cantera/test/general/test_matrices.cpp

277 lines
6.4 KiB
C++

#include "gtest/gtest.h"
#include "cantera/numerics/BandMatrix.h"
#include "cantera/numerics/DenseMatrix.h"
using namespace Cantera;
class BandMatrixTest : public testing::Test
{
public:
BandMatrixTest()
: x{1,2,3,4,5,6}
, b1{-8, -8, 6, 40, 149, 81}
, b2{1, 8, 30, 72, 140, 65}
, v1{3, 13, 28, 55, 100, 92}
, v2{0, 5, 16, 39, 115, 116}
{
A1.resize(6, 1, 2); // one lower, two upper
A2.resize(6, 2, 1); // two lower, one upper
// main diagonal
for (int i = 0; i < 6; i++) {
A1(i, i) = i + 1;
A2(i, i) = i + 1;
}
// first subdiagonal and superdiagonal
for (int i = 0; i < 5; i++) {
A1(i+1, i) = 2 * i + 1;
A1(i, i+1) = i * i;
A2(i+1, i) = 2 * i + 1;
A2(i, i+1) = i * i;
}
// second subdiagonal and superdiagonal
for (int i = 0; i < 4; i++) {
A1(i, i+2) = - i - 3;
A2(i+2, i) = - i - 1;
}
}
BandMatrix A1, A2;
vector_fp x;
vector_fp b1, b2;
vector_fp v1, v2;
};
TEST_F(BandMatrixTest, matrix_times_vector)
{
vector_fp c(6, 0.0);
A1.mult(x.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_DOUBLE_EQ(b1[i], c[i]);
}
A2.mult(x.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_DOUBLE_EQ(b2[i], c[i]);
}
}
TEST_F(BandMatrixTest, vector_times_matrix)
{
vector_fp c(6, 0.0);
A1.leftMult(x.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_DOUBLE_EQ(v1[i], c[i]);
}
A2.leftMult(x.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_DOUBLE_EQ(v2[i], c[i]);
}
}
TEST_F(BandMatrixTest, solve_linear_system)
{
vector_fp c(6, 0.0);
A1.solve(b1.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_NEAR(x[i], c[i], 1e-10);
}
A2.solve(b2.data(), c.data());
for (size_t i = 0; i < 6; i++) {
EXPECT_NEAR(x[i], c[i], 1e-10);
}
}
TEST_F(BandMatrixTest, oneNorm) {
EXPECT_DOUBLE_EQ(28, A1.oneNorm());
EXPECT_DOUBLE_EQ(23, A2.oneNorm());
}
TEST_F(BandMatrixTest, checkRowsColumns) {
double s;
size_t i = A1.checkRows(s);
EXPECT_EQ((size_t) 0, i);
EXPECT_DOUBLE_EQ(3, s);
i = A2.checkRows(s);
EXPECT_EQ((size_t) 0, i);
EXPECT_DOUBLE_EQ(1, s);
i = A1.checkColumns(s);
EXPECT_EQ((size_t) 0, i);
EXPECT_DOUBLE_EQ(1, s);
i = A2.checkColumns(s);
EXPECT_EQ((size_t) 0, i);
EXPECT_DOUBLE_EQ(1, s);
}
class DenseMatrixTest : public testing::Test
{
public:
DenseMatrixTest()
: x4{1,2,3,4}
, x3{3,2,1}
, b1{14, 32, 66, -34}
, b2{-6, 4, 26, 2}
, b3{14, 32, 66}
{
A1.resize(4, 4); // square
A2.resize(4, 3); // more rows
A3.resize(3, 4); // more columns
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 3; j++) {
A1(i,j) = A2(i,j) = A3(i,j) = i*i + 2*j*j + i*j - 3;
}
A1(3,i) = A2(3,i) = pow(-1, i);
A1(i,3) = A3(i,3) = pow(2, i);
}
A1(3,3) = -9;
}
double special_sum(DenseMatrix M) {
double sum = 0;
for (size_t i = 0; i < M.nRows(); i++) {
for (size_t j = 0; j < M.nColumns(); j++) {
sum += M(i,j) * (i+2*j+1);
}
}
return sum;
}
DenseMatrix A1, A2, A3;
vector_fp x4, x3;
vector_fp b1, b2, b3;
};
TEST_F(DenseMatrixTest, matrix_times_vector)
{
vector_fp c(4, 0.0);
A1.mult(x4.data(), c.data());
for (size_t i = 0; i < 4; i++) {
EXPECT_DOUBLE_EQ(b1[i], c[i]);
}
A2.mult(x3.data(), c.data());
for (size_t i = 0; i < 4; i++) {
EXPECT_DOUBLE_EQ(b2[i], c[i]);
}
A3.mult(x4.data(), c.data());
for (size_t i = 0; i < 3; i++) {
EXPECT_DOUBLE_EQ(b3[i], c[i]);
}
}
TEST_F(DenseMatrixTest, matrix_times_matrix)
{
DenseMatrix c(4, 3);
A1.mult(A2, c);
EXPECT_DOUBLE_EQ(3033, special_sum(c));
c.resize(3, 4);
A3.mult(A1, c);
EXPECT_DOUBLE_EQ(3386, special_sum(c));
c.resize(3, 3);
A3.mult(A2, c);
EXPECT_DOUBLE_EQ(2989, special_sum(c));
c.resize(4, 4);
A2.mult(A3, c);
EXPECT_DOUBLE_EQ(4014, special_sum(c));
}
TEST_F(DenseMatrixTest, solve_single_rhs)
{
vector_fp c(b1);
solve(A1, c.data());
for (size_t i = 0; i < 4; i++) {
EXPECT_NEAR(x4[i], c[i], 1e-12);
}
}
TEST_F(DenseMatrixTest, solve_multi_rhs)
{
DenseMatrix B(A1.nColumns(), 5);
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 5; j++) {
B(i,j) = b1[i] * (j+1);
}
}
solve(A1, B);
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 5; j++) {
EXPECT_NEAR(x4[i] * (j+1), B(i,j), 1e-12);
}
}
}
TEST_F(DenseMatrixTest, increment)
{
vector_fp c(b1.size(), 3.0);
increment(A1, x4.data(), c.data());
for (size_t i = 0; i < 4; i++) {
EXPECT_DOUBLE_EQ(3.0 + b1[i], c[i]);
}
c.assign(b2.size(), 3.0);
increment(A2, x3.data(), c.data());
for (size_t i = 0; i < 4; i++) {
EXPECT_DOUBLE_EQ(3.0 + b2[i], c[i]);
}
c.assign(b3.size(), 3.0);
increment(A3, x4.data(), c.data());
for (size_t i = 0; i < 3; i++) {
EXPECT_DOUBLE_EQ(3.0 + b3[i], c[i]);
}
}
TEST_F(DenseMatrixTest, invert_full)
{
DenseMatrix B(A1);
DenseMatrix C(A1.nRows(), A1.nColumns());
invert(B);
A1.mult(B, C);
for (size_t i = 0; i < 4; i++) {
for (size_t j = 0; j < 4; j++) {
if (i == j) {
EXPECT_NEAR(1.0, C(i,j), 1e-14);
} else {
EXPECT_NEAR(0.0, C(i,j), 1e-14);
}
}
}
}
TEST_F(DenseMatrixTest, invert_partial)
{
DenseMatrix B(A1);
DenseMatrix Aref(A1);
size_t N = 3;
invert(B, N);
DenseMatrix As(3, 3);
DenseMatrix Bs(3, 3);
DenseMatrix C(3, 3);
for (size_t i = 0; i < 3; i++) {
for (size_t j = 0; j < 3; j++) {
As(i,j) = A1(i,j);
Bs(i,j) = B(i,j);
}
}
As.mult(Bs, C);
for (size_t i = 0; i < 3; i++) {
for (size_t j = 0; j < 3; j++) {
if (i == j) {
EXPECT_NEAR(1.0, C(i,j), 1e-14);
} else {
EXPECT_NEAR(0.0, C(i,j), 1e-14);
}
}
}
for (size_t i = 0; i < 4; i++) {
EXPECT_DOUBLE_EQ(Aref(3,i), A1(3,i));
EXPECT_DOUBLE_EQ(Aref(i,3), A1(i,3));
}
}