build/colt/src/hep/aida/bin/package.html (a20104a) - Rabbit simulation · Portfolio Code

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<p>Multisets (bags) with efficient statistics operations defined upon; This package 
  requires the Colt distribution.</p>
<p>Bins contain information about the data filled into them. They can be asked 
  for various descriptive statistical measures, such as the minimum, maximum, 
  size, mean, rms, variance, etc. </p>
<H4>Static vs. Dynamic bins and their space-time-functionality trade-offs</H4>

<p>Bins come in two flavours: <i>Dynamic</i> and <i>Static</i>. Dynamic bins preserve 
  all the values filled into them and can return these exact values, when asked 
  to do so. They are rebinnable. <br>
  Static bins do not preserve the values filled into them. They merely collect 
  basic statistics incrementally while they are being filled. They immediately 
  forget about the filled values and keep only the derived statistics. They are 
  not rebinnable. </p>
<p> The data filled into static bins is not preserved. As a consequence infinitely 
  many elements can be added to such bins. As a further consequence such bins 
  cannot compute more than basic statistics. They are also not rebinnable. If 
  these drawbacks matter, consider to use a {@link hep.aida.bin.DynamicBin1D}, 
  which overcomes them at the expense of increased memory requirements. </p>
<p>
The data filled into dynamic bins is fully preserved.
Technically speaking, they are k-dimensional multisets (or bags) with efficient statistics operations defined upon.
As a consequence such bins can compute more than only basic statistics.
They are also rebinnable.
On the other hand side, if many elements are filled into them, one may quickly run out of memory (each <tt>double</tt> element takes 8 bytes).
If these drawbacks matter, consider to use a {@link hep.aida.bin.StaticBin1D}, 
which overcomes them at the expense of limited functionality.

<H4>Available bin types</H4>

All bins are derived from a common abstract base class {@link hep.aida.bin.AbstractBin}. 
This base class is extended by {@link hep.aida.bin.AbstractBin1D}, the common 
abstract base class for 1-dimensional bins. 
<p> Static 1-dimensional bins currently offered are: {@link hep.aida.bin.StaticBin1D}, 
  {@link hep.aida.bin.MightyStaticBin1D} and {@link hep.aida.bin.QuantileBin1D}. 
  <br>
  Dynamic 1-dimensional bins currently offered are: {@link hep.aida.bin.DynamicBin1D}. 
<h4> Advanced statistics on dynamic bins</h4>
<p>In case not each and every statistics measure needed is directly provided by 
  methods of bins one can use dynamic bins and retrieve their filled elements. 
  From these elements, one can compute whatever necessary, either by using a statistics 
  library or self written functions. Use methods like {@link hep.aida.bin.DynamicBin1D#elements()} 
  and, for example, the descriptive statistics library {@link cern.jet.stat.Descriptive}.</p>
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Rabbit simulation

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