Drake
Drake C++ Documentation

Detailed Description

An affine subspace (also known as a "flat", a "linear variety", or a "linear manifold") is a vector subspace of some Euclidean space, potentially translated so as to not pass through the origin.

Examples include points, lines, and planes (not necessarily through the origin).

An affine subspace is described by a basis of its corresponding vector subspace, plus a translation. This description is not unique as any point in the affine subspace can be used as a translation, and any basis of the corresponding vector subspace is valid.

An affine subspace can never be empty, because a vector subspace can never be empty. Thus, the translation will always be contained in the flat. An affine subspace is bounded if it is a point, which is when the basis has zero columns.

#include <drake/geometry/optimization/affine_subspace.h>

Public Member Functions

 AffineSubspace ()
 Constructs a default (zero-dimensional, nonempty) affine subspace. More...
 
 AffineSubspace (const Eigen::Ref< const Eigen::MatrixXd > &basis, const Eigen::Ref< const Eigen::VectorXd > &translation)
 Constructs the affine subspace from an n-by-m matrix describing the basis, where n is the ambient dimension, and m is the dimension of the subspace, and from an n-dimensional vector describing the translation. More...
 
 AffineSubspace (const ConvexSet &set, double tol=1e-12)
 Constructs an affine subspace as the affine hull of another convex set. More...
 
 ~AffineSubspace () final
 
const Eigen::MatrixXd & basis () const
 Returns the basis in an n-by-m matrix, where n is the ambient dimension, and m is the number of vectors in the basis. More...
 
const Eigen::VectorXd & translation () const
 Returns the translation as a length n vector. More...
 
template<typename Archive >
void Serialize (Archive *a)
 Passes this object to an Archive. More...
 
int AffineDimension () const
 Returns the affine dimension of this set. More...
 
Eigen::MatrixXd Project (const Eigen::Ref< const Eigen::MatrixXd > &x) const
 Computes the orthogonal projection of x onto the AffineSubspace. More...
 
Eigen::MatrixXd ToLocalCoordinates (const Eigen::Ref< const Eigen::MatrixXd > &x) const
 Given a point x in the standard basis of the ambient space, returns the coordinates of x in the basis of the AffineSubspace, with the zero point at translation_. More...
 
Eigen::MatrixXd ToGlobalCoordinates (const Eigen::Ref< const Eigen::MatrixXd > &y) const
 Given a point y in the basis of the AffineSubspace, with the zero point at translation_, returns the coordinates of y in the standard basis of the ambient space. More...
 
bool ContainedIn (const AffineSubspace &other, double tol=1e-15) const
 Returns true if this AffineSubspace is contained in other. More...
 
bool IsNearlyEqualTo (const AffineSubspace &other, double tol=1e-15) const
 Returns true if the two AffineSubspaces describe the same set, by checking that each set is contained in the other. More...
 
Eigen::MatrixXd OrthogonalComplementBasis () const
 Returns an orthonormal basis of the vector subspace which is orthogonal to this AffineSubspace. More...
 
Implements CopyConstructible, CopyAssignable, MoveConstructible, MoveAssignable
 AffineSubspace (const AffineSubspace &)=default
 
AffineSubspaceoperator= (const AffineSubspace &)=default
 
 AffineSubspace (AffineSubspace &&)=default
 
AffineSubspaceoperator= (AffineSubspace &&)=default
 
- Public Member Functions inherited from ConvexSet
virtual ~ConvexSet ()
 
std::unique_ptr< ConvexSetClone () const
 Creates a unique deep copy of this set. More...
 
int ambient_dimension () const
 Returns the dimension of the vector space in which the elements of this set are evaluated. More...
 
bool IntersectsWith (const ConvexSet &other) const
 Returns true iff the intersection between this and other is non-empty. More...
 
bool IsBounded () const
 Returns true iff the set is bounded, e.g., there exists an element-wise finite lower and upper bound for the set. More...
 
bool IsEmpty () const
 Returns true iff the set is empty. More...
 
std::optional< Eigen::VectorXd > MaybeGetPoint () const
 If this set trivially contains exactly one point, returns the value of that point. More...
 
std::optional< Eigen::VectorXd > MaybeGetFeasiblePoint () const
 Returns a feasible point within this convex set if it is nonempty, and nullopt otherwise. More...
 
bool PointInSet (const Eigen::Ref< const Eigen::VectorXd > &x, double tol=0) const
 Returns true iff the point x is contained in the set. More...
 
std::pair< VectorX< symbolic::Variable >, std::vector< solvers::Binding< solvers::Constraint > > > AddPointInSetConstraints (solvers::MathematicalProgram *prog, const Eigen::Ref< const solvers::VectorXDecisionVariable > &vars) const
 Adds a constraint to an existing MathematicalProgram enforcing that the point defined by vars is inside the set. More...
 
std::vector< solvers::Binding< solvers::Constraint > > AddPointInNonnegativeScalingConstraints (solvers::MathematicalProgram *prog, const Eigen::Ref< const solvers::VectorXDecisionVariable > &x, const symbolic::Variable &t) const
 Let S be this convex set. More...
 
std::vector< solvers::Binding< solvers::Constraint > > AddPointInNonnegativeScalingConstraints (solvers::MathematicalProgram *prog, const Eigen::Ref< const Eigen::MatrixXd > &A, const Eigen::Ref< const Eigen::VectorXd > &b, const Eigen::Ref< const Eigen::VectorXd > &c, double d, const Eigen::Ref< const solvers::VectorXDecisionVariable > &x, const Eigen::Ref< const solvers::VectorXDecisionVariable > &t) const
 Let S be this convex set. More...
 
std::pair< std::unique_ptr< Shape >, math::RigidTransformd > ToShapeWithPose () const
 Constructs a Shape and a pose of the set in the world frame for use in the SceneGraph geometry ecosystem. More...
 
double CalcVolume () const
 Computes the exact volume for the convex set. More...
 
SampledVolume CalcVolumeViaSampling (RandomGenerator *generator, const double desired_rel_accuracy=1e-2, const int max_num_samples=1e4) const
 Calculates an estimate of the volume of the convex set using sampling and performing Monte Carlo integration. More...
 
std::optional< std::pair< std::vector< double >, Eigen::MatrixXd > > Projection (const Eigen::Ref< const Eigen::MatrixXd > &points) const
 Computes in the L₂ norm the distance and the nearest point in this convex set to every column of points. More...
 
bool has_exact_volume () const
 Returns true if the exact volume can be computed for this convex set instance. More...
 

Additional Inherited Members

- Protected Member Functions inherited from ConvexSet
 ConvexSet (int ambient_dimension, bool has_exact_volume)
 For use by derived classes to construct a ConvexSet. More...
 
template<typename Archive >
void Serialize (Archive *a)
 Implements non-virtual base class serialization. More...
 
virtual bool DoPointInSet (const Eigen::Ref< const Eigen::VectorXd > &x, double tol) const
 Non-virtual interface implementation for PointInSet(). More...
 
std::optional< symbolic::VariableHandleZeroAmbientDimensionConstraints (solvers::MathematicalProgram *prog, const ConvexSet &set, std::vector< solvers::Binding< solvers::Constraint >> *constraints) const
 Instances of subclasses such as CartesianProduct and MinkowskiSum can have constituent sets with zero ambient dimension, which much be handled in a special manner when calling methods such as DoAddPointInSetConstraints. More...
 
 ConvexSet (const ConvexSet &)=default
 
ConvexSetoperator= (const ConvexSet &)=default
 
 ConvexSet (ConvexSet &&)=default
 
ConvexSetoperator= (ConvexSet &&)=default
 

Constructor & Destructor Documentation

◆ AffineSubspace() [1/5]

AffineSubspace ( const AffineSubspace )
default

◆ AffineSubspace() [2/5]

AffineSubspace ( AffineSubspace &&  )
default

◆ AffineSubspace() [3/5]

Constructs a default (zero-dimensional, nonempty) affine subspace.

◆ AffineSubspace() [4/5]

AffineSubspace ( const Eigen::Ref< const Eigen::MatrixXd > &  basis,
const Eigen::Ref< const Eigen::VectorXd > &  translation 
)
explicit

Constructs the affine subspace from an n-by-m matrix describing the basis, where n is the ambient dimension, and m is the dimension of the subspace, and from an n-dimensional vector describing the translation.

The set is {x | x = translation + basis*y, y ∈ Rᵐ} The columns must be linearly independent.

Precondition
basis.rows() == translation.size().

◆ AffineSubspace() [5/5]

AffineSubspace ( const ConvexSet set,
double  tol = 1e-12 
)
explicit

Constructs an affine subspace as the affine hull of another convex set.

This is done by finding a feasible point in the set, and then iteratively computing feasible vectors until we have a basis that spans the set. If you pass in a convex set whose points are matrix-valued (e.g. a Spectrahedron), then the affine subspace will work over a flattened representation of those coordinates. (So a Spectrahedron with n-by-n matrices will output an AffineSubspace with ambient dimension (n * (n+1)) / 2.)

tol sets the numerical precision of the computation. For each dimension, a pair of feasible points are constructed, so as to maximize the displacement in that dimension. If their displacement along that dimension is larger than tol, then the vector connecting the points is added as a basis vector.

Precondition
!set.IsEmpty()

◆ ~AffineSubspace()

~AffineSubspace ( )
final

Member Function Documentation

◆ AffineDimension()

int AffineDimension ( ) const

Returns the affine dimension of this set.

For an affine subspace, this is simply the number of columns in the basis_ matrix. A point will have affine dimension zero.

◆ basis()

const Eigen::MatrixXd& basis ( ) const

Returns the basis in an n-by-m matrix, where n is the ambient dimension, and m is the number of vectors in the basis.

◆ ContainedIn()

bool ContainedIn ( const AffineSubspace other,
double  tol = 1e-15 
) const

Returns true if this AffineSubspace is contained in other.

This is computed by checking if translation() is in other and then checking if each basis vector is in the span of the basis of other. The latter step requires finding a least-squares solution, so a nonzero tolerance (tol) is almost always necessary. (You may have to adjust the default tolerance depending on the dimension of your space and the scale of your basis vectors.)

◆ IsNearlyEqualTo()

bool IsNearlyEqualTo ( const AffineSubspace other,
double  tol = 1e-15 
) const

Returns true if the two AffineSubspaces describe the same set, by checking that each set is contained in the other.

◆ operator=() [1/2]

AffineSubspace& operator= ( AffineSubspace &&  )
default

◆ operator=() [2/2]

AffineSubspace& operator= ( const AffineSubspace )
default

◆ OrthogonalComplementBasis()

Eigen::MatrixXd OrthogonalComplementBasis ( ) const

Returns an orthonormal basis of the vector subspace which is orthogonal to this AffineSubspace.

◆ Project()

Eigen::MatrixXd Project ( const Eigen::Ref< const Eigen::MatrixXd > &  x) const

Computes the orthogonal projection of x onto the AffineSubspace.

This is achieved by finding the least squares solution y for y to x = translation_

  • basis_*y, and returning translation_ + basis_*y. Each column of the input should be a vector in the ambient space, and the corresponding column of the output will be its projection onto the affine subspace.
    Precondition
    x.rows() == ambient_dimension() (Deprecated.)
    Deprecated:
    Projection has moved to `ConvexSet`; use `Projection()` instead.
    This will be removed from Drake on or after 2024-08-01.

◆ Serialize()

void Serialize ( Archive *  a)

Passes this object to an Archive.

Refer to YAML Serialization for background.

◆ ToGlobalCoordinates()

Eigen::MatrixXd ToGlobalCoordinates ( const Eigen::Ref< const Eigen::MatrixXd > &  y) const

Given a point y in the basis of the AffineSubspace, with the zero point at translation_, returns the coordinates of y in the standard basis of the ambient space.

If the AffineSubspace is a point, it has an empty basis, so the only possible local coordinates are also empty (and should be passed in as a length-zero vector). Each column of the input should be a vector in the affine subspace, represented in its local coordinates, and the corresponding column of the output will be its representation in the coordinate system of the ambient space.

Precondition
y.rows() == AffineDimension()

◆ ToLocalCoordinates()

Eigen::MatrixXd ToLocalCoordinates ( const Eigen::Ref< const Eigen::MatrixXd > &  x) const

Given a point x in the standard basis of the ambient space, returns the coordinates of x in the basis of the AffineSubspace, with the zero point at translation_.

The component of x that is orthogonal to the AffineSubspace (if it exists) is discarded, so ToGlobalCoordinates(ToLocalCoordinates(x)) is equivalent to Project(x). Note that if the AffineSubspace is a point, the basis is empty, so the local coordinates will also be empty (and returned as a length-zero vector). Each column of the input should be a vector in the ambient space, and the corresponding column of the output will be its representation in the local coordinates of the affine subspace.

Precondition
x.rows() == ambient_dimension()

◆ translation()

const Eigen::VectorXd& translation ( ) const

Returns the translation as a length n vector.


The documentation for this class was generated from the following file: