RuleStats.java
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weka.classifiers.rules |
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Weka |
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|---|---|---|
| JAVA0034 | JAVA0034 Missing braces in if statement |  |
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| ELOC | Effective lines of code | |
| JAVA0035 | JAVA0035 Missing braces in for statement | |
| JAVA0233 | JAVA0233 Definition of serialVersionUID other than 'private static final long serialVersionUID' | |
| LOC | Lines of code | |
| INTERFACE_COMPLEXITY | Interface complexity | |
| JAVA0076 | JAVA0076 Use of magic number | |
| JAVA0039 | JAVA0039 Break statement with label | |
| JAVA0177 | JAVA0177 Variable declaration missing initializer | |
| PROGRAM_VOCAB | Halstead program vocabulary | |
| UNIQUE_OPERANDS | Number of unique operands | |
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| UNIQUE_OPERATORS | Number of unique operators | |
| JAVA0117 | JAVA0117 Missing javadoc: method 'method' | |
| PROGRAM_VOLUME | Halstead program volume | |
| JAVA0136 | JAVA0136 N methods defined in class (maximum: M) | |
| RETURNS | Number of return points from functions | |
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| JAVA0110 | JAVA0110 Incorrect javadoc: no @return tag | |
| JAVA0108 | JAVA0108 Incorrect javadoc: no @param tag for 'parameter' | |
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| EXITS | Procedure exits | |
/*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* RuleStats.java
* Copyright (C) 2001 University of Waikato, Hamilton, New Zealand
*/
package weka.classifiers.rules;
import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.Utils;
import java.io.Serializable;
import java.util.Enumeration;
import java.util.Random;
/**
* This class implements the statistics functions used in the
* propositional rule learner, from the simpler ones like count of
* true/false positive/negatives, filter data based on the ruleset, etc.
* to the more sophisticated ones such as MDL calculation and rule
* variants generation for each rule in the ruleset. <p>
*
* Obviously the statistics functions listed above need the specific
* data and the specific ruleset, which are given in order to instantiate
* an object of this class. <p>
*
* @author Xin Xu (xx5@cs.waikato.ac.nz)
* @version $Revision: 1.7 $
*/
public class RuleStats
implements Serializable, RevisionHandler {
/** for serialization */
static final long serialVersionUID = -5708153367675298624L;
/** The data on which the stats calculation is based */
private Instances m_Data;
/** The specific ruleset in question */
private FastVector m_Ruleset;
/** The simple stats of each rule */
private FastVector m_SimpleStats;
/** The set of instances filtered by the ruleset */
private FastVector m_Filtered;
/** The total number of possible conditions that could
* appear in a rule */
private double m_Total;
/** The redundancy factor in theory description length */
private static double REDUNDANCY_FACTOR = 0.5;
/** The theory weight in the MDL calculation */
private double MDL_THEORY_WEIGHT = 1.0;
/** The class distributions predicted by each rule */
private FastVector m_Distributions;
/** Default constructor */
public RuleStats(){
m_Data = null;
m_Ruleset = null;
m_SimpleStats = null;
m_Filtered = null;
m_Distributions = null;
m_Total = -1;
}
/**
* Constructor that provides ruleset and data
*
* @param data the data
* @param rules the ruleset
*/
public RuleStats(Instances data, FastVector rules){
this();
m_Data = data;
m_Ruleset = rules;
}
/**
* Set the number of all conditions that could appear
* in a rule in this RuleStats object, if the number set
* is smaller than 0 (typically -1), then it calcualtes
* based on the data store
*
* @param total the set number
*/
public void setNumAllConds(double total){
if(total < 0)
m_Total = numAllConditions(m_Data);
else
m_Total = total;
}
/**
* Set the data of the stats, overwriting the old one if any
*
* @param data the data to be set
*/
public void setData(Instances data){
m_Data = data;
}
/**
* Get the data of the stats
*
* @return the data
*/
public Instances getData(){
return m_Data;
}
/**
* Set the ruleset of the stats, overwriting the old one if any
*
* @param rules the set of rules to be set
*/
public void setRuleset(FastVector rules){
m_Ruleset = rules;
}
/**
* Get the ruleset of the stats
*
* @return the set of rules
*/
public FastVector getRuleset(){
return m_Ruleset;
}
/**
* Get the size of the ruleset in the stats
*
* @return the size of ruleset
*/
public int getRulesetSize(){
return m_Ruleset.size();
}
/**
* Get the simple stats of one rule, including 6 parameters:
* 0: coverage; 1:uncoverage; 2: true positive; 3: true negatives;
* 4: false positives; 5: false negatives
*
* @param index the index of the rule
* @return the stats
*/
public double[] getSimpleStats(int index){
if((m_SimpleStats != null) && (index < m_SimpleStats.size()))
return (double[])m_SimpleStats.elementAt(index);
return null;
}
/**
* Get the data after filtering the given rule
*
* @param index the index of the rule
* @return the data covered and uncovered by the rule
*/
public Instances[] getFiltered(int index){
if((m_Filtered != null) && (index < m_Filtered.size()))
return (Instances[])m_Filtered.elementAt(index);
return null;
}
/**
* Get the class distribution predicted by the rule in
* given position
*
* @param index the position index of the rule
* @return the class distributions
*/
public double[] getDistributions(int index){
if((m_Distributions != null) && (index < m_Distributions.size()))
return (double[])m_Distributions.elementAt(index);
return null;
}
/**
* Set the weight of theory in MDL calcualtion
*
* @param weight the weight to be set
*/
public void setMDLTheoryWeight(double weight){
MDL_THEORY_WEIGHT = weight;
}
/**
* Compute the number of all possible conditions that could
* appear in a rule of a given data. For nominal attributes,
* it's the number of values that could appear; for numeric
* attributes, it's the number of values * 2, i.e. <= and >=
* are counted as different possible conditions.
*
* @param data the given data
* @return number of all conditions of the data
*/
public static double numAllConditions(Instances data){
double total = 0;
Enumeration attEnum = data.enumerateAttributes();
while(attEnum.hasMoreElements()){
Attribute att= (Attribute)attEnum.nextElement();
if(att.isNominal())
total += (double)att.numValues();
else
total += 2.0 * (double)data.numDistinctValues(att);
}
return total;
}
/**
* Filter the data according to the ruleset and compute the basic
* stats: coverage/uncoverage, true/false positive/negatives of
* each rule
*/
public void countData(){
if((m_Filtered != null) ||
(m_Ruleset == null) ||
(m_Data == null))
return;
int size = m_Ruleset.size();
m_Filtered = new FastVector(size);
m_SimpleStats = new FastVector(size);
m_Distributions = new FastVector(size);
Instances data = new Instances(m_Data);
for(int i=0; i < size; i++){
double[] stats = new double[6]; // 6 statistics parameters
double[] classCounts = new double[m_Data.classAttribute().numValues()];
Instances[] filtered = computeSimpleStats(i, data, stats, classCounts);
m_Filtered.addElement(filtered);
m_SimpleStats.addElement(stats);
m_Distributions.addElement(classCounts);
data = filtered[1]; // Data not covered
}
}
/**
* Count data from the position index in the ruleset
* assuming that given data are not covered by the rules
* in position 0...(index-1), and the statistics of these
* rules are provided.<br>
* This procedure is typically useful when a temporary
* object of RuleStats is constructed in order to efficiently
* calculate the relative DL of rule in position index,
* thus all other stuff is not needed.
*
* @param index the given position
* @param uncovered the data not covered by rules before index
* @param prevRuleStats the provided stats of previous rules
*/
public void countData(int index, Instances uncovered,
double[][] prevRuleStats){
if((m_Filtered != null) ||
(m_Ruleset == null))
return;
int size = m_Ruleset.size();
m_Filtered = new FastVector(size);
m_SimpleStats = new FastVector(size);
Instances[] data = new Instances[2];
data[1] = uncovered;
for(int i=0; i < index; i++){
m_SimpleStats.addElement(prevRuleStats[i]);
if(i+1 == index)
m_Filtered.addElement(data);
else
m_Filtered.addElement(new Object()); // Stuff sth.
}
for(int j=index; j < size; j++){
double[] stats = new double[6]; // 6 statistics parameters
Instances[] filtered = computeSimpleStats(j, data[1], stats, null);
m_Filtered.addElement(filtered);
m_SimpleStats.addElement(stats);
data = filtered; // Data not covered
}
}
/**
* Find all the instances in the dataset covered/not covered by
* the rule in given index, and the correponding simple statistics
* and predicted class distributions are stored in the given double array,
* which can be obtained by getSimpleStats() and getDistributions().<br>
*
* @param index the given index, assuming correct
* @param insts the dataset to be covered by the rule
* @param stats the given double array to hold stats, side-effected
* @param dist the given array to hold class distributions, side-effected
* if null, the distribution is not necessary
* @return the instances covered and not covered by the rule
*/
private Instances[] computeSimpleStats(int index, Instances insts,
double[] stats, double[] dist){
Rule rule = (Rule)m_Ruleset.elementAt(index);
Instances[] data = new Instances[2];
data[0] = new Instances(insts, insts.numInstances());
data[1] = new Instances(insts, insts.numInstances());
for(int i=0; i<insts.numInstances(); i++){
Instance datum = insts.instance(i);
double weight = datum.weight();
if(rule.covers(datum)){
data[0].add(datum); // Covered by this rule
stats[0] += weight; // Coverage
if((int)datum.classValue() == (int)rule.getConsequent())
stats[2] += weight; // True positives
else
stats[4] += weight; // False positives
if(dist != null)
dist[(int)datum.classValue()] += weight;
}
else{
data[1].add(datum); // Not covered by this rule
stats[1] += weight;
if((int)datum.classValue() != (int)rule.getConsequent())
stats[3] += weight; // True negatives
else
stats[5] += weight; // False negatives
}
}
return data;
}
/**
* Add a rule to the ruleset and update the stats
*
* @param lastRule the rule to be added
*/
public void addAndUpdate(Rule lastRule){
if(m_Ruleset == null)
m_Ruleset = new FastVector();
m_Ruleset.addElement(lastRule);
Instances data = (m_Filtered == null) ?
m_Data : ((Instances[])m_Filtered.lastElement())[1];
double[] stats = new double[6];
double[] classCounts = new double[m_Data.classAttribute().numValues()];
Instances[] filtered =
computeSimpleStats(m_Ruleset.size()-1, data, stats, classCounts);
if(m_Filtered == null)
m_Filtered = new FastVector();
m_Filtered.addElement(filtered);
if(m_SimpleStats == null)
m_SimpleStats = new FastVector();
m_SimpleStats.addElement(stats);
if(m_Distributions == null)
m_Distributions = new FastVector();
m_Distributions.addElement(classCounts);
}
/**
* Subset description length: <br>
* S(t,k,p) = -k*log2(p)-(n-k)log2(1-p)
*
* Details see Quilan: "MDL and categorical theories (Continued)",ML95
*
* @param t the number of elements in a known set
* @param k the number of elements in a subset
* @param p the expected proportion of subset known by recipient
* @return the subset description length
*/
public static double subsetDL(double t, double k, double p){
double rt = Utils.gr(p, 0.0) ? (- k*Utils.log2(p)) : 0.0;
rt -= (t-k)*Utils.log2(1-p);
return rt;
}
/**
* The description length of the theory for a given rule. Computed as:<br>
* 0.5* [||k||+ S(t, k, k/t)]<br>
* where k is the number of antecedents of the rule; t is the total
* possible antecedents that could appear in a rule; ||K|| is the
* universal prior for k , log2*(k) and S(t,k,p) = -k*log2(p)-(n-k)log2(1-p)
* is the subset encoding length.<p>
*
* Details see Quilan: "MDL and categorical theories (Continued)",ML95
*
* @param index the index of the given rule (assuming correct)
* @return the theory DL, weighted if weight != 1.0
*/
public double theoryDL(int index){
double k = ((Rule)m_Ruleset.elementAt(index)).size();
if(k == 0)
return 0.0;
double tdl = Utils.log2(k);
if(k > 1) // Approximation
tdl += 2.0 * Utils.log2(tdl); // of log2 star
tdl += subsetDL(m_Total, k, k/m_Total);
//System.out.println("!!!theory: "+MDL_THEORY_WEIGHT * REDUNDANCY_FACTOR * tdl);
return MDL_THEORY_WEIGHT * REDUNDANCY_FACTOR * tdl;
}
/**
* The description length of data given the parameters of the data
* based on the ruleset. <p>
* Details see Quinlan: "MDL and categorical theories (Continued)",ML95<p>
*
* @param expFPOverErr expected FP/(FP+FN)
* @param cover coverage
* @param uncover uncoverage
* @param fp False Positive
* @param fn False Negative
* @return the description length
*/
public static double dataDL(double expFPOverErr, double cover,
double uncover, double fp, double fn){
double totalBits = Utils.log2(cover+uncover+1.0); // how many data?
double coverBits, uncoverBits; // What's the error?
double expErr; // Expected FP or FN
if(Utils.gr(cover, uncover)){
expErr = expFPOverErr*(fp+fn);
coverBits = subsetDL(cover, fp, expErr/cover);
uncoverBits = Utils.gr(uncover, 0.0) ?
subsetDL(uncover, fn, fn/uncover) : 0.0;
}
else{
expErr = (1.0-expFPOverErr)*(fp+fn);
coverBits = Utils.gr(cover, 0.0) ?
subsetDL(cover, fp, fp/cover) : 0.0;
uncoverBits = subsetDL(uncover, fn, expErr/uncover);
}
/*
System.err.println("!!!cover: " + cover + "|uncover" + uncover +
"|coverBits: "+coverBits+"|uncBits: "+ uncoverBits+
"|FPRate: "+expFPOverErr + "|expErr: "+expErr+
"|fp: "+fp+"|fn: "+fn+"|total: "+totalBits);
*/
return (totalBits + coverBits + uncoverBits);
}
/**
* Calculate the potential to decrease DL of the ruleset,
* i.e. the possible DL that could be decreased by deleting
* the rule whose index and simple statstics are given.
* If there's no potentials (i.e. smOrEq 0 && error rate < 0.5),
* it returns NaN. <p>
*
* The way this procedure does is copied from original RIPPER
* implementation and is quite bizzare because it
* does not update the following rules' stats recursively
* any more when testing each rule, which means it assumes
* after deletion no data covered by the following rules (or
* regards the deleted rule as the last rule). Reasonable
* assumption?<p>
*
* @param index the index of the rule in m_Ruleset to be deleted
* @param expFPOverErr expected FP/(FP+FN)
* @param rulesetStat the simple statistics of the ruleset, updated
* if the rule should be deleted
* @param ruleStat the simple statistics of the rule to be deleted
* @param checkErr whether check if error rate >= 0.5
* @return the potential DL that could be decreased
*/
public double potential(int index, double expFPOverErr,
double[] rulesetStat, double[] ruleStat,
boolean checkErr){
//System.out.println("!!!inside potential: ");
// Restore the stats if deleted
double pcov = rulesetStat[0] - ruleStat[0];
double puncov = rulesetStat[1] + ruleStat[0];
double pfp = rulesetStat[4] - ruleStat[4];
double pfn = rulesetStat[5] + ruleStat[2];
double dataDLWith = dataDL(expFPOverErr, rulesetStat[0],
rulesetStat[1], rulesetStat[4],
rulesetStat[5]);
double theoryDLWith = theoryDL(index);
double dataDLWithout = dataDL(expFPOverErr, pcov, puncov, pfp, pfn);
double potential = dataDLWith + theoryDLWith - dataDLWithout;
double err = ruleStat[4] / ruleStat[0];
/*System.out.println("!!!"+dataDLWith +" | "+
theoryDLWith + " | "
+dataDLWithout+"|"+ruleStat[4] + " / " + ruleStat[0]);
*/
boolean overErr = Utils.grOrEq(err, 0.5);
if(!checkErr)
overErr = false;
if(Utils.grOrEq(potential, 0.0) || overErr){
// If deleted, update ruleset stats. Other stats do not matter
rulesetStat[0] = pcov;
rulesetStat[1] = puncov;
rulesetStat[4] = pfp;
rulesetStat[5] = pfn;
return potential;
}
else
return Double.NaN;
}
/**
* Compute the minimal data description length of the ruleset
* if the rule in the given position is deleted.<br>
* The min_data_DL_if_deleted = data_DL_if_deleted - potential
*
* @param index the index of the rule in question
* @param expFPRate expected FP/(FP+FN), used in dataDL calculation
* @param checkErr whether check if error rate >= 0.5
* @return the minDataDL
*/
public double minDataDLIfDeleted(int index, double expFPRate,
boolean checkErr){
//System.out.println("!!!Enter without: ");
double[] rulesetStat = new double[6]; // Stats of ruleset if deleted
int more = m_Ruleset.size() - 1 - index; // How many rules after?
FastVector indexPlus = new FastVector(more); // Their stats
// 0...(index-1) are OK
for(int j=0; j<index; j++){
// Covered stats are cumulative
rulesetStat[0] += ((double[])m_SimpleStats.elementAt(j))[0];
rulesetStat[2] += ((double[])m_SimpleStats.elementAt(j))[2];
rulesetStat[4] += ((double[])m_SimpleStats.elementAt(j))[4];
}
// Recount data from index+1
Instances data = (index == 0) ?
m_Data : ((Instances[])m_Filtered.elementAt(index-1))[1];
//System.out.println("!!!without: " + data.sumOfWeights());
for(int j=(index+1); j<m_Ruleset.size(); j++){
double[] stats = new double[6];
Instances[] split = computeSimpleStats(j, data, stats, null);
indexPlus.addElement(stats);
rulesetStat[0] += stats[0];
rulesetStat[2] += stats[2];
rulesetStat[4] += stats[4];
data = split[1];
}
// Uncovered stats are those of the last rule
if(more > 0){
rulesetStat[1] = ((double[])indexPlus.lastElement())[1];
rulesetStat[3] = ((double[])indexPlus.lastElement())[3];
rulesetStat[5] = ((double[])indexPlus.lastElement())[5];
}
else if(index > 0){
rulesetStat[1] =
((double[])m_SimpleStats.elementAt(index-1))[1];
rulesetStat[3] =
((double[])m_SimpleStats.elementAt(index-1))[3];
rulesetStat[5] =
((double[])m_SimpleStats.elementAt(index-1))[5];
}
else{ // Null coverage
rulesetStat[1] = ((double[])m_SimpleStats.elementAt(0))[0] +
((double[])m_SimpleStats.elementAt(0))[1];
rulesetStat[3] = ((double[])m_SimpleStats.elementAt(0))[3] +
((double[])m_SimpleStats.elementAt(0))[4];
rulesetStat[5] = ((double[])m_SimpleStats.elementAt(0))[2] +
((double[])m_SimpleStats.elementAt(0))[5];
}
// Potential
double potential = 0;
for(int k=index+1; k<m_Ruleset.size(); k++){
double[] ruleStat = (double[])indexPlus.elementAt(k-index-1);
double ifDeleted = potential(k, expFPRate, rulesetStat,
ruleStat, checkErr);
if(!Double.isNaN(ifDeleted))
potential += ifDeleted;
}
// Data DL of the ruleset without the rule
// Note that ruleset stats has already been updated to reflect
// deletion if any potential
double dataDLWithout = dataDL(expFPRate, rulesetStat[0],
rulesetStat[1], rulesetStat[4],
rulesetStat[5]);
//System.out.println("!!!without: "+dataDLWithout + " |potential: "+
// potential);
// Why subtract potential again? To reflect change of theory DL??
return (dataDLWithout - potential);
}
/**
* Compute the minimal data description length of the ruleset
* if the rule in the given position is NOT deleted.<br>
* The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential
*
* @param index the index of the rule in question
* @param expFPRate expected FP/(FP+FN), used in dataDL calculation
* @param checkErr whether check if error rate >= 0.5
* @return the minDataDL
*/
public double minDataDLIfExists(int index, double expFPRate,
boolean checkErr){
// System.out.println("!!!Enter with: ");
double[] rulesetStat = new double[6]; // Stats of ruleset if rule exists
for(int j=0; j<m_SimpleStats.size(); j++){
// Covered stats are cumulative
rulesetStat[0] += ((double[])m_SimpleStats.elementAt(j))[0];
rulesetStat[2] += ((double[])m_SimpleStats.elementAt(j))[2];
rulesetStat[4] += ((double[])m_SimpleStats.elementAt(j))[4];
if(j == m_SimpleStats.size()-1){ // Last rule
rulesetStat[1] = ((double[])m_SimpleStats.elementAt(j))[1];
rulesetStat[3] = ((double[])m_SimpleStats.elementAt(j))[3];
rulesetStat[5] = ((double[])m_SimpleStats.elementAt(j))[5];
}
}
// Potential
double potential = 0;
for(int k=index+1; k<m_SimpleStats.size(); k++){
double[] ruleStat = (double[])getSimpleStats(k);
double ifDeleted = potential(k, expFPRate, rulesetStat,
ruleStat, checkErr);
if(!Double.isNaN(ifDeleted))
potential += ifDeleted;
}
// Data DL of the ruleset without the rule
// Note that ruleset stats has already been updated to reflect deletion
// if any potential
double dataDLWith = dataDL(expFPRate, rulesetStat[0],
rulesetStat[1], rulesetStat[4],
rulesetStat[5]);
//System.out.println("!!!with: "+dataDLWith + " |potential: "+
// potential);
return (dataDLWith - potential);
}
/**
* The description length (DL) of the ruleset relative to if the
* rule in the given position is deleted, which is obtained by: <br>
* MDL if the rule exists - MDL if the rule does not exist <br>
* Note the minimal possible DL of the ruleset is calculated(i.e. some
* other rules may also be deleted) instead of the DL of the current
* ruleset.<p>
*
* @param index the given position of the rule in question
* (assuming correct)
* @param expFPRate expected FP/(FP+FN), used in dataDL calculation
* @param checkErr whether check if error rate >= 0.5
* @return the relative DL
*/
public double relativeDL(int index, double expFPRate, boolean checkErr){
return (minDataDLIfExists(index, expFPRate, checkErr)
+ theoryDL(index) -
minDataDLIfDeleted(index, expFPRate, checkErr));
}
/**
* Try to reduce the DL of the ruleset by testing removing the rules
* one by one in reverse order and update all the stats
* @param expFPRate expected FP/(FP+FN), used in dataDL calculation
* @param checkErr whether check if error rate >= 0.5
*/
public void reduceDL(double expFPRate, boolean checkErr){
boolean needUpdate = false;
double[] rulesetStat = new double[6];
for(int j=0; j<m_SimpleStats.size(); j++){
// Covered stats are cumulative
rulesetStat[0] += ((double[])m_SimpleStats.elementAt(j))[0];
rulesetStat[2] += ((double[])m_SimpleStats.elementAt(j))[2];
rulesetStat[4] += ((double[])m_SimpleStats.elementAt(j))[4];
if(j == m_SimpleStats.size()-1){ // Last rule
rulesetStat[1] = ((double[])m_SimpleStats.elementAt(j))[1];
rulesetStat[3] = ((double[])m_SimpleStats.elementAt(j))[3];
rulesetStat[5] = ((double[])m_SimpleStats.elementAt(j))[5];
}
}
// Potential
for(int k=m_SimpleStats.size()-1; k>=0; k--){
double[] ruleStat = (double[])m_SimpleStats.elementAt(k);
// rulesetStat updated
double ifDeleted = potential(k, expFPRate, rulesetStat,
ruleStat, checkErr);
if(!Double.isNaN(ifDeleted)){
/*System.err.println("!!!deleted ("+k+"): save "+ifDeleted
+" | "+rulesetStat[0]
+" | "+rulesetStat[1]
+" | "+rulesetStat[4]
+" | "+rulesetStat[5]);
*/
if(k == (m_SimpleStats.size()-1))
removeLast();
else{
m_Ruleset.removeElementAt(k);
needUpdate = true;
}
}
}
if(needUpdate){
m_Filtered = null;
m_SimpleStats = null;
countData();
}
}
/**
* Remove the last rule in the ruleset as well as it's stats.
* It might be useful when the last rule was added for testing
* purpose and then the test failed
*/
public void removeLast(){
int last = m_Ruleset.size()-1;
m_Ruleset.removeElementAt(last);
m_Filtered.removeElementAt(last);
m_SimpleStats.removeElementAt(last);
if(m_Distributions != null)
m_Distributions.removeElementAt(last);
}
/**
* Static utility function to count the data covered by the
* rules after the given index in the given rules, and then
* remove them. It returns the data not covered by the
* successive rules.
*
* @param data the data to be processed
* @param rules the ruleset
* @param index the given index
* @return the data after processing
*/
public static Instances rmCoveredBySuccessives(Instances data, FastVector rules, int index){
Instances rt = new Instances(data, 0);
for(int i=0; i < data.numInstances(); i++){
Instance datum = data.instance(i);
boolean covered = false;
for(int j=index+1; j<rules.size();j++){
Rule rule = (Rule)rules.elementAt(j);
if(rule.covers(datum)){
covered = true;
break;
}
}
if(!covered)
rt.add(datum);
}
return rt;
}
/**
* Stratify the given data into the given number of bags based on the class
* values. It differs from the <code>Instances.stratify(int fold)</code>
* that before stratification it sorts the instances according to the
* class order in the header file. It assumes no missing values in the class.
*
* @param data the given data
* @param folds the given number of folds
* @param rand the random object used to randomize the instances
* @return the stratified instances
*/
public static final Instances stratify(Instances data, int folds, Random rand){
if(!data.classAttribute().isNominal())
return data;
Instances result = new Instances(data, 0);
Instances[] bagsByClasses = new Instances[data.numClasses()];
for(int i=0; i < bagsByClasses.length; i++)
bagsByClasses[i] = new Instances(data, 0);
// Sort by class
for(int j=0; j < data.numInstances(); j++){
Instance datum = data.instance(j);
bagsByClasses[(int)datum.classValue()].add(datum);
}
// Randomize each class
for(int j=0; j < bagsByClasses.length; j++)
bagsByClasses[j].randomize(rand);
for(int k=0; k < folds; k++){
int offset = k, bag = 0;
oneFold:
while (true){
while(offset >= bagsByClasses[bag].numInstances()){
offset -= bagsByClasses[bag].numInstances();
if (++bag >= bagsByClasses.length)// Next bag
break oneFold;
}
result.add(bagsByClasses[bag].instance(offset));
offset += folds;
}
}
return result;
}
/**
* Compute the combined DL of the ruleset in this class, i.e. theory
* DL and data DL. Note this procedure computes the combined DL
* according to the current status of the ruleset in this class
*
* @param expFPRate expected FP/(FP+FN), used in dataDL calculation
* @param predicted the default classification if ruleset covers null
* @return the combined class
*/
public double combinedDL(double expFPRate, double predicted){
double rt = 0;
if(getRulesetSize() > 0) {
double[] stats = (double[])m_SimpleStats.lastElement();
for(int j=getRulesetSize()-2; j >= 0; j--){
stats[0] += getSimpleStats(j)[0];
stats[2] += getSimpleStats(j)[2];
stats[4] += getSimpleStats(j)[4];
}
rt += dataDL(expFPRate, stats[0], stats[1],
stats[4], stats[5]); // Data DL
}
else{ // Null coverage ruleset
double fn = 0.0;
for(int j=0; j < m_Data.numInstances(); j++)
if((int)m_Data.instance(j).classValue() == (int)predicted)
fn += m_Data.instance(j).weight();
rt += dataDL(expFPRate, 0.0, m_Data.sumOfWeights(), 0.0, fn);
}
for(int i=0; i<getRulesetSize(); i++) // Theory DL
rt += theoryDL(i);
return rt;
}
/**
* Patition the data into 2, first of which has (numFolds-1)/numFolds of
* the data and the second has 1/numFolds of the data
*
*
* @param data the given data
* @param numFolds the given number of folds
* @return the patitioned instances
*/
public static final Instances[] partition(Instances data, int numFolds){
Instances[] rt = new Instances[2];
int splits = data.numInstances() * (numFolds - 1) / numFolds;
rt[0] = new Instances(data, 0, splits);
rt[1] = new Instances(data, splits, data.numInstances()-splits);
return rt;
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.7 $");
}
}
The table below shows all metrics for RuleStats.java.
| Metric | Value | Description | |
|---|---|---|---|
| BLOCKS | 66.00 | Number of blocks | |
| BLOCK_COMMENT | 35.00 | Number of block comment lines | |
| COMMENTS | 351.00 | Comment lines | |
| COMMENT_DENSITY | 0.92 | Comment density | |
| COMPARISONS | 85.00 | Number of comparison operators | |
| CYCLOMATIC | 102.00 | Cyclomatic complexity | |
| DECL_COMMENTS | 43.00 | Comments in declarations | |
| DOC_COMMENT | 286.00 | Number of javadoc comment lines | |
| ELOC | 380.00 | Effective lines of code | |
| EXEC_COMMENTS | 25.00 | Comments in executable code | |
| EXITS | 40.00 | Procedure exits | |
| FUNCTIONS | 31.00 | Number of function declarations | |
| HALSTEAD_DIFFICULTY | 130.42 | Halstead difficulty | |
| HALSTEAD_EFFORT | 0.00 | Halstead effort | |
| INTERFACE_COMPLEXITY | 92.00 | Interface complexity | |
| JAVA0001 | 0.00 | JAVA0001 Package name does not contain only lower case letters | |
| JAVA0002 | 1.00 | JAVA0002 Package name does not begin with a top level domain name or country code | |
| JAVA0003 | 0.00 | JAVA0003 Minimize use of on-demand (.*) imports | |
| JAVA0004 | 0.00 | JAVA0004 Unnecessary import from java.lang | |
| JAVA0005 | 1.00 | JAVA0005 Imports not in specified order | |
| JAVA0006 | 0.00 | JAVA0006 Empty finally block | |
| JAVA0007 | 0.00 | JAVA0007 Should not declare public field | |
| JAVA0008 | 0.00 | JAVA0008 Empty catch block | |
| JAVA0009 | 0.00 | JAVA0009 Protected member in final class | |
| JAVA0010 | 0.00 | JAVA0010 Non-instantiable class does not contain a non-private static member | |
| JAVA0011 | 0.00 | JAVA0011 Abstract class does not contain an abstract method | |
| JAVA0012 | 0.00 | JAVA0012 Non-constructor method with same name as declaring class | |
| JAVA0013 | 0.00 | JAVA0013 Non-blank final field is not static | |
| JAVA0014 | 0.00 | JAVA0014 Class with only static members has non-private constructor | |
| JAVA0015 | 0.00 | JAVA0015 Package class contains public nested type | |
| JAVA0016 | 0.00 | JAVA0016 Abstract class contains public constructor | |
| JAVA0017 | 0.00 | JAVA0017 Class name does not have required form | |
| JAVA0018 | 0.00 | JAVA0018 Method name does not have required form | |
| JAVA0019 | 0.00 | JAVA0019 Interface name does not have required form | |
| JAVA0020 | 0.00 | JAVA0020 Field name does not have required form | |
| JAVA0021 | 0.00 | JAVA0021 Interface method name does not have required form | |
| JAVA0022 | 0.00 | JAVA0022 Static final field name does not have required form | |
| JAVA0023 | 0.00 | JAVA0023 Empty finalize method | |
| JAVA0024 | 0.00 | JAVA0024 Empty class | |
| JAVA0025 | 0.00 | JAVA0025 Method override is empty | |
| JAVA0026 | 0.00 | JAVA0026 Finalize method with parameters | |
| JAVA0029 | 0.00 | JAVA0029 Private method not used | |
| JAVA0030 | 0.00 | JAVA0030 Private field not used | |
| JAVA0031 | 0.00 | JAVA0031 Case statement not properly closed | |
| JAVA0032 | 0.00 | JAVA0032 Switch statement missing default | |
| JAVA0033 | 0.00 | JAVA0033 default: not last case in switch statement | |
| JAVA0034 | 32.00 | JAVA0034 Missing braces in if statement | |
| JAVA0035 | 4.00 | JAVA0035 Missing braces in for statement | |
| JAVA0036 | 0.00 | JAVA0036 Missing braces in while statement | |
| JAVA0038 | 0.00 | JAVA0038 Non-case label in switch statement | |
| JAVA0039 | 1.00 | JAVA0039 Break statement with label | |
| JAVA0040 | 0.00 | JAVA0040 Switch statement contains N cases (maximum: M) | |
| JAVA0041 | 0.00 | JAVA0041 Nested synchronized block | |
| JAVA0042 | 0.00 | JAVA0042 Empty synchronized statement | |
| JAVA0043 | 0.00 | JAVA0043 Inner class does not use outer class | |
| JAVA0044 | 0.00 | JAVA0044 Serializable class with no instance variables | |
| JAVA0045 | 0.00 | JAVA0045 Serializable class with only transient fields | |
| JAVA0046 | 0.00 | JAVA0046 Name of class not derived from Exception ends with 'Exception' | |
| JAVA0047 | 0.00 | JAVA0047 Serializable class derives from invalid base class | |
| JAVA0048 | 0.00 | JAVA0048 Name of class derived from Exception does not end with 'Exception' | |
| JAVA0049 | 0.00 | JAVA0049 Nested block at depth N (maximum: M) | |
| JAVA0050 | 0.00 | JAVA0050 Class derives from java.lang.Error | |
| JAVA0051 | 0.00 | JAVA0051 Class derives from java.lang.RuntimeException | |
| JAVA0052 | 0.00 | JAVA0052 Class derives from java.lang.Throwable | |
| JAVA0053 | 0.00 | JAVA0053 Unused label | |
| JAVA0054 | 0.00 | JAVA0054 Inheritance depth N exceeds maximum M | |
| JAVA0055 | 0.00 | JAVA0055 Class should be interface | |
| JAVA0056 | 0.00 | JAVA0056 Unnecessary abstract modifier for interface or annotation | |
| JAVA0057 | 0.00 | JAVA0057 Unnecessary default constructor | |
| JAVA0058 | 0.00 | JAVA0058 Constructor calls super() | |
| JAVA0059 | 0.00 | JAVA0059 Method override only calls super() | |
| JAVA0061 | 0.00 | JAVA0061 Inaccessible member in anonymous class | |
| JAVA0062 | 0.00 | JAVA0062 Public class missing public member or protected constructor | |
| JAVA0063 | 0.00 | JAVA0063 Identifier name should not contain '$' | |
| JAVA0064 | 0.00 | JAVA0064 N variations of identifier name (maximum: M) | |
| JAVA0065 | 0.00 | JAVA0065 Unnecessary final modifier for method in final class | |
| JAVA0066 | 0.00 | JAVA0066 Unnecessary modifier for interface nested type | |
| JAVA0067 | 0.00 | JAVA0067 Array descriptor on identifier name | |
| JAVA0068 | 0.00 | JAVA0068 Modifiers not declared in recommended order | |
| JAVA0071 | 0.00 | JAVA0071 Strings compared with == | |
| JAVA0073 | 0.00 | JAVA0073 Integer division in floating-point context | |
| JAVA0074 | 0.00 | JAVA0074 Use of Object.notify() | |
| JAVA0075 | 0.00 | JAVA0075 Method parameter hides field | |
| JAVA0076 | 9.00 | JAVA0076 Use of magic number | |
| JAVA0077 | 0.00 | JAVA0077 Private field not used in declaring class | |
| JAVA0078 | 1.00 | JAVA0078 Floating point values compared with == | |
| JAVA0079 | 0.00 | JAVA0079 Use of instance to reference static member | |
| JAVA0080 | 0.00 | JAVA0080 Import declaration not used | |
| JAVA0081 | 0.00 | JAVA0081 Boolean literal in comparison | |
| JAVA0082 | 1.00 | JAVA0082 Unnecessary widening cast | |
| JAVA0083 | 0.00 | JAVA0083 Unnecessary instanceof test | |
| JAVA0084 | 0.00 | JAVA0084 Should use compound assignment operator | |
| JAVA0085 | 0.00 | JAVA0085 Use of sun.* class | |
| JAVA0087 | 0.00 | JAVA0087 Use of Thread.sleep() | |
| JAVA0089 | 0.00 | JAVA0089 Use of restricted package | |
| JAVA0092 | 0.00 | JAVA0092 Use of restricted type | |
| JAVA0093 | 0.00 | JAVA0093 Redundant assignment | |
| JAVA0094 | 0.00 | JAVA0094 Field hides a superclass field | |
| JAVA0095 | 0.00 | JAVA0095 Uninitialized private field | |
| JAVA0096 | 0.00 | JAVA0096 Field in nested class hides outer field | |
| JAVA0098 | 0.00 | JAVA0098 Minimize use of implicit field initializers | |
| JAVA0100 | 0.00 | JAVA0100 Class contains N non-final fields (maximum: M) | |
| JAVA0101 | 0.00 | JAVA0101 Unnecessary modifier for field in interface | |
| JAVA0102 | 0.00 | JAVA0102 Last statement in finalize() not super.finalize() | |
| JAVA0103 | 0.00 | JAVA0103 Explicit call to finalize() | |
| JAVA0104 | 0.00 | JAVA0104 finalize() only calls super.finalize() | |
| JAVA0105 | 0.00 | JAVA0105 Duplicate import declaration | |
| JAVA0106 | 0.00 | JAVA0106 Unnecessary import from current package | |
| JAVA0108 | 0.00 | JAVA0108 Incorrect javadoc: no @param tag for 'parameter' | |
| JAVA0109 | 0.00 | JAVA0109 Incorrect javadoc: no parameter 'parameter' | |
| JAVA0110 | 0.00 | JAVA0110 Incorrect javadoc: no @return tag | |
| JAVA0111 | 0.00 | JAVA0111 Incorrect javadoc: @return tag for void method | |
| JAVA0112 | 0.00 | JAVA0112 Incorrect javadoc: no exception 'exception' in throws | |
| JAVA0113 | 0.00 | JAVA0113 Incorrect javadoc: no @author tag | |
| JAVA0114 | 0.00 | JAVA0114 Incorrect javadoc: no @version tag | |
| JAVA0115 | 0.00 | JAVA0115 Incorrect javadoc: no @throws or @exception tag for 'exception' | |
| JAVA0116 | 0.00 | JAVA0116 Missing javadoc: field 'field' | |
| JAVA0117 | 0.00 | JAVA0117 Missing javadoc: method 'method' | |
| JAVA0118 | 0.00 | JAVA0118 Missing javadoc: type 'type' | |
| JAVA0119 | 0.00 | JAVA0119 Control variable changed within body of for loop | |
| JAVA0123 | 0.00 | JAVA0123 Use all three components of for loop | |
| JAVA0125 | 0.00 | JAVA0125 Continue statement with label | |
| JAVA0126 | 0.00 | JAVA0126 Method declares unchecked exception in throws | |
| JAVA0128 | 0.00 | JAVA0128 Public constructor in non-public class | |
| JAVA0130 | 0.00 | JAVA0130 Non-static method does not use instance fields | |
| JAVA0131 | 0.00 | JAVA0131 Compatible method does not override base | |
| JAVA0132 | 0.00 | JAVA0132 Method overload with compatible signature | |
| JAVA0133 | 0.00 | JAVA0133 Non-synchronized method overrides synchronized method | |
| JAVA0135 | 0.00 | JAVA0135 Only one of Object.equals and Object.hashCode defined: missing 'method' | |
| JAVA0136 | 1.00 | JAVA0136 N methods defined in class (maximum: M) | |
| JAVA0137 | 0.00 | JAVA0137 Non-abstract class missing constructor | |
| JAVA0138 | 0.00 | JAVA0138 N parameters defined for method (maximum: M) | |
| JAVA0139 | 0.00 | JAVA0139 Definition of main other than public static void main(java.lang.String[]) | |
| JAVA0141 | 0.00 | JAVA0141 Unnecessary modifier for method in interface | |
| JAVA0143 | 0.00 | JAVA0143 Synchronized method | |
| JAVA0144 | 0.00 | JAVA0144 Line exceeds maximum M characters | |
| JAVA0145 | 233.00 | JAVA0145 Tab character used in source file | |
| JAVA0150 | 0.00 | JAVA0150 java.lang.Error (or subclass) thrown | |
| JAVA0153 | 0.00 | JAVA0153 Inefficient conversion of integer to string | |
| JAVA0159 | 0.00 | JAVA0159 Inefficient conversion of string to integer | |
| JAVA0160 | 0.00 | JAVA0160 Method does not throw specified exception | |
| JAVA0161 | 0.00 | JAVA0161 Conditional wait() not in loop | |
| JAVA0163 | 0.00 | JAVA0163 Empty statement | |
| JAVA0165 | 0.00 | JAVA0165 Conflicting return statement in finally block | |
| JAVA0166 | 0.00 | JAVA0166 Generic exception caught | |
| JAVA0167 | 0.00 | JAVA0167 ThreadDeath not rethrown | |
| JAVA0169 | 0.00 | JAVA0169 Unnecessary catch block: exception 'exception' | |
| JAVA0170 | 0.00 | JAVA0170 Caught exception not derived from java.lang.Exception | |
| JAVA0171 | 0.00 | JAVA0171 Unused local variable | |
| JAVA0173 | 0.00 | JAVA0173 Unused method parameter | |
| JAVA0174 | 0.00 | JAVA0174 Assigned local variable never used | |
| JAVA0175 | 0.00 | JAVA0175 Successive assignment to variable | |
| JAVA0176 | 0.00 | JAVA0176 Local variable name does not have required form | |
| JAVA0177 | 3.00 | JAVA0177 Variable declaration missing initializer | |
| JAVA0179 | 0.00 | JAVA0179 Local variable hides visible field | |
| JAVA0233 | 1.00 | JAVA0233 Definition of serialVersionUID other than 'private static final long serialVersionUID' | |
| JAVA0234 | 0.00 | JAVA0234 Class is Serializable but does not define serialVersionUID | |
| JAVA0235 | 0.00 | JAVA0235 Class defines serialVersionUID but does not implement Serializable | |
| JAVA0236 | 0.00 | JAVA0236 Attempt to clone an object which does not implement Cloneable | |
| JAVA0237 | 0.00 | JAVA0237 Class implements Cloneable but does not have public clone method | |
| JAVA0238 | 0.00 | JAVA0238 Clone method does not call super.clone() | |
| JAVA0239 | 0.00 | JAVA0239 Class declares 'readObject' or 'writeObject' but does not implement Serializable | |
| JAVA0240 | 0.00 | JAVA0240 Serializable class which declares readObject or writeObject but not both | |
| JAVA0241 | 0.00 | JAVA0241 'readObject' or 'writeObject' should be declared private in Serializable class | |
| JAVA0242 | 0.00 | JAVA0242 Transient field in non-Serializable class | |
| JAVA0243 | 0.00 | JAVA0243 'readResolve' or 'writeReplace' should be declared private or protected | |
| JAVA0244 | 0.00 | JAVA0244 Field or method name in subclass differs only by case from inherited field or method | |
| JAVA0245 | 0.00 | JAVA0245 JUnit TestCase with non-trivial constructor | |
| JAVA0246 | 0.00 | JAVA0246 JUnit assertXXX statement missing message parameter | |
| JAVA0247 | 0.00 | JAVA0247 JUnit 'setUp()' and 'tearDown()' should call super method | |
| JAVA0248 | 0.00 | JAVA0248 JUnit method 'setUp' or 'tearDown' with incorrect signature | |
| JAVA0249 | 0.00 | JAVA0249 JUnit TestCase 'suite()' should be declared static | |
| JAVA0250 | 0.00 | JAVA0250 JUnit TestCase declares testXXX method with incorrect signature | |
| JAVA0251 | 0.00 | JAVA0251 Use '%n' for line breaks in printf/format for platform independence | |
| JAVA0252 | 0.00 | JAVA0252 'enum' is a Java 1.5 reserved word | |
| JAVA0253 | 0.00 | JAVA0253 Not all enum constants consumed in switch statement | |
| JAVA0254 | 0.00 | JAVA0254 Use enhanced for loop construct instead of Iterator | |
| JAVA0255 | 0.00 | JAVA0255 Result of method invocation not used | |
| JAVA0256 | 0.00 | JAVA0256 Assignment of external collection/array to field | |
| JAVA0257 | 0.00 | JAVA0257 Use of 'Constant Interface' anti-pattern | |
| JAVA0258 | 0.00 | JAVA0258 Implement Iterable for foreach compatibility | |
| JAVA0259 | 0.00 | JAVA0259 Return of collection/array field | |
| JAVA0260 | 0.00 | JAVA0260 Use 'enum' instead of Enumerated Type pattern | |
| JAVA0261 | 0.00 | JAVA0261 Use specialized Enum collection types | |
| JAVA0262 | 0.00 | JAVA0262 Use of char in integer context | |
| JAVA0263 | 0.00 | JAVA0263 Long literal ends with 'l' instead of 'L' | |
| JAVA0264 | 0.00 | JAVA0264 Integer math in long context - check for overflow | |
| JAVA0265 | 0.00 | JAVA0265 Use of Throwable.printStackTrace() | |
| JAVA0266 | 0.00 | JAVA0266 Use of System.out | |
| JAVA0267 | 0.00 | JAVA0267 Use of System.err | |
| JAVA0269 | 0.00 | JAVA0269 Contents of StringBuffer never used | |
| JAVA0270 | 1.00 | JAVA0270 Use Java 5.0 enhanced for loop construct to iterate over all elements in an array | |
| JAVA0271 | 0.00 | JAVA0271 Minimize use of on-demand (.*) static imports | |
| JAVA0272 | 0.00 | JAVA0272 Thread.run() called | |
| JAVA0273 | 0.00 | JAVA0273 Non-final derivative of Thread calls start() in constructor | |
| JAVA0274 | 0.00 | JAVA0274 Serializable class has a synchronized readObject() | |
| JAVA0275 | 0.00 | JAVA0275 Serializable class has a synchronized writeObject() and no other synchronized methods | |
| JAVA0276 | 0.00 | JAVA0276 Unnecessary use of String constructor | |
| JAVA0277 | 0.00 | JAVA0277 Iterator.next() implementation does not throw NoSuchElementException | |
| JAVA0278 | 0.00 | JAVA0278 Unnecessary use of Boolean constructor | |
| JAVA0279 | 0.00 | JAVA0279 Serialization method readObject or readObjectNoData calls an overridable method | |
| JAVA0280 | 0.00 | JAVA0280 IllegalMonitorStateException caught | |
| JAVA0281 | 0.00 | JAVA0281 Iterator.next() not called in loop | |
| JAVA0282 | 0.00 | JAVA0282 Call to Iterator.next() in loop which does not test Iterator.hasNext() | |
| JAVA0283 | 0.00 | JAVA0283 Control variable not updated in loop body | |
| JAVA0284 | 0.00 | JAVA0284 Explicit garbage collection | |
| JAVA0285 | 0.00 | JAVA0285 Dereference of potentially null variable | |
| JAVA0286 | 0.00 | JAVA0286 Dereference of null variable | |
| JAVA0287 | 0.00 | JAVA0287 Unnecessary null check | |
| JAVA0288 | 0.00 | JAVA0288 Inconsistent null check | |
| LINES | 912.00 | Number of lines in the source file | |
| LINE_COMMENT | 30.00 | Number of line comments | |
| LOC | 447.00 | Lines of code | |
| LOGICAL_LINES | 282.00 | Number of statements | |
| LOOPS | 23.00 | Number of loops | |
| NEST_DEPTH | 4.00 | Maximum nesting depth | |
| OPERANDS | 1254.00 | Number of operands | |
| OPERATORS | 2629.00 | Number of operators | |
| PARAMS | 53.00 | Number of formal parameter declarations | |
| PROGRAM_LENGTH | 3883.00 | Halstead program length | |
| PROGRAM_VOCAB | 302.00 | Halstead program vocabulary | |
| PROGRAM_VOLUME | 0.00 | Halstead program volume | |
| RETURNS | 39.00 | Number of return points from functions | |
| SIZE | 29715.00 | Size of the file in bytes | |
| UNIQUE_OPERANDS | 250.00 | Number of unique operands | |
| UNIQUE_OPERATORS | 52.00 | Number of unique operators | |
| WHITESPACE | 114.00 | Number of whitespace lines | |