drake::schema Namespace Reference

Classes
class	Deterministic
	A single deterministic value. More...
class	DeterministicVector
	A single deterministic vector value. More...
class	Distribution
	Base class for a single distribution, to be used with YAML archives. More...
class	DistributionVector
	Base class for a vector of distributions, to be used with YAML archives. More...
class	Gaussian
	A gaussian distribution with mean and stddev. More...
class	GaussianVector
	A gaussian distribution with vector mean and vector or scalar stddev. More...
class	Rotation
	A specification for an SO(3) rotation, to be used for serialization purposes, e.g., to define stochastic scenarios. More...
class	Transform
	A specification for a 3d rotation and translation, optionally with respect to a base frame. More...
class	Uniform
	A uniform distribution with min inclusive and max exclusive. More...
class	UniformDiscrete
	Chooses from among discrete values with equal probability. More...
class	UniformVector
	A uniform distribution with vector min inclusive and vector max exclusive. More...

Typedefs
using	DistributionVariant
	Variant over all kinds of distributions.
template<int Size>
using	DistributionVectorVariant
	Variant over all kinds of vector distributions.
using	DistributionVectorVariantX = DistributionVectorVariant<Eigen::Dynamic>
	DistributionVectorVariant that permits any vector size dynamically.

Functions
std::unique_ptr< Distribution >	ToDistribution (const DistributionVariant &var)
	Copies the given variant into a Distribution base class.
double	Sample (const DistributionVariant &var, drake::RandomGenerator *generator)
	Like Distribution::Sample, but on a DistributionVariant instead.
double	Mean (const DistributionVariant &var)
	Like Distribution::Mean, but on a DistributionVariant instead.
drake::symbolic::Expression	ToSymbolic (const DistributionVariant &var)
	Like Distribution::ToSymbolic, but on a DistributionVariant instead.
Eigen::VectorXd	Sample (const std::vector< DistributionVariant > &vec, drake::RandomGenerator *generator)
	Like Distribution::Sample, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.
Eigen::VectorXd	Mean (const std::vector< DistributionVariant > &vec)
	Like Distribution::Mean, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.
drake::VectorX< drake::symbolic::Expression >	ToSymbolic (const std::vector< DistributionVariant > &vec)
	Like Distribution::ToSymbolic, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.
bool	IsDeterministic (const DistributionVariant &var)
	Returns true iff var is set to a deterministic value.
double	GetDeterministicValue (const DistributionVariant &var)
	If var is deterministic, retrieves its value.
template<int Size>
std::unique_ptr< DistributionVector >	ToDistributionVector (const DistributionVectorVariant< Size > &vec)
	Copies the given variant into a DistributionVector base class.
template<int Size>
bool	IsDeterministic (const DistributionVectorVariant< Size > &vec)
	Returns true iff all of vec's elements are set to a deterministic value.
template<int Size>
Eigen::VectorXd	GetDeterministicValue (const DistributionVectorVariant< Size > &vec)
	If vec is deterministic, retrieves its value.

Typedef Documentation

DistributionVariant

using DistributionVariant

Initial value:

 
    std::variant<double, Deterministic, Gaussian, Uniform, UniformDiscrete>

Variant over all kinds of distributions.

DistributionVectorVariant

template<int Size>

using DistributionVectorVariant

Initial value:

 std::variant<
    drake::Vector<double, Size>,  
    DeterministicVector<Size>,    
    GaussianVector<Size>,         
    UniformVector<Size>,          
    std::conditional_t<(Size == Eigen::Dynamic || Size == 1), Deterministic,
                       internal::InvalidVariantSelection<Deterministic>>,
    std::conditional_t<(Size == Eigen::Dynamic || Size == 1), Gaussian,
                       internal::InvalidVariantSelection<Gaussian>>,
    std::conditional_t<(Size == Eigen::Dynamic || Size == 1), Uniform,
                       internal::InvalidVariantSelection<Uniform>>>

Variant over all kinds of vector distributions.

If the Size parameter allows for 1-element vectors (i.e, is either 1 or Eigen::Dynamic), then this variant also offers the single distribution types (Deterministic, Gaussian, Uniform). If the Size parameter is 2 or greater, the single distribution types are not allowed.

Template Parameters

Size	rows at compile time (max 6) or else Eigen::Dynamic.

DistributionVectorVariantX

using DistributionVectorVariantX = DistributionVectorVariant<Eigen::Dynamic>

DistributionVectorVariant that permits any vector size dynamically.

Function Documentation

GetDeterministicValue() [1/2]

double GetDeterministicValue

(

const DistributionVariant &

var

)

If var is deterministic, retrieves its value.

Exceptions

std::exception

if var is not deterministic.

GetDeterministicValue() [2/2]

template<int Size>

Eigen::VectorXd GetDeterministicValue

(

const DistributionVectorVariant< Size > &

vec

)

If vec is deterministic, retrieves its value.

Exceptions

std::exception

if vec is not deterministic.

Template Parameters

Size	rows at compile time (max 6) or else Eigen::Dynamic.

IsDeterministic() [1/2]

bool IsDeterministic

(

const DistributionVariant &

var

)

Returns true iff var is set to a deterministic value.

IsDeterministic() [2/2]

template<int Size>

bool IsDeterministic

(

const DistributionVectorVariant< Size > &

vec

)

Returns true iff all of vec's elements are set to a deterministic value.

Template Parameters

Size	rows at compile time (max 6) or else Eigen::Dynamic.

Mean() [1/2]

double Mean

(

const DistributionVariant &

var

)

Like Distribution::Mean, but on a DistributionVariant instead.

Mean() [2/2]

Eigen::VectorXd Mean

(

const std::vector< DistributionVariant > &

vec

)

Like Distribution::Mean, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.

Sample() [1/2]

double Sample	(	const DistributionVariant &	var,
		drake::RandomGenerator *	generator )

Like Distribution::Sample, but on a DistributionVariant instead.

Sample() [2/2]

Eigen::VectorXd Sample	(	const std::vector< DistributionVariant > &	vec,
		drake::RandomGenerator *	generator )

Like Distribution::Sample, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.

ToDistribution()

std::unique_ptr< Distribution > ToDistribution

(

const DistributionVariant &

var

)

Copies the given variant into a Distribution base class.

ToDistributionVector()

template<int Size>

std::unique_ptr< DistributionVector > ToDistributionVector

(

const DistributionVectorVariant< Size > &

vec

)

Copies the given variant into a DistributionVector base class.

Template Parameters

Size	rows at compile time (max 6) or else Eigen::Dynamic.

ToSymbolic() [1/2]

drake::symbolic::Expression ToSymbolic

(

const DistributionVariant &

var

)

Like Distribution::ToSymbolic, but on a DistributionVariant instead.

ToSymbolic() [2/2]

drake::VectorX< drake::symbolic::Expression > ToSymbolic

(

const std::vector< DistributionVariant > &

vec

)

Like Distribution::ToSymbolic, but elementwise over a collection of possibly-heterogenous DistributionVariant instead.