| 1 | /** |
| 2 | * |
| 3 | */ |
| 4 | package de.uka.ipd.sdq.probfunction.math.impl; |
| 5 | |
| 6 | import java.util.ArrayList; |
| 7 | import java.util.Arrays; |
| 8 | import java.util.Iterator; |
| 9 | import java.util.List; |
| 10 | |
| 11 | import de.uka.ipd.sdq.probfunction.math.IProbabilityDensityFunction; |
| 12 | import de.uka.ipd.sdq.probfunction.math.IRandomGenerator; |
| 13 | import de.uka.ipd.sdq.probfunction.math.ISamplePDF; |
| 14 | import de.uka.ipd.sdq.probfunction.math.IUnit; |
| 15 | import de.uka.ipd.sdq.probfunction.math.exception.DomainNotNumbersException; |
| 16 | import de.uka.ipd.sdq.probfunction.math.exception.FunctionNotInTimeDomainException; |
| 17 | import de.uka.ipd.sdq.probfunction.math.exception.FunctionsInDifferenDomainsException; |
| 18 | import de.uka.ipd.sdq.probfunction.math.exception.IncompatibleUnitsException; |
| 19 | import de.uka.ipd.sdq.probfunction.math.exception.InvalidSampleValueException; |
| 20 | import de.uka.ipd.sdq.probfunction.math.exception.NegativeDistanceException; |
| 21 | import de.uka.ipd.sdq.probfunction.math.exception.ProbabilityFunctionException; |
| 22 | import de.uka.ipd.sdq.probfunction.math.exception.ProbabilitySumNotOneException; |
| 23 | import de.uka.ipd.sdq.probfunction.math.exception.SizeTooSmallException; |
| 24 | import de.uka.ipd.sdq.probfunction.math.exception.UnitNameNotSetException; |
| 25 | import de.uka.ipd.sdq.probfunction.math.exception.UnitNotSetException; |
| 26 | import de.uka.ipd.sdq.probfunction.math.exception.UnknownPDFTypeException; |
| 27 | import de.uka.ipd.sdq.probfunction.math.exception.UnorderedDomainException; |
| 28 | import de.uka.ipd.sdq.probfunction.math.util.MathTools; |
| 29 | import flanagan.complex.Complex; |
| 30 | import flanagan.math.FourierTransform; |
| 31 | |
| 32 | /** |
| 33 | * @author Ihssane |
| 34 | * |
| 35 | */ |
| 36 | public class SamplePDFImpl extends ProbabilityDensityFunctionImpl |
| 37 | implements |
| 38 | ISamplePDF { |
| 39 | |
| 40 | private enum Operation { |
| 41 | ADD, SUB, MULT, DIV |
| 42 | } |
| 43 | |
| 44 | private static final Complex DEFAULT_FILL_VALUE = new Complex(0, 0); |
| 45 | |
| 46 | private static final int FOURIER_TRANSFORM = 0; |
| 47 | |
| 48 | private static final int INVERSE_FOURIER_TRANSFORM = 1; |
| 49 | |
| 50 | private double distance; |
| 51 | |
| 52 | private List<Complex> values; |
| 53 | |
| 54 | private Complex fillValue; |
| 55 | |
| 56 | private FourierTransform fft = new FourierTransform(); |
| 57 | |
| 58 | protected SamplePDFImpl(double distance, IUnit unit, |
| 59 | IRandomGenerator generator) { |
| 60 | this(distance, unit, false, generator); |
| 61 | } |
| 62 | |
| 63 | protected SamplePDFImpl(double distance, IUnit unit, |
| 64 | boolean isInFrequencyDomain, IRandomGenerator generator) { |
| 65 | super(unit, isInFrequencyDomain); |
| 66 | this.distance = distance; |
| 67 | values = new ArrayList<Complex>(); |
| 68 | fillValue = DEFAULT_FILL_VALUE; |
| 69 | randomGenerator = generator; |
| 70 | } |
| 71 | |
| 72 | public IProbabilityDensityFunction add(IProbabilityDensityFunction pdf) |
| 73 | throws UnknownPDFTypeException, |
| 74 | FunctionsInDifferenDomainsException, IncompatibleUnitsException { |
| 75 | return performOperation(Operation.ADD, this, pdf); |
| 76 | } |
| 77 | |
| 78 | public IProbabilityDensityFunction mult(IProbabilityDensityFunction pdf) |
| 79 | throws UnknownPDFTypeException, |
| 80 | FunctionsInDifferenDomainsException, IncompatibleUnitsException { |
| 81 | return performOperation(Operation.MULT, this, pdf); |
| 82 | } |
| 83 | |
| 84 | public IProbabilityDensityFunction div(IProbabilityDensityFunction pdf) |
| 85 | throws FunctionsInDifferenDomainsException, |
| 86 | UnknownPDFTypeException, IncompatibleUnitsException { |
| 87 | return performOperation(Operation.DIV, this, pdf); |
| 88 | } |
| 89 | |
| 90 | public IProbabilityDensityFunction sub(IProbabilityDensityFunction pdf) |
| 91 | throws FunctionsInDifferenDomainsException, |
| 92 | UnknownPDFTypeException, IncompatibleUnitsException { |
| 93 | return performOperation(Operation.SUB, this, pdf); |
| 94 | } |
| 95 | |
| 96 | public IProbabilityDensityFunction scale(double scalar) { |
| 97 | ArrayList<Complex> resultList = new ArrayList<Complex>(); |
| 98 | |
| 99 | for (Complex z : values) { |
| 100 | resultList.add(z.times(scalar)); |
| 101 | } |
| 102 | |
| 103 | return pfFactory.createSamplePDFFromComplex(distance, resultList, this |
| 104 | .isInFrequencyDomain(), pfFactory.createDefaultUnit()); |
| 105 | } |
| 106 | |
| 107 | public IProbabilityDensityFunction getFourierTransform() { |
| 108 | return transformFunction(FOURIER_TRANSFORM); |
| 109 | } |
| 110 | |
| 111 | public IProbabilityDensityFunction getInverseFourierTransform() { |
| 112 | return transformFunction(INVERSE_FOURIER_TRANSFORM); |
| 113 | } |
| 114 | |
| 115 | public void expand(int newSize) throws SizeTooSmallException { |
| 116 | int diff = newSize - values.size(); |
| 117 | |
| 118 | if (diff < 0) |
| 119 | throw new SizeTooSmallException(); |
| 120 | |
| 121 | for (int i = 0; i < diff; i++) { |
| 122 | values.add(new Complex(fillValue)); |
| 123 | } |
| 124 | } |
| 125 | |
| 126 | public double getDistance() { |
| 127 | return distance; |
| 128 | } |
| 129 | |
| 130 | public List<Double> getValuesAsDouble() { |
| 131 | return MathTools.transformComplexToDouble(values); |
| 132 | } |
| 133 | |
| 134 | public void setValuesAsDouble(List<Double> values) { |
| 135 | this.values = new ArrayList<Complex>(MathTools |
| 136 | .transformDoubleToComplex(values)); |
| 137 | } |
| 138 | |
| 139 | /** |
| 140 | * @return the fillValue |
| 141 | */ |
| 142 | public double getFillValueAsDouble() { |
| 143 | return fillValue.getReal(); |
| 144 | } |
| 145 | |
| 146 | /** |
| 147 | * @param fillValue |
| 148 | * the fillValue to set |
| 149 | */ |
| 150 | public void setFillValue(double fillValue) { |
| 151 | this.fillValue = new Complex(fillValue); |
| 152 | } |
| 153 | |
| 154 | public Complex getFillValue() { |
| 155 | return fillValue; |
| 156 | } |
| 157 | |
| 158 | public ISamplePDF getFunctionWithNewDistance(double distance) |
| 159 | throws NegativeDistanceException, FunctionNotInTimeDomainException { |
| 160 | List<Double> newList = getValuesForDistance(distance); |
| 161 | return pfFactory.createSamplePDFFromDouble(distance, newList, this |
| 162 | .getUnit()); |
| 163 | } |
| 164 | |
| 165 | public List<Complex> getValues() { |
| 166 | return new ArrayList<Complex>(values); |
| 167 | } |
| 168 | |
| 169 | public void setFillValue(Complex fillValue) { |
| 170 | this.fillValue = fillValue; |
| 171 | |
| 172 | } |
| 173 | |
| 174 | public void setValues(List<Complex> values, boolean isInFrequencyDomain) { |
| 175 | this.values = new ArrayList<Complex>(values); |
| 176 | this.setInFrequencyDomain(isInFrequencyDomain); |
| 177 | } |
| 178 | |
| 179 | public double getLowerDomainBorder() { |
| 180 | return 0; |
| 181 | } |
| 182 | |
| 183 | public double drawSample() { |
| 184 | double result = 0.0; |
| 185 | List<Double> intervals = MathTools |
| 186 | .computeCumulativeProbabilities(getValuesAsDouble()); |
| 187 | |
| 188 | double probability = randomGenerator.random(); |
| 189 | double lowerBoundProbability; |
| 190 | double upperBoundProbability; |
| 191 | double probabilityDistance; |
| 192 | double middleValue; |
| 193 | double scalingFactor; |
| 194 | for (int currentInterval = 0; currentInterval < intervals.size(); currentInterval++) { |
| 195 | upperBoundProbability = intervals.get(currentInterval); |
| 196 | if (probability < upperBoundProbability) { |
| 197 | middleValue = distance * currentInterval; |
| 198 | double lowerBoundValue = middleValue - (distance / 2); |
| 199 | // special case first interval (no negative values allowed) |
| 200 | if (currentInterval == 0) |
| 201 | lowerBoundProbability = 0.0; |
| 202 | else |
| 203 | lowerBoundProbability = intervals.get(currentInterval - 1); |
| 204 | probabilityDistance = upperBoundProbability |
| 205 | - lowerBoundProbability; |
| 206 | // sepcial case no values in interval. |
| 207 | if (probabilityDistance > 0) |
| 208 | scalingFactor = (probability - lowerBoundProbability) |
| 209 | / (probabilityDistance); |
| 210 | else |
| 211 | scalingFactor = 0.0; |
| 212 | result = lowerBoundValue + distance * scalingFactor; |
| 213 | break; |
| 214 | } |
| 215 | } |
| 216 | return result; |
| 217 | } |
| 218 | |
| 219 | public double getArithmeticMeanValue() throws DomainNotNumbersException, |
| 220 | FunctionNotInTimeDomainException { |
| 221 | if (!isInTimeDomain()) |
| 222 | throw new FunctionNotInTimeDomainException(); |
| 223 | double pos = 0; |
| 224 | double mean = 0; |
| 225 | for (Complex val : values) { |
| 226 | mean += pos * val.getReal(); |
| 227 | pos += distance; |
| 228 | } |
| 229 | return mean; |
| 230 | } |
| 231 | |
| 232 | public Object getMedian() throws UnorderedDomainException { |
| 233 | return getPercentile(50); |
| 234 | } |
| 235 | |
| 236 | public Object getPercentile(int p) throws IndexOutOfBoundsException, |
| 237 | UnorderedDomainException { |
| 238 | if (!hasOrderedDomain()) |
| 239 | throw new UnorderedDomainException(); |
| 240 | if (p < 0 || p > 100) |
| 241 | throw new IndexOutOfBoundsException(); |
| 242 | double prob = ((double)p) / 100.0; |
| 243 | double currProb = 0; |
| 244 | int i; |
| 245 | for(i=0; i < values.size() && currProb < prob; i++){ |
| 246 | currProb += values.get(i).getReal(); |
| 247 | } |
| 248 | return i*distance; |
| 249 | } |
| 250 | |
| 251 | public int numberOfSamples() { |
| 252 | return values.size(); |
| 253 | } |
| 254 | |
| 255 | @Override |
| 256 | public boolean equals(Object obj) { |
| 257 | boolean result = false; |
| 258 | if (obj instanceof ISamplePDF) { |
| 259 | ISamplePDF pdf = (ISamplePDF) obj; |
| 260 | if ((pdf.getDistance() == this.getDistance())) { |
| 261 | List<Complex> v1 = values; |
| 262 | List<Complex> v2 = pdf.getValues(); |
| 263 | if (v1.size() > v2.size()) { |
| 264 | List<Complex> tmp = v2; |
| 265 | v2 = v1; |
| 266 | v1 = tmp; |
| 267 | } |
| 268 | Iterator<Complex> iter = v2.iterator(); |
| 269 | result = true; |
| 270 | for (Complex z : v1) { |
| 271 | if (!MathTools.equalsComplex(iter.next(), z)) { |
| 272 | result = false; |
| 273 | break; |
| 274 | } |
| 275 | } |
| 276 | while (iter.hasNext() && result) { |
| 277 | if (!(MathTools.equalsComplex(iter.next(), |
| 278 | new Complex(0, 0)))) { |
| 279 | result = false; |
| 280 | } |
| 281 | } |
| 282 | } |
| 283 | } |
| 284 | return result; |
| 285 | } |
| 286 | |
| 287 | @Override |
| 288 | public int hashCode() { |
| 289 | // TODO Auto-generated method stub |
| 290 | return super.hashCode(); |
| 291 | } |
| 292 | |
| 293 | @Override |
| 294 | public String toString() { |
| 295 | String result = "unit = " + getUnit().getUnitName() + "; "; |
| 296 | result += "distance = " + getDistance() + "; "; |
| 297 | result += "samples: "; |
| 298 | boolean isFirst = true; |
| 299 | for (Complex z : values) { |
| 300 | if (isFirst) { |
| 301 | isFirst = false; |
| 302 | } else { |
| 303 | result += ", "; |
| 304 | } |
| 305 | result += "(" + MathTools.asString(z.getReal()) + ", " |
| 306 | + MathTools.asString(z.getImag()) + ")"; |
| 307 | } |
| 308 | return result; |
| 309 | } |
| 310 | |
| 311 | private List<Double> getValuesForDistance(double newDistance) |
| 312 | throws NegativeDistanceException, FunctionNotInTimeDomainException { |
| 313 | // same distance |
| 314 | if (MathTools.equalsDouble(distance, newDistance)) |
| 315 | return getValuesAsDouble(); |
| 316 | |
| 317 | // check preconditions |
| 318 | if ((distance < 0) || (newDistance < 0)) |
| 319 | throw new NegativeDistanceException(); |
| 320 | |
| 321 | if (!isInTimeDomain()) |
| 322 | throw new FunctionNotInTimeDomainException(); |
| 323 | |
| 324 | // begin implementation |
| 325 | double oldPoint = distance / 2; |
| 326 | double newPoint = newDistance / 2; |
| 327 | int currentIndex = 0; |
| 328 | double buffer = 0.0; |
| 329 | |
| 330 | List<Double> newValues = new ArrayList<Double>(); |
| 331 | |
| 332 | if (MathTools.equalsDouble(newDistance, distance)) { |
| 333 | newValues = getValuesAsDouble(); |
| 334 | } else if (newDistance < distance) { |
| 335 | while (currentIndex < values.size()) { |
| 336 | if (newPoint < oldPoint) { |
| 337 | if (newPoint == newDistance / 2) |
| 338 | newValues |
| 339 | .add(getProb(currentIndex, newPoint, oldPoint)); |
| 340 | else |
| 341 | newValues.add(getProb(currentIndex, newDistance, |
| 342 | distance)); |
| 343 | |
| 344 | } else { |
| 345 | if (oldPoint == distance / 2) { |
| 346 | newValues.add(getLeftProb(oldPoint, currentIndex, |
| 347 | newPoint, newDistance, oldPoint) |
| 348 | + getRightProb(oldPoint, currentIndex + 1, |
| 349 | newPoint)); |
| 350 | } else |
| 351 | newValues.add(getLeftProb(oldPoint, currentIndex, |
| 352 | newPoint, newDistance, distance) |
| 353 | + getRightProb(oldPoint, currentIndex + 1, |
| 354 | newPoint)); |
| 355 | oldPoint += distance; |
| 356 | currentIndex++; |
| 357 | } |
| 358 | newPoint += newDistance; |
| 359 | } |
| 360 | } else if (newDistance > distance) { |
| 361 | while (currentIndex < values.size()) { |
| 362 | if (oldPoint < newPoint) { |
| 363 | buffer += values.get(currentIndex).getReal(); |
| 364 | |
| 365 | } else { |
| 366 | newValues.add(buffer |
| 367 | + getLeftProb(newPoint, currentIndex, oldPoint, |
| 368 | distance, distance)); |
| 369 | buffer = getRightProb(newPoint, currentIndex, oldPoint); |
| 370 | newPoint += newDistance; |
| 371 | } |
| 372 | oldPoint += distance; |
| 373 | currentIndex++; |
| 374 | } |
| 375 | if (buffer != 0) |
| 376 | newValues.add(buffer); |
| 377 | } |
| 378 | return newValues; |
| 379 | } |
| 380 | |
| 381 | private double getProb(int index, double newDistance, double distance) { |
| 382 | return (newDistance / distance) * values.get(index).getReal(); |
| 383 | } |
| 384 | |
| 385 | private double getLeftProb(double oldP, int index, double newP, double diff, double distance) { |
| 386 | double fractal = (diff - (newP - oldP)) / distance; |
| 387 | return values.get(index).getReal() * fractal; |
| 388 | } |
| 389 | |
| 390 | private double getRightProb(double oldP, int index, double newP) { |
| 391 | double fractal = (newP - oldP) / distance; |
| 392 | if (index < values.size()) |
| 393 | return values.get(index).getReal() * fractal; |
| 394 | else |
| 395 | return 0; |
| 396 | } |
| 397 | |
| 398 | private static IProbabilityDensityFunction performOperation(Operation op, |
| 399 | IProbabilityDensityFunction pdf1, IProbabilityDensityFunction pdf2) |
| 400 | throws FunctionsInDifferenDomainsException, |
| 401 | UnknownPDFTypeException, IncompatibleUnitsException { |
| 402 | |
| 403 | List<ISamplePDF> operands = prepareForComputation(pdf1, pdf2); |
| 404 | |
| 405 | ISamplePDF sPDF1 = operands.get(0); |
| 406 | ISamplePDF sPDF2 = operands.get(1); |
| 407 | ArrayList<Complex> resultList = new ArrayList<Complex>(); |
| 408 | double distance = sPDF1.getDistance(); |
| 409 | boolean inFrequencyDomain = sPDF1.isInFrequencyDomain(); |
| 410 | |
| 411 | Iterator<Complex> iterator = sPDF2.getValues().iterator(); |
| 412 | for (Complex z1 : sPDF1.getValues()) { |
| 413 | Complex z2 = iterator.next(); |
| 414 | Complex result; |
| 415 | switch (op) { |
| 416 | case ADD : |
| 417 | result = z1.plus(z2); |
| 418 | break; |
| 419 | case SUB : |
| 420 | result = z1.minus(z2); |
| 421 | break; |
| 422 | case MULT : |
| 423 | result = z1.times(z2); |
| 424 | break; |
| 425 | case DIV : |
| 426 | result = z1.over(z2); |
| 427 | break; |
| 428 | default : |
| 429 | result = null; |
| 430 | break; |
| 431 | } |
| 432 | resultList.add(result); |
| 433 | } |
| 434 | IProbabilityDensityFunction p = pfFactory.createSamplePDFFromComplex( |
| 435 | distance, resultList, inFrequencyDomain, sPDF1.getUnit()); |
| 436 | return p; |
| 437 | } |
| 438 | |
| 439 | private static List<ISamplePDF> prepareForComputation( |
| 440 | IProbabilityDensityFunction pdf1, IProbabilityDensityFunction pdf2) |
| 441 | throws FunctionsInDifferenDomainsException, |
| 442 | UnknownPDFTypeException, IncompatibleUnitsException { |
| 443 | // check preconditions |
| 444 | if (pdf1.isInTimeDomain() != pdf2.isInTimeDomain()) |
| 445 | throw new FunctionsInDifferenDomainsException(); |
| 446 | |
| 447 | if (pdf1.getUnit() != null && !pdf1.getUnit().equals(pdf2.getUnit())) |
| 448 | throw new IncompatibleUnitsException(); |
| 449 | |
| 450 | // ensure that we only have SamplePDFs with equal distances and the same |
| 451 | // number of samples |
| 452 | ISamplePDF sPDF1 = pfFactory.transformToSamplePDF(pdf1); |
| 453 | ISamplePDF sPDF2 = pfFactory.transformToSamplePDF(pdf2); |
| 454 | |
| 455 | List<ISamplePDF> operands; |
| 456 | operands = createFunctionsWithEqualDistance(sPDF1, sPDF2); |
| 457 | sPDF1 = operands.get(0); |
| 458 | sPDF2 = operands.get(1); |
| 459 | |
| 460 | try { |
| 461 | int maxSize = Math.max(sPDF1.numberOfSamples(), sPDF2 |
| 462 | .numberOfSamples()); |
| 463 | sPDF1.expand(maxSize); |
| 464 | sPDF2.expand(maxSize); |
| 465 | } catch (SizeTooSmallException e) { |
| 466 | // should never happen... |
| 467 | e.printStackTrace(); |
| 468 | throw new RuntimeException(e); |
| 469 | } |
| 470 | return operands; |
| 471 | } |
| 472 | |
| 473 | private IProbabilityDensityFunction transformFunction(int flag) { |
| 474 | Complex[] cValues = new Complex[values.size()]; |
| 475 | values.toArray(cValues); |
| 476 | fft.setData(cValues); |
| 477 | |
| 478 | if (flag == FOURIER_TRANSFORM) |
| 479 | fft.transform(); |
| 480 | else |
| 481 | fft.inverse(); |
| 482 | |
| 483 | List<Complex> resultList = Arrays.asList(fft |
| 484 | .getTransformedDataAsComplex()); |
| 485 | |
| 486 | ISamplePDF spdf = pfFactory.createSamplePDFFromComplex(distance, |
| 487 | resultList, !this.isInFrequencyDomain(), pfFactory |
| 488 | .createDefaultUnit()); |
| 489 | return spdf; |
| 490 | } |
| 491 | |
| 492 | /** |
| 493 | * Creates two functions with an equal distance, if both functions are in |
| 494 | * the time domain. Precondition: Functions are in the same domain. |
| 495 | * |
| 496 | * @param pdf1 |
| 497 | * @param pdf2 |
| 498 | * @return |
| 499 | * @throws FunctionNotInTimeDomainException |
| 500 | * @throws NegativeDistanceException |
| 501 | * @throws FunctionNotInTimeDomainException |
| 502 | * Thrown if one of the input pdfs is not in the time domain. |
| 503 | */ |
| 504 | protected static List<ISamplePDF> createFunctionsWithEqualDistance( |
| 505 | ISamplePDF pdf1, ISamplePDF pdf2) { |
| 506 | |
| 507 | ArrayList<ISamplePDF> resultList = new ArrayList<ISamplePDF>(); |
| 508 | |
| 509 | try { |
| 510 | if (!MathTools.equalsDouble(pdf1.getDistance(), pdf2.getDistance())) { |
| 511 | boolean inTimeDomain = pdf1.isInTimeDomain(); |
| 512 | |
| 513 | if (!inTimeDomain) { |
| 514 | pdf1 = (ISamplePDF) pdf1.getInverseFourierTransform(); |
| 515 | pdf2 = (ISamplePDF) pdf2.getInverseFourierTransform(); |
| 516 | } |
| 517 | |
| 518 | double distance = MathTools.gcd(pdf1.getDistance(), pdf2 |
| 519 | .getDistance()); |
| 520 | |
| 521 | pdf1 = pdf1.getFunctionWithNewDistance(distance); |
| 522 | pdf2 = pdf2.getFunctionWithNewDistance(distance); |
| 523 | |
| 524 | if (!inTimeDomain) { |
| 525 | pdf1 = (ISamplePDF) pdf1.getFourierTransform(); |
| 526 | pdf2 = (ISamplePDF) pdf2.getFourierTransform(); |
| 527 | } |
| 528 | |
| 529 | } |
| 530 | |
| 531 | resultList.add(pdf1); |
| 532 | resultList.add(pdf2); |
| 533 | } catch (ProbabilityFunctionException e) { |
| 534 | // should never happen |
| 535 | e.printStackTrace(); |
| 536 | throw new RuntimeException(e); |
| 537 | } |
| 538 | return resultList; |
| 539 | } |
| 540 | |
| 541 | public double getProbabilitySum() throws FunctionNotInTimeDomainException { |
| 542 | if (!isInTimeDomain()) |
| 543 | throw new FunctionNotInTimeDomainException(); |
| 544 | double sum = 0; |
| 545 | for (Complex value : values) { |
| 546 | sum += value.getReal(); |
| 547 | } |
| 548 | return sum; |
| 549 | } |
| 550 | |
| 551 | public void checkConstrains() throws NegativeDistanceException, |
| 552 | ProbabilitySumNotOneException, FunctionNotInTimeDomainException, |
| 553 | UnitNotSetException, UnitNameNotSetException, |
| 554 | InvalidSampleValueException { |
| 555 | if (distance <= 0.0) |
| 556 | throw new NegativeDistanceException(); |
| 557 | if (getUnit() == null) |
| 558 | throw new UnitNotSetException(); |
| 559 | if (getUnit().getUnitName() == null) |
| 560 | throw new UnitNameNotSetException(); |
| 561 | try { |
| 562 | if (!MathTools.equalsDouble(getProbabilitySum(), 1.0)) |
| 563 | throw new ProbabilitySumNotOneException(); |
| 564 | for (double p : getValuesAsDouble()) |
| 565 | if (!(p >= 0.0 - MathTools.EPSILON_ERROR && p <= 1.0 + MathTools.EPSILON_ERROR)) |
| 566 | throw new InvalidSampleValueException(); |
| 567 | } catch (FunctionNotInTimeDomainException e) { |
| 568 | throw e; |
| 569 | } |
| 570 | |
| 571 | } |
| 572 | |
| 573 | public IProbabilityDensityFunction getCumulativeFunction() |
| 574 | throws FunctionNotInTimeDomainException { |
| 575 | |
| 576 | if (!isInTimeDomain()) |
| 577 | throw new FunctionNotInTimeDomainException(); |
| 578 | |
| 579 | List<Double> cumulativeProbabilities = MathTools |
| 580 | .computeCumulativeProbabilities(getValuesAsDouble()); |
| 581 | ISamplePDF spdf = pfFactory.createSamplePDFFromDouble(distance, |
| 582 | cumulativeProbabilities, isInFrequencyDomain(), this.getUnit(), |
| 583 | this.getRandomGenerator()); |
| 584 | spdf.setFillValue(new Complex(1.0, 0.0)); |
| 585 | return spdf; |
| 586 | } |
| 587 | |
| 588 | public double probabilisticEquals(IProbabilityDensityFunction pdf) |
| 589 | throws ProbabilityFunctionException { |
| 590 | return compareTo(pdf, CompareOperation.EQUALS); |
| 591 | } |
| 592 | |
| 593 | public double greaterThan(IProbabilityDensityFunction pdf) |
| 594 | throws ProbabilityFunctionException { |
| 595 | return compareTo(pdf, CompareOperation.GREATER); |
| 596 | } |
| 597 | |
| 598 | public double lessThan(IProbabilityDensityFunction pdf) |
| 599 | throws ProbabilityFunctionException { |
| 600 | return compareTo(pdf, CompareOperation.LESS); |
| 601 | } |
| 602 | |
| 603 | private double compareTo(IProbabilityDensityFunction pdf, |
| 604 | CompareOperation op) throws ProbabilityFunctionException { |
| 605 | ISamplePDF sPDF = pfFactory.transformToSamplePDF(pdf); |
| 606 | sPDF = sPDF.getFunctionWithNewDistance(this.distance); |
| 607 | int maxSize = Math |
| 608 | .max(sPDF.getValues().size(), this.getValues().size()); |
| 609 | sPDF.expand(maxSize); |
| 610 | this.expand(maxSize); |
| 611 | List<Double> pdfValues = sPDF.getValuesAsDouble(); |
| 612 | List<Double> thisValues = this.getValuesAsDouble(); |
| 613 | |
| 614 | switch (op) { |
| 615 | case EQUALS : |
| 616 | return equals(thisValues, pdfValues); |
| 617 | case GREATER : |
| 618 | return greaterThan(thisValues, pdfValues); |
| 619 | case LESS : |
| 620 | return greaterThan(pdfValues, thisValues); |
| 621 | default : |
| 622 | return 0; |
| 623 | } |
| 624 | } |
| 625 | |
| 626 | private double greaterThan(List<Double> firstValues, |
| 627 | List<Double> secondValues) { |
| 628 | assert (firstValues.size() == secondValues.size()); |
| 629 | double prob = 0; |
| 630 | for (int i = 0; i < secondValues.size(); i++) { |
| 631 | double tempProb = greaterThan(secondValues, i); |
| 632 | prob += tempProb * secondValues.get(i); |
| 633 | } |
| 634 | return prob; |
| 635 | } |
| 636 | |
| 637 | private double greaterThan(List<Double> secondValues, int i) { |
| 638 | double prob = 0; |
| 639 | for (int j = i + 1; j < secondValues.size(); j++) { |
| 640 | prob += secondValues.get(j); |
| 641 | } |
| 642 | return prob; |
| 643 | } |
| 644 | |
| 645 | private double equals(List<Double> firstValues, List<Double> secondValues) { |
| 646 | double prob = 0; |
| 647 | for (int i = 0; i < firstValues.size(); i++) { |
| 648 | prob += firstValues.get(i) * secondValues.get(i); |
| 649 | } |
| 650 | return prob; |
| 651 | } |
| 652 | |
| 653 | public IProbabilityDensityFunction stretchDomain(double scalar) { |
| 654 | SamplePDFImpl sPDF = new SamplePDFImpl(this.getDistance() * scalar, |
| 655 | this.getUnit(), this.randomGenerator); |
| 656 | sPDF.setValues(this.getValues(), this.isInFrequencyDomain()); |
| 657 | sPDF.setFillValue(this.getFillValue()); |
| 658 | return sPDF; |
| 659 | } |
| 660 | |
| 661 | public IProbabilityDensityFunction shiftDomain(double scalar) |
| 662 | throws DomainNotNumbersException { |
| 663 | throw new UnsupportedOperationException(); |
| 664 | // SamplePDFImpl sPDF = new SamplePDFImpl(this.getDistance(), |
| 665 | // this.getUnit(), this.randomGenerator); |
| 666 | // List<Complex> sampleList = this.getValues(); |
| 667 | // sampleList.add(0, new Complex(0,0)); |
| 668 | } |
| 669 | |
| 670 | public Complex getValue(int pos) { |
| 671 | return pos < values.size() ? values.get(pos) : fillValue; |
| 672 | } |
| 673 | |
| 674 | public Double getValueAsDouble(int pos) { |
| 675 | return getValue(pos).getReal(); |
| 676 | } |
| 677 | } |