Namespaces
namespace	_core
namespace	example_clock
namespace	example_clock_sched_fifo
namespace	example_robot_driver_subclass

Classes
class	Clock
	Clock utility for timing and statistics in control loops. More...
class	Object
	Base class for SAS objects. More...
class	RobotDriver
	Abstract interface for robot hardware drivers. More...
class	RobotDriverExample
	Simple in-memory RobotDriver implementation for testing. More...
struct	RobotDriverExampleConfiguration
	Configuration for the RobotDriverExample. More...
class	ShutdownSignaler
	Shutdown coordinator. More...
class	ThreadManager

Enumerations
enum class	Statistics { Mean }
	Statistical measures supported by sas_core utilities. More...

Functions
std::vector< double >	vectorxd_to_std_vector_double (const Eigen::VectorXd &vectorxd)
	Convert an Eigen::VectorXd to a std::vector<double>.
std::vector< int >	vectorxi_to_std_vector_int (const Eigen::VectorXi &vectorxi)
	Convert an Eigen::VectorXi to a std::vector<int>.
Eigen::VectorXd	std_vector_double_to_vectorxd (std::vector< double > std_vector_double)
	Convert a std::vector<double> to an Eigen::VectorXd.
Eigen::VectorXi	std_vector_int_to_vectorxi (std::vector< int > std_vector_int)
	Convert a std::vector<int> to an Eigen::VectorXi.
DQ	std_vector_double_to_dq (const std::vector< double > &std_vector_double)
	Convert a std::vector<double> to a DQ (dual quaternion) object.
template<class T>
constexpr T	incremental_mean (const T &current_mean, const int &current_number_of_samples, const T &new_sample)
	incremental_mean a simple implementation of incremental mean, for the many cases in which keeping a vector of all values would be impractical.
Eigen::VectorXd	concatenate (const Eigen::VectorXd &a, const Eigen::VectorXd &b)
	Concatenate two vectors by appending b after a.
Eigen::VectorXd	concatenate (const std::vector< Eigen::VectorXd > &as)
	Concatenate a list of vectors into a single vector.
Eigen::MatrixXd	vstack (const Eigen::MatrixXd &A, const Eigen::MatrixXd &B)
	Stack two matrices vertically (A above B).
Eigen::MatrixXd	block_diag (const std::vector< Eigen::MatrixXd > &As)
	Create a block-diagonal matrix from a list of matrices.
std::vector< Eigen::VectorXd >	split (const Eigen::VectorXd &a, const std::vector< int > &ns)
	Split a vector into pieces with sizes specified by ns.

Detailed Description

@file __init__.py
@brief Package entry for the sas_core Python bindings.

This module re-exports the primary Python bindings provided by the
compiled extension module :mod:`marinholab.sas.core._core`.

- Clock: high-resolution timing and sleep class.
- Statistics: enumeration for statistical types.
- RobotDriver: abstract robot driver interface that can be inherited by Python classes.
- ShutdownSignaler: request and wait for orderly shutdown.

The concrete implementations live in the compiled extension module
``marinholab.sas.core._core``.

Enumeration Type Documentation

◆ Statistics

enum class marinholab::sas::core::Statistics

strong

Statistical measures supported by sas_core utilities.

Enumeration of lightweight statistics that classes and functions may compute (for example, Clock statistics). Add new entries here as new statistics are supported.

Function Documentation

◆ block_diag()

Eigen::MatrixXd marinholab::sas::core::block_diag ( const std::vector< Eigen::MatrixXd > & As )

Create a block-diagonal matrix from a list of matrices.

block_diag creates a block diagonal matrix using an input of std::vector<Eigen::MatrixXd>. e.g. if As= [A, B, C], then block_diag(As) = |A 0 0| |0 B 0| |0 0 C|

Parameters

As	Vector of matrices to place on the block diagonal.

Returns: Block-diagonal matrix containing the input matrices along its diagonal.

Parameters

As	the std::vector<Eigen::MatrixXd> contaning the matrix to form the block diagonal matrix.

Returns: the block diagonal matrix.

◆ concatenate() [1/2]

Eigen::VectorXd marinholab::sas::core::concatenate	(	const Eigen::VectorXd &	a,
		const Eigen::VectorXd &	b )

Concatenate two vectors by appending b after a.

concatenate two Eigen::VectorXd.

Parameters

a	First vector.
b	Second vector.

Returns: Concatenated vector containing all elements of a followed by b.

Parameters

a	a Eigen::VectorXd.
b	a Eigen::VectorXd.

Returns: the result of the concatenated vectors.

◆ concatenate() [2/2]

Eigen::VectorXd marinholab::sas::core::concatenate ( const std::vector< Eigen::VectorXd > & as )

Concatenate a list of vectors into a single vector.

concatenate a std::vector of Eigen::VectorXd.

Parameters

as	Vector of vectors to concatenate in order.

Returns: Concatenated vector containing the elements of each input vector in order.

Parameters

a	an std::vector of Eigen::VectorXd.

Returns: the result of the concatenated vectors.

◆ incremental_mean()

template<class T>

T marinholab::sas::core::incremental_mean	(	const T &	current_mean,
		const int &	current_number_of_samples,
		const T &	new_sample )

constexpr

incremental_mean a simple implementation of incremental mean, for the many cases in which keeping a vector of all values would be impractical.

Parameters

current_mean	the current value of the mean.
current_number_of_samples	the current number of samples, not considering the new_sample.
new_sample	the new sample that will change the mean.

Exceptions

std::range_error if current_number_of_samples is negative.

Returns: the incremental mean, considering the new_sample.

◆ split()

std::vector< Eigen::VectorXd > marinholab::sas::core::split	(	const Eigen::VectorXd &	a,
		const std::vector< int > &	ns )

Split a vector into pieces with sizes specified by ns.

split splits the input Eigen::VectorXd as into a set of subvectors defined by ns.

Parameters

a	Vector to split.
ns	Sizes of each piece; their sum must equal a.size().

Returns: Vector containing the split Eigen::VectorXd pieces.

Parameters

as	the Eigen::VectorXd to be split.
ns	the sizes of the subvectors.

Returns: an std::vector<Eigen::VectorXd> of the splitted vectors.

◆ std_vector_double_to_dq()

DQ marinholab::sas::core::std_vector_double_to_dq ( const std::vector< double > & std_vector_double )

Convert a std::vector<double> to a DQ (dual quaternion) object.

Parameters

std_vector_double Source std::vector<double> containing the DQ coefficients.

Returns: DQ constructed from the provided coefficients.

◆ std_vector_double_to_vectorxd()

Eigen::VectorXd marinholab::sas::core::std_vector_double_to_vectorxd ( std::vector< double > std_vector_double )

Convert a std::vector<double> to an Eigen::VectorXd.

Parameters

std_vector_double Source std::vector<double>.

Returns: Eigen::VectorXd containing the same elements.

◆ std_vector_int_to_vectorxi()

Eigen::VectorXi marinholab::sas::core::std_vector_int_to_vectorxi ( std::vector< int > std_vector_int )

Convert a std::vector<int> to an Eigen::VectorXi.

Parameters

std_vector_int Source std::vector<int>.

Returns: Eigen::VectorXi containing the same elements.

◆ vectorxd_to_std_vector_double()

std::vector< double > marinholab::sas::core::vectorxd_to_std_vector_double ( const Eigen::VectorXd & vectorxd )

Convert an Eigen::VectorXd to a std::vector<double>.

Parameters

vectorxd Source Eigen vector.

Returns: std::vector<double> containing the same elements in order.

◆ vectorxi_to_std_vector_int()

std::vector< int > marinholab::sas::core::vectorxi_to_std_vector_int ( const Eigen::VectorXi & vectorxi )

Convert an Eigen::VectorXi to a std::vector<int>.

Parameters

vectorxi Source Eigen integer vector.

Returns: std::vector<int> containing the same elements in order.

◆ vstack()

Eigen::MatrixXd marinholab::sas::core::vstack	(	const Eigen::MatrixXd &	A,
		const Eigen::MatrixXd &	B )

Stack two matrices vertically (A above B).

vstack vertically (row-wise) stack two Eigen::MatrixXd.

Parameters

A	Top matrix.
B	Bottom matrix.

Returns: Matrix formed by stacking A on top of B. Columns must match.

Exceptions

std::range_error if A and B have different numbers of columns.

Parameters

A	the first Eigen::MatrixXd.
B	the second Eigen::MatrixXd.

Returns: the vstacked Eigen::MatrixXd.

Exceptions

a	std::range_error if A and B don't have the same number of columns.

Note: returns an empty matrix if both arguments are empty or return the other argument of only one of the arguments is empty.

Namespaces

Classes

Enumerations

Functions

Detailed Description

Enumeration Type Documentation

◆ Statistics

Function Documentation

◆ block_diag()

◆ concatenate() [1/2]

◆ concatenate() [2/2]

◆ incremental_mean()

◆ split()

◆ std_vector_double_to_dq()

◆ std_vector_double_to_vectorxd()

◆ std_vector_int_to_vectorxi()

◆ vectorxd_to_std_vector_double()

◆ vectorxi_to_std_vector_int()

◆ vstack()