/**
* The calculation is done here. Example: From 1.96 (Z-score) to 0.975 (P-value) From -1.96
* (Z-score) to 0.025
*
* @return double a p value
*/
public static double cumulativeProbability(Distribution obj, Number n) {
NormalDistribution dist = new NormalDistributionImpl();
double lQuantile = 0;
try {
lQuantile = dist.cumulativeProbability(obj.zScore(n));
} catch (MathException e) {
e.printStackTrace();
}
return lQuantile;
}
@Override
public void executeTest() {
int iRange1 =
(int) (Math.pow(1, iDecimalPlaces)) * (int) (this.fMaximumValue - this.fMinimumValue) + 1;
String sLocalOutput = null;
if (isHadoop) {
Job conf = null;
try {
conf = this.test();
} catch (Exception e) {
e.printStackTrace();
}
try {
sLocalOutput = UtilityHadoop.getFileFromHDFS(sOutput + File.separator + sFileName, conf);
} catch (IOException e) {
e.printStackTrace();
}
} else {
try {
this.testLinear();
} catch (IOException e) {
e.printStackTrace();
}
sLocalOutput = sOutput + File.separator + this.sFileName;
}
int numOfCombinations = UtilityMath.getCombinationAmount(iRange1, 1, true, true).intValue();
double[] dArrExpected = new double[numOfCombinations];
for (int i = 0; i < dArrExpected.length; i++) {
dArrExpected[i] = 1.0;
}
Evaluator evaluator = null;
if (sLocalOutput != null) {
evaluator =
new Evaluator(
sEvaluation, sLocalOutput, dArrExpected, dSignificance, iRange1, iDecimalPlaces);
}
boolean isPass = false;
if (evaluator != null) {
try {
isPass = evaluator.evaluate();
} catch (MathException e) {
e.printStackTrace();
} catch (ParameterNotValidException e) {
e.printStackTrace();
} catch (ArrayLengthNotEqualException e) {
e.printStackTrace();
}
}
System.out.println("Passed: " + isPass);
}
/**
* Generate a random value from this distribution.
*
* @param rng random number generator
* @return random value from this distribution
*/
public double generate(MersenneTwisterFast rng) {
try {
return gammaDist.inverseCumulativeProbability(rng.nextDouble());
} catch (MathException e) {
System.out.println(e.getMessage());
e.printStackTrace();
System.exit(-1);
}
return -1d;
}
/**
* Checks weather values of a target attribute are significantly different
*
* @return
*/
public boolean targetSignDifferent() {
boolean res = false;
int att = -1;
String att_name;
String att_name2;
ClusStatistic targetStat = m_StatManager.getStatistic(ClusAttrType.ATTR_USE_TARGET);
if (targetStat instanceof ClassificationStat) {
for (int i = 0; i < targetStat.getNbNominalAttributes(); i++) {
att_name = ((ClassificationStat) targetStat).getAttribute(i).getName();
for (int j = 0; j < m_ClassStat.getNbNominalAttributes(); j++) {
att_name2 = m_ClassStat.getAttribute(j).getName();
if (att_name.equals(att_name2)) {
att = j;
break;
}
}
if (SignDifferentNom(att)) {
res = true;
break; // TODO: If one target att significant, the whole rule significant!?
}
}
// System.out.println("Target sign. testing: " + res);
return res;
} else if (targetStat instanceof RegressionStat) {
for (int i = 0; i < targetStat.getNbNumericAttributes(); i++) {
att_name = ((RegressionStat) targetStat).getAttribute(i).getName();
for (int j = 0; j < m_RegStat.getNbNumericAttributes(); j++) {
att_name2 = m_RegStat.getAttribute(j).getName();
if (att_name.equals(att_name2)) {
att = j;
break;
}
}
try {
if (SignDifferentNum(att)) {
res = true;
break; // TODO: If one target att significant, the whole rule significant!?
}
} catch (IllegalArgumentException e) {
e.printStackTrace();
} catch (MathException e) {
e.printStackTrace();
}
}
return res;
} else {
// TODO: Classification and regression
return true;
}
}
private void calculateZValues(int n) {
zValues = new double[n];
NormalDistributionImpl normalDist = new NormalDistributionImpl(0, 1);
double x;
try {
x = 1 - Math.pow(0.5, 1.0 / n);
zValues[0] = normalDist.inverseCumulativeProbability(x);
for (int i = 2; i < n; i++) {
x = (i - 0.3175) / (n + 0.365);
zValues[i - 1] = normalDist.inverseCumulativeProbability(x);
}
x = Math.pow(0.5, 1.0 / n);
zValues[n - 1] = normalDist.inverseCumulativeProbability(x);
} catch (MathException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
/** Returns a number of attributes with significantly different distributions */
public int signDifferent() {
int sign_diff = 0;
// Nominal attributes
for (int i = 0; i < m_ClassStat.getNbAttributes(); i++) {
if (SignDifferentNom(i)) {
sign_diff++;
}
}
// Numeric attributes
for (int i = 0; i < m_RegStat.getNbAttributes(); i++) {
try {
if (SignDifferentNum(i)) {
sign_diff++;
}
} catch (IllegalArgumentException e) {
e.printStackTrace();
} catch (MathException e) {
e.printStackTrace();
}
}
System.out.println("Nb.sig.atts: " + sign_diff);
return sign_diff;
}