Package | Description |
---|---|
org.shared.array |
A package of multidimensional arrays.
|
org.shared.array.kernel |
A package for basic operations on
Array s. |
org.shared.array.sparse |
A package of multidimensional sparse arrays.
|
org.shared.fft |
A package for FFTs.
|
org.shared.image |
A package for representing images and image statistics as matrices and arrays.
|
org.shared.image.filter |
A package of two-dimensional filters.
|
org.shared.stat.ml |
A package of machine learning algorithms.
|
org.shared.stat.plot |
A package of plotting classes for reporting machine learning metrics.
|
org.shared.test.stat |
A suite of tests for statistical tools.
|
Modifier and Type | Method and Description |
---|---|
static RealArray |
RealArray.eye(int size,
int nDims)
Creates an array of the given size and number of dimensions, with ones for diagonals.
|
RealArray |
RealArray.mDiag() |
RealArray[] |
RealArray.mEigs() |
RealArray |
RealArray.mInvert() |
RealArray |
RealArray.mMul(RealArray b) |
RealArray[] |
RealArray.mSvd() |
RealArray |
RealArray.mTranspose() |
static RealArray |
RealArray.parse(byte[] data)
Parses an array from
byte s. |
RealArray |
IntegerArray.tor()
Converts this array to a
RealArray . |
protected RealArray |
RealArray.wrap(int parity,
Array.IndexingOrder order,
int[] dims,
int[] strides) |
protected RealArray |
ComplexArray.wrapDown(int parity,
Array.IndexingOrder order,
int[] dims,
int[] strides) |
Modifier and Type | Method and Description |
---|---|
RealArray |
RealArray.mMul(RealArray b) |
Constructor and Description |
---|
RealArray(RealArray array)
Alternate constructor.
|
Modifier and Type | Method and Description |
---|---|
static byte[] |
MatlabIoKernel.getBytes(RealArray array,
String name)
Converts the given
RealArray into byte s. |
Modifier and Type | Method and Description |
---|---|
RealArray |
RealSparseArray.toDense() |
Modifier and Type | Method and Description |
---|---|
RealArray |
ConvolutionCache.convolve(ComplexArray cIm,
RealArray ker)
Performs convolution in the real domain.
|
static RealArray |
ConvolutionCache.pad(RealArray im,
int... margins)
Pads an image in an extrapolative way.
|
Modifier and Type | Method and Description |
---|---|
RealArray |
ConvolutionCache.convolve(ComplexArray cIm,
RealArray ker)
Performs convolution in the real domain.
|
static RealArray |
ConvolutionCache.pad(RealArray im,
int... margins)
Pads an image in an extrapolative way.
|
Modifier and Type | Class and Description |
---|---|
class |
IntegralHistogram
A data structure for computing the histogram over any rectangular region quickly.
|
class |
IntegralImage
A data structure for computing the sum over any rectangular region quickly.
|
Modifier and Type | Method and Description |
---|---|
static RealArray |
IntensityImages.createMatrix(BufferedImage image)
Converts a
BufferedImage to a RealArray . |
static RealArray |
IntensityImages.createMatrix(byte[] data)
Creates a
RealArray from a byte array. |
static RealArray |
IntensityImages.createMatrix(File file)
Creates a
RealArray from an image file. |
Modifier and Type | Method and Description |
---|---|
static BufferedImage |
IntensityImages.createImage(RealArray m,
String cmName,
double rangeMin,
double rangeMax)
Converts a
RealArray to a BufferedImage . |
protected static int[] |
IntegralImage.getDimensionsPlusOne(RealArray arr)
Gets the original dimensions plus one.
|
protected static int[] |
IntegralHistogram.getDimensionsPlusOne(RealArray arr,
int nBins)
Gets the original dimensions plus one with an additional "bins" dimension at the end.
|
Constructor and Description |
---|
IntegralHistogram(RealArray src,
IntegerArray membership,
int nBins)
Default constructor.
|
IntegralImage(RealArray src)
Default constructor.
|
Modifier and Type | Class and Description |
---|---|
class |
DerivativeOfGaussian
An implementation of DooG filters up to
0 th and 1 st derivatives. |
class |
LaplacianOfGaussian
An implementation of LoG filters.
|
class |
Mean
A mean low-pass filter.
|
Modifier and Type | Method and Description |
---|---|
static RealArray[] |
Filters.createGradientKernels(int supportRadius)
Creates a pair of
x - and y -axis aligned DooG kernels for gradient calculations. |
static RealArray |
Filters.createPointSupport(int supportRadius)
Creates a point support matrix.
|
static RealArray |
Filters.createRotationMatrix(double theta)
Creates the
rotation matrix
-cos(θ) -sin(θ)
-sin(θ) cos(θ) . |
protected static RealArray |
DerivativeOfGaussian.derivative(double sigma,
RealArray support,
int order)
Calculates a Gaussian derivative to the specified order.
|
Modifier and Type | Method and Description |
---|---|
protected static RealArray |
DerivativeOfGaussian.derivative(double sigma,
RealArray support,
int order)
Calculates a Gaussian derivative to the specified order.
|
Modifier and Type | Field and Description |
---|---|
RealArray |
GmComponents.centers
The centers.
|
RealArray |
GmComponents.covariances
The (diagonal) covariances.
|
RealArray |
GmComponents.weights
The weights.
|
Modifier and Type | Method and Description |
---|---|
RealArray |
GmModel.computeLogWeightedDensities(GmComponents gmc,
RealArray points) |
protected abstract RealArray |
AbstractGmModel.computeLogWeightedDensities(GmComponents gmc,
RealArray points)
Computes the log of the weighted densities.
|
RealArray |
AbstractGmModel.computePosterior(GmComponents gmc,
RealArray points)
Computes the posterior distribution and updates the mean likelihood of the points.
|
static RealArray |
KMeans.distances(RealArray aPts,
RealArray bPts)
Computes point-to-point distances.
|
protected static RealArray |
KMeans.subsetFurthestFirst(int nCenters,
RealArray points)
Performs subset furthest first initialization.
|
Modifier and Type | Method and Description |
---|---|
static List<RealArray> |
KMeans.cluster(int nClusters,
RealArray points)
Groups a set of points into the given number of clusters.
|
Modifier and Type | Method and Description |
---|---|
static List<RealArray> |
KMeans.cluster(int nClusters,
RealArray points)
Groups a set of points into the given number of clusters.
|
RealArray |
GmModel.computeLogWeightedDensities(GmComponents gmc,
RealArray points) |
protected abstract RealArray |
AbstractGmModel.computeLogWeightedDensities(GmComponents gmc,
RealArray points)
Computes the log of the weighted densities.
|
RealArray |
AbstractGmModel.computePosterior(GmComponents gmc,
RealArray points)
Computes the posterior distribution and updates the mean likelihood of the points.
|
static RealArray |
KMeans.distances(RealArray aPts,
RealArray bPts)
Computes point-to-point distances.
|
GmComponents |
GmModel.initialize(RealArray input,
int nComps,
double regularization) |
protected abstract GmComponents |
AbstractGmModel.initialize(RealArray points,
int nComps,
double regularization)
Initializes the mixture components.
|
protected static RealArray |
KMeans.subsetFurthestFirst(int nCenters,
RealArray points)
Performs subset furthest first initialization.
|
GmComponents |
AbstractGmModel.train(RealArray points,
int nComps,
double regularization,
double delta)
Trains the model.
|
void |
GmModel.update(GmComponents gmc,
RealArray posterior,
RealArray points,
double regularization) |
protected abstract void |
AbstractGmModel.update(GmComponents gmc,
RealArray posterior,
RealArray points,
double regularization)
Performs the update rule.
|
Modifier and Type | Field and Description |
---|---|
protected RealArray[] |
ErrorDistribution.datasets
The datasets.
|
protected RealArray[] |
Histogram.datasets
The datasets.
|
Modifier and Type | Method and Description |
---|---|
RealArray[] |
Scatter.getDatasets() |
RealArray[] |
ErrorDistribution.getDatasets() |
RealArray[] |
Plottable.getDatasets()
Gets the datasets.
|
RealArray[] |
Histogram.getDatasets() |
Modifier and Type | Method and Description |
---|---|
GnuplotContext.Gnuplot |
GnuplotContext.addPlot(RealArray... datasets) |
P |
PlotContext.addPlot(RealArray... datasets)
Creates a
Plot at the given coordinates. |
static int |
PlotBase.inferDimensionality(RealArray... datasets)
Infers the dimensionality of the given datasets.
|
protected void |
Roc.initDataset(RealArray dataset,
boolean[] outcomes) |
protected abstract void |
ErrorDistribution.initDataset(RealArray dataset,
boolean[] outcomes)
Initializes the given dataset.
|
protected void |
PrecisionRecall.initDataset(RealArray dataset,
boolean[] outcomes) |
protected abstract void |
ProbabilityDistribution.Mode.initDistribution(RealArray distribution)
Initializes the probability distribution.
|
Constructor and Description |
---|
GnuplotContext.Gnuplot(RealArray[] datasets)
Default constructor.
|
Scatter(RealArray... datasets)
Default constructor.
|
Modifier and Type | Method and Description |
---|---|
protected static RealArray |
GmModelTest.generatePoints(RealArray input,
int nPoints)
Draws random samples from a mixture of Gaussians.
|
Modifier and Type | Method and Description |
---|---|
protected static RealArray |
GmModelTest.generatePoints(RealArray input,
int nPoints)
Draws random samples from a mixture of Gaussians.
|