/** @file check_matrices.cpp
 *
 *  Here we test manipulations on GiNaC's symbolic matrices.  They are a
 *  well-tried resource for cross-checking the underlying symbolic
 *  manipulations. */

/*
 *  GiNaC Copyright (C) 1999-2003 Johannes Gutenberg University Mainz, Germany
 *
 *  This program 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.
 *
 *  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 General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program; if not, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */

#include "checks.h"

/* determinants of some sparse symbolic matrices with coefficients in
 * an integral domain. */
static unsigned integdom_matrix_determinants()
{
	unsigned result = 0;
	symbol a("a");
	
	for (unsigned size=3; size<22; ++size) {
		matrix A(size,size);
		// populate one element in each row:
		for (unsigned r=0; r<size-1; ++r)
			A.set(r,unsigned(rand()%size),dense_univariate_poly(a,5));
		// set the last row to a linear combination of two other lines
		// to guarantee that the determinant is zero:
		for (unsigned c=0; c<size; ++c)
			A.set(size-1,c,A(0,c)-A(size-2,c));
		if (!A.determinant().is_zero()) {
			clog << "Determinant of " << size << "x" << size << " matrix "
			     << endl << A << endl
			     << "was not found to vanish!" << endl;
			++result;
		}
	}
	
	return result;
}

/* determinants of some symbolic matrices with multivariate rational function
 * coefficients. */
static unsigned rational_matrix_determinants()
{
	unsigned result = 0;
	symbol a("a"), b("b"), c("c");
	
	for (unsigned size=3; size<9; ++size) {
		matrix A(size,size);
		for (unsigned r=0; r<size-1; ++r) {
			// populate one or two elements in each row:
			for (unsigned ec=0; ec<2; ++ec) {
				ex numer = sparse_tree(a, b, c, 1+rand()%4, false, false, false);
				ex denom;
				do {
					denom = sparse_tree(a, b, c, rand()%2, false, false, false);
				} while (denom.is_zero());
				A.set(r,unsigned(rand()%size),numer/denom);
			}
		}
		// set the last row to a linear combination of two other lines
		// to guarantee that the determinant is zero:
		for (unsigned co=0; co<size; ++co)
			A.set(size-1,co,A(0,co)-A(size-2,co));
		if (!A.determinant().is_zero()) {
			clog << "Determinant of " << size << "x" << size << " matrix "
			     << endl << A << endl
			     << "was not found to vanish!" << endl;
			++result;
		}
	}
	
	return result;
}

/* Some quite funny determinants with functions and stuff like that inside. */
static unsigned funny_matrix_determinants()
{
	unsigned result = 0;
	symbol a("a"), b("b"), c("c");
	
	for (unsigned size=3; size<8; ++size) {
		matrix A(size,size);
		for (unsigned co=0; co<size-1; ++co) {
			// populate one or two elements in each row:
			for (unsigned ec=0; ec<2; ++ec) {
				ex numer = sparse_tree(a, b, c, 1+rand()%3, true, true, false);
				ex denom;
				do {
					denom = sparse_tree(a, b, c, rand()%2, false, true, false);
				} while (denom.is_zero());
				A.set(unsigned(rand()%size),co,numer/denom);
			}
		}
		// set the last column to a linear combination of two other columns
		// to guarantee that the determinant is zero:
		for (unsigned ro=0; ro<size; ++ro)
			A.set(ro,size-1,A(ro,0)-A(ro,size-2));
		if (!A.determinant().is_zero()) {
			clog << "Determinant of " << size << "x" << size << " matrix "
			     << endl << A << endl
			     << "was not found to vanish!" << endl;
			++result;
		}
	}
	
	return result;
}

/* compare results from different determinant algorithms.*/
static unsigned compare_matrix_determinants()
{
	unsigned result = 0;
	symbol a("a");
	
	for (unsigned size=2; size<8; ++size) {
		matrix A(size,size);
		for (unsigned co=0; co<size; ++co) {
			for (unsigned ro=0; ro<size; ++ro) {
				// populate some elements
				ex elem = 0;
				if (rand()%(size/2) == 0)
					elem = sparse_tree(a, a, a, rand()%3, false, true, false);
				A.set(ro,co,elem);
			}
		}
		ex det_gauss = A.determinant(determinant_algo::gauss);
		ex det_laplace = A.determinant(determinant_algo::laplace);
		ex det_divfree = A.determinant(determinant_algo::divfree);
		ex det_bareiss = A.determinant(determinant_algo::bareiss);
		if ((det_gauss-det_laplace).normal() != 0 ||
			(det_bareiss-det_laplace).normal() != 0 ||
			(det_divfree-det_laplace).normal() != 0) {
			clog << "Determinant of " << size << "x" << size << " matrix "
			     << endl << A << endl
			     << "is inconsistent between different algorithms:" << endl
			     << "Gauss elimination:   " << det_gauss << endl
			     << "Minor elimination:   " << det_laplace << endl
			     << "Division-free elim.: " << det_divfree << endl
			     << "Fraction-free elim.: " << det_bareiss << endl;
			++result;
		}
	}
	
	return result;
}

static unsigned symbolic_matrix_inverse()
{
	unsigned result = 0;
	symbol a("a"), b("b"), c("c");
	
	for (unsigned size=2; size<6; ++size) {
		matrix A(size,size);
		do {
			for (unsigned co=0; co<size; ++co) {
				for (unsigned ro=0; ro<size; ++ro) {
					// populate some elements
					ex elem = 0;
					if (rand()%(size/2) == 0)
						elem = sparse_tree(a, b, c, rand()%2, false, true, false);
					A.set(ro,co,elem);
				}
			}
		} while (A.determinant() == 0);
		matrix B = A.inverse();
		matrix C = A.mul(B);
		bool ok = true;
		for (unsigned ro=0; ro<size; ++ro)
			for (unsigned co=0; co<size; ++co)
				if (C(ro,co).normal() != (ro==co?1:0))
					ok = false;
		if (!ok) {
			clog << "Inverse of " << size << "x" << size << " matrix "
			     << endl << A << endl
			     << "erroneously returned: "
			     << endl << B << endl;
			++result;
		}
	}
	
	return result;
}

unsigned check_matrices()
{
	unsigned result = 0;
	
	cout << "checking symbolic matrix manipulations" << flush;
	clog << "---------symbolic matrix manipulations:" << endl;
	
	result += integdom_matrix_determinants();  cout << '.' << flush;
	result += rational_matrix_determinants();  cout << '.' << flush;
	result += funny_matrix_determinants();  cout << '.' << flush;
	result += compare_matrix_determinants();  cout << '.' << flush;
	result += symbolic_matrix_inverse();  cout << '.' << flush;
	
	if (!result) {
		cout << " passed " << endl;
		clog << "(no output)" << endl;
	} else {
		cout << " failed " << endl;
	}
	
	return result;
}