Colt 1.2.0

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

Packages that use DoubleBufferConsumer
cern.colt.buffer: Fixed sized (non resizable) streaming buffers connected to a target objects to which data is automatically flushed upon buffer overflow.
cern.colt.list: Resizable lists holding objects or primitive data types such as `int`, `double`, etc.
hep.aida.bin: Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

Uses of DoubleBufferConsumer in cern.colt.buffer

Classes in cern.colt.buffer 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 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

Classes in cern.colt.list 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.bin

Classes in hep.aida.bin that implement DoubleBufferConsumer
`class` `AbstractBin1D` Abstract base class for all 1-dimensional bins consumes `double` elements.
`class` `DynamicBin1D` 1-dimensional rebinnable bin holding `double` elements; Efficiently computes advanced statistics of data sequences.
`class` `MightyStaticBin1D` 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`

`QuantileBin1D`
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` `StaticBin1D` 1-dimensional non-rebinnable bin consuming `double` elements; Efficiently computes basic statistics of data sequences.

Colt 1.2.0

Jump to the Colt Homepage