This source file includes following definitions.
- TEST
- TEST
- TEST
- TEST
- TEST
- TEST
- TEST
- TEST
#include <cmath>
#include <limits>
#include "base/basictypes.h"
#include "testing/gtest/include/gtest/gtest.h"
#include "ui/gfx/geometry/matrix3_f.h"
namespace gfx {
namespace {
TEST(Matrix3fTest, Constructors) {
Matrix3F zeros = Matrix3F::Zeros();
Matrix3F ones = Matrix3F::Ones();
Matrix3F identity = Matrix3F::Identity();
Matrix3F product_ones = Matrix3F::FromOuterProduct(
Vector3dF(1.0f, 1.0f, 1.0f), Vector3dF(1.0f, 1.0f, 1.0f));
Matrix3F product_zeros = Matrix3F::FromOuterProduct(
Vector3dF(1.0f, 1.0f, 1.0f), Vector3dF(0.0f, 0.0f, 0.0f));
EXPECT_EQ(ones, product_ones);
EXPECT_EQ(zeros, product_zeros);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 3; ++j)
EXPECT_EQ(i == j ? 1.0f : 0.0f, identity.get(i, j));
}
}
TEST(Matrix3fTest, DataAccess) {
Matrix3F matrix = Matrix3F::Ones();
Matrix3F identity = Matrix3F::Identity();
EXPECT_EQ(Vector3dF(0.0f, 1.0f, 0.0f), identity.get_column(1));
matrix.set(0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f);
EXPECT_EQ(Vector3dF(2.0f, 5.0f, 8.0f), matrix.get_column(2));
matrix.set_column(0, Vector3dF(0.1f, 0.2f, 0.3f));
EXPECT_EQ(Vector3dF(0.1f, 0.2f, 0.3f), matrix.get_column(0));
EXPECT_EQ(0.1f, matrix.get(0, 0));
EXPECT_EQ(5.0f, matrix.get(1, 2));
}
TEST(Matrix3fTest, Determinant) {
EXPECT_EQ(1.0f, Matrix3F::Identity().Determinant());
EXPECT_EQ(0.0f, Matrix3F::Zeros().Determinant());
EXPECT_EQ(0.0f, Matrix3F::Ones().Determinant());
Matrix3F matrix = Matrix3F::Zeros();
matrix.set(0, 5, 6, 8, 7, 0, 1, 9, 0);
EXPECT_EQ(390.0f, matrix.Determinant());
matrix.set(2, 0, 3 * matrix.get(0, 0));
matrix.set(2, 1, 3 * matrix.get(0, 1));
matrix.set(2, 2, 3 * matrix.get(0, 2));
EXPECT_EQ(0, matrix.Determinant());
matrix.set(0.57f, 0.205f, 0.942f,
0.314f, 0.845f, 0.826f,
0.131f, 0.025f, 0.962f);
EXPECT_NEAR(0.3149f, matrix.Determinant(), 0.0001f);
}
TEST(Matrix3fTest, Inverse) {
Matrix3F identity = Matrix3F::Identity();
Matrix3F inv_identity = identity.Inverse();
EXPECT_EQ(identity, inv_identity);
Matrix3F singular = Matrix3F::Zeros();
singular.set(1.0f, 3.0f, 4.0f,
2.0f, 11.0f, 5.0f,
0.5f, 1.5f, 2.0f);
EXPECT_EQ(0, singular.Determinant());
EXPECT_EQ(Matrix3F::Zeros(), singular.Inverse());
Matrix3F regular = Matrix3F::Zeros();
regular.set(0.57f, 0.205f, 0.942f,
0.314f, 0.845f, 0.826f,
0.131f, 0.025f, 0.962f);
Matrix3F inv_regular = regular.Inverse();
regular.set(2.51540616f, -0.55138018f, -1.98968043f,
-0.61552266f, 1.34920184f, -0.55573636f,
-0.32653861f, 0.04002158f, 1.32488726f);
EXPECT_TRUE(regular.IsNear(inv_regular, 0.00001f));
}
TEST(Matrix3fTest, EigenvectorsIdentity) {
Matrix3F identity = Matrix3F::Identity();
Vector3dF eigenvals = identity.SolveEigenproblem(NULL);
EXPECT_EQ(Vector3dF(1.0f, 1.0f, 1.0f), eigenvals);
}
TEST(Matrix3fTest, EigenvectorsDiagonal) {
Matrix3F matrix = Matrix3F::Zeros();
matrix.set(0, 0, 1.0f);
matrix.set(1, 1, -2.5f);
matrix.set(2, 2, 3.14f);
Matrix3F eigenvectors = Matrix3F::Zeros();
Vector3dF eigenvals = matrix.SolveEigenproblem(&eigenvectors);
EXPECT_EQ(Vector3dF(3.14f, 1.0f, -2.5f), eigenvals);
EXPECT_EQ(Vector3dF(0.0f, 0.0f, 1.0f), eigenvectors.get_column(0));
EXPECT_EQ(Vector3dF(1.0f, 0.0f, 0.0f), eigenvectors.get_column(1));
EXPECT_EQ(Vector3dF(0.0f, 1.0f, 0.0f), eigenvectors.get_column(2));
}
TEST(Matrix3fTest, EigenvectorsNiceNotPositive) {
Matrix3F matrix = Matrix3F::Zeros();
matrix.set(3, 2, 4, 2, 0, 2, 4, 2, 3);
Matrix3F eigenvectors = Matrix3F::Zeros();
Vector3dF eigenvals = matrix.SolveEigenproblem(&eigenvectors);
EXPECT_EQ(Vector3dF(8.0f, -1.0f, -1.0f), eigenvals);
Vector3dF expected_principal(0.66666667f, 0.33333333f, 0.66666667f);
EXPECT_NEAR(0.0f,
(expected_principal - eigenvectors.get_column(0)).Length(),
0.000001f);
}
TEST(Matrix3fTest, EigenvectorsPositiveDefinite) {
Matrix3F matrix = Matrix3F::Zeros();
Matrix3F eigenvectors = Matrix3F::Zeros();
Matrix3F expected_eigenvectors = Matrix3F::Zeros();
matrix.set(1, -1, 2, -1, 4, 5, 2, 5, 0);
Vector3dF eigenvals = matrix.SolveEigenproblem(&eigenvectors);
Vector3dF expected_eigv(7.3996266f, 1.91197255f, -4.31159915f);
expected_eigv -= eigenvals;
EXPECT_NEAR(0, expected_eigv.LengthSquared(), 0.00001f);
expected_eigenvectors.set(0.04926317f, -0.92135662f, -0.38558414f,
0.82134249f, 0.25703273f, -0.50924521f,
0.56830419f, -0.2916096f, 0.76941158f);
EXPECT_TRUE(expected_eigenvectors.IsNear(eigenvectors, 0.00001f));
}
}
}