/** Execute the algorithm.
*/
void MaskMD::exec() {
IMDWorkspace_sptr ws = getProperty("Workspace");
std::string dimensions_string = getPropertyValue("Dimensions");
std::vector<double> extents = getProperty("Extents");
// Dimension names may contain brackets with commas (i.e. [H,0,0])
// so getProperty would return an incorrect vector of names;
// instead get the string and parse it here
std::vector<std::string> dimensions = parseDimensionNames(dimensions_string);
// Report what dimension names were found
g_log.debug() << "Dimension names parsed as: \n";
for (const auto &name : dimensions) {
g_log.debug() << name << '\n';
}
size_t nDims = ws->getNumDims();
size_t nDimensionIds = dimensions.size();
size_t nGroups = nDimensionIds / nDims;
bool bClearExistingMasks = getProperty("ClearExistingMasks");
if (bClearExistingMasks) {
ws->clearMDMasking();
}
this->interruption_point();
this->progress(0.0);
// Explicitly cast nGroups and group to double to avoid compiler warnings
// loss of precision does not matter as we are only using the result
// for reporting algorithm progress
const double nGroups_double = static_cast<double>(nGroups);
// Loop over all groups
for (size_t group = 0; group < nGroups; ++group) {
std::vector<InputArgument> arguments(nDims);
// Loop over all arguments within the group. and construct InputArguments
// for sorting.
for (size_t i = 0; i < nDims; ++i) {
size_t index = i + (group * nDims);
InputArgument &arg = arguments[i];
// Try to get the index of the dimension in the workspace.
arg.index = tryFetchDimensionIndex(ws, dimensions[index]);
arg.min = extents[index * 2];
arg.max = extents[(index * 2) + 1];
}
// Sort all the inputs by the dimension index. Without this it will not be
// possible to construct the MDImplicit function property.
LessThanIndex comparator;
std::sort(arguments.begin(), arguments.end(), comparator);
// Create inputs for a box implicit function
VMD mins(nDims);
VMD maxs(nDims);
for (size_t i = 0; i < nDims; ++i) {
mins[i] = float(arguments[i].min);
maxs[i] = float(arguments[i].max);
}
// Add new masking.
ws->setMDMasking(new MDBoxImplicitFunction(mins, maxs));
this->interruption_point();
double group_double = static_cast<double>(group);
this->progress(group_double / nGroups_double);
}
this->progress(1.0); // Ensure algorithm progress is reported as complete
}
/** Execute the algorithm.
*/
void MaskMD::exec() {
IMDWorkspace_sptr ws = getProperty("Workspace");
std::vector<std::string> dimensions = getProperty("Dimensions");
std::vector<double> extents = getProperty("Extents");
size_t nDims = ws->getNumDims();
size_t nDimensionIds = dimensions.size();
std::stringstream messageStream;
// Check cardinality on names/ids
if (nDimensionIds % nDims != 0) {
messageStream << "Number of dimension ids/names must be n * " << nDims;
this->g_log.error(messageStream.str());
throw std::invalid_argument(messageStream.str());
}
// Check cardinality on extents
if (extents.size() != (2 * dimensions.size())) {
messageStream << "Number of extents must be " << 2 * dimensions.size();
this->g_log.error(messageStream.str());
throw std::invalid_argument(messageStream.str());
}
// Check extent value provided.
for (size_t i = 0; i < nDimensionIds; ++i) {
double min = extents[i * 2];
double max = extents[(i * 2) + 1];
if (min > max) {
messageStream << "Cannot have minimum extents " << min
<< " larger than maximum extents " << max;
this->g_log.error(messageStream.str());
throw std::invalid_argument(messageStream.str());
}
}
size_t nGroups = nDimensionIds / nDims;
bool bClearExistingMasks = getProperty("ClearExistingMasks");
if (bClearExistingMasks) {
ws->clearMDMasking();
}
// Loop over all groups
for (size_t group = 0; group < nGroups; ++group) {
std::vector<InputArgument> arguments(nDims);
// Loop over all arguments within the group. and construct InputArguments
// for sorting.
for (size_t i = 0; i < nDims; ++i) {
size_t index = i + (group * nDims);
InputArgument &arg = arguments[i];
// Try to get the index of the dimension in the workspace.
arg.index = tryFetchDimensionIndex(ws, dimensions[index]);
arg.min = extents[index * 2];
arg.max = extents[(index * 2) + 1];
}
// Sort all the inputs by the dimension index. Without this it will not be
// possible to construct the MDImplicit function propertly.
LessThanIndex comparitor;
std::sort(arguments.begin(), arguments.end(), comparitor);
// Create inputs for a box implicit function
VMD mins(nDims);
VMD maxs(nDims);
for (size_t i = 0; i < nDims; ++i) {
mins[i] = float(arguments[i].min);
maxs[i] = float(arguments[i].max);
}
// Add new masking.
ws->setMDMasking(new MDBoxImplicitFunction(mins, maxs));
}
}
