/**
* Constructs an image information class based on the 5D image source, and the individual set of
* pixels desired in that image. Needs Factory to query the database about statistics. (this might
* not be a good thing)
*
* @param imageSource The image to store information about.
* @param pixels The pixel source of the image.
* @param dataSource The factory used to access the OME database. Is there a better way to do
* this?
*/
public ImageInformation(Image imageSource, ImagePixels pixels, Factory dataSource) {
this.imageSource = imageSource;
this.pixels = pixels;
this.pixelsAttribute = pixels.getPixelsAttribute();
this.dataSource = dataSource;
Map imageSourceMap = new HashMap();
imageSourceMap.put("target", imageSource);
// extract the channel/wavelength information for this image.
List channelComponents = dataSource.findAttributes("PixelChannelComponent", imageSourceMap);
final int pixelsID = pixelsAttribute.getID();
// this taken straight out of the SVG viewer code
// might be a faster/better/less OME-call-intensive way to do it
channelComponents =
Filter.grep(
channelComponents,
new GrepOperator() {
public boolean eval(Object o) {
Attribute attribute = (Attribute) o;
Attribute pixels = attribute.getAttributeElement("Pixels");
return pixels.getID() == pixelsID;
}
});
channelInfo = new Wavelength[channelComponents.size()];
for (int i = 0; i < channelComponents.size(); i++) {
Attribute channel = (Attribute) channelComponents.get(i);
channelInfo[i] = new Wavelength(channel.getIntElement("Index"));
}
CBS = ChannelBlackScaleData.getDefaultChannelScale(channelInfo);
cbsMap = new HashMap();
// hopefully this doesn't break right here
// extract the proper stack statistics for this image,
// this might be done the hard way (I dunno)
Map moduleConstraints = new HashMap();
moduleConstraints.put("name", "Fast Stack statistics");
Module stackModule = (Module) dataSource.findObject("OME::Module", moduleConstraints);
Map formalInputConstraints = new HashMap();
formalInputConstraints.put("module_id", new Integer(stackModule.getID()));
formalInputConstraints.put("name", "Pixels");
Module.FormalInput formalInput =
(Module.FormalInput)
dataSource.findObject("OME::Module::FormalInput", formalInputConstraints);
RemoteModuleExecution moduleExecution =
(RemoteModuleExecution) pixelsAttribute.getModuleExecution();
Map actualInputConstraints = new HashMap();
actualInputConstraints.put("formal_input_id", new Integer(formalInput.getID()));
actualInputConstraints.put("input_module_execution_id", new Integer(moduleExecution.getID()));
ModuleExecution.ActualInput actualInput =
(ModuleExecution.ActualInput)
dataSource.findObject("OME::ModuleExecution::ActualInput", actualInputConstraints);
final int stackAnalysisID = actualInput.getModuleExecution().getID();
// retrieve statistics
List stackMins = dataSource.findAttributes("StackMinimum", imageSourceMap);
List stackMaxes = dataSource.findAttributes("StackMaximum", imageSourceMap);
List stackMeans = dataSource.findAttributes("StackMean", imageSourceMap);
List stackSigmas = dataSource.findAttributes("StackSigma", imageSourceMap);
List stackGeomeans = dataSource.findAttributes("StackGeometricMean", imageSourceMap);
List stackGeosigmas = dataSource.findAttributes("StackGeometricSigma", imageSourceMap);
GrepOperator stackIDOperator =
new GrepOperator() {
public boolean eval(Object o) {
Attribute attribute = (Attribute) o;
RemoteModuleExecution execution =
(RemoteModuleExecution) attribute.getModuleExecution();
if (execution.getID() == stackAnalysisID) {
return true;
} else return false;
}
};
List usableMins = Filter.grep(stackMins, stackIDOperator);
List usableMaxes = Filter.grep(stackMaxes, stackIDOperator);
List usableMeans = Filter.grep(stackMeans, stackIDOperator);
List usableSigmas = Filter.grep(stackSigmas, stackIDOperator);
List usableGeomeans = Filter.grep(stackGeomeans, stackIDOperator);
List usableGeosigmas = Filter.grep(stackGeosigmas, stackIDOperator);
sizeX = pixelsAttribute.getIntElement("SizeX");
sizeY = pixelsAttribute.getIntElement("SizeY");
sizeZ = pixelsAttribute.getIntElement("SizeZ");
sizeC = pixelsAttribute.getIntElement("SizeC");
sizeT = pixelsAttribute.getIntElement("SizeT");
bitsPerPixel = pixelsAttribute.getIntElement("BitsPerPixel");
stackStats = new StackStatistics[sizeC][sizeT];
// initialize array
for (int i = 0; i < sizeC; i++) {
for (int j = 0; j < sizeT; j++) {
stackStats[i][j] = new StackStatistics();
}
}
// populate internal data structures
for (Iterator iter = usableMins.iterator(); iter.hasNext(); ) {
Attribute stackMin = (Attribute) iter.next();
int theC = stackMin.getIntElement("TheC");
int theT = stackMin.getIntElement("TheT");
stackStats[theC][theT].setMin(stackMin.getIntElement("Minimum"));
}
for (Iterator iter = usableMaxes.iterator(); iter.hasNext(); ) {
Attribute stackMax = (Attribute) iter.next();
int theC = stackMax.getIntElement("TheC");
int theT = stackMax.getIntElement("TheT");
stackStats[theC][theT].setMax(stackMax.getIntElement("Maximum"));
}
for (Iterator iter = usableMeans.iterator(); iter.hasNext(); ) {
Attribute stackMean = (Attribute) iter.next();
int theC = stackMean.getIntElement("TheC");
int theT = stackMean.getIntElement("TheT");
stackStats[theC][theT].setMean(stackMean.getFloatElement("Mean"));
}
for (Iterator iter = usableSigmas.iterator(); iter.hasNext(); ) {
Attribute stackSigma = (Attribute) iter.next();
int theC = stackSigma.getIntElement("TheC");
int theT = stackSigma.getIntElement("TheT");
stackStats[theC][theT].setSigma(stackSigma.getFloatElement("Sigma"));
}
for (Iterator iter = usableGeomeans.iterator(); iter.hasNext(); ) {
Attribute stackMean = (Attribute) iter.next();
int theC = stackMean.getIntElement("TheC");
int theT = stackMean.getIntElement("TheT");
stackStats[theC][theT].setGeoMean(stackMean.getFloatElement("GeometricMean"));
}
for (Iterator iter = usableGeosigmas.iterator(); iter.hasNext(); ) {
Attribute stackSigma = (Attribute) iter.next();
int theC = stackSigma.getIntElement("TheC");
int theT = stackSigma.getIntElement("TheT");
stackStats[theC][theT].setGeoSigma(stackSigma.getFloatElement("GeometricSigma"));
}
}
// analogous to getConvertedWBS4OME_JPEG in OMEimage.js
// and boundary conditions modifier in updatePic in OMEimage.js
public ChannelBlackScaleData getNormalizedScale(int t) {
if (t < 0 || t >= getDimT()) {
return null;
}
Integer tObj = new Integer(t);
if (cbsMap.containsKey(tObj)) {
return (ChannelBlackScaleData) cbsMap.get(tObj);
}
ChannelBlackScaleData convertedData = new ChannelBlackScaleData();
ChannelBlackScaleData.CBSChunk[] dataChunks = {
CBS.getCBSChunk(ChannelBlackScaleData.RED_CHUNK),
CBS.getCBSChunk(ChannelBlackScaleData.GREEN_CHUNK),
CBS.getCBSChunk(ChannelBlackScaleData.BLUE_CHUNK),
CBS.getCBSChunk(ChannelBlackScaleData.GRAY_CHUNK)
};
ChannelBlackScaleData.CBSChunk[] newChunks =
new ChannelBlackScaleData.CBSChunk[dataChunks.length];
for (int i = 0; i < dataChunks.length; i++) {
ChannelBlackScaleData.CBSChunk chunk = dataChunks[i];
int channel = chunk.getChannel();
int blackLevel = chunk.getBlackLevel();
float scale = chunk.getScale();
float newBlack = getStackGeoMean(channel, t) + getStackGeoSigma(channel, t) * blackLevel;
float scaleMod = scale == 0f ? 0.00001f : scale;
float newScale = 255f / (getStackGeoSigma(channel, t) * scaleMod);
int newB = Math.round(newBlack);
float newS = Math.round(newScale * 100000f) / 100000f;
// black-level overcorrection adjustment
if (newB < getStackMin(channel, t)) {
newB = Math.round((float) Math.ceil(getStackMin(channel, t)));
}
if (newB > getStackMax(channel, t)) {
newB = Math.round((float) Math.floor(getStackMax(channel, t)));
}
// end black-level overcorrection adjustment
// white-level overcorrection adjustment
float whiteLevel =
getStackGeoMean(channel, t) + dataChunks[i].getScale() * getStackGeoSigma(channel, t);
boolean recalculate = false;
if (whiteLevel < getStackMin(channel, t)) {
whiteLevel = getStackMin(channel, t);
recalculate = true;
}
if (whiteLevel > getStackMax(channel, t)) {
whiteLevel = getStackMax(channel, t);
recalculate = true;
}
if (recalculate) {
if (whiteLevel - getStackGeoMean(channel, t) == 0f) {
whiteLevel += 0.00001f;
}
newS = 255f / (whiteLevel - getStackGeoMean(channel, t));
}
// end white-level correction adjustment
newChunks[i] = new ChannelBlackScaleData.CBSChunk(channel, newB, newS);
}
convertedData.setCBSChunk(ChannelBlackScaleData.RED_CHUNK, newChunks[0]);
convertedData.setCBSChunk(ChannelBlackScaleData.GREEN_CHUNK, newChunks[1]);
convertedData.setCBSChunk(ChannelBlackScaleData.BLUE_CHUNK, newChunks[2]);
convertedData.setCBSChunk(ChannelBlackScaleData.RED_CHUNK, newChunks[3]);
cbsMap.put(tObj, convertedData);
return convertedData;
}
