/**
* Get the logged image value.
*
* @param bean
* @return a dataset that can be absolute, if complex, and also be logged according to bean
* Package private for testing
*/
/* package */ Dataset getImageLoggedDataCalc(ImageServiceBean bean) {
Dataset ret = DatasetUtils.convertToDataset(bean.getImage());
if (ret.isComplex()) {
ret = Maths.abs(ret);
}
if (bean.isLogColorScale()) {
double offset = bean.getLogOffset();
if (!Double.isNaN(offset) && !Double.isInfinite(offset)) {
ret = Maths.subtract(ret, offset);
}
ret = Maths.log10(ret);
}
return ret;
}
/**
* getImageData(...) provides an image in a given palette data and origin. Faster than getting a
* resolved image
*
* <p>This method should be thread safe.
*/
public ImageData getImageData(ImageServiceBean bean) {
ImageOrigin origin = bean.getOrigin();
if (origin == null) origin = ImageOrigin.TOP_LEFT;
// orientate the image
Dataset oImage =
DatasetUtils.rotate90(DatasetUtils.convertToDataset(bean.getImage()), origin.ordinal());
Dataset image = oImage;
if (image instanceof RGBDataset) {
return SWTImageUtils.createImageData(
(RGBDataset) image, 0, 255, null, null, null, false, false, false);
}
createMaxMin(bean);
double max = getMax(bean);
double min = getMin(bean);
double maxCut = getMaxCut(bean);
double minCut = getMinCut(bean);
// now deal with the log if needed
if (bean.isLogColorScale()) {
image = DatasetUtils.rotate90(getImageLoggedData(bean), origin.ordinal());
max = Math.log10(max);
// note createMaxMin() -> getFastStatistics() -> getImageLogged() which ensures min >= 0
min = Math.log10(min);
maxCut = Math.log10(maxCut);
// no guarantees for minCut though
minCut = minCut <= 0 ? Double.NEGATIVE_INFINITY : Math.log10(minCut);
}
if (oImage.isComplex()) { // handle complex datasets by creating RGB dataset
Dataset hue = Maths.angle(oImage, true);
Dataset value = DatasetUtils.rotate90(getImageLoggedData(bean), origin.ordinal());
double maxmax = Math.max(Math.abs(max), Math.abs(min));
if (max - min > Math.ulp(maxmax)) {
value.isubtract(min);
value.imultiply(1. / (max - min));
} else {
value.imultiply(1. / maxmax);
}
image = RGBDataset.createFromHSV(hue, null, value);
return SWTImageUtils.createImageData(image, 0, 255, null, null, null, false, false, false);
}
if (bean.getFunctionObject() != null && bean.getFunctionObject() instanceof FunctionContainer) {
final FunctionContainer fc = (FunctionContainer) bean.getFunctionObject();
// TODO This does not support masking or cut bounds for zingers and dead pixels.
return SWTImageUtils.createImageData(
image,
min,
max,
fc.getRedFunc(),
fc.getGreenFunc(),
fc.getBlueFunc(),
fc.isInverseRed(),
fc.isInverseGreen(),
fc.isInverseBlue());
}
return SWTImageUtils.createImageData(min, max, minCut, maxCut, image, bean);
}
/**
* Fast statistics as a rough guide - this is faster than Dataset.getMin() and getMax() which may
* cache but slows the opening of images too much. The return array[2] was added in "Updated for
* Diffraction Tool." commit, but no trace of such usage. However it should not be removed,
* because it is useful as return array[3].
*
* @param bean
* @return [0] = min [1] = max(=mean*constant) [2] = mean [3] max
*/
public double[] getFastStatistics(ImageServiceBean bean) {
Dataset image = getImageLoggedData(bean);
if (bean.getHistogramType() == HistoType.OUTLIER_VALUES && !bean.isLogColorScale()) {
double[] ret = null;
try {
double[] stats = Stats.outlierValues(image, bean.getLo(), bean.getHi(), -1);
ret = new double[] {stats[0], stats[1], -1};
} catch (IllegalArgumentException iae) {
bean.setLo(10);
bean.setHi(90);
double[] stats = Stats.outlierValues(image, bean.getLo(), bean.getHi(), -1);
ret = new double[] {stats[0], stats[1], -1};
}
if (bean.isLogColorScale() && ret != null) {
ret = new double[] {Math.pow(10, ret[0]), Math.pow(10, ret[1]), -1};
}
return ret;
}
double min = Double.MAX_VALUE;
double max = -Double.MAX_VALUE;
double sum = 0.0;
int size = 0;
BooleanDataset mask =
bean.getMask() != null
? (BooleanDataset) DatasetUtils.cast(bean.getMask(), Dataset.BOOL)
: null;
// Big loop warning:
final IndexIterator it = image.getIterator();
final IndexIterator mit = mask == null ? null : mask.getIterator();
while (it.hasNext()) {
final double val = image.getElementDoubleAbs(it.index);
if (mit != null && mit.hasNext()) {
if (!mask.getElementBooleanAbs(mit.index)) {
continue; // Masked!
}
}
if (Double.isNaN(val)) continue;
if (!bean.isInBounds(val)) continue;
sum += val;
if (val < min) min = val;
if (val > max) max = val;
size++;
}
double retMax = Double.NaN;
double retExtra = Double.NaN;
if (bean.getHistogramType() == HistoType.MEDIAN) {
double median = Double.NaN;
try {
median = ((Number) Stats.median(image)).doubleValue(); // SLOW
} catch (Exception ne) {
median = ((Number) Stats.median(image.cast(Dataset.INT16))).doubleValue(); // SLOWER
}
retMax = 2 * median;
retExtra = median;
} else { // Use mean based histo
double mean = sum / size;
retMax = (Math.E) * mean; // Not statistical, E seems to be better than 3...
retExtra = mean;
}
if (retMax > max) retMax = max;
if (bean.isLogColorScale()) {
return new double[] {Math.pow(10, min), Math.pow(10, retMax), Math.pow(10, retExtra)};
}
return new double[] {min, retMax, retExtra, max};
}