Some useful tools for initialization, point search, ... More...

#include <nurbs_tools.h>

Static Public Member Functions
static void	computeBoundingBox (const ON_NurbsCurve &nurbs, Eigen::Vector3d &_min, Eigen::Vector3d &_max)
static void	computeBoundingBox (const ON_NurbsSurface &nurbs, Eigen::Vector3d &_min, Eigen::Vector3d &_max)
static Eigen::Vector3d	computeMean (const vector_vec3d &data)
	Compute the mean of a set of points.
static Eigen::Vector2d	computeMean (const vector_vec2d &data)
	Compute the mean of a set of points.
static double	computeRScale (const Eigen::Vector3d &_min, const Eigen::Vector3d &_max)
static Eigen::Vector3d	computeVariance (const Eigen::Vector3d &mean, const vector_vec3d &data)
	Compute the variance of a set of points.
static Eigen::Vector2d	computeVariance (const Eigen::Vector2d &mean, const vector_vec2d &data)
	Compute the variance of a set of points.
static void	downsample_random (const vector_vec3d &data1, vector_vec3d &data2, unsigned size)
	Downsample data points to a certain size.
static void	downsample_random (vector_vec3d &data1, unsigned size)
	Downsample data points to a certain size.
static unsigned	getClosestPoint (const Eigen::Vector2d &point, const vector_vec2d &data)
	Get the closest point with respect to 'point'.
static unsigned	getClosestPoint (const Eigen::Vector3d &point, const vector_vec3d &data)
	Get the closest point with respect to 'point'.
static unsigned	getClosestPoint (const Eigen::Vector2d &point, const Eigen::Vector2d &dir, const vector_vec2d &data, unsigned &idxcp)
	Get the closest point with respect to 'point' in Non-Euclidean metric.
static void	pca (const vector_vec3d &data, Eigen::Vector3d &mean, Eigen::Matrix3d &eigenvectors, Eigen::Vector3d &eigenvalues)
	PCA - principal-component-analysis.
static void	pca (const vector_vec2d &data, Eigen::Vector2d &mean, Eigen::Matrix2d &eigenvectors, Eigen::Vector2d &eigenvalues)
	PCA - principal-component-analysis.

Detailed Description

Some useful tools for initialization, point search, ...

Definition at line 59 of file nurbs_tools.h.

Member Function Documentation

void NurbsTools::computeBoundingBox	(	const ON_NurbsCurve &	nurbs,
		Eigen::Vector3d &	_min,
		Eigen::Vector3d &	_max
	)		`[static]`

compute bounding box of curve control points

Definition at line 258 of file nurbs_tools.cpp.

void NurbsTools::computeBoundingBox	(	const ON_NurbsSurface &	nurbs,
		Eigen::Vector3d &	_min,
		Eigen::Vector3d &	_max
	)		`[static]`

Definition at line 284 of file nurbs_tools.cpp.

Eigen::Vector3d NurbsTools::computeMean ( const vector_vec3d & data ) [static]

Compute the mean of a set of points.

Parameters:

[in] data Set of points.

Definition at line 196 of file nurbs_tools.cpp.

Eigen::Vector2d NurbsTools::computeMean ( const vector_vec2d & data ) [static]

Compute the mean of a set of points.

Parameters:

[in] data Set of points.

Definition at line 210 of file nurbs_tools.cpp.

double NurbsTools::computeRScale	(	const Eigen::Vector3d &	_min,
		const Eigen::Vector3d &	_max
	)		`[static]`

Definition at line 313 of file nurbs_tools.cpp.

Eigen::Vector3d NurbsTools::computeVariance	(	const Eigen::Vector3d &	mean,
		const vector_vec3d &	data
	)		`[static]`

Compute the variance of a set of points.

Parameters:

[in] data Set of points

Definition at line 224 of file nurbs_tools.cpp.

Eigen::Vector2d NurbsTools::computeVariance	(	const Eigen::Vector2d &	mean,
		const vector_vec2d &	data
	)		`[static]`

Compute the variance of a set of points.

Parameters:

[in] data Set of points

Definition at line 241 of file nurbs_tools.cpp.

void NurbsTools::downsample_random	(	const vector_vec3d &	data1,
		vector_vec3d &	data2,
		unsigned	size
	)		`[static]`

Downsample data points to a certain size.

Parameters:

[in]	data1	The original set of points.
[out]	data2	The downsampled set of points of size 'size'.
[in]	size	The desired size of the resulting set of points.

Definition at line 49 of file nurbs_tools.cpp.

void NurbsTools::downsample_random	(	vector_vec3d &	data1,
		unsigned	size
	)		`[static]`

Downsample data points to a certain size.

Parameters:

	in/out]	data1 The set of points for downsampling; will be replaced by the resulting set of points of size 'size'.
[in]	size	The desired size of the resulting set of points.

Definition at line 68 of file nurbs_tools.cpp.

unsigned NurbsTools::getClosestPoint	(	const Eigen::Vector2d &	point,
		const vector_vec2d &	data
	)		`[static]`

Get the closest point with respect to 'point'.

Parameters:

[in]	point	The point to which the closest point is searched for.
[in]	data	Vector containing the set of points for searching.

Definition at line 119 of file nurbs_tools.cpp.

unsigned NurbsTools::getClosestPoint	(	const Eigen::Vector3d &	point,
		const vector_vec3d &	data
	)		`[static]`

Get the closest point with respect to 'point'.

Parameters:

[in]	point	The point to which the closest point is searched for.
[in]	data	Vector containing the set of points for searching.

Definition at line 139 of file nurbs_tools.cpp.

unsigned NurbsTools::getClosestPoint	(	const Eigen::Vector2d &	point,
		const Eigen::Vector2d &	dir,
		const vector_vec2d &	data,
		unsigned &	idxcp
	)		`[static]`

Get the closest point with respect to 'point' in Non-Euclidean metric.

Related paper: TODO

Parameters:

[in]	point	The point to which the closest point is searched for.
[in]	dir	The direction defining 'inside' and 'outside'
[in]	data	Vector containing the set of points for searching.
[out]	idxcp	Closest point with respect to Euclidean metric.

Definition at line 159 of file nurbs_tools.cpp.

void NurbsTools::pca	(	const vector_vec3d &	data,
		Eigen::Vector3d &	mean,
		Eigen::Matrix3d &	eigenvectors,
		Eigen::Vector3d &	eigenvalues
	)		`[static]`

PCA - principal-component-analysis.

Parameters:

[in]	data	Set of points.
[out]	mean	The mean of the set of points.
[out]	eigenvectors	Matrix containing column-wise the eigenvectors of the set of points.
[out]	eigenvalues	The eigenvalues of the set of points with respect to the eigenvectors.

Definition at line 321 of file nurbs_tools.cpp.

void NurbsTools::pca	(	const vector_vec2d &	data,
		Eigen::Vector2d &	mean,
		Eigen::Matrix2d &	eigenvectors,
		Eigen::Vector2d &	eigenvalues
	)		`[static]`

PCA - principal-component-analysis.

Parameters:

[in]	data	Set of points.
[out]	mean	The mean of the set of points.
[out]	eigenvectors	Matrix containing column-wise the eigenvectors of the set of points.
[out]	eigenvalues	The eigenvalues of the set of points with respect to the eigenvectors.

Definition at line 359 of file nurbs_tools.cpp.

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

Static Public Member Functions

Detailed Description

Member Function Documentation