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

#include <ScalarFieldTools.h>

Inheritance diagram for CCCoreLib::ScalarFieldTools:

Collaboration diagram for CCCoreLib::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)
	Computes the geometrical gradient of a scalar field associated to a point cloud. More...

static bool	applyScalarFieldGaussianFilter (PointCoordinateType sigma, GenericIndexedCloudPersist theCloud, PointCoordinateType sigmaSF, GenericProgressCallback progressCb=nullptr, DgmOctree *theOctree=nullptr)
	Computes a spatial gaussian filter on a scalar field associated to a point cloud. More...

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)
	Classifies automaticaly a scalar field in K classes with the K-means algorithm. More...

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)
	"Cellular" function to compute the gradient norms of points inside an octree cell More...

static bool	computeCellGaussianFilter (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)
	"Cellular" function to apply a gaussian filter on the scalar values of points inside an octree cell More...

Detailed Description

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

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

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 precised (sigma). As 99% of the gaussian distribution is between -3*sigma and +3*sigma around the mean value, this filter will only look for neighbouring points (around each point) in a sphere of radius 3*sigma. It also permits to use the filter as a bilateral filter. Where the wights are computed also considering the distance of the neighbor's scalar value from the current point scalar value. (weighted with gaussian as distances are) Warning: this method assumes the input scalar field is different from output.

Parameters

sigma	filter variance
theCloud	a point cloud (associated to scalar values)
sigmaSF	the sigma for the bilateral filter. when different than -1 turns the gaussian filter into a 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

◆ 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)

◆ 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)

◆ 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)

◆ 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

◆ 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

◆ 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

◆ 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)

◆ 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

◆ 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

◆ 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)

◆ 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

◆ 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

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

ScalarFieldTools.h
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()

◆ SetScalarValueToNaN()

◆ SetScalarValueToZero()