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First prototype, segfaults

release/4.3a0
dellaert 2014-10-11 10:27:30 +02:00
parent e09e24964a
commit eef2d49e8d
3 changed files with 374 additions and 344 deletions
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120
gtsam_unstable/nonlinear/Expression-inl.h
View File

@ -21,6 +21,7 @@
#include <gtsam/nonlinear/Values.h>
#include <gtsam/base/Matrix.h>
#include <gtsam/base/Testable.h>
#include <boost/foreach.hpp>
#include <boost/tuple/tuple.hpp>
@ -43,10 +44,7 @@ typedef std::map<Key, Matrix> JacobianMap;
*/
template<int COLS>
struct CallRecord {
/// Make sure destructor is virtual
virtual ~CallRecord() {
}
virtual void print() const = 0;
virtual void startReverseAD(JacobianMap& jacobians) const = 0;
virtual void reverseAD(const Matrix& dFdT, JacobianMap& jacobians) const = 0;
typedef Eigen::Matrix<double, 2, COLS> Jacobian2T;
@ -72,15 +70,11 @@ class ExecutionTrace {
CallRecord<T::dimension>* ptr;
} content;
public:
T value;
/// Pointer always starts out as a Constant
ExecutionTrace() :
type(Constant) {
}
/// Destructor cleans up pointer if Function
~ExecutionTrace() {
if (type == Function)
delete content.ptr;
}
/// Change pointer to a Leaf Record
void setLeaf(Key key) {
type = Leaf;
@ -91,6 +85,14 @@ public:
type = Function;
content.ptr = record;
}
/// Print
virtual void print() const {
GTSAM_PRINT(value);
if (type == Leaf)
std::cout << "Leaf, key = " << content.key << std::endl;
else if (type == Function)
content.ptr->print();
}
/// Return record pointer, quite unsafe, used only for testing
template<class Record>
boost::optional<Record*> record() {
@ -158,14 +160,6 @@ struct Select<2, A> {
}
};
//template <class Derived>
//struct TypedTrace {
// virtual void startReverseAD(JacobianMap& jacobians) const = 0;
// virtual void reverseAD(const Matrix& dFdT, JacobianMap& jacobians) const = 0;
//// template<class JacobianFT>
//// void reverseAD(const JacobianFT& dFdT, JacobianMap& jacobians) const {
//};
//-----------------------------------------------------------------------------
/**
* Value and Jacobians
@ -310,8 +304,8 @@ public:
virtual Augmented<T> forward(const Values& values) const = 0;
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values,
ExecutionTrace<T>& p) const = 0;
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const = 0;
};
//-----------------------------------------------------------------------------
@ -348,8 +342,11 @@ public:
}
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values, ExecutionTrace<T>& p) const {
return constant_;
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const {
ExecutionTrace<T> trace;
trace.value = constant_;
return trace;
}
};
@ -388,9 +385,12 @@ public:
}
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values, ExecutionTrace<T>& p) const {
p.setLeaf(key_);
return values.at<T>(key_);
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const {
ExecutionTrace<T> trace;
trace.setLeaf(key_);
trace.value = values.at<T>(key_);
return trace;
}
};
@ -443,7 +443,11 @@ public:
struct Record: public CallRecord<T::dimension> {
ExecutionTrace<A1> trace1;
JacobianTA dTdA1;
/// print to std::cout
virtual void print() const {
std::cout << dTdA1 << std::endl;
trace1.print();
}
/// Start the reverse AD process
virtual void startReverseAD(JacobianMap& jacobians) const {
Select<T::dimension, A1>::reverseAD(trace1, dTdA1, jacobians);
@ -461,11 +465,14 @@ public:
};
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values, ExecutionTrace<T>& p) const {
Record* record = new Record();
p.setFunction(record);
A1 a = this->expressionA1_->traceExecution(values, record->trace1);
return function_(a, record->dTdA1);
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const {
ExecutionTrace<T> trace;
// Record* record = new Record();
// p.setFunction(record);
// A1 a = this->expressionA1_->traceExecution(values, record->trace1);
// return function_(a, record->dTdA1);
return trace;
}
};
@ -534,7 +541,13 @@ public:
ExecutionTrace<A2> trace2;
JacobianTA1 dTdA1;
JacobianTA2 dTdA2;
/// print to std::cout
virtual void print() const {
std::cout << dTdA1 << std::endl;
trace1.print();
std::cout << dTdA2 << std::endl;
trace2.print();
}
/// Start the reverse AD process
virtual void startReverseAD(JacobianMap& jacobians) const {
Select<T::dimension, A1>::reverseAD(trace1, dTdA1, jacobians);
@ -555,12 +568,18 @@ public:
};
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values, ExecutionTrace<T>& p) const {
Record* record = new Record();
p.setFunction(record);
A1 a1 = this->expressionA1_->traceExecution(values, record->trace1);
A2 a2 = this->expressionA2_->traceExecution(values, record->trace2);
return function_(a1, a2, record->dTdA1, record->dTdA2);
/// The raw buffer is [Record | A1 raw | A2 raw]
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const {
ExecutionTrace<T> trace;
Record* record = static_cast<Record*>(raw);
trace.setFunction(record);
record->trace1 = this->expressionA1_->traceExecution(values, raw);
record->trace2 = this->expressionA2_->traceExecution(values, raw);
trace.value = function_(record->trace1.value, record->trace2.value,
record->dTdA1, record->dTdA2);
trace.print();
return trace;
}
};
@ -643,7 +662,15 @@ public:
JacobianTA1 dTdA1;
JacobianTA2 dTdA2;
JacobianTA3 dTdA3;
/// print to std::cout
virtual void print() const {
std::cout << dTdA1 << std::endl;
trace1.print();
std::cout << dTdA2 << std::endl;
trace2.print();
std::cout << dTdA3 << std::endl;
trace3.print();
}
/// Start the reverse AD process
virtual void startReverseAD(JacobianMap& jacobians) const {
Select<T::dimension, A1>::reverseAD(trace1, dTdA1, jacobians);
@ -667,13 +694,16 @@ public:
};
/// Construct an execution trace for reverse AD
virtual T traceExecution(const Values& values, ExecutionTrace<T>& p) const {
Record* record = new Record();
p.setFunction(record);
A1 a1 = this->expressionA1_->traceExecution(values, record->trace1);
A2 a2 = this->expressionA2_->traceExecution(values, record->trace2);
A3 a3 = this->expressionA3_->traceExecution(values, record->trace3);
return function_(a1, a2, a3, record->dTdA1, record->dTdA2, record->dTdA3);
virtual ExecutionTrace<T> traceExecution(const Values& values,
void* raw) const {
ExecutionTrace<T> trace;
// Record* record = new Record();
// p.setFunction(record);
// A1 a1 = this->expressionA1_->traceExecution(values, record->trace1);
// A2 a2 = this->expressionA2_->traceExecution(values, record->trace2);
// A3 a3 = this->expressionA3_->traceExecution(values, record->trace3);
// return function_(a1, a2, a3, record->dTdA1, record->dTdA2, record->dTdA3);
return trace;
}
};

6
gtsam_unstable/nonlinear/Expression.h
View File

@ -117,9 +117,9 @@ public:
Augmented<T> augmented(const Values& values) const {
#define REVERSE_AD
#ifdef REVERSE_AD
ExecutionTrace<T> trace;
T value = root_->traceExecution(values, trace);
Augmented<T> augmented(value);
char raw[10];
ExecutionTrace<T> trace = root_->traceExecution(values, raw);
Augmented<T> augmented(trace.value);
trace.startReverseAD(augmented.jacobians());
return augmented;
#else

592
gtsam_unstable/nonlinear/tests/testExpressionFactor.cpp
View File

@ -33,79 +33,79 @@ 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));
}
///* ************************************************************************* */
//// 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,
@ -137,236 +137,236 @@ TEST(ExpressionFactor, binary) {
Matrix2 expected22;
expected22 << 1, 0, 0, 1;
// Do old trace
ExecutionTrace<Point2> trace;
tester.binary_.traceExecution(values, trace);
// traceRaw will fill raw with [Trace<Point2> | Binary::Record]
EXPECT_LONGS_EQUAL(8, sizeof(double));
EXPECT_LONGS_EQUAL(48, sizeof(ExecutionTrace<Point2>));
EXPECT_LONGS_EQUAL(72, sizeof(ExecutionTrace<Cal3_S2>));
EXPECT_LONGS_EQUAL(2*5*8, sizeof(Binary::JacobianTA1));
EXPECT_LONGS_EQUAL(2*2*8, sizeof(Binary::JacobianTA2));
size_t expectedRecordSize = 8 + 48 + 72 + 80 + 32; // 240
EXPECT_LONGS_EQUAL(expectedRecordSize, sizeof(Binary::Record));
size_t size = sizeof(Binary::Record);
// Use Variable Length Array, allocated on stack by gcc
// Note unclear for Clang: http://clang.llvm.org/compatibility.html#vla
char raw[size];
ExecutionTrace<Point2> trace = tester.binary_.traceExecution(values, raw);
// 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));
}
///* ************************************************************************* */
//// 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() {