C++ AMnDIndex::at方法代码示例

// Helper function to implement the base-class version of values() when rank > 4.
void AMDataSource::valuesImplementationRecursive(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, AMnDIndex current, int dimension, double **outputValues) const
{
    if(dimension == current.rank()-1) {	// base case: final dimension
        for(int i=indexStart.at(dimension); i<=indexEnd.at(dimension); ++i) {
            current[dimension] = i;
            *((*outputValues)++) = double(value(current));
        }
    }
    else {
        for(int i=indexStart.at(dimension); i<indexEnd.at(dimension); ++i) {
            current[dimension] = i;
            valuesImplementationRecursive(indexStart, indexEnd, current, dimension+1, outputValues);
        }
    }
}

void AMNormalizationAB::reviewState()
{
	// Are there data sources?
	if(sources_.isEmpty()){

		setState(AMDataSource::InvalidFlag);
		return;
	}

	// Are all the data sources the same size?
	AMnDIndex firstSize = sources_.first()->size();

	for (int i = 0, size = firstSize.rank(); i < size; i++)
		foreach (AMDataSource *dataSource, sources_)
			if(firstSize.at(i) != dataSource->size(i)){

				setState(AMDataSource::InvalidFlag);
				return;
			}

	// Validity check on all data sources.
	bool valid = true;

	for (int i = 0; i < sources_.size(); i++)
		valid = valid && sources_.at(i)->isValid();

	if (valid)
		setState(0);
	else
		setState(AMDataSource::InvalidFlag);
}

void AMInMemoryDataStore::measurementValuesImplementationRecursive(const AMIMDSMeasurement &measurement, const AMnDIndex &indexStart, const AMnDIndex &indexEnd, const AMnDIndex &fullSize, double **outputValues, int dimension, int cOffset) const {

	if(dimension == indexStart.rank()-1) { // base case: final dimension
		for(int i=indexStart.at(dimension); i<=indexEnd.at(dimension); ++i) {
			*((*outputValues)++) = double(measurement.at(cOffset+i));
		}
	}
	else {
		for(int i=indexStart.at(dimension); i<=indexEnd.at(dimension); ++i) {
			// get product of all higher dimensions:
			int multiplier = 1;
			for(int mu=dimension+1; mu<indexStart.rank(); ++mu)
				multiplier *= fullSize.at(mu);

			// recurse:
			measurementValuesImplementationRecursive(measurement, indexStart, indexEnd, fullSize, outputValues, dimension+1, cOffset + i*multiplier);
		}
	}
}

void AMInMemoryDataStore::valuesImplementationRecursive(const AMnDIndex &siStart, const AMnDIndex &siEnd, int measurementId, const AMnDIndex &miStart, const AMnDIndex &miEnd, double **outputValues, int scanDimension, int scanSpaceOffset, const AMnDIndex &fullSize, int measurementSpaceSize) const {

	if(scanDimension == axes_.count()-1) { // base case: last (final) dimension
		for(int i=siStart.at(scanDimension); i<=siEnd.at(scanDimension); ++i) {
			measurementValues(scanPoints_.at(scanSpaceOffset+i).at(measurementId), fullSize, miStart, miEnd, *outputValues);
			*outputValues += measurementSpaceSize;
		}
	}
	else {
		for(int i=siStart.at(scanDimension); i<=siEnd.at(scanDimension); ++i) {
			// get product of all higher scan dimensions:
			int multiplier = 1;
			for(int mu=scanDimension+1; mu<siStart.rank(); ++mu)
				multiplier *= scanSize_.at(mu);

			// recurse:
			valuesImplementationRecursive(siStart, siEnd, measurementId, miStart, miEnd, outputValues, scanDimension+1, scanSpaceOffset + i*multiplier, fullSize, measurementSpaceSize);
		}
	}
}

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;
}

AMNumber AMNormalizationAB::value(const AMnDIndex &indexes) const
{
	if(indexes.rank() != rank())
		return AMNumber(AMNumber::DimensionError);

	if(!isValid())
		return AMNumber(AMNumber::InvalidError);

	for (int i = 0, size = indexes.rank(); i < size; i++)
		if((unsigned)indexes.at(i) >= (unsigned)axes_.at(i).size)
			return AMNumber(AMNumber::OutOfBoundsError);

	if (cacheUpdateRequired_)
		computeCachedValues();

	return cachedData_.at(indexes.flatIndexInArrayOfSize(size()));
}

AMNumber AMnDDeadTimeAB::value(const AMnDIndex &indexes) const
{
	if(indexes.rank() != rank())
		return AMNumber(AMNumber::DimensionError);

	if(!isValid())
		return AMNumber(AMNumber::InvalidError);

#ifdef AM_ENABLE_BOUNDS_CHECKING
	for (int i = 0, size = axes_.size(); i < size; i++)
		if (indexes.at(i) >= axes_.at(i).size)
			return AMNumber(AMNumber::OutOfBoundsError);
#endif

	if ((int)spectrum_->value(indexes) == 0 || double(outputCounts_->value(indexes.i())) == 0)
		return 0;
	else
		return double(inputCounts_->value(indexes.i()))/double(outputCounts_->value(indexes.i()))*(int)spectrum_->value(indexes);
}

void AMExternalScanDataSourceAB::copyAxisValues(int dataSourceIndex)
{
	AMDataSource* ds = scan_->dataSourceAt(dataSourceIndex);
	const AMnDIndex size = ds->size();

	axisValues_.clear();

	for(int mu=0; mu<size.rank(); mu++) {	// for each axis
		QVector<AMNumber> av;

		if(!axes_.at(mu).isUniform) {
			int axisLength = size.at(mu);
			for(int i=0; i<axisLength; i++)	// copy all the axis values
				av << axisValue(mu, i);
		}

		axisValues_ << av;
	}
}

/* This base-class implementation simply calls value() repeatedly and should absolutely be re-implemented for better performance. */
bool AMDataSource::values(const AMnDIndex &indexStart, const AMnDIndex &indexEnd, double *outputValues) const
{
    static bool programmerWarningIssued = false;
    if(!programmerWarningIssued) {
        AMErrorMon::debug(0, AMDATASOURCE_VALUES_BASE_IMPLEMENTATION_CALLED, QString("AMDataSource: Warning: Data source '%1' is using the base implementation of AMDataSource::values(), which is very inefficient. Re-implement values() to improve performance.  (This warning will only be given once.)").arg(name()));
        programmerWarningIssued = true;	// one problem with this warning method: if multiple classes have this problem, it will only be given once, and the subsequent classes will not be named.
    }

    int _rank = rank();

    if(indexStart.rank() != _rank || indexEnd.rank() != _rank)
        return false;

#ifdef AM_ENABLE_BOUNDS_CHECKING
    for(int mu=0; mu<_rank; ++mu) {
        if(indexEnd.at(mu) >= size(mu))
            return false;
        if(indexEnd.at(mu) < indexStart.at(mu))
            return false;
    }
#endif

    switch(_rank) {
    case 0:
        *outputValues = double(value(indexStart));
        break;

    case 1: {
        for(int i=indexStart.i(); i<=indexEnd.i(); ++i)
            *(outputValues++) = double(value(AMnDIndex(i)));
        break;
    }

    case 2: {
        for(int i=indexStart.i(); i<=indexEnd.i(); ++i)
            for(int j=indexStart.j(); j<=indexEnd.j(); ++j)
                *(outputValues++) = double(value(AMnDIndex(i,j)));
        break;
    }

    case 3: {
        for(int i=indexStart.i(); i<=indexEnd.i(); ++i)
            for(int j=indexStart.j(); j<=indexEnd.j(); ++j)
                for(int k=indexStart.k(); k<=indexEnd.k(); ++k)
                    *(outputValues++) = double(value(AMnDIndex(i,j,k)));
        break;
    }

    case 4: {
        for(int i=indexStart.i(); i<=indexEnd.i(); ++i)
            for(int j=indexStart.j(); j<=indexEnd.j(); ++j)
                for(int k=indexStart.k(); k<=indexEnd.k(); ++k)
                    for(int l=indexStart.l(); l<=indexEnd.l(); ++l)
                        *(outputValues++) = double(value(AMnDIndex(i,j,k,l)));
        break;
    }

    default: {
        valuesImplementationRecursive(indexStart, indexEnd, AMnDIndex(_rank, AMnDIndex::DoNotInit), 0, &outputValues);
        break;
    }
    }
    return true;
}

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){
//.........这里部分代码省略.........

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;
					}
				}
//.........这里部分代码省略.........