|
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface Kernel1dShape
Factory interface for for Kernel1d smoothing functional forms.
Some implementations are provided in the StandardKernel1dShape
class.
Method Summary | |
---|---|
Kernel1d |
createFixedWidthKernel(double width)
Creates a fixed width kernel with a given nominal width. |
Kernel1d |
createKnnKernel(double k,
boolean isSymmetric,
int minWidth,
int maxWidth)
Creates an adaptive kernel that uses a K-nearest-neighbours algorithm to determine local smoothing width, so that the width of the kernel is determined by the distance (number of 1-pixel bins) within which the given number k of samples is found. |
String |
getDescription()
Returns a short description for this shape. |
String |
getName()
Returns a one-word name for this shape. |
Method Detail |
---|
String getName()
String getDescription()
Kernel1d createFixedWidthKernel(double width)
width
- half-width
Kernel1d createKnnKernel(double k, boolean isSymmetric, int minWidth, int maxWidth)
k
of samples is found.
The nearest neighbour search may be symmetric or asymmetric. In the asymmetric case, the kernel width is determined separately for the positive and negative directions along the axis.
Minimum and maximum smoothing widths are also supplied as bounds
on the smoothing width for the case that the samples are very
dense or very spread out (the latter case covers the edge of the
data region as well).
If minWidth==maxWidth
, the result is a fixed-width kernel.
k
- number of nearest neighbours included in the distance
that characterises the smoothingisSymmetric
- true for bidirectional KNN search,
false for unidirectionalminWidth
- minimum smoothing widthmaxWidth
- maximum smoothing width
|
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |