// 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){
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;
}
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;
}