Uses of Class
cern.colt.PersistentObject

Packages that use PersistentObject

cern.colt	Core base classes; Operations on primitive arrays such as sorting, partitioning and permuting.
cern.colt.bitvector	Bit vectors and bit matrices.
cern.colt.buffer	Fixed sized (non resizable) streaming buffers connected to a target objects to which data is automatically flushed upon buffer overflow.
cern.colt.list	Resizable lists holding objects or primitive data types such as int, double, etc.
cern.colt.map	Automatically growing and shrinking maps holding objects or primitive data types such as int, double, etc.
cern.colt.matrix	Matrix interfaces and factories; efficient and flexible dense and sparse 1, 2, 3 and d-dimensional matrices holding objects or primitive data types such as int, double, etc; Templated, fixed sized (not dynamically resizable); Also known as multi-dimensional arrays or Data Cubes.
cern.colt.matrix.doublealgo	Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
cern.colt.matrix.impl	Matrix implementations; You normally need not look at this package, because all concrete classes implement the abstract interfaces of cern.colt.matrix, without subsetting or supersetting.
cern.colt.matrix.linalg	Linear Algebraic matrix computations operating on DoubleMatrix2D and DoubleMatrix1D.
cern.jet.random	Large variety of probability distributions featuring high performance generation of random numbers, CDF's and PDF's.
cern.jet.random.engine	Engines generating strong uniformly distributed pseudo-random numbers; Needed by all JET probability distributions since they rely on uniform random numbers to generate random numbers from their own distribution.
cern.jet.random.sampling	Samples (picks) random subsets of data sequences.
cern.jet.stat.quantile	Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
hep.aida.bin	Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

Uses of PersistentObject in cern.colt

Subclasses of PersistentObject in cern.colt

class

Timer A handy stopwatch for benchmarking.

Uses of PersistentObject in cern.colt.bitvector

Subclasses of PersistentObject in cern.colt.bitvector

class	BitMatrix Fixed sized (non resizable) n*m bit matrix.
class	BitVector Fixed sized (non resizable) bitvector.

Uses of PersistentObject in cern.colt.buffer

Subclasses of PersistentObject in cern.colt.buffer

class	DoubleBuffer Fixed sized (non resizable) streaming buffer connected to a target DoubleBufferConsumer to which data is automatically flushed upon buffer overflow.
class	DoubleBuffer2D Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer2DConsumer to which data is automatically flushed upon buffer overflow.
class	DoubleBuffer3D Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer3DConsumer to which data is automatically flushed upon buffer overflow.
class	IntBuffer Fixed sized (non resizable) streaming buffer connected to a target IntBufferConsumer to which data is automatically flushed upon buffer overflow.
class	IntBuffer2D Fixed sized (non resizable) streaming buffer connected to a target IntBuffer2DConsumer to which data is automatically flushed upon buffer overflow.
class	IntBuffer3D Fixed sized (non resizable) streaming buffer connected to a target IntBuffer3DConsumer to which data is automatically flushed upon buffer overflow.
class	ObjectBuffer Fixed sized (non resizable) streaming buffer connected to a target ObjectBufferConsumer to which data is automatically flushed upon buffer overflow.

Uses of PersistentObject in cern.colt.list

Subclasses of PersistentObject in cern.colt.list

class	AbstractBooleanList Abstract base class for resizable lists holding boolean elements; abstract.
class	AbstractByteList Abstract base class for resizable lists holding byte elements; abstract.
class	AbstractCharList Abstract base class for resizable lists holding char elements; abstract.
class	AbstractCollection Abstract base class for resizable collections holding objects or primitive data types such as int, float, etc.
class	AbstractDoubleList Abstract base class for resizable lists holding double elements; abstract.
class	AbstractFloatList Abstract base class for resizable lists holding float elements; abstract.
class	AbstractIntList Abstract base class for resizable lists holding int elements; abstract.
class	AbstractList Abstract base class for resizable lists holding objects or primitive data types such as int, float, etc.
class	AbstractLongList Abstract base class for resizable lists holding long elements; abstract.
class	AbstractShortList Abstract base class for resizable lists holding short elements; abstract.
class	BooleanArrayList Resizable list holding boolean elements; implemented with arrays.
class	ByteArrayList Resizable list holding byte elements; implemented with arrays.
class	CharArrayList Resizable list holding char elements; implemented with arrays.
class	DistinctNumberList Resizable compressed list holding numbers; based on the fact that a number from a large list with few distinct values need not take more than log(distinctValues) bits; implemented with a MinMaxNumberList.
class	DoubleArrayList Resizable list holding double elements; implemented with arrays.
class	FloatArrayList Resizable list holding float elements; implemented with arrays.
class	IntArrayList Resizable list holding int elements; implemented with arrays.
class	LongArrayList Resizable list holding long elements; implemented with arrays.
class	MinMaxNumberList Resizable compressed list holding numbers; based on the fact that a value in a given interval need not take more than log(max-min+1) bits; implemented with a cern.colt.bitvector.BitVector.
class	ObjectArrayList Resizable list holding Object elements; implemented with arrays.
class	ShortArrayList Resizable list holding short elements; implemented with arrays.
class	SimpleLongArrayList Resizable list holding long elements; implemented with arrays; not efficient; just to demonstrate which methods you must override to implement a fully functional list.

Uses of PersistentObject in cern.colt.map

Subclasses of PersistentObject in cern.colt.map

class	AbstractDoubleIntMap Abstract base class for hash maps holding (key,value) associations of type (double-->int).
class	AbstractIntDoubleMap Abstract base class for hash maps holding (key,value) associations of type (int-->double).
class	AbstractIntIntMap Abstract base class for hash maps holding (key,value) associations of type (int-->int).
class	AbstractIntObjectMap Abstract base class for hash maps holding (key,value) associations of type (int-->Object).
class	AbstractLongObjectMap Abstract base class for hash maps holding (key,value) associations of type (long-->Object).
class	AbstractMap Abstract base class for hash maps holding objects or primitive data types such as int, float, etc.
class	OpenDoubleIntHashMap Hash map holding (key,value) associations of type (double-->int); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.
class	OpenIntDoubleHashMap Hash map holding (key,value) associations of type (int-->double); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.
class	OpenIntIntHashMap Hash map holding (key,value) associations of type (int-->int); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.
class	OpenIntObjectHashMap Hash map holding (key,value) associations of type (int-->Object); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.
class	OpenLongObjectHashMap Hash map holding (key,value) associations of type (long-->Object); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.

Uses of PersistentObject in cern.colt.matrix

Subclasses of PersistentObject in cern.colt.matrix

class	DoubleFactory1D Factory for convenient construction of 1-d matrices holding double cells.
class	DoubleFactory2D Factory for convenient construction of 2-d matrices holding double cells.
class	DoubleFactory3D Factory for convenient construction of 3-d matrices holding double cells.
class	DoubleMatrix1D Abstract base class for 1-d matrices (aka vectors) holding double elements.
class	DoubleMatrix2D Abstract base class for 2-d matrices holding double elements.
class	DoubleMatrix3D Abstract base class for 3-d matrices holding double elements.
class	ObjectFactory1D Factory for convenient construction of 1-d matrices holding Object cells.
class	ObjectFactory2D Factory for convenient construction of 2-d matrices holding Object cells.
class	ObjectFactory3D Factory for convenient construction of 3-d matrices holding Object cells.
class	ObjectMatrix1D Abstract base class for 1-d matrices (aka vectors) holding Object elements.
class	ObjectMatrix2D Abstract base class for 2-d matrices holding Object elements.
class	ObjectMatrix3D Abstract base class for 3-d matrices holding Object elements.

Uses of PersistentObject in cern.colt.matrix.doublealgo

Subclasses of PersistentObject in cern.colt.matrix.doublealgo

class	Formatter Flexible, well human readable matrix print formatting; By default decimal point aligned.
class	Sorting Matrix quicksorts and mergesorts.
class	Transform Deprecated.

Uses of PersistentObject in cern.colt.matrix.impl

Subclasses of PersistentObject in cern.colt.matrix.impl

class	AbstractFormatter Abstract base class for flexible, well human readable matrix print formatting.
class	AbstractMatrix Abstract base class for arbitrary-dimensional matrices holding objects or primitive data types such as int, float, etc.
class	AbstractMatrix1D Abstract base class for 1-d matrices (aka vectors) holding objects or primitive data types such as int, double, etc.
class	AbstractMatrix2D Abstract base class for 2-d matrices holding objects or primitive data types such as int, double, etc.
class	AbstractMatrix3D Abstract base class for 3-d matrices holding objects or primitive data types such as int, double, etc.
class	DenseDoubleMatrix1D Dense 1-d matrix (aka vector) holding double elements.
class	DenseDoubleMatrix2D Dense 2-d matrix holding double elements.
class	DenseDoubleMatrix3D Dense 3-d matrix holding double elements.
class	DenseObjectMatrix1D Dense 1-d matrix (aka vector) holding Object elements.
class	DenseObjectMatrix2D Dense 2-d matrix holding Object elements.
class	DenseObjectMatrix3D Dense 3-d matrix holding Object elements.
class	RCDoubleMatrix2D Sparse row-compressed 2-d matrix holding double elements.
class	SparseDoubleMatrix1D Sparse hashed 1-d matrix (aka vector) holding double elements.
class	SparseDoubleMatrix2D Sparse hashed 2-d matrix holding double elements.
class	SparseDoubleMatrix3D Sparse hashed 3-d matrix holding double elements.
class	SparseObjectMatrix1D Sparse hashed 1-d matrix (aka vector) holding Object elements.
class	SparseObjectMatrix2D Sparse hashed 2-d matrix holding Object elements.
class	SparseObjectMatrix3D Sparse hashed 3-d matrix holding Object elements.
(package private) class	cern.colt.matrix.impl.WrapperDoubleMatrix2D 2-d matrix holding double elements; either a view wrapping another matrix or a matrix whose views are wrappers.

Uses of PersistentObject in cern.colt.matrix.linalg

Subclasses of PersistentObject in cern.colt.matrix.linalg

class	Algebra Linear algebraic matrix operations operating on DoubleMatrix2D; concentrates most functionality of this package.
class	Property Tests matrices for linear algebraic properties (equality, tridiagonality, symmetry, singularity, etc).

Uses of PersistentObject in cern.jet.random

Subclasses of PersistentObject in cern.jet.random

class	AbstractContinousDistribution Abstract base class for all continous distributions.
class	AbstractDiscreteDistribution Abstract base class for all discrete distributions.
class	AbstractDistribution Abstract base class for all random distributions.
class	Benchmark Benchmarks random number generation from various distributions as well as PDF and CDF lookups.
class	Beta Beta distribution; math definition and animated definition.
class	Binomial Binomial distribution; See the math definition and animated definition.
class	BreitWigner BreitWigner (aka Lorentz) distribution; See the math definition.
class	BreitWignerMeanSquare Mean-square BreitWigner distribution; See the math definition.
class	ChiSquare ChiSquare distribution; See the math definition and animated definition.
class	Empirical Empirical distribution.
class	EmpiricalWalker Discrete Empirical distribution (pdf's can be specified).
class	Exponential Exponential Distribution (aka Negative Exponential Distribution); See the math definition animated definition.
class	ExponentialPower Exponential Power distribution.
class	Gamma Gamma distribution; math definition, definition of gamma function and animated definition.
class	Hyperbolic Hyperbolic distribution.
class	HyperGeometric HyperGeometric distribution; See the math definition The hypergeometric distribution with parameters N, n and s is the probability distribution of the random variable X, whose value is the number of successes in a sample of n items from a population of size N that has s 'success' items and N - s 'failure' items.
class	Logarithmic Logarithmic distribution.
class	NegativeBinomial Negative Binomial distribution; See the math definition.
class	Normal Normal (aka Gaussian) distribution; See the math definition and animated definition.
class	Poisson Poisson distribution (quick); See the math definition and animated definition.
class	PoissonSlow Poisson distribution; See the math definition and animated definition.
class	StudentT StudentT distribution (aka T-distribution); See the math definition and animated definition.
class	Uniform Uniform distribution; Math definition and animated definition.
class	VonMises Von Mises distribution.
class	Zeta Zeta distribution.

Uses of PersistentObject in cern.jet.random.engine

Subclasses of PersistentObject in cern.jet.random.engine

class	DRand Quick medium quality uniform pseudo-random number generator.
class	MersenneTwister MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.
class	MersenneTwister64 Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers.
class	RandomEngine Abstract base class for uniform pseudo-random number generating engines.
class	RandomSeedGenerator Deterministic seed generator for pseudo-random number generators.

Uses of PersistentObject in cern.jet.random.sampling

Subclasses of PersistentObject in cern.jet.random.sampling

class	RandomSampler Space and time efficiently computes a sorted Simple Random Sample Without Replacement (SRSWOR), that is, a sorted set of n random numbers from an interval of N numbers; Example: Computing n=3 random numbers from the interval [1,50] may yield the sorted random set (7,13,47).
class	RandomSamplingAssistant Conveniently computes a stable Simple Random Sample Without Replacement (SRSWOR) subsequence of n elements from a given input sequence of N elements; Example: Computing a sublist of n=3 random elements from a list (1,...,50) may yield the sublist (7,13,47).
class	WeightedRandomSampler Conveniently computes a stable subsequence of elements from a given input sequence; Picks (samples) exactly one random element from successive blocks of weight input elements each.

Uses of PersistentObject in cern.jet.stat.quantile

Subclasses of PersistentObject in cern.jet.stat.quantile

class

EquiDepthHistogram Read-only equi-depth histogram for selectivity estimation.

Uses of PersistentObject in hep.aida.bin

Subclasses of PersistentObject in hep.aida.bin

class	AbstractBin Abstract base class for all arbitrary-dimensional bins consumes double elements.
class	AbstractBin1D Abstract base class for all 1-dimensional bins consumes double elements.
class	DynamicBin1D 1-dimensional rebinnable bin holding double elements; Efficiently computes advanced statistics of data sequences.
class	MightyStaticBin1D Static and the same as its superclass, except that it can do more: Additionally computes moments of arbitrary integer order, harmonic mean, geometric mean, etc.
class	QuantileBin1D 1-dimensional non-rebinnable bin holding double elements with scalable quantile operations defined upon; Using little main memory, quickly computes approximate quantiles over very large data sequences with and even without a-priori knowledge of the number of elements to be filled; Conceptually a strongly lossily compressed multiset (or bag); Guarantees to respect the worst case approximation error specified upon instance construction.
class	StaticBin1D 1-dimensional non-rebinnable bin consuming double elements; Efficiently computes basic statistics of data sequences.