// TODO: different sorting methods, e.g. "widest SSIs"
sclass G22DataWrangler > Stages is IHasChangeListeners {
  event change;
  
  settable BufferedImage inputImage;
  
  settable bool withDiagonals = true;
  settableWithVar int blur = 1; // in pixels
  
  // kilobytes per compressed image (pessimistic estimate
  // counting 2 bytes for each int)
  settable TargetAndActual<Double> kilobytes = new(250.0);
  settable new TargetAndActual<Double> coveredPixelsPercentage;
  settable new TargetAndActual<Double> detailLevel;
  
  settable bool vectorize = true;
  settable bool allowPartialSSIs = true;
  
  settable SortMode sortMode = SortMode.compressibility;
  
  enum SortMode { compressibility, pixels }
  
  settable IPosterizer posterizer = new SinglePixelPosterizer(4);
  
  BufferedImage blurredImage;
  int maxLines, maxInts;
  L<? extends AbstractSSI> currentSSIs; // ssis at current stage
  L<SSI> initialSSIs;
  AbstractSSIList sortedSSIs, cutSSIs,
    vectorizedSSIs, cutVectorizedSSIs;
  CutListToBudget<AbstractSSI> cutter;
  
  // We store the posterized image as Hi15
  Hi15Image posterizedImage;
  
  FastRegions_Hi15Image regionMaker;
  L<IImageRegion<Hi15Image>> regions;
  
  selfType kb(TargetAndActual<Double> kb) { ret kilobytes(kb); }
  TargetAndActual<Double> kb() { ret kilobytes; }
  
  WidthAndHeight resolution() {
    ret imageSize(inputImage);
  }

  double detailDivisor() {
    ret areaRoot(inputImage);
  }
  
  // choose number of colors for posterized image
  selfType colors(int colors) {
    int perChannel = iceil(cbrt(colors));
    posterizer = new SinglePixelPosterizer(perChannel);
    this;
  }

  stage "Blur" {
    blurredImage = blurBufferedImage(blur, inputImage);
  }
  
  stage "Posterize" {
    posterizedImage = new Hi15Image(posterizeBufferedImage(blurredImage, posterizer));
  }
  
  stage "Regions" {
    regionMaker = new FastRegions_Hi15Image(posterizedImage);
    regionMaker.withDiagonals(withDiagonals);
    regions = regionMaker!;
  }
  
  stage "SSIs" {
    initialSSIs = new L;
    for (region : regions)
      initialSSIs.addAll(new G22_RegionToSSIs_v2(region).withDiagonals (withDiagonals)!);
    currentSSIs = initialSSIs;
  }
  
  int initialSSILines() {
    ret totalSSILines(initialSSIs);
  }
  
  stage "Vector-Optimize" {
    currentSSIs = vectorizedSSIs = vectorize
      ? new VectorOptimizedSSIList(currentSSIs)
      : new GeneralSSIList(currentSSIs);
  }
  
  stage "Sort SSIs" {
    if (sortMode == SortMode.compressibility)
      sortedSSIs = sortedDesc(currentSSIs, (a, b) -> {
        int x = cmp(a.compressibility(), b.compressibility());
        if (x != 0) ret x;
        ret cmp(a.numberOfPixels(), b.numberOfPixels());
      });
    else if (sortMode == SortMode.pixels)
      sortedSSIs = biggestSSIsFirst(currentSSIs);
    else
      fail("Unknown sort mode");
    currentSSIs = sortedSSIs;
  }
  
  stage "Cut SSI List by detail level" {
    maxLines = !detailLevel.hasTarget() ? Int.MAX_VALUE
      : iround(detailDivisor()*detailLevel.target());
    currentSSIs = cutSSIs = takeFirstNSSILines(maxLines, currentSSIs);
    detailLevel.set(l(cutSSIs)/detailDivisor());
  }
  
  stage "Cut Vector-Optimized SSIs by file size" {
    maxInts = !kilobytes.hasTarget() ? Int.MAX_VALUE
      : iround(kilobytes.target()*512); // assuming 16 bit ints
    cutter = new CutListToBudget<AbstractSSI>(ssi -> (double) ssi.sizeInInts(), maxInts, currentSSIs);
    
    if (allowPartialSSIs)
      cutter.allowPartial((ssi, budget) -> ssi.reduceToInts(iround(budget)));
      
    currentSSIs = cutVectorizedSSIs = new GeneralSSIList(cutter!);
    kilobytes.set(totalSizeInInts(cutVectorizedSSIs)/512.0);
  }
}