better docstrings w/ usage examples
Gerry Chen
parent
040eb63949
commit
d16d26394e
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@ -277,25 +277,48 @@ public:
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* A convenient base class for creating your own NoiseModelFactor
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* with n variables. To derive from this class, implement evaluateError().
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*
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* For example, a 2-way factor could be implemented like so:
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* For example, a 2-way factor that computes the difference in x-translation
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* between a Pose3 and Point3 could be implemented like so:
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*
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* ~~~~~~~~~~~~~~~~~~~~{.cpp}
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* class MyFactor : public NoiseModelFactorN<double, double> {
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* class MyFactor : public NoiseModelFactorN<Pose3, Point3> {
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* public:
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* using Base = NoiseModelFactorN<double, double>;
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* using Base = NoiseModelFactorN<Pose3, Point3>;
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*
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* MyFactor(Key key1, Key key2, const SharedNoiseModel& noiseModel)
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* : Base(noiseModel, key1, key2) {}
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* MyFactor(Key pose_key, Key point_key, const SharedNoiseModel& noiseModel)
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* : Base(noiseModel, pose_key, point_key) {}
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*
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* Vector evaluateError(
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* const double& x1, const double& x2,
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* boost::optional<Matrix&> H1 = boost::none,
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* boost::optional<Matrix&> H2 = boost::none) const override {
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* if (H1) *H1 = (Matrix(1, 1) << 1.0).finished();
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* if (H2) *H2 = (Matrix(1, 1) << 2.0).finished();
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* return (Vector(1) << x1 + 2 * x2).finished();
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* const Pose3& T, const Point3& p,
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* boost::optional<Matrix&> H_T = boost::none,
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* boost::optional<Matrix&> H_p = boost::none) const override {
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* Matrix36 t_H_T; // partial derivative of translation w.r.t. pose T
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*
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* // Only compute t_H_T if needed:
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* Point3 t = T.translation(H_T ? &t_H_T : 0);
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* double a = t(0); // a_H_t = [1, 0, 0]
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* double b = p(0); // b_H_p = [1, 0, 0]
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* double error = a - b; // H_a = 1, H_b = -1
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*
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* // H_T = H_a * a_H_t * t_H_T = the first row of t_H_T
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* if (H_T) *H_T = (Matrix(1, 6) << t_H_T.row(0)).finished();
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* // H_p = H_b * b_H_p = -1 * [1, 0, 0]
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* if (H_p) *H_p = (Matrix(1, 3) << -1., 0., 0.).finished();
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*
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* return Vector1(error);
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* }
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* };
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*
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* // Unit Test
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* TEST(NonlinearFactor, MyFactor) {
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* MyFactor f(X(1), X(2), noiseModel::Unit::Create(1));
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* EXPECT_DOUBLES_EQUAL(-8., f.evaluateError(Pose3(), Point3(8., 7., 6.))(0),
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* 1e-9);
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* Values values;
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* values.insert(X(1), Pose3(Rot3::RzRyRx(0.1, 0.2, 0.3), Point3(1, 2, 3)));
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* values.insert(X(2), Point3(1, 2, 3));
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* EXPECT_CORRECT_FACTOR_JACOBIANS(f, values, 1e-5, 1e-5);
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* }
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* ~~~~~~~~~~~~~~~~~~~~
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*
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* These factors are templated on a values structure type. The values structures
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@ -379,8 +402,8 @@ class NoiseModelFactorN : public NoiseModelFactor {
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/**
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* Constructor.
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* Example usage: NoiseModelFactorN(noise, {key1, key2, ..., keyN})
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* Example usage: NoiseModelFactorN(noise, keys); where keys is a vector<Key>
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* Example usage: `NoiseModelFactorN(noise, {key1, key2, ..., keyN})`
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* Example usage: `NoiseModelFactorN(noise, keys)` where keys is a vector<Key>
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* @param noiseModel Shared pointer to noise model.
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* @param keys A container of keys for the variables in this factor.
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*/
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@ -388,7 +411,10 @@ class NoiseModelFactorN : public NoiseModelFactor {
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typename = IsContainerOfKeys<CONTAINER>>
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NoiseModelFactorN(const SharedNoiseModel& noiseModel, CONTAINER keys)
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: Base(noiseModel, keys) {
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assert(keys.size() == N);
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if (keys.size() != N) {
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throw std::invalid_argument(
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"NoiseModelFactorN: wrong number of keys given");
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}
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}
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/// @}
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@ -413,12 +439,21 @@ class NoiseModelFactorN : public NoiseModelFactor {
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/// @name NoiseModelFactor methods
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/// @{
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/** Calls the n-key specific version of evaluateError, which is pure virtual
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* so must be implemented in the derived class.
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/** This implements the `unwhitenedError` virtual function by calling the
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* n-key specific version of evaluateError, which is pure virtual so must be
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* implemented in the derived class.
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*
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* Example usage:
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* ```
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* gtsam::Values values;
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* values.insert(...) // populate values
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* std::vector<Matrix> Hs(2); // this will be an optional output argument
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* const Vector error = factor.unwhitenedError(values, Hs);
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* ```
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* @param[in] x A Values object containing the values of all the variables
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* used in this factor
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* @param[out] H A vector of (dynamic) matrices whose size should be equal to
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* n. The jacobians w.r.t. each variable will be output in this parameter.
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* n. The Jacobians w.r.t. each variable will be output in this parameter.
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*/
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Vector unwhitenedError(
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const Values& x,
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@ -430,17 +465,19 @@ class NoiseModelFactorN : public NoiseModelFactor {
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/// @}
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/// @name Virtual methods
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/// @{
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/**
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* Override this method to finish implementing an n-way factor.
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* Override `evaluateError` to finish implementing an n-way factor.
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*
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* Both the `x` and `H` arguments are written here as parameter packs, but
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* when overriding this method, you probably want to explicitly write them
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* out. For example, for a 2-way factor with variable types Pose3 and double:
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* out. For example, for a 2-way factor with variable types Pose3 and Point3,
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* you should implement:
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* ```
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* Vector evaluateError(const Pose3& x1, const double& x2,
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* Vector evaluateError(
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* const Pose3& x1, const Point3& x2,
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* boost::optional<Matrix&> H1 = boost::none,
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* boost::optional<Matrix&> H2 = boost::none) const
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* override {...}
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* boost::optional<Matrix&> H2 = boost::none) const override { ... }
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* ```
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*
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* If any of the optional Matrix reference arguments are specified, it should
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@ -458,17 +495,20 @@ class NoiseModelFactorN : public NoiseModelFactor {
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/// @name Convenience method overloads
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/// @{
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/** No-jacobians requested function overload (since parameter packs can't have
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* default args). This specializes the version below to avoid recursive calls
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* since this is commonly used.
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/** No-Jacobians requested function overload.
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* This specializes the version below to avoid recursive calls since this is
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* commonly used.
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*
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* e.g. `Vector error = factor.evaluateError(x1, x2, x3);`
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* e.g. `const Vector error = factor.evaluateError(pose, point);`
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*/
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inline Vector evaluateError(const ValueTypes&... x) const {
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return evaluateError(x..., OptionalMatrix<ValueTypes>()...);
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}
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/** Some optional jacobians omitted function overload */
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/** Some (but not all) optional Jacobians are omitted (function overload)
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*
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* e.g. `const Vector error = factor.evaluateError(pose, point, Hpose);`
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*/
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template <typename... OptionalJacArgs,
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typename = IndexIsValid<sizeof...(OptionalJacArgs) + 1>>
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inline Vector evaluateError(const ValueTypes&... x,
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@ -481,7 +521,10 @@ class NoiseModelFactorN : public NoiseModelFactor {
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private:
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/** Pack expansion with index_sequence template pattern, used to index into
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* `keys_` and `H`
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* `keys_` and `H`.
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*
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* Example: For `NoiseModelFactorN<Pose3, Point3>`, the call would look like:
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* `const Vector error = unwhitenedError(0, 1, values, H);`
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*/
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template <std::size_t... Indices>
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inline Vector unwhitenedError(
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@ -510,8 +553,8 @@ class NoiseModelFactorN : public NoiseModelFactor {
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}; // \class NoiseModelFactorN
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 1 variable. To derive from this class, implement evaluateError().
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*/
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@ -544,8 +587,8 @@ class GTSAM_DEPRECATED NoiseModelFactor1 : public NoiseModelFactorN<VALUE> {
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}; // \class NoiseModelFactor1
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 2 variables. To derive from this class, implement evaluateError().
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*/
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@ -581,8 +624,8 @@ class GTSAM_DEPRECATED NoiseModelFactor2
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}; // \class NoiseModelFactor2
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 3 variables. To derive from this class, implement evaluateError().
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*/
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@ -620,8 +663,8 @@ class GTSAM_DEPRECATED NoiseModelFactor3
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}; // \class NoiseModelFactor3
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 4 variables. To derive from this class, implement evaluateError().
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*/
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@ -661,8 +704,8 @@ class GTSAM_DEPRECATED NoiseModelFactor4
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}; // \class NoiseModelFactor4
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 5 variables. To derive from this class, implement evaluateError().
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*/
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@ -705,8 +748,8 @@ class GTSAM_DEPRECATED NoiseModelFactor5
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}; // \class NoiseModelFactor5
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/* ************************************************************************* */
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<0> and X1
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* with ValueType<0>.
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/** @deprecated: use NoiseModelFactorN, replacing .key1() with .key<1> and X1
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* with ValueType<1>.
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* A convenient base class for creating your own NoiseModelFactor
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* with 6 variables. To derive from this class, implement evaluateError().
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*/
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