. 
     Numerically dependent rows and columns do not have dependencies
     automatically calculated. This is a change from linsol, so be
     careful in making comparisons.
   Authors: Karl Westerberg, Joe Zaher
     with some clean ups and restructuring by Ben Allan

 ranki_jz:
   As ranki_kw, except where ranki_kw looks only across the current row
   for pivots if the diagonal element is too small, ranki_jz also looks
   down the current column. This introduces additional spikes to the
   current block, but sometimes the overall effect is reduced fill. The
   main motivation is to broaden pivot choices on those problems
   where restricting the choice to the current row results in immediate
   explosions of fill due to a full subdiagonal and a moderately small
   pivot. 

 ranki_kw2:
 ranki_jz2:
   As the ranki_XX factorizations, except uses drop tolerance and
   uses much faster bilevel matrices (master + slave matrix of mtx)
   to segregate the contents of U from L. Also, dependency information
   is not calculated automatically.
   Author: Ben Allan

 ranki_ba2:
   As the ranki_kw2 factorization, except pivot and row being eliminated
   are stored as linked lists/full org vectors (dual access) during
   elimination which removes the last significant quadratic effect from
   the ranki factorization.

 plain_qr:
   Reordering method: Transpose SPK1 (tspk1), LORA
     The region used may be rectangular, but will be modified
     if needed so that the upper left corner is on the diagonal.
     The region in sys->coef is not permuted in the solution process.
   Solution method:
     The rectangular region is QR factored with standard column pivoting
     modified by the pivot_tolerance. That is, at each step the column
     to factor in next is the leftmost col with norm alpha that satisfies
     alpha >= ptol * maxalpha.
     ptol = 1 --> Stewart's QRDC style pivoting.
     ptol = 0 --> no pivoting (Sometimes a dumb idea).
     plain_qr is to QRDC as ranki_kw is to LU factorization with strict
     partial pivoting.
     This implementation is best used on matrices where nrows about = ncols
     and data are not highly correlated.
     There are better QR methods (not available here) for vector processors, 
     distributed processors, data fitting and so forth.
     Some care has been taken that the implementation here will scale up
     reasonably to larger matrices.
     Detailed references are given in the plain_qr section of the .c file.
 Author: Ben Allan

 cond_qr: (broken)
   Reordering method: Transpose SPK1 (tspk1)
     The region used is confined to the main diagonal.
     The square region is permuted in the solution process.
   Solution method:
     The square region is QR factored with pivoting by a local minimum
     fill criteria balanced against choosing pivots based on the
     incremental inverse R condition number.
     Ref:Incremental Condition Calculation and Column Selection,
         UMIACS TR 90-87, G.W.Stewart, July 1990)
     (Allan, Safrit, Westerberg, 1995)
 Authors: Ben Allan

 opt_qr:
   As cond_qr, except region may be underspecified (MxN, M < N)
   The region's upper left corner should be (or will be forced to be)
   on the main diagonal. The columns pivoted are expected to be a
   good basis. Solution is not a least squares solution of the
   transpose NxM problem; for this we need rowwise Householder
   transforms and spk1 reordering.
 Authors: Ben Allan

 ls_qr:    
   As cond_qr, except region may be overspecified (MxN, M > N)
   Solves the system in a linear least squares sense.
 Authors: Ben Allan

 band_lu:   
 symmetric_lu:
 (cholesky?)
   The best codes we can find already implemented to complement and/or
   verify our own. More detailed semantics unknown at this time.

 The parameters pivot_tolerance, condition_tolerance and drop_tolerance
 have semantics varying with the method.
 See the header of linsolqr_set_pivot_tolerance below for details.
\*********************************************************************/

/* Functions for managing interfaces */

extern char *linsolqr_rmethods();
/**
 *** s=linsolqr_rmethods();
 ***
 *** Returns a , separated list of the names of reordering methods
 *** implemented. If you implement a new method, update this
 *** function. Do not free the pointer returned.
 ***
 *** Not all reorderings are appropriate to all factorizations.
 **/

extern char *linsolqr_fmethods();
/**
 *** s=linsolqr_fmethods();
 ***
 *** Returns a , separated list of the names of factorization methods
 *** implemented. If you implement a new method, update this
 *** function. Do not free the pointer returned. The string returned
 *** will contain no whitespace of any sort, tabs, blanks, or \n.
 **/

extern enum reorder_method linsolqr_rmethod_to_enum(char *);
/**  
 *** meth=linsolqr_rmethod_to_enum(s);
 ***
 *** Returns the enum of a reorder method with the name s.
 *** If you implement a new method, update this function.
 **/

extern enum factor_method linsolqr_fmethod_to_enum(char *);
/**  
 *** meth=linsolqr_fmethod_to_enum(s);
 ***
 *** Returns the enum of a factor method with the name s.
 *** If you implement a new method, update this function.
 **/

extern enum factor_class linsolqr_fmethod_to_fclass(enum factor_method);
/**  
 *** class=linsolqr_fmethod_to_fclass(fm);
 ***
 *** Returns the enum of the factor class containing the method given.
 *** If you implement a new method or class, update this function.
 **/

extern char *linsolqr_enum_to_rmethod(enum reorder_method);
/**  
 *** s=linsolqr_enum_to_rmethod(m);
 ***
 *** Returns the name of a reorder method with the enum m.
 *** If you implement a new method, update this function.
 *** Do not free the name.
 **/

extern char *linsolqr_enum_to_fmethod(enum factor_method);
/**  
 *** s=linsolqr_enum_to_fmethod(m);
 ***
 *** Returns the name of a factor method with the enum m.
 *** If you implement a new method, update this function.
 *** Do not free the name.
 **/

extern char *linsolqr_rmethod_description(enum reorder_method);
/**  
 *** description=linsolqr_rmethod_description(meth);
 ***
 *** Returns a string describing the method inquired on. Do not mess
 *** with the string: linsolqr owns it.
 *** If you implement a new method, update this function.
 **/

extern char *linsolqr_fmethod_description(enum factor_method);
/**  
 *** description=linsolqr_fmethod_description(meth);
 ***
 *** Returns a string describing the method inquired on. Do not mess
 *** with the string: linsolqr owns it.
 *** If you implement a new method, update this function.
 **/

/* Functions for specifying problems and controlling them */

extern linsolqr_system_t linsolqr_create();
/**
 ***  sys = linsolqr_create()
 ***  linsolqr_system_t sys;
 ***
 ***  Creates a linear system and returns a pointer to it.  Initially the
 ***  system has no coefficient matrix and no rhs.
 **/

extern void linsolqr_destroy(linsolqr_system_t);
/**
 ***  linsolqr_destroy(sys)
 ***  linsolqr_system_t sys;
 ***
 ***  Destroys the linear system.  The coefficient matrix and each rhs are
 ***  not destroyed by this call.
 **/

extern void linsolqr_set_matrix(linsolqr_system_t, mtx_matrix_t);
/**
 ***  linsolqr_set_matrix(sys,mtx)
 ***  linsolqr_system_t sys;
 ***  mtx_matrix_t mtx;
 ***
 ***  Sets the coefficient matrix to mtx.
 **/

extern void linsolqr_set_region(linsolqr_system_t, mtx_region_t);
/**
 ***  linsolqr_set_region(sys,region)
 ***  linsolqr_system_t sys;
 ***  mtx_region_t region;
 ***
 ***  Sets the reg to region.
 **/

extern mtx_matrix_t linsolqr_get_matrix(linsolqr_system_t);
/**
 ***  mtx = linsolqr_get_matrix(sys)
 ***  mtx_matrix_t mtx;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the coefficient matrix.
 **/

extern void linsolqr_add_rhs(linsolqr_system_t, real64 *, boolean);
/**
 ***  linsolqr_add_rhs(sys,rhs,transpose)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs;
 ***  boolean transpose;
 ***
 ***  Adds the given rhs to the collection of rhs's already part of the
 ***  system. 
 ***
 ***  You continue to be responsible for deallocating rhs. We do not take
 ***  over management of that memory. Do not free the rhs you have given
 ***  us without calling linsolqr_remove_rhs first.
 ***
 ***  Rhs should point to an array of reals indexed by original
 ***  column number if the linear system is to be solved using the transpose
 ***  of the matrix or by original row number if the matrix is not to be
 ***  transposed.  This is determined using the boolean transpose.  The
 ***  rhs should be refered to in the future by its pointer.
 ***
 ***  For the mathematically impaired:
 ***  M' denotes Transpose(M).
 ***
 ***  transpose==FALSE --> rhs will be solved for x in A x = b.
 ***                   --> rhs b is an org row indexed column vector.
 ***                   --> x is an org col indexed column vector.
 ***                   --> yields dx = Newton direction in J.dx = -f
 ***                       if the b given is -f.
 ***
 ***  transpose==TRUE  --> rhs will be solved for y in A' y = d.
 ***                   --> rhs d is an org column indexed column vector.
 ***                   --> y is an org row indexed column vector.
 ***                   --> yields dx = Newton direction in J'.dx = -f.
 ***                       if the d given is -f and f,dx are properly indexed.
 ***                       This may be useful if A was created using
 ***                       mtx_transpose in order to improve factorization.
 ***
 ***  Useful matrix identity: (M')^-1 == (M^-1)' for invertible M.
 **/

extern void linsolqr_remove_rhs(linsolqr_system_t, real64 *);
/**
 ***  linsolqr_remove_rhs(sys,rhs)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs;
 ***
 ***  Removes the given rhs from the system.  The rhs is not destroyed, just
 ***  removed from the system.
 **/

extern int32 linsolqr_number_of_rhs(linsolqr_system_t);
/**
 ***  nrhs = linsolqr_number_of_rhs(sys)
 ***  int32 nrhs;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the number of rhs's currently part of the system.
 **/

extern real64 *linsolqr_get_rhs(linsolqr_system_t,int);
/**
 ***  rhs = linsolqr_get_rhs(sys,n)
 ***  real64 *rhs;
 ***  linsolqr_system_t sys;
 ***  int n;
 ***
 ***  Returns the n-th rhs, where rhs's are indexed in the order they were
 ***  added using linsolqr_add_rhs() from 0 to (# rhs's)-1.  NULL is returned
 ***  if the index is out of range.
 **/

extern void linsolqr_matrix_was_changed(linsolqr_system_t);
/**
 ***  linsolqr_matrix_was_changed(sys)
 ***  linsolqr_system_t sys;
 ***
 ***  Informs the solver that a numerical value of a non-zero was changed.
 ***  This must be called whenever any numerical changes to the matrix are
 ***  made.  
 **/

extern void linsolqr_rhs_was_changed(linsolqr_system_t, real64 *);
/**
 ***  linsolqr_rhs_was_changed(sys,rhs)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs;  
 ***
 ***  Informs the solver that the given rhs has been modified.  This must be
 ***  called whenever the rhs is modified.
 **/

extern void linsolqr_set_pivot_zero(linsolqr_system_t, real64);
extern real64 linsolqr_pivot_zero(linsolqr_system_t);
/**
 ***  linsolqr_set_pivot_zero(sys,pivot_zero)
 ***  pivot_zero = linsolqr_pivot_zero(sys)
 ***  linsolqr_system_t sys;
 ***  real64 pivot_zero;
 ***
 ***  Sets/gets the pivot zero for the system.  Pivots less than or equal to
 ***  this value are regarded as zero.  linsolqr_set_pivot_zero() will
 ***  automatically call linsolqr_matrix_was_changed().
 **/

extern void linsolqr_set_pivot_tolerance(linsolqr_system_t, real64);
extern real64 linsolqr_pivot_tolerance(linsolqr_system_t);
extern void linsolqr_set_condition_tolerance(linsolqr_system_t, real64);
extern real64 linsolqr_condition_tolerance(linsolqr_system_t);
extern void linsolqr_set_drop_tolerance(linsolqr_system_t, real64);
extern real64 linsolqr_drop_tolerance(linsolqr_system_t);
/**
 ***  linsolqr_set_pivot_tolerance(sys,ptol)
 ***  ptol = linsolqr_pivot_tolerance(sys)
 ***
 ***  linsolqr_set_condition_tolerance(sys,ctol)
 ***  ctol = linsolqr_condition_tolerance(sys)
 ***
 ***  linsolqr_set_drop_tolerance(sys,dtol)
 ***  dtol = linsolqr_drop_tolerance(sys)
 ***
 ***  linsolqr_system_t sys;
 ***  real64 ptol, ctol,dtol;
 ***
 ***  Sets/gets the pivot/condition/drop tolerance for the system. Semantics of
 ***  tolerances vary with method. Not to be confused with pivot zero, epsilon.
 ***
 ***  pivot_tolerance: Pivots less than this fraction of the maximum pivot
 ***  value in the same row or column (depending on method) are disregarded.
 ***  
 ***  ranki_kw: pivot_tolerance applies to row. condition_tolerance ignored. 
 ***  ranki_jz: pivot_tolerance applies to row and col. condition ignored.
 ***  ranki_ba2:
 ***  ranki_kw2:
 ***  ranki_jz2: as ranki_kw/ranki_jz except that matrix entries below
 ***             dtol in magnitude are dropped.
 ***  plain_qr: pivot_tolerance applies to cols. condition_tolerance used
 ***            with a condition heuristic rather than actual condition.
 *** 
 ***  cond_qr and variants:
 ***  Unpivoted columns are ordered by fill potential and then the first
 ***  of these to meet the criterion CI*condition_tolerance <= min_CI
 ***  is chosen as the next column to pivot with.
 ***  Pivot_tolerance is applied to choose the pivot within the
 ***  selected column.
 *** 
 ***  linsolqr_set_pivot/condition/drop_tolerance() will automatically call
 ***  linsolqr_matrix_was_changed().
 **/

/* Functions for analyzing and querying linear systems. */

extern enum factor_class linsolqr_fclass(linsolqr_system_t);
/**
 ***  meth = linsolqr_fclass(sys)
 ***  enum factor_class;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the most recently set factorization class of the system.
 ***  The system should be previously prepped.
 **/

extern enum factor_method linsolqr_fmethod(linsolqr_system_t);
/**
 ***  meth = linsolqr_fmethod(sys)
 ***  enum factor_method;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the most recently used factorization method of the system.
 ***  The system should be previously prepped.
 **/

extern enum reorder_method linsolqr_rmethod(linsolqr_system_t);
/**
 ***  meth = linsolqr_rmethod(sys)
 ***  enum reorder_method;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the most recently set reorder method of the system.
 ***  The system should be previously prepped.
 **/

extern int32 linsolqr_rank(linsolqr_system_t);
/**
 ***  rank = linsolqr_rank(sys)
 ***  int32 rank;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the rank of the system.  The system must be previously
 ***  factored.
 **/

extern real64 linsolqr_smallest_pivot(linsolqr_system_t);
/**
 ***  smallest_pivot = linsolqr_smallest_pivot(sys)
 ***  real64 smallest_pivot;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns the smallest pivot accepted in solving the system.  The
 ***  system must be previously factored.  If no pivoting was performed,
 ***  MAXDOUBLE is returned.
 **/

extern int linsolqr_prep(linsolqr_system_t,enum factor_class);
/**
 ***  linsolqr_prep(sys,fclass)
 ***  linsolqr_system_t sys;
 ***  enum factor_class;
 ***
 ***  This function is analogous to slv_select_solver. It
 ***  takes care of allocations. The prep call should be done (once) at
 ***  the beginning of any series of linear solutions being performed on
 ***  on the same linsolqr system with the same factorization class.
 *** 
 ***  You must prep before doing a reordering, factorization or solution
 ***  as prep sets up the appropriate internal settings. You should set
 ***  the matrix before you call prep.
 ***  Prep (or subsequent preps) do not affect the right hand sides of
 ***  the system.
 ***  
 ***  If you wish to change from 1 factoring method to another and they
 ***  are not part of the class of compatible methods, you should call
 ***  prep again with the new class.
 ***  After prep is called, reorder should be called before factorization.
 ***  As most of the sparse routines depend for performance on the
 ***  prior reordering.
 ***  
 ***  Return 0 if ok, or 1 otherwise.
 **/

extern int linsolqr_reorder(linsolqr_system_t,mtx_region_t *,
                            enum reorder_method);
/**
 ***  linsolqr_reorder(sys,region,rmeth)
 ***  linsolqr_system_t sys;
 ***  mtx_region_t *region;
 ***  enum reorder_method;
 ***
 ***  The specified region of the coefficient matrix is reordered.  This
 ***  must be called before factoring the matrix.  The specified region
 ***  is assumed to contain only nonempty rows and columns and have a full
 ***  diagonal.
 ***  If the coefficient matrix in use is from a nonlinear system, the
 ***  pattern in the coefficient matrix should be the structural one (as
 ***  opposed to the numerically derived incidence which may be less.)
 ***
 ***  If you use the numerically derived incidence, you will need to reorder
 ***  before every factorization. This is generally not cost effective.
 ***  If region given is mtx_ENTIRE_MATRIX, a search will be done to find
 ***  an appropriate bounding region in the coefficient mtx. This is
 ***  not a particularly cheap search.
 *** 
 ***  This function is analogous to slv_presolve. It
 ***  takes care of any structural analysis necessary
 ***  to the linear solution. The reorder call should be done (once) at
 ***  the beginning of any series of linear solutions being performed on
 ***  on structurally identical matrices.
 *** 
 ***  The reordering done must be appropriate to the factorization class.
 ***  You must reorder before doing a factorization or solution as reorder
 ***  sets up the appropriate internal settings. Even were the internals
 ***  method independent, the reordering is critical to the performance of
 ***  these methods.
 ***  Return 0 if ok, 1 if not.
 ***
 ***  Brief notes on the reorderings available.
 ***    SPK1:  The region you give becomes the region for the problem,
 ***   TSPK1:  but for factorization purposes rows and columns that
 ***           do not intersect the main diagonal within the region
 ***           are considered structurally (therefore numerically) dependent.
 ***   Natural:  Blesses the system and does nothing.
 ***             Again, the rows/cols not in the diagonal are dependent.
 **/

extern int linsolqr_factor(linsolqr_system_t,enum factor_method);
/**
 ***  linsolqr_factor(sys,fmethod)
 ***  linsolqr_system_t sys;
 ***  enum factor_method fmethod;
 ***
 ***  Decompose the reordered region of a copy of the coefficient matrix
 ***  into upper and lower triangular factors (if necessary) which can be
 ***  inverted easily when applied to any rhs.  Matrix must be factored in
 ***  order to perform any of the operations below.  The numerical rank and
 ***  the smallest pivot encountered during pivoting are computed in the
 ***  process. Factorization method used is that given if it is compatible
 ***  with the class set when the prep was done, otherwise the call fails.
 ***
 ***  If you are handed a linsolqr system and want to refactor it using the
 ***  usual method, but don't know what that method is, call like:
 ***  status = linsolqr_factor(sys,linsolqr_fmethod(sys));
 ***
 ***  Return 0 if ok, 1 if not.
 **/

extern int linsolqr_get_pivot_sets(linsolqr_system_t, unsigned *, unsigned *);
/**
 ***  status=linsolqr_get_pivot_sets(sys,org_rowpivots,org_colpivots)
 ***  linsolqr_system_t sys;
 ***  unsigned *org_rowpivots,*org_colpivots;  (see the "set" module)
 ***
 ***  Returns the set of original row numbers / original column numbers which
 ***  have been pivoted.  org_rowpivots and org_colpivots are assumed to be
 ***  sets created by (or at least for) the set module with sufficient size
 ***  before calling this function.  They must also be previously NULLed.
 ***  The system must be previously factored.
 ***  The sets input should be the result of set_create(neqn),set_create(nvar).
 ***  There is no association of rows with columns here.
 ***
 ***  Status is 0 if not factored, 1 if factored. If 0, sets will not be
 ***  changed.
 ***  This bizarre piece of functionality should be done away with as soon
 ***  as the equivalents below have been implemented.
 **/

extern mtx_sparse_t *linsolqr_unpivoted_rows(linsolqr_system_t);
extern mtx_sparse_t *linsolqr_unpivoted_cols(linsolqr_system_t);
/**
 ***  singrows = linsolqr_unpivoted_rows(sys);
 ***  singcols = linsolqr_unpivoted_cols(sys);
 ***  linsolqr_system_t sys;
 ***  mtx_sparse_t *singrows, *singcols;
 ***
 ***  Returns the set of original row numbers / original column numbers which
 ***  have NOT been pivoted and the rejected pivots in an mtx_sparse_t.
 ***  Return is NULL if sys not factored or if no unpivoted rows/cols exist.
 ***  E.g. singrows->idata[i] are the original rows that were not pivoted,
 ***       singrows->data[i] is the pivot that was rejected,
 ***       for i = 0 to singrows->len-1.
 ***  If len is 0, the data and idata pointers may be NULL.
 *** 
 ***  BUGS: only deals with ranki based square systems at the moment.
 ***  Then again, that's all we have at the moment (10/95).
 ***  Returns NULL from non-ranki systems.
 *** 
 ***  The CALLER is responsible for deallocating the mtx_sparse_t returned;
 ***  linsolqr wants nothing further to do with it.
 **/

extern mtx_sparse_t *linsolqr_pivoted_rows(linsolqr_system_t);
extern mtx_sparse_t *linsolqr_pivoted_cols(linsolqr_system_t);
/**
 ***  pivrows = linsolqr_pivoted_rows(sys);
 ***  pivcols = linsolqr_pivoted_cols(sys);
 ***  linsolqr_system_t sys;
 ***  mtx_sparse_t *pivrows, *pivcols;
 ***
 ***  Returns the set of original row numbers / original column numbers which
 ***  have been pivoted and the pivots in an mtx_sparse_t.
 ***  Return is NULL if sys not factored or if no pivoted rows/cols exist.
 ***  E.g. pivrows->idata[i] are the original rows that were pivoted,
 ***       pivrows->data[i] is the pivot,
 ***       for i = 0 to pivrows->len-1.
 ***  If len is 0, the data and idata pointers may be NULL.
 *** 
 ***  BUGS: only deals with ranki based square systems at the moment.
 ***  Then again, that's all we have at the moment (10/95).
 ***  Returns NULL from non-ranki systems.
 *** 
 ***  The CALLER is responsible for deallocating the mtx_sparse_t returned;
 ***  linsolqr wants nothing further to do with it.
 **/
     
extern int32 linsolqr_org_row_to_org_col(linsolqr_system_t, int32);
extern int32 linsolqr_org_col_to_org_row(linsolqr_system_t, int32);
/**
 ***  org_col = linsolqr_org_row_to_org_col(sys,org_row)
 ***  org_row = linsolqr_org_col_to_org_row(sys,org_col)
 ***  linsolqr_system_t sys;
 ***  int32 org_col,org_row;
 ***
 ***  Pivoted original columns and pivoted original rows can be associated
 ***  with one another via the pivot sequence.  These functions returned the
 ***  org_col/org_row associated with the given org_row/org_col.  If the given
 ***  org_row/org_col is not pivoted, a meaningless value is returned.  The
 ***  system must be previously factored. If not factored, these functions
 ***  will return a value, but linsolqr may reorder making the value wrong.
 **/

extern void linsolqr_calc_row_dependencies(linsolqr_system_t);
extern void linsolqr_calc_col_dependencies(linsolqr_system_t);
/**
 ***  linsolqr_calc_row_dependencies(sys);
 ***  linsolqr_calc_col_dependencies(sys);
 ***  linsolqr_system_t sys;
 ***
 ***  Given a factored system for which dependencies are not yet
 ***  calculated, calculates row/column dependencies. This must be
 ***  called before either linsolqr_org_row/col_dependency
 ***  or linsolqr_row/col_dependence_coefs can be called.
 ***  All rows/columns in the region specified to reorder
 ***  and not part of the final factorization have their dependencies
 ***  calculated.
 ***
 ***  The calculation method is fairly standard.
 ***  We will give the version for LU column dependency. Transpose it
 ***  for row dependency. Similar things can be done for QR.
 ***  Given a matrix region A, factor it and arrive at
 ***      A11 | A12  where A11 = L U and columns of A12 are dependent,
 ***      ---------  that is A12 = A11 . Y. (The row A2 need not exist,
 ***      A21 | eps  but if it does, A22 must be small or we could have
 ***  factored further.) Solve for Y. The Yi are the coefficients of the
 ***  linear combination of columns in A11 which sum to A12.
 ***  And, note that since the columns of A12 were treated during
 ***  factoring as if they were ultimately going to be pivoted in,
 ***  we only need to substitute on the other triangle factor, half the
 ***  work of a regular solve.
 **/

extern mtx_sparse_t *linsolqr_row_dependence_coefs(linsolqr_system_t,
                                                   int32);
extern mtx_sparse_t *linsolqr_col_dependence_coefs(linsolqr_system_t,
                                                   int32);
/**
 ***  rowcoefs = linsolqr_row_dependence_coefs(sys,orgrow);
 ***  colcoefs = linsolqr_col_dependence_coefs(sys,orgcol);
 *** 
 ***  linsolqr_system_t sys;
 ***  int32 orgrow, orgcol;
 ***  mtx_sparse_t *rowcoefs, *colcoefs;
 ***  
 ***  Given an org row/col and a factored system, returns a mtx_sparse_t
 ***  containing the org row/col indices and linear combination coefficients
 ***  contributing to the given dependent row/col. If the orgrow/orgcol
 ***  given is not dependent or dependencies have not been calculated,
 ***  return is NULL.
 ***    E.g. rowcoefs->idata[i] is the org row index of a contributing row,
 ***         rowcoefs->data[i] is the dependency coefficient,
 ***           for i = 0 to rowcoefs->len-1.
 ***  Numeric dependency calculation is a numeric process with lots of room
 ***  for interpretation of the results. Not everything that claims to  
 ***  contribute to a singularity really does so. We leave this interpre-
 ***  tation to the the caller.
 ***  
 ***  The CALLER is responsible for deallocating the mtx_sparse_t returned;
 ***  linsol wants nothing further to do with it.
 **/

extern real64 linsolqr_org_row_dependency(linsolqr_system_t,
                                                int32,int32);
extern real64 linsolqr_org_col_dependency(linsolqr_system_t,
                                                int32,int32);
/**
 ***  coef = linsolqr_org_row_dependency(sys,dep,ind)
 ***  coef = linsolqr_org_col_dependency(sys,dep,ind)
 ***  real64 coef;
 ***  linsolqr_system_t sys;
 ***  int32 dep,ind;
 ***
 ***  Any original row / column of the coefficient matrix which when submitted
 ***  to the linear solver is not pivoted, is called dependent and can be
 ***  written as a linear combination of the independent (pivoted) original
 ***  rows / columns.  These functions return the previously computed
 ***  coefficients of the linear combination.  The system must be previously
 ***  factored and the independent row / column must be a member of the
 ***  set of row / column pivots obtained by linsolqr_get_pivot_sets.
 ***  This is a slow and clunky way to retrieve dependency info.
 ***  This ought to be done away with when the above function is done.
 **/

extern int linsolqr_solve(linsolqr_system_t, real64 *);
/**
 ***  linsolqr_solve(sys,rhs)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs; 
 ***
 ***  Solves the system of linear equations (if necessary) utilizing the
 ***  specified rhs along with the previously factored matrix.  The rhs
 ***  is automatically checked if the matrix factors need to be transposed
 ***  or not (see linsolqr_add_rhs.)
 ***  Solution method will be appropriate to the factorization method used
 ***  in linsolqr_factor.
 ***  Return 0 if ok, 1 if not.
 **/

extern real64 linsolqr_var_value(linsolqr_system_t,
                                       real64 *,int32);
/**
 ***  value = linsolqr_var_value(sys,rhs,var)
 ***  real64 value;
 ***  linsolqr_system_t sys;
 ***  real64 *rhs;
 ***  int32 var;
 *** 
 ***  Returns the value of the variable in the solution vector associated
 ***  with the given rhs and either the matrix or its transpose.  The rhs
 ***  must be solved for first.  If rhs specifies transpose, then var is
 ***  expected to be an original row number, otherwise it should be an
 ***  original column number.
 ***  If sys, rhs, and var are not proper, the value returned is 0.0
 ***  and a warning is issued to stderr.
 **/

extern boolean linsolqr_copy_solution(linsolqr_system_t, real64 *,
                                      real64 *);
/**
 ***  not_ok = linsolqr_copy_solution(sys,rhs,vector)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs, *vector;
 *** 
 ***  Once a sys has been factored and rhs solved, this
 ***  fills in a copy of the solution vector associated with rhs. Caller
 ***  must provide vector and vector must be of length at least as long
 ***  as the order of the matrix that was solved. The vector entries
 ***  will be in org_col order if the rhs is normal or in org_row order
 ***  if the rhs is a transpose.
 ***  
 ***  The return value is TRUE if something is amiss, FALSE otherwise.
 ***  
 **/

extern real64 linsolqr_eqn_residual(linsolqr_system_t,
                                          real64 *,int32);
/**
 ***  residual = linsolqr_eqn_residual(sys,rhs,eqn)
 ***  real64 residual;
 ***  linsolqr_system_t sys;
 ***  real64 *rhs;
 ***  int32 eqn;
 ***
 ***  Returns the equation residual using the solution vector associated
 ***  with the given rhs and either the matrix or its transpose.
 ***
 ***                                           T
 ***     residual = A x - b   or   residual = A x - b
 ***
 ***  The rhs must be solved for first.  If rhs specifies transpose, then
 ***  eqn is expected to be an original column number, otherwise it should
 ***  be an original row number.
 ***  If the system and rhs and eqn are not properly solved, the return
 ***  value is MAXDOUBLE.
 **/

extern boolean linsolqr_calc_residual(linsolqr_system_t,
				      real64 *, real64 *);
/**
 ***  not_ok = linsolqr_calc_residual(sys,rhs,vector)
 ***  linsolqr_system_t sys;
 ***  real64 *rhs, *vector;
 ***
 ***  Returns the residuals using the solution associated
 ***  with the given rhs and either the matrix or its transpose.
 ***
 ***                                           T
 ***     residual = A x - b   or   residual = A x - b
 ***
 ***  The rhs must be solved for first. Caller
 ***  must provide vector and vector must be of length at least as long
 ***  as the order of the matrix that was solved. The vector entries
 ***  will be in org_row order if the rhs is normal or in org_col order
 ***  if the rhs is a transpose. Entries of the vector which do not 
 ***  correspond to rows/cols of factored system solved will not be modified.
 ***  
 ***  If the system and rhs are not properly solved, or other is amiss
 ***  return value is TRUE, else FALSE. 
 **/

/* miscellaneous functions for C programmers wanting to know things. */

extern size_t linsolqr_size(linsolqr_system_t);
/**
 *** size = linsolqr_size(sys)
 *** size_t size;
 *** linsolqr_system_t sys;
 ***
 ***  Returns the amount of memory in use by a system and all its
 ***  bits and pieces. User supplied RHS vectors and coefficient
 ***  matrix are NOT included in the size calculation. The user
 ***  must do accounting for those.
 **/

extern void linsolqr_free_reused_mem();
/**
 ***  linsolqr_free_reused_mem()
 ***
 ***  Deallocates any memory that linsolqr may be squirrelling away for
 ***  internal reuse. Calling this while any slv_system_t using linsolqr exists
 ***  is likely to be fatal: handle with care.
 ***  There isn't a way to query how many bytes this is.
 **/

/**
 ***  The following calls exist to facilitate debugging of the linear
 ***  solver when it is being tested on large systems. Do not use them
 ***  in routine coding. If you need access to the factor/inverse matrices
 ***  for computational purpose, you should probably consider adding that
 ***  functionality to linsol.
 **/
 
extern mtx_matrix_t linsolqr_get_factors(linsolqr_system_t);
extern mtx_matrix_t linsolqr_get_inverse(linsolqr_system_t);
/**
 ***  linsolqr_get_factors(sys)
 ***  linsolqr_get_inverse(sys)
 ***
 ***  Returns the handle of the factor (L\U, Q\R) or inverse matrix.
 ***  The handle may be NULL, and should be checked before use.
 ***  The matrix should not be tampered (other than to look at it)
 ***  with if any other mathematical operations will take place with
 ***  sys. Linsol expects to deallocate both factors and inverse; do
 ***  not do so yourself.
 ***  Note: All the factorization methods use some sort of dense vectors
 ***  for storing pivots and whatnot. As with a FORTRAN factorization,
 ***  there's not much you can do with a factorization without
 ***  also understanding in detail the factorization routine and getting
 ***  your hands on the dense vectors.
 **/

extern mtx_region_t *linsolqr_get_region(linsolqr_system_t);
/**
 ***  reg = linsolqr_get_region(sys)
 ***  mtx_region_t *reg;
 ***  linsolqr_system_t sys;
 ***
 ***  Returns a pointer to the current linsolqr region.
 ***  This is being created for use in the check numeric dependency
 ***  routine and may be removed once the new "problem manager" window
 ***  is created to take over this functionality (and others).
 **/

extern int linsolqr_setup_ngslv(linsolqr_system_t, real64 *, mtx_range_t *,
				real64 *);
extern real64 *linsolqr_get_varvalue(linsolqr_system_t,int);     
#endif