PointCloud represents the base class in PCL for storing collections of 3D points. More...

#include <pcl/point_cloud.h>

Public Types
using	PointType = PointT
using	VectorType = std::vector<PointT, Eigen::aligned_allocator<PointT> >
using	CloudVectorType = std::vector<PointCloud<PointT>, Eigen::aligned_allocator<PointCloud<PointT> > >
using	Ptr = shared_ptr<PointCloud<PointT> >
using	ConstPtr = shared_ptr<const PointCloud<PointT> >
using	value_type = PointT
using	reference = PointT&
using	const_reference = const PointT&
using	difference_type = typename VectorType::difference_type
using	size_type = typename VectorType::size_type
using	iterator = typename VectorType::iterator
using	const_iterator = typename VectorType::const_iterator
using	reverse_iterator = typename VectorType::reverse_iterator
using	const_reverse_iterator = typename VectorType::const_reverse_iterator

Public Member Functions
	PointCloud ()=default
	Default constructor.
	PointCloud (const PointCloud< PointT > &pc, const Indices &indices)
	Copy constructor from point cloud subset.
	PointCloud (std::uint32_t width_, std::uint32_t height_, const PointT &value_=PointT())
	Allocate constructor from point cloud subset.
PointCloud &	operator+= (const PointCloud &rhs)
	Add a point cloud to the current cloud.
PointCloud	operator+ (const PointCloud &rhs)
	Add a point cloud to another cloud.
const PointT &	at (int column, int row) const
	Obtain the point given by the (column, row) coordinates.
PointT &	at (int column, int row)
	Obtain the point given by the (column, row) coordinates.
const PointT &	operator() (std::size_t column, std::size_t row) const
	Obtain the point given by the (column, row) coordinates.
PointT &	operator() (std::size_t column, std::size_t row)
	Obtain the point given by the (column, row) coordinates.
bool	isOrganized () const
	Return whether a dataset is organized (e.g., arranged in a structured grid).
Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap (int dim, int stride, int offset)
	Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.
const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap (int dim, int stride, int offset) const
	Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.
Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap ()
const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap () const
iterator	begin () noexcept
iterator	end () noexcept
const_iterator	begin () const noexcept
const_iterator	end () const noexcept
const_iterator	cbegin () const noexcept
const_iterator	cend () const noexcept
reverse_iterator	rbegin () noexcept
reverse_iterator	rend () noexcept
const_reverse_iterator	rbegin () const noexcept
const_reverse_iterator	rend () const noexcept
const_reverse_iterator	crbegin () const noexcept
const_reverse_iterator	crend () const noexcept
std::size_t	size () const
index_t	max_size () const noexcept
void	reserve (std::size_t n)
bool	empty () const
PointT *	data () noexcept
const PointT *	data () const noexcept
void	resize (std::size_t count)
	Resizes the container to contain count elements.
void	resize (uindex_t new_width, uindex_t new_height)
	Resizes the container to contain new_width * new_height elements.
void	resize (index_t count, const PointT &value)
	Resizes the container to contain count elements.
void	resize (index_t new_width, index_t new_height, const PointT &value)
	Resizes the container to contain count elements.
const PointT &	operator[] (std::size_t n) const
PointT &	operator[] (std::size_t n)
const PointT &	at (std::size_t n) const
PointT &	at (std::size_t n)
const PointT &	front () const
PointT &	front ()
const PointT &	back () const
PointT &	back ()
void	assign (index_t count, const PointT &value)
	Replaces the points with count copies of value.
void	assign (index_t new_width, index_t new_height, const PointT &value)
	Replaces the points with new_width * new_height copies of value.
template<class InputIterator>
void	assign (InputIterator first, InputIterator last)
	Replaces the points with copies of those in the range [first, last).
template<class InputIterator>
void	assign (InputIterator first, InputIterator last, index_t new_width)
	Replaces the points with copies of those in the range [first, last).
void	assign (std::initializer_list< PointT > ilist)
	Replaces the points with the elements from the initializer list ilist.
void	assign (std::initializer_list< PointT > ilist, index_t new_width)
	Replaces the points with the elements from the initializer list ilist.
void	push_back (const PointT &pt)
	Insert a new point in the cloud, at the end of the container.
void	transient_push_back (const PointT &pt)
	Insert a new point in the cloud, at the end of the container.
template<class... Args>
reference	emplace_back (Args &&...args)
	Emplace a new point in the cloud, at the end of the container.
template<class... Args>
reference	transient_emplace_back (Args &&...args)
	Emplace a new point in the cloud, at the end of the container.
iterator	insert (iterator position, const PointT &pt)
	Insert a new point in the cloud, given an iterator.
iterator	transient_insert (iterator position, const PointT &pt)
	Insert a new point in the cloud, given an iterator.
void	insert (iterator position, std::size_t n, const PointT &pt)
	Insert a new point in the cloud N times, given an iterator.
void	transient_insert (iterator position, std::size_t n, const PointT &pt)
	Insert a new point in the cloud N times, given an iterator.
template<class InputIterator>
void	insert (iterator position, InputIterator first, InputIterator last)
	Insert a new range of points in the cloud, at a certain position.
template<class InputIterator>
void	transient_insert (iterator position, InputIterator first, InputIterator last)
	Insert a new range of points in the cloud, at a certain position.
template<class... Args>
iterator	emplace (iterator position, Args &&...args)
	Emplace a new point in the cloud, given an iterator.
template<class... Args>
iterator	transient_emplace (iterator position, Args &&...args)
	Emplace a new point in the cloud, given an iterator.
iterator	erase (iterator position)
	Erase a point in the cloud.
iterator	transient_erase (iterator position)
	Erase a point in the cloud.
iterator	erase (iterator first, iterator last)
	Erase a set of points given by a (first, last) iterator pair.
iterator	transient_erase (iterator first, iterator last)
	Erase a set of points given by a (first, last) iterator pair.
void	swap (PointCloud< PointT > &rhs)
	Swap a point cloud with another cloud.
void	clear ()
	Removes all points in a cloud and sets the width and height to 0.
Ptr	makeShared () const
	Copy the cloud to the heap and return a smart pointer Note that deep copy is performed, so avoid using this function on non-empty clouds.

Static Public Member Functions
static bool	concatenate (pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2)
static bool	concatenate (const pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2, pcl::PointCloud< PointT > &cloud_out)

Public Attributes
pcl::PCLHeader	header
	The point cloud header.
std::vector< PointT, Eigen::aligned_allocator< PointT > >	points
	The point data.
std::uint32_t	width = 0
	The point cloud width (if organized as an image-structure).
std::uint32_t	height = 0
	The point cloud height (if organized as an image-structure).
bool	is_dense = true
	True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
Eigen::Vector4f	sensor_origin_ = Eigen::Vector4f::Zero ()
	Sensor acquisition pose (origin/translation).
Eigen::Quaternionf	sensor_orientation_ = Eigen::Quaternionf::Identity ()
	Sensor acquisition pose (rotation).

Detailed Description

template<typename PointT>
class pcl::PointCloud< PointT >

PointCloud represents the base class in PCL for storing collections of 3D points.

The class is templated, which means you need to specify the type of data that it should contain. For example, to create a point cloud that holds 4 random XYZ data points, use:

pcl::PointCloud<pcl::PointXYZ> cloud;
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));

The PointCloud class contains the following elements:

width - specifies the width of the point cloud dataset in the number of points. WIDTH has two meanings:
- it can specify the total number of points in the cloud (equal with POINTS see below) for unorganized datasets;
- it can specify the width (total number of points in a row) of an organized point cloud dataset. Mandatory.
height - specifies the height of the point cloud dataset in the number of points. HEIGHT has two meanings:
- it can specify the height (total number of rows) of an organized point cloud dataset;
- it is set to 1 for unorganized datasets (thus used to check whether a dataset is organized or not). Mandatory.
points - the data array where all points of type PointT are stored. Mandatory.
is_dense - specifies if all the data in points is finite (true), or whether it might contain Inf/NaN values (false). Mandatory.
sensor_origin_ - specifies the sensor acquisition pose (origin/translation). Optional.
sensor_orientation_ - specifies the sensor acquisition pose (rotation). Optional.

Author: Patrick Mihelich, Radu B. Rusu

Definition at line 173 of file point_cloud.h.

Member Typedef Documentation

◆ CloudVectorType

template<typename PointT>

using pcl::PointCloud< PointT >::CloudVectorType = std::vector<PointCloud<PointT>, Eigen::aligned_allocator<PointCloud<PointT> > >

Definition at line 413 of file point_cloud.h.

◆ const_iterator

template<typename PointT>

using pcl::PointCloud< PointT >::const_iterator = typename VectorType::const_iterator

Definition at line 427 of file point_cloud.h.

◆ const_reference

template<typename PointT>

using pcl::PointCloud< PointT >::const_reference = const PointT&

Definition at line 421 of file point_cloud.h.

◆ const_reverse_iterator

template<typename PointT>

using pcl::PointCloud< PointT >::const_reverse_iterator = typename VectorType::const_reverse_iterator

Definition at line 429 of file point_cloud.h.

◆ ConstPtr

template<typename PointT>

using pcl::PointCloud< PointT >::ConstPtr = shared_ptr<const PointCloud<PointT> >

Definition at line 415 of file point_cloud.h.

◆ difference_type

template<typename PointT>

using pcl::PointCloud< PointT >::difference_type = typename VectorType::difference_type

Definition at line 422 of file point_cloud.h.

◆ iterator

template<typename PointT>

using pcl::PointCloud< PointT >::iterator = typename VectorType::iterator

Definition at line 426 of file point_cloud.h.

◆ PointType

template<typename PointT>

using pcl::PointCloud< PointT >::PointType = PointT

Definition at line 411 of file point_cloud.h.

◆ Ptr

template<typename PointT>

using pcl::PointCloud< PointT >::Ptr = shared_ptr<PointCloud<PointT> >

Definition at line 414 of file point_cloud.h.

◆ reference

template<typename PointT>

using pcl::PointCloud< PointT >::reference = PointT&

Definition at line 420 of file point_cloud.h.

◆ reverse_iterator

template<typename PointT>

using pcl::PointCloud< PointT >::reverse_iterator = typename VectorType::reverse_iterator

Definition at line 428 of file point_cloud.h.

◆ size_type

template<typename PointT>

using pcl::PointCloud< PointT >::size_type = typename VectorType::size_type

Definition at line 423 of file point_cloud.h.

◆ value_type

template<typename PointT>

using pcl::PointCloud< PointT >::value_type = PointT

Definition at line 419 of file point_cloud.h.

◆ VectorType

template<typename PointT>

using pcl::PointCloud< PointT >::VectorType = std::vector<PointT, Eigen::aligned_allocator<PointT> >

Definition at line 412 of file point_cloud.h.

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

template<typename PointT>

pcl::PointCloud< PointT >::PointCloud ( )

default

Default constructor.

Sets is_dense to true, width and height to 0, and the sensor_origin_ and sensor_orientation_ to identity.

◆ PointCloud() [2/3]

template<typename PointT>

pcl::PointCloud< PointT >::PointCloud	(	const PointCloud< PointT > &	pc,
		const Indices &	indices )

inline

Copy constructor from point cloud subset.

Parameters

[in]	pc	the cloud to copy into this
[in]	indices	the subset to copy

Definition at line 186 of file point_cloud.h.

◆ PointCloud() [3/3]

template<typename PointT>

pcl::PointCloud< PointT >::PointCloud	(	std::uint32_t	width_,
		std::uint32_t	height_,
		const PointT &	value_ = PointT () )

inline

Allocate constructor from point cloud subset.

Parameters

[in]	width_	the cloud width
[in]	height_	the cloud height
[in]	value_	default value

Definition at line 202 of file point_cloud.h.

Member Function Documentation

◆ assign() [1/6]

template<typename PointT>

void pcl::PointCloud< PointT >::assign	(	index_t	count,
		const PointT &	value )

inline

Replaces the points with count copies of value.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	count	new size of the point cloud
[in]	value	value each point of the cloud should have

Definition at line 549 of file point_cloud.h.

Referenced by pcl::PointCloud< PointInT >::assign(), pcl::PointCloud< PointInT >::assign(), pcl::transformPointCloud(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ assign() [2/6]

template<typename PointT>

void pcl::PointCloud< PointT >::assign	(	index_t	new_width,
		index_t	new_height,
		const PointT &	value )

inline

Replaces the points with new_width * new_height copies of value.

Parameters

[in]	new_width	new width of the point cloud
[in]	new_height	new height of the point cloud
[in]	value	value each point of the cloud should have

Definition at line 563 of file point_cloud.h.

◆ assign() [3/6]

template<typename PointT>

template<class InputIterator>

void pcl::PointCloud< PointT >::assign	(	InputIterator	first,
		InputIterator	last )

inline

Replaces the points with copies of those in the range [first, last).

The behavior is undefined if either argument is an iterator into *this

Note: This breaks the organized structure of the cloud by setting the height to 1!

Definition at line 579 of file point_cloud.h.

◆ assign() [4/6]

template<typename PointT>

template<class InputIterator>

void pcl::PointCloud< PointT >::assign	(	InputIterator	first,
		InputIterator	last,
		index_t	new_width )

inline

Replaces the points with copies of those in the range [first, last).

The behavior is undefined if either argument is an iterator into *this

Note: This calculates the height based on size and width provided. This means the assignment happens even if the size is not perfectly divisible by width

Parameters

[in]	first,last	the range from which the points are copied
[in]	new_width	new width of the point cloud

Definition at line 597 of file point_cloud.h.

◆ assign() [5/6]

template<typename PointT>

void pcl::PointCloud< PointT >::assign ( std::initializer_list< PointT > ilist )

inline

Replaces the points with the elements from the initializer list ilist.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Definition at line 624 of file point_cloud.h.

◆ assign() [6/6]

template<typename PointT>

void pcl::PointCloud< PointT >::assign	(	std::initializer_list< PointT >	ilist,
		index_t	new_width )

inline

Replaces the points with the elements from the initializer list ilist.

Note: This calculates the height based on size and width provided. This means the assignment happens even if the size is not perfectly divisible by width

Parameters

[in]	ilist	initializer list from which the points are copied
[in]	new_width	new width of the point cloud

Definition at line 639 of file point_cloud.h.

◆ at() [1/4]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::at	(	int	column,
		int	row )

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 277 of file point_cloud.h.

◆ at() [2/4]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::at	(	int	column,
		int	row ) const

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 263 of file point_cloud.h.

Referenced by pcl::filters::Pyramid< PointT >::compute(), pcl::occlusion_reasoning::filter(), pcl::occlusion_reasoning::filter(), pcl::occlusion_reasoning::getOccludedCloud(), and pcl::PointCloudDepthAndRGBtoXYZRGBA().

◆ at() [3/4]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::at ( std::size_t n )

inline

Definition at line 535 of file point_cloud.h.

◆ at() [4/4]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::at ( std::size_t n ) const

inline

Definition at line 534 of file point_cloud.h.

◆ back() [1/2]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::back ( )

inline

Definition at line 539 of file point_cloud.h.

◆ back() [2/2]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::back ( ) const

inline

Definition at line 538 of file point_cloud.h.

◆ begin() [1/2]

template<typename PointT>

const_iterator pcl::PointCloud< PointT >::begin ( ) const

inlinenoexcept

Definition at line 432 of file point_cloud.h.

◆ begin() [2/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::begin ( )

inlinenoexcept

Definition at line 430 of file point_cloud.h.

Referenced by pcl::PointCloud< PointInT >::concatenate(), pcl::common::deleteCols(), pcl::common::deleteRows(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::getFeaturePointCloud(), pcl::SupervoxelClustering< PointT >::getLabeledCloud(), pcl::SupervoxelClustering< PointT >::getLabeledVoxelCloud(), pcl::SupervoxelClustering< PointT >::makeSupervoxelNormalCloud(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::transformPointCloud(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ cbegin()

template<typename PointT>

const_iterator pcl::PointCloud< PointT >::cbegin ( ) const

inlinenoexcept

Definition at line 434 of file point_cloud.h.

Referenced by pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::readRange(), pcl::MinCutSegmentation< PointT >::setBackgroundPoints(), and pcl::MinCutSegmentation< PointT >::setForegroundPoints().

◆ cend()

template<typename PointT>

const_iterator pcl::PointCloud< PointT >::cend ( ) const

inlinenoexcept

Definition at line 435 of file point_cloud.h.

Referenced by pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::readRange(), pcl::MinCutSegmentation< PointT >::setBackgroundPoints(), and pcl::MinCutSegmentation< PointT >::setForegroundPoints().

◆ clear()

template<typename PointT>

void pcl::PointCloud< PointT >::clear ( )

inline

Removes all points in a cloud and sets the width and height to 0.

Definition at line 886 of file point_cloud.h.

Referenced by pcl::DisparityMapConverter< PointT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::VoxelGridCovariance< PointT >::getDisplayCloud(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), and pcl::SegmentDifferences< PointT >::segment().

◆ concatenate() [1/2]

template<typename PointT>

bool pcl::PointCloud< PointT >::concatenate	(	const pcl::PointCloud< PointT > &	cloud1,
		const pcl::PointCloud< PointT > &	cloud2,
		pcl::PointCloud< PointT > &	cloud_out )

inlinestatic

Definition at line 249 of file point_cloud.h.

◆ concatenate() [2/2]

template<typename PointT>

bool pcl::PointCloud< PointT >::concatenate	(	pcl::PointCloud< PointT > &	cloud1,
		const pcl::PointCloud< PointT > &	cloud2 )

inlinestatic

Definition at line 232 of file point_cloud.h.

Referenced by pcl::concatenate(), pcl::PointCloud< PointInT >::concatenate(), and pcl::PointCloud< PointInT >::operator+=().

◆ crbegin()

template<typename PointT>

const_reverse_iterator pcl::PointCloud< PointT >::crbegin ( ) const

inlinenoexcept

Definition at line 440 of file point_cloud.h.

◆ crend()

template<typename PointT>

const_reverse_iterator pcl::PointCloud< PointT >::crend ( ) const

inlinenoexcept

Definition at line 441 of file point_cloud.h.

◆ data() [1/2]

template<typename PointT>

const PointT * pcl::PointCloud< PointT >::data ( ) const

inlinenoexcept

Definition at line 449 of file point_cloud.h.

◆ data() [2/2]

template<typename PointT>

PointT * pcl::PointCloud< PointT >::data ( )

inlinenoexcept

Definition at line 448 of file point_cloud.h.

Referenced by pcl::copyPointCloud(), pcl::detail::copyPointCloudMemcpy(), pcl::fromPCLPointCloud2(), pcl::toPCLPointCloud2(), and pcl::transformPointCloud().

◆ emplace()

template<typename PointT>

template<class... Args>

iterator pcl::PointCloud< PointT >::emplace	(	iterator	position,
		Args &&...	args )

inline

Emplace a new point in the cloud, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	iterator before which the point will be emplaced
[in]	args	the parameters to forward to the point to construct

Returns: returns the new position iterator

Definition at line 794 of file point_cloud.h.

◆ emplace_back()

template<typename PointT>

template<class... Args>

reference pcl::PointCloud< PointT >::emplace_back ( Args &&... args )

inline

Emplace a new point in the cloud, at the end of the container.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] args the parameters to forward to the point to construct

Returns: reference to the emplaced point

Definition at line 687 of file point_cloud.h.

Referenced by pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures().

◆ empty()

template<typename PointT>

bool pcl::PointCloud< PointT >::empty ( ) const

inline

Definition at line 447 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::applyMorphologicalOperator(), pcl::compute3DCentroid(), pcl::computeCovarianceMatrix(), pcl::computeNDCentroid(), pcl::copyPointCloud(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segmentAndRefine(), pcl::SupervoxelClustering< PointT >::setInputCloud(), pcl::PCDWriter::writeASCII(), pcl::PCDWriter::writeASCII(), pcl::PCDWriter::writeBinary(), pcl::PCDWriter::writeBinary(), and pcl::PCDWriter::writeBinaryCompressed().

◆ end() [1/2]

template<typename PointT>

const_iterator pcl::PointCloud< PointT >::end ( ) const

inlinenoexcept

Definition at line 433 of file point_cloud.h.

◆ end() [2/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::end ( )

inlinenoexcept

Definition at line 431 of file point_cloud.h.

Referenced by pcl::PointCloud< PointInT >::concatenate(), pcl::common::deleteRows(), pcl::common::duplicateRows(), pcl::common::expandRows(), pcl::SupervoxelClustering< PointT >::getLabeledCloud(), pcl::SupervoxelClustering< PointT >::getLabeledVoxelCloud(), pcl::common::mirrorRows(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::transformPointCloud(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ erase() [1/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::erase	(	iterator	first,
		iterator	last )

inline

Erase a set of points given by a (first, last) iterator pair.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	first	where to start erasing points from
[in]	last	where to stop erasing points from

Returns: returns the new position iterator

Definition at line 848 of file point_cloud.h.

◆ erase() [2/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::erase ( iterator position )

inline

Erase a point in the cloud.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] position what data point to erase

Returns: returns the new position iterator

Definition at line 821 of file point_cloud.h.

Referenced by pcl::common::deleteCols(), and pcl::common::deleteRows().

◆ front() [1/2]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::front ( )

inline

Definition at line 537 of file point_cloud.h.

◆ front() [2/2]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::front ( ) const

inline

Definition at line 536 of file point_cloud.h.

◆ getMatrixXfMap() [1/4]

template<typename PointT>

Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap ( )

inline

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Note: This method is for advanced users only! Use with care!

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 375 of file point_cloud.h.

◆ getMatrixXfMap() [2/4]

template<typename PointT>

const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap ( ) const

inline

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Note: This method is for advanced users only! Use with care!

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 387 of file point_cloud.h.

◆ getMatrixXfMap() [3/4]

template<typename PointT>

Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap	(	int	dim,
		int	stride,
		int	offset )

inline

Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.

Note: This method is for advanced users only! Use with care!

Attention

Compile time flags used for Eigen might affect the dimension of the Eigen::Map returned. If Eigen is using row major storage, the matrix shape would be (number of Points X elements in a Point) else the matrix shape would be (elements in a Point X number of Points). Essentially,

Major direction: number of points in cloud
Minor direction: number of point dimensions By default, as of Eigen 3.3, Eigen uses Column major storage

Parameters

[in]	dim	the number of dimensions to consider for each point
[in]	stride	the number of values in each point (will be the number of values that separate two of the columns)
[in]	offset	the number of dimensions to skip from the beginning of each point (stride = offset + dim + x, where x is the number of dimensions to skip from the end of each point)

Note: for getting only XYZ coordinates out of PointXYZ use dim=3, stride=4 and offset=0 due to the alignment.

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 334 of file point_cloud.h.

◆ getMatrixXfMap() [4/4]

template<typename PointT>

const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap	(	int	dim,
		int	stride,
		int	offset ) const

inline

Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.

Note: This method is for advanced users only! Use with care!

Attention

Compile time flags used for Eigen might affect the dimension of the Eigen::Map returned. If Eigen is using row major storage, the matrix shape would be (number of Points X elements in a Point) else the matrix shape would be (elements in a Point X number of Points). Essentially,

Major direction: number of points in cloud
Minor direction: number of point dimensions By default, as of Eigen 3.3, Eigen uses Column major storage

Parameters

[in]	dim	the number of dimensions to consider for each point
[in]	stride	the number of values in each point (will be the number of values that separate two of the columns)
[in]	offset	the number of dimensions to skip from the beginning of each point (stride = offset + dim + x, where x is the number of dimensions to skip from the end of each point)

Note: for getting only XYZ coordinates out of PointXYZ use dim=3, stride=4 and offset=0 due to the alignment.

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 360 of file point_cloud.h.

◆ insert() [1/3]

template<typename PointT>

iterator pcl::PointCloud< PointT >::insert	(	iterator	position,
		const PointT &	pt )

inline

Insert a new point in the cloud, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the point
[in]	pt	the point to insert

Returns: returns the new position iterator

Definition at line 714 of file point_cloud.h.

Referenced by pcl::PointCloud< PointInT >::concatenate(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), and pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing().

◆ insert() [2/3]

template<typename PointT>

template<class InputIterator>

void pcl::PointCloud< PointT >::insert	(	iterator	position,
		InputIterator	first,
		InputIterator	last )

inline

Insert a new range of points in the cloud, at a certain position.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the data
[in]	first	where to start inserting the points from
[in]	last	where to stop inserting the points from

Definition at line 768 of file point_cloud.h.

◆ insert() [3/3]

template<typename PointT>

void pcl::PointCloud< PointT >::insert	(	iterator	position,
		std::size_t	n,
		const PointT &	pt )

inline

Insert a new point in the cloud N times, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the point
[in]	n	the number of times to insert the point
[in]	pt	the point to insert

Definition at line 742 of file point_cloud.h.

◆ isOrganized()

template<typename PointT>

bool pcl::PointCloud< PointT >::isOrganized ( ) const

inline

Return whether a dataset is organized (e.g., arranged in a structured grid).

Note: The height value must be different than 1 for a dataset to be organized.

Definition at line 311 of file point_cloud.h.

Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRectangle(), pcl::visualization::ImageViewer::addRectangle(), pcl::common::deleteCols(), pcl::common::duplicateColumns(), pcl::common::expandColumns(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::common::mirrorColumns(), and pcl::PCDGrabber< PointT >::publish().

◆ makeShared()

template<typename PointT>

Ptr pcl::PointCloud< PointT >::makeShared ( ) const

inline

Copy the cloud to the heap and return a smart pointer Note that deep copy is performed, so avoid using this function on non-empty clouds.

The changes of the returned cloud are not mirrored back to this one.

Returns: shared pointer to the copy of the cloud

Definition at line 899 of file point_cloud.h.

Referenced by pcl::Edge< PointInT, PointOutT >::canny(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::estimateFeatures(), and pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection().

◆ max_size()

template<typename PointT>

index_t pcl::PointCloud< PointT >::max_size ( ) const

inlinenoexcept

Definition at line 445 of file point_cloud.h.

◆ operator()() [1/2]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::operator()	(	std::size_t	column,
		std::size_t	row )

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 302 of file point_cloud.h.

◆ operator()() [2/2]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::operator()	(	std::size_t	column,
		std::size_t	row ) const

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 291 of file point_cloud.h.

◆ operator+()

template<typename PointT>

PointCloud pcl::PointCloud< PointT >::operator+ ( const PointCloud< PointT > & rhs )

inline

Add a point cloud to another cloud.

Parameters

[in] rhs the cloud to add to the current cloud

Returns: the new cloud as a concatenation of the current cloud and the new given cloud

Definition at line 226 of file point_cloud.h.

◆ operator+=()

template<typename PointT>

PointCloud & pcl::PointCloud< PointT >::operator+= ( const PointCloud< PointT > & rhs )

inline

Add a point cloud to the current cloud.

Parameters

[in] rhs the cloud to add to the current cloud

Returns: the new cloud as a concatenation of the current cloud and the new given cloud

Definition at line 215 of file point_cloud.h.

◆ operator[]() [1/2]

template<typename PointT>

PointT & pcl::PointCloud< PointT >::operator[] ( std::size_t n )

inline

Definition at line 533 of file point_cloud.h.

◆ operator[]() [2/2]

template<typename PointT>

const PointT & pcl::PointCloud< PointT >::operator[] ( std::size_t n ) const

inline

Definition at line 532 of file point_cloud.h.

◆ push_back()

template<typename PointT>

void pcl::PointCloud< PointT >::push_back ( const PointT & pt )

inline

Insert a new point in the cloud, at the end of the container.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] pt the point to insert

Definition at line 664 of file point_cloud.h.

Referenced by pcl::geometry::MeshBase< PolygonMesh< MeshTraitsT >, MeshTraitsT, PolygonMeshTag >::addData(), pcl::MovingLeastSquares< PointInT, PointOutT >::addProjectedPointNormal(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::MarchingCubes< PointNT >::createSurface(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::VoxelGridCovariance< PointT >::getDisplayCloud(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::PointCloudRGBtoI(), pcl::PointCloudRGBtoI(), pcl::PointCloudXYZHSVtoXYZRGB(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), and pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack().

◆ rbegin() [1/2]

template<typename PointT>

const_reverse_iterator pcl::PointCloud< PointT >::rbegin ( ) const

inlinenoexcept

Definition at line 438 of file point_cloud.h.

◆ rbegin() [2/2]

template<typename PointT>

reverse_iterator pcl::PointCloud< PointT >::rbegin ( )

inlinenoexcept

Definition at line 436 of file point_cloud.h.

◆ rend() [1/2]

template<typename PointT>

const_reverse_iterator pcl::PointCloud< PointT >::rend ( ) const

inlinenoexcept

Definition at line 439 of file point_cloud.h.

◆ rend() [2/2]

template<typename PointT>

reverse_iterator pcl::PointCloud< PointT >::rend ( )

inlinenoexcept

Definition at line 437 of file point_cloud.h.

◆ reserve()

template<typename PointT>

void pcl::PointCloud< PointT >::reserve ( std::size_t n )

inline

Definition at line 446 of file point_cloud.h.

Referenced by pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::VoxelGridCovariance< PointT >::getDisplayCloud(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::transformPointCloud(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ resize() [1/4]

template<typename PointT>

void pcl::PointCloud< PointT >::resize	(	index_t	count,
		const PointT &	value )

inline

Resizes the container to contain count elements.

If the current size is greater than count, the pointcloud is reduced to its first count elements
If the current size is less than count, additional copies of value are appended
Note
This potentially breaks the organized structure of the cloud by setting the height to 1 IFF width * height != count!

Parameters

[in] count new size of the point cloud

[in] value the value to initialize the new points with

Definition at line 503 of file point_cloud.h.

◆ resize() [2/4]

template<typename PointT>

void pcl::PointCloud< PointT >::resize	(	index_t	new_width,
		index_t	new_height,
		const PointT &	value )

inline

Resizes the container to contain count elements.

If the current size is greater then the requested size, the pointcloud is reduced to its first requested elements
If the current size is less then the requested size, additional default-inserted points are appended
Parameters

[in] new_width new width of the point cloud

[in] new_height new height of the point cloud

[in] value the value to initialize the new points with

Definition at line 524 of file point_cloud.h.

◆ resize() [3/4]

template<typename PointT>

void pcl::PointCloud< PointT >::resize ( std::size_t count )

inline

Resizes the container to contain count elements.

If the current size is greater than count, the pointcloud is reduced to its first count elements
If the current size is less than count, additional default-inserted points are appended
Note
This potentially breaks the organized structure of the cloud by setting the height to 1 IFF width * height != count!

Parameters

[in] count new size of the point cloud

Definition at line 463 of file point_cloud.h.

Referenced by pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::Edge< PointInT, PointOutT >::canny(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::DisparityMapConverter< PointT >::compute(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateNormals(), pcl::NormalBasedSignatureEstimation< PointT, PointNT, PointFeature >::computeFeature(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::concatenateFields(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::demeanPointCloud(), pcl::Edge< PointInT, PointOutT >::detectEdgeCanny(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::Morphology< PointT >::erosionBinary(), pcl::Morphology< PointT >::erosionGray(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::fromPCLPointCloud2(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::Morphology< PointT >::intersectionBinary(), pcl::isPointIn2DPolygon(), pcl::SupervoxelClustering< PointT >::makeSupervoxelNormalCloud(), pcl::search::Search< PointInT >::nearestKSearchT(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::Poisson< PointNT >::performReconstruction(), pcl::Poisson< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::ColorGradientModality< PointInT >::processInputData(), pcl::search::Search< PointInT >::radiusSearchT(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::ExtractPolygonalPrismData< PointT >::segment(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segment(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segmentAndRefine(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::subtractionBinary(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation(), pcl::io::vtkPolyDataToPointCloud(), and pcl::io::vtkStructuredGridToPointCloud().

◆ resize() [4/4]

template<typename PointT>

void pcl::PointCloud< PointT >::resize	(	uindex_t	new_width,
		uindex_t	new_height )

inline

Resizes the container to contain new_width * new_height elements.

If the current size is greater than the requested size, the pointcloud is reduced to its first requested elements
If the current size is less then the requested size, additional default-inserted points are appended
Parameters

[in] new_width new width of the point cloud

[in] new_height new height of the point cloud

Definition at line 483 of file point_cloud.h.

◆ size()

template<typename PointT>

std::size_t pcl::PointCloud< PointT >::size ( ) const

inline

Definition at line 444 of file point_cloud.h.

◆ swap()

template<typename PointT>

void pcl::PointCloud< PointT >::swap ( PointCloud< PointT > & rhs )

inline

Swap a point cloud with another cloud.

Parameters

[in,out] rhs point cloud to swap this with

Definition at line 873 of file point_cloud.h.

Referenced by pcl::applyMorphologicalOperator(), and pcl::MarchingCubes< PointNT >::performReconstruction().

◆ transient_emplace()

template<typename PointT>

template<class... Args>

iterator pcl::PointCloud< PointT >::transient_emplace	(	iterator	position,
		Args &&...	args )

inline

Emplace a new point in the cloud, given an iterator.

Note: This assumes the user would correct the width and height later on!

Parameters

[in]	position	iterator before which the point will be emplaced
[in]	args	the parameters to forward to the point to construct

Returns: returns the new position iterator

Definition at line 809 of file point_cloud.h.

◆ transient_emplace_back()

template<typename PointT>

template<class... Args>

reference pcl::PointCloud< PointT >::transient_emplace_back ( Args &&... args )

inline

Emplace a new point in the cloud, at the end of the container.

Note: This assumes the user would correct the width and height later on!

Parameters

[in] args the parameters to forward to the point to construct

Returns: reference to the emplaced point

Definition at line 701 of file point_cloud.h.

◆ transient_erase() [1/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::transient_erase	(	iterator	first,
		iterator	last )

inline

Erase a set of points given by a (first, last) iterator pair.

Note: This assumes the user would correct the width and height later on!

Parameters

[in]	first	where to start erasing points from
[in]	last	where to stop erasing points from

Returns: returns the new position iterator

Definition at line 863 of file point_cloud.h.

◆ transient_erase() [2/2]

template<typename PointT>

iterator pcl::PointCloud< PointT >::transient_erase ( iterator position )

inline

Erase a point in the cloud.

Note: This assumes the user would correct the width and height later on!

Parameters

[in] position what data point to erase

Returns: returns the new position iterator

Definition at line 835 of file point_cloud.h.

◆ transient_insert() [1/3]

template<typename PointT>

iterator pcl::PointCloud< PointT >::transient_insert	(	iterator	position,
		const PointT &	pt )

inline

Insert a new point in the cloud, given an iterator.

Note: This assumes the user would correct the width and height later on!

Parameters

[in]	position	where to insert the point
[in]	pt	the point to insert

Returns: returns the new position iterator

Definition at line 729 of file point_cloud.h.

◆ transient_insert() [2/3]

template<typename PointT>

template<class InputIterator>

void pcl::PointCloud< PointT >::transient_insert	(	iterator	position,
		InputIterator	first,
		InputIterator	last )

inline

Insert a new range of points in the cloud, at a certain position.

Note: This assumes the user would correct the width and height later on!

Parameters

[in]	position	where to insert the data
[in]	first	where to start inserting the points from
[in]	last	where to stop inserting the points from

Definition at line 782 of file point_cloud.h.

◆ transient_insert() [3/3]

template<typename PointT>

void pcl::PointCloud< PointT >::transient_insert	(	iterator	position,
		std::size_t	n,
		const PointT &	pt )

inline

Insert a new point in the cloud N times, given an iterator.

Note: This assumes the user would correct the width and height later on!

Parameters

[in]	position	where to insert the point
[in]	n	the number of times to insert the point
[in]	pt	the point to insert

Definition at line 756 of file point_cloud.h.

◆ transient_push_back()

template<typename PointT>

void pcl::PointCloud< PointT >::transient_push_back ( const PointT & pt )

inline

Insert a new point in the cloud, at the end of the container.

Note: This assumes the user would correct the width and height later on!

Parameters

[in] pt the point to insert

Definition at line 676 of file point_cloud.h.

Referenced by pcl::copyPointCloud(), and pcl::copyPointCloud().

Member Data Documentation

◆ header

template<typename PointT>

pcl::PCLHeader pcl::PointCloud< PointT >::header

The point cloud header.

It contains information about the acquisition time.

Definition at line 393 of file point_cloud.h.

Referenced by pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::features::computeApproximateNormals(), pcl::PointCloud< PointInT >::concatenate(), pcl::concatenateFields(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::gpu::extractEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::Filter< PointT >::filter(), pcl::fromPCLPointCloud2(), pcl::operator<<(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::SegmentDifferences< PointT >::segment(), pcl::PointCloud< PointInT >::swap(), pcl::toPCLPointCloud2(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), and pcl::transformPointCloudWithNormals().

◆ height

template<typename PointT>

std::uint32_t pcl::PointCloud< PointT >::height = 0

The point cloud height (if organized as an image-structure).

Definition at line 401 of file point_cloud.h.

◆ is_dense

template<typename PointT>

bool pcl::PointCloud< PointT >::is_dense = true

True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).

Definition at line 404 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::FilterIndices< PointT >::applyFilter(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::compute3DCentroid(), pcl::compute3DCentroid(), pcl::computeCentroid(), pcl::computeCentroid(), pcl::computeCentroidAndOBB(), pcl::computeCentroidAndOBB(), pcl::computeCovarianceMatrix(), pcl::computeCovarianceMatrix(), pcl::computeCovarianceMatrix(), pcl::computeCovarianceMatrix(), pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::SHOTEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::computeMeanAndCovarianceMatrix(), pcl::computeMeanAndCovarianceMatrix(), pcl::PointCloud< PointInT >::concatenate(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::fromPCLPointCloud2(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::getMaxDistance(), pcl::getMaxDistance(), pcl::getMinMax3D(), pcl::getMinMax3D(), pcl::getMinMax3D(), pcl::getMinMax3D(), pcl::getPointCloudDifference(), pcl::getPointsInBox(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::operator<<(), pcl::operator<<(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::io::pointCloudTovtkPolyData(), pcl::ColorGradientModality< PointInT >::processInputData(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::PointCloud< PointInT >::swap(), pcl::toPCLPointCloud2(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::transformPointCloudWithNormals(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::io::vtkPolyDataToPointCloud(), and pcl::io::vtkStructuredGridToPointCloud().

◆ points

template<typename PointT>

std::vector<PointT, Eigen::aligned_allocator<PointT> > pcl::PointCloud< PointT >::points

The point data.

Definition at line 396 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::features::computeApproximateCovariances(), pcl::features::computeApproximateNormals(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computePointMomentInvariants(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::visualization::createPolygon(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::getMinMax3D(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segmentAndRefine(), pcl::PlanarPolygon< PointT >::setContour(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::shiftCloud(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::PointCloud< PointInT >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras(), and pcl::PCDWriter::writeASCII().

◆ sensor_orientation_

template<typename PointT>

Eigen::Quaternionf pcl::PointCloud< PointT >::sensor_orientation_ = Eigen::Quaternionf::Identity ()

Sensor acquisition pose (rotation).

Definition at line 409 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::Filter< PointT >::filter(), pcl::PCDWriter::generateHeader(), pcl::operator<<(), pcl::operator<<(), pcl::ImageGrabber< PointT >::operator[](), pcl::PCDGrabber< PointT >::operator[](), pcl::ImageGrabber< PointT >::publish(), pcl::PCDGrabber< PointT >::publish(), pcl::StereoGrabber< PointT >::publish(), pcl::FileReader::read(), pcl::IFSReader::read(), pcl::io::LZFDepth16ImageReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), pcl::PLYReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::PointCloud< PointInT >::swap(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::transformPointCloudWithNormals(), pcl::FileWriter::write(), and pcl::PLYWriter::write().

◆ sensor_origin_

template<typename PointT>

Eigen::Vector4f pcl::PointCloud< PointT >::sensor_origin_ = Eigen::Vector4f::Zero ()

Sensor acquisition pose (origin/translation).

Definition at line 407 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::Filter< PointT >::filter(), pcl::PCDWriter::generateHeader(), pcl::operator<<(), pcl::operator<<(), pcl::ImageGrabber< PointT >::operator[](), pcl::PCDGrabber< PointT >::operator[](), pcl::ImageGrabber< PointT >::publish(), pcl::PCDGrabber< PointT >::publish(), pcl::StereoGrabber< PointT >::publish(), pcl::FileReader::read(), pcl::IFSReader::read(), pcl::io::LZFDepth16ImageReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), pcl::PLYReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::PointCloud< PointInT >::swap(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::transformPointCloudWithNormals(), pcl::FileWriter::write(), and pcl::PLYWriter::write().

◆ width

template<typename PointT>

std::uint32_t pcl::PointCloud< PointT >::width = 0

The point cloud width (if organized as an image-structure).

Definition at line 399 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRGBImage(), pcl::LineRGBD< PointXYZT, PointRGBT >::applyProjectiveDepthICPOnDetections(), pcl::Edge< PointInT, PointOutT >::canny(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::DisparityMapConverter< PointT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::Feature< PointInT, ReferenceFrame >::compute(), pcl::filters::Pyramid< PointT >::compute(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateNormals(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradients(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradientsSobel(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::PointCloud< PointInT >::concatenate(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::GaussianKernel::convolve(), pcl::GaussianKernel::convolve(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::copyPointCloud(), pcl::common::deleteCols(), pcl::common::deleteRows(), pcl::demeanPointCloud(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::Edge< PointInT, PointOutT >::detectEdgeCanny(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::Edge< PointInT, PointInT >::detectEdgeSobel(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::downsample(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::Morphology< PointT >::erosionBinary(), pcl::Morphology< PointT >::erosionGray(), pcl::estimateProjectionMatrix(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::OrganizedEdgeBase< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::occlusion_reasoning::filter(), pcl::occlusion_reasoning::filter(), pcl::fromPCLPointCloud2(), pcl::PCDWriter::generateHeader(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::Morphology< PointT >::intersectionBinary(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::mismatchVector(), pcl::operator<<(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::PointCloudRGBtoI(), pcl::PointCloudRGBtoI(), pcl::io::pointCloudTovtkStructuredGrid(), pcl::PointCloudXYZHSVtoXYZRGB(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ColorGradientModality< PointInT >::processInputData(), pcl::PCDGrabber< PointT >::publish(), pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::queryBBIncludes(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::SegmentDifferences< PointT >::segment(), pcl::Registration< PointSource, PointTarget, float >::setInputSource(), pcl::visualization::ImageViewer::showCorrespondences(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::spatialGradient(), pcl::Morphology< PointT >::subtractionBinary(), pcl::PointCloud< PointInT >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::toPCLPointCloud2(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::io::vtkPolyDataToPointCloud(), pcl::io::vtkStructuredGridToPointCloud(), pcl::PCDWriter::writeASCII(), and pcl::PCDWriter::writeASCII().

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

pcl/common/distances.h
pcl/point_cloud.h

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Detailed Description

Member Typedef Documentation

◆ CloudVectorType

◆ const_iterator

◆ const_reference

◆ const_reverse_iterator

◆ ConstPtr

◆ difference_type

◆ iterator

◆ PointType

◆ Ptr

◆ reference

◆ reverse_iterator

◆ size_type

◆ value_type

◆ VectorType

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

◆ PointCloud() [2/3]

◆ PointCloud() [3/3]

Member Function Documentation

◆ assign() [1/6]

◆ assign() [2/6]

◆ assign() [3/6]

◆ assign() [4/6]

◆ assign() [5/6]

◆ assign() [6/6]

◆ at() [1/4]

◆ at() [2/4]

◆ at() [3/4]

◆ at() [4/4]

◆ back() [1/2]

◆ back() [2/2]

◆ begin() [1/2]

◆ begin() [2/2]

◆ cbegin()

◆ cend()

◆ clear()

◆ concatenate() [1/2]

◆ concatenate() [2/2]

◆ crbegin()

◆ crend()

◆ data() [1/2]

◆ data() [2/2]

◆ emplace()

◆ emplace_back()

◆ empty()

◆ end() [1/2]

◆ end() [2/2]

◆ erase() [1/2]

◆ erase() [2/2]

◆ front() [1/2]

◆ front() [2/2]

◆ getMatrixXfMap() [1/4]

◆ getMatrixXfMap() [2/4]

◆ getMatrixXfMap() [3/4]

◆ getMatrixXfMap() [4/4]

◆ insert() [1/3]

◆ insert() [2/3]

◆ insert() [3/3]

◆ isOrganized()

◆ makeShared()

◆ max_size()

◆ operator()() [1/2]

◆ operator()() [2/2]

◆ operator+()

◆ operator+=()

◆ operator[]() [1/2]

◆ operator[]() [2/2]

◆ push_back()

◆ rbegin() [1/2]

◆ rbegin() [2/2]

◆ rend() [1/2]

◆ rend() [2/2]

◆ reserve()

◆ resize() [1/4]