Uses of Interface
cern.colt.buffer.tdouble.DoubleBufferConsumer

Packages that use DoubleBufferConsumer

cern.colt.buffer.tdouble	Fixed sized (non resizable) streaming buffers holding double elements connected to a target objects to which data is automatically flushed upon buffer overflow.
cern.colt.list.tdouble	Resizable list holding elements of double data type.
hep.aida.tdouble.bin	Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

Uses of DoubleBufferConsumer in cern.colt.buffer.tdouble

Classes in cern.colt.buffer.tdouble that implement DoubleBufferConsumer

class

DoubleBuffer Fixed sized (non resizable) streaming buffer connected to a target DoubleBufferConsumer to which data is automatically flushed upon buffer overflow.

Constructors in cern.colt.buffer.tdouble with parameters of type DoubleBufferConsumer

DoubleBuffer(DoubleBufferConsumer target, int capacity)
Constructs and returns a new buffer with the given target.

Uses of DoubleBufferConsumer in cern.colt.list.tdouble

Classes in cern.colt.list.tdouble that implement DoubleBufferConsumer

class	AbstractDoubleList Abstract base class for resizable lists holding double elements; abstract.
class	DoubleArrayList Resizable list holding double elements; implemented with arrays.

Uses of DoubleBufferConsumer in hep.aida.tdouble.bin

Classes in hep.aida.tdouble.bin that implement DoubleBufferConsumer

class	AbstractDoubleBin1D Abstract base class for all 1-dimensional bins consumes double elements.
class	DynamicDoubleBin1D 1-dimensional rebinnable bin holding double elements; Efficiently computes advanced statistics of data sequences.
class	MightyStaticDoubleBin1D 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	QuantileDoubleBin1D 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	StaticDoubleBin1D 1-dimensional non-rebinnable bin consuming double elements; Efficiently computes basic statistics of data sequences.