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-rw-r--r--src/libcola/conjugate_gradient.cpp137
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diff --git a/src/libcola/conjugate_gradient.cpp b/src/libcola/conjugate_gradient.cpp
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--- a/src/libcola/conjugate_gradient.cpp
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-/*
- * vim: ts=4 sw=4 et tw=0 wm=0
- *
- * libcola - A library providing force-directed network layout using the
- * stress-majorization method subject to separation constraints.
- *
- * Copyright (C) 2006 Nathan Hurst <njh@njhurst.com>
- * Copyright (C) 2006-2008 Monash University
- *
- * This library is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- * See the file LICENSE.LGPL distributed with the library.
- *
- * This library 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.
- *
- * Author(s): Nathan Hurst
- * Tim Dwyer
- *
-*/
-
-
-#include <cmath>
-#include <cstdlib>
-#include <cassert>
-#include <valarray>
-
-#include "libvpsc/assertions.h"
-#include "libcola/commondefs.h"
-#include "libcola/conjugate_gradient.h"
-
-/* lifted wholely from wikipedia. Well, apart from the bug in the wikipedia version. */
-
-using std::valarray;
-
-static void
-matrix_times_vector(valarray<double> const &matrix, /* m * n */
- valarray<double> const &vec, /* n */
- valarray<double> &result) /* m */
-{
- unsigned n = vec.size();
- unsigned m = result.size();
- COLA_ASSERT(m*n == matrix.size());
-# if defined(_MSC_VER)
- // magmy: The following lines show how operator[] is defined for valarray under MSVC
- // _Ty valarray<_Ty>::operator[](size_t _Off) const;
- // _Ty &valarray<_Ty>::operator[](size_t _Off);
- // As a consequence, it is not possible to take the address of a constant valarray[n].
- // This looks like a bug in the Microsoft's <valarray> file.
- // Below is a workaround
- double const *mp = &const_cast<valarray<double> &>(matrix)[0];
-# else
- const double* mp = &matrix[0];
-# endif
- for (unsigned i = 0; i < m; i++) {
- double res = 0;
- for (unsigned j = 0; j < n; j++)
- res += *mp++ * vec[j];
- result[i] = res;
- }
-}
-
-/*
-static double Linfty(valarray<double> const &vec) {
- return std::max(vec.max(), -vec.min());
-}
-*/
-
-double
-inner(valarray<double> const &x,
- valarray<double> const &y) {
- double total = 0;
- for(unsigned i = 0; i < x.size(); i++)
- total += x[i]*y[i];
- return total;// (x*y).sum(); <- this is more concise, but ineff
-}
-
-double compute_cost(valarray<double> const &A,
- valarray<double> const &b,
- valarray<double> const &x,
- const unsigned n) {
- // computes cost = 2 b x - x A x
- double cost = 2. * inner(b,x);
- valarray<double> Ax(n);
- for (unsigned i=0; i<n; i++) {
- Ax[i] = 0;
- for (unsigned j=0; j<n; j++) {
- Ax[i] += A[i*n+j]*x[j];
- }
- }
- return cost - inner(x,Ax);
-}
-void
-conjugate_gradient(valarray<double> const &A,
- valarray<double> &x,
- valarray<double> const &b,
- unsigned const n, double const tol,
- unsigned const max_iterations) {
- //printf("Conjugate Gradient...\n");
- valarray<double> Ap(n), p(n), r(n);
- matrix_times_vector(A,x,Ap);
- r=b-Ap;
- double r_r = inner(r,r);
- unsigned k = 0;
- double tol_squared = tol*tol;
-#ifdef EXAMINE_COST
- double previousCost=compute_cost(A,b,x,n),cost;
-#endif
- while(k < max_iterations && r_r > tol_squared) {
- k++;
- double r_r_new = r_r;
- if(k == 1)
- p = r;
- else {
- r_r_new = inner(r,r);
- if(r_r_new<tol_squared) break;
- p = r + (r_r_new/r_r)*p;
- }
- matrix_times_vector(A, p, Ap);
- double alpha_k = r_r_new / inner(p, Ap);
- x += alpha_k*p;
-#ifdef EXAMINE_COST
- cost=compute_cost(A,b,x,n);
- printf(" CG[%d] %.15f %.15f\n",k,previousCost,cost);
- previousCost=cost;
-#endif
- r -= alpha_k*Ap;
- r_r = r_r_new;
- }
- //printf(" CG finished after %d iterations\n",k);
- //printf("njh: %d iters, Linfty = %g L2 = %g\n", k,
- //std::max(-r.min(), r.max()), sqrt(r_r));
- // x is solution
-}