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IndexPeaks.cpp
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IndexPeaks.cpp
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#include "MantidCrystal/IndexPeaks.h"
#include "MantidDataObjects/PeaksWorkspace.h"
#include "MantidGeometry/Crystal/IndexingUtils.h"
#include "MantidGeometry/Crystal/OrientedLattice.h"
#include "MantidKernel/BoundedValidator.h"
#include "MantidAPI/Sample.h"
namespace Mantid {
namespace Crystal {
// Register the algorithm into the AlgorithmFactory
DECLARE_ALGORITHM(IndexPeaks)
using namespace Mantid::Kernel;
using namespace Mantid::API;
using namespace Mantid::DataObjects;
using namespace Mantid::Geometry;
/** Initialize the algorithm's properties.
*/
void IndexPeaks::init() {
this->declareProperty(make_unique<WorkspaceProperty<PeaksWorkspace>>(
"PeaksWorkspace", "", Direction::InOut),
"Input Peaks Workspace");
auto mustBePositive = boost::make_shared<BoundedValidator<double>>();
mustBePositive->setLower(0.0);
this->declareProperty(
make_unique<PropertyWithValue<double>>("Tolerance", 0.15, mustBePositive,
Direction::Input),
"Indexing Tolerance (0.15)");
this->declareProperty(
make_unique<PropertyWithValue<int>>("NumIndexed", 0, Direction::Output),
"Gets set with the number of indexed peaks.");
this->declareProperty(make_unique<PropertyWithValue<double>>(
"AverageError", 0.0, Direction::Output),
"Gets set with the average HKL indexing error.");
this->declareProperty("RoundHKLs", true,
"Round H, K and L values to integers");
}
/** Execute the algorithm.
*/
void IndexPeaks::exec() {
PeaksWorkspace_sptr ws = this->getProperty("PeaksWorkspace");
if (!ws) {
throw std::runtime_error("Could not read the peaks workspace");
}
OrientedLattice o_lattice = ws->mutableSample().getOrientedLattice();
const Matrix<double> &UB = o_lattice.getUB();
if (!IndexingUtils::CheckUB(UB)) {
throw std::runtime_error(
"ERROR: The stored UB is not a valid orientation matrix");
}
bool round_hkls = this->getProperty("RoundHKLs");
std::vector<Peak> &peaks = ws->getPeaks();
size_t n_peaks = ws->getNumberPeaks();
// get list of run numbers in this peaks workspace
std::vector<int> run_numbers;
for (size_t i = 0; i < n_peaks; i++) {
int run = peaks[i].getRunNumber();
bool found = false;
size_t k = 0;
while (k < run_numbers.size() && !found) {
if (run == run_numbers[k])
found = true;
else
k++;
}
if (!found)
run_numbers.push_back(run);
}
// index the peaks for each run separately, using a UB matrix optimized for
// that run
int total_indexed = 0;
double average_error;
double total_error = 0;
double tolerance = this->getProperty("Tolerance");
for (size_t run_index = 0; run_index < run_numbers.size(); run_index++) {
std::vector<V3D> miller_indices;
std::vector<V3D> q_vectors;
int run = run_numbers[run_index];
for (size_t i = 0; i < n_peaks; i++) {
if (peaks[i].getRunNumber() == run)
q_vectors.push_back(peaks[i].getQSampleFrame());
}
Matrix<double> tempUB(UB);
int num_indexed = 0;
int original_indexed = 0;
double original_error = 0;
original_indexed = IndexingUtils::CalculateMillerIndices(
tempUB, q_vectors, tolerance, miller_indices, original_error);
IndexingUtils::RoundHKLs(miller_indices); // HKLs must be rounded for
// Optimize_UB to work
num_indexed = original_indexed;
average_error = original_error;
bool done = false;
if (num_indexed < 3) // can't optimize without at least 3
{ // peaks
done = true;
}
int iteration = 0;
while (iteration < 4 && !done) // try repeatedly optimizing 4 times
{ // which is usually sufficient
try {
IndexingUtils::Optimize_UB(tempUB, miller_indices, q_vectors);
} catch (...) // If there is any problem, such as too few
{ // independent peaks, just use the original UB
tempUB = UB;
done = true;
}
num_indexed = IndexingUtils::CalculateMillerIndices(
tempUB, q_vectors, tolerance, miller_indices, average_error);
IndexingUtils::RoundHKLs(miller_indices); // HKLs must be rounded for
// Optimize_UB to work
if (num_indexed < original_indexed) // just use the original UB
{
num_indexed = original_indexed;
average_error = original_error;
done = true;
}
iteration++;
}
if (!round_hkls) // If user wants fractional hkls, recalculate them
{
num_indexed = IndexingUtils::CalculateMillerIndices(
tempUB, q_vectors, tolerance, miller_indices, average_error);
}
total_indexed += num_indexed;
total_error = average_error * num_indexed;
// tell the user how many were indexed in each run
if (run_numbers.size() > 1) {
g_log.notice() << "Run " << run << ": indexed " << num_indexed
<< " Peaks out of " << q_vectors.size()
<< " with tolerance of " << tolerance << '\n';
g_log.notice() << "Average error in h,k,l for indexed peaks = "
<< average_error << '\n';
}
size_t miller_index_counter = 0;
for (size_t i = 0; i < n_peaks; i++) {
if (peaks[i].getRunNumber() == run) {
peaks[i].setHKL(miller_indices[miller_index_counter]);
miller_index_counter++;
}
}
}
if (total_indexed > 0)
average_error = total_error / total_indexed;
else
average_error = 0;
// tell the user how many were indexed overall and the overall average error
g_log.notice() << "ALL Runs: indexed " << total_indexed << " Peaks out of "
<< n_peaks << " with tolerance of " << tolerance << '\n';
g_log.notice() << "Average error in h,k,l for indexed peaks = "
<< average_error << '\n';
// Save output properties
this->setProperty("NumIndexed", total_indexed);
this->setProperty("AverageError", average_error);
// Show the lattice parameters
g_log.notice() << o_lattice << "\n";
}
} // namespace Mantid
} // namespace Crystal