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Parallel Colt 0.9.4 | |||||||||
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Packages that use DoubleBufferConsumer | |
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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 |
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Classes in cern.colt.buffer.tdouble that implement DoubleBufferConsumer | |
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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 | |
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DoubleBuffer(DoubleBufferConsumer target,
int capacity)
Constructs and returns a new buffer with the given target. |
Uses of DoubleBufferConsumer in cern.colt.list.tdouble |
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Classes in cern.colt.list.tdouble that implement DoubleBufferConsumer | |
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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 |
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Classes in hep.aida.tdouble.bin that implement DoubleBufferConsumer | |
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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. |
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