samples.c File Reference

Detailed Description

Implementation of the auxiliary functions to deal with sets of samples.

See Also

samples.h

Definition in file samples.c.

Macros
#define	DISPERSION   1
	Evenly distribute points on the path. More...
#define	REMOVE_POINTS   ((DISPERSION)&&(1))
	To remove points when optimizint paths via gradient. More...
#define	APPROXIMATED_CHARTS_IN_GRADIENT   1
	Speed up gradient smooth by using approximated charts. More...

Functions
double	StepDispersion (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Dispersion path step. More...
boolean	StepDispersionGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Gradient of the step dispersion penalty term. More...
double	StepLength (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Length path step. More...
boolean	StepLengthGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Gradient of the length of a path step. More...
double	StepEffort (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Control effort of a path step. More...
boolean	StepEffortGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Gradient of the control effort of a path step. More...
boolean	StepCostNumericalGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Generic numerical gradient. More...
double	CombineCosts (TStepCost c1, TStepCost c2, Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Combines two cost functions. More...
boolean	CombineGradients (TStepCostGradient g1, TStepCostGradient g2, Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Combines two gradients. More...
double	LengthAndDispersion (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Combines length and dispersion cost functions. More...
boolean	LengthAndDispersionGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Gradient of the length and dispersion. More...
double	EffortAndDispersion (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xp, double *x, double *xn, unsigned int current, Tchart *cp, Tchart *c, Tchart *cn, Tworld *w)
	Combines control effort and dispersion cost functions. More...
boolean	EffortAndDispersionGradient (Tparameters *p, unsigned int *tp, boolean *sv, unsigned int m, double *xpp, double *xp, double *x, double *xn, double *xnn, Tchart *cpp, Tchart *cp, Tchart *c, Tchart *cn, Tchart *cnn, TJacobian *sJ, TStepCost cost, double *u, Tworld *w)
	Gradient of the effort and dispersion. More...
int	cmpUInt (const void *a, const void *b)
	Compares two unsigned in integers. More...
void	ShortcutSmooth (Tparameters *pr, boolean *sv, Tstatistics *stime, unsigned int *np, double ***point, TAtlasBase *w)
	Fixed-cut based smoothing. More...
void	RandomSmooth (Tparameters *pr, unsigned int nCores, unsigned int maxIterations, boolean *sv, Tstatistics *stime, unsigned int *np, double ***point, TAtlasBase *w)
	Random-based path smoothing. More...
void	GradientSmooth (Tparameters *pr, unsigned int nCores, unsigned int maxIterations, boolean *sv, Tstatistics *stime, unsigned int *np, double ***point, TStepCost stepCost, TStepCostGradient stepCostGradient, TAtlasBase *w)
	Gradient-based path smoothing. More...
void	SaveSamplesInt (Tfilename *fpath, unsigned int nvs, unsigned int ns, double **path)
	Internal function to save a set of samples to a file. More...
void	InitSamples (unsigned int *ms, unsigned int *ns, double ***path)
	Initializes a set of samples. More...
void	AddSample2Samples (unsigned int nv, double *sample, unsigned int nvs, boolean *systemVars, unsigned int *ms, unsigned int *ns, double ***path)
	Adds a sample to a set of samples. More...
double	ConnectSamplesChart (Tparameters *pr, unsigned int *tp, boolean *sv, Tbox *domain, unsigned int m, unsigned int n, double *s1, double *s2, double md, boolean checkCollisions, TJacobian *sJ, boolean *reached, boolean *collision, double *lastSample, unsigned int *ns, double ***path, TAtlasBase *w)
	Determines the connection between two points on the manifold. More...
double	ConnectSamples (Tparameters *pr, unsigned int *tp, boolean *sv, Tbox *domain, unsigned int m, unsigned int n, double *s1, double *s2, double md, boolean checkCollisions, TJacobian *sJ, boolean *reached, boolean *collision, double *lastSample, unsigned int *ns, double ***path, TAtlasBase *w)
	Determines the connection between two points on the manifold. More...
double	PathLength (unsigned int *tp, boolean *sv, unsigned int m, unsigned int np, double **point)
	Length of a path formed by a set of samples. More...
double	PathEffort (Tparameters *p, unsigned int m, unsigned int np, double **point, Tworld *w)
	Approximated control effort of a path. More...
void	SmoothSamples (Tparameters *pr, boolean parallel, int mode, unsigned int maxIterations, unsigned int ns, double **path, unsigned int *sns, double ***spath, TAtlasBase *w)
	Path smoothing. More...
void	ConcatSamples (unsigned int nvs, unsigned int ns1, double **path1, unsigned int ns2, double **path2, unsigned int *ns, double ***path)
	Concats two path. More...
void	ReverseConcatSamples (unsigned int nvs, unsigned int ns1, double **path1, unsigned int ns2, double **path2, unsigned int *ns, double ***path)
	Reverses and concats a path. More...
void	ReverseSamples (unsigned int ns, double **path)
	Reverses a set of samples. More...
unsigned int	ReadOneSample (Tparameters *p, char *fname, unsigned int nvs, double **s)
	Reads one sample from a file. More...
unsigned int	ReadTwoSamples (Tparameters *p, char *fname, unsigned int nvs, double **s1, double **s2)
	Reads two samples from a file. More...
void	SaveSamples (char *fname, char *suffix, unsigned int nvs, unsigned int ns, double **path)
	Saves a set of samples to a file. More...
void	SaveSamplesN (char *fname, boolean smooth, unsigned int n, unsigned int nvs, unsigned int ns, double **path)
	Saves a set of samples to a file. More...
boolean	LoadSamples (Tfilename *fname, unsigned int *nvs, unsigned int *ns, double ***path)
	Reads a set of samples from file. More...
void	PlotSamples (Tparameters *p, Tplot3d *p3d, unsigned int xID, unsigned int yID, unsigned int zID, unsigned int ns, double **path)
	Plots a 3D projection of a path. More...
void	PlotForceField (Tparameters *p, Tplot3d *p3d, unsigned int xID, unsigned int yID, unsigned int zID, Tworld *w, unsigned int ns, double **sols)
	Plots the force-field on a set of points. More...
void	DeleteSamples (unsigned int ns, double **path)
	Deletes the space used by a set of samples. More...

Macro Definition Documentation

#define DISPERSION   1

If set, the cost and the gradient are complemented with a penalty term that penalized path steps with different lengths. In other words, we try to evenly distribute the steps along the path.

Long steps are too far from the manifold and, thus, they introduce large errors, but they are shorter that paths that closely follow the manifold. This is way long steps often appear when minimizing the path length (and related measures) since the error with respect to the manifold is not taken into account.

Long steps appear more often if we remove steps along the paths (if we remove the points that are very close the its neightours). In this case the minimization of the dispersion is a must

See Also

REMOVE_POINTS.

See StepDispersion and StepDispersionGradient.

Definition at line 44 of file samples.c.

#define REMOVE_POINTS   ((DISPERSION)&&(1))

If set, we remove the points that are too close each other during the path gradient optimization.

It can only be set if DISPERSION is also set.

Definition at line 54 of file samples.c.

#define APPROXIMATED_CHARTS_IN_GRADIENT   1

When displacing a point along a gradient we have to compute the chart at this point. Howerver, this chart is very close to the chart at the original point (the point before the gradient displacement. If this flag is set, we use the already computed chart as an approximation of the chart at the new point.

Todo:

Verify that this results in actual speed up.

Definition at line 69 of file samples.c.

Function Documentation

double StepDispersion	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xp,
		double *	x,
		double *	xn,
		unsigned int	current,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tworld *	w
	)

Penalizes path steps that have different length. This is used to evenly distribute the path step along the path.

For a path sequence (x_1,x_2,x_3), the formula to optimize is

• (|x_2-x_1|-|x_3-x_2|)^2

i.e., penalizes the difference in length of the two path steps around x_2. This is applied for all points on the path (except for 'stalled' points, i.e., points that can not be moved due to collision, for instance).

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	First point in the path (simplified).
x	Second point along the path. This is the point used to compute the cost.
xn	Third point along the path.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	Chart on c1. Atually not used. Can be NULL.
c	Chart on c2. Atually not used. Can be NULL.
cn	Chart on c3. Atually not used. Can be NULL.
w	The world structure.

Definition at line 1112 of file samples.c.

References DistanceTopologySubset().

Referenced by CombineGradients(), EffortAndDispersion(), LengthAndDispersion(), and SmoothSamples().

boolean StepDispersionGradient	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xpp,
		double *	xp,
		double *	x,
		double *	xn,
		double *	xnn,
		Tchart *	cpp,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tchart *	cnn,
		TJacobian *	sJ,
		TStepCost	cost,
		double *	u,
		Tworld *	w
	)

Gradient of the StepDispersion cost funtion.

Note that the actual position of a point (say x_3) affects the cost of different triplets of points

• (x_1,x_2,x_3)
• (x_2,x_3,x_4)
• (x_3,x_4,x_5)

We have to accumulate the gradient in the three cases. This is why this function consideres sequences of 5 points (x_1,x_2,x_3,x_4,x_5), but returns the derivative w.r.t x_3.

Note that the step dispersion is orthogonal ot any other cost to evaluate on the path. Thus it can be applied on the top of different cost functions (path length, path effort, ...).

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	First point in the sequence. NULL at the beginning of the path.
xp	Second point in the sequence.
x	Third point in the sequence.
xn	Fourth point in the sequence.
xnn	Fith point in the sequence. NULL at the end of the path.
cpp	Chart at xpp.
cp	Chart at xp.
c	Chart at x.
cn	Chart at xn.
cnn	Chart at xnn.
sJ	The symbolic Jacobian of the constraints. Not used. Can be NULL.
cost	Cost function. Not used. Can be NULL.
u	The resulting gradient (in tangent space!) of the cost function w.r.t. x_3.
w	The world structure.

Returns

TRUE if the gradient could be computed.

Definition at line 1135 of file samples.c.

References CT_EPSILON, CT_N_DOF, DifferenceVectorTopologySubset(), DistanceTopologySubset(), FALSE, GetChartTangentSpace(), GetParameter(), NEW, Norm(), ScaleVector(), SumVectorScale(), TMatrixVectorProduct(), and TRUE.

Referenced by EffortAndDispersionGradient(), LengthAndDispersionGradient(), and SmoothSamples().

double StepLength	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xp,
		double *	x,
		double *	xn,
		unsigned int	current,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tworld *	w
	)

Auxiliary function used to compute the path length.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	Fist poinnt in the path. Not used. Can be NULL.
x	Second point in the path (simplified).
xn	point along the path. Not used. Can be NULL.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	A chart on xp
c	A chart defined on x.
cn	A chart defined on xn. Not used. Cam be NULL.
w	The world structure.

Definition at line 1203 of file samples.c.

References DistanceTopologySubset(), and Error().

Referenced by CombineGradients(), EffortAndDispersionGradient(), LengthAndDispersion(), LengthAndDispersionGradient(), and SmoothSamples().

boolean StepLengthGradient	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xpp,
		double *	xp,
		double *	x,
		double *	xn,
		double *	xnn,
		Tchart *	cpp,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tchart *	cnn,
		TJacobian *	sJ,
		TStepCost	cost,
		double *	u,
		Tworld *	w
	)

Auxiliary function used to compute the gradient of a path step length (see StepLength).

It is used also when smoothing a path via gradient descent.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1224 of file samples.c.

References CT_EPSILON, CT_N_DOF, DifferenceVectorTopologySubset(), FALSE, GetChartTangentSpace(), GetParameter(), NEW, Norm(), ScaleVector(), SumVectorScale(), TMatrixVectorProduct(), and TRUE.

Referenced by LengthAndDispersionGradient(), and SmoothSamples().

double StepEffort	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xp,
		double *	x,
		double *	xn,
		unsigned int	current,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tworld *	w
	)

Auxiliary function used to compute the path control effort (see PathEffort).

Computes the control effort of moving from x1 to x2 taking into account the drift introduced by the potential energy gradient. If there is no such a gradient, the output is close to the step length.

Note that we actually compute and approximation of the control effort. The shorter the steps in the path, the closer the approximation.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	Previous point in the path. Actually not used. Can be NULL.
x	Current point in the path (simplified).
xn	Next point along the path.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn. Actually not used. Can be NULL.
w	The world structure.

Definition at line 1275 of file samples.c.

References CT_EPSILON, CT_N_DOF, DifferenceVector(), DifferenceVectorTopologySubset(), Error(), GeneralDotProduct(), GetChartTangentSpace(), GetParameter(), KINEMATIC_SUBSPACE, NEW, Norm(), ScaleVector(), TMatrixVectorProduct(), TRUE, and WorldForceField().

Referenced by EffortAndDispersion(), PathEffort(), and SmoothSamples().

boolean StepEffortGradient	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xpp,
		double *	xp,
		double *	x,
		double *	xn,
		double *	xnn,
		Tchart *	cpp,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tchart *	cnn,
		TJacobian *	sJ,
		TStepCost	cost,
		double *	u,
		Tworld *	w
	)

Auxiliary function used to compute the gradient of a path step control effort (see StepEffort).

This is also used to smooth a path via gradient descent.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1344 of file samples.c.

References CT_EPSILON, CT_N_DOF, DifferenceVector(), DifferenceVectorTopologySubset(), Error(), FALSE, GeneralDotProduct(), GetChartTangentSpace(), GetParameter(), MatrixVectorProduct(), NEW, Norm(), ScaleVector(), SumVectorScale(), TMatrixVectorProduct(), TRUE, WorldForceField(), and WorldForceFieldProjectedGradient().

Referenced by EffortAndDispersionGradient(), and SmoothSamples().

boolean StepCostNumericalGradient	(	Tparameters *	p,
		unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		double *	xpp,
		double *	xp,
		double *	x,
		double *	xn,
		double *	xnn,
		Tchart *	cpp,
		Tchart *	cp,
		Tchart *	c,
		Tchart *	cn,
		Tchart *	cnn,
		TJacobian *	sJ,
		TStepCost	cost,
		double *	u,
		Tworld *	w
	)

Numerical gradient. Works for any cost function but it is slower than a specific gradient.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1558 of file samples.c.

References Chart2Manifold(), CT_EPSILON, CT_N_DOF, FALSE, GetParameter(), INF, NEW, and TRUE.

Referenced by GradientSmooth().

double CombineCosts ( TStepCost  c1, TStepCost  c2, Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xp, double *  x, double *  xn, unsigned int  current, Tchart *  cp, Tchart *  c, Tchart *  cn, Tworld *  w  )

inline

Adds two cost functions.

Parameters

c1	The first cost function to add.
c2	The second cost function to add.
p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	Previous point in the path. Actually not used. Can be NULL.
x	Current point in the path (simplified).
xn	Next point along the path.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn. Actually not used. Can be NULL.
w	The world structure.

Definition at line 1611 of file samples.c.

Referenced by EffortAndDispersion(), and LengthAndDispersion().

boolean CombineGradients ( TStepCostGradient  g1, TStepCostGradient  g2, Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xpp, double *  xp, double *  x, double *  xn, double *  xnn, Tchart *  cpp, Tchart *  cp, Tchart *  c, Tchart *  cn, Tchart *  cnn, TJacobian *  sJ, TStepCost  cost, double *  u, Tworld *  w  )

inline

Gradient of CombineCosts (if called with the right set of parameters).

Parameters

g1	The first gradient to add.
g2	Teh second gradient to add.
p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1622 of file samples.c.

References CT_N_DOF, GetParameter(), NEW, StepDispersion(), StepLength(), and SumVector().

Referenced by EffortAndDispersionGradient(), and LengthAndDispersionGradient().

double LengthAndDispersion ( Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xp, double *  x, double *  xn, unsigned int  current, Tchart *  cp, Tchart *  c, Tchart *  cn, Tworld *  w  )

inline

Adds the length and dispersion cost functions. See CombineCosts.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	Previous point in the path. Actually not used. Can be NULL.
x	Current point in the path (simplified).
xn	Next point along the path.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn. Actually not used. Can be NULL.
w	The world structure.

Definition at line 1658 of file samples.c.

References CombineCosts(), StepDispersion(), and StepLength().

Referenced by SmoothSamples().

boolean LengthAndDispersionGradient ( Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xpp, double *  xp, double *  x, double *  xn, double *  xnn, Tchart *  cpp, Tchart *  cp, Tchart *  c, Tchart *  cn, Tchart *  cnn, TJacobian *  sJ, TStepCost  cost, double *  u, Tworld *  w  )

inline

Gradient of LengthAndDispersion.

See CombineGradients.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1668 of file samples.c.

References CombineGradients(), StepDispersionGradient(), StepLength(), and StepLengthGradient().

Referenced by SmoothSamples().

double EffortAndDispersion ( Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xp, double *  x, double *  xn, unsigned int  current, Tchart *  cp, Tchart *  c, Tchart *  cn, Tworld *  w  )

inline

Adds the control effort and dispersion cost functions.

See CombineCosts.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xp	Previous point in the path. Actually not used. Can be NULL.
x	Current point in the path (simplified).
xn	Next point along the path.
current	Which of the three points is the current (i.e., the point for which we evaluate the cost).
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn. Actually not used. Can be NULL.
w	The world structure.

Definition at line 1683 of file samples.c.

References CombineCosts(), StepDispersion(), and StepEffort().

Referenced by SmoothSamples().

boolean EffortAndDispersionGradient ( Tparameters *  p, unsigned int *  tp, boolean *  sv, unsigned int  m, double *  xpp, double *  xp, double *  x, double *  xn, double *  xnn, Tchart *  cpp, Tchart *  cp, Tchart *  c, Tchart *  cn, Tchart *  cnn, TJacobian *  sJ, TStepCost  cost, double *  u, Tworld *  w  )

inline

Gradient of EffortAndDispersion.

See CombineGradients.

Parameters

p	The set of parameters.
tp	The topology of the variables (in simplified system).
sv	The selected variables to compute the path length component of the effort.
m	The size of the points (in simplified system!)
xpp	Previous of the previous point in the path. Not used. Can be NULL.
xp	Previous point in the path.
x	Current point. We compute the gradient with respect to this point.
xn	Next point in the path.
xnn	Next of the next point in the path. Not used. Can be NULL.
cpp	Chart at xpp. Not used. Can be NULL.
cp	A chart defined on xp.
c	A chart defined on x.
cn	A chart defined on xn.
cnn	Chart at xnn. Not used. Can be NULL.
sJ	The symbolic Jacobian of the constraints.
cost	Cost function.
u	The output gradient (in tangent space!)
w	The world structure.

Returns

TRUE if the gradient can be actually computed.

Definition at line 1693 of file samples.c.

References CombineGradients(), StepDispersionGradient(), StepEffortGradient(), and StepLength().

Referenced by SmoothSamples().

int cmpUInt	(	const void *	a,
		const void *	b
	)

Auxiliary function used for qsort inside RandomSmooth when we exploit parallelism to speed up the smoothing.

Parameters

a	Pointer to the first unsigned integer.
b	Pointer to the second unsigned integer.

Returns

-1 if a<b, 0 if a==b, or 1 if a>b.

Definition at line 1803 of file samples.c.

Referenced by RandomSmooth().

void ShortcutSmooth	(	Tparameters *	pr,
		boolean *	sv,
		Tstatistics *	stime,
		unsigned int *	np,
		double ***	point,
		TAtlasBase *	w
	)

This is like the RandomSmooth but the tentative shortcuts are selected systematically: from the first sample as far as possible and so on.

Parameters

pr	The set of parameters.
sv	The variables to use in the distance computations.
stime	Statistics initilized at the beginning of the smoothing process.
np	Number of points defining the path.
point	The points defining the path.
w	The world/cuiksystem on which the sample is defined.

Definition at line 1819 of file samples.c.

References CS_WD_GENERATE_SIMP_INITIAL_BOX, CS_WD_GET_SIMP_JACOBIAN, CS_WD_GET_SIMP_TOPOLOGY, CS_WD_INIT_CD, CT_N_DOF, DEFAULT_CONNECT, DeleteBox(), DeleteJacobian(), DeleteSamples(), FALSE, GetElapsedTime(), GetParameter(), PathLength(), and TRUE.

Referenced by SmoothSamples().

void RandomSmooth	(	Tparameters *	pr,
		unsigned int	nCores,
		unsigned int	maxIterations,
		boolean *	sv,
		Tstatistics *	stime,
		unsigned int *	np,
		double ***	point,
		TAtlasBase *	w
	)

Tries to reduce the lenght of a path by ramdomly selecting points on the path and verifying if a direct collision free path between them exists. If so, the new path replaces a segment of the previous path.

IMPORTANT: this is a sub-process of SmoothSamples and it is intended for internal use only and the points are defined in the simplified system and not in the original system as most of the functions on samples.

Parameters

pr	The set of parameters.
nCores	Number of computing cores available.
maxIterations	Maximum number of iterations. To be scaled by the number of steps in the path.
sv	Array with the components to use distance computations.
stime	Statistics initilized at the beginning of the smoothing process.
np	Number of points defining the path.
point	The points defining the path.
w	The world/cuiksystem on which the sample is defined.

Definition at line 1927 of file samples.c.

References cmpUInt(), CS_WD_GENERATE_SIMP_INITIAL_BOX, CS_WD_GET_SIMP_JACOBIAN, CS_WD_GET_SIMP_TOPOLOGY, CS_WD_INIT_CD, CT_N_DOF, DEFAULT_CONNECT, DeleteBox(), DeleteJacobian(), DeleteSamples(), FALSE, GetElapsedTime(), GetParameter(), NEW, PathLength(), randomMax(), and TRUE.

Referenced by SmoothSamples().

void GradientSmooth	(	Tparameters *	pr,
		unsigned int	nCores,
		unsigned int	maxIterations,
		boolean *	sv,
		Tstatistics *	stime,
		unsigned int *	np,
		double ***	point,
		TStepCost	stepCost,
		TStepCostGradient	stepCostGradient,
		TAtlasBase *	w
	)

Reduces the length of a path by applying a movement to the points forming the path according the the gradient of the path lenght for w.r.t. the parameters of this points.

IMPORTANT: this is a sub-process of SmoothSamples and it is intended for internal use only and the points are defined in the simplified system and not in the original system as most of the functions on samples.

Parameters

pr	The set of parameters.
nCores	Number of computing cores available. Up to now this is not used.
maxIterations	Maximum number of iterations. To be scaled by the number of steps in the path.
sv	Array with the components to use distance computations.
stime	Statistics initilized at the beginning of the smoothing process.
np	Number of points defining the path.
point	The points defining the path.
stepCost	Function giving the cost of moving between two path steps See TStepCost
stepCostGradient	Function giving the gradient of the cost when moving a point in between two other points along the path. See TStepCostGradient If NULL a numerical gradient is used.
w	The world/cuiksystem on which the sample is defined.

Todo:

Implement a parallel version of the GradientSmooth function.

Definition at line 2149 of file samples.c.

References Chart2Manifold(), CopyChart(), CS_WD_GENERATE_SIMP_INITIAL_BOX, CS_WD_GET_SIMP_JACOBIAN, CS_WD_GET_SIMP_TOPOLOGY, CS_WD_IN_COLLISION, CS_WD_INIT_CD, CT_CE, CT_DELTA, CT_E, CT_EPSILON, CT_N_DOF, CT_R, DeleteBox(), DeleteChart(), DeleteJacobian(), DistanceTopology(), Error(), FALSE, GeneralDotProduct(), GET_WORLD, GetElapsedTime(), GetJacobianSize(), GetParameter(), INF, InitTrustedChart(), NEW, NEWZ, PointInBoxTopology(), ScaleVector(), StepCostNumericalGradient(), and TRUE.

Referenced by SmoothSamples().

void SaveSamplesInt	(	Tfilename *	fpath,
		unsigned int	nvs,
		unsigned int	ns,
		double **	path
	)

Internal function to save a set of samples to a file. This includes code shared by SaveSamples and SaveSamplesN.

Parameters

fpath	Name of the file where to store the samples.
nvs	The dimensionality of each sample.
ns	The number of samples defining the path.
path	The collection of samples defining the path.

Definition at line 2845 of file samples.c.

References DeleteBox(), Error(), GetFileFullName(), InitBoxFromPoint(), and PrintBox().

Referenced by SaveSamples(), and SaveSamplesN().

void InitSamples	(	unsigned int *	ms,
		unsigned int *	ns,
		double ***	path
	)

Initializes the space where to store the samples.

Parameters

ms	Max number of samples in the set. This will be automatically enlarged in AddSample2Samples if necessary.
ns	Number of samples in the set. 0 after initialization.
path	The sample set.

Definition at line 665 of file samples.c.

References INIT_NUM_SAMPLES, and NEW.

Referenced by AddBranchToAtlasRRT(), ConnectSamples(), ConnectSamplesChart(), MinimizeOnAtlas(), New_AddBranchToAtlasRRT(), ReconstructAtlasPath(), ReconstructAtlasRRTPath(), Steps2PathinAtlasRRT(), and Steps2PathinRRT().

void AddSample2Samples	(	unsigned int	nv,
		double *	sample,
		unsigned int	nvs,
		boolean *	systemVars,
		unsigned int *	ms,
		unsigned int *	ns,
		double ***	path
	)

Adds a sample to a set of samples. The sample is given in full form (including all variables) but we only store the system variables.

Parameters

nv	Number of variables.
sample	The sample to add.
nvs	Number of system variables.
systemVars	Array to identify the system variables. Use NULL if all variables are to be included in the sample.
ms	Max number of samples in the set. This will be automatically enlarged in AddSample2Samples if necessary.
ns	Number of samples in the set. 0 after initialization.
path	The sample set.

Definition at line 672 of file samples.c.

References MEM_DUP, and NEW.

Referenced by AddBranchToAtlasRRT(), ConnectSamples(), ConnectSamplesChart(), MinimizeOnAtlas(), New_AddBranchToAtlasRRT(), PathInChart(), ReconstructAtlasPath(), ReconstructAtlasRRTPath(), SmoothSamples(), Steps2PathinAtlasRRT(), and Steps2PathinRRT().

double ConnectSamplesChart	(	Tparameters *	pr,
		unsigned int *	tp,
		boolean *	sv,
		Tbox *	domain,
		unsigned int	m,
		unsigned int	n,
		double *	s1,
		double *	s2,
		double	md,
		boolean	checkCollisions,
		TJacobian *	sJ,
		boolean *	reached,
		boolean *	collision,
		double *	lastSample,
		unsigned int *	ns,
		double ***	path,
		TAtlasBase *	w
	)

Determines if two points on the manifold can be connected with a path of length below a given threshold.

This is the same as ConnectSamples but using a chart-based way to move over the manifold from s1 to s2.

As in the case of ConnectSamples the connection can fail depending on the shape of the manifold. However, for close samples it typically works fine.

This can be seen as a simply version of AddBranchToAtlasRRT. The main difference is that here we do not maintain an atlas: we generate charts as we advance over the manifold but we release them when they are not any longer useful.

IMPORTANT: here samples are suposed to be given in the simplified form and not in the non-simplified one, as it is the case of many of the functions on samples.

Parameters

pr	The set of parameters.
tp	The topology for the variables.
sv	Components of the configuration to use to compute the length of the connection. If NULL all components are used. Up to now, it is only used for path smoothing purposes.
domain	The domain for the variables.
m	The size of each sample. IMPORTANT: here samples are suposed to be given in the simplified form and not in the non-simplified one, as it is the case of many of the functions on samples.
n	The number of equations in the problem. This is actually not used in this function but we keep this parameter for compatibility with ConnectSamples.
s1	The first sample to connect.
s2	The second sample to connect.
md	Maximum displacement between the two samples (along the components selected by 'sv').
checkCollisions	TRUE if the path has to be collision free.
sJ	The symbolic Jacobian.
reached	(output) TRUE if s2 can be reached form s1.
collision	(output) TRUE if the connection can not be established due to a collision.
lastSample	Buffer to store the last sample generated along the path from s1 to s2. Set to NULL if this sample is not requiered.
ns	Number of steps of the path connecting the two samples.
path	Samples along the path connecting the two samples. Set ns or path to NULL if you are not interested in the path but only in verifying that the two samples can be connected. Note that the two given samples are NOT included in this output path.
w	The The world/cuiksystem on which the sample is defined.

Returns

The maximum distance travelled form s1 to s2. The distance from s1 to the sample stored in 'lastSample', if any.

Definition at line 694 of file samples.c.

References AccumulateVector(), AddSample2Samples(), ArrayPi2Pi(), Chart2Manifold(), CS_WD_IN_COLLISION, CS_WD_SIMP_INEQUALITIES_HOLD, CT_CE, CT_DELTA, CT_E, CT_EPSILON, CT_N_DOF, CT_R, DeleteChart(), DeleteSamples(), DifferenceVector(), DifferenceVectorTopology(), DistanceTopology(), DistanceTopologySubset(), Error(), FALSE, GetJacobianSize(), GetParameter(), InitChart(), InitSamples(), Manifold2Chart(), NEW, Norm(), PointInBoxTopology(), ScaleVector(), SumVectorScale(), and TRUE.

Referenced by WireAtlasRRTstar().

double ConnectSamples	(	Tparameters *	pr,
		unsigned int *	tp,
		boolean *	sv,
		Tbox *	domain,
		unsigned int	m,
		unsigned int	n,
		double *	s1,
		double *	s2,
		double	md,
		boolean	checkCollisions,
		TJacobian *	sJ,
		boolean *	reached,
		boolean *	collision,
		double *	lastSample,
		unsigned int *	ns,
		double ***	path,
		TAtlasBase *	w
	)

Determines if two points on the manifold can be connected with a path of length below a given threshold.

The method used to determine the path does not return the sortest path and it can fail in many cases, specially when the samples are far away.

IMPORTANT: here samples are suposed to be given in the simplified form and not in the non-simplified one, as it is the case of many of the functions on samples.

Parameters

pr	The set of parameters.
tp	The topology for the variables.
sv	Components of the configuration to use to compute the length of the connection. If NULL all components are used. Up to now, it is only used for path smoothing purposes.
domain	The domain for the variables.
m	The size of each sample. IMPORTANT: here samples are suposed to be given in the simplified form and not in the non-simplified one, as it is the case of many of the functions on samples.
n	The number of equations in the problem.
s1	The first sample to connect.
s2	The second sample to connect.
md	Maximum displacement between the two samples (along the components selected by 'sv').
checkCollisions	TRUE if the path has to be collision free.
sJ	The symbolic Jacobian. It is actually not used in this function but the parameter is keep for compatibility with ConnectSamplesChart. You can safely set it to NULL in this case.
reached	(output) TRUE if s2 can be reached form s1.
collision	(output) TRUE if the connection can not be established due to a collision.
lastSample	Buffer to store the last sample generated along the path from s1 to s2. Set to NULL if this sample is not requiered.
ns	Number of steps of the path connecting the two samples.
path	Samples along the path connecting the two samples. Set ns or path to NULL if you are not interested in the path but only in verifying that the two samples can be connected. Note that the two given samples are NOT included in this output path.
w	The The world/cuiksystem on which the sample is defined.

Returns

The maximum distance travelled form s1 to s2. The distance from s1 to the sample stored in 'lastSample', if any.

Definition at line 966 of file samples.c.

References AddSample2Samples(), ArrayPi2Pi(), CS_WD_IN_COLLISION, CS_WD_NEWTON_IN_SIMP, CS_WD_SIMP_INEQUALITIES_HOLD, CT_DELTA, CT_EPSILON, DeleteSamples(), DifferenceVectorTopology(), DistanceTopology(), DistanceTopologySubset(), DIVERGED, FALSE, GetParameter(), InitSamples(), NEW, Norm(), PointInBoxTopology(), SumVectorScale(), and TRUE.

Referenced by AddStepToRRTstar(), BiRRTstar(), ReWireRRTstar(), Steps2PathinRRT(), and WireRRTstar().

double PathLength	(	unsigned int *	tp,
		boolean *	sv,
		unsigned int	m,
		unsigned int	np,
		double **	point
	)

Computes the length of a path defined by a set of points. IMPORTANT: this is for internal use only and the points are defined in the simplified system and not in the original system as most of the functions on samples.

Parameters

tp	The topology of the variables.
sv	The components to use in the distance computation.
m	The size of each point.
np	Number of points in the path.
point	The set of points.

Returns

The path length.

Definition at line 1096 of file samples.c.

References DistanceTopologySubset().

Referenced by main(), RandomSmooth(), ShortcutSmooth(), and SmoothSamples().

double PathEffort	(	Tparameters *	p,
		unsigned int	m,
		unsigned int	np,
		double **	point,
		Tworld *	w
	)

Computes the approximated control effort of a path. This only makes sense in problems where there is an associated energy which generates a force field (i.e., the gradient of the energy). The control effort is the effort to compensate this force field and to drive the robot along the path. If no force filed is defined, the control effort gives the path length (see PathLength).

The control effort is defined over the continuous path and we approximate it at discrete times (i.e., an integral approximated as a discrete sum).

Parameters

p	The set of parameters.
m	The size of each point.
np	Number of points in the path.
point	The set of points.
w	The world structure giving semantic to the path points.

Returns

The (approximated) control effort along the path.

Definition at line 1708 of file samples.c.

References ChangeParameter(), CS_WD_FROM_WORLD, CT_CE, CT_E, CT_N_DOF, CT_R, DeleteBox(), DeleteChart(), DeleteJacobian(), Error(), GetParameter(), GetWorldSimpInitialBox(), GetWorldSimpJacobian(), GetWorldSimpTopology(), InitTrustedChart(), KINEMATIC_SUBSPACE, NEW, RegenerateWorldSolutionPoint(), StepEffort(), TRUE, WorldGenerateSimplifiedPoint(), WorldManifoldDimension(), and WorldSimpKinematicVars().

Referenced by main().

void SmoothSamples	(	Tparameters *	pr,
		boolean	parallel,
		int	mode,
		unsigned int	maxIterations,
		unsigned int	ns,
		double **	path,
		unsigned int *	sns,
		double ***	spath,
		TAtlasBase *	w
	)

Produces a path that (locally) minimizes the length and connects the two extremes of the given path.

This implements a basic smoothing structure transforming the input samples (in the original system) to the simplified system and then call a speciallized smoothing procedure.

Only path with more than 2 steps are suitable of optimization. Otherwise this function triggers an error.

Parameters

pr	The set of parameters.
parallel	TRUE if we have to execute a parallel vesion of smoothing process. Not relevant in SMOOTH_CUT.
mode	Smoothing mode to be used: SMOOTH_RANDOM, SMOOTH_GRADIENT, or SMOOTH_CUT.
maxIterations	Maximum number of iterations. To be scaled by the number of steps in the path.
ns	The numer of samples in the input path.
path	The samples in the input path.
sns	The number of samples in the output (smoothed) path.
spath	The samples in the output (smoothed) path.
w	The The world/cuiksystem on which the sample is defined.

Definition at line 2541 of file samples.c.

References AddSample2Samples(), ChangeParameter(), CS_WD_GENERATE_SIMPLIFIED_POINT, CS_WD_GET_SIMP_TOPOLOGY, CS_WD_GET_SYSTEM_VARS, CS_WD_MANIFOLD_DIMENSION, CS_WD_REGENERATE_ORIGINAL_POINT, CS_WD_REGENERATE_SOLUTION_POINT, CT_DELTA, CT_N_DOF, DeleteStatistics(), EffortAndDispersion(), EffortAndDispersionGradient(), Error(), GET_WORLD, GetElapsedTime(), GetParameter(), GradientSmooth(), InitStatistics(), KINEMATIC_SUBSPACE, LengthAndDispersion(), LengthAndDispersionGradient(), NEW, ON_CUIKSYSTEM, PathLength(), RandomSmooth(), ShortcutSmooth(), SMOOTH_DISPERSION, SMOOTH_EFFORT, SMOOTH_GRADIENT, SMOOTH_RANDOM, SMOOTH_SHORTCUT, StepDispersion(), StepDispersionGradient(), StepEffort(), StepEffortGradient(), StepLength(), StepLengthGradient(), and WorldSimpKinematicVars().

Referenced by main().

void ConcatSamples	(	unsigned int	nvs,
		unsigned int	ns1,
		double **	path1,
		unsigned int	ns2,
		double **	path2,
		unsigned int *	ns,
		double ***	path
	)

Produces a path that is the concatenation of two paths.

Parameters

nvs	The number of values per sample.
ns1	The number of samples defining the first path.
path1	The collection of samples defining the first path.
ns2	The number of samples defining the second path.
path2	The collection of samples defining the second path.
ns	The number of samples defining the output path.
path	The collection of samples defining the output path.

Definition at line 2706 of file samples.c.

References NEW.

void ReverseConcatSamples	(	unsigned int	nvs,
		unsigned int	ns1,
		double **	path1,
		unsigned int	ns2,
		double **	path2,
		unsigned int *	ns,
		double ***	path
	)

Produces a path that is the concatenation of a path and the reverse of a second path. This is basically used to reconstruct paths for bidirectional (Atlas)RRTs.

Parameters

nvs	The number of values per sample.
ns1	The number of samples defining the first path.
path1	The collection of samples defining the first path.
ns2	The number of samples defining the second path.
path2	The collection of samples defining the second path.
ns	The number of samples defining the output path.
path	The collection of samples defining the output path.

Definition at line 2727 of file samples.c.

References NEW.

Referenced by PathStart2GoalInRRT().

void ReverseSamples	(	unsigned int	ns,
		double **	path
	)

Reverses a set of samples.

Parameters

ns	Number of samples.
path	The samples to reverse.

Definition at line 2752 of file samples.c.

Referenced by ReconstructAtlasRRTPath(), and ReconstructRRTPath().

unsigned int ReadOneSample	(	Tparameters *	p,
		char *	fname,
		unsigned int	nvs,
		double **	s
	)

Reads one sample from a file.

If the mechanisms representation is DOF-based (see REP_JOINTS) the samples are read from a .dof file. Otherwise they are read from a .samples file.

Parameters

p	The set of parameters.
fname	File from where to read the sample.
nvs	Number of system variables in the problem = Number of values in the sample.
s	Where to store the sample. The space is allocated internally.

Returns

The dimensionality of the sample. Number of system variables of w.

Definition at line 2772 of file samples.c.

References CreateFileName(), CT_REPRESENTATION, DeleteFileName(), Error(), GetFileFullName(), GetParameter(), JOINTS_EXT, LINKS_EXT, NEW, and REP_JOINTS.

Referenced by main().

unsigned int ReadTwoSamples	(	Tparameters *	p,
		char *	fname,
		unsigned int	nvs,
		double **	s1,
		double **	s2
	)

Reads two sample from a file.

If the mechanisms representation is DOF-based (see REP_JOINTS) the samples are read from a .dof file. Otherwise they are read from a .samples file.

Parameters

p	The set of parameters.
fname	File from where to read the sample.
nvs	Number of system variables in the problem = Number of values in the sample.
s1	Where to store the first sample. The space is allocated internally.
s2	Where to store the second sample. The space is allocated internally.

Returns

The dimensionality of the sample. Number of system variables of w.

Definition at line 2803 of file samples.c.

References CreateFileName(), CT_EPSILON, CT_REPRESENTATION, DeleteFileName(), Distance(), Error(), GetFileFullName(), GetParameter(), JOINTS_EXT, LINKS_EXT, NEW, and REP_JOINTS.

Referenced by main().

void SaveSamples	(	char *	fname,
		char *	suffix,
		unsigned int	nvs,
		unsigned int	ns,
		double **	path
	)

Saves a set of samples (possibly defining a solution path) to a file.

Parameters

fname	The file where to store the samples.
suffix	Suffix to be added to the filename. It is used when generating smoothed paths.
nvs	The dimensionality of each sample.
ns	The number of samples defining the path.
path	The collection of samples defining the path.

Definition at line 2879 of file samples.c.

References CreateFileName(), DeleteFileName(), SaveSamplesInt(), and SOL_EXT.

Referenced by main(), and MinimizeOnAtlas().

void SaveSamplesN	(	char *	fname,
		boolean	smooth,
		unsigned int	n,
		unsigned int	nvs,
		unsigned int	ns,
		double **	path
	)

Saves a set of samples (possibly defining a solution path) to a file. This function is used to save sets of paths.

Parameters

fname	The file where to store the samples.
smooth	TRUE if the set of samples is the result of a smoothing process.
n	The number of this path. Used to define a different name for a sequence of paths to store.
nvs	The dimensionality of each sample.
ns	The number of samples defining the path.
path	The collection of samples defining the path.

Definition at line 2894 of file samples.c.

References CreateFileName(), DeleteFileName(), SaveSamplesInt(), and SOL_EXT.

Referenced by MinimizeOnAtlas().

boolean LoadSamples	(	Tfilename *	fname,
		unsigned int *	nvs,
		unsigned int *	ns,
		double ***	path
	)

Reads a set of samples from a file created using SaveSamples.

Parameters

fname	Name of the file containing the samples.
nvs	Number of entries for each sample.
ns	Number of samples (output).
path	The set of samples (output).

Returns

TRUE if the sample set could be actually read.

Definition at line 2913 of file samples.c.

References Advance(), DeleteListOfBoxes(), EndOfList(), Error(), FALSE, First(), GetBoxCenter(), GetBoxNIntervals(), GetCurrent(), GetFileFullName(), InitIterator(), ListSize(), NEW, ReadListOfBoxes(), and TRUE.

Referenced by main().

void PlotSamples	(	Tparameters *	p,
		Tplot3d *	p3d,
		unsigned int	xID,
		unsigned int	yID,
		unsigned int	zID,
		unsigned int	ns,
		double **	path
	)

Plots a 3D projection of a set of samples representing a path. The path is represented by a red line.

Parameters

p	The set of parametres.
p3d	The 3d plot where to add the plot.
xID	First dimension for the projection (in the original system including system vars only).
yID	Second dimension for the projection (in the original system including system vars only).
zID	Third dimension for the projection (in the original system including system vars only).
ns	The number of samples.
path	The set of samples.

Definition at line 2960 of file samples.c.

References Close3dObject(), CT_CUT_X, CT_CUT_Y, CT_CUT_Z, DeleteColor(), GetParameter(), M_2PI, NEW, NewColor(), PlotVect3d(), and StartNew3dObject().

Referenced by main().

void PlotForceField	(	Tparameters *	p,
		Tplot3d *	p3d,
		unsigned int	xID,
		unsigned int	yID,
		unsigned int	zID,
		Tworld *	w,
		unsigned int	ns,
		double **	sols
	)

Plots a 3D projection of the force field on a set of points. The force filed is represented as a short line on each point pointing in the direction of the force field and with length proportional to the force-field magnitude.

Parameters

p	The set of parametres.
p3d	The 3d plot where to add the plot.
xID	First dimension for the projection (in the original system including system vars only).
yID	Second dimension for the projection (in the original system including system vars only).
zID	Third dimension for the projection (in the original system including system vars only).
w	The world from where to compute the force field.
ns	The number of solution points.
sols	The set of solution points.

Definition at line 3056 of file samples.c.

References Close3dObject(), CT_DELTA, CT_EPSILON, DeleteColor(), Error(), FALSE, GetParameter(), GetWorldSystemVars(), INF, NEW, NewColor(), NO_UINT, Norm(), PlotLine(), RegenerateWorldSolutionPoint(), ScaleVector(), StartNew3dObject(), Warning(), and WorldForceField().

Referenced by main().

void DeleteSamples	(	unsigned int	ns,
		double **	path
	)

Release the memory used by a set of samples.

Parameters

ns	The number of samples.
path	The set of samples.

Definition at line 3159 of file samples.c.

Referenced by ConnectSamples(), ConnectSamplesChart(), main(), PathStart2GoalInRRT(), RandomSmooth(), ReconstructAtlasRRTPath(), ShortcutSmooth(), Steps2PathinAtlasRRT(), and Steps2PathinRRT().