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 | Colt 1.2.0 | ||||||||||
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| 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 | DoubleBufferFixed 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 | AbstractDoubleListAbstract base class for resizable lists holding doubleelements; abstract. | 
|  class | DoubleArrayListResizable list holding doubleelements; implemented with arrays. | 
| Uses of DoubleBufferConsumer in hep.aida.bin | 
| Classes in hep.aida.bin that implement DoubleBufferConsumer | |
|  class | AbstractBin1DAbstract base class for all 1-dimensional bins consumes double elements. | 
|  class | DynamicBin1D1-dimensional rebinnable bin holding double elements; Efficiently computes advanced statistics of data sequences. | 
|  class | MightyStaticBin1DStatic 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 | QuantileBin1D1-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 | StaticBin1D1-dimensional non-rebinnable bin consuming double elements; Efficiently computes basic statistics of data sequences. | 
| 
 | Colt 1.2.0 | ||||||||||
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