本文整理汇总了C++中GaussianFactorGraph::jacobian方法的典型用法代码示例。如果您正苦于以下问题：C++ GaussianFactorGraph::jacobian方法的具体用法？C++ GaussianFactorGraph::jacobian怎么用？C++ GaussianFactorGraph::jacobian使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类GaussianFactorGraph的用法示例。
在下文中一共展示了GaussianFactorGraph::jacobian方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: Ab
/* ************************************************************************* */
TEST(GaussianFactorGraph, matrices) {
// Create factor graph:
// x1 x2 x3 x4 x5 b
// 1 2 3 0 0 4
// 5 6 7 0 0 8
// 9 10 0 11 12 13
// 0 0 0 14 15 16
Matrix A00 = (Matrix(2, 3) << 1, 2, 3, 5, 6, 7).finished();
Matrix A10 = (Matrix(2, 3) << 9, 10, 0, 0, 0, 0).finished();
Matrix A11 = (Matrix(2, 2) << 11, 12, 14, 15).finished();
GaussianFactorGraph gfg;
SharedDiagonal model = noiseModel::Unit::Create(2);
gfg.add(0, A00, Vector2(4., 8.), model);
gfg.add(0, A10, 1, A11, Vector2(13., 16.), model);
Matrix Ab(4, 6);
Ab << 1, 2, 3, 0, 0, 4, 5, 6, 7, 0, 0, 8, 9, 10, 0, 11, 12, 13, 0, 0, 0, 14, 15, 16;
// augmented versions
EXPECT(assert_equal(Ab, gfg.augmentedJacobian()));
EXPECT(assert_equal(Ab.transpose() * Ab, gfg.augmentedHessian()));
// jacobian
Matrix A = Ab.leftCols(Ab.cols() - 1);
Vector b = Ab.col(Ab.cols() - 1);
Matrix actualA;
Vector actualb;
boost::tie(actualA, actualb) = gfg.jacobian();
EXPECT(assert_equal(A, actualA));
EXPECT(assert_equal(b, actualb));
// hessian
Matrix L = A.transpose() * A;
Vector eta = A.transpose() * b;
Matrix actualL;
Vector actualeta;
boost::tie(actualL, actualeta) = gfg.hessian();
EXPECT(assert_equal(L, actualL));
EXPECT(assert_equal(eta, actualeta));
// hessianBlockDiagonal
VectorValues expectLdiagonal; // Make explicit that diagonal is sum-squares of columns
expectLdiagonal.insert(0, Vector3(1 + 25 + 81, 4 + 36 + 100, 9 + 49));
expectLdiagonal.insert(1, Vector2(121 + 196, 144 + 225));
EXPECT(assert_equal(expectLdiagonal, gfg.hessianDiagonal()));
// hessianBlockDiagonal
map<Key, Matrix> actualBD = gfg.hessianBlockDiagonal();
LONGS_EQUAL(2, actualBD.size());
EXPECT(assert_equal(A00.transpose() * A00 + A10.transpose() * A10, actualBD[0]));
EXPECT(assert_equal(A11.transpose() * A11, actualBD[1]));
}示例2: EXPECT
/* ************************************************************************* */
TEST(GaussianFactorGraph, matricesMixed) {
GaussianFactorGraph gfg = createGaussianFactorGraphWithHessianFactor();
Matrix A;
Vector b;
boost::tie(A, b) = gfg.jacobian(); // incorrect !
Matrix AtA;
Vector eta;
boost::tie(AtA, eta) = gfg.hessian(); // correct
EXPECT(assert_equal(A.transpose() * A, AtA));
Vector expected = -(Vector(6) << -25, 17.5, 5, -13.5, 29, 4).finished();
EXPECT(assert_equal(expected, eta));
EXPECT(assert_equal(A.transpose() * b, eta));
}示例3: expectedAtA
/* ************************************************************************* */
TEST(GaussianFactorGraph, matrices2) {
GaussianFactorGraph gfg = createSimpleGaussianFactorGraph();
Matrix A;
Vector b;
boost::tie(A, b) = gfg.jacobian();
Matrix AtA;
Vector eta;
boost::tie(AtA, eta) = gfg.hessian();
EXPECT(assert_equal(A.transpose() * A, AtA));
EXPECT(assert_equal(A.transpose() * b, eta));
Matrix expectedAtA(6, 6);
expectedAtA << 125, 0, -25, 0, -100, 0, //
0, 125, 0, -25, 0, -100, //
-25, 0, 50, 0, -25, 0, //
0, -25, 0, 50, 0, -25, //
-100, 0, -25, 0, 225, 0, //
0, -100, 0, -25, 0, 225;
EXPECT(assert_equal(expectedAtA, AtA));
}