hep.aida.bin
Class AbstractBin1D

java.lang.Object
  cern.colt.PersistentObject
      hep.aida.bin.AbstractBin
          hep.aida.bin.AbstractBin1D

All Implemented Interfaces:

Cloneable, DoubleBufferConsumer, Serializable

Direct Known Subclasses:

StaticBin1D

public abstract class AbstractBin1D

extends AbstractBin

implements DoubleBufferConsumer

Abstract base class for all 1-dimensional bins consumes double elements. First see the package summary and javadoc tree view to get the broad picture.

This class is fully thread safe (all public methods are synchronized). Thus, you can have one or more threads adding to the bin as well as one or more threads reading and viewing the statistics of the bin while it is filled. For high performance, add data in large chunks (buffers) via method addAllOf rather than piecewise via method add.

Version:

0.9, 03-Jul-99

See Also:

Serialized Form

add

public abstract void add(double element)

Adds the specified element to the receiver.

Parameters:

element - element to be appended.

addAllOf

public final void addAllOf(DoubleArrayList list)

Adds all values of the specified list to the receiver.

Specified by:

addAllOf in interface DoubleBufferConsumer

Parameters:

list - the list of which all values shall be added.

addAllOfFromTo

public void addAllOfFromTo(DoubleArrayList list,
                           int from,
                           int to)

Adds the part of the specified list between indexes from (inclusive) and to (inclusive) to the receiver. You may want to override this method for performance reasons.

Parameters:

list - the list of which elements shall be added.

from - the index of the first element to be added (inclusive).

to - the index of the last element to be added (inclusive).

Throws:

IndexOutOfBoundsException - if list.size()>0 && (from<0 || from>to || to>=list.size()).

buffered

public DoubleBuffer buffered(int capacity)

Constructs and returns a streaming buffer connected to the receiver. Whenever the buffer is full it's contents are automatically flushed to this. (Addding elements via a buffer to a bin is significantly faster than adding them directly.)

Parameters:

capacity - the number of elements the buffer shall be capable of holding before overflowing and flushing to the receiver.

Returns:

a streaming buffer having the receiver as target.

compareWith

public String compareWith(AbstractBin1D other)

Computes the deviations from the receiver's measures to another bin's measures.

Parameters:

other - the other bin to compare with

Returns:

a summary of the deviations.

equals

public boolean equals(Object object)

Returns whether two bins are equal; They are equal if the other object is of the same class or a subclass of this class and both have the same size, minimum, maximum, sum and sumOfSquares.

Overrides:

equals in class AbstractBin

max

public abstract double max()

Returns the maximum.

mean

public double mean()

Returns the arithmetic mean, which is Sum( x[i] ) / size().

min

public abstract double min()

Returns the minimum.

rms

public double rms()

Returns the rms (Root Mean Square), which is Math.sqrt( Sum( x[i]*x[i] ) / size() ).

standardDeviation

public double standardDeviation()

Returns the sample standard deviation, which is Math.sqrt(variance()).

standardError

public double standardError()

Returns the sample standard error, which is Math.sqrt(variance() / size())

sum

public abstract double sum()

Returns the sum of all elements, which is Sum( x[i] ).

sumOfSquares

public abstract double sumOfSquares()

Returns the sum of squares, which is Sum( x[i] * x[i] ).

toString

public String toString()

Returns a String representation of the receiver.

Overrides:

toString in class AbstractBin

trimToSize

public void trimToSize()

Trims the capacity of the receiver to be the receiver's current size. Releases any superfluos internal memory. An application can use this operation to minimize the storage of the receiver. This default implementation does nothing.

Overrides:

trimToSize in class AbstractBin

variance

public double variance()

Returns the sample variance, which is Sum( (x[i]-mean())² ) / (size()-1).