diff --git a/GUI/Model/FromCore/ItemizeSample.cpp b/GUI/Model/FromCore/ItemizeSample.cpp
index c7f308439be8aa35f7ab5f0d753454a731068de2..49503da25e905359362dceeac55d5bbb0791b93b 100644
--- a/GUI/Model/FromCore/ItemizeSample.cpp
+++ b/GUI/Model/FromCore/ItemizeSample.cpp
@@ -322,7 +322,8 @@ void set_Roughness(LayerItem* parent, const LayerInterface* top_interface)
if (const auto* autocorrItem = dynamic_cast<const K_CorrelationModel*>(autocorrelation)) {
auto* k_corr = new K_CorrelationRoughnessItem(autocorrItem->sigma(), autocorrItem->hurst(),
- autocorrItem->lateralCorrLength());
+ autocorrItem->lateralCorrLength(),
+ autocorrItem->maxSpatialFrequency());
set_InterlayerModel(k_corr, interlayer);
set_CrosscorrelationModel(k_corr, crosscorrelation);
parent->roughnessSelection().setCertainItem(k_corr);
diff --git a/GUI/Model/Sample/RoughnessCatalog.cpp b/GUI/Model/Sample/RoughnessCatalog.cpp
index 0280bb9d6840ef2549bc69a575b2ccc88dbac229..579a9693bbd370cc2b1f09d2e7235a95b31ffa74 100644
--- a/GUI/Model/Sample/RoughnessCatalog.cpp
+++ b/GUI/Model/Sample/RoughnessCatalog.cpp
@@ -24,7 +24,7 @@ RoughnessItem* RoughnessCatalog::create(Type type)
case Type::None:
return nullptr;
case Type::K_Correlation:
- return new K_CorrelationRoughnessItem(0., .7, 25.);
+ return new K_CorrelationRoughnessItem(0., .7, 25., 0.5);
}
ASSERT_NEVER;
}
diff --git a/GUI/Model/Sample/RoughnessItems.cpp b/GUI/Model/Sample/RoughnessItems.cpp
index 85509f13bf35d148439265e10dc2fabc2fb9ef92..0d178b6ab23832b87fa733aa70acf0b0d4bf7be9 100644
--- a/GUI/Model/Sample/RoughnessItems.cpp
+++ b/GUI/Model/Sample/RoughnessItems.cpp
@@ -22,6 +22,7 @@ namespace Tag {
const QString BaseData("BaseData");
const QString HeightDistributionModel("HeightDistributionModel");
const QString CrosscorrelationModel("CrosscorrelationModel");
+const QString MaxSpatialFrequency("MaxSpatialFrequency");
const QString Sigma("Sigma");
const QString Hurst("Hurst");
const QString LateralCorrelationLength("LateralCorrelationLength");
@@ -33,6 +34,7 @@ void RoughnessItem::writeTo(QXmlStreamWriter* w) const
{
XML::writeTaggedElement(w, Tag::HeightDistributionModel, m_interlayer_model);
XML::writeTaggedElement(w, Tag::CrosscorrelationModel, m_crosscorr_model);
+ m_max_spatial_frequency.writeTo2(w, Tag::MaxSpatialFrequency);
}
void RoughnessItem::readFrom(QXmlStreamReader* r)
@@ -44,12 +46,14 @@ void RoughnessItem::readFrom(QXmlStreamReader* r)
XML::readTaggedElement(r, tag, m_interlayer_model);
else if (tag == Tag::CrosscorrelationModel)
XML::readTaggedElement(r, tag, m_crosscorr_model);
+ else if (tag == Tag::MaxSpatialFrequency)
+ m_max_spatial_frequency.readFrom2(r, tag);
else
r->skipCurrentElement();
}
}
-RoughnessItem::RoughnessItem()
+RoughnessItem::RoughnessItem(double max_spat_frequency)
{
m_interlayer_model.simpleInit("Interlayer profile",
"Laterally averaged profile of the interlayer transition (or "
@@ -58,12 +62,19 @@ RoughnessItem::RoughnessItem()
m_crosscorr_model.simpleInit("Crosscorrelation",
"Model of roughness crosscorrelation between interfaces",
CrosscorrelationCatalog::Type::None);
+ m_max_spatial_frequency.init("Max spatial frequency (1/nm)",
+ "The upper limit of the roughness spatial frequency.\n "
+ "Minimum spatial scale of relief (in nm) is 1/max_frequency.",
+ max_spat_frequency, 3, RealLimits::positive(),
+ "maxSpatialFrequency");
}
//------------------------------------------------------------------------------------------------
K_CorrelationRoughnessItem::K_CorrelationRoughnessItem(double sigma, double hurst,
- double corr_length)
+ double corr_length,
+ double max_spat_frequency)
+ : RoughnessItem(max_spat_frequency)
{
m_sigma.init("Sigma (nm)", "rms of the roughness", sigma, "sigma");
m_hurst.init("Hurst",
@@ -104,5 +115,15 @@ void K_CorrelationRoughnessItem::readFrom(QXmlStreamReader* r)
std::unique_ptr<AutocorrelationModel> K_CorrelationRoughnessItem::createModel() const
{
return std::make_unique<K_CorrelationModel>(m_sigma.dVal(), m_hurst.dVal(),
- m_lateral_correlation_length.dVal());
+ m_lateral_correlation_length.dVal(),
+ m_max_spatial_frequency.dVal());
+}
+
+DoubleProperties K_CorrelationRoughnessItem::lateralProperties()
+{
+ DoubleProperties result = {&m_sigma, &m_hurst, &m_lateral_correlation_length};
+ const auto base_pars = RoughnessItem::lateralProperties();
+ for (const auto base_par : base_pars)
+ result.push_back(base_par);
+ return result;
}
diff --git a/GUI/Model/Sample/RoughnessItems.h b/GUI/Model/Sample/RoughnessItems.h
index d65f782c69823f4353fc188138f272e4f6491f80..9b4083a67d15c4815e4caba1cdc1aa70498fc3fe 100644
--- a/GUI/Model/Sample/RoughnessItems.h
+++ b/GUI/Model/Sample/RoughnessItems.h
@@ -30,7 +30,7 @@ public:
virtual void writeTo(QXmlStreamWriter* w) const;
virtual void readFrom(QXmlStreamReader* r);
virtual std::unique_ptr<AutocorrelationModel> createModel() const = 0;
- virtual DoubleProperties lateralProperties() = 0;
+ virtual DoubleProperties lateralProperties() { return {&m_max_spatial_frequency}; }
PolyPtr<InterlayerItem, InterlayerCatalog>& interlayerModelSelection()
{
@@ -47,14 +47,16 @@ public:
void setCrosscorrModelType(CrosscorrelationItem* p) { m_crosscorr_model.setCertainItem(p); }
protected:
- RoughnessItem();
+ RoughnessItem(double max_spat_frequency);
PolyPtr<InterlayerItem, InterlayerCatalog> m_interlayer_model;
PolyPtr<CrosscorrelationItem, CrosscorrelationCatalog> m_crosscorr_model;
+ DoubleProperty m_max_spatial_frequency;
};
class K_CorrelationRoughnessItem : public RoughnessItem {
public:
- K_CorrelationRoughnessItem(double sigma, double hurst, double corr_length);
+ K_CorrelationRoughnessItem(double sigma, double hurst, double corr_length,
+ double max_spat_frequency);
DoubleProperty& sigma() { return m_sigma; }
const DoubleProperty& sigma() const { return m_sigma; }
@@ -72,10 +74,7 @@ public:
void readFrom(QXmlStreamReader* r) override;
std::unique_ptr<AutocorrelationModel> createModel() const override;
- DoubleProperties lateralProperties() override
- {
- return {&m_sigma, &m_hurst, &m_lateral_correlation_length};
- }
+ DoubleProperties lateralProperties() override;
private:
DoubleProperty m_sigma;
diff --git a/GUI/View/Realspace/RealspaceBuilder.cpp b/GUI/View/Realspace/RealspaceBuilder.cpp
index 74ec96b73a738f22f97fb098d873405106dd4660..2a512a8bc30bc266af78ef1e1f18a01f1a6d6ede 100644
--- a/GUI/View/Realspace/RealspaceBuilder.cpp
+++ b/GUI/View/Realspace/RealspaceBuilder.cpp
@@ -105,7 +105,7 @@ std::unique_ptr<const double2d_t> layerRoughnessMap(const LayerItem& layerItem,
roughItem->certainInterlayerModel()->createModel();
auto roughness = LayerRoughness(autocorrelation.get(), interlayer.get());
- if (roughness.sigma() == 0)
+ if (roughness.rms() == 0)
return result;
int n = sceneGeometry.numRoughnessPointsAlongAxis;
diff --git a/Resample/Processed/ReSample.cpp b/Resample/Processed/ReSample.cpp
index 9c10b553f74761c3bc801501e1c3751cf3a42881..2d03aa05aaf3dcc6df3a57553274aab7afa5b96d 100644
--- a/Resample/Processed/ReSample.cpp
+++ b/Resample/Processed/ReSample.cpp
@@ -402,7 +402,7 @@ bool ReSample::polarizing() const
bool ReSample::hasRoughness() const
{
for (const auto& slice : m_stack)
- if (slice.topRoughness() && slice.topRoughness()->sigma() > 0)
+ if (slice.topRoughness() && slice.topRoughness()->rms() > 0)
return true;
return false;
}
diff --git a/Resample/Slice/ProfileHelper.cpp b/Resample/Slice/ProfileHelper.cpp
index 0e25c53674886136c9072816f5cd0c1209b7c6f2..c969445e83c3afb840999ec14fb06a6fb352d7ac 100644
--- a/Resample/Slice/ProfileHelper.cpp
+++ b/Resample/Slice/ProfileHelper.cpp
@@ -27,7 +27,7 @@ double Transition(double x, const LayerRoughness* roughness)
if (!roughness)
return Math::Heaviside(x);
- return roughness->interlayerModel()->transient(x, roughness->sigma());
+ return roughness->interlayerModel()->transient(x, roughness->rms());
}
const std::string SLD = "SLD";
@@ -113,9 +113,9 @@ std::pair<double, double> ProfileHelper::defaultLimits() const
const LayerRoughness* bottomRoughness = m_stack.back().topRoughness();
double top_margin =
- topRoughness && topRoughness->sigma() > 0 ? 5.0 * topRoughness->sigma() : default_margin;
- double bottom_margin = bottomRoughness && bottomRoughness->sigma() > 0
- ? 5.0 * bottomRoughness->sigma()
+ topRoughness && topRoughness->rms() > 0 ? 5.0 * topRoughness->rms() : default_margin;
+ double bottom_margin = bottomRoughness && bottomRoughness->rms() > 0
+ ? 5.0 * bottomRoughness->rms()
: default_margin;
double z_min = m_stack.back().hig() - bottom_margin;
double z_max = m_stack.front().low() + top_margin;
diff --git a/Resample/Specular/ComputeFluxMagnetic.cpp b/Resample/Specular/ComputeFluxMagnetic.cpp
index 83e5b8a730254c0b409d43aeeb2bf7da8980bb8c..63b2380f5c5da6a009b218a376f8b5e65c8c8057 100644
--- a/Resample/Specular/ComputeFluxMagnetic.cpp
+++ b/Resample/Specular/ComputeFluxMagnetic.cpp
@@ -182,7 +182,7 @@ std::vector<MatrixFlux> computeTR(const SliceStack& slices, const std::vector<co
for (size_t i = N - 1; i > 0; --i) {
const auto* roughness = slices.bottomRoughness(i);
- const double sigma = roughness ? roughness->sigma() : 0.;
+ const double sigma = roughness ? roughness->rms() : 0.;
const auto* r_model = roughness ? roughness->interlayerModel() : nullptr;
// compute the 2x2 blocks of the transfer matrix
@@ -288,7 +288,7 @@ SpinMatrix Compute::polarizedReflectivity(const SliceStack& slices,
for (size_t i = N - 1; i > 0; --i) {
MatrixFlux tr_i = createCoeff(i - 1);
const auto* roughness = slices.bottomRoughness(i - 1);
- const double sigma = roughness ? roughness->sigma() : 0.;
+ const double sigma = roughness ? roughness->rms() : 0.;
const auto* r_model = roughness ? roughness->interlayerModel() : nullptr;
// compute the 2x2 blocks of the transfer matrix
diff --git a/Resample/Specular/ComputeFluxScalar.cpp b/Resample/Specular/ComputeFluxScalar.cpp
index 7f8a70ddeacf043c87177eb10d8ed4be63b615d7..8d40208f83747891a7290becf2707a0f06a88826 100644
--- a/Resample/Specular/ComputeFluxScalar.cpp
+++ b/Resample/Specular/ComputeFluxScalar.cpp
@@ -84,10 +84,10 @@ std::vector<Spinor> computeTR(const SliceStack& slices, const std::vector<comple
const size_t jthis = X[i - 1];
const size_t jlast = X[i];
const auto* roughness = slices.bottomRoughness(jthis);
- const double sigma = roughness ? roughness->sigma() : 0.;
+ const double rms = roughness ? roughness->rms() : 0.;
const auto* r_model = roughness ? roughness->interlayerModel() : nullptr;
- const auto [slp, slm] = transition(kz[jthis], kz[jlast], sigma, r_model);
+ const auto [slp, slm] = transition(kz[jthis], kz[jlast], rms, r_model);
const complex_t delta = exp_I(kz[jthis] * slices[jthis].thicknessOr0());
const complex_t f = delta / (slp + slm * ratio[jlast]);
@@ -138,7 +138,7 @@ complex_t Compute::scalarReflectivity(const SliceStack& slices, const std::vecto
for (size_t i = N - 1; i > 0; i--) {
const auto* roughness = slices.bottomRoughness(i - 1);
- const double sigma = roughness ? roughness->sigma() : 0.;
+ const double sigma = roughness ? roughness->rms() : 0.;
const auto* r_model = roughness ? roughness->interlayerModel() : nullptr;
const auto [sp, sm] = ::transition(kz[i - 1], kz[i], sigma, r_model);
diff --git a/Sample/Interface/AutocorrelationModels.cpp b/Sample/Interface/AutocorrelationModels.cpp
index f148c7c54771ff04f45449c02cb44add4ce02c90..8d41aa7e2614af4d35a061adcd7c66176580014f 100644
--- a/Sample/Interface/AutocorrelationModels.cpp
+++ b/Sample/Interface/AutocorrelationModels.cpp
@@ -1,4 +1,4 @@
-// ************************************************************************************************
+// ************************************************************************************************
//
// BornAgain: simulate and fit reflection and scattering
//
@@ -20,12 +20,34 @@
using std::numbers::pi;
-//! @param sigma: rms of the roughness in nanometers
+AutocorrelationModel::AutocorrelationModel(double maxSpatFrequency)
+ : m_max_spatial_frequency(maxSpatFrequency)
+{
+}
+
+std::vector<std::string> AutocorrelationModel::validationErrs() const
+{
+ std::vector<std::string> errs;
+ requestGt0(errs, m_max_spatial_frequency, "maxSpatialFrequency");
+ return errs;
+}
+
+std::string AutocorrelationModel::pythonArguments() const
+{
+ return Py::Fmt::printArguments(
+ {{m_max_spatial_frequency, AutocorrelationModel::parDefs()[0].unit}});
+}
+
+//-------------------------------------------------------------------------------------------------
+
+//! @param sigma: height scale of the roughness in nanometers (usually close to rms)
//! @param hurstParameter: hurst parameter which describes how jagged the interface,
//! dimensionless (0.0, 1.0], where 0.0 gives more spikes, 1.0 more smoothness
//! @param lateralCorrLength: lateral correlation length of the roughness in nanometers
-K_CorrelationModel::K_CorrelationModel(double sigma, double hurst, double lateralCorrLength)
- : m_sigma(sigma)
+K_CorrelationModel::K_CorrelationModel(double sigma, double hurst, double lateralCorrLength,
+ double maxSpatFrequency)
+ : AutocorrelationModel(maxSpatFrequency)
+ , m_sigma(sigma)
, m_hurst_parameter(hurst)
, m_lateral_corr_length(lateralCorrLength)
{
@@ -34,16 +56,26 @@ K_CorrelationModel::K_CorrelationModel(double sigma, double hurst, double latera
K_CorrelationModel* K_CorrelationModel::clone() const
{
- return new K_CorrelationModel(m_sigma, m_hurst_parameter, m_lateral_corr_length);
+ return new K_CorrelationModel(m_sigma, m_hurst_parameter, m_lateral_corr_length,
+ m_max_spatial_frequency);
+}
+
+std::vector<ParaMeta> K_CorrelationModel::parDefs() const
+{
+ std::vector<ParaMeta> result = {{"Sigma", "nm"}, {"Hurst", ""}, {"CorrLength", "nm"}};
+ const auto base_pars = AutocorrelationModel::parDefs();
+ result.insert(result.end(), base_pars.begin(), base_pars.end());
+ return result;
}
std::string K_CorrelationModel::validate() const
{
- std::vector<std::string> errs;
+ std::vector<std::string> errs = AutocorrelationModel::validationErrs();
requestGe0(errs, m_sigma, "sigma");
if (m_sigma > 0) {
+ requestGt0(errs, m_hurst_parameter, "hurst");
requestIn(errs, m_hurst_parameter, "hurst", 0, 1);
- requestGe0(errs, m_lateral_corr_length, "lateralCorrLength"); // may be zero if unused
+ requestGt0(errs, m_lateral_corr_length, "lateralCorrLength");
}
if (!errs.empty())
return jointError(errs);
@@ -55,7 +87,8 @@ std::string K_CorrelationModel::pythonArguments() const
{
return Py::Fmt::printArguments({{m_sigma, parDefs()[0].unit},
{m_hurst_parameter, parDefs()[1].unit},
- {m_lateral_corr_length, parDefs()[2].unit}});
+ {m_lateral_corr_length, parDefs()[2].unit}})
+ + ", " + AutocorrelationModel::pythonArguments();
}
//! Power spectral density of the surface roughness is a result of two-dimensional
@@ -65,19 +98,18 @@ std::string K_CorrelationModel::pythonArguments() const
double K_CorrelationModel::spectralFunction(const R3& q) const
{
ASSERT(m_validated);
+ const double Qpar2 = q.magxy2();
+ if (Qpar2 > 4 * pi * pi * m_max_spatial_frequency * m_max_spatial_frequency)
+ return 0;
const double H = m_hurst_parameter;
const double clength2 = m_lateral_corr_length * m_lateral_corr_length;
- const double Qpar2 = q.magxy2();
return 4.0 * pi * H * m_sigma * m_sigma * clength2 * std::pow(1 + Qpar2 * clength2, -1 - H);
}
-//! Correlation function of the roughness profile
-double K_CorrelationModel::corrFunction(const R3& r) const
+double K_CorrelationModel::rms() const
{
- ASSERT(m_validated);
+ // integration of spectral function: rms^2 = Integrate[PSD(f) * 2*pi*f, {f, 0, max_frequency}]
const double H = m_hurst_parameter;
- const double clength = m_lateral_corr_length;
- const double R = r.magxy();
- return m_sigma * m_sigma * std::pow(2., 1 - H) / tgamma(H) * std::pow(R / clength, H)
- * gsl_sf_bessel_Knu(H, R / clength);
+ const double val = 2 * pi * m_lateral_corr_length * m_max_spatial_frequency;
+ return m_sigma * std::sqrt(1. - std::pow(1 + val * val, -H));
}
diff --git a/Sample/Interface/AutocorrelationModels.h b/Sample/Interface/AutocorrelationModels.h
index 6f2595588df27d326ec8e15804185a445b8cabec..3feb4b8fdd2df2f82cd9521b8c90f1025e5c4060 100644
--- a/Sample/Interface/AutocorrelationModels.h
+++ b/Sample/Interface/AutocorrelationModels.h
@@ -23,13 +23,22 @@
class AutocorrelationModel : public ICloneable, public INode {
public:
AutocorrelationModel* clone() const override = 0;
- virtual double sigma() const = 0;
+ virtual double rms() const = 0;
virtual double spectralFunction(const R3& k) const = 0;
- virtual double corrFunction(const R3& k) const = 0;
+
+ void setMaxSpatialFrequency(double val) { m_max_spatial_frequency = val; }
+ double maxSpatialFrequency() const { return m_max_spatial_frequency; }
+
+ std::vector<ParaMeta> parDefs() const override { return {{"MaxSpatialFrequency", "1/nm"}}; }
#ifndef SWIG
//! Used to create the Python constructor of this class
- virtual std::string pythonArguments() const = 0;
+ virtual std::string pythonArguments() const;
+
+protected:
+ std::vector<std::string> validationErrs() const;
+ AutocorrelationModel(double maxSpatFrequency);
+ double m_max_spatial_frequency; // nm^-1
#endif
};
@@ -38,56 +47,36 @@ public:
//! 14472-14478 (1993)
class K_CorrelationModel : public AutocorrelationModel {
public:
- K_CorrelationModel(double sigma = 0, double hurst = 0, double lateralCorrLength = 0);
+ K_CorrelationModel(double sigma = 0, double hurst = 0.7, double lateralCorrLength = 25,
+ double maxSpatFrequency = 0.5);
K_CorrelationModel* clone() const override;
std::string className() const override { return "K_CorrelationModel"; }
- std::vector<ParaMeta> parDefs() const final
- {
- return {{"Sigma", "nm"}, {"Hurst", ""}, {"CorrLength", "nm"}};
- }
+ std::vector<ParaMeta> parDefs() const final;
std::string validate() const override;
-#ifndef SWIG
- std::string pythonArguments() const override;
-#endif
-
//! Returns power spectral density of the surface roughness
double spectralFunction(const R3& q) const override;
- double corrFunction(const R3& r) const override;
+ double rms() const override;
//! Sets rms of roughness
- void setSigma(double sigma)
- {
- m_sigma = sigma;
- }
+ void setSigma(double sigma) { m_sigma = sigma; }
//! Returns rms of roughness
- double sigma() const override
- {
- return m_sigma;
- }
+ double sigma() const { return m_sigma; }
//! Sets hurst parameter. It describes how jagged the surface is.
- void setHurstParameter(double hurstParameter)
- {
- m_hurst_parameter = hurstParameter;
- }
+ void setHurstParameter(double hurstParameter) { m_hurst_parameter = hurstParameter; }
//! Returns hurst parameter
- double hurst() const
- {
- return m_hurst_parameter;
- }
+ double hurst() const { return m_hurst_parameter; }
//! Sets lateral correlation length
- void setLatteralCorrLength(double lateralCorrLen)
- {
- m_lateral_corr_length = lateralCorrLen;
- }
+ void setLatteralCorrLength(double lateralCorrLen) { m_lateral_corr_length = lateralCorrLen; }
//! Returns lateral correlation length
- double lateralCorrLength() const
- {
- return m_lateral_corr_length;
- }
+ double lateralCorrLength() const { return m_lateral_corr_length; }
+
+#ifndef SWIG
+ std::string pythonArguments() const override;
+#endif
private:
double m_sigma; //!< rms of roughness
diff --git a/Sample/Interface/CrosscorrelationModels.cpp b/Sample/Interface/CrosscorrelationModels.cpp
index 7f9e47f789140b88dfa524b14706c542c1b1623f..d821c3e4ce8b1af99376b434f617e0e7a51e72ef 100644
--- a/Sample/Interface/CrosscorrelationModels.cpp
+++ b/Sample/Interface/CrosscorrelationModels.cpp
@@ -27,15 +27,15 @@ double cross_spectrum(const AutocorrelationModel* up, const AutocorrelationModel
{
ASSERT(up && low);
- const double sigma_up = up->sigma();
- const double sigma_low = low->sigma();
+ const double rms_up = up->rms();
+ const double rms_low = low->rms();
- if (sigma_up <= 0 || sigma_low <= 0)
+ if (rms_up <= 0 || rms_low <= 0)
return 0;
const double spectrum_up = up->spectralFunction(qvec);
const double spectrum_low = low->spectralFunction(qvec);
- return 0.5 * ((sigma_low / sigma_up) * spectrum_up + (sigma_up / sigma_low) * spectrum_low);
+ return 0.5 * ((rms_low / rms_up) * spectrum_up + (rms_up / rms_low) * spectrum_low);
}
} // namespace
diff --git a/Sample/Interface/LayerRoughness.h b/Sample/Interface/LayerRoughness.h
index 711445d47578d001aa105634895866643faf7b35..796e868eb442862de08a9fd6045dd9a58be9974f 100644
--- a/Sample/Interface/LayerRoughness.h
+++ b/Sample/Interface/LayerRoughness.h
@@ -35,15 +35,8 @@ public:
std::string className() const final { return "LayerRoughness"; }
std::vector<const INode*> nodeChildren() const override;
-#ifndef SWIG
- bool showInScriptOrGui() const;
-#endif
-
//! Returns rms of roughness
- double sigma() const
- {
- return m_autocorrelation_model->sigma();
- }
+ double rms() const { return m_autocorrelation_model->rms(); }
void setAutocorrelationModel(const AutocorrelationModel* autocorrelation);
const AutocorrelationModel* autocorrelationModel() const
@@ -52,10 +45,7 @@ public:
}
void setInterlayerModel(const InterlayerModel* interlayer);
- const InterlayerModel* interlayerModel() const
- {
- return m_interlayer_model.get();
- }
+ const InterlayerModel* interlayerModel() const { return m_interlayer_model.get(); }
void setCrosscorrelationModel(const CrosscorrelationModel* crosscorrelation);
const CrosscorrelationModel* crosscorrelationModel() const
@@ -63,6 +53,10 @@ public:
return m_crosscorrelation_model.get();
}
+#ifndef SWIG
+ bool showInScriptOrGui() const;
+#endif
+
private:
std::unique_ptr<AutocorrelationModel> m_autocorrelation_model; // never nullptr
std::unique_ptr<InterlayerModel> m_interlayer_model; // never nullptr
diff --git a/Sample/Interface/RoughnessMap.cpp b/Sample/Interface/RoughnessMap.cpp
index d79718316c64e8cddf21420045421dcf1ed5a5ff..0ce1956f57a48c7265218e13671079bf2da20b85 100644
--- a/Sample/Interface/RoughnessMap.cpp
+++ b/Sample/Interface/RoughnessMap.cpp
@@ -70,9 +70,9 @@ double2d_t RoughnessMap::generateMap()
double2d_t RoughnessMap::mapFromHeights() const
{
const size_t z_steps = 3999;
- const double sigma = m_layerRoughness->sigma();
+ const double rms = m_layerRoughness->rms();
const double sigma_factor = m_layerRoughness->interlayerModel()->sigmaRange();
- const double z_limit = sigma * sigma_factor;
+ const double z_limit = rms * sigma_factor;
const double step = 2 * z_limit / (z_steps - 1);
// create mesh of values
@@ -83,7 +83,7 @@ double2d_t RoughnessMap::mapFromHeights() const
// fill mesh with weights
std::vector<double> z_weights(z_steps);
for (size_t i = 0; i < z_steps; i++)
- z_weights[i] = m_layerRoughness->interlayerModel()->distribution(z_points[i], sigma);
+ z_weights[i] = m_layerRoughness->interlayerModel()->distribution(z_points[i], rms);
// fill map with random values
std::discrete_distribution<int> d(z_weights.begin(), z_weights.end());
@@ -196,7 +196,7 @@ double2d_t RoughnessMap::applyHeightsToSpectrum(const double2d_t& h_map,
void RoughnessMap::createMap()
{
- if (m_layerRoughness->sigma() < 1e-10) {
+ if (m_layerRoughness->rms() < 1e-10) {
m_rough_map = double2d_t(m_y_points, std::vector<double>(m_x_points));
return;
}
diff --git a/Sim/Computation/RoughMultiLayerContribution.cpp b/Sim/Computation/RoughMultiLayerContribution.cpp
index 6d8d2e0fe55424ea3d5122c3ddd4838c93431fbd..fd532c4584dbe8b2414822c311064a34e692b3d0 100644
--- a/Sim/Computation/RoughMultiLayerContribution.cpp
+++ b/Sim/Computation/RoughMultiLayerContribution.cpp
@@ -87,15 +87,15 @@ complex_t get_sum8terms(const ReSample& re_sample, size_t i_layer, const Diffuse
const complex_t qz4_B = -qz1_B;
const LayerRoughness* roughness = re_sample.averageSlices().bottomRoughness(i_layer);
- const double sigma = roughness ? roughness->sigma() : 0.;
- const complex_t term1 = T_i_A * T_f_A * ::h_above(qz1_A * sigma);
- const complex_t term2 = T_i_A * R_f_A * ::h_above(qz2_A * sigma);
- const complex_t term3 = R_i_A * T_f_A * ::h_above(qz3_A * sigma);
- const complex_t term4 = R_i_A * R_f_A * ::h_above(qz4_A * sigma);
- const complex_t term5 = i_B->getScalarT() * f_B->getScalarT() * ::h_below(qz1_B * sigma);
- const complex_t term6 = i_B->getScalarT() * f_B->getScalarR() * ::h_below(qz2_B * sigma);
- const complex_t term7 = i_B->getScalarR() * f_B->getScalarT() * ::h_below(qz3_B * sigma);
- const complex_t term8 = i_B->getScalarR() * f_B->getScalarR() * ::h_below(qz4_B * sigma);
+ const double rms = roughness ? roughness->rms() : 0.;
+ const complex_t term1 = T_i_A * T_f_A * ::h_above(qz1_A * rms);
+ const complex_t term2 = T_i_A * R_f_A * ::h_above(qz2_A * rms);
+ const complex_t term3 = R_i_A * T_f_A * ::h_above(qz3_A * rms);
+ const complex_t term4 = R_i_A * R_f_A * ::h_above(qz4_A * rms);
+ const complex_t term5 = i_B->getScalarT() * f_B->getScalarT() * ::h_below(qz1_B * rms);
+ const complex_t term6 = i_B->getScalarT() * f_B->getScalarR() * ::h_below(qz2_B * rms);
+ const complex_t term7 = i_B->getScalarR() * f_B->getScalarT() * ::h_below(qz3_B * rms);
+ const complex_t term8 = i_B->getScalarR() * f_B->getScalarR() * ::h_below(qz4_B * rms);
return term1 + term2 + term3 + term4 + term5 + term6 + term7 + term8;
}
diff --git a/Tests/ReferenceData/MiniExamples/scatter2d/CorrelatedRoughness.int b/Tests/ReferenceData/MiniExamples/scatter2d/CorrelatedRoughness.int
index 4c971e661be5a8627444b08256939b3ceff35ff7..69884314aee33fa5dab4f5860d5e7da1c35d56e9 100644
--- a/Tests/ReferenceData/MiniExamples/scatter2d/CorrelatedRoughness.int
+++ b/Tests/ReferenceData/MiniExamples/scatter2d/CorrelatedRoughness.int
@@ -7,15 +7,15 @@ EquiDivision("phi_f (rad)", 11, -0.00872664625997165, 0.00872664625997165)
EquiDivision("alpha_f (rad)", 11, 0, 0.0174532925199433)
# data
-2.8179885826988499e+04 2.5786611270078618e+05 7.3459303383909795e+05 3.2326594450118492e+05 2.7669391052557045e+05 1.5741001599005650e+05 1.5235297237767055e+05 1.1785575366113306e+05 7.2716878694842628e+04 3.5850420947635714e+04 2.0941811226909791e+04
-4.5656415138695258e+04 4.1778884789297404e+05 1.1901706169750141e+06 5.2374733233537787e+05 4.4829108449178282e+05 2.5502935914303592e+05 2.4683348017306224e+05 1.9093979992554992e+05 1.1780663132573027e+05 5.8078159525141135e+04 3.3924305308454510e+04
-7.9861955549654478e+04 7.3079397541147587e+05 2.0818386996295466e+06 9.1613339736359159e+05 7.8414185144539387e+05 4.4608750001419755e+05 4.3174352286625939e+05 3.3396834037304611e+05 2.0604364525466738e+05 1.0157217218403005e+05 5.9324620982625631e+04
-1.4989286794671894e+05 1.3716267858557820e+06 3.9073976379877729e+06 1.7194815830702402e+06 1.4717337445089482e+06 8.3723304843237763e+05 8.1028479217053123e+05 6.2674966983118979e+05 3.8664603519392718e+05 1.9058113601888486e+05 1.1129422916629040e+05
-2.7548361485291377e+05 2.5208715421649711e+06 7.1812763759446768e+06 3.1601586392130880e+06 2.7047932583545828e+06 1.5386444479782083e+06 1.4890426071532443e+06 1.1516691180582601e+06 7.1038463788018213e+05 3.5009304584917607e+05 2.0439549575065018e+05
-3.6760864178021072e+05 3.3638810025867396e+06 9.5827700526836626e+06 4.2169313620222528e+06 3.6092534823984085e+06 2.0531136888079946e+06 1.9868583873222570e+06 1.5366101666021368e+06 9.4775028729677212e+05 4.6701741789077199e+05 2.7261594405784033e+05
-2.7548361485291377e+05 2.5208715421649711e+06 7.1812763759446768e+06 3.1601586392130884e+06 2.7047932583545828e+06 1.5386444479782083e+06 1.4890426071532443e+06 1.1516691180582601e+06 7.1038463788018213e+05 3.5009304584917607e+05 2.0439549575065018e+05
-1.4989286794671894e+05 1.3716267858557820e+06 3.9073976379877729e+06 1.7194815830702402e+06 1.4717337445089482e+06 8.3723304843237763e+05 8.1028479217053123e+05 6.2674966983118979e+05 3.8664603519392718e+05 1.9058113601888486e+05 1.1129422916629040e+05
-7.9861955549654478e+04 7.3079397541147587e+05 2.0818386996295466e+06 9.1613339736359159e+05 7.8414185144539387e+05 4.4608750001419755e+05 4.3174352286625939e+05 3.3396834037304611e+05 2.0604364525466738e+05 1.0157217218403005e+05 5.9324620982625631e+04
-4.5656415138695258e+04 4.1778884789297404e+05 1.1901706169750141e+06 5.2374733233537787e+05 4.4829108449178282e+05 2.5502935914303592e+05 2.4683348017306224e+05 1.9093979992554992e+05 1.1780663132573027e+05 5.8078159525141135e+04 3.3924305308454510e+04
-2.8179885826988499e+04 2.5786611270078618e+05 7.3459303383909795e+05 3.2326594450118492e+05 2.7669391052557045e+05 1.5741001599005650e+05 1.5235297237767055e+05 1.1785575366113306e+05 7.2716878694842628e+04 3.5850420947635714e+04 2.0941811226909791e+04
+2.8393425529724122e+04 2.5916462408006378e+05 7.3689936794983700e+05 3.3088408058728353e+05 2.9112412991256081e+05 1.6395135161943635e+05 1.6379563380402478e+05 1.2958014794853794e+05 8.1939538501573174e+04 4.1811841301041932e+04 2.5495062933303034e+04
+4.6002387346514159e+04 4.1989266668020468e+05 1.1939072860978872e+06 5.3609004430955078e+05 4.7167048850527330e+05 2.6562736750393099e+05 2.6537221894194058e+05 2.0993465960184272e+05 1.3274801090276931e+05 6.7735739943224660e+04 4.1300262421777807e+04
+8.0467128272846167e+04 7.3447396376436087e+05 2.0883748569653593e+06 9.3772314101315686e+05 8.2503664015509409e+05 4.6462512687317579e+05 4.6417016287391499e+05 3.6719180540593818e+05 2.3217609876733267e+05 1.1846219470760522e+05 7.2223215567227235e+04
+1.5102871635484416e+05 1.3785337538458090e+06 3.9196653346956377e+06 1.7600031563277177e+06 1.5484880211068213e+06 8.7202513271619973e+05 8.7114225010449137e+05 6.8909927974404080e+05 4.3568423548513826e+05 2.2227209637169796e+05 1.3549226226928187e+05
+2.7757115663978469e+05 2.5335656505239182e+06 7.2038227683876874e+06 3.2346314344170038e+06 2.8458544052486294e+06 1.6025844076570647e+06 1.6008790240767868e+06 1.2662381776372597e+06 8.0048250773676811e+05 4.0830859156854340e+05 2.4883597581790332e+05
+3.7039428259351553e+05 3.3808201719332151e+06 9.6128561937800627e+06 4.3163082293142704e+06 3.7974842960072006e+06 2.1384329493150464e+06 2.1360838842341374e+06 1.6894735011896486e+06 1.0679531710426670e+06 5.4467584088873572e+05 3.3188918480870535e+05
+2.7757115663978469e+05 2.5335656505239182e+06 7.2038227683876874e+06 3.2346314344170038e+06 2.8458544052486294e+06 1.6025844076570650e+06 1.6008790240767868e+06 1.2662381776372597e+06 8.0048250773676811e+05 4.0830859156854340e+05 2.4883597581790332e+05
+1.5102871635484416e+05 1.3785337538458090e+06 3.9196653346956377e+06 1.7600031563277177e+06 1.5484880211068213e+06 8.7202513271619973e+05 8.7114225010449137e+05 6.8909927974404080e+05 4.3568423548513826e+05 2.2227209637169796e+05 1.3549226226928187e+05
+8.0467128272846167e+04 7.3447396376436087e+05 2.0883748569653593e+06 9.3772314101315686e+05 8.2503664015509409e+05 4.6462512687317579e+05 4.6417016287391499e+05 3.6719180540593818e+05 2.3217609876733267e+05 1.1846219470760522e+05 7.2223215567227235e+04
+4.6002387346514159e+04 4.1989266668020468e+05 1.1939072860978872e+06 5.3609004430955078e+05 4.7167048850527330e+05 2.6562736750393099e+05 2.6537221894194058e+05 2.0993465960184272e+05 1.3274801090276931e+05 6.7735739943224660e+04 4.1300262421777807e+04
+2.8393425529724122e+04 2.5916462408006378e+05 7.3689936794983700e+05 3.3088408058728353e+05 2.9112412991256081e+05 1.6395135161943635e+05 1.6379563380402478e+05 1.2958014794853794e+05 8.1939538501573174e+04 4.1811841301041932e+04 2.5495062933303034e+04
diff --git a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.0.int b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.0.int
index 92d8a2c5e90e3b6a3ce13ef0a6258db319a99855..03deddeaf17bf03c25e37b92f21c27e219f87312 100644
--- a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.0.int
+++ b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.0.int
@@ -4,1504 +4,1504 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.1.int b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.1.int
index 9d4ba9dd3663413d5f59b256f14c29253cf1f638..76a67bdbbbc1e88b5bb976e42e49629612e0c53d 100644
--- a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.1.int
+++ b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.1.int
@@ -4,1504 +4,1504 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.2.int b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.2.int
index 0bee9f0bbacd2ae1cb33c3022535f7e0c87d529b..2b787aaa8ff6dba7e7cf958460c62f425eea4a0a 100644
--- a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.2.int
+++ b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.2.int
@@ -4,1504 +4,1504 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.3.int b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.3.int
index 172bb4925976f4211137258a88e7af4ae6ad2c42..7acaf8506604de2d095efce3082c9be653352f37 100644
--- a/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.3.int
+++ b/Tests/ReferenceData/MiniExamples/specular/MagneticLayerImperfect.3.int
@@ -4,1504 +4,1504 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.0.int b/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.0.int
index daa056d32f1123bf91b0ef4fcf7bb57abf7335c1..5ae2ba12d2907131455cddada3b5c295b33e8706 100644
--- a/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.0.int
+++ b/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.0.int
@@ -4,54 +4,54 @@
ListScan("alpha_i (deg)", [0.04,0.08,0.12,0.16,0.2,0.24,0.28,0.32,0.36,0.4,0.44,0.48,0.52,0.56,0.6,0.64,0.68,0.72,0.76,0.8,0.84,0.88,0.92,0.96,1,1.04,1.08,1.12,1.16,1.2,1.24,1.28,1.32,1.36,1.4,1.44,1.48,1.52,1.56,1.6,1.64,1.68,1.72,1.76,1.8,1.84,1.88,1.92,1.96,2,])
# data
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diff --git a/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.1.int b/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.1.int
index f9ddd5957810ddea44dd74a9758184ac35e0e8ee..491cd95f21d292c538d042d527361a3f4a52033d 100644
--- a/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.1.int
+++ b/Tests/ReferenceData/MiniExamples/specular/RoughnessModel.1.int
@@ -4,54 +4,54 @@
ListScan("alpha_i (deg)", [0.04,0.08,0.12,0.16,0.2,0.24,0.28,0.32,0.36,0.4,0.44,0.48,0.52,0.56,0.6,0.64,0.68,0.72,0.76,0.8,0.84,0.88,0.92,0.96,1,1.04,1.08,1.12,1.16,1.2,1.24,1.28,1.32,1.36,1.4,1.44,1.48,1.52,1.56,1.6,1.64,1.68,1.72,1.76,1.8,1.84,1.88,1.92,1.96,2,])
# data
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diff --git a/Tests/ReferenceData/MiniExamples/specular/SpecularSimulationWithRoughness.int b/Tests/ReferenceData/MiniExamples/specular/SpecularSimulationWithRoughness.int
index 67287489758f79b0e1b858a2b2275fd7cb0f357c..e82d84b66eea181a2e8cf46f4f9397278830c006 100644
--- a/Tests/ReferenceData/MiniExamples/specular/SpecularSimulationWithRoughness.int
+++ b/Tests/ReferenceData/MiniExamples/specular/SpecularSimulationWithRoughness.int
@@ -4,54 +4,54 @@
ListScan("alpha_i (rad)", [0.000698131700797732,0.00139626340159546,0.0020943951023932,0.00279252680319093,0.00349065850398866,0.00418879020478639,0.00488692190558412,0.00558505360638185,0.00628318530717959,0.00698131700797732,0.00767944870877505,0.00837758040957278,0.00907571211037051,0.00977384381116825,0.010471975511966,0.0111701072127637,0.0118682389135614,0.0125663706143592,0.0132645023151569,0.0139626340159546,0.0146607657167524,0.0153588974175501,0.0160570291183478,0.0167551608191456,0.0174532925199433,0.018151424220741,0.0188495559215388,0.0195476876223365,0.0202458193231342,0.020943951023932,0.0216420827247297,0.0223402144255274,0.0230383461263251,0.0237364778271229,0.0244346095279206,0.0251327412287183,0.0258308729295161,0.0265290046303138,0.0272271363311115,0.0279252680319093,0.028623399732707,0.0293215314335047,0.0300196631343025,0.0307177948351002,0.0314159265358979,0.0321140582366957,0.0328121899374934,0.0335103216382911,0.0342084533390889,0.0349065850398866,])
# data
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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Erf.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Erf.int
index 6f4bf3b6e63e8ae5f3b8d070b39b3caf2422b372..a3aa3f1087e8986b26f39943103b9ae9665b57a5 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Erf.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Erf.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Tanh.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Tanh.int
index 4043179ff73376a6daf8a9a8a2b30299ec1934f3..35a45d6dd55dcbf2873914514362fe54c6daa13b 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Tanh.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMM_Tanh.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Erf.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Erf.int
index 9ca1c81a78061a3027c269c5b61d708da27f8262..096206071a9322c4accf5e38cdeef885864df95b 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Erf.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Erf.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Tanh.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Tanh.int
index 1d00a709905570317eafc3356df15fc35b4a74ee..4d7eae222ba35ab883c61dac9641773f24144edb 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Tanh.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityMP_Tanh.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Erf.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Erf.int
index 5656f56aba2cf8a451fb707a25b94fb73e84b9de..9f612f803658d12be0e2d2d9a7abc85fd948bc0d 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Erf.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Erf.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Tanh.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Tanh.int
index a4e71cec4e4735360e4566781f910298e3704f46..5068bc9a963d592883b7454363a5dbabe626cd93 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Tanh.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPM_Tanh.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Erf.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Erf.int
index f23af68cb36624e8e3088155a1e91944da32b5cb..5908471efe78f9ae41f20e6f5c45eb5c53dd2919 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Erf.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Erf.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Tanh.int b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Tanh.int
index 5777fcc23201f5b78a46a1e75fb5770c2cc62a37..745999189fb69b5dd24b9b1e29cd624a5c0f3428 100644
--- a/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Tanh.int
+++ b/Tests/ReferenceData/Suite/MagneticRotationReflectivityPP_Tanh.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/MultiLayerWithRoughness.int b/Tests/ReferenceData/Suite/MultiLayerWithRoughness.int
index eab43930222273be559da99152b9497e8076911f..762dfac32a8574e5266b87090f22a1ebeae75059 100644
--- a/Tests/ReferenceData/Suite/MultiLayerWithRoughness.int
+++ b/Tests/ReferenceData/Suite/MultiLayerWithRoughness.int
@@ -7,29 +7,29 @@ EquiDivision("phi_f (rad)", 25, -0.0349065850398866, 0.0349065850398866)
EquiDivision("alpha_f (rad)", 25, 0, 0.0349065850398866)
# data
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diff --git a/Tests/ReferenceData/Suite/NCRoughnessInSpecular.int b/Tests/ReferenceData/Suite/NCRoughnessInSpecular.int
index 6a0447fe9d9fa7c773fe4cd1c27545a8f78c933a..516f797825f5dc13c1c0c4512b107e9f904cfe53 100644
--- a/Tests/ReferenceData/Suite/NCRoughnessInSpecular.int
+++ b/Tests/ReferenceData/Suite/NCRoughnessInSpecular.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/OffspecResonator.int b/Tests/ReferenceData/Suite/OffspecResonator.int
index c4756207389a2e1d0b05a047aa66dd495fec2709..4bfe6b35b841dad29a75a11f1d207eeee1499513 100644
--- a/Tests/ReferenceData/Suite/OffspecResonator.int
+++ b/Tests/ReferenceData/Suite/OffspecResonator.int
@@ -7,24 +7,24 @@ ListScan("alpha_i (rad)", [0.00349065850398866,0.00698131700797732,0.01047197551
EquiDivision("alpha_f (rad)", 25, 0.00174532925199433, 0.0890117918517108)
# data
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM.int
index 8999e06aed368155e9316d378e676fe854881768..b00438604dbb9a38393a992a39c1c86a682d24b6 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM.int
@@ -5,2003 +5,2003 @@ ListScan("alpha_i (rad)", [4.36332312998582e-05,8.72664625997165e-05,0.000130899
# data
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM_Q.int
index baa85cfb6ac76d4515d63cf1bff61942841f9918..8d38e24ed0766ad8466ebaebba55596cd9e4d0aa 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCMM_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP.int
index cecc06eef06c1b3399d03101a06209372d2a787a..3a07b231af913eb3c5c281a09dec26fae79db4a6 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP_Q.int
index 0d77bfdd0f436a4e80f435e3f902e854ebb830f7..32818a6d581ddbf8cb1789bae16108100a4fb6cc 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerNCPP_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM.int
index 5cb4b1dbeb4211851bfd0ff494d2e6f13525b372..97535357e3dbad9bf2b53749557f0dd3618c7a55 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM_Q.int
index e6af7df8f370233f6950e00052a82749a11b71d9..7da5a47c294fff4b9f0f5a22fab6b5e3ccb62128 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMM_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP.int
index 0208e6e70f237f05a5fa23fffb65556f6dc1f9d5..0d25b3248f0154830a61efa3ee85ae7c78b0db5f 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP_Q.int
index 64324cbf68a9eb686ee486972972a3d7531594f2..5103388584a9df670f25613c73ed413e57d1998b 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCMP_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM.int
index 7f8a0dee8c0bcab6f4b9f2a66f92af1ebe6cda24..e59d53f78abd60fb37ef85042ce3e9342b4bd40a 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM_Q.int
index 3270d24db2d55c6237c735d9411807353ef73abc..970d4b19dd76b60ee4134bb3cc9a2896a510d098 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPM_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP.int
index 18962372cab77b211c0fc77d6748c015361fa5b6..f0d51fc03bf5acfd7884ca5c2df2d7d14add892d 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP_Q.int
index 09b5caf9b2d0a4431aaeb9c836e9ff2e199e0d05..59a11d32c11bf82e89fd1ae7308f14fa06c96249 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipNCPP_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM.int
index 6d9d5f6d2ffaf3eb6e14ecf49dc31815f1222ae3..535c8dcaeb8210ed99ca81424ce6f8a9eb333754 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM_Q.int
index 276fbbcebaf9ffc14e5b7d46e246bd8784bd962b..c5341951e0ffb6e5685a6c42213518ec25c52ac4 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMM_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP.int
index 6b81bffcbbae3fbf6a62d12cf22db2ea8951116c..f35bf102e852d9f1c1969879683be12aa4efff27 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP_Q.int
index fa58fa11ba937766bb9b2b09eb89401e3a1d9ac3..69b90412ba9862849309af5d2ce1417dba8c86ee 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhMP_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM.int
index ee8ee35458e3565ef7116139b4540b60f5a206e7..1d08cd902d9f7d935d0f7091c9e73d6d22f73f69 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM_Q.int
index c34e8687ef80f4a02cb82cea6aa49db1c2fbdf7c..1db2486e4e8987f867c88172250f01abb83d9f06 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPM_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP.int
index 4d370d438acbe4fffe04953a011f9082e1ded40b..202e046b831b7a4808653da65cc09713ca9fa20f 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP.int
@@ -4,2004 +4,2004 @@
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP_Q.int
index b711120a5955ba789ad1f3817ce78316930bf512..404b1b0fa210024a3595314600ef5c40b95a64e8 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerSpinFlipTanhPP_Q.int
@@ -4,2004 +4,2004 @@
ListScan("q (1/nm)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM.int
index 0503d9d8e8603c12acbc402d99b573a4b7c93cb8..20c1de96d1034af8b81dc688a103f07c79ee95f2 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM_Q.int
index 1ab899f276f879a875d15dfa1472ad3f4b7665bb..2d2643ab6035cec3d450b56db830448c62d3b1b4 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhMM_Q.int
@@ -5,2003 +5,2003 @@ ListScan("q (1/nm)", [0.00356046334702656,0.00712092668727451,0.0106813900139652
# data
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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP.int
index 61de821b4a0a030b19bf2ab7ccd55ba171ac9477..de191c11da4916b98824a3d93f6af14143772ee6 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP.int
@@ -4,2004 +4,2004 @@
ListScan("alpha_i (rad)", 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diff --git a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP_Q.int b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP_Q.int
index 6c42014a8f8943760dd628edd5bb804f1068a02a..89ef37381a2ace29dce615f3168e20564e12e902 100644
--- a/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP_Q.int
+++ b/Tests/ReferenceData/Suite/PolarizedFeNiBilayerTanhPP_Q.int
@@ -5,2003 +5,2003 @@ ListScan("q (1/nm)", [0.00356046334702656,0.00712092668727451,0.0106813900139652
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diff --git a/Tests/ReferenceData/Suite/RoughnessInSpecular.int b/Tests/ReferenceData/Suite/RoughnessInSpecular.int
index eb43d6afa4ff2817e74bcac1044767e7575952b0..4f267067c187c5db9d38f009fa678a2a041ca566 100644
--- a/Tests/ReferenceData/Suite/RoughnessInSpecular.int
+++ b/Tests/ReferenceData/Suite/RoughnessInSpecular.int
@@ -6,2002 +6,2002 @@ ListScan("alpha_i (rad)", [4.36332312998582e-05,8.72664625997165e-05,0.000130899
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diff --git a/Tests/Unit/Sample/MultiLayerTest.cpp b/Tests/Unit/Sample/MultiLayerTest.cpp
index 29b10dfff5259d5a7285d300a19c0218522908ef..2b6248f0ec7f4fb2a744950ecbcfd87bfc92c670 100644
--- a/Tests/Unit/Sample/MultiLayerTest.cpp
+++ b/Tests/Unit/Sample/MultiLayerTest.cpp
@@ -87,17 +87,17 @@ TEST_F(MultiLayerTest, LayerInterfaces)
const LayerInterface* interface0 = mLayer.layerInterface(0);
EXPECT_TRUE(nullptr != interface0);
EXPECT_TRUE(nullptr != interface0->roughness());
- EXPECT_EQ(interface0->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface0->roughness()->rms(), 0.0);
const LayerInterface* interface1 = mLayer.layerInterface(1);
EXPECT_TRUE(nullptr != interface1);
EXPECT_TRUE(nullptr != interface1->roughness());
- EXPECT_EQ(interface1->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface1->roughness()->rms(), 0.0);
const LayerInterface* interface2 = mLayer.layerInterface(2);
EXPECT_TRUE(nullptr != interface2);
EXPECT_TRUE(nullptr != interface2->roughness());
- EXPECT_EQ(interface2->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface2->roughness()->rms(), 0.0);
}
TEST_F(MultiLayerTest, Clone)
@@ -119,19 +119,19 @@ TEST_F(MultiLayerTest, Clone)
const LayerInterface* interface0 = mLayerClone->layerInterface(0);
EXPECT_TRUE(nullptr != interface0);
EXPECT_TRUE(nullptr != interface0->roughness());
- EXPECT_EQ(interface0->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface0->roughness()->rms(), 0.0);
EXPECT_TRUE(nullptr == interface0->roughness()->crosscorrelationModel());
const LayerInterface* interface1 = mLayerClone->layerInterface(1);
EXPECT_TRUE(nullptr != interface1);
EXPECT_TRUE(nullptr != interface1->roughness());
- EXPECT_EQ(interface1->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface1->roughness()->rms(), 0.0);
EXPECT_TRUE(nullptr == interface1->roughness()->crosscorrelationModel());
const LayerInterface* interface2 = mLayerClone->layerInterface(2);
EXPECT_TRUE(nullptr != interface2);
EXPECT_TRUE(nullptr != interface2->roughness());
- EXPECT_EQ(interface2->roughness()->sigma(), 0.0);
+ EXPECT_EQ(interface2->roughness()->rms(), 0.0);
EXPECT_TRUE(nullptr == interface2->roughness()->crosscorrelationModel());
delete mLayerClone;
@@ -139,7 +139,7 @@ TEST_F(MultiLayerTest, Clone)
TEST_F(MultiLayerTest, WithRoughness)
{
- K_CorrelationModel autocorrelation(1.1, .3, 0.1);
+ K_CorrelationModel autocorrelation(1.1, .3, 0.1, 1e100);
ErfInterlayer interlayer;
LayerRoughness lr(&autocorrelation, &interlayer);
mLayer.addLayer(topLayer);
@@ -157,21 +157,21 @@ TEST_F(MultiLayerTest, WithRoughness)
dynamic_cast<const K_CorrelationModel*>(roughness0->autocorrelationModel());
EXPECT_TRUE(roughness0_AC);
- EXPECT_EQ(1.1, roughness0->sigma());
+ EXPECT_EQ(1.1, roughness0->rms());
EXPECT_EQ(.3, roughness0_AC->hurst());
EXPECT_EQ(0.1, roughness0_AC->lateralCorrLength());
EXPECT_TRUE(roughness1);
- EXPECT_EQ(roughness1->sigma(), 0.0);
+ EXPECT_EQ(roughness1->rms(), 0.0);
}
TEST_F(MultiLayerTest, CloneWithRoughness)
{
ErfInterlayer interlayer;
- K_CorrelationModel autocorrelation0(2.1, .3, 12.1);
+ K_CorrelationModel autocorrelation0(2.1, .3, 12.1, 1e100);
LayerRoughness lr0(&autocorrelation0, &interlayer);
- K_CorrelationModel autocorrelation1(1.1, .3, 0.1);
+ K_CorrelationModel autocorrelation1(1.1, .3, 0.1, 1e100);
LayerRoughness lr1(&autocorrelation1, &interlayer);
auto magnetization = R3{0., 1e8, 0.};
@@ -196,7 +196,7 @@ TEST_F(MultiLayerTest, CloneWithRoughness)
dynamic_cast<const K_CorrelationModel*>(roughness0->autocorrelationModel());
EXPECT_TRUE(roughness0_AC);
- EXPECT_EQ(2.1, roughness0->sigma());
+ EXPECT_EQ(2.1, roughness0->rms());
EXPECT_EQ(.3, roughness0_AC->hurst());
EXPECT_EQ(12.1, roughness0_AC->lateralCorrLength());
@@ -204,7 +204,7 @@ TEST_F(MultiLayerTest, CloneWithRoughness)
dynamic_cast<const K_CorrelationModel*>(roughness1->autocorrelationModel());
EXPECT_TRUE(roughness1_AC);
- EXPECT_EQ(1.1, roughness1->sigma());
+ EXPECT_EQ(1.1, roughness1->rms());
EXPECT_EQ(.3, roughness1_AC->hurst());
EXPECT_EQ(0.1, roughness1_AC->lateralCorrLength());
diff --git a/auto/Wrap/libBornAgainSample.py b/auto/Wrap/libBornAgainSample.py
index 9f35ceb0dcbb1e8a5928a6ffdada8b2fd91e1c3e..af45c6c8e5d2371d62dc4417a5dd3ff7b890b259 100644
--- a/auto/Wrap/libBornAgainSample.py
+++ b/auto/Wrap/libBornAgainSample.py
@@ -4191,9 +4191,9 @@ class LayerRoughness(ISampleNode):
r"""nodeChildren(LayerRoughness self) -> swig_dummy_type_const_inode_vector"""
return _libBornAgainSample.LayerRoughness_nodeChildren(self)
- def sigma(self):
- r"""sigma(LayerRoughness self) -> double"""
- return _libBornAgainSample.LayerRoughness_sigma(self)
+ def rms(self):
+ r"""rms(LayerRoughness self) -> double"""
+ return _libBornAgainSample.LayerRoughness_rms(self)
def setAutocorrelationModel(self, autocorrelation):
r"""setAutocorrelationModel(LayerRoughness self, AutocorrelationModel autocorrelation)"""
@@ -4326,17 +4326,25 @@ class AutocorrelationModel(libBornAgainBase.ICloneable, libBornAgainParam.INode)
r"""clone(AutocorrelationModel self) -> AutocorrelationModel"""
return _libBornAgainSample.AutocorrelationModel_clone(self)
- def sigma(self):
- r"""sigma(AutocorrelationModel self) -> double"""
- return _libBornAgainSample.AutocorrelationModel_sigma(self)
+ def rms(self):
+ r"""rms(AutocorrelationModel self) -> double"""
+ return _libBornAgainSample.AutocorrelationModel_rms(self)
def spectralFunction(self, k):
r"""spectralFunction(AutocorrelationModel self, R3 k) -> double"""
return _libBornAgainSample.AutocorrelationModel_spectralFunction(self, k)
- def corrFunction(self, k):
- r"""corrFunction(AutocorrelationModel self, R3 k) -> double"""
- return _libBornAgainSample.AutocorrelationModel_corrFunction(self, k)
+ def setMaxSpatialFrequency(self, val):
+ r"""setMaxSpatialFrequency(AutocorrelationModel self, double val)"""
+ return _libBornAgainSample.AutocorrelationModel_setMaxSpatialFrequency(self, val)
+
+ def maxSpatialFrequency(self):
+ r"""maxSpatialFrequency(AutocorrelationModel self) -> double"""
+ return _libBornAgainSample.AutocorrelationModel_maxSpatialFrequency(self)
+
+ def parDefs(self):
+ r"""parDefs(AutocorrelationModel self) -> std::vector< ParaMeta,std::allocator< ParaMeta > >"""
+ return _libBornAgainSample.AutocorrelationModel_parDefs(self)
__swig_destroy__ = _libBornAgainSample.delete_AutocorrelationModel
# Register AutocorrelationModel in _libBornAgainSample:
@@ -4347,9 +4355,9 @@ class K_CorrelationModel(AutocorrelationModel):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
- def __init__(self, sigma=0, hurst=0, lateralCorrLength=0):
- r"""__init__(K_CorrelationModel self, double sigma=0, double hurst=0, double lateralCorrLength=0) -> K_CorrelationModel"""
- _libBornAgainSample.K_CorrelationModel_swiginit(self, _libBornAgainSample.new_K_CorrelationModel(sigma, hurst, lateralCorrLength))
+ def __init__(self, sigma=0, hurst=0.7, lateralCorrLength=25, maxSpatFrequency=0.5):
+ r"""__init__(K_CorrelationModel self, double sigma=0, double hurst=0.7, double lateralCorrLength=25, double maxSpatFrequency=0.5) -> K_CorrelationModel"""
+ _libBornAgainSample.K_CorrelationModel_swiginit(self, _libBornAgainSample.new_K_CorrelationModel(sigma, hurst, lateralCorrLength, maxSpatFrequency))
def clone(self):
r"""clone(K_CorrelationModel self) -> K_CorrelationModel"""
@@ -4371,9 +4379,9 @@ class K_CorrelationModel(AutocorrelationModel):
r"""spectralFunction(K_CorrelationModel self, R3 q) -> double"""
return _libBornAgainSample.K_CorrelationModel_spectralFunction(self, q)
- def corrFunction(self, r):
- r"""corrFunction(K_CorrelationModel self, R3 r) -> double"""
- return _libBornAgainSample.K_CorrelationModel_corrFunction(self, r)
+ def rms(self):
+ r"""rms(K_CorrelationModel self) -> double"""
+ return _libBornAgainSample.K_CorrelationModel_rms(self)
def setSigma(self, sigma):
r"""setSigma(K_CorrelationModel self, double sigma)"""
diff --git a/auto/Wrap/libBornAgainSample_wrap.cpp b/auto/Wrap/libBornAgainSample_wrap.cpp
index c2f75f61b9fd956d19e0089ce50c2c5d7c2541ac..8082a19426021cd166ee0066659f8e8acbaa2a77 100644
--- a/auto/Wrap/libBornAgainSample_wrap.cpp
+++ b/auto/Wrap/libBornAgainSample_wrap.cpp
@@ -50738,7 +50738,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_LayerRoughness_sigma(PyObject *self, PyObject *args) {
+SWIGINTERN PyObject *_wrap_LayerRoughness_rms(PyObject *self, PyObject *args) {
PyObject *resultobj = 0;
LayerRoughness *arg1 = (LayerRoughness *) 0 ;
void *argp1 = 0 ;
@@ -50751,12 +50751,12 @@ SWIGINTERN PyObject *_wrap_LayerRoughness_sigma(PyObject *self, PyObject *args)
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_LayerRoughness, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "LayerRoughness_sigma" "', argument " "1"" of type '" "LayerRoughness const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "LayerRoughness_rms" "', argument " "1"" of type '" "LayerRoughness const *""'");
}
arg1 = reinterpret_cast< LayerRoughness * >(argp1);
{
try {
- result = (double)((LayerRoughness const *)arg1)->sigma();
+ result = (double)((LayerRoughness const *)arg1)->rms();
} catch (const std::exception& ex) {
// message shown in the Python interpreter
const std::string msg {
@@ -52085,7 +52085,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_AutocorrelationModel_sigma(PyObject *self, PyObject *args) {
+SWIGINTERN PyObject *_wrap_AutocorrelationModel_rms(PyObject *self, PyObject *args) {
PyObject *resultobj = 0;
AutocorrelationModel *arg1 = (AutocorrelationModel *) 0 ;
void *argp1 = 0 ;
@@ -52098,12 +52098,12 @@ SWIGINTERN PyObject *_wrap_AutocorrelationModel_sigma(PyObject *self, PyObject *
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_AutocorrelationModel, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_sigma" "', argument " "1"" of type '" "AutocorrelationModel const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_rms" "', argument " "1"" of type '" "AutocorrelationModel const *""'");
}
arg1 = reinterpret_cast< AutocorrelationModel * >(argp1);
{
try {
- result = (double)((AutocorrelationModel const *)arg1)->sigma();
+ result = (double)((AutocorrelationModel const *)arg1)->rms();
} catch (const std::exception& ex) {
// message shown in the Python interpreter
const std::string msg {
@@ -52163,35 +52163,65 @@ fail:
}
-SWIGINTERN PyObject *_wrap_AutocorrelationModel_corrFunction(PyObject *self, PyObject *args) {
+SWIGINTERN PyObject *_wrap_AutocorrelationModel_setMaxSpatialFrequency(PyObject *self, PyObject *args) {
PyObject *resultobj = 0;
AutocorrelationModel *arg1 = (AutocorrelationModel *) 0 ;
- R3 *arg2 = 0 ;
+ double arg2 ;
void *argp1 = 0 ;
int res1 = 0 ;
- void *argp2 = 0 ;
- int res2 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
PyObject *swig_obj[2] ;
- double result;
(void)self;
- if (!SWIG_Python_UnpackTuple(args, "AutocorrelationModel_corrFunction", 2, 2, swig_obj)) SWIG_fail;
+ if (!SWIG_Python_UnpackTuple(args, "AutocorrelationModel_setMaxSpatialFrequency", 2, 2, swig_obj)) SWIG_fail;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_AutocorrelationModel, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_corrFunction" "', argument " "1"" of type '" "AutocorrelationModel const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_setMaxSpatialFrequency" "', argument " "1"" of type '" "AutocorrelationModel *""'");
}
arg1 = reinterpret_cast< AutocorrelationModel * >(argp1);
- res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_Vec3T_double_t, 0 | 0);
- if (!SWIG_IsOK(res2)) {
- SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "AutocorrelationModel_corrFunction" "', argument " "2"" of type '" "R3 const &""'");
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "AutocorrelationModel_setMaxSpatialFrequency" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ {
+ try {
+ (arg1)->setMaxSpatialFrequency(arg2);
+ } catch (const std::exception& ex) {
+ // message shown in the Python interpreter
+ const std::string msg {
+ "BornAgain C++ Exception: " + std::string(ex.what())
+ };
+ SWIG_exception(SWIG_RuntimeError, msg.c_str());
+ }
}
- if (!argp2) {
- SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "AutocorrelationModel_corrFunction" "', argument " "2"" of type '" "R3 const &""'");
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_AutocorrelationModel_maxSpatialFrequency(PyObject *self, PyObject *args) {
+ PyObject *resultobj = 0;
+ AutocorrelationModel *arg1 = (AutocorrelationModel *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ (void)self;
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_AutocorrelationModel, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_maxSpatialFrequency" "', argument " "1"" of type '" "AutocorrelationModel const *""'");
}
- arg2 = reinterpret_cast< R3 * >(argp2);
+ arg1 = reinterpret_cast< AutocorrelationModel * >(argp1);
{
try {
- result = (double)((AutocorrelationModel const *)arg1)->corrFunction((R3 const &)*arg2);
+ result = (double)((AutocorrelationModel const *)arg1)->maxSpatialFrequency();
} catch (const std::exception& ex) {
// message shown in the Python interpreter
const std::string msg {
@@ -52207,6 +52237,40 @@ fail:
}
+SWIGINTERN PyObject *_wrap_AutocorrelationModel_parDefs(PyObject *self, PyObject *args) {
+ PyObject *resultobj = 0;
+ AutocorrelationModel *arg1 = (AutocorrelationModel *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ SwigValueWrapper< std::vector< ParaMeta,std::allocator< ParaMeta > > > result;
+
+ (void)self;
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_AutocorrelationModel, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "AutocorrelationModel_parDefs" "', argument " "1"" of type '" "AutocorrelationModel const *""'");
+ }
+ arg1 = reinterpret_cast< AutocorrelationModel * >(argp1);
+ {
+ try {
+ result = ((AutocorrelationModel const *)arg1)->parDefs();
+ } catch (const std::exception& ex) {
+ // message shown in the Python interpreter
+ const std::string msg {
+ "BornAgain C++ Exception: " + std::string(ex.what())
+ };
+ SWIG_exception(SWIG_RuntimeError, msg.c_str());
+ }
+ }
+ resultobj = SWIG_NewPointerObj((new std::vector< ParaMeta,std::allocator< ParaMeta > >(result)), SWIGTYPE_p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
SWIGINTERN PyObject *_wrap_delete_AutocorrelationModel(PyObject *self, PyObject *args) {
PyObject *resultobj = 0;
AutocorrelationModel *arg1 = (AutocorrelationModel *) 0 ;
@@ -52248,6 +52312,62 @@ SWIGINTERN PyObject *AutocorrelationModel_swigregister(PyObject *SWIGUNUSEDPARM(
}
SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_0(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ K_CorrelationModel *result = 0 ;
+
+ (void)self;
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_K_CorrelationModel" "', argument " "1"" of type '" "double""'");
+ }
+ arg1 = static_cast< double >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_K_CorrelationModel" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "new_K_CorrelationModel" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ ecode4 = SWIG_AsVal_double(swig_obj[3], &val4);
+ if (!SWIG_IsOK(ecode4)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode4), "in method '" "new_K_CorrelationModel" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ {
+ try {
+ result = (K_CorrelationModel *)new K_CorrelationModel(arg1,arg2,arg3,arg4);
+ } catch (const std::exception& ex) {
+ // message shown in the Python interpreter
+ const std::string msg {
+ "BornAgain C++ Exception: " + std::string(ex.what())
+ };
+ SWIG_exception(SWIG_RuntimeError, msg.c_str());
+ }
+ }
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_K_CorrelationModel, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_1(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
PyObject *resultobj = 0;
double arg1 ;
double arg2 ;
@@ -52295,7 +52415,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_1(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
+SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_2(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
PyObject *resultobj = 0;
double arg1 ;
double arg2 ;
@@ -52335,7 +52455,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_2(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
+SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_3(PyObject *self, Py_ssize_t nobjs, PyObject **swig_obj) {
PyObject *resultobj = 0;
double arg1 ;
double val1 ;
@@ -52367,7 +52487,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_3(PyObject *self, Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+SWIGINTERN PyObject *_wrap_new_K_CorrelationModel__SWIG_4(PyObject *self, Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
PyObject *resultobj = 0;
K_CorrelationModel *result = 0 ;
@@ -52393,14 +52513,14 @@ fail:
SWIGINTERN PyObject *_wrap_new_K_CorrelationModel(PyObject *self, PyObject *args) {
Py_ssize_t argc;
- PyObject *argv[4] = {
+ PyObject *argv[5] = {
0
};
- if (!(argc = SWIG_Python_UnpackTuple(args, "new_K_CorrelationModel", 0, 3, argv))) SWIG_fail;
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_K_CorrelationModel", 0, 4, argv))) SWIG_fail;
--argc;
if (argc == 0) {
- return _wrap_new_K_CorrelationModel__SWIG_3(self, argc, argv);
+ return _wrap_new_K_CorrelationModel__SWIG_4(self, argc, argv);
}
if (argc == 1) {
int _v = 0;
@@ -52409,7 +52529,7 @@ SWIGINTERN PyObject *_wrap_new_K_CorrelationModel(PyObject *self, PyObject *args
_v = SWIG_CheckState(res);
}
if (_v) {
- return _wrap_new_K_CorrelationModel__SWIG_2(self, argc, argv);
+ return _wrap_new_K_CorrelationModel__SWIG_3(self, argc, argv);
}
}
if (argc == 2) {
@@ -52424,7 +52544,7 @@ SWIGINTERN PyObject *_wrap_new_K_CorrelationModel(PyObject *self, PyObject *args
_v = SWIG_CheckState(res);
}
if (_v) {
- return _wrap_new_K_CorrelationModel__SWIG_1(self, argc, argv);
+ return _wrap_new_K_CorrelationModel__SWIG_2(self, argc, argv);
}
}
}
@@ -52445,7 +52565,35 @@ SWIGINTERN PyObject *_wrap_new_K_CorrelationModel(PyObject *self, PyObject *args
_v = SWIG_CheckState(res);
}
if (_v) {
- return _wrap_new_K_CorrelationModel__SWIG_0(self, argc, argv);
+ return _wrap_new_K_CorrelationModel__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v = 0;
+ {
+ int res = SWIG_AsVal_double(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[3], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_K_CorrelationModel__SWIG_0(self, argc, argv);
+ }
}
}
}
@@ -52454,6 +52602,7 @@ SWIGINTERN PyObject *_wrap_new_K_CorrelationModel(PyObject *self, PyObject *args
fail:
SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_K_CorrelationModel'.\n"
" Possible C/C++ prototypes are:\n"
+ " K_CorrelationModel::K_CorrelationModel(double,double,double,double)\n"
" K_CorrelationModel::K_CorrelationModel(double,double,double)\n"
" K_CorrelationModel::K_CorrelationModel(double,double)\n"
" K_CorrelationModel::K_CorrelationModel(double)\n"
@@ -52642,35 +52791,25 @@ fail:
}
-SWIGINTERN PyObject *_wrap_K_CorrelationModel_corrFunction(PyObject *self, PyObject *args) {
+SWIGINTERN PyObject *_wrap_K_CorrelationModel_rms(PyObject *self, PyObject *args) {
PyObject *resultobj = 0;
K_CorrelationModel *arg1 = (K_CorrelationModel *) 0 ;
- R3 *arg2 = 0 ;
void *argp1 = 0 ;
int res1 = 0 ;
- void *argp2 = 0 ;
- int res2 = 0 ;
- PyObject *swig_obj[2] ;
+ PyObject *swig_obj[1] ;
double result;
(void)self;
- if (!SWIG_Python_UnpackTuple(args, "K_CorrelationModel_corrFunction", 2, 2, swig_obj)) SWIG_fail;
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_K_CorrelationModel, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "K_CorrelationModel_corrFunction" "', argument " "1"" of type '" "K_CorrelationModel const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "K_CorrelationModel_rms" "', argument " "1"" of type '" "K_CorrelationModel const *""'");
}
arg1 = reinterpret_cast< K_CorrelationModel * >(argp1);
- res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_Vec3T_double_t, 0 | 0);
- if (!SWIG_IsOK(res2)) {
- SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "K_CorrelationModel_corrFunction" "', argument " "2"" of type '" "R3 const &""'");
- }
- if (!argp2) {
- SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "K_CorrelationModel_corrFunction" "', argument " "2"" of type '" "R3 const &""'");
- }
- arg2 = reinterpret_cast< R3 * >(argp2);
{
try {
- result = (double)((K_CorrelationModel const *)arg1)->corrFunction((R3 const &)*arg2);
+ result = (double)((K_CorrelationModel const *)arg1)->rms();
} catch (const std::exception& ex) {
// message shown in the Python interpreter
const std::string msg {
@@ -74399,7 +74538,7 @@ static PyMethodDef SwigMethods[] = {
{ "LayerRoughness_clone", _wrap_LayerRoughness_clone, METH_O, "LayerRoughness_clone(LayerRoughness self) -> LayerRoughness"},
{ "LayerRoughness_className", _wrap_LayerRoughness_className, METH_O, "LayerRoughness_className(LayerRoughness self) -> std::string"},
{ "LayerRoughness_nodeChildren", _wrap_LayerRoughness_nodeChildren, METH_O, "LayerRoughness_nodeChildren(LayerRoughness self) -> swig_dummy_type_const_inode_vector"},
- { "LayerRoughness_sigma", _wrap_LayerRoughness_sigma, METH_O, "LayerRoughness_sigma(LayerRoughness self) -> double"},
+ { "LayerRoughness_rms", _wrap_LayerRoughness_rms, METH_O, "LayerRoughness_rms(LayerRoughness self) -> double"},
{ "LayerRoughness_setAutocorrelationModel", _wrap_LayerRoughness_setAutocorrelationModel, METH_VARARGS, "LayerRoughness_setAutocorrelationModel(LayerRoughness self, AutocorrelationModel autocorrelation)"},
{ "LayerRoughness_autocorrelationModel", _wrap_LayerRoughness_autocorrelationModel, METH_O, "LayerRoughness_autocorrelationModel(LayerRoughness self) -> AutocorrelationModel"},
{ "LayerRoughness_setInterlayerModel", _wrap_LayerRoughness_setInterlayerModel, METH_VARARGS, "LayerRoughness_setInterlayerModel(LayerRoughness self, InterlayerModel interlayer)"},
@@ -74435,18 +74574,20 @@ static PyMethodDef SwigMethods[] = {
{ "MultiLayer_swigregister", MultiLayer_swigregister, METH_O, NULL},
{ "MultiLayer_swiginit", MultiLayer_swiginit, METH_VARARGS, NULL},
{ "AutocorrelationModel_clone", _wrap_AutocorrelationModel_clone, METH_O, "AutocorrelationModel_clone(AutocorrelationModel self) -> AutocorrelationModel"},
- { "AutocorrelationModel_sigma", _wrap_AutocorrelationModel_sigma, METH_O, "AutocorrelationModel_sigma(AutocorrelationModel self) -> double"},
+ { "AutocorrelationModel_rms", _wrap_AutocorrelationModel_rms, METH_O, "AutocorrelationModel_rms(AutocorrelationModel self) -> double"},
{ "AutocorrelationModel_spectralFunction", _wrap_AutocorrelationModel_spectralFunction, METH_VARARGS, "AutocorrelationModel_spectralFunction(AutocorrelationModel self, R3 k) -> double"},
- { "AutocorrelationModel_corrFunction", _wrap_AutocorrelationModel_corrFunction, METH_VARARGS, "AutocorrelationModel_corrFunction(AutocorrelationModel self, R3 k) -> double"},
+ { "AutocorrelationModel_setMaxSpatialFrequency", _wrap_AutocorrelationModel_setMaxSpatialFrequency, METH_VARARGS, "AutocorrelationModel_setMaxSpatialFrequency(AutocorrelationModel self, double val)"},
+ { "AutocorrelationModel_maxSpatialFrequency", _wrap_AutocorrelationModel_maxSpatialFrequency, METH_O, "AutocorrelationModel_maxSpatialFrequency(AutocorrelationModel self) -> double"},
+ { "AutocorrelationModel_parDefs", _wrap_AutocorrelationModel_parDefs, METH_O, "AutocorrelationModel_parDefs(AutocorrelationModel self) -> std::vector< ParaMeta,std::allocator< ParaMeta > >"},
{ "delete_AutocorrelationModel", _wrap_delete_AutocorrelationModel, METH_O, "delete_AutocorrelationModel(AutocorrelationModel self)"},
{ "AutocorrelationModel_swigregister", AutocorrelationModel_swigregister, METH_O, NULL},
- { "new_K_CorrelationModel", _wrap_new_K_CorrelationModel, METH_VARARGS, "K_CorrelationModel(double sigma=0, double hurst=0, double lateralCorrLength=0)"},
+ { "new_K_CorrelationModel", _wrap_new_K_CorrelationModel, METH_VARARGS, "K_CorrelationModel(double sigma=0, double hurst=0.7, double lateralCorrLength=25, double maxSpatFrequency=0.5)"},
{ "K_CorrelationModel_clone", _wrap_K_CorrelationModel_clone, METH_O, "K_CorrelationModel_clone(K_CorrelationModel self) -> K_CorrelationModel"},
{ "K_CorrelationModel_className", _wrap_K_CorrelationModel_className, METH_O, "K_CorrelationModel_className(K_CorrelationModel self) -> std::string"},
{ "K_CorrelationModel_parDefs", _wrap_K_CorrelationModel_parDefs, METH_O, "K_CorrelationModel_parDefs(K_CorrelationModel self) -> std::vector< ParaMeta,std::allocator< ParaMeta > >"},
{ "K_CorrelationModel_validate", _wrap_K_CorrelationModel_validate, METH_O, "K_CorrelationModel_validate(K_CorrelationModel self) -> std::string"},
{ "K_CorrelationModel_spectralFunction", _wrap_K_CorrelationModel_spectralFunction, METH_VARARGS, "K_CorrelationModel_spectralFunction(K_CorrelationModel self, R3 q) -> double"},
- { "K_CorrelationModel_corrFunction", _wrap_K_CorrelationModel_corrFunction, METH_VARARGS, "K_CorrelationModel_corrFunction(K_CorrelationModel self, R3 r) -> double"},
+ { "K_CorrelationModel_rms", _wrap_K_CorrelationModel_rms, METH_O, "K_CorrelationModel_rms(K_CorrelationModel self) -> double"},
{ "K_CorrelationModel_setSigma", _wrap_K_CorrelationModel_setSigma, METH_VARARGS, "K_CorrelationModel_setSigma(K_CorrelationModel self, double sigma)"},
{ "K_CorrelationModel_sigma", _wrap_K_CorrelationModel_sigma, METH_O, "K_CorrelationModel_sigma(K_CorrelationModel self) -> double"},
{ "K_CorrelationModel_setHurstParameter", _wrap_K_CorrelationModel_setHurstParameter, METH_VARARGS, "K_CorrelationModel_setHurstParameter(K_CorrelationModel self, double hurstParameter)"},