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A single jar with all the Cognitive Foundry components.
/*
* File: FieldConfidenceInterval.java
* Authors: Kevin R. Dixon
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright October 30, 2007, Sandia Corporation. Under the terms of Contract
* DE-AC04-94AL85000, there is a non-exclusive license for use of this work by
* or on behalf of the U.S. Government. Export of this program may require a
* license from the United States Government. See CopyrightHistory.txt for
* complete details.
*
*/
package gov.sandia.cognition.statistics.method;
import gov.sandia.cognition.util.ObjectUtil;
import java.lang.reflect.Field;
import java.util.ArrayList;
import java.util.Collection;
import java.util.LinkedList;
/**
* This class has methods that automatically compute confidence intervals for
* Double/double Fields in dataclasses.
* For example, if you're in a hurry and want to compute the confidence
* intervals for all given class (e.g., LinearRegression.Statistic), then
* you can simply class the computeConfidenceInterval() with a Collection
* of your desired class and it will return the confidence interval associated
* with the internal Fields of the data. That is, it will return a confidence
* interval associated with each public/protected/private field within the class
* automatically, with you having to specify them individually
* (unless you want to).
*
* @author Kevin R. Dixon
* @since 2.0
*
*/
public class FieldConfidenceInterval
extends ConfidenceInterval
{
/**
* Field associated with the confidence interval
*/
private Field field;
/**
* Creates a new instance of FieldConfidenceInterval
* @param field Field associated with the confidence interval
* @param confidenceInterval ConfidenceInterval associated with the Field
*/
public FieldConfidenceInterval(
Field field,
ConfidenceInterval confidenceInterval )
{
super( confidenceInterval );
this.setField( field );
}
/**
* Determines if the given field is a match to the internal Field
* @param field
* Field to compare against the internal Field
* @return
* True if a match, false otherwise
*/
public boolean isMatch(
Field field )
{
return this.isMatch( field.getName() );
}
/**
* Determines if the given field is a match to the internal Field
* @param fieldName
* Field name to compare against the internal Field
* @return
* True if a match, false otherwise
*/
public boolean isMatch(
String fieldName )
{
return this.getField().getName().equals( fieldName );
}
/**
* Determines whether the Field within the given Object is within the
* specified interval
* @param o
* Object from which to pull the Field's value to determine if it's
* within the specified interval
* @return
* True if o's Field is within the interval, false otherwise
*/
public boolean withinInterval(
Object o )
{
boolean retval;
try
{
this.getField().setAccessible( true );
double value = this.getField().getDouble( o );
retval = this.withinInterval( value );
}
catch (Exception e)
{
retval = false;
}
return retval;
}
/**
* Getter for field
* @return
* Field associated with the confidence interval
*/
public Field getField()
{
return this.field;
}
/**
* Setter for field
* @param field
* Field associated with the confidence interval
*/
public void setField(
Field field )
{
this.field = field;
}
@Override
public String toString()
{
return "Field: " + this.getField().getName() +
", Interval: " + super.toString();
}
/**
* Computes a FieldConfidenceInterval for each Double/double Field
* in the given data.
*
* @param The type of data to compute the confidence interval
* over.
* @param data
* Collection of data from which to pull the values. Must all be same type!
* @param confidenceIntervalEvaluator
* Statistical test that transforms a Collection of Doubles into a
* ConfidenceInterval
* @param confidence
* Confidence (power) of the resulting ConfidenceInterval
* @return
* Collection of FieldConfidenceInterval, one for each Double/double Field
* found in "DataType"
*/
public static ArrayList computeConfidenceInterval(
Collection data,
ConfidenceIntervalEvaluator> confidenceIntervalEvaluator,
double confidence )
{
// Get the fields from the first object in the dataset
Class dataClass = data.iterator().next().getClass();
// Now, get the list of fields
LinkedList allFields = ObjectUtil.getAllFields( dataClass );
// Copy over any "double" or "Double" Fields
ArrayList interestedFields =
new ArrayList( allFields.size() );
for (Field f : allFields)
{
Class c = f.getType();
if (c.isPrimitive() || Number.class.isAssignableFrom( c ))
{
interestedFields.add( f );
}
}
return FieldConfidenceInterval.computeConfidenceInterval(
data, interestedFields, confidenceIntervalEvaluator, confidence );
}
/**
* Computes a FieldConfidenceInterval for the given Fields in the given data
*
* @param The type of data to compute the confidence interval
* over.
* @param interestedFields
* Fields from which to pull data
* @param data
* Collection of data from which to pull the values. Must all be same type!
* @param confidenceIntervalEvaluator
* Statistical test that transforms a Collection of Doubles into a
* ConfidenceInterval
* @param confidence
* Confidence (power) of the resulting ConfidenceInterval
* @return
* Collection of FieldConfidenceInterval, one for each Double/double Field
* found in "DataType"
*/
public static ArrayList computeConfidenceInterval(
Collection data,
ArrayList interestedFields,
ConfidenceIntervalEvaluator> confidenceIntervalEvaluator,
double confidence )
{
// First of all, all data objects must be the EXACT same class
Class dataClass = null;
for (Object o : data)
{
if (dataClass == null)
{
dataClass = o.getClass();
}
if (!dataClass.isInstance( o ))
{
throw new IllegalArgumentException(
"All classes in data must be EXACT same type" );
}
}
// Create a new ArrayList of data,
// one for each field we're interested in
int numFields = interestedFields.size();
ArrayList> fieldValues =
new ArrayList>( numFields );
for (int i = 0; i < numFields; i++)
{
fieldValues.add( new ArrayList( data.size() ) );
}
// Add the field values to the list of data
for (Object o : data)
{
ArrayList