gtsam/gtsam_unstable/nonlinear/tests/testExpressionFactor.cpp

/* ----------------------------------------------------------------------------

 * GTSAM Copyright 2010, Georgia Tech Research Corporation, 
 * Atlanta, Georgia 30332-0415
 * All Rights Reserved
 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)

 * See LICENSE for the license information

 * -------------------------------------------------------------------------- */

/**
 * @file testExpressionFactor.cpp
 * @date September 18, 2014
 * @author Frank Dellaert
 * @author Paul Furgale
 * @brief unit tests for Block Automatic Differentiation
 */

#include <gtsam_unstable/slam/expressions.h>
#include <gtsam_unstable/nonlinear/ExpressionFactor.h>
#include <gtsam/slam/GeneralSFMFactor.h>
#include <gtsam/slam/ProjectionFactor.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/geometry/Cal3_S2.h>
#include <gtsam/base/Testable.h>

#include <CppUnitLite/TestHarness.h>

using namespace std;
using namespace gtsam;

Point2 measured(-17, 30);
SharedNoiseModel model = noiseModel::Unit::Create(2);

/* ************************************************************************* */
// Leaf
TEST(ExpressionFactor, leaf) {

  // Create some values
  Values values;
  values.insert(2, Point2(3, 5));

  JacobianFactor expected( //
      2, (Matrix(2, 2) << 1, 0, 0, 1), //
      (Vector(2) << -3, -5));

  // Create leaves
  Point2_ p(2);

  // Concise version
  ExpressionFactor<Point2> f(model, Point2(0, 0), p);
  EXPECT_LONGS_EQUAL(2, f.dim());
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf, 1e-9));
}

/* ************************************************************************* */
// non-zero noise model
TEST(ExpressionFactor, model) {

  // Create some values
  Values values;
  values.insert(2, Point2(3, 5));

  JacobianFactor expected( //
      2, (Matrix(2, 2) << 10, 0, 0, 100), //
      (Vector(2) << -30, -500));

  // Create leaves
  Point2_ p(2);

  // Concise version
  SharedNoiseModel model = noiseModel::Diagonal::Sigmas(Vector2(0.1, 0.01));

  ExpressionFactor<Point2> f(model, Point2(0, 0), p);
  EXPECT_LONGS_EQUAL(2, f.dim());
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf, 1e-9));
}

/* ************************************************************************* */
// Unary(Leaf))
TEST(ExpressionFactor, unary) {

  // Create some values
  Values values;
  values.insert(2, Point3(0, 0, 1));

  JacobianFactor expected( //
      2, (Matrix(2, 3) << 1, 0, 0, 0, 1, 0), //
      (Vector(2) << -17, 30));

  // Create leaves
  Point3_ p(2);

  // Concise version
  ExpressionFactor<Point2> f(model, measured, project(p));
  EXPECT_LONGS_EQUAL(2, f.dim());
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf, 1e-9));
}
/* ************************************************************************* */
struct TestBinaryExpression {
  static Point2 myUncal(const Cal3_S2& K, const Point2& p,
      boost::optional<Matrix25&> Dcal, boost::optional<Matrix2&> Dp) {
    return K.uncalibrate(p, Dcal, Dp);
  }
  Cal3_S2_ K_;
  Point2_ p_;
  BinaryExpression<Point2, Cal3_S2, Point2> binary_;
  TestBinaryExpression() :
      K_(1), p_(2), binary_(myUncal, K_, p_) {
  }
};
/* ************************************************************************* */
// Binary(Leaf,Leaf)
TEST(ExpressionFactor, binary) {

  typedef BinaryExpression<Point2, Cal3_S2, Point2> Binary;
  TestBinaryExpression tester;

  // Create some values
  Values values;
  values.insert(1, Cal3_S2());
  values.insert(2, Point2(0, 0));

  // Expected Jacobians
  Matrix25 expected25;
  expected25 << 0, 0, 0, 1, 0, 0, 0, 0, 0, 1;
  Matrix2 expected22;
  expected22 << 1, 0, 0, 1;

  // Do old trace
  ExecutionTrace<Point2> trace;
  tester.binary_.traceExecution(values, trace);

  // Check matrices
  boost::optional<Binary::Record*> p = trace.record<Binary::Record>();
  CHECK(p);
  EXPECT( assert_equal(expected25, (Matrix)(*p)->dTdA1, 1e-9));
  EXPECT( assert_equal(expected22, (Matrix)(*p)->dTdA2, 1e-9));

//  // Check raw memory trace
//  double raw[10];
//  tester.binary_.traceRaw(values, 0);
//
//  // Check matrices
//  boost::optional<Binary::Record*> p = trace.record<Binary::Record>();
//  CHECK(p);
//  EXPECT( assert_equal(expected25, (Matrix)(*p)->dTdA1, 1e-9));
//  EXPECT( assert_equal(expected22, (Matrix)(*p)->dTdA2, 1e-9));
}
/* ************************************************************************* */
// Unary(Binary(Leaf,Leaf))
TEST(ExpressionFactor, shallow) {

  // Create some values
  Values values;
  values.insert(1, Pose3());
  values.insert(2, Point3(0, 0, 1));

  // Create old-style factor to create expected value and derivatives
  GenericProjectionFactor<Pose3, Point3> old(measured, model, 1, 2,
      boost::make_shared<Cal3_S2>());
  double expected_error = old.error(values);
  GaussianFactor::shared_ptr expected = old.linearize(values);

  // Create leaves
  Pose3_ x(1);
  Point3_ p(2);

  // Concise version
  ExpressionFactor<Point2> f2(model, measured, project(transform_to(x, p)));
  EXPECT_DOUBLES_EQUAL(expected_error, f2.error(values), 1e-9);
  EXPECT_LONGS_EQUAL(2, f2.dim());
  boost::shared_ptr<GaussianFactor> gf2 = f2.linearize(values);
  EXPECT( assert_equal(*expected, *gf2, 1e-9));
}

/* ************************************************************************* */
// Binary(Leaf,Unary(Binary(Leaf,Leaf)))
TEST(ExpressionFactor, tree) {

  // Create some values
  Values values;
  values.insert(1, Pose3());
  values.insert(2, Point3(0, 0, 1));
  values.insert(3, Cal3_S2());

  // Create old-style factor to create expected value and derivatives
  GeneralSFMFactor2<Cal3_S2> old(measured, model, 1, 2, 3);
  double expected_error = old.error(values);
  GaussianFactor::shared_ptr expected = old.linearize(values);

  // Create leaves
  Pose3_ x(1);
  Point3_ p(2);
  Cal3_S2_ K(3);

  // Create expression tree
  Point3_ p_cam(x, &Pose3::transform_to, p);
  Point2_ xy_hat(PinholeCamera<Cal3_S2>::project_to_camera, p_cam);
  Point2_ uv_hat(K, &Cal3_S2::uncalibrate, xy_hat);

  // Create factor and check value, dimension, linearization
  ExpressionFactor<Point2> f(model, measured, uv_hat);
  EXPECT_DOUBLES_EQUAL(expected_error, f.error(values), 1e-9);
  EXPECT_LONGS_EQUAL(2, f.dim());
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  EXPECT( assert_equal(*expected, *gf, 1e-9));

  // Concise version
  ExpressionFactor<Point2> f2(model, measured,
      uncalibrate(K, project(transform_to(x, p))));
  EXPECT_DOUBLES_EQUAL(expected_error, f2.error(values), 1e-9);
  EXPECT_LONGS_EQUAL(2, f2.dim());
  boost::shared_ptr<GaussianFactor> gf2 = f2.linearize(values);
  EXPECT( assert_equal(*expected, *gf2, 1e-9));

  TernaryExpression<Point2, Pose3, Point3, Cal3_S2>::Function fff = project6;

  // Try ternary version
  ExpressionFactor<Point2> f3(model, measured, project3(x, p, K));
  EXPECT_DOUBLES_EQUAL(expected_error, f3.error(values), 1e-9);
  EXPECT_LONGS_EQUAL(2, f3.dim());
  boost::shared_ptr<GaussianFactor> gf3 = f3.linearize(values);
  EXPECT( assert_equal(*expected, *gf3, 1e-9));
}

/* ************************************************************************* */

TEST(ExpressionFactor, compose1) {

  // Create expression
  Rot3_ R1(1), R2(2);
  Rot3_ R3 = R1 * R2;

  // Create factor
  ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);

  // Create some values
  Values values;
  values.insert(1, Rot3());
  values.insert(2, Rot3());

  // Check unwhitenedError
  std::vector<Matrix> H(2);
  Vector actual = f.unwhitenedError(values, H);
  EXPECT( assert_equal(eye(3), H[0],1e-9));
  EXPECT( assert_equal(eye(3), H[1],1e-9));

  // Check linearization
  JacobianFactor expected(1, eye(3), 2, eye(3), zero(3));
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf,1e-9));
}

/* ************************************************************************* */
// Test compose with arguments referring to the same rotation
TEST(ExpressionFactor, compose2) {

  // Create expression
  Rot3_ R1(1), R2(1);
  Rot3_ R3 = R1 * R2;

  // Create factor
  ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);

  // Create some values
  Values values;
  values.insert(1, Rot3());

  // Check unwhitenedError
  std::vector<Matrix> H(1);
  Vector actual = f.unwhitenedError(values, H);
  EXPECT_LONGS_EQUAL(1, H.size());
  EXPECT( assert_equal(2*eye(3), H[0],1e-9));

  // Check linearization
  JacobianFactor expected(1, 2 * eye(3), zero(3));
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf,1e-9));
}

/* ************************************************************************* */
// Test compose with one arguments referring to a constant same rotation
TEST(ExpressionFactor, compose3) {

  // Create expression
  Rot3_ R1(Rot3::identity()), R2(3);
  Rot3_ R3 = R1 * R2;

  // Create factor
  ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), R3);

  // Create some values
  Values values;
  values.insert(3, Rot3());

  // Check unwhitenedError
  std::vector<Matrix> H(1);
  Vector actual = f.unwhitenedError(values, H);
  EXPECT_LONGS_EQUAL(1, H.size());
  EXPECT( assert_equal(eye(3), H[0],1e-9));

  // Check linearization
  JacobianFactor expected(3, eye(3), zero(3));
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf,1e-9));
}

/* ************************************************************************* */
// Test compose with three arguments
Rot3 composeThree(const Rot3& R1, const Rot3& R2, const Rot3& R3,
    boost::optional<Matrix3&> H1, boost::optional<Matrix3&> H2,
    boost::optional<Matrix3&> H3) {
  // return dummy derivatives (not correct, but that's ok for testing here)
  if (H1)
    *H1 = eye(3);
  if (H2)
    *H2 = eye(3);
  if (H3)
    *H3 = eye(3);
  return R1 * (R2 * R3);
}

TEST(ExpressionFactor, composeTernary) {

  // Create expression
  Rot3_ A(1), B(2), C(3);
  Rot3_ ABC(composeThree, A, B, C);

  // Create factor
  ExpressionFactor<Rot3> f(noiseModel::Unit::Create(3), Rot3(), ABC);

  // Create some values
  Values values;
  values.insert(1, Rot3());
  values.insert(2, Rot3());
  values.insert(3, Rot3());

  // Check unwhitenedError
  std::vector<Matrix> H(3);
  Vector actual = f.unwhitenedError(values, H);
  EXPECT_LONGS_EQUAL(3, H.size());
  EXPECT( assert_equal(eye(3), H[0],1e-9));
  EXPECT( assert_equal(eye(3), H[1],1e-9));
  EXPECT( assert_equal(eye(3), H[2],1e-9));

  // Check linearization
  JacobianFactor expected(1, eye(3), 2, eye(3), 3, eye(3), zero(3));
  boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
  boost::shared_ptr<JacobianFactor> jf = //
      boost::dynamic_pointer_cast<JacobianFactor>(gf);
  EXPECT( assert_equal(expected, *jf,1e-9));
}

/* ************************************************************************* */
int main() {
  TestResult tr;
  return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */