430 lines
14 KiB
C++
430 lines
14 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testExpressionFactor.cpp
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* @date September 18, 2014
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* @author Frank Dellaert
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* @author Paul Furgale
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* @brief unit tests for Block Automatic Differentiation
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*/
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#include <gtsam_unstable/slam/expressions.h>
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#include <gtsam_unstable/nonlinear/ExpressionFactor.h>
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#include <gtsam/slam/GeneralSFMFactor.h>
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#include <gtsam/slam/ProjectionFactor.h>
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#include <gtsam/slam/PriorFactor.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Cal3_S2.h>
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#include <gtsam/base/Testable.h>
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#include <CppUnitLite/TestHarness.h>
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using namespace std;
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using namespace gtsam;
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Point2 measured(-17, 30);
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SharedNoiseModel model = noiseModel::Unit::Create(2);
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namespace leaf {
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// Create some values
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struct MyValues: public Values {
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MyValues() {
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insert(2, Point2(3, 5));
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}
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} values;
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// Create leaf
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Point2_ p(2);
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}
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/* ************************************************************************* */
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// Leaf
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TEST(ExpressionFactor, Leaf) {
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using namespace leaf;
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// Create old-style factor to create expected value and derivatives
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PriorFactor<Point2> old(2, Point2(0, 0), model);
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// Concise version
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ExpressionFactor<Point2> f(model, Point2(0, 0), p);
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EXPECT_DOUBLES_EQUAL(old.error(values), f.error(values), 1e-9);
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EXPECT_LONGS_EQUAL(2, f.dim());
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boost::shared_ptr<GaussianFactor> gf2 = f.linearize(values);
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EXPECT( assert_equal(*old.linearize(values), *gf2, 1e-9));
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}
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///* ************************************************************************* */
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//// non-zero noise model
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//TEST(ExpressionFactor, Model) {
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// using namespace leaf;
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//
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// SharedNoiseModel model = noiseModel::Diagonal::Sigmas(Vector2(0.1, 0.01));
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//
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// // Create old-style factor to create expected value and derivatives
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// PriorFactor<Point2> old(2, Point2(0, 0), model);
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//
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// // Concise version
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// ExpressionFactor<Point2> f(model, Point2(0, 0), p);
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// EXPECT_DOUBLES_EQUAL(old.error(values), f.error(values), 1e-9);
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// EXPECT_LONGS_EQUAL(2, f.dim());
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// boost::shared_ptr<GaussianFactor> gf2 = f.linearize(values);
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// EXPECT( assert_equal(*old.linearize(values), *gf2, 1e-9));
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//}
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//
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///* ************************************************************************* */
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//// Constrained noise model
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//TEST(ExpressionFactor, Constrained) {
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// using namespace leaf;
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//
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// SharedDiagonal model = noiseModel::Constrained::MixedSigmas(Vector2(0.2, 0));
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//
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// // Create old-style factor to create expected value and derivatives
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// PriorFactor<Point2> old(2, Point2(0, 0), model);
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//
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// // Concise version
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// ExpressionFactor<Point2> f(model, Point2(0, 0), p);
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// EXPECT_DOUBLES_EQUAL(old.error(values), f.error(values), 1e-9);
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// EXPECT_LONGS_EQUAL(2, f.dim());
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// boost::shared_ptr<GaussianFactor> gf2 = f.linearize(values);
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// EXPECT( assert_equal(*old.linearize(values), *gf2, 1e-9));
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//}
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/* ************************************************************************* */
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// Unary(Leaf))
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TEST(ExpressionFactor, Unary) {
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// Create some values
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Values values;
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values.insert(2, Point3(0, 0, 1));
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JacobianFactor expected( //
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2, (Matrix(2, 3) << 1, 0, 0, 0, 1, 0), //
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(Vector(2) << -17, 30));
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// Create leaves
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Point3_ p(2);
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// Concise version
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ExpressionFactor<Point2> f(model, measured, project(p));
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EXPECT_LONGS_EQUAL(2, f.dim());
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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boost::shared_ptr<JacobianFactor> jf = //
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boost::dynamic_pointer_cast<JacobianFactor>(gf);
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EXPECT( assert_equal(expected, *jf, 1e-9));
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}
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/* ************************************************************************* */
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static Point2 myUncal(const Cal3_S2& K, const Point2& p,
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boost::optional<Matrix25&> Dcal, boost::optional<Matrix2&> Dp) {
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return K.uncalibrate(p, Dcal, Dp);
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}
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// Binary(Leaf,Leaf)
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TEST(ExpressionFactor, Binary) {
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typedef BinaryExpression<Point2, Cal3_S2, Point2> Binary;
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Cal3_S2_ K_(1);
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Point2_ p_(2);
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Binary binary(myUncal, K_, p_);
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// Create some values
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Values values;
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values.insert(1, Cal3_S2());
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values.insert(2, Point2(0, 0));
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// traceRaw will fill raw with [Trace<Point2> | Binary::Record]
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EXPECT_LONGS_EQUAL(8, sizeof(double));
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EXPECT_LONGS_EQUAL(16, sizeof(Point2));
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EXPECT_LONGS_EQUAL(40, sizeof(Cal3_S2));
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EXPECT_LONGS_EQUAL(16, sizeof(ExecutionTrace<Point2>));
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EXPECT_LONGS_EQUAL(16, sizeof(ExecutionTrace<Cal3_S2>));
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EXPECT_LONGS_EQUAL(2*5*8, sizeof(Jacobian<Point2,Cal3_S2>::type));
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EXPECT_LONGS_EQUAL(2*2*8, sizeof(Jacobian<Point2,Point2>::type));
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size_t expectedRecordSize = 16 + 16 + 40 + 2 * 16 + 80 + 32;
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EXPECT_LONGS_EQUAL(expectedRecordSize + 8, sizeof(Binary::Record));
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// Check size
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size_t size = binary.traceSize();
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CHECK(size);
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EXPECT_LONGS_EQUAL(expectedRecordSize + 8, size);
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// Use Variable Length Array, allocated on stack by gcc
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// Note unclear for Clang: http://clang.llvm.org/compatibility.html#vla
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char raw[size];
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ExecutionTrace<Point2> trace;
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Point2 value = binary.traceExecution(values, trace, raw);
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// trace.print();
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// Expected Jacobians
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Matrix25 expected25;
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expected25 << 0, 0, 0, 1, 0, 0, 0, 0, 0, 1;
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Matrix2 expected22;
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expected22 << 1, 0, 0, 1;
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// Check matrices
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boost::optional<Binary::Record*> r = trace.record<Binary::Record>();
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CHECK(r);
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EXPECT(
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assert_equal(expected25, (Matrix) (*r)-> jacobian<Cal3_S2, 1>(), 1e-9));
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EXPECT( assert_equal(expected22, (Matrix) (*r)->jacobian<Point2, 2>(), 1e-9));
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}
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/* ************************************************************************* */
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// Unary(Binary(Leaf,Leaf))
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TEST(ExpressionFactor, Shallow) {
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// Create some values
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Values values;
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values.insert(1, Pose3());
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values.insert(2, Point3(0, 0, 1));
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// Create old-style factor to create expected value and derivatives
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GenericProjectionFactor<Pose3, Point3> old(measured, model, 1, 2,
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boost::make_shared<Cal3_S2>());
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double expected_error = old.error(values);
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GaussianFactor::shared_ptr expected = old.linearize(values);
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// Create leaves
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Pose3_ x_(1);
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Point3_ p_(2);
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// Construct expression, concise evrsion
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Point2_ expression = project(transform_to(x_, p_));
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// traceExecution of shallow tree
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typedef UnaryExpression<Point2, Point3> Unary;
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typedef BinaryExpression<Point3, Pose3, Point3> Binary;
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size_t expectedTraceSize = sizeof(Unary::Record) + sizeof(Binary::Record);
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EXPECT_LONGS_EQUAL(112, sizeof(Unary::Record));
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#ifdef GTSAM_USE_QUATERNIONS
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EXPECT_LONGS_EQUAL(464, sizeof(Binary::Record));
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LONGS_EQUAL(112+464, expectedTraceSize);
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#else
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EXPECT_LONGS_EQUAL(400, sizeof(Binary::Record));
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LONGS_EQUAL(112+400, expectedTraceSize);
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#endif
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size_t size = expression.traceSize();
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CHECK(size);
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EXPECT_LONGS_EQUAL(expectedTraceSize, size);
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char raw[size];
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ExecutionTrace<Point2> trace;
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Point2 value = expression.traceExecution(values, trace, raw);
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// trace.print();
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// Expected Jacobians
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Matrix23 expected23;
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expected23 << 1, 0, 0, 0, 1, 0;
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// Check matrices
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boost::optional<Unary::Record*> r = trace.record<Unary::Record>();
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CHECK(r);
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EXPECT(assert_equal(expected23, (Matrix)(*r)->jacobian<Point3, 1>(), 1e-9));
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// Linearization
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ExpressionFactor<Point2> f2(model, measured, expression);
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EXPECT_DOUBLES_EQUAL(expected_error, f2.error(values), 1e-9);
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EXPECT_LONGS_EQUAL(2, f2.dim());
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boost::shared_ptr<GaussianFactor> gf2 = f2.linearize(values);
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EXPECT( assert_equal(*expected, *gf2, 1e-9));
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}
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/* ************************************************************************* */
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// Binary(Leaf,Unary(Binary(Leaf,Leaf)))
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TEST(ExpressionFactor, tree) {
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// Create some values
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Values values;
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values.insert(1, Pose3());
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values.insert(2, Point3(0, 0, 1));
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values.insert(3, Cal3_S2());
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// Create old-style factor to create expected value and derivatives
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GeneralSFMFactor2<Cal3_S2> old(measured, model, 1, 2, 3);
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double expected_error = old.error(values);
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GaussianFactor::shared_ptr expected = old.linearize(values);
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// Create leaves
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Pose3_ x(1);
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Point3_ p(2);
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Cal3_S2_ K(3);
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// Create expression tree
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Point3_ p_cam(x, &Pose3::transform_to, p);
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Point2_ xy_hat(PinholeCamera<Cal3_S2>::project_to_camera, p_cam);
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Point2_ uv_hat(K, &Cal3_S2::uncalibrate, xy_hat);
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// Create factor and check value, dimension, linearization
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ExpressionFactor<Point2> f(model, measured, uv_hat);
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EXPECT_DOUBLES_EQUAL(expected_error, f.error(values), 1e-9);
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EXPECT_LONGS_EQUAL(2, f.dim());
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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EXPECT( assert_equal(*expected, *gf, 1e-9));
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// Concise version
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ExpressionFactor<Point2> f2(model, measured,
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uncalibrate(K, project(transform_to(x, p))));
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EXPECT_DOUBLES_EQUAL(expected_error, f2.error(values), 1e-9);
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EXPECT_LONGS_EQUAL(2, f2.dim());
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boost::shared_ptr<GaussianFactor> gf2 = f2.linearize(values);
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EXPECT( assert_equal(*expected, *gf2, 1e-9));
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TernaryExpression<Point2, Pose3, Point3, Cal3_S2>::Function fff = project6;
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// Try ternary version
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ExpressionFactor<Point2> f3(model, measured, project3(x, p, K));
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EXPECT_DOUBLES_EQUAL(expected_error, f3.error(values), 1e-9);
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EXPECT_LONGS_EQUAL(2, f3.dim());
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boost::shared_ptr<GaussianFactor> gf3 = f3.linearize(values);
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EXPECT( assert_equal(*expected, *gf3, 1e-9));
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}
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/* ************************************************************************* */
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TEST(ExpressionFactor, Compose1) {
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// Create expression
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Rot3_ R1(1), R2(2);
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Rot3_ R3 = R1 * R2;
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// Create factor
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ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);
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// Create some values
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Values values;
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values.insert(1, Rot3());
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values.insert(2, Rot3());
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// Check unwhitenedError
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std::vector<Matrix> H(2);
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Vector actual = f.unwhitenedError(values, H);
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EXPECT( assert_equal(eye(3), H[0],1e-9));
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EXPECT( assert_equal(eye(3), H[1],1e-9));
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// Check linearization
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JacobianFactor expected(1, eye(3), 2, eye(3), zero(3));
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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boost::shared_ptr<JacobianFactor> jf = //
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boost::dynamic_pointer_cast<JacobianFactor>(gf);
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EXPECT( assert_equal(expected, *jf,1e-9));
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}
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/* ************************************************************************* */
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// Test compose with arguments referring to the same rotation
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TEST(ExpressionFactor, compose2) {
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// Create expression
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Rot3_ R1(1), R2(1);
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Rot3_ R3 = R1 * R2;
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// Create factor
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ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);
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// Create some values
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Values values;
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values.insert(1, Rot3());
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// Check unwhitenedError
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std::vector<Matrix> H(1);
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Vector actual = f.unwhitenedError(values, H);
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EXPECT_LONGS_EQUAL(1, H.size());
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EXPECT( assert_equal(2*eye(3), H[0],1e-9));
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// Check linearization
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JacobianFactor expected(1, 2 * eye(3), zero(3));
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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boost::shared_ptr<JacobianFactor> jf = //
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boost::dynamic_pointer_cast<JacobianFactor>(gf);
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EXPECT( assert_equal(expected, *jf,1e-9));
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}
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/* ************************************************************************* */
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// Test compose with one arguments referring to a constant same rotation
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TEST(ExpressionFactor, compose3) {
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// Create expression
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Rot3_ R1(Rot3::identity()), R2(3);
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Rot3_ R3 = R1 * R2;
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// Create factor
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ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);
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// Create some values
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Values values;
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values.insert(3, Rot3());
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// Check unwhitenedError
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std::vector<Matrix> H(1);
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Vector actual = f.unwhitenedError(values, H);
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EXPECT_LONGS_EQUAL(1, H.size());
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EXPECT( assert_equal(eye(3), H[0],1e-9));
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// Check linearization
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JacobianFactor expected(3, eye(3), zero(3));
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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boost::shared_ptr<JacobianFactor> jf = //
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boost::dynamic_pointer_cast<JacobianFactor>(gf);
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EXPECT( assert_equal(expected, *jf,1e-9));
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}
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/* ************************************************************************* */
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// Test compose with three arguments
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Rot3 composeThree(const Rot3& R1, const Rot3& R2, const Rot3& R3,
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boost::optional<Matrix3&> H1, boost::optional<Matrix3&> H2,
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boost::optional<Matrix3&> H3) {
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// return dummy derivatives (not correct, but that's ok for testing here)
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if (H1)
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*H1 = eye(3);
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if (H2)
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*H2 = eye(3);
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if (H3)
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*H3 = eye(3);
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return R1 * (R2 * R3);
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}
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TEST(ExpressionFactor, composeTernary) {
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// Create expression
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Rot3_ A(1), B(2), C(3);
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Rot3_ ABC(composeThree, A, B, C);
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// Create factor
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ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), ABC);
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// Create some values
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Values values;
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values.insert(1, Rot3());
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values.insert(2, Rot3());
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values.insert(3, Rot3());
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// Check unwhitenedError
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std::vector<Matrix> H(3);
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Vector actual = f.unwhitenedError(values, H);
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EXPECT_LONGS_EQUAL(3, H.size());
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EXPECT( assert_equal(eye(3), H[0],1e-9));
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EXPECT( assert_equal(eye(3), H[1],1e-9));
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EXPECT( assert_equal(eye(3), H[2],1e-9));
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// Check linearization
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JacobianFactor expected(1, eye(3), 2, eye(3), 3, eye(3), zero(3));
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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boost::shared_ptr<JacobianFactor> jf = //
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boost::dynamic_pointer_cast<JacobianFactor>(gf);
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EXPECT( assert_equal(expected, *jf,1e-9));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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