opm-simulators/tests/test_autodiffhelpers.cpp

227 lines
6.5 KiB
C++

/*
Copyright 2015 SINTEF ICT, Applied Mathematics.
This file is part of the Open Porous Media project (OPM).
OPM 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 3 of the License, or
(at your option) any later version.
OPM 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 OPM. If not, see <http://www.gnu.org/licenses/>.
*/
#include <config.h>
#define BOOST_TEST_MODULE AutoDiffHelpersTest
#include <opm/autodiff/AutoDiffHelpers.hpp>
#include <boost/test/unit_test.hpp>
using namespace Opm;
namespace {
template <typename Scalar>
bool
operator ==(const Eigen::SparseMatrix<Scalar>& A,
const Eigen::SparseMatrix<Scalar>& B)
{
// Two SparseMatrices are equal if
// 0) They have the same ordering (enforced by equal types)
// 1) They have the same outer and inner dimensions
// 2) They have the same number of non-zero elements
// 3) They have the same sparsity structure
// 4) The non-zero elements are equal
// 1) Outer and inner dimensions
bool eq = (A.outerSize() == B.outerSize());
eq = eq && (A.innerSize() == B.innerSize());
// 2) Equal number of non-zero elements
eq = eq && (A.nonZeros() == B.nonZeros());
for (typename Eigen::SparseMatrix<Scalar>::Index
k0 = 0, kend = A.outerSize(); eq && (k0 < kend); ++k0) {
for (typename Eigen::SparseMatrix<Scalar>::InnerIterator
iA(A, k0), iB(B, k0); eq && (iA && iB); ++iA, ++iB) {
// 3) Sparsity structure
eq = (iA.row() == iB.row()) && (iA.col() == iB.col());
// 4) Equal non-zero elements
eq = eq && (iA.value() == iB.value());
}
}
return eq;
// Note: Investigate implementing this operator as
// return A.cwiseNotEqual(B).count() == 0;
}
}
BOOST_AUTO_TEST_CASE(vertcatCollapseJacsTest)
{
typedef AutoDiffBlock<double> ADB;
typedef ADB::V V;
typedef ADB::M M;
typedef Eigen::SparseMatrix<double> S;
// We will build a system with the block structure
// { 2, 0, 1 } (total of three columns) and { 1, 2, 1 } (row) sizes.
//
// value jacobians
// 10 1 2 | 3
// ----------------------------------
// 11 0 0 | 0 (empty jacobian)
// 12 0 0 | 0
// ----------------------------------
// 13 4 5 | 6
std::vector<ADB> v;
{
// First block.
V val(1);
val << 10;
std::vector<M> jacs;
jacs.reserve(3);
S s1(1, 2);
S s2(1, 0);
S s3(1, 1);
s1.insert(0, 0) = 1.0;
s1.insert(0, 1) = 2.0;
s3.insert(0, 0) = 3.0;
jacs.push_back(M(s1));
jacs.push_back(M(s2));
jacs.push_back(M(s3));
v.push_back(ADB::function(val, jacs));
}
{
// Second block (with empty jacobian).
V val(2);
val << 11, 12;
v.push_back(ADB::constant(val));
}
{
// Third block.
V val(1);
val << 13;
std::vector<M> jacs(0);
jacs.reserve(3);
S s1(1, 2);
S s2(1, 0);
S s3(1, 1);
s1.insert(0, 0) = 4.0;
s1.insert(0, 1) = 5.0;
s3.insert(0, 0) = 6.0;
jacs.push_back(M(s1));
jacs.push_back(M(s2));
jacs.push_back(M(s3));
v.push_back(ADB::function(val, jacs));
}
std::vector<int> expected_block_pattern{ 2, 0, 1 };
BOOST_CHECK(v[0].blockPattern() == expected_block_pattern);
// Call vertcatCollapseJacs().
const ADB x = vertcatCollapseJacs(v);
// Build expected results.
V expected_val(4);
expected_val << 10, 11, 12, 13;
S expected_jac_s(4, 3);
expected_jac_s.insert(0, 0) = 1.0;
expected_jac_s.insert(0, 1) = 2.0;
expected_jac_s.insert(0, 2) = 3.0;
expected_jac_s.insert(3, 0) = 4.0;
expected_jac_s.insert(3, 1) = 5.0;
expected_jac_s.insert(3, 2) = 6.0;
M expected_jac(expected_jac_s);
// Compare.
BOOST_CHECK((x.value() == expected_val).all());
S derivative;
x.derivative()[0].toSparse(derivative);
BOOST_CHECK(derivative == expected_jac_s);
}
BOOST_AUTO_TEST_CASE(supersetTest)
{
typedef AutoDiffBlock<double> ADB;
{
ADB subset = ADB::constant(ADB::V::Ones(3));
const int full_size = 32;
std::vector<int> indices = {1, 3, 5};
AutoDiffBlock<double> n_vals = superset(subset, indices, full_size);
BOOST_CHECK_EQUAL(n_vals.size(), full_size);
for (int i=0; i<n_vals.size(); ++i) {
if (find(indices.begin(), indices.end(), i) != indices.end()) {
BOOST_CHECK_EQUAL(n_vals.value()[i], 1);
}
else {
BOOST_CHECK_EQUAL(n_vals.value()[i], 0);
}
}
}
}
BOOST_AUTO_TEST_CASE(supersetEmptyTest)
{
typedef AutoDiffBlock<double> ADB;
{
ADB subset = ADB::constant(ADB::V::Ones(0));
const int full_size = 32;
std::vector<int> indices = {};
AutoDiffBlock<double> n_vals = superset(subset, indices, full_size);
BOOST_CHECK_EQUAL(n_vals.size(), full_size);
for (int i=0; i<n_vals.size(); ++i) {
BOOST_CHECK_EQUAL(n_vals.value()[i], 0);
}
}
}
BOOST_AUTO_TEST_CASE(subsetTest)
{
typedef AutoDiffBlock<double> ADB;
{
ADB superset = ADB::constant(ADB::V::Ones(32));
std::vector<int> indices = {1, 3, 5};
AutoDiffBlock<double> n_vals = subset(superset, indices);
BOOST_CHECK_EQUAL(n_vals.size(), 3);
for (int i=0; i<n_vals.size(); ++i) {
if (find(indices.begin(), indices.end(), i) != indices.end()) {
BOOST_CHECK_EQUAL(n_vals.value()[i], 1);
}
}
}
}
BOOST_AUTO_TEST_CASE(subsetEmptyTest)
{
typedef AutoDiffBlock<double> ADB;
{
ADB superset = ADB::constant(ADB::V::Ones(32));
std::vector<int> indices = {};
AutoDiffBlock<double> n_vals = subset(superset, indices);
BOOST_CHECK_EQUAL(n_vals.size(), 0);
}
}