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Package Summary
Package
Description
A Java port of CLHEP 1.4.0
(C++) - A Class Library for High Energy Physics; still quite incomplete - should
probably find a way to take cern.clhep out of this distribution and merge cern.clhep
with hep.lcd
(SLAC).
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.
Core interfaces for functions, comparisons and procedures on objects and primitive data types.
Resizable lists holding objects or primitive data types such as int,
double, etc.
List adapters that make Colt lists compatible with the JDK 1.2 Collections Framework.
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.
Matrix benchmarks.
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.
Tools for basic and advanced mathematics: Arithmetics and Algebra, Polynomials and Chebyshev series, Bessel and Airy functions,
Function Objects for generic function evaluation, etc.
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.
Tools for basic and advanced statistics: Estimators, Gamma functions, Beta functions, Probabilities, Special integrals, etc.
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
C-like number formatting that follows printf conventions.
Interfaces for compact, extensible, modular and performant histogramming functionality.
Multisets (bags) with efficient statistics operations defined upon; This package
requires the Colt distribution.
Reference implementation of the AIDA histogram
interfaces.