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.
  • Uses of PersistentObject in cern.colt

    Subclasses of PersistentObject in cern.colt
    Modifier and Type
    Class
    Description
    class 
    A handy stopwatch for benchmarking.
  • Uses of PersistentObject in cern.colt.bitvector

    Modifier and Type
    Class
    Description
    class 
    Fixed sized (non resizable) n*m bit matrix.
    class 
    Fixed sized (non resizable) bitvector.
  • Uses of PersistentObject in cern.colt.buffer

    Modifier and Type
    Class
    Description
    class 
    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

    Modifier and Type
    Class
    Description
    class 
    Abstract base class for resizable lists holding boolean elements; abstract.
    class 
    Abstract base class for resizable lists holding byte elements; abstract.
    class 
    Abstract base class for resizable lists holding char elements; abstract.
    class 
    Abstract base class for resizable collections holding objects or primitive data types such as int, float, etc.
    class 
    Abstract base class for resizable lists holding double elements; abstract.
    class 
    Abstract base class for resizable lists holding float elements; abstract.
    class 
    Abstract base class for resizable lists holding int elements; abstract.
    class 
    Abstract base class for resizable lists holding objects or primitive data types such as int, float, etc.
    class 
    Abstract base class for resizable lists holding long elements; abstract.
    class 
    Abstract base class for resizable lists holding short elements; abstract.
    class 
    Resizable list holding boolean elements; implemented with arrays.
    class 
    Resizable list holding byte elements; implemented with arrays.
    class 
    Resizable list holding char 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 holding double elements; implemented with arrays.
    class 
    Resizable list holding float elements; implemented with arrays.
    class 
    Resizable list holding int elements; implemented with arrays.
    class 
    Resizable list holding long 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 holding Object elements; implemented with arrays.
    class 
    Resizable list holding short elements; implemented with arrays.
    class 
    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

    Modifier and Type
    Class
    Description
    class 
    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 as int, 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

    Modifier and Type
    Class
    Description
    class 
    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

    Modifier and Type
    Class
    Description
    class 
    Flexible, well human readable matrix print formatting; By default decimal point aligned.
    class 
    Matrix quicksorts and mergesorts.
    class 
    Deprecated. 
  • Uses of PersistentObject in cern.colt.matrix.impl

    Modifier and Type
    Class
    Description
    class 
    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 as int, float, etc.
    class 
    Abstract base class for 1-d matrices (aka vectors) holding objects or primitive data types such as int, double, etc.
    class 
    Abstract base class for 2-d matrices holding objects or primitive data types such as int, double, etc.
    class 
    Abstract base class for 3-d matrices holding objects or primitive data types such as int, 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

    Modifier and Type
    Class
    Description
    class 
    Linear algebraic matrix operations operating on DoubleMatrix2D; 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

    Modifier and Type
    Class
    Description
    class 
    Flexible, well human readable matrix print formatting.
    class 
    Matrix quicksorts and mergesorts.
  • Uses of PersistentObject in cern.jet.random

    Modifier and Type
    Class
    Description
    class 
    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 
    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

    Modifier and Type
    Class
    Description
    class 
    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

    Modifier and Type
    Class
    Description
    class 
    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

    Modifier and Type
    Class
    Description
    (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

    Modifier and Type
    Class
    Description
    class 
    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.