#created on: Aug 5, 2007
package edu.uoregon.tau.perfexplorer.rules

#list any import classes here.
import edu.uoregon.tau.perfexplorer.glue.*;
import java.lang.Math;
import java.text.NumberFormat;
import java.text.DecimalFormat;

#declare any global variables here

#function myFunction( ... ) 
    #function content (can have multiple functions) 
#end

rule "Differences in Particles Per Cell"
	salience 1
	when
		// there exists a difference operation between metadata collections
		d : DifferenceMetadataOperation ()
		f : FactWrapper ( factName == "input:micell", factType == DifferenceMetadataOperation.NAME )
	then 
		String[] values = (String[])d.getDifferences().get("input:micell");
		System.out.println("Differences in particles per cell... " + values[0] + ", " + values[1]);
		double tmp = Double.parseDouble(values[0]) / Double.parseDouble(values[1]);
		// an increase in particles per cell means an increase in time
		d.setExpectedRatio(d.getExpectedRatio() / tmp);
		System.out.println("New Expected Ratio: " + d.getExpectedRatio());
		d.removeFact("input:micell");
end

rule "Differences in Timesteps"
	salience 1
	when
		// there exists a difference operation between metadata collections
		d : DifferenceMetadataOperation ()
		f : FactWrapper ( factName == "input:mstep", factType == DifferenceMetadataOperation.NAME )
	then 
		String[] values = (String[])d.getDifferences().get("input:mstep");
		double tmp = Double.parseDouble(values[0]) / Double.parseDouble(values[1]);
		// an increase in timesteps means an increase in time
		d.setExpectedRatio(d.getExpectedRatio() / tmp);
		System.out.println("New Expected Ratio: " + d.getExpectedRatio());
		d.removeFact("input:mstep");
end

rule "Direct Correlation with Metadata"
	salience 1
	when
		// there exists a difference operation between metadata collections
		c : CorrelationResult ()
		d : FactData ( e : event, m : metric, t : type, e2 : event2, m2 : metric2 )
		eval ( d.getType() == AbstractResult.EXCLUSIVE || d.getType() == AbstractResult.CALLS )
		eval ( d.getType2() == CorrelationResult.CORRELATION )
		eval ( Math.abs(d.getValue()) > 0.99 )
	then 
		StringBuffer buf = new StringBuffer();

		buf.append(e + ": '" + m + ":" + AbstractResult.typeToString(t.intValue()));
		buf.append("' metric is ");
		if (d.getValue() < 0.0)
			buf.append("inversely ");
		buf.append("correlated with the metadata field '");
		buf.append(e2 + "'.");
		System.out.println(buf.toString());
		
		NumberFormat f = new DecimalFormat ("0.000");
		System.out.println("\tThe correlation is " + f.format(d.getValue()) + " (direct).");
		// c.removeFact(n);
end

rule "Very High Correlation with Metadata"
	salience 1
	when
		// there exists a difference operation between metadata collections
		c : CorrelationResult ()
		d : FactData ( e : event, m : metric, t : type, e2 : event2, m2 : metric2 )
		eval ( d.getType() == AbstractResult.EXCLUSIVE || d.getType() == AbstractResult.CALLS )
		eval ( d.getType2() == CorrelationResult.CORRELATION )
		eval ( Math.abs(d.getValue()) >= 0.95 && Math.abs(d.getValue()) < 0.99 )
	then 
		StringBuffer buf = new StringBuffer();

		buf.append(e + ": '" + m + ":" + AbstractResult.typeToString(t.intValue()));
		buf.append("' metric is ");
		if (d.getValue() < 0.0)
			buf.append("inversely ");
		buf.append("correlated with the metadata field '");
		buf.append(e2 + "'.");
		System.out.println(buf.toString());
		
		NumberFormat f = new DecimalFormat ("0.000");
		System.out.println("\tThe correlation is " + f.format(d.getValue()) + " (very high).");
		// c.removeFact(n);
end

rule "High Correlation with Metadata"
	salience 1
	when
		// there exists a difference operation between metadata collections
		c : CorrelationResult ()
		d : FactData ( e : event, m : metric, t : type, e2 : event2, m2 : metric2 )
		eval ( d.getType() == AbstractResult.EXCLUSIVE || d.getType() == AbstractResult.CALLS )
		eval ( d.getType2() == CorrelationResult.CORRELATION )
		eval ( Math.abs(d.getValue()) >= 0.9 && Math.abs(d.getValue()) < 0.95 )
	then 
		StringBuffer buf = new StringBuffer();

		buf.append(e + ": '" + m + ":" + AbstractResult.typeToString(t.intValue()));
		buf.append("' metric is ");
		if (d.getValue() < 0.0)
			buf.append("inversely ");
		buf.append("correlated with the metadata field '");
		buf.append(e2 + "'.");
		System.out.println(buf.toString());
		
		NumberFormat f = new DecimalFormat ("0.000");
		System.out.println("\tThe correlation is " + f.format(d.getValue()) + " (high).");
		// c.removeFact(n);
end

rule "Moderate Correlation with Metadata"
	salience 1
	when
		// there exists a difference operation between metadata collections
		c : CorrelationResult ()
		d : FactData ( e : event, m : metric, t : type, e2 : event2, m2 : metric2 )
		eval ( d.getType() == AbstractResult.EXCLUSIVE || d.getType() == AbstractResult.CALLS )
		eval ( d.getType2() == CorrelationResult.CORRELATION )
		eval ( Math.abs(d.getValue()) >= 0.85 && Math.abs(d.getValue()) < 0.90 )
	then 
		StringBuffer buf = new StringBuffer();

		buf.append(e + ": '" + m + ":" + AbstractResult.typeToString(t.intValue()));
		buf.append("' metric is ");
		if (d.getValue() < 0.0)
			buf.append("inversely ");
		buf.append("correlated with the metadata field '");
		buf.append(e2 + "'.");
		System.out.println(buf.toString());
		
		NumberFormat f = new DecimalFormat ("0.000");
		System.out.println("\tThe correlation is " + f.format(d.getValue()) + " (moderate).");
		// c.removeFact(n);
end