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// ************************************************************************************************
//
// BornAgain: simulate and fit reflection and scattering
//
//! @file Sim/Scan/LambdaScan.cpp
//! @brief Implements class LambdaScan.
//!
//! @homepage http://www.bornagainproject.org
//! @license GNU General Public License v3 or higher (see COPYING)
//! @copyright Forschungszentrum Jülich GmbH 2018
//! @authors Scientific Computing Group at MLZ (see CITATION, AUTHORS)
//
// ************************************************************************************************
#include "Sim/Scan/LambdaScan.h"
#include "Base/Axis/MakeScale.h"
#include "Base/Axis/Scale.h"
#include "Base/Vector/GisasDirection.h"
#include "Device/Beam/Beam.h"
#include "Device/Beam/IFootprint.h"
#include "Param/Distrib/ParameterSample.h"
#include "Resample/Element/ScanElement.h"
#include <algorithm> // is_sorted
#include <numbers>
using std::numbers::pi;
LambdaScan::LambdaScan(const Scale& lambdaScale)
: PhysicalScan(lambdaScale)
{
std::vector<double> axis_values = m_axis->binCenters();
if (!std::is_sorted(axis_values.begin(), axis_values.end()))
throw std::runtime_error("LambdaScan: wavelength values are not "
"sorted in ascending order.");
if (axis_values.front() <= 0)
throw std::runtime_error("LambdaScan: non-positive wavelengths.");
for (size_t i = 0; i < nScan(); i++) {
auto* beam = new Beam(defaultIntensity, m_axis->binCenter(i), defaultGrazingAngle);
m_beams.push_back(beam);
}
}
LambdaScan::LambdaScan(std::vector<double> points)
: LambdaScan(ListScan("lambda (nm)", std::move(points)))
{
}
LambdaScan::LambdaScan(int nbins, double lambda_min, double lambda_max)
: LambdaScan(EquiScan("lambda (nm)", nbins, lambda_min, lambda_max))
{
}
LambdaScan::~LambdaScan() = default;
LambdaScan* LambdaScan::clone() const
{
auto* result = new LambdaScan(*m_axis);
copyPhysicalScan(result);
return result;
}
std::vector<ScanElement> LambdaScan::generateElements() const
{
std::vector<ScanElement> result;
result.reserve(nElements());
for (size_t i = 0; i < m_axis->size(); ++i) {
const std::vector<ParameterSample> alphaDistrib =
drawDistribution(m_alpha_distrib.get(), grazingAngleAt(i));
const std::vector<ParameterSample> lambdaDistrib =
drawDistribution(m_lambda_distrib.get(), wavelengthAt(i));
const std::vector<ParameterSample> phiDistrib =
drawDistribution(m_phi_distrib.get(), azimuthalAngleAt(i));
for (auto ad : alphaDistrib) {
const double alpha = ad.value;
for (auto ld : lambdaDistrib) {
const double lambda = ld.value;
for (auto pd : phiDistrib) {
const double phi = pd.value;
const R3 kvec = vecOfLambdaAlphaPhi(lambda, -alpha, -phi);
const bool computable =
lambda > 0 && alpha >= 0 && alpha <= (pi / 2) && kvec.z() <= 0;
const double weight = ad.weight * ld.weight * pd.weight;
const double footprint = footprintAt(i) ? footprintAt(i)->calculate(alpha) : 1;
result.emplace_back(i, computable, weight, intensityAt(i), footprint,
polarizerMatrixAt(i), analyzerMatrix(), lambda, alpha, phi,
kvec);
}
}
}
}
return result;
}
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