Пример #1
0
QPair<double, double> AM2DScanView::getCurrentExclusiveDataSourceRange(const AMnDIndex &start, const AMnDIndex &end) const
{
	if (start == end && start.rank() == 2 && end.rank() == 2){

		QPair<double, double> range = exclusive2DScanBar_->range();
		double val = double(currentExclusiveDataSource_->value(start));

		if ((val != -1 && range.first > val) || range.first == -1)
			range.first = val;

		if (range.second < val)
			range.second = val;

		return range;
	}

	else {

		int totalSize = 0;
		AMnDIndex startIndex = start;
		AMnDIndex endIndex = end;

		if (startIndex.rank() == 0 || endIndex.rank() == 0){

			startIndex = AMnDIndex(0, 0);
			endIndex = AMnDIndex(currentExclusiveDataSource_->size(0)-1, currentExclusiveDataSource_->size(1)-1);
			totalSize = startIndex.totalPointsTo(endIndex);
		}

		else
			totalSize = start.totalPointsTo(end);

		if (totalSize > 0){

			QVector<double> data(totalSize);
			currentExclusiveDataSource_->values(startIndex, endIndex, data.data());

			double min = data.at(0);
			double max = data.at(0);

			foreach (double value, data){

				if ((value != -1 && min > value) || min == -1)
					min = value;

				if (max < value)
					max = value;
			}

			return qMakePair(min, max);
		}

		else
			return qMakePair(-1.0, -1.0);
Пример #2
0
void AM3DAdditionAB::computeCachedValues() const
{
	AMnDIndex start = AMnDIndex();
	AMnDIndex end = AMnDIndex();

	if (dirtyIndices_.isEmpty()){

		start = AMnDIndex(rank(), AMnDIndex::DoInit);
		end = size()-1;
	}

	else {

		start = dirtyIndices_.first();
		end = dirtyIndices_.last();
		end[rank()-1] = size(rank()-1);
	}

	int totalSize = start.totalPointsTo(end);
	int flatStartIndex = start.flatIndexInArrayOfSize(size());
	QVector<double> data = QVector<double>(totalSize);
	sources_.at(0)->values(start, end, data.data());

	// Do the first data source separately to initialize the values.
	memcpy(cachedData_.data()+flatStartIndex, data.constData(), totalSize*sizeof(double));
	cachedData_ = data;

	// Iterate through the rest of the sources.
	for (int i = 1, count = sources_.size(); i < count; i++){

		sources_.at(i)->values(start, end, data.data());

		for (int j = 0; j < totalSize; j++)
			cachedData_[flatStartIndex+j] += data.at(j);
	}

	if (dirtyIndices_.isEmpty())
		cachedDataRange_ = AMUtility::rangeFinder(cachedData_);

	else{
		AMRange cachedRange = AMUtility::rangeFinder(cachedData_.mid(flatStartIndex, totalSize));

		if (cachedDataRange_.minimum() > cachedRange.minimum())
			cachedDataRange_.setMinimum(cachedRange.minimum());

		if (cachedDataRange_.maximum() < cachedRange.maximum())
			cachedDataRange_.setMaximum(cachedRange.maximum());
	}

	cacheUpdateRequired_ = false;
	dirtyIndices_.clear();
}
Пример #3
0
bool AM3DDeadTimeAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != 3 || indexEnd.rank() != 3)
		return false;

	if(!isValid())
		return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
	if((unsigned)indexEnd.i() >= (unsigned)axes_.at(0).size || (unsigned)indexStart.i() > (unsigned)indexEnd.i()
			|| (unsigned)indexEnd.j() >= (unsigned)axes_.at(1).size || (unsigned)indexStart.j() > (unsigned)indexEnd.j()
			|| (unsigned)indexEnd.k() >= (unsigned)axes_.at(2).size || (unsigned)indexStart.k() > (unsigned)indexEnd.k())
		return false;
#endif

	int totalSize = indexStart.totalPointsTo(indexEnd);
	AMnDIndex start2D = AMnDIndex(indexStart.i(), indexStart.j());
	AMnDIndex end2D = AMnDIndex(indexEnd.i(), indexEnd.j());
	int icrOcrTotalSize = start2D.totalPointsTo(end2D);

	QVector<double> data = QVector<double>(totalSize);
	QVector<double> icr = QVector<double>(icrOcrTotalSize);
	QVector<double> ocr = QVector<double>(icrOcrTotalSize);
	spectra_->values(indexStart, indexEnd, data.data());
	icr_->values(start2D, end2D, icr.data());
	ocr_->values(start2D, end2D, ocr.data());

	for (int i = 0, iSize = indexEnd.i()-indexStart.i()+1; i < iSize; i++){

		for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++){

			// If ocr is equal to 0 then that will cause division by zero.  Since these are both count rates, they should both be greater than zero.
			if (icr.at(i*jSize+j) <= 0 || ocr.at(i*jSize+j) <= 0){

				for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++)
					outputValues[i*jSize*kSize+j*kSize+k] = 0;
			}

			else {

				double factor = icr.at(i*jSize+j)/ocr.at(i*jSize+j);

				for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++)
					outputValues[i*jSize*kSize+j*kSize+k] = data.at(i*jSize*kSize+j*kSize+k)*factor;
			}
		}
	}

	return true;
}
bool AM3DDeadTimeCorrectionAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != 3 || indexEnd.rank() != 3)
		return false;

	if(!isValid())
		return false;

	if((unsigned)indexEnd.i() >= (unsigned)axes_.at(0).size || (unsigned)indexStart.i() > (unsigned)indexEnd.i()
			|| (unsigned)indexEnd.j() >= (unsigned)axes_.at(1).size || (unsigned)indexStart.j() > (unsigned)indexEnd.j()
			|| (unsigned)indexEnd.k() >= (unsigned)axes_.at(2).size || (unsigned)indexStart.k() > (unsigned)indexEnd.k())
		return false;

	int totalSize = indexStart.totalPointsTo(indexEnd);

	QVector<double> data = QVector<double>(totalSize);
	QVector<double> icr = QVector<double>(totalSize);
	QVector<double> ocr = QVector<double>(totalSize);
	spectra_->values(indexStart, indexEnd, data.data());
	icr_->values(indexStart, indexEnd, icr.data());
	ocr_->values(indexStart, indexEnd, ocr.data());

	for (int i = 0, iSize = indexEnd.i()-indexStart.i()+1; i < iSize; i++){

		for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++){

			for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++){

				int index = i + j*iSize + k*iSize*jSize;

				// If ocr is equal to 0 then that will cause division by zero.  Since these are both count rates, they should both be greater than zero.
				if (icr.at(index) <= 0 || ocr.at(index) <= 0)
					outputValues[index] = 0;

				else
					outputValues[index] = data.at(index)*icr.at(index)/ocr.at(index);
			}
		}
	}

	return true;
}
Пример #5
0
bool AMNormalizationAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != rank() || indexEnd.rank() != rank())
		return false;

	if(!isValid())
		return false;

	for (int i = 0, size = indexStart.rank(); i < size; i++)
		if((unsigned)indexStart.at(i) >= (unsigned)axes_.at(i).size || (unsigned)indexStart.at(i) > (unsigned)indexEnd.at(i))
			return false;

	if (cacheUpdateRequired_)
		computeCachedValues();

	int totalSize = indexStart.totalPointsTo(indexEnd);
	memcpy(outputValues, cachedData_.constData()+indexStart.flatIndexInArrayOfSize(size()), totalSize*sizeof(double));

	return true;
}
Пример #6
0
bool AM1DSummingAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != 1 || indexEnd.rank() != 1)
		return false;

	if(!isValid())
		return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
	for (int i = 0; i < sources_.size(); i++)
		if ((unsigned)indexEnd.i() >= (unsigned)axes_.at(0).size)
			return false;

	if ((unsigned)indexStart.i() > (unsigned)indexEnd.i())
		return false;
#endif

	int totalSize = indexStart.totalPointsTo(indexEnd);

	QVector<double> data = QVector<double>(totalSize);
	sources_.at(0)->values(indexStart, indexEnd, data.data());

	// Do the first data source separately to initialize the values.
	for (int i = 0; i < totalSize; i++)
		outputValues[i] = data.at(i);

	// Iterate through the rest of the sources.
	for (int i = 1, count = sources_.size(); i < count; i++){

		sources_.at(i)->values(indexStart, indexEnd, data.data());

		for (int j = 0; j < totalSize; j++)
			outputValues[j] += data.at(j);
	}

	return true;
}
Пример #7
0
void AMAdditionAB::computeCachedValues() const
{
    AMnDIndex start = AMnDIndex(rank(), AMnDIndex::DoInit, 0);
    AMnDIndex end = size()-1;
    int totalSize = start.totalPointsTo(end);

    QVector<double> data = QVector<double>(totalSize);
    sources_.at(0)->values(start, end, data.data());

    // Do the first data source separately to initialize the values.
    cachedData_ = data;

    // Iterate through the rest of the sources.
    for (int i = 1, count = sources_.size(); i < count; i++) {

        sources_.at(i)->values(start, end, data.data());

        for (int j = 0; j < totalSize; j++)
            cachedData_[j] += data.at(j);
    }

    cachedDataRange_ = AMUtility::rangeFinder(cachedData_);
    cacheUpdateRequired_ = false;
}
Пример #8
0
bool AMDeadTimeAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != 1 || indexEnd.rank() != 1)
		return false;

	if(!isValid())
		return false;

	if((unsigned)indexEnd.i() >= (unsigned)axes_.at(0).size || (unsigned)indexStart.i() > (unsigned)indexEnd.i())
		return false;

	int totalSize = indexStart.totalPointsTo(indexEnd);

	QVector<double> data = QVector<double>(totalSize);
	spectra_->values(indexStart, indexEnd, data.data());

	double icr = double(icr_->value(AMnDIndex()));
	double ocr = double(ocr_->value(AMnDIndex()));

	// If ocr is equal to 0 then that will cause division by zero.  Since these are both count rates, they should both be greater than zero.
	if (icr <= 0 || ocr <= 0){

		for (int i = 0; i < totalSize; i++)
			outputValues[i] = 0;
	}

	else {

		double factor = icr/ocr;

		for (int i = 0; i < totalSize; i++)
			outputValues[i] = data.at(i)*factor;
	}

	return true;
}
bool AM1DRunningAverageFilterAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != 1 || indexEnd.rank() != 1)
		return false;

	if(!isValid())
		return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
	if((unsigned)indexEnd.i() >= (unsigned)axes_.at(0).size || (unsigned)indexStart.i() > (unsigned)indexEnd.i())
		return false;
#endif

	int totalSize = indexStart.totalPointsTo(indexEnd);

	QVector<double> data = QVector<double>(totalSize);
	inputSource_->values(indexStart, indexEnd, data.data());

	int numberOfPoints = (filterSize_-1)/2;
	double average = 0;
	int tempNumberOfPoints = 1;

	// If the filter size is bigger then the total size of the data then we will just check every point along the way.
	if (numberOfPoints > totalSize){

		for (int i = 0; i < totalSize; i++){

			average = data.at(i);
			tempNumberOfPoints = 1;

			for (int j = 1; j < numberOfPoints; j++){

				if ((i-j) >= 0){

					average += data.at(i-j);
					tempNumberOfPoints++;
				}

				if ((i+j) < totalSize){

					average += data.at(i+j);
					tempNumberOfPoints++;
				}
			}

			outputValues[i] = average/double(tempNumberOfPoints);
		}
	}

	// Otherwise, we can optimize the middle indices of the without having to check if we will be accessing data outside of the array range.
	else {

		// Compute the beginning values.
		for (int i = 0; i < numberOfPoints; i++){

			average = data.at(i);
			tempNumberOfPoints = 1;

			// Only need the substraction check at the beginning.
			for (int j = 1; j < numberOfPoints; j++){

				if ((i-j) >= 0){

					average += data.at(i-j);
					tempNumberOfPoints++;
				}

				average += data.at(i+j);
				tempNumberOfPoints++;
			}

			outputValues[i] = average/double(tempNumberOfPoints);
		}

		// No need for conditionals in the middle of the data.
		double averagePoints = double(numberOfPoints);

		for (int i = numberOfPoints, count = totalSize-numberOfPoints; i < count; i++){

			average = data.at(i);

			for (int j = 1; j < numberOfPoints; j++)
				average += data.at(i-j) + data.at(i+j);

			outputValues[i] = average/averagePoints;
		}

		// Compute the last values.
		for (int i = totalSize-numberOfPoints; i < totalSize; i++){

			average = data.at(i);
			tempNumberOfPoints = 1;

			// Only need the addition check at the end.
			for (int j = 1; j < numberOfPoints; j++){

				average += data.at(i-j);
				tempNumberOfPoints++;

				if ((i+j) < totalSize){

					average += data.at(i+j);
					tempNumberOfPoints++;
				}
			}

			outputValues[i] = average/double(tempNumberOfPoints);
		}
	}

	return true;
}
Пример #10
0
bool AMnDDeadTimeAB::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
	if(indexStart.rank() != rank() || indexEnd.rank() != indexStart.rank())
		return false;

	if(!isValid())
		return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
	for (int i = 0, size = axes_.size(); i < size; i++)
		if (indexEnd.at(i) >= axes_.at(i).size || (unsigned)indexStart.at(i) > (unsigned)indexEnd.at(i))
			return false;
#endif

	switch(rank()){

	case 0:	// Can't happen.
		break;

	case 1:{

		int totalSize = indexStart.totalPointsTo(indexEnd);
		double inputCounts = inputCounts_->value(AMnDIndex());
		double outputCounts = outputCounts_->value(AMnDIndex());

		if (outputCounts == 0){

			QVector<double> data = QVector<double>(totalSize, 0);
			outputValues = data.data();
		}

		else {

			double scalingFactor = qAbs(inputCounts/outputCounts);

			QVector<double> data = QVector<double>(totalSize);
			spectrum_->values(indexStart, indexEnd, data.data());

			for (int i = 0, size = data.size(); i < size; i++)
				outputValues[i] = data.at(i)*scalingFactor;
		}

		break;
	}

	case 2:{

		int totalSize = indexStart.totalPointsTo(indexEnd);
		int crTotalSize = AMnDIndex(indexStart.i()).totalPointsTo(AMnDIndex(indexEnd.i()));

		QVector<double> data = QVector<double>(totalSize);
		QVector<double> inputCounts = QVector<double>(crTotalSize);
		QVector<double> outputCounts = QVector<double>(crTotalSize);
		spectrum_->values(indexStart, indexEnd, data.data());
		inputCounts_->values(indexStart.i(), indexEnd.i(), inputCounts.data());
		outputCounts_->values(indexStart.i(), indexEnd.i(), outputCounts.data());

		for (int i = 0, iSize = indexEnd.i() - indexStart.i()+1; i < iSize; i++){

			// If outputCounts is equal to 0 then that will cause division by zero.
			if (outputCounts.at(i) <= 0){

				for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++)
					outputValues[i*jSize+j] = 0;
			}

			else {

				double factor = qAbs(inputCounts.at(i)/outputCounts.at(i));

				for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++)
					outputValues[i*jSize+j] = data.at(i*jSize+j)*factor;
			}
		}

		break;
	}

	case 3:{

		int totalSize = indexStart.totalPointsTo(indexEnd);
		AMnDIndex start2D = AMnDIndex(indexStart.i(), indexStart.j());
		AMnDIndex end2D = AMnDIndex(indexEnd.i(), indexEnd.j());
		int icrOcrTotalSize = start2D.totalPointsTo(end2D);

		QVector<double> data = QVector<double>(totalSize);
		QVector<double> inputCounts = QVector<double>(icrOcrTotalSize);
		QVector<double> outputCounts = QVector<double>(icrOcrTotalSize);
		spectrum_->values(indexStart, indexEnd, data.data());
		inputCounts_->values(start2D, end2D, inputCounts.data());
		outputCounts_->values(start2D, end2D, outputCounts.data());

		for (int i = 0, iSize = indexEnd.i()-indexStart.i()+1; i < iSize; i++){

			for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++){

				int scaleFactorIndex = i*jSize+j;

				// If outputCounts is equal to 0 then that will cause division by zero.
				if (outputCounts.at(scaleFactorIndex) <= 0){

					for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++)
						outputValues[i*jSize*kSize+j*kSize+k] = 0;
				}

				else {

					double scaleFactor = qAbs(inputCounts.at(scaleFactorIndex)/outputCounts.at(scaleFactorIndex));

					for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++){

						int spectrumIndex = i*jSize*kSize+j*kSize+k;
						outputValues[spectrumIndex] = data.at(spectrumIndex)*scaleFactor;
					}
				}
			}
		}

		break;
	}

	case 4:{

		int totalSize = indexStart.totalPointsTo(indexEnd);
		AMnDIndex start3D = AMnDIndex(indexStart.i(), indexStart.j());
		AMnDIndex end3D = AMnDIndex(indexEnd.i(), indexEnd.j());
		int icrOcrTotalSize = start3D.totalPointsTo(end3D);

		QVector<double> data = QVector<double>(totalSize);
		QVector<double> inputCounts = QVector<double>(icrOcrTotalSize);
		QVector<double> outputCounts = QVector<double>(icrOcrTotalSize);
		spectrum_->values(indexStart, indexEnd, data.data());
		inputCounts_->values(start3D, end3D, inputCounts.data());
		outputCounts_->values(start3D, end3D, outputCounts.data());

		for (int i = 0, iSize = indexEnd.i()-indexStart.i()+1; i < iSize; i++){

			for (int j = 0, jSize = indexEnd.j()-indexStart.j()+1; j < jSize; j++){

				for (int k = 0, kSize = indexEnd.k()-indexStart.k()+1; k < kSize; k++){

					int scaleFactorIndex = i*jSize*kSize+j*kSize+k;

					// If outputCounts is equal to 0 then that will cause division by zero.
					if (outputCounts.at(scaleFactorIndex) <= 0){

						for (int l = 0, lSize = indexEnd.l()-indexStart.l()+1; l < lSize; l++)
							outputValues[i*jSize*kSize*lSize+j*kSize*lSize+k*lSize+l] = 0;
					}

					else {

						double scaleFactor = qAbs(inputCounts.at(scaleFactorIndex)/outputCounts.at(scaleFactorIndex));

						for (int l = 0, lSize = indexEnd.l()-indexStart.l()+1; l < lSize; l++){

							int spectrumIndex = i*jSize*kSize*lSize+j*kSize*lSize+k*lSize+l;
							outputValues[spectrumIndex] = data.at(spectrumIndex)*scaleFactor;
						}
					}
				}
			}
		}

		break;
	}
	}

	return true;
}
Пример #11
0
bool AMInMemoryDataStore::values(const AMnDIndex &scanIndexStart, const AMnDIndex &scanIndexEnd, int measurementId, const AMnDIndex &measurementIndexStart, const AMnDIndex &measurementIndexEnd, double *outputValues) const {

	if(scanIndexStart.rank() != axes_.count() || scanIndexEnd.rank() != axes_.count())
		return false;
	if(measurementId >= measurements_.count())
		return false;

	const AMMeasurementInfo& mi = measurements_.at(measurementId);
	if(measurementIndexStart.rank() != mi.rank() || measurementIndexEnd.rank() != mi.rank())
		return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
	// check bounds for scan axes
	for(int mu=axes_.count()-1; mu >= 0; --mu) {
		if(scanIndexEnd.at(mu) < scanIndexStart.at(mu))
			return false;
		if(scanIndexEnd.at(mu) >= axes_.at(mu).size)
			return false;
	}

	// check bounds for measurement axes
	for(int mu=mi.rank()-1; mu >= 0; --mu) {
		if(measurementIndexEnd.at(mu) < measurementIndexStart.at(mu))
			return false;
		if(measurementIndexEnd.at(mu) >= mi.size(mu))
			return false;
	}
#endif

	// Determine the full size of the measurement (not necessarily the size of the block that we want to read out).
	AMnDIndex measurementSize = mi.size();
	int flatMeasurementSize = measurementSize.product();

	// specific cases of scan rank:
	switch(scanIndexStart.rank()) {
	case 0: {
		// null scan space; just copy in the measurement block

		if(measurementIndexStart.rank() == 0) {	// If measurements are scalar values, can optimize.
			outputValues[0] = double(scalarScanPoint_.at(measurementId).at(0));
		}

		else {
			// need to find out how many points one measurement block takes
			int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

			if(measurementSpaceSize == flatMeasurementSize)	// if asking for the whole measurement, can optimize.
				measurementValues(scalarScanPoint_.at(measurementId), flatMeasurementSize, outputValues);
			else
				measurementValues(scalarScanPoint_.at(measurementId), measurementSize, measurementIndexStart, measurementIndexEnd, outputValues);
		}
		break;
	}

	case 1:{
		if(measurementIndexStart.rank() == 0) {	// If measurements are scalar values, can optimize.
			for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i)
				*(outputValues++) = double(scanPoints_.at(i).at(measurementId).at(0));
		}

		else {
			// need to find out how many points one measurement block takes
			int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

			if(measurementSpaceSize == flatMeasurementSize)	// if asking for the whole measurement, can optimize.
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					measurementValues(scanPoints_.at(i).at(measurementId), flatMeasurementSize, outputValues);
					outputValues += measurementSpaceSize;
				}
			else
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					measurementValues(scanPoints_.at(i).at(measurementId), measurementSize, measurementIndexStart, measurementIndexEnd, outputValues);
					outputValues += measurementSpaceSize;
				}
		}
		break;
	}

	case 2:{
		if(measurementIndexStart.rank() == 0) {	// If measurements are scalar values, can optimize.
			for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
				int ic = i*scanSize_.j();
				for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
					*(outputValues++) = double(scanPoints_.at(ic+j).at(measurementId).at(0));
				}
			}
		}

		else {
			// need to find out how many points one measurement block takes
			int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

			if(measurementSpaceSize == flatMeasurementSize) {	// if asking for the whole measurement, can optimize.
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						measurementValues(scanPoints_.at(ic+j).at(measurementId), flatMeasurementSize, outputValues);
						outputValues += measurementSpaceSize;
					}
				}
			}
			else {
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						measurementValues(scanPoints_.at(ic+j).at(measurementId), measurementSize, measurementIndexStart, measurementIndexEnd, outputValues);
						outputValues += measurementSpaceSize;
					}
				}
			}
		}
		break;
	}

	case 3:{
		if(measurementIndexStart.rank() == 0) {	// If measurements are scalar values, can optimize.
			for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
				int ic = i*scanSize_.j()*scanSize_.k();
				for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
					int jc = j*scanSize_.k();
					for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
						*(outputValues++) = double(scanPoints_.at(ic+jc+k).at(measurementId).at(0));
					}
				}
			}
		}

		else {
			// need to find out how many points one measurement block takes
			int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

			if(measurementSpaceSize == flatMeasurementSize) {	// if asking for the whole measurement, can optimize.
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j()*scanSize_.k();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						int jc = j*scanSize_.k();
						for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
							measurementValues(scanPoints_.at(ic+jc+k).at(measurementId), flatMeasurementSize, outputValues);
							outputValues += measurementSpaceSize;
						}
					}
				}
			}
			else {
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j()*scanSize_.k();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						int jc = j*scanSize_.k();
						for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
							measurementValues(scanPoints_.at(ic+jc+k).at(measurementId), measurementSize, measurementIndexStart, measurementIndexEnd, outputValues);
							outputValues += measurementSpaceSize;
						}
					}
				}
			}
		}
		break;
	}

	case 4:{
		if(measurementIndexStart.rank() == 0) {	// If measurements are scalar values, can optimize.
			for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
				int ic = i*scanSize_.j()*scanSize_.k()*scanSize_.l();
				for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
					int jc = j*scanSize_.k()*scanSize_.l();
					for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
						int kc = k*scanSize_.l();
						for(int l=scanIndexStart.l(); l<=scanIndexEnd.l(); ++l) {
							*(outputValues++) = double(scanPoints_.at(ic+jc+kc+l).at(measurementId).at(0));
						}
					}
				}
			}
		}

		else {
			int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

			if(measurementSpaceSize == flatMeasurementSize) {	// if asking for the whole measurement, can optimize.
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j()*scanSize_.k()*scanSize_.l();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						int jc = j*scanSize_.k()*scanSize_.l();
						for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
							int kc = k*scanSize_.l();
							for(int l=scanIndexStart.l(); l<=scanIndexEnd.l(); ++l) {
								measurementValues(scanPoints_.at(ic+jc+kc+l).at(measurementId), flatMeasurementSize, outputValues);
								outputValues += measurementSpaceSize;
							}
						}
					}
				}
			}
			else {
				for(int i=scanIndexStart.i(); i<=scanIndexEnd.i(); ++i) {
					int ic = i*scanSize_.j()*scanSize_.k()*scanSize_.l();
					for(int j=scanIndexStart.j(); j<=scanIndexEnd.j(); ++j) {
						int jc = j*scanSize_.k()*scanSize_.l();
						for(int k=scanIndexStart.k(); k<=scanIndexEnd.k(); ++k) {
							int kc = k*scanSize_.l();
							for(int l=scanIndexStart.l(); l<=scanIndexEnd.l(); ++l) {
								measurementValues(scanPoints_.at(ic+jc+kc+l).at(measurementId), measurementSize, measurementIndexStart, measurementIndexEnd, outputValues);
								outputValues += measurementSpaceSize;
							}
						}
					}
				}
			}
		}
		break;
	}
	default:{
		int measurementSpaceSize = measurementIndexStart.totalPointsTo(measurementIndexEnd);

		valuesImplementationRecursive(scanIndexStart, scanIndexEnd, measurementId, measurementIndexStart, measurementIndexEnd, &outputValues, 0, 0, measurementSize, measurementSpaceSize);
		return false;
		break;
	}
	}

	return true;
}