Uses of Package
cern.colt

Packages that use cern.colt
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.
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.
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.