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## Uses of Package
hep.aida.bin

Packages that use hep.aida.bin
cern.colt.matrix.doublealgo | Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
hep.aida.bin | Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

Classes in hep.aida.bin used by cern.colt.matrix.doublealgo
BinFunction1D Interface that represents a function object: a function that takes two bins as arguments and returns a single value.
DynamicBin1D 1-dimensional rebinnable bin holding `double` elements; Efficiently computes advanced statistics of data sequences.

Classes in hep.aida.bin used by hep.aida.bin
AbstractBin Abstract base class for all arbitrary-dimensional bins consumes `double` elements.
AbstractBin1D Abstract base class for all 1-dimensional bins consumes `double` elements.
BinBinFunction1D Interface that represents a function object: a function that takes two bins as arguments and returns a single value.
BinFunction1D Interface that represents a function object: a function that takes two bins as arguments and returns a single value.
BinFunctions1D Function objects computing dynamic bin aggregations; to be passed to generic methods.
DynamicBin1D 1-dimensional rebinnable bin holding `double` elements; Efficiently computes advanced statistics of data sequences.
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.
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.
StaticBin1D 1-dimensional non-rebinnable bin consuming `double` elements; Efficiently computes basic statistics of data sequences.

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