| Package | Description |
|---|---|
| org.openimaj.knn.approximate | |
| org.openimaj.util.array | |
| org.openimaj.util.tree |
| Constructor and Description |
|---|
ByteKDTreeNode(byte[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
DoubleKDTreeNode(double[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
FloatKDTreeNode(float[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
IntKDTreeNode(int[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
LongKDTreeNode(long[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
ShortKDTreeNode(short[][] pnts,
IntArrayView inds,
cern.jet.random.Uniform rng)
Construct a new node with the given data
|
| Modifier and Type | Method and Description |
|---|---|
IntArrayView |
IntArrayView.clone() |
IntArrayView |
IntArrayView.subView(int l1,
int r1)
Get a subview of this view from l1 (inclusive) to r1 (exclusive).
|
| Modifier and Type | Method and Description |
|---|---|
IntBytePair |
ByteKDTree.SplitChooser.chooseSplit(byte[][] pnts,
IntArrayView inds,
int depth,
byte[] minBounds,
byte[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntBytePair |
ByteKDTree.BasicMedianSplit.chooseSplit(byte[][] pnts,
IntArrayView inds,
int depth,
byte[] minBounds,
byte[] maxBounds) |
IntBytePair |
ByteKDTree.BBFMedianSplit.chooseSplit(byte[][] pnts,
IntArrayView inds,
int depth,
byte[] minBounds,
byte[] maxBounds) |
IntBytePair |
ByteKDTree.ApproximateBBFMedianSplit.chooseSplit(byte[][] pnts,
IntArrayView inds,
int depth,
byte[] minBounds,
byte[] maxBounds) |
IntBytePair |
ByteKDTree.RandomisedBBFMeanSplit.chooseSplit(byte[][] pnts,
IntArrayView inds,
int depth,
byte[] minBounds,
byte[] maxBounds) |
IntDoublePair |
DoubleKDTree.SplitChooser.chooseSplit(double[][] pnts,
IntArrayView inds,
int depth,
double[] minBounds,
double[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntDoublePair |
DoubleKDTree.BasicMedianSplit.chooseSplit(double[][] pnts,
IntArrayView inds,
int depth,
double[] minBounds,
double[] maxBounds) |
IntDoublePair |
DoubleKDTree.BBFMedianSplit.chooseSplit(double[][] pnts,
IntArrayView inds,
int depth,
double[] minBounds,
double[] maxBounds) |
IntDoublePair |
DoubleKDTree.ApproximateBBFMedianSplit.chooseSplit(double[][] pnts,
IntArrayView inds,
int depth,
double[] minBounds,
double[] maxBounds) |
IntDoublePair |
DoubleKDTree.RandomisedBBFMeanSplit.chooseSplit(double[][] pnts,
IntArrayView inds,
int depth,
double[] minBounds,
double[] maxBounds) |
IntFloatPair |
FloatKDTree.SplitChooser.chooseSplit(float[][] pnts,
IntArrayView inds,
int depth,
float[] minBounds,
float[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntFloatPair |
FloatKDTree.BasicMedianSplit.chooseSplit(float[][] pnts,
IntArrayView inds,
int depth,
float[] minBounds,
float[] maxBounds) |
IntFloatPair |
FloatKDTree.BBFMedianSplit.chooseSplit(float[][] pnts,
IntArrayView inds,
int depth,
float[] minBounds,
float[] maxBounds) |
IntFloatPair |
FloatKDTree.ApproximateBBFMedianSplit.chooseSplit(float[][] pnts,
IntArrayView inds,
int depth,
float[] minBounds,
float[] maxBounds) |
IntFloatPair |
FloatKDTree.RandomisedBBFMeanSplit.chooseSplit(float[][] pnts,
IntArrayView inds,
int depth,
float[] minBounds,
float[] maxBounds) |
IntIntPair |
IntKDTree.SplitChooser.chooseSplit(int[][] pnts,
IntArrayView inds,
int depth,
int[] minBounds,
int[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntIntPair |
IntKDTree.BasicMedianSplit.chooseSplit(int[][] pnts,
IntArrayView inds,
int depth,
int[] minBounds,
int[] maxBounds) |
IntIntPair |
IntKDTree.BBFMedianSplit.chooseSplit(int[][] pnts,
IntArrayView inds,
int depth,
int[] minBounds,
int[] maxBounds) |
IntIntPair |
IntKDTree.ApproximateBBFMedianSplit.chooseSplit(int[][] pnts,
IntArrayView inds,
int depth,
int[] minBounds,
int[] maxBounds) |
IntIntPair |
IntKDTree.RandomisedBBFMeanSplit.chooseSplit(int[][] pnts,
IntArrayView inds,
int depth,
int[] minBounds,
int[] maxBounds) |
IntLongPair |
LongKDTree.SplitChooser.chooseSplit(long[][] pnts,
IntArrayView inds,
int depth,
long[] minBounds,
long[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntLongPair |
LongKDTree.BasicMedianSplit.chooseSplit(long[][] pnts,
IntArrayView inds,
int depth,
long[] minBounds,
long[] maxBounds) |
IntLongPair |
LongKDTree.BBFMedianSplit.chooseSplit(long[][] pnts,
IntArrayView inds,
int depth,
long[] minBounds,
long[] maxBounds) |
IntLongPair |
LongKDTree.ApproximateBBFMedianSplit.chooseSplit(long[][] pnts,
IntArrayView inds,
int depth,
long[] minBounds,
long[] maxBounds) |
IntLongPair |
LongKDTree.RandomisedBBFMeanSplit.chooseSplit(long[][] pnts,
IntArrayView inds,
int depth,
long[] minBounds,
long[] maxBounds) |
IntShortPair |
ShortKDTree.SplitChooser.chooseSplit(short[][] pnts,
IntArrayView inds,
int depth,
short[] minBounds,
short[] maxBounds)
Choose the dimension and discriminant on which to split the data.
|
IntShortPair |
ShortKDTree.BasicMedianSplit.chooseSplit(short[][] pnts,
IntArrayView inds,
int depth,
short[] minBounds,
short[] maxBounds) |
IntShortPair |
ShortKDTree.BBFMedianSplit.chooseSplit(short[][] pnts,
IntArrayView inds,
int depth,
short[] minBounds,
short[] maxBounds) |
IntShortPair |
ShortKDTree.ApproximateBBFMedianSplit.chooseSplit(short[][] pnts,
IntArrayView inds,
int depth,
short[] minBounds,
short[] maxBounds) |
IntShortPair |
ShortKDTree.RandomisedBBFMeanSplit.chooseSplit(short[][] pnts,
IntArrayView inds,
int depth,
short[] minBounds,
short[] maxBounds) |
| Constructor and Description |
|---|
KDTreeNode(byte[][] pnts,
IntArrayView inds,
ByteKDTree.SplitChooser split)
Construct a new node with the given data
|
KDTreeNode(double[][] pnts,
IntArrayView inds,
DoubleKDTree.SplitChooser split)
Construct a new node with the given data
|
KDTreeNode(float[][] pnts,
IntArrayView inds,
FloatKDTree.SplitChooser split)
Construct a new node with the given data
|
KDTreeNode(int[][] pnts,
IntArrayView inds,
IntKDTree.SplitChooser split)
Construct a new node with the given data
|
KDTreeNode(long[][] pnts,
IntArrayView inds,
LongKDTree.SplitChooser split)
Construct a new node with the given data
|
KDTreeNode(short[][] pnts,
IntArrayView inds,
ShortKDTree.SplitChooser split)
Construct a new node with the given data
|