Uses of Class
cern.colt.PersistentObject
Packages that use PersistentObject
Package
Description
Core base classes; Operations on primitive arrays such as sorting, partitioning and permuting.
Bit vectors and bit matrices.
Fixed sized (non resizable) streaming buffers connected to a target objects to which data is automatically flushed upon buffer overflow.
Resizable lists holding objects or primitive data types such as int,
double, etc.
Automatically growing and shrinking maps holding objects or primitive
data types such as int, double, etc.
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.
Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
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.Linear Algebraic matrix computations operating on
DoubleMatrix2D
and DoubleMatrix1D
.Object matrix algorithms such as print formatting, sorting, partitioning and statistics.
Large variety of probability distributions featuring high performance generation
of random numbers, CDF's and PDF's.
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.
Samples (picks) random subsets of data sequences.
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
Multisets (bags) with efficient statistics operations defined upon; This package
requires the Colt distribution.
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Uses of PersistentObject in cern.colt
Subclasses of PersistentObject in cern.colt -
Uses of PersistentObject in cern.colt.bitvector
Subclasses of PersistentObject in cern.colt.bitvector -
Uses of PersistentObject in cern.colt.buffer
Subclasses of PersistentObject in cern.colt.bufferModifier and TypeClassDescriptionclass
Fixed sized (non resizable) streaming buffer connected to a target DoubleBufferConsumer to which data is automatically flushed upon buffer overflow.class
Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer2DConsumer to which data is automatically flushed upon buffer overflow.class
Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer3DConsumer to which data is automatically flushed upon buffer overflow.class
Fixed sized (non resizable) streaming buffer connected to a target IntBufferConsumer to which data is automatically flushed upon buffer overflow.class
Fixed sized (non resizable) streaming buffer connected to a target IntBuffer2DConsumer to which data is automatically flushed upon buffer overflow.class
Fixed sized (non resizable) streaming buffer connected to a target IntBuffer3DConsumer to which data is automatically flushed upon buffer overflow.class
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.listModifier and TypeClassDescriptionclass
Abstract base class for resizable lists holdingboolean
elements; abstract.class
Abstract base class for resizable lists holdingbyte
elements; abstract.class
Abstract base class for resizable lists holdingchar
elements; abstract.class
Abstract base class for resizable collections holding objects or primitive data types such asint
,float
, etc.class
Abstract base class for resizable lists holdingdouble
elements; abstract.class
Abstract base class for resizable lists holdingfloat
elements; abstract.class
Abstract base class for resizable lists holdingint
elements; abstract.class
Abstract base class for resizable lists holding objects or primitive data types such asint
,float
, etc.class
Abstract base class for resizable lists holdinglong
elements; abstract.class
Abstract base class for resizable lists holdingshort
elements; abstract.class
Resizable list holdingboolean
elements; implemented with arrays.class
Resizable list holdingbyte
elements; implemented with arrays.class
Resizable list holdingchar
elements; implemented with arrays.class
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
Resizable list holdingdouble
elements; implemented with arrays.class
Resizable list holdingfloat
elements; implemented with arrays.class
Resizable list holdingint
elements; implemented with arrays.class
Resizable list holdinglong
elements; implemented with arrays.class
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
Resizable list holdingObject
elements; implemented with arrays.class
Resizable list holdingshort
elements; implemented with arrays.class
Resizable list holdinglong
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.mapModifier and TypeClassDescriptionclass
Abstract base class for hash maps holding (key,value) associations of type (double-->int).class
Abstract base class for hash maps holding (key,value) associations of type (int-->double).class
Abstract base class for hash maps holding (key,value) associations of type (int-->int).class
Abstract base class for hash maps holding (key,value) associations of type (int-->Object).class
Abstract base class for hash maps holding (key,value) associations of type (long-->Object).class
Abstract base class for hash maps holding objects or primitive data types such asint
,float
, etc.class
Hash map holding (key,value) associations of type (double-->int); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.class
Hash map holding (key,value) associations of type (int-->double); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.class
Hash map holding (key,value) associations of type (int-->int); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.class
Hash map holding (key,value) associations of type (int-->Object); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.class
Hash map holding (key,value) associations of type (long-->Object); Automatically grows and shrinks as needed; Implemented using open addressing with double hashing.(package private) class
Status: Experimental; Do not use for production yet. -
Uses of PersistentObject in cern.colt.matrix
Subclasses of PersistentObject in cern.colt.matrixModifier and TypeClassDescriptionclass
Factory for convenient construction of 1-d matrices holding double cells.class
Factory for convenient construction of 2-d matrices holding double cells.class
Factory for convenient construction of 3-d matrices holding double cells.class
Abstract base class for 1-d matrices (aka vectors) holding double elements.class
Abstract base class for 2-d matrices holding double elements.class
Abstract base class for 3-d matrices holding double elements.class
Factory for convenient construction of 1-d matrices holding Object cells.class
Factory for convenient construction of 2-d matrices holding Object cells.class
Factory for convenient construction of 3-d matrices holding Object cells.class
Abstract base class for 1-d matrices (aka vectors) holding Object elements.class
Abstract base class for 2-d matrices holding Object elements.class
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 -
Uses of PersistentObject in cern.colt.matrix.impl
Subclasses of PersistentObject in cern.colt.matrix.implModifier and TypeClassDescriptionclass
Abstract base class for flexible, well human readable matrix print formatting.class
Abstract base class for arbitrary-dimensional matrices holding objects or primitive data types such asint
,float
, etc.class
Abstract base class for 1-d matrices (aka vectors) holding objects or primitive data types such asint
,double
, etc.class
Abstract base class for 2-d matrices holding objects or primitive data types such asint
,double
, etc.class
Abstract base class for 3-d matrices holding objects or primitive data types such asint
,double
, etc.(package private) class
1-d matrix holding double elements; either a view wrapping another 2-d matrix and therefore delegating calls to it.class
Dense 1-d matrix (aka vector) holding double elements.class
Dense 2-d matrix holding double elements.class
Dense 3-d matrix holding double elements.class
Dense 1-d matrix (aka vector) holding Object elements.class
Dense 2-d matrix holding Object elements.class
Dense 3-d matrix holding Object elements.class
Sparse row-compressed 2-d matrix holding double elements.(package private) class
Sparse row-compressed-modified 2-d matrix holding double elements.(package private) class
Selection view on dense 1-d matrices holding double elements.(package private) class
Selection view on dense 2-d matrices holding double elements.(package private) class
Selection view on dense 3-d matrices holding double elements.(package private) class
Selection view on dense 1-d matrices holding Object elements.(package private) class
Selection view on dense 2-d matrices holding Object elements.(package private) class
Selection view on dense 3-d matrices holding Object elements.(package private) class
Selection view on sparse 1-d matrices holding double elements.(package private) class
Selection view on sparse 2-d matrices holding double elements.(package private) class
Selection view on sparse 3-d matrices holding double elements.(package private) class
Selection view on sparse 1-d matrices holding Object elements.(package private) class
Selection view on sparse 2-d matrices holding Object elements.(package private) class
Selection view on sparse 3-d matrices holding Object elements.class
Sparse hashed 1-d matrix (aka vector) holding double elements.class
Sparse hashed 2-d matrix holding double elements.class
Sparse hashed 3-d matrix holding double elements.class
Sparse hashed 1-d matrix (aka vector) holding Object elements.class
Sparse hashed 2-d matrix holding Object elements.class
Sparse hashed 3-d matrix holding Object elements.(package private) class
Tridiagonal 2-d matrix holding double elements.(package private) class
1-d matrix holding double elements; either a view wrapping another matrix or a matrix whose views are wrappers.(package private) class
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.linalgModifier and TypeClassDescriptionclass
Linear algebraic matrix operations operating onDoubleMatrix2D
; concentrates most functionality of this package.class
Tests matrices for linear algebraic properties (equality, tridiagonality, symmetry, singularity, etc). -
Uses of PersistentObject in cern.colt.matrix.objectalgo
Subclasses of PersistentObject in cern.colt.matrix.objectalgo -
Uses of PersistentObject in cern.jet.random
Subclasses of PersistentObject in cern.jet.randomModifier and TypeClassDescriptionclass
Abstract base class for all continous distributions.class
Abstract base class for all discrete distributions.class
Abstract base class for all random distributions.class
Benchmarks random number generation from various distributions as well as PDF and CDF lookups.class
Beta distribution; math definition and animated definition.class
Binomial distribution; See the math definition and animated definition.class
BreitWigner (aka Lorentz) distribution; See the math definition.class
Mean-square BreitWigner distribution; See the math definition.class
ChiSquare distribution; See the math definition and animated definition.class
Empirical distribution.class
Discrete Empirical distribution (pdf's can be specified).class
Exponential Distribution (aka Negative Exponential Distribution); See the math definition animated definition.class
Exponential Power distribution.class
class
Hyperbolic distribution.class
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 distribution.class
Negative Binomial distribution; See the math definition.class
Normal (aka Gaussian) distribution; See the math definition and animated definition.class
Poisson distribution (quick); See the math definition and animated definition.class
Poisson distribution; See the math definition and animated definition.class
StudentT distribution (aka T-distribution); See the math definition and animated definition.class
Uniform distribution; Math definition and animated definition.class
Von Mises distribution.class
Zeta distribution. -
Uses of PersistentObject in cern.jet.random.engine
Subclasses of PersistentObject in cern.jet.random.engineModifier and TypeClassDescriptionclass
Quick medium quality uniform pseudo-random number generator.class
MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.class
Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers.class
Abstract base class for uniform pseudo-random number generating engines.class
Deterministic seed generator for pseudo-random number generators. -
Uses of PersistentObject in cern.jet.random.sampling
Subclasses of PersistentObject in cern.jet.random.samplingModifier and TypeClassDescriptionclass
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
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
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.quantileModifier and TypeClassDescription(package private) class
A buffer holding elements; internally used for computing approximate quantiles.(package private) class
An abstract set of buffers; internally used for computing approximate quantiles.(package private) class
A buffer holding double elements; internally used for computing approximate quantiles.(package private) class
A set of buffers holding double elements; internally used for computing approximate quantiles.(package private) class
The abstract base class for approximate quantile finders computing quantiles over a sequence of double elements.class
Read-only equi-depth histogram for selectivity estimation.(package private) class
Exact quantile finding algorithm for known and unknown N requiring large main memory; computes quantiles over a sequence of double elements.(package private) class
Approximate quantile finding algorithm for known N requiring only one pass and little main memory; computes quantiles over a sequence of double elements.(package private) class
Approximate quantile finding algorithm for unknown N requiring only one pass and little main memory; computes quantiles over a sequence of double elements. -
Uses of PersistentObject in hep.aida.bin
Subclasses of PersistentObject in hep.aida.binModifier and TypeClassDescriptionclass
Abstract base class for all arbitrary-dimensional bins consumes double elements.class
Abstract base class for all 1-dimensional bins consumes double elements.class
1-dimensional rebinnable bin holding double elements; Efficiently computes advanced statistics of data sequences.class
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
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
1-dimensional non-rebinnable bin consuming double elements; Efficiently computes basic statistics of data sequences.