Commit e0021a2a authored by Wuttke, Joachim's avatar Wuttke, Joachim
Browse files

shorthand for default c'tor

parent 7ce3830b
......@@ -16,8 +16,8 @@
#define BORNAGAIN_PARAM_DISTRIB_DISTRIBUTIONS_H
#include "Base/Types/ICloneable.h"
#include "Fit/Param/RealLimits.h"
#include "Param/Node/INode.h"
#include "Fit/Param/RealLimits.h"
#include <vector>
class ParameterSample;
......@@ -44,7 +44,7 @@ public:
//! Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
std::vector<ParameterSample> equidistantSamples(size_t nbr_samples, double sigma_factor = 0.,
const RealLimits& limits = RealLimits()) const;
const RealLimits& limits = {}) const;
//! Returns equidistant samples from xmin to xmax, weighted with probabilityDensity().
std::vector<ParameterSample> equidistantSamplesInRange(size_t nbr_samples, double xmin,
......@@ -54,7 +54,7 @@ public:
//! way from mean and width parameter, taking into account limits and sigma_factor.
virtual std::vector<double>
equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const = 0;
const RealLimits& limits = {}) const = 0;
//! Returns equidistant interpolation points from xmin to xmax.
virtual std::vector<double> equidistantPointsInRange(size_t nbr_samples, double xmin,
......@@ -109,7 +109,7 @@ public:
//! Returns list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......@@ -150,7 +150,7 @@ public:
//! generate list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......@@ -194,7 +194,7 @@ public:
//! generate list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......@@ -238,7 +238,7 @@ public:
//! generate list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......@@ -281,7 +281,7 @@ public:
//! generate list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......@@ -329,7 +329,7 @@ public:
//! generate list of sample values
std::vector<double> equidistantPoints(size_t nbr_samples, double sigma_factor,
const RealLimits& limits = RealLimits()) const override;
const RealLimits& limits = {}) const override;
bool isDelta() const override;
......
......@@ -44,7 +44,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionCosine::sigma "double DistributionCosine::sigma() const
";
%feature("docstring") DistributionCosine::equidistantPoints "std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionCosine::equidistantPoints "std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
";
......@@ -106,7 +106,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionGate::max "double DistributionGate::max() const
";
%feature("docstring") DistributionGate::equidistantPoints "std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionGate::equidistantPoints "std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
Returns list of sample values.
";
......@@ -165,7 +165,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionGaussian::getStdDev "double DistributionGaussian::getStdDev() const
";
%feature("docstring") DistributionGaussian::equidistantPoints "std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionGaussian::equidistantPoints "std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
";
......@@ -258,7 +258,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionLogNormal::getScalePar "double DistributionLogNormal::getScalePar() const
";
%feature("docstring") DistributionLogNormal::equidistantPoints "std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionLogNormal::equidistantPoints "std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
";
......@@ -317,7 +317,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionLorentz::hwhm "double DistributionLorentz::hwhm() const
";
%feature("docstring") DistributionLorentz::equidistantPoints "std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionLorentz::equidistantPoints "std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
";
......@@ -382,7 +382,7 @@ Returns the distribution-specific mean.
%feature("docstring") DistributionTrapezoid::getRightWidth "double DistributionTrapezoid::getRightWidth() const
";
%feature("docstring") DistributionTrapezoid::equidistantPoints "std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
%feature("docstring") DistributionTrapezoid::equidistantPoints "std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
";
......@@ -422,7 +422,7 @@ Returns the distribution-specific probability density for value x.
Returns the distribution-specific mean.
";
%feature("docstring") IDistribution1D::equidistantSamples "std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const
%feature("docstring") IDistribution1D::equidistantSamples "std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits={}) const
Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
";
......@@ -432,7 +432,7 @@ Returns equidistant samples, using intrinsic parameters, weighted with probabil
Returns equidistant samples from xmin to xmax, weighted with probabilityDensity().
";
%feature("docstring") IDistribution1D::equidistantPoints "virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const =0
%feature("docstring") IDistribution1D::equidistantPoints "virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const =0
Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor.
";
......
......@@ -2180,8 +2180,8 @@ class IDistribution1D(libBornAgainBase.ICloneable, INode):
def equidistantSamples(self, *args):
r"""
equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits const & limits=RealLimits()) -> std::vector< ParameterSample,std::allocator< ParameterSample > >
std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const
equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits const & limits={}) -> std::vector< ParameterSample,std::allocator< ParameterSample > >
std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits={}) const
Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
......@@ -2200,8 +2200,8 @@ class IDistribution1D(libBornAgainBase.ICloneable, INode):
def equidistantPoints(self, *args):
r"""
equidistantPoints(IDistribution1D self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const =0
equidistantPoints(IDistribution1D self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const =0
Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor.
......@@ -2321,8 +2321,8 @@ class DistributionGate(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionGate self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionGate self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
Returns list of sample values.
......@@ -2424,8 +2424,8 @@ class DistributionLorentz(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionLorentz self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionLorentz self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
......@@ -2527,8 +2527,8 @@ class DistributionGaussian(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionGaussian self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionGaussian self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
......@@ -2637,8 +2637,8 @@ class DistributionLogNormal(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionLogNormal self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionLogNormal self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
......@@ -2740,8 +2740,8 @@ class DistributionCosine(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionCosine self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionCosine self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
......@@ -2859,8 +2859,8 @@ class DistributionTrapezoid(IDistribution1D):
def equidistantPoints(self, *args):
r"""
equidistantPoints(DistributionTrapezoid self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t
std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override
equidistantPoints(DistributionTrapezoid self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t
std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override
generate list of sample values
......
......@@ -34848,8 +34848,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "IDistribution1D_equidistantSamples", _wrap_IDistribution1D_equidistantSamples, METH_VARARGS, "\n"
"IDistribution1D_equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits const & limits=RealLimits()) -> std::vector< ParameterSample,std::allocator< ParameterSample > >\n"
"std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const\n"
"IDistribution1D_equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits const & limits={}) -> std::vector< ParameterSample,std::allocator< ParameterSample > >\n"
"std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits={}) const\n"
"\n"
"Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity(). \n"
"\n"
......@@ -34862,8 +34862,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "IDistribution1D_equidistantPoints", _wrap_IDistribution1D_equidistantPoints, METH_VARARGS, "\n"
"IDistribution1D_equidistantPoints(IDistribution1D self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const =0\n"
"IDistribution1D_equidistantPoints(IDistribution1D self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const =0\n"
"\n"
"Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor. \n"
"\n"
......@@ -34935,8 +34935,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionGate_equidistantPoints", _wrap_DistributionGate_equidistantPoints, METH_VARARGS, "\n"
"DistributionGate_equidistantPoints(DistributionGate self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionGate_equidistantPoints(DistributionGate self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"Returns list of sample values. \n"
"\n"
......@@ -34997,8 +34997,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionLorentz_equidistantPoints", _wrap_DistributionLorentz_equidistantPoints, METH_VARARGS, "\n"
"DistributionLorentz_equidistantPoints(DistributionLorentz self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionLorentz_equidistantPoints(DistributionLorentz self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"generate list of sample values \n"
"\n"
......@@ -35059,8 +35059,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionGaussian_equidistantPoints", _wrap_DistributionGaussian_equidistantPoints, METH_VARARGS, "\n"
"DistributionGaussian_equidistantPoints(DistributionGaussian self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionGaussian_equidistantPoints(DistributionGaussian self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"generate list of sample values \n"
"\n"
......@@ -35125,8 +35125,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionLogNormal_equidistantPoints", _wrap_DistributionLogNormal_equidistantPoints, METH_VARARGS, "\n"
"DistributionLogNormal_equidistantPoints(DistributionLogNormal self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionLogNormal_equidistantPoints(DistributionLogNormal self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"generate list of sample values \n"
"\n"
......@@ -35187,8 +35187,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionCosine_equidistantPoints", _wrap_DistributionCosine_equidistantPoints, METH_VARARGS, "\n"
"DistributionCosine_equidistantPoints(DistributionCosine self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionCosine_equidistantPoints(DistributionCosine self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"generate list of sample values \n"
"\n"
......@@ -35259,8 +35259,8 @@ static PyMethodDef SwigMethods[] = {
"\n"
""},
{ "DistributionTrapezoid_equidistantPoints", _wrap_DistributionTrapezoid_equidistantPoints, METH_VARARGS, "\n"
"DistributionTrapezoid_equidistantPoints(DistributionTrapezoid self, size_t nbr_samples, double sigma_factor, RealLimits const & limits=RealLimits()) -> vdouble1d_t\n"
"std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const override\n"
"DistributionTrapezoid_equidistantPoints(DistributionTrapezoid self, size_t nbr_samples, double sigma_factor, RealLimits const & limits={}) -> vdouble1d_t\n"
"std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits={}) const override\n"
"\n"
"generate list of sample values \n"
"\n"
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