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//
// CCP4 Coordinate Library: support of coordinate-related
// functionality in protein crystallography applications.
//
// Copyright (C) Eugene Krissinel 2000-2008.
//
// This library is free software: you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License version 3, modified in accordance with the provisions
// of the license to address the requirements of UK law.
//
// You should have received a copy of the modified GNU Lesser
// General Public License along with this library. If not, copies
// may be downloaded from http://www.ccp4.ac.uk/ccp4license.php
//
// This program is distributed in the 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 Lesser General Public License for more details.
//
// =================================================================
//
// 27.06.01 <-- Date of Last Modification.
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// -----------------------------------------------------------------
//
// **** Module : linalg_ <interface>
// ~~~~~~~~~
// **** Project : MMDB ( MacroMolecular Data Base )
// ~~~~~~~~~
//
// (C) E.Krissinel 2000-2008
//
// =================================================================
//
//
#ifndef __LinAlg__
#define __LinAlg__
#ifndef __MatType__
#include "mattype_.h"
#endif
// ========================== Jacobi =============================
// Diagonalization of symmetric matrices by the method of Jacobi.
extern void Jacobi ( int N, // dimension of the matrix
rmatrix A, // matrix to diagonalize; the
// lower triangle, except the
// diagonal, will remain unchanged
rmatrix T, // eigenvectors placed as columns
rvector Eigen, // vector of eigenvalues, orderd
// by increasing
rvector Aik, // working array
int & Signal // 0 <=> Ok, ItMax <=> iteration
// limit exchausted.
);
// A5.5.2 : Perturbated Cholessky Decomposition
extern void PbCholDecomp ( int N,
rvector HDiag,
realtype MaxOff,
realtype MachEps,
rmatrix L,
realtype & MaxAdd );
// A3.2.3a : Cholessky's L - Solution of
// L*Y = B ( given B )
extern void LSolve ( int N, rmatrix L, rvector B, rvector Y );
// A3.2.3b : Cholessky's LT - Solution of
// LT*X = Y ( given Y )
extern void LTSolve ( int N, rmatrix L, rvector Y, rvector X );
// A3.2.3 : Solution of the equation L*LT*S = G
// by the Cholessky's method
extern void ChSolve ( int N, rmatrix L, rvector G, rvector S );
// ----------------------------------------------------
extern void FastInverse ( int N, rmatrix A, ivector J0,
//#D realtype & Det,
int & Signal );
//
// 13.09.90 <-- Last Modification Date
// ------------------------
//
// ================================================
//
// Fast Inversion of the matrix A
// by the method of GAUSS - JORDAN .
//
// ------------------------------------------------
//
// Input parameters are :
//
// N - dimension of the matrix
// A - the matrix [1..N][1..N] to be inverted.
// ------------------------------------------------
//
// J0 - integer vector [1..N] for temporal storage
//
// ------------------------------------------------
//
// Output parameters are :
//
// A - the inverted matrix
// Signal - the error key :
// = 0 <=> O'K
// else
// degeneration was found, and
// the rang of matrix is Signal-1.
//
// Variable Det may return the determinant
// of matrix A. To obtain it, remove all comments
// of form //#D.
//
// ================================================
// ----------------------------------------------------
void SVD ( int NA, int M, int N,
rmatrix A, rmatrix U, rmatrix V,
rvector W, rvector RV1,
Boolean MatU, Boolean MatV,
int & RetCode );
//
// 13.12.01 <-- Last Modification Date
// ------------------------
//
// ================================================
//
// The Singular Value Decomposition
// of the matrix A by the algorithm from
// G.Forsait, M.Malkolm, K.Mouler. Numerical
// methods of mathematical calculations //
// M., Mir, 1980.
//
// Matrix A is represented as
//
// A = U * W * VT
//
// ------------------------------------------------
//
// All dimensions are indexed from 1 on.
//
// ------------------------------------------------
//
// Input parameters:
//
// NA - number of lines in A. NA may be
// equal to M or N only. If NA=M
// then usual SVD will be made. If MA=N
// then matrix A is transposed before
// the decomposition, and the meaning of
// output parameters U and V is
// swapped (U accepts VT and VT accepts U).
// In other words, matrix A has physical
// dimension of M x N , same as U and V;
// however the logical dimension of it
// remains that of N x M .
// M - number of lines in U
// N - number of columns in U,V and length
// of W,RV1 . Always provide M >= N !
// A - matrix [1..M][1..N] or [1..N][1..M]
// to be decomposed. The matrix does not
// change, and it may coincide with U or
// V, if NA=M (in which case A does change)
// MatU - compute U , if set True
// MatV - compute V , if set True
// RV1 - temporary array [1..N].
// U - should be always supplied as an array of
// [1..M][1..N], M>=N .
// V - should be suuplied as an array of
// [1..N][1..N] if MatV is True .
//
// ------------------------------------------------
//
// Output parameters are :
//
// W - N non-ordered singular values,
// if RetCode=0. If RetCode<>0, the
// RetCode+1 ... N -th values are still
// valid
// U - matrix of right singular vectors
// (arranged in columns), corresponding
// to the singular values in W, if
// RetCode=0 and MatU is True. If MatU
// is False, U is still used as a
// temporary array. If RetCode<>0 then
// the RetCode+1 ... N -th vectors
// are valid
// V - matrix of left singular vectors
// (arranged in columns), corresponding
// to the singular values in W, if
// RetCode=0 and MatV is True. If MatV
// is False, V is not used and may be set
// to NULL. If RetCode<>0 then the
// RetCode+1 ... N -th vectors are valid
// RetCode - the error key :
// = 0 <=> O'K
// else
// = k, if the k-th singular value
// was not computed after 30 iterations.
//
// ------------------------------------------------
//
// Key Variables are :
//
// ItnLimit - the limit for iterations
//
// This routine does not use any machine-dependent
// constants.
//
// ================================================
//
//
void OrderSVD ( int M, int N, rmatrix U, rmatrix V,
rvector W, Boolean MatU, Boolean MatV );
#endif
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