SubsetMatcher (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- mpicbg.pointdescriptor.matcher.SubsetMatcher

All Implemented Interfaces:

Matcher

Direct Known Subclasses:

ModelPriorSubsetMatcher
```
public class SubsetMatcher
extends Object
implements Matcher
```

Constructor Summary

Constructors
Constructor and Description
`SubsetMatcher(int subsetSize, int numNeighbors)` Matches n out of m neighbor points, the effort increases exponentially(!) For example `SubsetMatcher`(4,4) is identical to calling `SimpleMatcher`(4)

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`protected static int[][]`	`computePD(int n, int k, int offset)`
`protected static int[][]`	`computePDRecursive(int tolerance, int n, int offset)` Computes recursively how to create different PointDescriptors of the same Point when some tolerance is allowed, e.g.
`ArrayList<ArrayList<PointMatch>>`	`createCandidates(AbstractPointDescriptor<?,?> pd1, AbstractPointDescriptor<?,?> pd2)`
`int[][]`	`getNeighbors()`
`double`	`getNormalizationFactor(ArrayList<PointMatch> matches, Object fitResult)` Computes a normalization factor for the case that the different set of `PointMatch`es are not comparable (for example number of neighbors used is not constant)
`int`	`getNumCombinations()`
`int`	`getNumMatchings()`
`int`	`getNumNeighbors()`
`int`	`getRequiredNumNeighbors()`
`int`	`getSubsetSize()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - SubsetMatcher
```
public SubsetMatcher(int subsetSize,
                     int numNeighbors)
```
    Matches n out of m neighbor points, the effort increases exponentially(!) For example SubsetMatcher(4,4) is identical to calling SimpleMatcher(4)
    
    Parameters:
    
    subsetSize - (n) - how many neighbors are matched in each try
    
    numNeighbors - (m) - out of how many neighbors to choose
- Method Detail
  - getNeighbors
```
public int[][] getNeighbors()
```
  - getSubsetSize
```
public int getSubsetSize()
```
  - getNumNeighbors
```
public int getNumNeighbors()
```
  - getNumCombinations
```
public int getNumCombinations()
```
  - getNumMatchings
```
public int getNumMatchings()
```
  - getRequiredNumNeighbors
```
public int getRequiredNumNeighbors()
```
    Specified by:
    
    getRequiredNumNeighbors in interface Matcher
    
    Returns:
    
    The number of nearest neighbors required for this Matcher
  - createCandidates
```
public ArrayList<ArrayList<PointMatch>> createCandidates(AbstractPointDescriptor<?,?> pd1,
                                                         AbstractPointDescriptor<?,?> pd2)
```
    Specified by:
    
    createCandidates in interface Matcher
    
    Returns:
    
    An ArrayList of corresponding set of PointMatches which contain LinkedPoints linking to the actual Point instance they are created from
  - getNormalizationFactor
```
public double getNormalizationFactor(ArrayList<PointMatch> matches,
                                     Object fitResult)
```
    Description copied from interface: Matcher
    
    Computes a normalization factor for the case that the different set of PointMatches are not comparable (for example number of neighbors used is not constant)
    
    Specified by:
    
    getNormalizationFactor in interface Matcher
    
    Parameters:
    
    matches - the set of PointMatches
    
    Returns:
    
    The normalization factor for a certain set of PointMatches
  - computePD
```
protected static int[][] computePD(int n,
                                   int k,
                                   int offset)
```
  - computePDRecursive
```
protected static int[][] computePDRecursive(int tolerance,
                                            int n,
                                            int offset)
```
    Computes recursively how to create different PointDescriptors of the same Point when some tolerance is allowed, e.g. there are outliers which should be identified. For 3 neighbors allowing 2 outliers and starting with the second nearest neigbor (the nearest one is in most cases the one you use as input) the result looks like that: (Each coloum will be one PointDescriptor) |1| |1| |1| |2| |1| |1| |2| |1| |2| |3| |2| |2| |3| |3| |2| |3| |3| |4| |4| |4| |3| |4| |4| |4| |5| |5| |5| |5| |5| |5|
    
    Parameters:
    
    tolerance - - How many tolerance is accepted [0 ... m]
    
    n - - initialized with the number of neighbors
    
    offset - - the starting position for the neighbors, usually 1
    
    Returns:
    
    an array containing the neighbors for each PointDescriptor as array

Class SubsetMatcher

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

SubsetMatcher

Method Detail

getNeighbors

getSubsetSize

getNumNeighbors

getNumCombinations

getNumMatchings

getRequiredNumNeighbors

createCandidates

getNormalizationFactor

computePD

computePDRecursive