Newer
Older
Peterson, Peter
committed
//----------------------------------------------------------------------
// Includes
//----------------------------------------------------------------------
#include "MantidAlgorithms/CrossCorrelate.h"
#include "MantidAPI/RawCountValidator.h"
#include "MantidAPI/WorkspaceUnitValidator.h"
#include "MantidKernel/BoundedValidator.h"
#include "MantidKernel/CompositeValidator.h"
#include "MantidKernel/VectorHelper.h"
#include <numeric>
#include <sstream>
Peterson, Peter
committed
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
namespace Mantid {
namespace Algorithms {
// Register the class into the algorithm factory
DECLARE_ALGORITHM(CrossCorrelate)
using namespace Kernel;
using namespace API;
/// Initialisation method.
void CrossCorrelate::init() {
auto wsValidator = boost::make_shared<CompositeValidator>();
wsValidator->add<API::WorkspaceUnitValidator>("dSpacing");
wsValidator->add<API::RawCountValidator>();
// Input and output workspaces
declareProperty(new WorkspaceProperty<MatrixWorkspace>(
"InputWorkspace", "", Direction::Input, wsValidator),
"A 2D workspace with X values of d-spacing");
declareProperty(new WorkspaceProperty<MatrixWorkspace>("OutputWorkspace", "",
Direction::Output),
"The name of the output workspace");
auto mustBePositive = boost::make_shared<BoundedValidator<int>>();
mustBePositive->setLower(0);
// Reference spectra against which cross correlation is performed
declareProperty("ReferenceSpectra", 0, mustBePositive,
"The Workspace Index of the spectra to correlate all other "
"spectra against. ");
// Spectra in the range [min to max] will be cross correlated to reference.
declareProperty("WorkspaceIndexMin", 0, mustBePositive,
"The workspace index of the first member of the range of "
"spectra to cross-correlate against.");
declareProperty("WorkspaceIndexMax", 0, mustBePositive,
" The workspace index of the last member of the range of "
"spectra to cross-correlate against.");
// Only the data in the range X_min, X_max will be used
declareProperty("XMin", 0.0,
"The starting point of the region to be cross correlated.");
declareProperty("XMax", 0.0,
"The ending point of the region to be cross correlated.");
}
/** Executes the algorithm
*
* @throw runtime_error Thrown if algorithm cannot execute
*/
void CrossCorrelate::exec() {
MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");
int reference = getProperty("ReferenceSpectra");
const size_t index_ref = static_cast<size_t>(reference);
// check that the data range specified makes sense
double xmin = getProperty("XMin");
double xmax = getProperty("XMax");
if (xmin >= xmax)
throw std::runtime_error("Must specify xmin < xmax");
// Now check if the range between x_min and x_max is valid
const MantidVec &referenceX = inputWS->readX(index_ref);
auto minIt = std::find_if(referenceX.cbegin(), referenceX.cend(),
std::bind2nd(std::greater<double>(), xmin));
if (minIt == referenceX.cend())
throw std::runtime_error("No daWorkspaceIndexMaxta above XMin");
auto maxIt = std::find_if(minIt, referenceX.cend(),
std::bind2nd(std::greater<double>(), xmax));
if (minIt == maxIt)
throw std::runtime_error("Range is not valid");
MantidVec::difference_type difminIt =
std::distance(referenceX.cbegin(), minIt);
MantidVec::difference_type difmaxIt =
std::distance(referenceX.cbegin(), maxIt);
// Now loop on the spectra in the range spectra_min and spectra_max and get
// valid spectra
int specmin = getProperty("WorkspaceIndexMin");
int specmax = getProperty("WorkspaceIndexMax");
if (specmin >= specmax)
throw std::runtime_error(
"Must specify WorkspaceIndexMin<WorkspaceIndexMax");
// Get the number of spectra in range specmin to specmax
int nspecs = 0;
std::vector<size_t> indexes; // Indexes of all spectra in range
indexes.reserve(specmax - specmin); // reserve at leat enough space
for (int i = specmin; i <= specmax; ++i) {
indexes.push_back(i); // If spectrum found then add its index to a vector.
++nspecs;
}
std::ostringstream mess;
if (nspecs == 0) // Throw if no spectra in range
Peterson, Peter
committed
{
mess << "No Workspaces in range between" << specmin << " and " << specmax;
throw std::runtime_error(mess.str());
}
Peterson, Peter
committed
// Output message information
mess << "There are " << nspecs << " Workspaces in the range" << std::endl;
g_log.information(mess.str());
mess.str("");
// Take a copy of the reference spectrum
const MantidVec &referenceY = inputWS->dataY(index_ref);
const MantidVec &referenceE = inputWS->dataE(index_ref);
std::vector<double> refX(maxIt - minIt);
std::vector<double> refY(maxIt - minIt - 1);
std::vector<double> refE(maxIt - minIt - 1);
std::copy(minIt, maxIt, refX.begin());
mess << "min max" << refX.front() << " " << refX.back();
g_log.information(mess.str());
mess.str("");
std::copy(referenceY.cbegin() + difminIt,
referenceY.cbegin() + (difmaxIt - 1), refY.begin());
std::copy(referenceE.cbegin() + difminIt,
referenceE.cbegin() + (difmaxIt - 1), refE.begin());
Peterson, Peter
committed
// Now start the real stuff
// Create a 2DWorkspace that will hold the result
const int nY = static_cast<int>(refY.size());
const int npoints = 2 * nY - 3;
MatrixWorkspace_sptr out =
WorkspaceFactory::Instance().create(inputWS, nspecs, npoints, npoints);
// Calculate the mean value of the reference spectrum and associated error
// squared
double refMean = std::accumulate(refY.cbegin(), refY.cend(), 0.0);
double refMeanE2 = std::accumulate(refE.cbegin(), refE.cend(), 0.0,
VectorHelper::SumSquares<double>());
refMean /= static_cast<double>(nY);
refMeanE2 /= static_cast<double>(nY * nY);
auto itY = refY.begin();
auto itE = refE.begin();
double refVar = 0.0, refVarE = 0.0;
for (; itY != refY.end(); ++itY, ++itE) {
(*itY) -= refMean; // Now the vector is (y[i]-refMean)
(*itE) = (*itE) * (*itE) + refMeanE2; // New error squared
double t = (*itY) * (*itY); //(y[i]-refMean)^2
refVar += t; // Sum previous term
refVarE += 4.0 * t * (*itE); // Error squared
}
double refNorm = 1.0 / sqrt(refVar);
double refNormE = 0.5 * pow(refNorm, 3) * sqrt(refVarE);
// Now copy the other spectra
bool is_distrib = inputWS->isDistribution();
std::vector<double> XX(npoints);
for (int i = 0; i < npoints; ++i)
XX[i] = static_cast<double>(i - nY + 2);
// Initialise the progress reporting object
m_progress = new Progress(this, 0.0, 1.0, nspecs);
PARALLEL_FOR2(inputWS, out)
for (int i = 0; i < nspecs; ++i) // Now loop on all spectra
{
PARALLEL_START_INTERUPT_REGION
size_t spec_index = indexes[i]; // Get the spectrum index from the table
// Copy spectra info from input Workspace
out->getSpectrum(i)->copyInfoFrom(*inputWS->getSpectrum(spec_index));
out->dataX(i) = XX;
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
const MantidVec &iX = inputWS->readX(spec_index);
const MantidVec &iY = inputWS->readY(spec_index);
const MantidVec &iE = inputWS->readE(spec_index);
// Copy Y,E data of spec(i) to temp vector
// Now rebin on the grid of reference spectrum
std::vector<double> tempY(nY);
std::vector<double> tempE(nY);
VectorHelper::rebin(iX, iY, iE, refX, tempY, tempE, is_distrib);
// Calculate the mean value of tempY
double tempMean = std::accumulate(tempY.begin(), tempY.end(), 0.0);
tempMean /= static_cast<double>(nY);
double tempMeanE2 = std::accumulate(tempE.begin(), tempE.end(), 0.0,
VectorHelper::SumSquares<double>());
tempMeanE2 /= static_cast<double>(nY * nY);
//
std::vector<double>::iterator itY;
std::vector<double>::iterator itE;
itY = tempY.begin();
itE = tempE.begin();
double tempVar = 0.0, tempVarE = 0.0;
for (; itY != tempY.end(); ++itY, ++itE) {
(*itY) -= tempMean; // Now the vector is (y[i]-refMean)
(*itE) = (*itE) * (*itE) + tempMeanE2; // New error squared
double t = (*itY) * (*itY);
tempVar += t;
tempVarE += 4.0 * t * (*itE);
}
// Calculate the normalisation constant
double tempNorm = 1.0 / sqrt(tempVar);
double tempNormE = 0.5 * pow(tempNorm, 3) * sqrt(tempVarE);
double normalisation = refNorm * tempNorm;
double normalisationE2 =
pow((refNorm * tempNormE), 2) + pow((tempNorm * refNormE), 2);
// Get reference to the ouput spectrum
MantidVec &outY = out->dataY(i);
MantidVec &outE = out->dataE(i);
for (int k = -nY + 2; k <= nY - 2; ++k) {
int kp = abs(k);
double val = 0, err2 = 0, x, y, xE, yE;
for (int j = nY - 1 - kp; j >= 0; --j) {
if (k >= 0) {
x = refY[j];
y = tempY[j + kp];
xE = refE[j];
yE = tempE[j + kp];
} else {
x = tempY[j];
y = refY[j + kp];
xE = tempE[j];
yE = refE[j + kp];
}
val += (x * y);
err2 += x * x * yE + y * y * xE;
}
outY[k + nY - 2] = (val * normalisation);
outE[k + nY - 2] = sqrt(val * val * normalisationE2 +
normalisation * normalisation * err2);
}
// Update progress information
// double prog=static_cast<double>(i)/nspecs;
// progress(prog);
m_progress->report();
// interruption_point();
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
setProperty("OutputWorkspace", out);
return;
Peterson, Peter
committed
}
Peterson, Peter
committed
} // namespace Mantid