Several scalar field treatment algorithms (gradient, classification, etc.) More...

#include <ScalarFieldTools.h>

Inheritance diagram for cloudViewer::ScalarFieldTools:

Collaboration diagram for cloudViewer::ScalarFieldTools:

Static Public Member Functions
static ScalarType	computeMeanScalarValue (GenericCloud *theCloud)
	Computes the mean value of a scalar field associated to a cloud. More...

static ScalarType	computeMeanSquareScalarValue (GenericCloud *theCloud)
	Computes the mean square value of a scalar field associated to a cloud. More...

static int	computeScalarFieldGradient (GenericIndexedCloudPersist theCloud, PointCoordinateType radius, bool euclideanDistances, bool sameInAndOutScalarField=false, GenericProgressCallback progressCb=nullptr, DgmOctree *theOctree=nullptr)

static bool	applyScalarFieldGaussianFilter (PointCoordinateType sigma, GenericIndexedCloudPersist theCloud, PointCoordinateType sigmaSF, GenericProgressCallback progressCb=nullptr, DgmOctree *theOctree=nullptr)

static void	multiplyScalarFields (GenericIndexedCloud firstCloud, GenericIndexedCloud secondCloud, GenericProgressCallback *progressCb=nullptr)
	Multiplies two scalar fields of the same size. More...

static void	computeScalarFieldHistogram (const GenericCloud *theCloud, unsigned numberOfClasses, std::vector< int > &histo)
	Computes an histogram of the scalar field with a given number of classes. More...

static void	computeScalarFieldExtremas (const GenericCloud *theCloud, ScalarType &minV, ScalarType &maxV)
	Compute the extreme values of a scalar field. More...

static unsigned	countScalarFieldValidValues (const GenericCloud *theCloud)
	Count the number of valid values in a scalar field. More...

static bool	computeKmeans (const GenericCloud theCloud, unsigned char K, KMeanClass kmcc[], GenericProgressCallback progressCb=nullptr)

static void	SetScalarValueToNaN (const CCVector3 &P, ScalarType &scalarValue)
	Sets the distance value associated to a point. More...

static void	SetScalarValueToZero (const CCVector3 &P, ScalarType &scalarValue)
	Sets the distance value associated to a point to zero. More...

static void	SetScalarValueInverted (const CCVector3 &P, ScalarType &scalarValue)

Static Protected Member Functions
static bool	computeMeanGradientOnPatch (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)

static bool	computeCellGaussianFilter (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)

Detailed Description

Several scalar field treatment algorithms (gradient, classification, etc.)

This toolbox provides several algorithms to apply treatments and handle scalar fields

Definition at line 35 of file ScalarFieldTools.h.

Member Function Documentation

◆ applyScalarFieldGaussianFilter()

bool ScalarFieldTools::applyScalarFieldGaussianFilter	(	PointCoordinateType	sigma,
		GenericIndexedCloudPersist *	theCloud,
		PointCoordinateType	sigmaSF,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	theOctree = `nullptr`
	)

static

Computes a spatial gaussian filter on a scalar field associated to a point cloud The "amplitutde" of the Gaussian filter must be specified (sigma). As 99% of the Gaussian distribution is between -3*sigma and +3*sigma around the mean value, this filter will only look for neighbors within a sphere of radius 3*sigma. One can also use the filter as a Bilateral filter. In this case the weights are computed considering the difference of the neighbors SF values with the current point SF value (also following a Gaussian distribution). Warning: this method assumes the input scalar field is different from the output one.

Parameters

sigma	filter variance
theCloud	a point cloud (associated to scalar values)
sigmaSF	if strictly positive, the variance for the Bilateral filter
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
theOctree	the octree, if it has already been computed

Returns: success

Definition at line 231 of file ScalarFieldTools.cpp.

References cloudViewer::DgmOctree::build(), computeCellGaussianFilter(), cloudViewer::GenericCloud::enableScalarField(), cloudViewer::DgmOctree::executeFunctionForAllCellsAtLevel(), cloudViewer::DgmOctree::findBestLevelForAGivenNeighbourhoodSizeExtraction(), cloudViewer::GenericProgressCallback::setInfo(), cloudViewer::GenericProgressCallback::setMethodTitle(), cloudViewer::GenericCloud::size(), cloudViewer::GenericProgressCallback::textCanBeEdited(), and cloudViewer::GenericProgressCallback::update().

Referenced by cloudViewer::AutoSegmentationTools::frontPropagationBasedSegmentation(), and ccEntityAction::sfGaussianFilter().

◆ computeCellGaussianFilter()

bool ScalarFieldTools::computeCellGaussianFilter	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to apply a gaussian filter on the scalar values of points inside an octree cell This function is meant to be applied to all cells of the octree The method also permits to use a bilateral behaviour for the filter. This is automatically switched on if its sigmaSF parameter in additionalParameters is different than -1 (it is of the form DgmOctree::localFunctionPtr). See ScalarFieldTools::applyScalarFieldGaussianFilter. Method parameters (defined in "additionalParameters") are :

(PointCoordinateType*) sigma
(std::vector<ScalarType>*) the smoothed values
Parameters

cell structure describing the cell on which processing is applied

additionalParameters see method description

nProgress optional (normalized) progress notification (per-point)

Definition at line 289 of file ScalarFieldTools.cpp.

Referenced by applyScalarFieldGaussianFilter().

◆ computeKmeans()

bool ScalarFieldTools::computeKmeans	(	const GenericCloud *	theCloud,
		unsigned char	K,
		KMeanClass	kmcc[],
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Classifies automaticaly a scalar field in K classes with the K-means algorithm The initial K classes positions are regularly spaced between the lowest and the highest values of the scalar field. Eventually the algorithm will converge and produce K classes.

Parameters

theCloud	a point cloud (associated to scalar values)
K	the number of classes
kmcc	an array of size K which will be filled with the computed classes limits (see ScalarFieldTools::KmeanClass)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Definition at line 520 of file ScalarFieldTools.cpp.

References abs(), computeScalarFieldExtremas(), cloudViewer::GenericCloud::getPointScalarValue(), cloudViewer::KMeanClass::maxValue, cloudViewer::KMeanClass::mean, cloudViewer::KMeanClass::minValue, cloudViewer::GenericProgressCallback::setInfo(), cloudViewer::GenericProgressCallback::setMethodTitle(), cloudViewer::GenericCloud::size(), cloudViewer::GenericProgressCallback::start(), cloudViewer::GenericProgressCallback::stop(), cloudViewer::GenericProgressCallback::textCanBeEdited(), cloudViewer::GenericProgressCallback::update(), and cloudViewer::ScalarField::ValidValue().

◆ computeMeanGradientOnPatch()

bool ScalarFieldTools::computeMeanGradientOnPatch	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to compute the gradient norms of points inside an octree cell This function is meant to be applied to all cells of the octree (it is of the form DgmOctree::localFunctionPtr). See ScalarFieldTools::computeScalarFieldGradient. Method parameters (defined in "additionalParameters") are :

(GenericCloud*) the point cloud
(bool*) specifies if the scalar values are euclidean distances
(PointCoordinateType*) radius
(std::vector<ScalarType>*) the gradient norms container
Parameters

cell structure describing the cell on which processing is applied

additionalParameters see method description

nProgress optional (normalized) progress notification (per-point)

Definition at line 113 of file ScalarFieldTools.cpp.

Referenced by computeScalarFieldGradient().

◆ computeMeanScalarValue()

ScalarType ScalarFieldTools::computeMeanScalarValue ( GenericCloud * theCloud )

static

Computes the mean value of a scalar field associated to a cloud.

Returns the mean of SF values associated to each point of a cloud Warning: be sure to activate an OUTPUT scalar field on the cloud

Parameters

theCloud the point cloud

Returns: the associated scalar field mean value

Definition at line 695 of file ScalarFieldTools.cpp.

References count, cloudViewer::GenericCloud::getPointScalarValue(), NAN_VALUE, cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

Referenced by cloudViewer::FastMarchingForPropagation::init().

◆ computeMeanSquareScalarValue()

ScalarType ScalarFieldTools::computeMeanSquareScalarValue ( GenericCloud * theCloud )

static

Computes the mean square value of a scalar field associated to a cloud.

Returns the mean of squared SF values associated to each point of a cloud Warning: be sure to activate an OUTPUT scalar field on the cloud

Parameters

theCloud the point cloud

Returns: the associated scalar field mean of squares value

Definition at line 716 of file ScalarFieldTools.cpp.

References count, cloudViewer::GenericCloud::getPointScalarValue(), NAN_VALUE, cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

◆ computeScalarFieldExtremas()

void ScalarFieldTools::computeScalarFieldExtremas	(	const GenericCloud *	theCloud,
		ScalarType &	minV,
		ScalarType &	maxV
	)

static

Compute the extreme values of a scalar field.

Parameters

theCloud	a point cloud, with a scalar field activated
minV	a field to store the minimum value
maxV	a field to store the maximum value

Definition at line 419 of file ScalarFieldTools.cpp.

References cloudViewer::GenericCloud::getPointScalarValue(), NAN_VALUE, cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

Referenced by computeKmeans(), computeScalarFieldHistogram(), define_ScalarFieldTools(), and cloudViewer::CloudSamplingTools::resampleCloudSpatially().

◆ computeScalarFieldGradient()

int ScalarFieldTools::computeScalarFieldGradient	(	GenericIndexedCloudPersist *	theCloud,
		PointCoordinateType	radius,
		bool	euclideanDistances,
		bool	sameInAndOutScalarField = `false`,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	theOctree = `nullptr`
	)

static

Computes the geometrical gradient of a scalar field associated to a point cloud See Daniel Girardeau-Montaut's PhD manuscript (Chapter 3, section 3.3.2) for more information. As explained in this section, if the scalar field corresponds to (euclidean) distances between the points and another entity, then it is possible to filter out aberrant values.

Parameters

theCloud	a point cloud (associated to scalar values)
radius	spherical neighborhood size (or 0 for automatic size)
euclideanDistances	indicates if the scalar values are euclidean distances
sameInAndOutScalarField	specifies that the 'in' and 'out' scalar field of the input point cloud are the same structure
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
theOctree	the octree, if it has already been computed

Returns: error code (0 if ok)

Definition at line 37 of file ScalarFieldTools.cpp.

References AVERAGE_NUMBER_OF_POINTS_FOR_GRADIENT_COMPUTATION, cloudViewer::DgmOctree::build(), computeMeanGradientOnPatch(), cloudViewer::GenericCloud::enableScalarField(), cloudViewer::DgmOctree::executeFunctionForAllCellsAtLevel(), cloudViewer::DgmOctree::findBestLevelForAGivenNeighbourhoodSizeExtraction(), cloudViewer::DgmOctree::findBestLevelForAGivenPopulationPerCell(), cloudViewer::DgmOctree::getCellSize(), octreeLevel, CCShareable::release(), cloudViewer::ScalarField::reserveSafe(), result, and cloudViewer::GenericCloud::size().

Referenced by ccLibAlgorithms::ApplyCCLibAlgorithm(), ccTrace::buildGradientCost(), and cloudViewer::AutoSegmentationTools::frontPropagationBasedSegmentation().

◆ computeScalarFieldHistogram()

void ScalarFieldTools::computeScalarFieldHistogram	(	const GenericCloud *	theCloud,
		unsigned	numberOfClasses,
		std::vector< int > &	histo
	)

static

Computes an histogram of the scalar field with a given number of classes.

The scalar values are projected in a given number of classes, regularly spaced between the lowest and the highest value of the scalar field.

Parameters

theCloud	a point cloud (associated to scalar values)
numberOfClasses	number of histogram classes
histo	number of elements per histogram class

Definition at line 464 of file ScalarFieldTools.cpp.

References computeScalarFieldExtremas(), cloudViewer::GenericCloud::getPointScalarValue(), cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

◆ countScalarFieldValidValues()

unsigned ScalarFieldTools::countScalarFieldValidValues ( const GenericCloud * theCloud )

static

Count the number of valid values in a scalar field.

Parameters

theCloud a point cloud, with a scalar field activated

Definition at line 447 of file ScalarFieldTools.cpp.

References count, cloudViewer::GenericCloud::getPointScalarValue(), cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

Referenced by cloudViewer::WeibullDistribution::computeChi2Dist(), and cloudViewer::NormalDistribution::computeChi2Dist().

◆ multiplyScalarFields()

void ScalarFieldTools::multiplyScalarFields	(	GenericIndexedCloud *	firstCloud,
		GenericIndexedCloud *	secondCloud,
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Multiplies two scalar fields of the same size.

The first scalar field is updated (S1 = S1*S2).

Parameters

firstCloud	the first point cloud (associated to scalar values)
secondCloud	the second point cloud (associated to scalar values)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Definition at line 399 of file ScalarFieldTools.cpp.

References cloudViewer::GenericCloud::getPointScalarValue(), NAN_VALUE, cloudViewer::GenericCloud::setPointScalarValue(), cloudViewer::GenericCloud::size(), and cloudViewer::ScalarField::ValidValue().

◆ SetScalarValueInverted()

void ScalarFieldTools::SetScalarValueInverted	(	const CCVector3 &	P,
		ScalarType &	scalarValue
	)

static

Definition at line 32 of file ScalarFieldTools.cpp.

◆ SetScalarValueToNaN()

void ScalarFieldTools::SetScalarValueToNaN	(	const CCVector3 &	P,
		ScalarType &	scalarValue
	)

static

Sets the distance value associated to a point.

Generic function that can be used with the GenericCloud::foreach() method.

Parameters

P	a 3D point
scalarValue	its associated scalar value

Definition at line 22 of file ScalarFieldTools.cpp.

References NAN_VALUE.

Referenced by cloudViewer::DistanceComputationTools::computeCloud2MeshDistances(), cloudViewer::DistanceComputationTools::computeGeodesicDistances(), and define_ScalarFieldTools().

◆ SetScalarValueToZero()

void ScalarFieldTools::SetScalarValueToZero	(	const CCVector3 &	P,
		ScalarType &	scalarValue
	)

static

Sets the distance value associated to a point to zero.

Generic function that can be used with the GenericCloud::foreach() method.

Parameters

P	a 3D point
scalarValue	its associated scalar value

Definition at line 27 of file ScalarFieldTools.cpp.

Referenced by cloudViewer::GeometricalAnalysisTools::FlagDuplicatePoints().

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

/root/ACloudViewer/core/include/ScalarFieldTools.h
/root/ACloudViewer/core/src/ScalarFieldTools.cpp

cell	structure describing the cell on which processing is applied
additionalParameters	see method description
nProgress	optional (normalized) progress notification (per-point)

Static Public Member Functions

Static Protected Member Functions

Detailed Description

Member Function Documentation

◆ applyScalarFieldGaussianFilter()

◆ computeCellGaussianFilter()

◆ computeKmeans()

◆ computeMeanGradientOnPatch()

◆ computeMeanScalarValue()

◆ computeMeanSquareScalarValue()

◆ computeScalarFieldExtremas()

◆ computeScalarFieldGradient()

◆ computeScalarFieldHistogram()

◆ countScalarFieldValidValues()

◆ multiplyScalarFields()

◆ SetScalarValueInverted()

◆ SetScalarValueToNaN()

◆ SetScalarValueToZero()