diff --git a/Core/Export/SampleToPython.cpp b/Core/Export/SampleToPython.cpp
index ba6216655433ff659fb60b360be5bbe63c7f071b..85853f600e2057f5125b335630762dd8f6834c8f 100644
--- a/Core/Export/SampleToPython.cpp
+++ b/Core/Export/SampleToPython.cpp
@@ -26,7 +26,7 @@
#include "Core/Multilayer/LayerInterface.h"
#include "Core/Multilayer/LayerRoughness.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/ParameterUtils.h"
+#include "Param/Varia/ParameterUtils.h"
#include "Core/Particle/Crystal.h"
#include "Core/Particle/MesoCrystal.h"
#include "Core/Particle/Particle.h"
diff --git a/Core/Export/SimulationToPython.cpp b/Core/Export/SimulationToPython.cpp
index 896e38e2d05404c47fe3a06fdd150048c90b5b88..2d7c96737647c37b8e614c4807691742178ec5e9 100644
--- a/Core/Export/SimulationToPython.cpp
+++ b/Core/Export/SimulationToPython.cpp
@@ -25,8 +25,8 @@
#include "Core/Export/INodeUtils.h"
#include "Core/Export/SampleToPython.h"
#include "Core/Instrument/PyFmt2.h"
-#include "Core/Parametrization/ParameterUtils.h"
-#include "Core/Parametrization/PyFmtLimits.h"
+#include "Param/Varia/ParameterUtils.h"
+#include "Param/Varia/PyFmtLimits.h"
#include "Core/Resolution/ConvolutionDetectorResolution.h"
#include "Core/Resolution/ResolutionFunction2DGaussian.h"
#include "Core/Scan/ISpecularScan.h"
diff --git a/Core/Histo/IHistogram.cpp b/Core/Histo/IHistogram.cpp
index 807cde9fb0f74acded94f7acb911238e88d469f9..3d68110312a694218257d9efc697d4b5db620c0f 100644
--- a/Core/Histo/IHistogram.cpp
+++ b/Core/Histo/IHistogram.cpp
@@ -15,7 +15,7 @@
#include "Core/Histo/IHistogram.h"
#include "Core/Histo/Histogram1D.h"
#include "Core/Histo/Histogram2D.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h" // TODO rm
+#include "Core/Histo/IntensityDataIOFactory.h" // TODO rm
#include "Fit/TestEngine/Numeric.h"
#include <memory>
diff --git a/Core/InputOutput/IntensityDataIOFactory.cpp b/Core/Histo/IntensityDataIOFactory.cpp
similarity index 95%
rename from Core/InputOutput/IntensityDataIOFactory.cpp
rename to Core/Histo/IntensityDataIOFactory.cpp
index bf1b41e0e00310cf7b27feb126b0be065a2b8a6f..87a357edac9f880679925930ef38d294a8974f18 100644
--- a/Core/InputOutput/IntensityDataIOFactory.cpp
+++ b/Core/Histo/IntensityDataIOFactory.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/InputOutput/IntensityDataIOFactory.cpp
+//! @file Core/Histo/IntensityDataIOFactory.cpp
//! @brief Implements class OutputDataIOFactory.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,7 +12,7 @@
//
// ************************************************************************** //
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Base/Utils/FileSystemUtils.h"
#include "Core/Histo/IHistogram.h"
#include "Core/InputOutput/OutputDataReadFactory.h"
diff --git a/Core/InputOutput/IntensityDataIOFactory.h b/Core/Histo/IntensityDataIOFactory.h
similarity index 97%
rename from Core/InputOutput/IntensityDataIOFactory.h
rename to Core/Histo/IntensityDataIOFactory.h
index 3442df1996e361c5db60129f7e85ea26c2fa4064..715cda6fd79372ef716296fb4e86c372e52cd01e 100644
--- a/Core/InputOutput/IntensityDataIOFactory.h
+++ b/Core/Histo/IntensityDataIOFactory.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/InputOutput/IntensityDataIOFactory.h
+//! @file Core/Histo/IntensityDataIOFactory.h
//! @brief Defines class IntensityDataIOFactory.
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Instrument/PyFmt2.cpp b/Core/Instrument/PyFmt2.cpp
index 82a1b2f6e99e1e5254eea765e98c492570de57e6..c1e3d9c8d38a3de3d40ddef5e333f3a4beb067f8 100644
--- a/Core/Instrument/PyFmt2.cpp
+++ b/Core/Instrument/PyFmt2.cpp
@@ -24,9 +24,9 @@
#include "Core/Mask/Line.h"
#include "Core/Mask/Polygon.h"
#include "Core/Mask/Rectangle.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterDistribution.h"
-#include "Core/Parametrization/PyFmtLimits.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/ParameterDistribution.h"
+#include "Param/Varia/PyFmtLimits.h"
#include "Fit/Tools/StringUtils.h"
#include "Param/Base/IParameterized.h"
#include "Param/Base/ParameterPool.h"
diff --git a/Core/Particle/ParticleDistribution.cpp b/Core/Particle/ParticleDistribution.cpp
index 9956ae434d38f8c810fb54e7109fa30b7a41be46..e748f4d83dd9daa1a2968240cd93dddd4cca5b36 100644
--- a/Core/Particle/ParticleDistribution.cpp
+++ b/Core/Particle/ParticleDistribution.cpp
@@ -14,9 +14,9 @@
#include "Core/Particle/ParticleDistribution.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/ParameterUtils.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Varia/ParameterUtils.h"
#include "Core/Particle/IParticle.h"
#include "Param/Base/ParameterPool.h"
#include "Param/Base/RealParameter.h"
diff --git a/Core/Particle/ParticleDistribution.h b/Core/Particle/ParticleDistribution.h
index 3bccc3f7bd9d39ff06fa85b49b503252e51f25cd..4c32826ca630d73d118faaa1500c31f28a571db8 100644
--- a/Core/Particle/ParticleDistribution.h
+++ b/Core/Particle/ParticleDistribution.h
@@ -16,7 +16,7 @@
#define BORNAGAIN_CORE_PARTICLE_PARTICLEDISTRIBUTION_H
#include "Base/Types/SafePointerVector.h"
-#include "Core/Parametrization/ParameterDistribution.h"
+#include "Param/Distrib/ParameterDistribution.h"
#include "Core/Particle/IAbstractParticle.h"
class IParticle;
diff --git a/Core/Resolution/ScanResolution.cpp b/Core/Resolution/ScanResolution.cpp
index ffda98add96143d8729a341ab5dfccad2e9115ec..942ede56f2a36f58c56cb5bdfce20b580cc7779d 100644
--- a/Core/Resolution/ScanResolution.cpp
+++ b/Core/Resolution/ScanResolution.cpp
@@ -14,7 +14,7 @@
#include "Core/Resolution/ScanResolution.h"
#include "Base/Utils/PyFmt.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/RangedDistributions.h"
namespace
{
diff --git a/Core/Resolution/ScanResolution.h b/Core/Resolution/ScanResolution.h
index 75841157aeedb0bbca1748c840c4de1ce433a058..6f88ed3e19beb2b0edd0160a6f95873d843a23fa 100644
--- a/Core/Resolution/ScanResolution.h
+++ b/Core/Resolution/ScanResolution.h
@@ -16,7 +16,7 @@
#define BORNAGAIN_CORE_DETECTOR_SCANRESOLUTION_H
#include "Base/Types/ICloneable.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Varia/ParameterSample.h"
#include <memory>
#include <string>
#include <vector>
diff --git a/Core/Scan/AngularSpecScan.cpp b/Core/Scan/AngularSpecScan.cpp
index 41ae500566c79d3f14297bdfdaca2966f65b5e73..372a1319ae08fc07f9111b4eccb0659e38483094 100644
--- a/Core/Scan/AngularSpecScan.cpp
+++ b/Core/Scan/AngularSpecScan.cpp
@@ -19,8 +19,8 @@
#include "Core/Beam/IFootprintFactor.h"
#include "Core/Instrument/PyFmt2.h"
#include "Core/Multilayer/SpecularSimulationElement.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Resolution/ScanResolution.h"
#include "Fit/Tools/RealLimits.h"
diff --git a/Core/Scan/QSpecScan.cpp b/Core/Scan/QSpecScan.cpp
index dc974ef0f1b2379099da8a5f359d00feda28ea15..9dede6897b54dcfea959d9958d3086ef967a7dd4 100644
--- a/Core/Scan/QSpecScan.cpp
+++ b/Core/Scan/QSpecScan.cpp
@@ -18,8 +18,8 @@
#include "Core/Axis/PointwiseAxis.h"
#include "Core/Instrument/PyFmt2.h"
#include "Core/Multilayer/SpecularSimulationElement.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Resolution/ScanResolution.h"
#include "Fit/Tools/RealLimits.h"
diff --git a/Core/Simulation/DepthProbeSimulation.cpp b/Core/Simulation/DepthProbeSimulation.cpp
index a9b674480ddae224aec7f9c7d2d904f560be12c9..acf33899a1ef025e2397ba6662426b30f6717eca 100644
--- a/Core/Simulation/DepthProbeSimulation.cpp
+++ b/Core/Simulation/DepthProbeSimulation.cpp
@@ -23,7 +23,7 @@
#include "Core/Histo/Histogram1D.h"
#include "Core/Material/MaterialUtils.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Param/Base/ParameterPool.h"
#include "Param/Base/RealParameter.h"
diff --git a/Core/Simulation/OffSpecSimulation.cpp b/Core/Simulation/OffSpecSimulation.cpp
index 4d3ee5b1dbfc0627e466305e12bdb21d1cdca8d3..0eceb614529458297968f36e5af520362eb5c17a 100644
--- a/Core/Simulation/OffSpecSimulation.cpp
+++ b/Core/Simulation/OffSpecSimulation.cpp
@@ -17,7 +17,7 @@
#include "Core/Detector/SimpleUnitConverters.h"
#include "Core/Histo/Histogram2D.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Core/Pixel/SimulationElement.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Param/Base/ParameterPool.h"
diff --git a/Core/Simulation/Simulation.cpp b/Core/Simulation/Simulation.cpp
index 571451835d0c8d96fc9d5098652024023791398c..7d9917441af6e1403bca9386727af4b080926b7a 100644
--- a/Core/Simulation/Simulation.cpp
+++ b/Core/Simulation/Simulation.cpp
@@ -18,7 +18,7 @@
#include "Core/Detector/DetectorFunctions.h"
#include "Core/Multilayer/MultiLayer.h"
#include "Core/Multilayer/MultiLayerUtils.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Varia/ParameterSample.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Core/Simulation/MPISimulation.h"
#include "Core/Simulation/UnitConverterUtils.h"
diff --git a/Core/Simulation/Simulation.h b/Core/Simulation/Simulation.h
index fa3dc1ffb558761d8059f5d605dc322f9f8cd7ee..a002320c1e70227ab29d693cffc97694c56b12d0 100644
--- a/Core/Simulation/Simulation.h
+++ b/Core/Simulation/Simulation.h
@@ -19,7 +19,7 @@
#include "Core/Detector/IDetector2D.h"
#include "Core/Instrument/Instrument.h"
#include "Core/Instrument/SimulationResult.h"
-#include "Core/Parametrization/DistributionHandler.h"
+#include "Param/Distrib/DistributionHandler.h"
#include "Core/RT/SimulationOptions.h"
#include "Core/SampleBuilderEngine/SampleProvider.h"
#include "Param/Node/INode.h"
diff --git a/Core/Simulation/SpecularSimulation.cpp b/Core/Simulation/SpecularSimulation.cpp
index dc52c912b3bbef3d45b82bbf92b656a4e91091d6..c5a81c18dfbb764dd8d410ac7aac00e9f683805e 100644
--- a/Core/Simulation/SpecularSimulation.cpp
+++ b/Core/Simulation/SpecularSimulation.cpp
@@ -23,7 +23,7 @@
#include "Core/Material/MaterialUtils.h"
#include "Core/Multilayer/MultiLayer.h"
#include "Core/Multilayer/SpecularSimulationElement.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Core/Scan/AngularSpecScan.h"
#include "Core/Scan/ISpecularScan.h"
diff --git a/Core/Simulation/StandardSimulations.cpp b/Core/Simulation/StandardSimulations.cpp
index 993294dd16baa440a40c2299f5c22d336d7abd9d..7f559b7cce55a2eb33f60df9a88af3cf2f70056a 100644
--- a/Core/Simulation/StandardSimulations.cpp
+++ b/Core/Simulation/StandardSimulations.cpp
@@ -24,9 +24,9 @@
#include "Core/Mask/Line.h"
#include "Core/Mask/Polygon.h"
#include "Core/Mask/Rectangle.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Resolution/ResolutionFunction2DGaussian.h"
#include "Core/Resolution/ScanResolution.h"
#include "Core/Scan/AngularSpecScan.h"
diff --git a/Core/SoftParticle/FormFactorSphereLogNormalRadius.cpp b/Core/SoftParticle/FormFactorSphereLogNormalRadius.cpp
index 4e101348acaa11d4e0df0163843233cd01c8c0a8..83a36a1ecfab88adbc0658f3916f39bcc4084d8e 100644
--- a/Core/SoftParticle/FormFactorSphereLogNormalRadius.cpp
+++ b/Core/SoftParticle/FormFactorSphereLogNormalRadius.cpp
@@ -14,8 +14,8 @@
#include "Core/SoftParticle/FormFactorSphereLogNormalRadius.h"
#include "Core/LibFF/SomeFormFactors.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
#include "Core/Shapes/TruncatedEllipsoid.h"
FormFactorSphereLogNormalRadius::FormFactorSphereLogNormalRadius(const std::vector<double> P,
diff --git a/Core/StandardSamples/ParticleDistributionsBuilder.cpp b/Core/StandardSamples/ParticleDistributionsBuilder.cpp
index 3c72ba4821a17746b0e34b239f578e585f0afcd3..86b4da9d39ea98c519be420295fa95770fb2f9a5 100644
--- a/Core/StandardSamples/ParticleDistributionsBuilder.cpp
+++ b/Core/StandardSamples/ParticleDistributionsBuilder.cpp
@@ -22,9 +22,9 @@
#include "Core/HardParticle/FormFactorPyramid.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
+#include "Param/Varia/ParameterSample.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleDistribution.h"
#include "Core/StandardSamples/ReferenceMaterials.h"
diff --git a/Core/StandardSamples/SizeDistributionModelsBuilder.cpp b/Core/StandardSamples/SizeDistributionModelsBuilder.cpp
index f68b34ab4819441d0b69a2cc289851404f4485ed..bb50518adc5cb2586b888b8a654b19265b24ab9b 100644
--- a/Core/StandardSamples/SizeDistributionModelsBuilder.cpp
+++ b/Core/StandardSamples/SizeDistributionModelsBuilder.cpp
@@ -19,8 +19,8 @@
#include "Core/HardParticle/FormFactorCylinder.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleDistribution.h"
#include "Core/StandardSamples/ReferenceMaterials.h"
diff --git a/Examples/cpp/CylindersAndPrisms/CylindersAndPrisms.cpp b/Examples/cpp/CylindersAndPrisms/CylindersAndPrisms.cpp
index 6a44e7e05c20e170bb28d2cb1b67f095cfc1b8a1..2b30ed3d78372c2979223b44879d6d316abbfbc3 100644
--- a/Examples/cpp/CylindersAndPrisms/CylindersAndPrisms.cpp
+++ b/Examples/cpp/CylindersAndPrisms/CylindersAndPrisms.cpp
@@ -18,7 +18,7 @@
#include "Core/HardParticle/FormFactorCylinder.h"
#include "Core/HardParticle/FormFactorPrism3.h"
#include "Core/Histo/Histogram2D.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Material/MaterialFactoryFuncs.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
diff --git a/GUI/coregui/Models/ApplicationModels.cpp b/GUI/coregui/Models/ApplicationModels.cpp
index 8ffb4fb2551627bf705ca3bf5bf11b1c84db5f53..20fbd45ba829d0a9b8ddb09036dbd604b77b74e3 100644
--- a/GUI/coregui/Models/ApplicationModels.cpp
+++ b/GUI/coregui/Models/ApplicationModels.cpp
@@ -13,7 +13,7 @@
// ************************************************************************** //
#include "GUI/coregui/Models/ApplicationModels.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Multilayer/MultiLayer.h"
#include "Core/Scattering/ISample.h"
#include "Core/Simulation/OffSpecSimulation.h"
diff --git a/GUI/coregui/Models/BeamDistributionItem.cpp b/GUI/coregui/Models/BeamDistributionItem.cpp
index 5df185b2c1948a40d292bc052c104441f72f6a8a..8b8ea14a38bec75b1b8cc1077a32fc0cf709e521 100644
--- a/GUI/coregui/Models/BeamDistributionItem.cpp
+++ b/GUI/coregui/Models/BeamDistributionItem.cpp
@@ -15,8 +15,8 @@
#include "GUI/coregui/Models/BeamDistributionItem.h"
#include "Base/Const/Units.h"
#include "Base/Utils/Assert.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterDistribution.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/ParameterDistribution.h"
#include "GUI/coregui/Models/GroupItem.h"
#include "GUI/coregui/Models/ParameterTranslators.h"
#include "GUI/coregui/Models/RealLimitsItems.h"
diff --git a/GUI/coregui/Models/DataItem.cpp b/GUI/coregui/Models/DataItem.cpp
index e24f550fe9db8ec4ba154c8dce75c1d2da09ed2c..1f6076b433fba893fb982dab1c5cf5138f7345b7 100644
--- a/GUI/coregui/Models/DataItem.cpp
+++ b/GUI/coregui/Models/DataItem.cpp
@@ -13,7 +13,7 @@
// ************************************************************************** //
#include "GUI/coregui/Models/DataItem.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Models/ComboProperty.h"
#include "GUI/coregui/utils/GUIHelpers.h"
#include "GUI/coregui/utils/ImportDataInfo.h"
diff --git a/GUI/coregui/Models/DistributionItems.cpp b/GUI/coregui/Models/DistributionItems.cpp
index e75fd3cad58d4aa22064e9b2bd96b1fa1a72ed7f..963106272dc31216bf0d628d34bb4cab6c08e528 100644
--- a/GUI/coregui/Models/DistributionItems.cpp
+++ b/GUI/coregui/Models/DistributionItems.cpp
@@ -13,8 +13,8 @@
// ************************************************************************** //
#include "GUI/coregui/Models/DistributionItems.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "GUI/coregui/Models/RealLimitsItems.h"
#include <cmath>
diff --git a/GUI/coregui/Models/ParticleDistributionItem.cpp b/GUI/coregui/Models/ParticleDistributionItem.cpp
index 2c04c5e2113a672c1485be9c80ce8692b4bdfb97..9b048c67f0fde2c39ebd64f38f8ed0018765b7fc 100644
--- a/GUI/coregui/Models/ParticleDistributionItem.cpp
+++ b/GUI/coregui/Models/ParticleDistributionItem.cpp
@@ -14,8 +14,8 @@
#include "GUI/coregui/Models/ParticleDistributionItem.h"
#include "Base/Const/Units.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterUtils.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterUtils.h"
#include "GUI/coregui/Models/ComboProperty.h"
#include "GUI/coregui/Models/DistributionItems.h"
#include "GUI/coregui/Models/ParameterTreeUtils.h"
diff --git a/GUI/coregui/Models/PointwiseAxisItem.cpp b/GUI/coregui/Models/PointwiseAxisItem.cpp
index 2cfaac98da8ecab91b6928d43c75d0c869638302..a748cea0043fe04c54c4b4fe6c64c1ee680712b7 100644
--- a/GUI/coregui/Models/PointwiseAxisItem.cpp
+++ b/GUI/coregui/Models/PointwiseAxisItem.cpp
@@ -15,7 +15,7 @@
#include "GUI/coregui/Models/PointwiseAxisItem.h"
#include "Core/Axis/PointwiseAxis.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Unit/IUnitConverter.h"
#include "GUI/coregui/Models/InstrumentItems.h"
diff --git a/GUI/coregui/Models/TransformFromDomain.cpp b/GUI/coregui/Models/TransformFromDomain.cpp
index 2e2e39abf2c30027536ba41a608e50f10da89463..db7ee365a722d692674da6d1346ed298a8d98b9e 100644
--- a/GUI/coregui/Models/TransformFromDomain.cpp
+++ b/GUI/coregui/Models/TransformFromDomain.cpp
@@ -35,9 +35,9 @@
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/LayerInterface.h"
#include "Core/Multilayer/LayerRoughness.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleDistribution.h"
#include "Core/Resolution/ConvolutionDetectorResolution.h"
diff --git a/GUI/coregui/Models/TransformToDomain.cpp b/GUI/coregui/Models/TransformToDomain.cpp
index b6247c2418514dbaac25fa7dec75a7c7b8d99442..ee8ffe76d5fcbb007d3ef4cfb9f89e4ad4a0f00a 100644
--- a/GUI/coregui/Models/TransformToDomain.cpp
+++ b/GUI/coregui/Models/TransformToDomain.cpp
@@ -15,9 +15,9 @@
#include "GUI/coregui/Models/TransformToDomain.h"
#include "Base/Const/Units.h"
#include "Core/Aggregate/InterferenceFunctions.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Particle/MesoCrystal.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleCoreShell.h"
diff --git a/GUI/coregui/Models/TransformToDomain.h b/GUI/coregui/Models/TransformToDomain.h
index 73d327e253017204229dc20e2ffaa7ad72c83504..35290e9dae36878a73aaef1326cc48108f07bfa8 100644
--- a/GUI/coregui/Models/TransformToDomain.h
+++ b/GUI/coregui/Models/TransformToDomain.h
@@ -22,7 +22,7 @@
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/LayerRoughness.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h" // for IDistribution1D
+#include "Param/Distrib/Distributions.h" // for IDistribution1D
#include "Core/Particle/IParticle.h"
#include "Core/Particle/ParticleDistribution.h"
#include <memory>
diff --git a/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp b/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
index 06adbf03bb6d15158a2606a066e6db3bed687ac3..a6e79ed041fdf441773ed68cdb527d071ab1bd08 100644
--- a/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
+++ b/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
@@ -14,7 +14,7 @@
#include "GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.h"
#include "Core/Axis/PointwiseAxis.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Models/AxesItems.h"
#include "GUI/coregui/Models/InstrumentItems.h"
#include "GUI/coregui/Models/IntensityDataItem.h"
diff --git a/GUI/coregui/Views/InfoWidgets/DistributionWidget.cpp b/GUI/coregui/Views/InfoWidgets/DistributionWidget.cpp
index 0f97b2d672fa63b5385e118bf352cec6b7a75611..1cb2773bd37145f41048ca0b105bb6a99f5c6e40 100644
--- a/GUI/coregui/Views/InfoWidgets/DistributionWidget.cpp
+++ b/GUI/coregui/Views/InfoWidgets/DistributionWidget.cpp
@@ -13,7 +13,7 @@
// ************************************************************************** //
#include "GUI/coregui/Views/InfoWidgets/DistributionWidget.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "GUI/coregui/Models/DistributionItems.h"
#include "GUI/coregui/Models/RealLimitsItems.h"
#include "GUI/coregui/Views/InfoWidgets/WarningSign.h"
diff --git a/GUI/coregui/Views/IntensityDataWidgets/SavePlotAssistant.cpp b/GUI/coregui/Views/IntensityDataWidgets/SavePlotAssistant.cpp
index 35d7c36cecc0358f4981c7f00ff64f0655a54f7f..6467194d6d85ba4d68f69eb6ea7251bc8da49784 100644
--- a/GUI/coregui/Views/IntensityDataWidgets/SavePlotAssistant.cpp
+++ b/GUI/coregui/Views/IntensityDataWidgets/SavePlotAssistant.cpp
@@ -14,7 +14,7 @@
#include "GUI/coregui/Views/IntensityDataWidgets/SavePlotAssistant.h"
#include "Base/Utils/Assert.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Views/IntensityDataWidgets/ColorMap.h"
#include <QFileDialog>
#include <QMessageBox>
diff --git a/GUI/coregui/mainwindow/OutputDataIOService.cpp b/GUI/coregui/mainwindow/OutputDataIOService.cpp
index abf7d89d9054213191fcb113dd7cfd0d731957d7..f834b9124395064514cdff8b4641d3209740e393 100644
--- a/GUI/coregui/mainwindow/OutputDataIOService.cpp
+++ b/GUI/coregui/mainwindow/OutputDataIOService.cpp
@@ -13,7 +13,7 @@
// ************************************************************************** //
#include "GUI/coregui/mainwindow/OutputDataIOService.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Models/ApplicationModels.h"
#include "GUI/coregui/Models/JobItem.h"
#include "GUI/coregui/Models/ModelPath.h"
diff --git a/Core/Parametrization/DistributionHandler.cpp b/Param/Distrib/DistributionHandler.cpp
similarity index 93%
rename from Core/Parametrization/DistributionHandler.cpp
rename to Param/Distrib/DistributionHandler.cpp
index 9af3eefa9680ac23a820fedf7f8770f517bd1305..b66d1ef52f419f67f4792709523a80e5b440ec13 100644
--- a/Core/Parametrization/DistributionHandler.cpp
+++ b/Param/Distrib/DistributionHandler.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/DistributionHandler.cpp
+//! @file Param/Distrib/DistributionHandler.cpp
//! @brief Implements class DistributionHandler.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,10 +12,10 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/DistributionHandler.h"
+#include "Param/Distrib/DistributionHandler.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
#include "Param/Base/ParameterPool.h"
DistributionHandler::DistributionHandler() : m_nbr_combinations(1)
diff --git a/Core/Parametrization/DistributionHandler.h b/Param/Distrib/DistributionHandler.h
similarity index 95%
rename from Core/Parametrization/DistributionHandler.h
rename to Param/Distrib/DistributionHandler.h
index a178d085457b5cb27e9bedf09075bcc7beb319d9..7e6d7a459915022c5d06fcb3fd96c3896b4c7e64 100644
--- a/Core/Parametrization/DistributionHandler.h
+++ b/Param/Distrib/DistributionHandler.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/DistributionHandler.h
+//! @file Param/Distrib/DistributionHandler.h
//! @brief Defines class DistributionHandler.
//!
//! @homepage http://www.bornagainproject.org
@@ -15,7 +15,7 @@
#ifndef BORNAGAIN_CORE_PARAMETRIZATION_DISTRIBUTIONHANDLER_H
#define BORNAGAIN_CORE_PARAMETRIZATION_DISTRIBUTIONHANDLER_H
-#include "Core/Parametrization/ParameterDistribution.h"
+#include "Param/Distrib/ParameterDistribution.h"
#include <vector>
//! Provides the functionality to average over parameter distributions with weights.
diff --git a/Core/Parametrization/Distributions.cpp b/Param/Distrib/Distributions.cpp
similarity index 99%
rename from Core/Parametrization/Distributions.cpp
rename to Param/Distrib/Distributions.cpp
index c9e433474e6ca450615803b792fa99b40000c2f5..f04024d352be661c159c54046b0f851cdb52de2c 100644
--- a/Core/Parametrization/Distributions.cpp
+++ b/Param/Distrib/Distributions.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/Distributions.cpp
+//! @file Param/Distrib/Distributions.cpp
//! @brief Implements classes representing one-dimensional distributions.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,10 +12,10 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Base/Const/MathConstants.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Varia/ParameterSample.h"
#include "Param/Base/ParameterPool.h"
#include "Param/Base/RealParameter.h"
#include <algorithm>
diff --git a/Core/Parametrization/Distributions.h b/Param/Distrib/Distributions.h
similarity index 99%
rename from Core/Parametrization/Distributions.h
rename to Param/Distrib/Distributions.h
index f4c1512b377331971e6d611273d8b78e79373d6d..8ebdf4e239cba9562726f534631e2b0f297d537b 100644
--- a/Core/Parametrization/Distributions.h
+++ b/Param/Distrib/Distributions.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/Distributions.h
+//! @file Param/Distrib/Distributions.h
//! @brief Defines classes representing one-dimensional distributions.
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Parametrization/ParameterDistribution.cpp b/Param/Distrib/ParameterDistribution.cpp
similarity index 95%
rename from Core/Parametrization/ParameterDistribution.cpp
rename to Param/Distrib/ParameterDistribution.cpp
index cabbd64fa0349466ce7077acc5ca901b06074013..0f32a7a28b88e60d3b5d541836e53c3f536d7a98 100644
--- a/Core/Parametrization/ParameterDistribution.cpp
+++ b/Param/Distrib/ParameterDistribution.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterDistribution.cpp
+//! @file Param/Distrib/ParameterDistribution.cpp
//! @brief Implements class ParameterDistribution.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,10 +12,10 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/ParameterDistribution.h"
+#include "Param/Distrib/ParameterDistribution.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
ParameterDistribution::ParameterDistribution(const std::string& par_name,
const IDistribution1D& distribution,
diff --git a/Core/Parametrization/ParameterDistribution.h b/Param/Distrib/ParameterDistribution.h
similarity index 96%
rename from Core/Parametrization/ParameterDistribution.h
rename to Param/Distrib/ParameterDistribution.h
index 4e133c121cf76066f43955178c06ed564256ac23..1339b397ebecc58f4f918d11064a2116bf9dc6ea 100644
--- a/Core/Parametrization/ParameterDistribution.h
+++ b/Param/Distrib/ParameterDistribution.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterDistribution.h
+//! @file Param/Distrib/ParameterDistribution.h
//! @brief Defines class ParameterDistribution.
//!
//! @homepage http://www.bornagainproject.org
@@ -15,7 +15,7 @@
#ifndef BORNAGAIN_CORE_PARAMETRIZATION_PARAMETERDISTRIBUTION_H
#define BORNAGAIN_CORE_PARAMETRIZATION_PARAMETERDISTRIBUTION_H
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Varia/ParameterSample.h"
#include "Fit/Tools/RealLimits.h"
#include "Param/Base/IParameterized.h"
#include <memory>
diff --git a/Core/Parametrization/RangedDistributions.cpp b/Param/Distrib/RangedDistributions.cpp
similarity index 97%
rename from Core/Parametrization/RangedDistributions.cpp
rename to Param/Distrib/RangedDistributions.cpp
index ad345236a38e73055cbc562c8e341c054f382f1a..3c39dacd2a579602c9cd4a69e62afaf6ada2c7fa 100644
--- a/Core/Parametrization/RangedDistributions.cpp
+++ b/Param/Distrib/RangedDistributions.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/RangedDistributions.cpp
+//! @file Param/Distrib/RangedDistributions.cpp
//! @brief Implements classes representing ranged one-dimensional distributions.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,11 +12,11 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Base/Utils/PyFmt.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/PyFmtLimits.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Varia/PyFmtLimits.h"
#include <limits>
namespace
diff --git a/Core/Parametrization/RangedDistributions.h b/Param/Distrib/RangedDistributions.h
similarity index 99%
rename from Core/Parametrization/RangedDistributions.h
rename to Param/Distrib/RangedDistributions.h
index 94b854514a4b2b3836d6b79a6d506c6cd146ef95..b2e44a5545d4f221d0c9bc6f9e03aa2b1e092a36 100644
--- a/Core/Parametrization/RangedDistributions.h
+++ b/Param/Distrib/RangedDistributions.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/RangedDistributions.h
+//! @file Param/Distrib/RangedDistributions.h
//! @brief Defines classes representing ranged one-dimensional distributions.
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Parametrization/ParameterPattern.cpp b/Param/Varia/ParameterPattern.cpp
similarity index 87%
rename from Core/Parametrization/ParameterPattern.cpp
rename to Param/Varia/ParameterPattern.cpp
index f0a6344c6329e5e9f96a9dbfdfbb1e119a4caeb8..f9ced422e57e020e30157f1a2b537c4d6f6b46bb 100644
--- a/Core/Parametrization/ParameterPattern.cpp
+++ b/Param/Varia/ParameterPattern.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterPattern.cpp
+//! @file Param/Varia/ParameterPattern.cpp
//! @brief Implements class ParameterPattern
//!
//! @homepage http://www.bornagainproject.org
@@ -12,7 +12,7 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Varia/ParameterPattern.h"
ParameterPattern& ParameterPattern::beginsWith(std::string start_type)
{
diff --git a/Core/Parametrization/ParameterPattern.h b/Param/Varia/ParameterPattern.h
similarity index 95%
rename from Core/Parametrization/ParameterPattern.h
rename to Param/Varia/ParameterPattern.h
index 1bd6f6ba0fb961eec0a50d2110427e8944915bd8..d9fa77f39e08c1f3b5f7bb2e301bbd2b166e6a79 100644
--- a/Core/Parametrization/ParameterPattern.h
+++ b/Param/Varia/ParameterPattern.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterPattern.h
+//! @file Param/Varia/ParameterPattern.h
//! @brief Defines class ParameterPattern
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Parametrization/ParameterSample.h b/Param/Varia/ParameterSample.h
similarity index 94%
rename from Core/Parametrization/ParameterSample.h
rename to Param/Varia/ParameterSample.h
index 46e841071e0eea5fe432bfdef117e6c6243710d7..4e5ef0bf0b42239ba5c01d0f9139c9e4b7b67a5f 100644
--- a/Core/Parametrization/ParameterSample.h
+++ b/Param/Varia/ParameterSample.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterSample.h
+//! @file Param/Varia/ParameterSample.h
//! @brief Defines class ParameterSample.
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Parametrization/ParameterUtils.cpp b/Param/Varia/ParameterUtils.cpp
similarity index 93%
rename from Core/Parametrization/ParameterUtils.cpp
rename to Param/Varia/ParameterUtils.cpp
index e52aad9e3e89bb2a20f2b0fe2a761248b989273c..58f88912595974b065409611bfc455d34ee43b33 100644
--- a/Core/Parametrization/ParameterUtils.cpp
+++ b/Param/Varia/ParameterUtils.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterUtils.cpp
+//! @file Param/Varia/ParameterUtils.cpp
//! @brief Implements namespace ParameterUtils
//!
//! @homepage http://www.bornagainproject.org
@@ -12,7 +12,7 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/ParameterUtils.h"
+#include "Param/Varia/ParameterUtils.h"
#include "Param/Base/IParameterized.h"
#include "Param/Base/ParameterPool.h"
#include "Param/Base/RealParameter.h"
diff --git a/Core/Parametrization/ParameterUtils.h b/Param/Varia/ParameterUtils.h
similarity index 95%
rename from Core/Parametrization/ParameterUtils.h
rename to Param/Varia/ParameterUtils.h
index ef9a21c8d90f58d909945ebeb4a14c578f6fcc50..62ab00cb17a443ce4920021680e5a3bb6c1c3eeb 100644
--- a/Core/Parametrization/ParameterUtils.h
+++ b/Param/Varia/ParameterUtils.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/ParameterUtils.h
+//! @file Param/Varia/ParameterUtils.h
//! @brief Defines namespace ParameterUtils
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Core/Parametrization/PyFmtLimits.cpp b/Param/Varia/PyFmtLimits.cpp
similarity index 95%
rename from Core/Parametrization/PyFmtLimits.cpp
rename to Param/Varia/PyFmtLimits.cpp
index c4ea3bc78d56bac8f393a24bcf6bdfd0b7470286..74b4a5d29ec9c85fffab417c0cca1cce852e254f 100644
--- a/Core/Parametrization/PyFmtLimits.cpp
+++ b/Param/Varia/PyFmtLimits.cpp
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/PyFmtLimits.cpp
+//! @file Param/Varia/PyFmtLimits.cpp
//! @brief Implements functions from namespace pyfmt.
//!
//! @homepage http://www.bornagainproject.org
@@ -12,7 +12,7 @@
//
// ************************************************************************** //
-#include "Core/Parametrization/PyFmtLimits.h"
+#include "Param/Varia/PyFmtLimits.h"
#include "Base/Utils/PyFmt.h"
#include "Fit/Tools/RealLimits.h"
#include <iomanip>
diff --git a/Core/Parametrization/PyFmtLimits.h b/Param/Varia/PyFmtLimits.h
similarity index 95%
rename from Core/Parametrization/PyFmtLimits.h
rename to Param/Varia/PyFmtLimits.h
index c82ac1aa425ae0cde1163d8d4e6bdfa1ee1978e8..1e74aaa935c791b285851ca55bfcff1558002092 100644
--- a/Core/Parametrization/PyFmtLimits.h
+++ b/Param/Varia/PyFmtLimits.h
@@ -2,7 +2,7 @@
//
// BornAgain: simulate and fit scattering at grazing incidence
//
-//! @file Core/Parametrization/PyFmtLimits.h
+//! @file Param/Varia/PyFmtLimits.h
//! @brief Defines functions in namespace pyfmt.
//!
//! @homepage http://www.bornagainproject.org
diff --git a/Tests/Functional/Core/Consistence/CompareTwoReferences.cpp b/Tests/Functional/Core/Consistence/CompareTwoReferences.cpp
index 73dad61f6660f2cb7c249ba78712a01fe88914ac..d7ce2456003c0dcde118b8b65e63e62e9ec54370 100644
--- a/Tests/Functional/Core/Consistence/CompareTwoReferences.cpp
+++ b/Tests/Functional/Core/Consistence/CompareTwoReferences.cpp
@@ -16,7 +16,7 @@
#include "BATesting.h"
#include "Base/Utils/Assert.h"
#include "Base/Utils/FileSystemUtils.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include <iostream>
diff --git a/Tests/Functional/Core/CoreSpecial/CoreIOPathTest.cpp b/Tests/Functional/Core/CoreSpecial/CoreIOPathTest.cpp
index 79c12f3a5fa9d1bec414e2b5eacdefd2b16b1494..270ccec638d4b0ee71825f7b75c9a13dde359ffd 100644
--- a/Tests/Functional/Core/CoreSpecial/CoreIOPathTest.cpp
+++ b/Tests/Functional/Core/CoreSpecial/CoreIOPathTest.cpp
@@ -15,7 +15,7 @@
#include "BATesting.h"
#include "Base/Utils/FileSystemUtils.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "Tests/GTestWrapper/google_test.h"
#include <boost/filesystem.hpp>
diff --git a/Tests/Functional/Core/CoreSpecial/FourierTransformationTest.cpp b/Tests/Functional/Core/CoreSpecial/FourierTransformationTest.cpp
index e33753c3a789775c3987833c43dc278af5e1295f..9478dfc155dc1b5edf9483fc27aa94a3287e476d 100644
--- a/Tests/Functional/Core/CoreSpecial/FourierTransformationTest.cpp
+++ b/Tests/Functional/Core/CoreSpecial/FourierTransformationTest.cpp
@@ -15,7 +15,7 @@
#include "BATesting.h"
#include "Base/Utils/FileSystemUtils.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "Tests/GTestWrapper/google_test.h"
#include <iostream>
diff --git a/Tests/Functional/Core/MPI/mpitest.cpp b/Tests/Functional/Core/MPI/mpitest.cpp
index 3a0680649e4f97f815d973f8d227722b37f09f46..1e3421ea85661f1c3832efa98f7ac2335cdf175c 100644
--- a/Tests/Functional/Core/MPI/mpitest.cpp
+++ b/Tests/Functional/Core/MPI/mpitest.cpp
@@ -1,6 +1,6 @@
#include <mpi.h>
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "Core/Multilayer/MultiLayer.h"
#include "Core/Simulation/SimulationFactory.h"
diff --git a/Tests/Functional/Core/Std/Check.cpp b/Tests/Functional/Core/Std/Check.cpp
index 1749a0be017b0e331cbf6215ce5cadb3f5ddc906..7a2010b5ac04ab3604226a705dc294473c5835e2 100644
--- a/Tests/Functional/Core/Std/Check.cpp
+++ b/Tests/Functional/Core/Std/Check.cpp
@@ -16,7 +16,7 @@
#include "BATesting.h"
#include "Base/Utils/Assert.h"
#include "Base/Utils/FileSystemUtils.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "Core/Multilayer/MultiLayer.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
diff --git a/Tests/Functional/Python/Std/Check.cpp b/Tests/Functional/Python/Std/Check.cpp
index a945f950a9545b2d7763f0aee90a27fa58757bda..559e9c469a9991ef1a1de02c765d8ed164f5dad9 100644
--- a/Tests/Functional/Python/Std/Check.cpp
+++ b/Tests/Functional/Python/Std/Check.cpp
@@ -17,7 +17,7 @@
#include "Base/Utils/Assert.h"
#include "Base/Utils/FileSystemUtils.h"
#include "Core/Export/ExportToPython.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "Core/Simulation/Simulation.h"
#include <fstream>
diff --git a/Tests/Performance/Core/CoreIO.cpp b/Tests/Performance/Core/CoreIO.cpp
index e526cd6b70a419a07d7038f066c20b9976e9a0b7..2b3d0192d3a8093e1d0a6eb60b69ee04fc5c5a4f 100644
--- a/Tests/Performance/Core/CoreIO.cpp
+++ b/Tests/Performance/Core/CoreIO.cpp
@@ -14,7 +14,7 @@
#include "Base/Utils/Assert.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Fit/TestEngine/Numeric.h"
#include "Tests/Performance/Benchmark.h"
#include <boost/format.hpp>
diff --git a/Tests/Performance/Core/Threading.cpp b/Tests/Performance/Core/Threading.cpp
index e10cc606bc135be47453622b36b0a8c5be707121..0af424eec551a99fd3dc98ed5efc43600cb62bed 100644
--- a/Tests/Performance/Core/Threading.cpp
+++ b/Tests/Performance/Core/Threading.cpp
@@ -14,8 +14,8 @@
#include "Base/Const/Units.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Core/Simulation/GISASSimulation.h"
#include "Core/StandardSamples/CylindersBuilder.h"
#include "Core/StandardSamples/ParaCrystalBuilder.h"
diff --git a/Tests/Performance/Core/ThreadingComponents.cpp b/Tests/Performance/Core/ThreadingComponents.cpp
index afe0efc084c2c61c00841a2f90bf03a496470b76..ee89007174c6833ec5e923107b9da78668c93010 100644
--- a/Tests/Performance/Core/ThreadingComponents.cpp
+++ b/Tests/Performance/Core/ThreadingComponents.cpp
@@ -22,8 +22,8 @@
#include "Core/Material/MaterialFactoryFuncs.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleDistribution.h"
#include "Core/Simulation/GISASSimulation.h"
diff --git a/Tests/UnitTests/Core/ExportToPython/PythonFormattingTest.cpp b/Tests/UnitTests/Core/ExportToPython/PythonFormattingTest.cpp
index 42a2976b263880b80b3c3b457183ce4ffc905aed..593386d08da55eb9b0dbb039b9dfe9abb7b2509f 100644
--- a/Tests/UnitTests/Core/ExportToPython/PythonFormattingTest.cpp
+++ b/Tests/UnitTests/Core/ExportToPython/PythonFormattingTest.cpp
@@ -3,9 +3,9 @@
#include "Core/Axis/FixedBinAxis.h"
#include "Core/Axis/PointwiseAxis.h"
#include "Core/Instrument/PyFmt2.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterDistribution.h"
-#include "Core/Parametrization/PyFmtLimits.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/ParameterDistribution.h"
+#include "Param/Varia/PyFmtLimits.h"
#include "Fit/Tools/RealLimits.h"
#include "Tests/GTestWrapper/google_test.h"
diff --git a/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp b/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
index 622806d3da46b32df5aeb4541bce4946b33449d7..5342e5d8552fa708af2624740c5a09ce99797d65 100644
--- a/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
+++ b/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
@@ -6,8 +6,8 @@
#include "Core/Material/MaterialFactoryFuncs.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Param/Base/RealParameter.h"
#include "Tests/GTestWrapper/google_test.h"
diff --git a/Tests/UnitTests/Core/Fresnel/SpecularScanTest.cpp b/Tests/UnitTests/Core/Fresnel/SpecularScanTest.cpp
index cba422cdac906317202c18f75e7735f6701f2445..e73a398baab5be1662ed16c4dfa25a1249898947 100644
--- a/Tests/UnitTests/Core/Fresnel/SpecularScanTest.cpp
+++ b/Tests/UnitTests/Core/Fresnel/SpecularScanTest.cpp
@@ -2,7 +2,7 @@
#include "Core/Axis/PointwiseAxis.h"
#include "Core/Beam/FootprintGauss.h"
#include "Core/Multilayer/SpecularSimulationElement.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Core/Resolution/ScanResolution.h"
#include "Core/Scan/AngularSpecScan.h"
#include "Core/Scan/QSpecScan.h"
diff --git a/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp b/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
index 0cf9d26c42b017acba5738db59cd8ea5466ac397..712b541bba181069fa538dfb5ffdb0a3b16e4ac2 100644
--- a/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
+++ b/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
@@ -8,8 +8,8 @@
#include "Core/Material/MaterialFactoryFuncs.h"
#include "Core/Multilayer/Layer.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Core/SampleBuilderEngine/ISampleBuilder.h"
#include "Core/Scan/AngularSpecScan.h"
#include "Core/Scan/QSpecScan.h"
diff --git a/Tests/UnitTests/Core/Parameters/DistributionHandlerTest.cpp b/Tests/UnitTests/Core/Parameters/DistributionHandlerTest.cpp
index 55c495652901e7cabc0c2d0deacd591e62b432f7..ba8a1bf455ad8d7691887c0a75df7acf5d682e48 100644
--- a/Tests/UnitTests/Core/Parameters/DistributionHandlerTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/DistributionHandlerTest.cpp
@@ -1,5 +1,5 @@
-#include "Core/Parametrization/DistributionHandler.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/DistributionHandler.h"
+#include "Param/Distrib/Distributions.h"
#include "Param/Base/IParameterized.h"
#include "Param/Base/ParameterPool.h"
#include "Tests/GTestWrapper/google_test.h"
diff --git a/Tests/UnitTests/Core/Parameters/DistributionsTest.cpp b/Tests/UnitTests/Core/Parameters/DistributionsTest.cpp
index 0bc9baa9c1053a20bc413552d95a740515859c3b..b205ba04d84851a16c1fe1e52dba7880641cc5dd 100644
--- a/Tests/UnitTests/Core/Parameters/DistributionsTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/DistributionsTest.cpp
@@ -1,7 +1,7 @@
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Base/Const/MathConstants.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/ParameterSample.h"
+#include "Param/Varia/ParameterSample.h"
#include "Param/Base/RealParameter.h"
#include "Tests/GTestWrapper/google_test.h"
#include <cmath>
diff --git a/Tests/UnitTests/Core/Parameters/ParameterDistributionTest.cpp b/Tests/UnitTests/Core/Parameters/ParameterDistributionTest.cpp
index 8808e920ec8f173a7b62930dc823381a5e78bfc2..36b2c598bb3f6f39354e5c641f66ee873df19353 100644
--- a/Tests/UnitTests/Core/Parameters/ParameterDistributionTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/ParameterDistributionTest.cpp
@@ -1,8 +1,8 @@
-#include "Core/Parametrization/ParameterDistribution.h"
+#include "Param/Distrib/ParameterDistribution.h"
#include "Base/Types/Exceptions.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/ParameterUtils.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Varia/ParameterUtils.h"
#include "Param/Base/IParameterized.h"
#include "Tests/GTestWrapper/google_test.h"
#include <cmath>
diff --git a/Tests/UnitTests/Core/Parameters/ParameterPatternTest.cpp b/Tests/UnitTests/Core/Parameters/ParameterPatternTest.cpp
index 0c6e16ae1e4a28a77dc4cce5ffad980d39e1964e..0cd4d2e35faed8e876327fbd36ef3fbd5ed54672 100644
--- a/Tests/UnitTests/Core/Parameters/ParameterPatternTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/ParameterPatternTest.cpp
@@ -1,4 +1,4 @@
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Tests/GTestWrapper/google_test.h"
#include <string>
diff --git a/Tests/UnitTests/Core/Parameters/RangedDistributionTest.cpp b/Tests/UnitTests/Core/Parameters/RangedDistributionTest.cpp
index cb26d9bca0b82bc422bf002675536bdc9d38fc2e..8a40268f8ac2ea837c5b38b09d2aa71f3073be34 100644
--- a/Tests/UnitTests/Core/Parameters/RangedDistributionTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/RangedDistributionTest.cpp
@@ -1,6 +1,6 @@
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Tests/GTestWrapper/google_test.h"
class RangedDistributionTest : public ::testing::Test
diff --git a/Tests/UnitTests/Core/Parameters/ScanResolutionTest.cpp b/Tests/UnitTests/Core/Parameters/ScanResolutionTest.cpp
index dbac20e564765c27c927ae2ed042bb332ce9b8c5..f7268d26ed407bd571ae073c193077bff8f7e924 100644
--- a/Tests/UnitTests/Core/Parameters/ScanResolutionTest.cpp
+++ b/Tests/UnitTests/Core/Parameters/ScanResolutionTest.cpp
@@ -1,6 +1,6 @@
#include "Core/Resolution/ScanResolution.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/RangedDistributions.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
#include "Tests/GTestWrapper/google_test.h"
#include <cmath>
diff --git a/Tests/UnitTests/Core/Sample/LayerRoughnessTest.cpp b/Tests/UnitTests/Core/Sample/LayerRoughnessTest.cpp
index 7e1194c0604a630a91c0f9836b1a3b58fe8b26c6..beae84de891d9c3334cbeac880c865ff75cc875f 100644
--- a/Tests/UnitTests/Core/Sample/LayerRoughnessTest.cpp
+++ b/Tests/UnitTests/Core/Sample/LayerRoughnessTest.cpp
@@ -1,5 +1,5 @@
#include "Core/Multilayer/LayerRoughness.h"
-#include "Core/Parametrization/ParameterPattern.h"
+#include "Param/Varia/ParameterPattern.h"
#include "Tests/GTestWrapper/google_test.h"
class LayerRoughnessTest : public ::testing::Test
diff --git a/Tests/UnitTests/Core/Sample/ParticleDistributionTest.cpp b/Tests/UnitTests/Core/Sample/ParticleDistributionTest.cpp
index 382b0d95be7e71bfdaef27d050efc143084a50d8..9a0ce617fa61323a3af4e0db282cb29fb8edc13b 100644
--- a/Tests/UnitTests/Core/Sample/ParticleDistributionTest.cpp
+++ b/Tests/UnitTests/Core/Sample/ParticleDistributionTest.cpp
@@ -3,7 +3,7 @@
#include "Core/HardParticle/FormFactorCone.h"
#include "Core/HardParticle/FormFactorFullSphere.h"
#include "Core/Material/MaterialFactoryFuncs.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Core/Particle/Particle.h"
#include "Tests/GTestWrapper/google_test.h"
diff --git a/Tests/UnitTests/GUI/TestOutputDataIOService.cpp b/Tests/UnitTests/GUI/TestOutputDataIOService.cpp
index 3c07e520bc86b22251e55354f2998ff461c48850..978bd1b21b4999ab3787a394ac852e5de833e8ba 100644
--- a/Tests/UnitTests/GUI/TestOutputDataIOService.cpp
+++ b/Tests/UnitTests/GUI/TestOutputDataIOService.cpp
@@ -1,5 +1,5 @@
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Models/ApplicationModels.h"
#include "GUI/coregui/Models/DataItem.h"
#include "GUI/coregui/Models/JobItem.h"
diff --git a/Tests/UnitTests/GUI/TestParticleDistributionItem.cpp b/Tests/UnitTests/GUI/TestParticleDistributionItem.cpp
index e28003664601315bf2c114799fa1d233633f7669..28e73b12c0559cb11eca228c2a8faca196ff22fb 100644
--- a/Tests/UnitTests/GUI/TestParticleDistributionItem.cpp
+++ b/Tests/UnitTests/GUI/TestParticleDistributionItem.cpp
@@ -1,6 +1,6 @@
#include "Core/HardParticle/HardParticles.h"
#include "Core/Material/MaterialFactoryFuncs.h"
-#include "Core/Parametrization/Distributions.h"
+#include "Param/Distrib/Distributions.h"
#include "Core/Particle/Particle.h"
#include "Core/Particle/ParticleDistribution.h"
#include "GUI/coregui/Models/ComboProperty.h"
diff --git a/Tests/UnitTests/GUI/TestSavingSpecularData.cpp b/Tests/UnitTests/GUI/TestSavingSpecularData.cpp
index cf2d6f447a230b344fd347f10affe49e4a0245cf..0aa8d41aa8cab0af8c017c3ac860d34c6cc01768 100644
--- a/Tests/UnitTests/GUI/TestSavingSpecularData.cpp
+++ b/Tests/UnitTests/GUI/TestSavingSpecularData.cpp
@@ -1,6 +1,6 @@
#include "Core/Axis/PointwiseAxis.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "GUI/coregui/Models/ApplicationModels.h"
#include "GUI/coregui/Models/DataItem.h"
#include "GUI/coregui/Models/GroupItem.h"
diff --git a/Tests/UnitTests/GUI/Utils.cpp b/Tests/UnitTests/GUI/Utils.cpp
index bdc753d40b0ed25d4a1bb9866b34eba9577e4476..1db9248e7537f18cae5d6dbe06f06dd2b0e33f3e 100644
--- a/Tests/UnitTests/GUI/Utils.cpp
+++ b/Tests/UnitTests/GUI/Utils.cpp
@@ -15,7 +15,7 @@
#include "Tests/UnitTests/GUI/Utils.h"
#include "Core/Data/OutputData.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Instrument/IntensityDataFunctions.h"
#include "GUI/coregui/Models/RealDataItem.h"
#include "GUI/coregui/Models/SessionModel.h"
diff --git a/Wrap/swig/libBornAgainBase.i b/Wrap/swig/libBornAgainBase.i
index d03abf5905fdeeed243b34600a3111af3a80dfe8..775f12a212877edaf7a211de129fad754b080bb6 100644
--- a/Wrap/swig/libBornAgainBase.i
+++ b/Wrap/swig/libBornAgainBase.i
@@ -55,20 +55,25 @@
#include "Base/Types/Complex.h"
#include "Base/Types/ICloneable.h"
#include "Base/Const/Units.h"
+#include "Base/Utils/ThreadInfo.h"
#include "Base/Vector/BasicVector3D.h"
#include "Base/Vector/Vectors3D.h"
#include "Base/Utils/MathFunctions.h"
+
%}
%include "Base/Types/ICloneable.h"
%include "Base/Types/Complex.h"
%include "Base/Const/Units.h"
+
%include "Base/Utils/MathFunctions.h"
+%include "Base/Utils/ThreadInfo.h"
%include "Base/Vector/BasicVector3D.h"
%include "Base/Vector/Vectors3D.h"
+
%include "fromBase.i"
%include "extendBase.i"
diff --git a/Wrap/swig/libBornAgainCore.i b/Wrap/swig/libBornAgainCore.i
index 9c66e98d98bead254d2bb9ef3bcee9193939aac2..b3b6914c991d5ed9989608980304244a2f85e743 100644
--- a/Wrap/swig/libBornAgainCore.i
+++ b/Wrap/swig/libBornAgainCore.i
@@ -144,7 +144,7 @@
#include "Core/HardParticle/FormFactorTruncatedCube.h"
#include "Core/HardParticle/FormFactorTruncatedSphere.h"
#include "Core/HardParticle/FormFactorTruncatedSpheroid.h"
-#include "Core/InputOutput/IntensityDataIOFactory.h"
+#include "Core/Histo/IntensityDataIOFactory.h"
#include "Core/Scan/AngularSpecScan.h"
#include "Core/Instrument/ChiSquaredModule.h"
#include "Core/Instrument/IChiSquaredModule.h"
@@ -178,12 +178,7 @@
#include "Core/Multilayer/LayerInterface.h"
#include "Core/Multilayer/LayerRoughness.h"
#include "Core/Multilayer/MultiLayer.h"
-#include "Core/Parametrization/Distributions.h"
-#include "Core/Parametrization/ParameterDistribution.h"
-#include "Core/Parametrization/ParameterSample.h"
-#include "Core/Parametrization/RangedDistributions.h"
#include "Core/RT/SimulationOptions.h"
-#include "Base/Utils/ThreadInfo.h"
#include "Core/Particle/Crystal.h"
#include "Core/Particle/FormFactorCrystal.h"
#include "Core/Particle/FormFactorWeighted.h"
@@ -262,6 +257,7 @@
%import(module="libBornAgainParam") "Param/Base/ParameterPool.h"
%import(module="libBornAgainParam") "Param/Base/IParameterized.h"
%import(module="libBornAgainParam") "Param/Node/INode.h"
+%import(module="libBornAgainParam") "Param/Distrib/ParameterDistribution.h"
%include "fromParam.i"
%template(swig_dummy_type_axisinfo_vector) std::vector<AxisInfo>;
@@ -275,9 +271,6 @@
%template(SampleBuilderFactoryTemp) IFactory<std::string, ISampleBuilder>;
%template(SimulationFactoryTemp) IFactory<std::string, Simulation>;
-%include "Core/Parametrization/ParameterSample.h"
-%template(ParameterSampleVector) std::vector<ParameterSample>;
-
%include "Core/Data/OutputData.h"
%template(IntensityData) OutputData<double>;
@@ -302,12 +295,7 @@
%include "Core/Mask/Polygon.h"
%include "Core/Mask/Rectangle.h"
-%include "Core/Parametrization/Distributions.h"
-%include "Core/Parametrization/Distributions.h"
-%include "Core/Parametrization/ParameterDistribution.h"
-%include "Core/Parametrization/RangedDistributions.h"
%include "Core/RT/SimulationOptions.h"
-%include "Base/Utils/ThreadInfo.h"
%include "Core/Scattering/ISample.h"
%include "Core/Scattering/IFormFactor.h"
@@ -418,7 +406,7 @@
%include "Core/Computation/PoissonNoiseBackground.h"
%include "Core/Computation/MultiLayerFuncs.h"
-%include "Core/InputOutput/IntensityDataIOFactory.h"
+%include "Core/Histo/IntensityDataIOFactory.h"
%include "Core/Detector/IDetector.h"
%include "Core/Detector/IDetector2D.h"
diff --git a/Wrap/swig/libBornAgainParam.i b/Wrap/swig/libBornAgainParam.i
index fd7da6e139f70bea1cbc084ad7f569c93995d57b..a04380eac32332625d543c14d58e3576429134bf 100644
--- a/Wrap/swig/libBornAgainParam.i
+++ b/Wrap/swig/libBornAgainParam.i
@@ -72,6 +72,12 @@
#include "Param/Node/INode.h"
#include "Param/Node/INodeVisitor.h"
+
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/ParameterDistribution.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
+
%}
%import(module="libBornAgainBase") "Base/Types/Complex.h"
@@ -93,4 +99,12 @@
%include "Param/Node/INode.h"
%include "Param/Node/INodeVisitor.h"
+%include "Param/Distrib/Distributions.h"
+%include "Param/Distrib/Distributions.h"
+%include "Param/Distrib/ParameterDistribution.h"
+%include "Param/Distrib/RangedDistributions.h"
+
+%include "Param/Varia/ParameterSample.h"
+%template(ParameterSampleVector) std::vector<ParameterSample>;
+
%include "extendParam.i"
diff --git a/auto/Wrap/doxygenCore.i b/auto/Wrap/doxygenCore.i
index bef5cea8e81b5508c9eb607940e381725440492c..65bfe828bb50d6e9abeb18ceafd94845c9d51b7b 100644
--- a/auto/Wrap/doxygenCore.i
+++ b/auto/Wrap/doxygenCore.i
@@ -85,7 +85,7 @@ Sets wavelength resolution values via ScanResolution object.
%feature("docstring") AngularSpecScan::setRelativeWavelengthResolution "void AngularSpecScan::setRelativeWavelengthResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
-Sets wavelength resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+Sets wavelength resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
";
%feature("docstring") AngularSpecScan::setAbsoluteWavelengthResolution "void AngularSpecScan::setAbsoluteWavelengthResolution(const RangedDistribution &distr, double std_dev)
@@ -93,7 +93,7 @@ Sets wavelength resolution values via RangedDistribution and values of relative
%feature("docstring") AngularSpecScan::setAbsoluteWavelengthResolution "void AngularSpecScan::setAbsoluteWavelengthResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
-Sets wavelength resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+Sets wavelength resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
";
%feature("docstring") AngularSpecScan::setAngleResolution "void AngularSpecScan::setAngleResolution(const ScanResolution &resolution)
@@ -106,7 +106,7 @@ Sets angle resolution values via ScanResolution object.
%feature("docstring") AngularSpecScan::setRelativeAngularResolution "void AngularSpecScan::setRelativeAngularResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
-Sets angular resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+Sets angular resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
";
%feature("docstring") AngularSpecScan::setAbsoluteAngularResolution "void AngularSpecScan::setAbsoluteAngularResolution(const RangedDistribution &distr, double std_dev)
@@ -114,7 +114,7 @@ Sets angular resolution values via RangedDistribution and values of relative de
%feature("docstring") AngularSpecScan::setAbsoluteAngularResolution "void AngularSpecScan::setAbsoluteAngularResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
-Sets angular resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+Sets angular resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
";
@@ -1492,346 +1492,6 @@ returns true if has masks
";
-// File: classDistributionCosine.xml
-%feature("docstring") DistributionCosine "
-
-Cosine distribution.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine(double mean, double sigma)
-";
-
-%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine()
-";
-
-%feature("docstring") DistributionCosine::clone "DistributionCosine* DistributionCosine::clone() const final
-";
-
-%feature("docstring") DistributionCosine::probabilityDensity "double DistributionCosine::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionCosine::getMean "double DistributionCosine::getMean() const final
-
-Returns the distribution-specific mean.
-";
-
-%feature("docstring") DistributionCosine::getSigma "double DistributionCosine::getSigma() const
-";
-
-%feature("docstring") DistributionCosine::equidistantPoints "std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
-generate list of sample values
-";
-
-%feature("docstring") DistributionCosine::isDelta "bool DistributionCosine::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionCosine::accept "void DistributionCosine::accept(INodeVisitor *visitor) const final
-";
-
-
-// File: classDistributionGate.xml
-%feature("docstring") DistributionGate "
-
-Uniform distribution function with half width hwhm.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate(double min, double max)
-";
-
-%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate()
-";
-
-%feature("docstring") DistributionGate::clone "DistributionGate* DistributionGate::clone() const final
-";
-
-%feature("docstring") DistributionGate::probabilityDensity "double DistributionGate::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionGate::getMean "double DistributionGate::getMean() const final
-
-Returns the distribution-specific mean.
-";
-
-%feature("docstring") DistributionGate::getMin "double DistributionGate::getMin() const
-";
-
-%feature("docstring") DistributionGate::getMax "double DistributionGate::getMax() const
-";
-
-%feature("docstring") DistributionGate::equidistantPoints "std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
-Returns list of sample values.
-";
-
-%feature("docstring") DistributionGate::isDelta "bool DistributionGate::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionGate::accept "void DistributionGate::accept(INodeVisitor *visitor) const final
-";
-
-
-// File: classDistributionGaussian.xml
-%feature("docstring") DistributionGaussian "
-
-Gaussian distribution with standard deviation std_dev.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian(double mean, double std_dev)
-";
-
-%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian()
-";
-
-%feature("docstring") DistributionGaussian::clone "DistributionGaussian* DistributionGaussian::clone() const final
-";
-
-%feature("docstring") DistributionGaussian::probabilityDensity "double DistributionGaussian::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionGaussian::getMean "double DistributionGaussian::getMean() const final
-
-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
-
-generate list of sample values
-";
-
-%feature("docstring") DistributionGaussian::isDelta "bool DistributionGaussian::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionGaussian::accept "void DistributionGaussian::accept(INodeVisitor *visitor) const final
-";
-
-
-// File: classDistributionHandler.xml
-%feature("docstring") DistributionHandler "
-
-Provides the functionality to average over parameter distributions with weights.
-
-C++ includes: DistributionHandler.h
-";
-
-%feature("docstring") DistributionHandler::DistributionHandler "DistributionHandler::DistributionHandler()
-";
-
-%feature("docstring") DistributionHandler::~DistributionHandler "DistributionHandler::~DistributionHandler()
-";
-
-%feature("docstring") DistributionHandler::addParameterDistribution "void DistributionHandler::addParameterDistribution(const std::string ¶m_name, const IDistribution1D &distribution, size_t nbr_samples, double sigma_factor=0.0, const RealLimits &limits=RealLimits())
-
-add a sampled parameter distribution
-";
-
-%feature("docstring") DistributionHandler::addParameterDistribution "void DistributionHandler::addParameterDistribution(const ParameterDistribution &par_distr)
-";
-
-%feature("docstring") DistributionHandler::getTotalNumberOfSamples "size_t DistributionHandler::getTotalNumberOfSamples() const
-
-get the total number of parameter value combinations (product of the individual sizes of each parameter distribution
-";
-
-%feature("docstring") DistributionHandler::setParameterValues "double DistributionHandler::setParameterValues(ParameterPool *p_parameter_pool, size_t index)
-
-set the parameter values of the simulation object to a specific combination of values, determined by the index (which must be smaller than the total number of combinations) and returns the weight associated with this combination of parameter values
-";
-
-%feature("docstring") DistributionHandler::setParameterToMeans "void DistributionHandler::setParameterToMeans(ParameterPool *p_parameter_pool) const
-
-Sets mean distribution values to the parameter pool.
-";
-
-%feature("docstring") DistributionHandler::getDistributions "const DistributionHandler::Distributions_t & DistributionHandler::getDistributions() const
-";
-
-
-// File: classDistributionLogNormal.xml
-%feature("docstring") DistributionLogNormal "
-
-Log-normal distribution.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal(double median, double scale_param)
-";
-
-%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal()=delete
-";
-
-%feature("docstring") DistributionLogNormal::clone "DistributionLogNormal* DistributionLogNormal::clone() const final
-";
-
-%feature("docstring") DistributionLogNormal::probabilityDensity "double DistributionLogNormal::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionLogNormal::getMean "double DistributionLogNormal::getMean() const final
-
-Returns the distribution-specific mean.
-";
-
-%feature("docstring") DistributionLogNormal::getMedian "double DistributionLogNormal::getMedian() const
-";
-
-%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
-
-generate list of sample values
-";
-
-%feature("docstring") DistributionLogNormal::isDelta "bool DistributionLogNormal::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionLogNormal::accept "void DistributionLogNormal::accept(INodeVisitor *visitor) const final
-";
-
-%feature("docstring") DistributionLogNormal::setUnits "void DistributionLogNormal::setUnits(const std::string &units)
-
-Sets distribution units.
-";
-
-
-// File: classDistributionLorentz.xml
-%feature("docstring") DistributionLorentz "
-
-Lorentz distribution with half width hwhm.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz(double mean, double hwhm)
-";
-
-%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz()
-";
-
-%feature("docstring") DistributionLorentz::clone "DistributionLorentz* DistributionLorentz::clone() const final
-";
-
-%feature("docstring") DistributionLorentz::probabilityDensity "double DistributionLorentz::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionLorentz::getMean "double DistributionLorentz::getMean() const final
-
-Returns the distribution-specific mean.
-";
-
-%feature("docstring") DistributionLorentz::getHWHM "double DistributionLorentz::getHWHM() const
-";
-
-%feature("docstring") DistributionLorentz::equidistantPoints "std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
-generate list of sample values
-";
-
-%feature("docstring") DistributionLorentz::isDelta "bool DistributionLorentz::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionLorentz::accept "void DistributionLorentz::accept(INodeVisitor *visitor) const final
-";
-
-
-// File: classDistributionTrapezoid.xml
-%feature("docstring") DistributionTrapezoid "
-
-Trapezoidal distribution.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid(const std::vector< double > P)
-";
-
-%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid(double center, double left, double middle, double right)
-";
-
-%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid()
-";
-
-%feature("docstring") DistributionTrapezoid::clone "DistributionTrapezoid* DistributionTrapezoid::clone() const final
-";
-
-%feature("docstring") DistributionTrapezoid::probabilityDensity "double DistributionTrapezoid::probabilityDensity(double x) const final
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") DistributionTrapezoid::getMean "double DistributionTrapezoid::getMean() const final
-
-Returns the distribution-specific mean.
-";
-
-%feature("docstring") DistributionTrapezoid::getLeftWidth "double DistributionTrapezoid::getLeftWidth() const
-";
-
-%feature("docstring") DistributionTrapezoid::getMiddleWidth "double DistributionTrapezoid::getMiddleWidth() const
-";
-
-%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
-
-generate list of sample values
-";
-
-%feature("docstring") DistributionTrapezoid::isDelta "bool DistributionTrapezoid::isDelta() const final
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") DistributionTrapezoid::accept "void DistributionTrapezoid::accept(INodeVisitor *visitor) const final
-";
-
-
// File: classDoubleEllipse.xml
%feature("docstring") DoubleEllipse "";
@@ -5741,61 +5401,6 @@ Applies the detector resolution to the matrix-valued intensity data.
";
-// File: classIDistribution1D.xml
-%feature("docstring") IDistribution1D "
-
-Interface for one-dimensional distributions.
-
-C++ includes: Distributions.h
-";
-
-%feature("docstring") IDistribution1D::IDistribution1D "IDistribution1D::IDistribution1D(const NodeMeta &meta, const std::vector< double > &PValues)
-";
-
-%feature("docstring") IDistribution1D::clone "virtual IDistribution1D* IDistribution1D::clone() const =0
-";
-
-%feature("docstring") IDistribution1D::probabilityDensity "virtual double IDistribution1D::probabilityDensity(double x) const =0
-
-Returns the distribution-specific probability density for value x.
-";
-
-%feature("docstring") IDistribution1D::getMean "virtual double IDistribution1D::getMean() const =0
-
-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
-
-Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
-";
-
-%feature("docstring") IDistribution1D::equidistantSamplesInRange "std::vector< ParameterSample > IDistribution1D::equidistantSamplesInRange(size_t nbr_samples, double xmin, double xmax) const
-
-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
-
-Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor.
-";
-
-%feature("docstring") IDistribution1D::equidistantPointsInRange "std::vector< double > IDistribution1D::equidistantPointsInRange(size_t nbr_samples, double xmin, double xmax) const
-
-Returns equidistant interpolation points from xmin to xmax.
-";
-
-%feature("docstring") IDistribution1D::isDelta "virtual bool IDistribution1D::isDelta() const =0
-
-Returns true if the distribution is in the limit case of a Dirac delta distribution.
-";
-
-%feature("docstring") IDistribution1D::setUnits "void IDistribution1D::setUnits(const std::string &units)
-
-Sets distribution units.
-";
-
-
// File: classIDistribution1DSampler.xml
%feature("docstring") IDistribution1DSampler "";
@@ -10389,106 +9994,6 @@ Sets concrete writing strategy.
";
-// File: classParameterDistribution.xml
-%feature("docstring") ParameterDistribution "
-
-A parametric distribution function, for use with any model parameter.
-
-C++ includes: ParameterDistribution.h
-";
-
-%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const std::string &par_name, const IDistribution1D &distribution, size_t nbr_samples, double sigma_factor=0.0, const RealLimits &limits=RealLimits())
-";
-
-%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const std::string &par_name, const IDistribution1D &distribution, size_t nbr_samples, double xmin, double xmax)
-";
-
-%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const ParameterDistribution &other)
-";
-
-%feature("docstring") ParameterDistribution::~ParameterDistribution "ParameterDistribution::~ParameterDistribution()
-";
-
-%feature("docstring") ParameterDistribution::linkParameter "ParameterDistribution & ParameterDistribution::linkParameter(std::string par_name)
-";
-
-%feature("docstring") ParameterDistribution::getMainParameterName "std::string ParameterDistribution::getMainParameterName() const
-
-get the main parameter's name
-";
-
-%feature("docstring") ParameterDistribution::getNbrSamples "size_t ParameterDistribution::getNbrSamples() const
-
-get number of samples for this distribution
-";
-
-%feature("docstring") ParameterDistribution::getSigmaFactor "double ParameterDistribution::getSigmaFactor() const
-
-get the sigma factor
-";
-
-%feature("docstring") ParameterDistribution::getDistribution "const IDistribution1D * ParameterDistribution::getDistribution() const
-";
-
-%feature("docstring") ParameterDistribution::getDistribution "IDistribution1D * ParameterDistribution::getDistribution()
-";
-
-%feature("docstring") ParameterDistribution::generateSamples "std::vector< ParameterSample > ParameterDistribution::generateSamples() const
-
-generate list of sampled values with their weight
-";
-
-%feature("docstring") ParameterDistribution::getLinkedParameterNames "std::vector<std::string> ParameterDistribution::getLinkedParameterNames() const
-
-get list of linked parameter names
-";
-
-%feature("docstring") ParameterDistribution::getLimits "RealLimits ParameterDistribution::getLimits() const
-";
-
-%feature("docstring") ParameterDistribution::getMinValue "double ParameterDistribution::getMinValue() const
-";
-
-%feature("docstring") ParameterDistribution::getMaxValue "double ParameterDistribution::getMaxValue() const
-";
-
-
-// File: classParameterPattern.xml
-%feature("docstring") ParameterPattern "
-
-Helper class for constructing parameter patterns.
-
-C++ includes: ParameterPattern.h
-";
-
-%feature("docstring") ParameterPattern::ParameterPattern "ParameterPattern::ParameterPattern()
-";
-
-%feature("docstring") ParameterPattern::ParameterPattern "ParameterPattern::ParameterPattern(std::string root_object)
-";
-
-%feature("docstring") ParameterPattern::beginsWith "ParameterPattern & ParameterPattern::beginsWith(std::string start_type)
-";
-
-%feature("docstring") ParameterPattern::add "ParameterPattern & ParameterPattern::add(std::string object_type)
-";
-
-%feature("docstring") ParameterPattern::toStdString "std::string ParameterPattern::toStdString() const
-";
-
-
-// File: classParameterSample.xml
-%feature("docstring") ParameterSample "
-
-A parameter value with a weight, as obtained when sampling from a distribution.
-
-C++ includes: ParameterSample.h
-";
-
-%feature("docstring") ParameterSample::ParameterSample "ParameterSample::ParameterSample(double _value=0., double _weight=1.)
-";
-
-
// File: classParticle.xml
%feature("docstring") Particle "
@@ -11540,7 +11045,7 @@ Sets q resolution values via ScanResolution object.
%feature("docstring") QSpecScan::setRelativeQResolution "void QSpecScan::setRelativeQResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
-Sets qz resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
+Sets qz resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
";
%feature("docstring") QSpecScan::setAbsoluteQResolution "void QSpecScan::setAbsoluteQResolution(const RangedDistribution &distr, double std_dev)
@@ -11548,7 +11053,7 @@ Sets qz resolution values via RangedDistribution and values of relative deviati
%feature("docstring") QSpecScan::setAbsoluteQResolution "void QSpecScan::setAbsoluteQResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
-Sets qz resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
+Sets qz resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
";
@@ -11564,198 +11069,6 @@ C++ includes: ParaCrystalBuilder.h
";
-// File: classRangedDistribution.xml
-%feature("docstring") RangedDistribution "
-
-Interface for one-dimensional ranged distributions. All derived distributions allow for generating samples in-place for known mean and standard deviation (except for RangedDistributionLorentz which uses median and hwhm).
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution()
-";
-
-%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution(size_t n_samples, double sigma_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistribution::clone "RangedDistribution* RangedDistribution::clone() const override=0
-";
-
-%feature("docstring") RangedDistribution::~RangedDistribution "RangedDistribution::~RangedDistribution() override
-";
-
-%feature("docstring") RangedDistribution::generateSamples "std::vector< ParameterSample > RangedDistribution::generateSamples(double mean, double stddev) const
-";
-
-%feature("docstring") RangedDistribution::generateSamples "std::vector< std::vector< ParameterSample > > RangedDistribution::generateSamples(const std::vector< double > &mean, const std::vector< double > &stddev) const
-
-Generates list of sampled values with their weights from given means and standard deviations.
-";
-
-%feature("docstring") RangedDistribution::distribution "std::unique_ptr< IDistribution1D > RangedDistribution::distribution(double mean, double stddev) const
-
-Public interface function to underlying IDistribution1D object.
-";
-
-%feature("docstring") RangedDistribution::limits "RealLimits RangedDistribution::limits() const
-
-Returns current limits of the distribution.
-";
-
-%feature("docstring") RangedDistribution::sigmaFactor "double RangedDistribution::sigmaFactor() const
-
-Returns sigma factor to use during sampling.
-";
-
-%feature("docstring") RangedDistribution::nSamples "size_t RangedDistribution::nSamples() const
-
-Returns number of samples to generate.
-";
-
-%feature("docstring") RangedDistribution::setLimits "void RangedDistribution::setLimits(const RealLimits &limits)
-";
-
-%feature("docstring") RangedDistribution::pyString "std::string RangedDistribution::pyString() const
-
-Prints python-formatted definition of the distribution.
-";
-
-
-// File: classRangedDistributionCosine.xml
-%feature("docstring") RangedDistributionCosine "
-
-Cosine distribution.
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine()
-";
-
-%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistributionCosine::clone "RangedDistributionCosine * RangedDistributionCosine::clone() const override
-";
-
-%feature("docstring") RangedDistributionCosine::~RangedDistributionCosine "RangedDistributionCosine::~RangedDistributionCosine() override=default
-";
-
-
-// File: classRangedDistributionGate.xml
-%feature("docstring") RangedDistributionGate "
-
-Uniform distribution function.
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate()
-";
-
-%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistributionGate::clone "RangedDistributionGate * RangedDistributionGate::clone() const override
-";
-
-%feature("docstring") RangedDistributionGate::~RangedDistributionGate "RangedDistributionGate::~RangedDistributionGate() override=default
-";
-
-
-// File: classRangedDistributionGaussian.xml
-%feature("docstring") RangedDistributionGaussian "
-
-Gaussian distribution with standard deviation std_dev.
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian()
-";
-
-%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistributionGaussian::clone "RangedDistributionGaussian * RangedDistributionGaussian::clone() const override
-";
-
-%feature("docstring") RangedDistributionGaussian::~RangedDistributionGaussian "RangedDistributionGaussian::~RangedDistributionGaussian() override=default
-";
-
-
-// File: classRangedDistributionLogNormal.xml
-%feature("docstring") RangedDistributionLogNormal "
-
-Log-normal distribution.
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal()
-";
-
-%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistributionLogNormal::clone "RangedDistributionLogNormal * RangedDistributionLogNormal::clone() const override
-";
-
-%feature("docstring") RangedDistributionLogNormal::~RangedDistributionLogNormal "RangedDistributionLogNormal::~RangedDistributionLogNormal() override=default
-";
-
-
-// File: classRangedDistributionLorentz.xml
-%feature("docstring") RangedDistributionLorentz "
-
-Lorentz distribution with median and hwhm.
-
-C++ includes: RangedDistributions.h
-";
-
-%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz()
-";
-
-%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, const RealLimits &limits=RealLimits::limitless())
-";
-
-%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max)
-
-Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, hwhm_factor = 2.0, while the limits are (-inf, +inf).
-";
-
-%feature("docstring") RangedDistributionLorentz::clone "RangedDistributionLorentz * RangedDistributionLorentz::clone() const override
-";
-
-%feature("docstring") RangedDistributionLorentz::~RangedDistributionLorentz "RangedDistributionLorentz::~RangedDistributionLorentz() override=default
-";
-
-
// File: structLattice2D_1_1ReciprocalBases.xml
%feature("docstring") Lattice2D::ReciprocalBases "";
@@ -14693,10 +14006,10 @@ C++ includes: WavevectorInfo.h
";
-// File: classFourierTransform_1_1Workspace.xml
+// File: classConvolve_1_1Workspace.xml
-// File: classConvolve_1_1Workspace.xml
+// File: classFourierTransform_1_1Workspace.xml
// File: classZLimits.xml
@@ -14837,70 +14150,61 @@ C++ includes: ZLimits.h
// File: namespace_0d4.xml
-// File: namespace_0d403.xml
+// File: namespace_0d409.xml
-// File: namespace_0d410.xml
+// File: namespace_0d442.xml
-// File: namespace_0d414.xml
+// File: namespace_0d447.xml
-// File: namespace_0d424.xml
+// File: namespace_0d449.xml
-// File: namespace_0d457.xml
+// File: namespace_0d459.xml
-// File: namespace_0d462.xml
+// File: namespace_0d465.xml
-// File: namespace_0d464.xml
+// File: namespace_0d469.xml
-// File: namespace_0d474.xml
+// File: namespace_0d477.xml
-// File: namespace_0d480.xml
+// File: namespace_0d500.xml
-// File: namespace_0d484.xml
+// File: namespace_0d508.xml
-// File: namespace_0d492.xml
+// File: namespace_0d514.xml
-// File: namespace_0d515.xml
+// File: namespace_0d516.xml
-// File: namespace_0d523.xml
+// File: namespace_0d527.xml
-// File: namespace_0d529.xml
+// File: namespace_0d539.xml
-// File: namespace_0d531.xml
+// File: namespace_0d545.xml
-// File: namespace_0d542.xml
+// File: namespace_0d549.xml
-// File: namespace_0d554.xml
+// File: namespace_0d567.xml
-// File: namespace_0d560.xml
+// File: namespace_0d586.xml
-// File: namespace_0d564.xml
-
-
-// File: namespace_0d582.xml
-
-
-// File: namespace_0d601.xml
-
-
-// File: namespace_0d615.xml
+// File: namespace_0d600.xml
// File: namespace_0d78.xml
@@ -15283,18 +14587,6 @@ Returns default metric name.
";
-// File: namespaceParameterUtils.xml
-%feature("docstring") ParameterUtils::isAngleRelated "bool ParameterUtils::isAngleRelated(const std::string &par_name)
-
-Returns true if given parameter name is related to angles.
-";
-
-%feature("docstring") ParameterUtils::poolParameterUnits "std::string ParameterUtils::poolParameterUnits(const IParameterized &node, const std::string &parName)
-
-Returns units of main parameter.
-";
-
-
// File: namespacePyArrayImport.xml
%feature("docstring") PyArrayImport::importArrayToOutputData "OutputData< double > * PyArrayImport::importArrayToOutputData(const std::vector< double > &vec)
@@ -15307,16 +14599,6 @@ for importing 2D array of doubles from python into OutputData
";
-// File: namespacepyfmt.xml
-%feature("docstring") pyfmt::printRealLimits "std::string pyfmt::printRealLimits(const RealLimits &limits, const std::string &units)
-";
-
-%feature("docstring") pyfmt::printRealLimitsArg "std::string pyfmt::printRealLimitsArg(const RealLimits &limits, const std::string &units)
-
-Prints RealLimits in the form of argument (in the context of ParameterDistribution and similar). Default RealLimits will not be printed, any other will be printed as \", ba.RealLimits.limited(1*deg, 2*deg)\"
-";
-
-
// File: namespacepyfmt2.xml
%feature("docstring") pyfmt2::representShape2D "std::string pyfmt2::representShape2D(const std::string &indent, const IShape2D *ishape, bool mask_value, std::function< std::string(double)> printValueFunc)
@@ -16938,51 +16220,6 @@ magnetization (in A/m)
// File: SSCApproximationStrategy_8h.xml
-// File: DistributionHandler_8cpp.xml
-
-
-// File: DistributionHandler_8h.xml
-
-
-// File: Distributions_8cpp.xml
-
-
-// File: Distributions_8h.xml
-
-
-// File: ParameterDistribution_8cpp.xml
-
-
-// File: ParameterDistribution_8h.xml
-
-
-// File: ParameterPattern_8cpp.xml
-
-
-// File: ParameterPattern_8h.xml
-
-
-// File: ParameterSample_8h.xml
-
-
-// File: ParameterUtils_8cpp.xml
-
-
-// File: ParameterUtils_8h.xml
-
-
-// File: PyFmtLimits_8cpp.xml
-
-
-// File: PyFmtLimits_8h.xml
-
-
-// File: RangedDistributions_8cpp.xml
-
-
-// File: RangedDistributions_8h.xml
-
-
// File: Crystal_8cpp.xml
@@ -17709,9 +16946,6 @@ Generate vertices of centered ellipse with given semi-axes at height z.
// File: dir_c21740227f50b02f28bdacfb625f042a.xml
-// File: dir_d4e34ce36424db6c5895519defe19e58.xml
-
-
// File: dir_3a34810b9fbc1682c26e767b1a1a5860.xml
diff --git a/auto/Wrap/doxygenParam.i b/auto/Wrap/doxygenParam.i
index e35a6a04ab82f35fccd3b554d9c4f1e41b57bae1..b2a6e5e3ff54f69503aa44895a0c50344c4e2f19 100644
--- a/auto/Wrap/doxygenParam.i
+++ b/auto/Wrap/doxygenParam.i
@@ -1,6 +1,413 @@
// File: index.xml
+// File: classDistributionCosine.xml
+%feature("docstring") DistributionCosine "
+
+Cosine distribution.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine(double mean, double sigma)
+";
+
+%feature("docstring") DistributionCosine::DistributionCosine "DistributionCosine::DistributionCosine()
+";
+
+%feature("docstring") DistributionCosine::clone "DistributionCosine* DistributionCosine::clone() const final
+";
+
+%feature("docstring") DistributionCosine::probabilityDensity "double DistributionCosine::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionCosine::getMean "double DistributionCosine::getMean() const final
+
+Returns the distribution-specific mean.
+";
+
+%feature("docstring") DistributionCosine::getSigma "double DistributionCosine::getSigma() const
+";
+
+%feature("docstring") DistributionCosine::equidistantPoints "std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
+
+generate list of sample values
+";
+
+%feature("docstring") DistributionCosine::isDelta "bool DistributionCosine::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionCosine::accept "void DistributionCosine::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+
+// File: classDistributionGate.xml
+%feature("docstring") DistributionGate "
+
+Uniform distribution function with half width hwhm.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate(double min, double max)
+";
+
+%feature("docstring") DistributionGate::DistributionGate "DistributionGate::DistributionGate()
+";
+
+%feature("docstring") DistributionGate::clone "DistributionGate* DistributionGate::clone() const final
+";
+
+%feature("docstring") DistributionGate::probabilityDensity "double DistributionGate::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionGate::getMean "double DistributionGate::getMean() const final
+
+Returns the distribution-specific mean.
+";
+
+%feature("docstring") DistributionGate::getMin "double DistributionGate::getMin() const
+";
+
+%feature("docstring") DistributionGate::getMax "double DistributionGate::getMax() const
+";
+
+%feature("docstring") DistributionGate::equidistantPoints "std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
+
+Returns list of sample values.
+";
+
+%feature("docstring") DistributionGate::isDelta "bool DistributionGate::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionGate::accept "void DistributionGate::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+
+// File: classDistributionGaussian.xml
+%feature("docstring") DistributionGaussian "
+
+Gaussian distribution with standard deviation std_dev.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian(double mean, double std_dev)
+";
+
+%feature("docstring") DistributionGaussian::DistributionGaussian "DistributionGaussian::DistributionGaussian()
+";
+
+%feature("docstring") DistributionGaussian::clone "DistributionGaussian* DistributionGaussian::clone() const final
+";
+
+%feature("docstring") DistributionGaussian::probabilityDensity "double DistributionGaussian::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionGaussian::getMean "double DistributionGaussian::getMean() const final
+
+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
+
+generate list of sample values
+";
+
+%feature("docstring") DistributionGaussian::isDelta "bool DistributionGaussian::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionGaussian::accept "void DistributionGaussian::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+
+// File: classDistributionHandler.xml
+%feature("docstring") DistributionHandler "
+
+Provides the functionality to average over parameter distributions with weights.
+
+C++ includes: DistributionHandler.h
+";
+
+%feature("docstring") DistributionHandler::DistributionHandler "DistributionHandler::DistributionHandler()
+";
+
+%feature("docstring") DistributionHandler::~DistributionHandler "DistributionHandler::~DistributionHandler()
+";
+
+%feature("docstring") DistributionHandler::addParameterDistribution "void DistributionHandler::addParameterDistribution(const std::string ¶m_name, const IDistribution1D &distribution, size_t nbr_samples, double sigma_factor=0.0, const RealLimits &limits=RealLimits())
+
+add a sampled parameter distribution
+";
+
+%feature("docstring") DistributionHandler::addParameterDistribution "void DistributionHandler::addParameterDistribution(const ParameterDistribution &par_distr)
+";
+
+%feature("docstring") DistributionHandler::getTotalNumberOfSamples "size_t DistributionHandler::getTotalNumberOfSamples() const
+
+get the total number of parameter value combinations (product of the individual sizes of each parameter distribution
+";
+
+%feature("docstring") DistributionHandler::setParameterValues "double DistributionHandler::setParameterValues(ParameterPool *p_parameter_pool, size_t index)
+
+set the parameter values of the simulation object to a specific combination of values, determined by the index (which must be smaller than the total number of combinations) and returns the weight associated with this combination of parameter values
+";
+
+%feature("docstring") DistributionHandler::setParameterToMeans "void DistributionHandler::setParameterToMeans(ParameterPool *p_parameter_pool) const
+
+Sets mean distribution values to the parameter pool.
+";
+
+%feature("docstring") DistributionHandler::getDistributions "const DistributionHandler::Distributions_t & DistributionHandler::getDistributions() const
+";
+
+
+// File: classDistributionLogNormal.xml
+%feature("docstring") DistributionLogNormal "
+
+Log-normal distribution.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal(double median, double scale_param)
+";
+
+%feature("docstring") DistributionLogNormal::DistributionLogNormal "DistributionLogNormal::DistributionLogNormal()=delete
+";
+
+%feature("docstring") DistributionLogNormal::clone "DistributionLogNormal* DistributionLogNormal::clone() const final
+";
+
+%feature("docstring") DistributionLogNormal::probabilityDensity "double DistributionLogNormal::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionLogNormal::getMean "double DistributionLogNormal::getMean() const final
+
+Returns the distribution-specific mean.
+";
+
+%feature("docstring") DistributionLogNormal::getMedian "double DistributionLogNormal::getMedian() const
+";
+
+%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
+
+generate list of sample values
+";
+
+%feature("docstring") DistributionLogNormal::isDelta "bool DistributionLogNormal::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionLogNormal::accept "void DistributionLogNormal::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+%feature("docstring") DistributionLogNormal::setUnits "void DistributionLogNormal::setUnits(const std::string &units)
+
+Sets distribution units.
+";
+
+
+// File: classDistributionLorentz.xml
+%feature("docstring") DistributionLorentz "
+
+Lorentz distribution with half width hwhm.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz(double mean, double hwhm)
+";
+
+%feature("docstring") DistributionLorentz::DistributionLorentz "DistributionLorentz::DistributionLorentz()
+";
+
+%feature("docstring") DistributionLorentz::clone "DistributionLorentz* DistributionLorentz::clone() const final
+";
+
+%feature("docstring") DistributionLorentz::probabilityDensity "double DistributionLorentz::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionLorentz::getMean "double DistributionLorentz::getMean() const final
+
+Returns the distribution-specific mean.
+";
+
+%feature("docstring") DistributionLorentz::getHWHM "double DistributionLorentz::getHWHM() const
+";
+
+%feature("docstring") DistributionLorentz::equidistantPoints "std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
+
+generate list of sample values
+";
+
+%feature("docstring") DistributionLorentz::isDelta "bool DistributionLorentz::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionLorentz::accept "void DistributionLorentz::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+
+// File: classDistributionTrapezoid.xml
+%feature("docstring") DistributionTrapezoid "
+
+Trapezoidal distribution.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid(const std::vector< double > P)
+";
+
+%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid(double center, double left, double middle, double right)
+";
+
+%feature("docstring") DistributionTrapezoid::DistributionTrapezoid "DistributionTrapezoid::DistributionTrapezoid()
+";
+
+%feature("docstring") DistributionTrapezoid::clone "DistributionTrapezoid* DistributionTrapezoid::clone() const final
+";
+
+%feature("docstring") DistributionTrapezoid::probabilityDensity "double DistributionTrapezoid::probabilityDensity(double x) const final
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") DistributionTrapezoid::getMean "double DistributionTrapezoid::getMean() const final
+
+Returns the distribution-specific mean.
+";
+
+%feature("docstring") DistributionTrapezoid::getLeftWidth "double DistributionTrapezoid::getLeftWidth() const
+";
+
+%feature("docstring") DistributionTrapezoid::getMiddleWidth "double DistributionTrapezoid::getMiddleWidth() const
+";
+
+%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
+
+generate list of sample values
+";
+
+%feature("docstring") DistributionTrapezoid::isDelta "bool DistributionTrapezoid::isDelta() const final
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") DistributionTrapezoid::accept "void DistributionTrapezoid::accept(INodeVisitor *visitor) const final
+
+Calls the INodeVisitor's visit method.
+";
+
+
+// File: classIDistribution1D.xml
+%feature("docstring") IDistribution1D "
+
+Interface for one-dimensional distributions.
+
+C++ includes: Distributions.h
+";
+
+%feature("docstring") IDistribution1D::IDistribution1D "IDistribution1D::IDistribution1D(const NodeMeta &meta, const std::vector< double > &PValues)
+";
+
+%feature("docstring") IDistribution1D::clone "virtual IDistribution1D* IDistribution1D::clone() const =0
+";
+
+%feature("docstring") IDistribution1D::probabilityDensity "virtual double IDistribution1D::probabilityDensity(double x) const =0
+
+Returns the distribution-specific probability density for value x.
+";
+
+%feature("docstring") IDistribution1D::getMean "virtual double IDistribution1D::getMean() const =0
+
+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
+
+Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
+";
+
+%feature("docstring") IDistribution1D::equidistantSamplesInRange "std::vector< ParameterSample > IDistribution1D::equidistantSamplesInRange(size_t nbr_samples, double xmin, double xmax) const
+
+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
+
+Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor.
+";
+
+%feature("docstring") IDistribution1D::equidistantPointsInRange "std::vector< double > IDistribution1D::equidistantPointsInRange(size_t nbr_samples, double xmin, double xmax) const
+
+Returns equidistant interpolation points from xmin to xmax.
+";
+
+%feature("docstring") IDistribution1D::isDelta "virtual bool IDistribution1D::isDelta() const =0
+
+Returns true if the distribution is in the limit case of a Dirac delta distribution.
+";
+
+%feature("docstring") IDistribution1D::setUnits "void IDistribution1D::setUnits(const std::string &units)
+
+Sets distribution units.
+";
+
+
// File: classINode.xml
%feature("docstring") INode "
@@ -706,6 +1113,94 @@ C++ includes: INode.h
";
+// File: classParameterDistribution.xml
+%feature("docstring") ParameterDistribution "
+
+A parametric distribution function, for use with any model parameter.
+
+C++ includes: ParameterDistribution.h
+";
+
+%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const std::string &par_name, const IDistribution1D &distribution, size_t nbr_samples, double sigma_factor=0.0, const RealLimits &limits=RealLimits())
+";
+
+%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const std::string &par_name, const IDistribution1D &distribution, size_t nbr_samples, double xmin, double xmax)
+";
+
+%feature("docstring") ParameterDistribution::ParameterDistribution "ParameterDistribution::ParameterDistribution(const ParameterDistribution &other)
+";
+
+%feature("docstring") ParameterDistribution::~ParameterDistribution "ParameterDistribution::~ParameterDistribution()
+";
+
+%feature("docstring") ParameterDistribution::linkParameter "ParameterDistribution & ParameterDistribution::linkParameter(std::string par_name)
+";
+
+%feature("docstring") ParameterDistribution::getMainParameterName "std::string ParameterDistribution::getMainParameterName() const
+
+get the main parameter's name
+";
+
+%feature("docstring") ParameterDistribution::getNbrSamples "size_t ParameterDistribution::getNbrSamples() const
+
+get number of samples for this distribution
+";
+
+%feature("docstring") ParameterDistribution::getSigmaFactor "double ParameterDistribution::getSigmaFactor() const
+
+get the sigma factor
+";
+
+%feature("docstring") ParameterDistribution::getDistribution "const IDistribution1D * ParameterDistribution::getDistribution() const
+";
+
+%feature("docstring") ParameterDistribution::getDistribution "IDistribution1D * ParameterDistribution::getDistribution()
+";
+
+%feature("docstring") ParameterDistribution::generateSamples "std::vector< ParameterSample > ParameterDistribution::generateSamples() const
+
+generate list of sampled values with their weight
+";
+
+%feature("docstring") ParameterDistribution::getLinkedParameterNames "std::vector<std::string> ParameterDistribution::getLinkedParameterNames() const
+
+get list of linked parameter names
+";
+
+%feature("docstring") ParameterDistribution::getLimits "RealLimits ParameterDistribution::getLimits() const
+";
+
+%feature("docstring") ParameterDistribution::getMinValue "double ParameterDistribution::getMinValue() const
+";
+
+%feature("docstring") ParameterDistribution::getMaxValue "double ParameterDistribution::getMaxValue() const
+";
+
+
+// File: classParameterPattern.xml
+%feature("docstring") ParameterPattern "
+
+Helper class for constructing parameter patterns.
+
+C++ includes: ParameterPattern.h
+";
+
+%feature("docstring") ParameterPattern::ParameterPattern "ParameterPattern::ParameterPattern()
+";
+
+%feature("docstring") ParameterPattern::ParameterPattern "ParameterPattern::ParameterPattern(std::string root_object)
+";
+
+%feature("docstring") ParameterPattern::beginsWith "ParameterPattern & ParameterPattern::beginsWith(std::string start_type)
+";
+
+%feature("docstring") ParameterPattern::add "ParameterPattern & ParameterPattern::add(std::string object_type)
+";
+
+%feature("docstring") ParameterPattern::toStdString "std::string ParameterPattern::toStdString() const
+";
+
+
// File: classParameterPool.xml
%feature("docstring") ParameterPool "
@@ -801,6 +1296,18 @@ Removes parameter with given name from the pool.
";
+// File: classParameterSample.xml
+%feature("docstring") ParameterSample "
+
+A parameter value with a weight, as obtained when sampling from a distribution.
+
+C++ includes: ParameterSample.h
+";
+
+%feature("docstring") ParameterSample::ParameterSample "ParameterSample::ParameterSample(double _value=0., double _weight=1.)
+";
+
+
// File: classPostorderStrategy.xml
%feature("docstring") PostorderStrategy "
@@ -849,6 +1356,198 @@ C++ includes: IterationStrategy.h
";
+// File: classRangedDistribution.xml
+%feature("docstring") RangedDistribution "
+
+Interface for one-dimensional ranged distributions. All derived distributions allow for generating samples in-place for known mean and standard deviation (except for RangedDistributionLorentz which uses median and hwhm).
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution()
+";
+
+%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistribution::RangedDistribution "RangedDistribution::RangedDistribution(size_t n_samples, double sigma_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistribution::clone "RangedDistribution* RangedDistribution::clone() const override=0
+";
+
+%feature("docstring") RangedDistribution::~RangedDistribution "RangedDistribution::~RangedDistribution() override
+";
+
+%feature("docstring") RangedDistribution::generateSamples "std::vector< ParameterSample > RangedDistribution::generateSamples(double mean, double stddev) const
+";
+
+%feature("docstring") RangedDistribution::generateSamples "std::vector< std::vector< ParameterSample > > RangedDistribution::generateSamples(const std::vector< double > &mean, const std::vector< double > &stddev) const
+
+Generates list of sampled values with their weights from given means and standard deviations.
+";
+
+%feature("docstring") RangedDistribution::distribution "std::unique_ptr< IDistribution1D > RangedDistribution::distribution(double mean, double stddev) const
+
+Public interface function to underlying IDistribution1D object.
+";
+
+%feature("docstring") RangedDistribution::limits "RealLimits RangedDistribution::limits() const
+
+Returns current limits of the distribution.
+";
+
+%feature("docstring") RangedDistribution::sigmaFactor "double RangedDistribution::sigmaFactor() const
+
+Returns sigma factor to use during sampling.
+";
+
+%feature("docstring") RangedDistribution::nSamples "size_t RangedDistribution::nSamples() const
+
+Returns number of samples to generate.
+";
+
+%feature("docstring") RangedDistribution::setLimits "void RangedDistribution::setLimits(const RealLimits &limits)
+";
+
+%feature("docstring") RangedDistribution::pyString "std::string RangedDistribution::pyString() const
+
+Prints python-formatted definition of the distribution.
+";
+
+
+// File: classRangedDistributionCosine.xml
+%feature("docstring") RangedDistributionCosine "
+
+Cosine distribution.
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine()
+";
+
+%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistributionCosine::RangedDistributionCosine "RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistributionCosine::clone "RangedDistributionCosine * RangedDistributionCosine::clone() const override
+";
+
+%feature("docstring") RangedDistributionCosine::~RangedDistributionCosine "RangedDistributionCosine::~RangedDistributionCosine() override=default
+";
+
+
+// File: classRangedDistributionGate.xml
+%feature("docstring") RangedDistributionGate "
+
+Uniform distribution function.
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate()
+";
+
+%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistributionGate::RangedDistributionGate "RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistributionGate::clone "RangedDistributionGate * RangedDistributionGate::clone() const override
+";
+
+%feature("docstring") RangedDistributionGate::~RangedDistributionGate "RangedDistributionGate::~RangedDistributionGate() override=default
+";
+
+
+// File: classRangedDistributionGaussian.xml
+%feature("docstring") RangedDistributionGaussian "
+
+Gaussian distribution with standard deviation std_dev.
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian()
+";
+
+%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistributionGaussian::RangedDistributionGaussian "RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistributionGaussian::clone "RangedDistributionGaussian * RangedDistributionGaussian::clone() const override
+";
+
+%feature("docstring") RangedDistributionGaussian::~RangedDistributionGaussian "RangedDistributionGaussian::~RangedDistributionGaussian() override=default
+";
+
+
+// File: classRangedDistributionLogNormal.xml
+%feature("docstring") RangedDistributionLogNormal "
+
+Log-normal distribution.
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal()
+";
+
+%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistributionLogNormal::RangedDistributionLogNormal "RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistributionLogNormal::clone "RangedDistributionLogNormal * RangedDistributionLogNormal::clone() const override
+";
+
+%feature("docstring") RangedDistributionLogNormal::~RangedDistributionLogNormal "RangedDistributionLogNormal::~RangedDistributionLogNormal() override=default
+";
+
+
+// File: classRangedDistributionLorentz.xml
+%feature("docstring") RangedDistributionLorentz "
+
+Lorentz distribution with median and hwhm.
+
+C++ includes: RangedDistributions.h
+";
+
+%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz()
+";
+
+%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, const RealLimits &limits=RealLimits::limitless())
+";
+
+%feature("docstring") RangedDistributionLorentz::RangedDistributionLorentz "RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max)
+
+Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, hwhm_factor = 2.0, while the limits are (-inf, +inf).
+";
+
+%feature("docstring") RangedDistributionLorentz::clone "RangedDistributionLorentz * RangedDistributionLorentz::clone() const override
+";
+
+%feature("docstring") RangedDistributionLorentz::~RangedDistributionLorentz "RangedDistributionLorentz::~RangedDistributionLorentz() override=default
+";
+
+
// File: classRealParameter.xml
%feature("docstring") RealParameter "
@@ -916,9 +1615,18 @@ C++ includes: Unit.h
";
+// File: namespace_0d12.xml
+
+
// File: namespace_0d16.xml
+// File: namespace_0d24.xml
+
+
+// File: namespace_0d29.xml
+
+
// File: namespaceNodeUtils.xml
%feature("docstring") NodeUtils::nodeToString "std::string NodeUtils::nodeToString(const INode &node)
@@ -931,6 +1639,28 @@ Returns path composed of node's displayName, with respect to root node.
";
+// File: namespaceParameterUtils.xml
+%feature("docstring") ParameterUtils::isAngleRelated "bool ParameterUtils::isAngleRelated(const std::string &par_name)
+
+Returns true if given parameter name is related to angles.
+";
+
+%feature("docstring") ParameterUtils::poolParameterUnits "std::string ParameterUtils::poolParameterUnits(const IParameterized &node, const std::string &parName)
+
+Returns units of main parameter.
+";
+
+
+// File: namespacepyfmt.xml
+%feature("docstring") pyfmt::printRealLimits "std::string pyfmt::printRealLimits(const RealLimits &limits, const std::string &units)
+";
+
+%feature("docstring") pyfmt::printRealLimitsArg "std::string pyfmt::printRealLimitsArg(const RealLimits &limits, const std::string &units)
+
+Prints RealLimits in the form of argument (in the context of ParameterDistribution and similar). Default RealLimits will not be printed, any other will be printed as \", ba.RealLimits.limited(1*deg, 2*deg)\"
+";
+
+
// File: IParameter_8h.xml
@@ -961,6 +1691,30 @@ Returns path composed of node's displayName, with respect to root node.
// File: Unit_8h.xml
+// File: DistributionHandler_8cpp.xml
+
+
+// File: DistributionHandler_8h.xml
+
+
+// File: Distributions_8cpp.xml
+
+
+// File: Distributions_8h.xml
+
+
+// File: ParameterDistribution_8cpp.xml
+
+
+// File: ParameterDistribution_8h.xml
+
+
+// File: RangedDistributions_8cpp.xml
+
+
+// File: RangedDistributions_8h.xml
+
+
// File: INode_8cpp.xml
%feature("docstring") nodeMetaUnion "NodeMeta nodeMetaUnion(const std::vector< ParaMeta > &base, const NodeMeta &other)
";
@@ -999,11 +1753,38 @@ Returns path composed of node's displayName, with respect to root node.
// File: NodeUtils_8h.xml
+// File: ParameterPattern_8cpp.xml
+
+
+// File: ParameterPattern_8h.xml
+
+
+// File: ParameterSample_8h.xml
+
+
+// File: ParameterUtils_8cpp.xml
+
+
+// File: ParameterUtils_8h.xml
+
+
+// File: PyFmtLimits_8cpp.xml
+
+
+// File: PyFmtLimits_8h.xml
+
+
// File: dir_a1f38e94e849d0203a55ad5a19f2f15a.xml
+// File: dir_dabc42ad3745509abd3a496944bb880e.xml
+
+
// File: dir_a98fb20d64e2aea67a6e042d91197081.xml
// File: dir_d452a16c8784395bb8c21da516e88a7f.xml
+
+// File: dir_dda74d2e7a2b62d18fb900593a370493.xml
+
diff --git a/auto/Wrap/libBornAgainBase.py b/auto/Wrap/libBornAgainBase.py
index 8e58a1b284fbcc72e3cf8def9c3499e9dd98d914..b1d007b23c331489c9f8b5396a184d63d5650e17 100644
--- a/auto/Wrap/libBornAgainBase.py
+++ b/auto/Wrap/libBornAgainBase.py
@@ -404,6 +404,54 @@ def GeneratePoissonRandom(average):
"""
return _libBornAgainBase.GeneratePoissonRandom(average)
+class ThreadInfo(object):
+ r"""
+
+
+ Information to run simulation with dedicated number of threads.
+
+ C++ includes: ThreadInfo.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self):
+ r"""
+ __init__(ThreadInfo self) -> ThreadInfo
+ ThreadInfo::ThreadInfo()
+
+ """
+ _libBornAgainBase.ThreadInfo_swiginit(self, _libBornAgainBase.new_ThreadInfo())
+ n_threads = property(_libBornAgainBase.ThreadInfo_n_threads_get, _libBornAgainBase.ThreadInfo_n_threads_set, doc=r"""n_threads : unsigned int""")
+ n_batches = property(_libBornAgainBase.ThreadInfo_n_batches_get, _libBornAgainBase.ThreadInfo_n_batches_set, doc=r"""n_batches : unsigned int""")
+ current_batch = property(_libBornAgainBase.ThreadInfo_current_batch_get, _libBornAgainBase.ThreadInfo_current_batch_set, doc=r"""current_batch : unsigned int""")
+ __swig_destroy__ = _libBornAgainBase.delete_ThreadInfo
+
+# Register ThreadInfo in _libBornAgainBase:
+_libBornAgainBase.ThreadInfo_swigregister(ThreadInfo)
+cvar = _libBornAgainBase.cvar
+I = cvar.I
+nanometer = cvar.nanometer
+angstrom = cvar.angstrom
+micrometer = cvar.micrometer
+millimeter = cvar.millimeter
+meter = cvar.meter
+nm = cvar.nm
+nm2 = cvar.nm2
+barn = cvar.barn
+radian = cvar.radian
+milliradian = cvar.milliradian
+degree = cvar.degree
+steradian = cvar.steradian
+rad = cvar.rad
+mrad = cvar.mrad
+sr = cvar.sr
+deg = cvar.deg
+tesla = cvar.tesla
+gauss = cvar.gauss
+
def vecOfLambdaAlphaPhi(_lambda, _alpha, _phi):
r"""
@@ -631,26 +679,6 @@ class kvector_t(object):
# Register kvector_t in _libBornAgainBase:
_libBornAgainBase.kvector_t_swigregister(kvector_t)
-cvar = _libBornAgainBase.cvar
-I = cvar.I
-nanometer = cvar.nanometer
-angstrom = cvar.angstrom
-micrometer = cvar.micrometer
-millimeter = cvar.millimeter
-meter = cvar.meter
-nm = cvar.nm
-nm2 = cvar.nm2
-barn = cvar.barn
-radian = cvar.radian
-milliradian = cvar.milliradian
-degree = cvar.degree
-steradian = cvar.steradian
-rad = cvar.rad
-mrad = cvar.mrad
-sr = cvar.sr
-deg = cvar.deg
-tesla = cvar.tesla
-gauss = cvar.gauss
class vector_kvector_t(object):
r"""Proxy of C++ std::vector< BasicVector3D< double > > class."""
diff --git a/auto/Wrap/libBornAgainBase_wrap.cpp b/auto/Wrap/libBornAgainBase_wrap.cpp
index 6dfb27d29f80483e27fb42fca0bc67aef69e705c..85022f30b4248e2ed86397b8b09856befd66b65f 100644
--- a/auto/Wrap/libBornAgainBase_wrap.cpp
+++ b/auto/Wrap/libBornAgainBase_wrap.cpp
@@ -3101,31 +3101,32 @@ namespace Swig {
#define SWIGTYPE_p_BasicVector3DT_int_t swig_types[1]
#define SWIGTYPE_p_BasicVector3DT_std__complexT_double_t_t swig_types[2]
#define SWIGTYPE_p_ICloneable swig_types[3]
-#define SWIGTYPE_p_allocator_type swig_types[4]
-#define SWIGTYPE_p_char swig_types[5]
-#define SWIGTYPE_p_difference_type swig_types[6]
-#define SWIGTYPE_p_int swig_types[7]
-#define SWIGTYPE_p_long_long swig_types[8]
-#define SWIGTYPE_p_p_PyObject swig_types[9]
-#define SWIGTYPE_p_short swig_types[10]
-#define SWIGTYPE_p_signed_char swig_types[11]
-#define SWIGTYPE_p_size_type swig_types[12]
-#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_double_t_t swig_types[13]
-#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t swig_types[14]
-#define SWIGTYPE_p_std__complexT_double_t swig_types[15]
-#define SWIGTYPE_p_std__invalid_argument swig_types[16]
-#define SWIGTYPE_p_std__vectorT_BasicVector3DT_double_t_std__allocatorT_BasicVector3DT_double_t_t_t swig_types[17]
-#define SWIGTYPE_p_std__vectorT_BasicVector3DT_std__complexT_double_t_t_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t_t swig_types[18]
-#define SWIGTYPE_p_std__vectorT_double_std__allocatorT_double_t_t swig_types[19]
-#define SWIGTYPE_p_std__vectorT_std__complexT_double_t_std__allocatorT_std__complexT_double_t_t_t swig_types[20]
-#define SWIGTYPE_p_swig__SwigPyIterator swig_types[21]
-#define SWIGTYPE_p_unsigned_char swig_types[22]
-#define SWIGTYPE_p_unsigned_int swig_types[23]
-#define SWIGTYPE_p_unsigned_long_long swig_types[24]
-#define SWIGTYPE_p_unsigned_short swig_types[25]
-#define SWIGTYPE_p_value_type swig_types[26]
-static swig_type_info *swig_types[28];
-static swig_module_info swig_module = {swig_types, 27, 0, 0, 0, 0};
+#define SWIGTYPE_p_ThreadInfo swig_types[4]
+#define SWIGTYPE_p_allocator_type swig_types[5]
+#define SWIGTYPE_p_char swig_types[6]
+#define SWIGTYPE_p_difference_type swig_types[7]
+#define SWIGTYPE_p_int swig_types[8]
+#define SWIGTYPE_p_long_long swig_types[9]
+#define SWIGTYPE_p_p_PyObject swig_types[10]
+#define SWIGTYPE_p_short swig_types[11]
+#define SWIGTYPE_p_signed_char swig_types[12]
+#define SWIGTYPE_p_size_type swig_types[13]
+#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_double_t_t swig_types[14]
+#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t swig_types[15]
+#define SWIGTYPE_p_std__complexT_double_t swig_types[16]
+#define SWIGTYPE_p_std__invalid_argument swig_types[17]
+#define SWIGTYPE_p_std__vectorT_BasicVector3DT_double_t_std__allocatorT_BasicVector3DT_double_t_t_t swig_types[18]
+#define SWIGTYPE_p_std__vectorT_BasicVector3DT_std__complexT_double_t_t_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t_t swig_types[19]
+#define SWIGTYPE_p_std__vectorT_double_std__allocatorT_double_t_t swig_types[20]
+#define SWIGTYPE_p_std__vectorT_std__complexT_double_t_std__allocatorT_std__complexT_double_t_t_t swig_types[21]
+#define SWIGTYPE_p_swig__SwigPyIterator swig_types[22]
+#define SWIGTYPE_p_unsigned_char swig_types[23]
+#define SWIGTYPE_p_unsigned_int swig_types[24]
+#define SWIGTYPE_p_unsigned_long_long swig_types[25]
+#define SWIGTYPE_p_unsigned_short swig_types[26]
+#define SWIGTYPE_p_value_type swig_types[27]
+static swig_type_info *swig_types[29];
+static swig_module_info swig_module = {swig_types, 28, 0, 0, 0, 0};
#define SWIG_TypeQuery(name) SWIG_TypeQueryModule(&swig_module, &swig_module, name)
#define SWIG_MangledTypeQuery(name) SWIG_MangledTypeQueryModule(&swig_module, &swig_module, name)
@@ -3774,6 +3775,7 @@ SWIGINTERNINLINE PyObject*
#include "Base/Types/Complex.h"
#include "Base/Types/ICloneable.h"
#include "Base/Const/Units.h"
+#include "Base/Utils/ThreadInfo.h"
#include "Base/Vector/BasicVector3D.h"
#include "Base/Vector/Vectors3D.h"
@@ -3781,6 +3783,7 @@ SWIGINTERNINLINE PyObject*
#include "Base/Utils/MathFunctions.h"
+
SWIGINTERNINLINE PyObject*
SWIG_From_std_complex_Sl_double_Sg_ (/*@SWIG:/usr/local/share/swig/4.0.2/typemaps/swigmacros.swg,104,%ifcplusplus@*/
@@ -3831,6 +3834,29 @@ SWIG_AsVal_int (PyObject * obj, int *val)
}
+SWIGINTERN int
+SWIG_AsVal_unsigned_SS_int (PyObject * obj, unsigned int *val)
+{
+ unsigned long v;
+ int res = SWIG_AsVal_unsigned_SS_long (obj, &v);
+ if (SWIG_IsOK(res)) {
+ if ((v > UINT_MAX)) {
+ return SWIG_OverflowError;
+ } else {
+ if (val) *val = static_cast< unsigned int >(v);
+ }
+ }
+ return res;
+}
+
+
+SWIGINTERNINLINE PyObject*
+ SWIG_From_unsigned_SS_int (unsigned int value)
+{
+ return PyInt_FromSize_t((size_t) value);
+}
+
+
namespace swig {
template <class Type>
struct noconst_traits {
@@ -7344,6 +7370,208 @@ fail:
}
+SWIGINTERN PyObject *_wrap_new_ThreadInfo(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *result = 0 ;
+
+ if (!SWIG_Python_UnpackTuple(args, "new_ThreadInfo", 0, 0, 0)) SWIG_fail;
+ result = (ThreadInfo *)new ThreadInfo();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ThreadInfo, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_n_threads_set(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ unsigned int arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ unsigned int val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ThreadInfo_n_threads_set", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_n_threads_set" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ ecode2 = SWIG_AsVal_unsigned_SS_int(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ThreadInfo_n_threads_set" "', argument " "2"" of type '" "unsigned int""'");
+ }
+ arg2 = static_cast< unsigned int >(val2);
+ if (arg1) (arg1)->n_threads = arg2;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_n_threads_get(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ unsigned int result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_n_threads_get" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ result = (unsigned int) ((arg1)->n_threads);
+ resultobj = SWIG_From_unsigned_SS_int(static_cast< unsigned int >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_n_batches_set(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ unsigned int arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ unsigned int val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ThreadInfo_n_batches_set", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_n_batches_set" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ ecode2 = SWIG_AsVal_unsigned_SS_int(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ThreadInfo_n_batches_set" "', argument " "2"" of type '" "unsigned int""'");
+ }
+ arg2 = static_cast< unsigned int >(val2);
+ if (arg1) (arg1)->n_batches = arg2;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_n_batches_get(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ unsigned int result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_n_batches_get" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ result = (unsigned int) ((arg1)->n_batches);
+ resultobj = SWIG_From_unsigned_SS_int(static_cast< unsigned int >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_current_batch_set(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ unsigned int arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ unsigned int val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ThreadInfo_current_batch_set", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_current_batch_set" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ ecode2 = SWIG_AsVal_unsigned_SS_int(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ThreadInfo_current_batch_set" "', argument " "2"" of type '" "unsigned int""'");
+ }
+ arg2 = static_cast< unsigned int >(val2);
+ if (arg1) (arg1)->current_batch = arg2;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ThreadInfo_current_batch_get(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ unsigned int result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ThreadInfo_current_batch_get" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ result = (unsigned int) ((arg1)->current_batch);
+ resultobj = SWIG_From_unsigned_SS_int(static_cast< unsigned int >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_ThreadInfo(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ThreadInfo *arg1 = (ThreadInfo *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ThreadInfo, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_ThreadInfo" "', argument " "1"" of type '" "ThreadInfo *""'");
+ }
+ arg1 = reinterpret_cast< ThreadInfo * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *ThreadInfo_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_ThreadInfo, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *ThreadInfo_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
SWIGINTERN PyObject *_wrap_vecOfLambdaAlphaPhi(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
PyObject *resultobj = 0;
double arg1 ;
@@ -12459,6 +12687,20 @@ static PyMethodDef SwigMethods[] = {
"double MathFunctions::GeneratePoissonRandom(double average)\n"
"\n"
""},
+ { "new_ThreadInfo", _wrap_new_ThreadInfo, METH_NOARGS, "\n"
+ "new_ThreadInfo() -> ThreadInfo\n"
+ "ThreadInfo::ThreadInfo()\n"
+ "\n"
+ ""},
+ { "ThreadInfo_n_threads_set", _wrap_ThreadInfo_n_threads_set, METH_VARARGS, "ThreadInfo_n_threads_set(ThreadInfo self, unsigned int n_threads)"},
+ { "ThreadInfo_n_threads_get", _wrap_ThreadInfo_n_threads_get, METH_O, "ThreadInfo_n_threads_get(ThreadInfo self) -> unsigned int"},
+ { "ThreadInfo_n_batches_set", _wrap_ThreadInfo_n_batches_set, METH_VARARGS, "ThreadInfo_n_batches_set(ThreadInfo self, unsigned int n_batches)"},
+ { "ThreadInfo_n_batches_get", _wrap_ThreadInfo_n_batches_get, METH_O, "ThreadInfo_n_batches_get(ThreadInfo self) -> unsigned int"},
+ { "ThreadInfo_current_batch_set", _wrap_ThreadInfo_current_batch_set, METH_VARARGS, "ThreadInfo_current_batch_set(ThreadInfo self, unsigned int current_batch)"},
+ { "ThreadInfo_current_batch_get", _wrap_ThreadInfo_current_batch_get, METH_O, "ThreadInfo_current_batch_get(ThreadInfo self) -> unsigned int"},
+ { "delete_ThreadInfo", _wrap_delete_ThreadInfo, METH_O, "delete_ThreadInfo(ThreadInfo self)"},
+ { "ThreadInfo_swigregister", ThreadInfo_swigregister, METH_O, NULL},
+ { "ThreadInfo_swiginit", ThreadInfo_swiginit, METH_VARARGS, NULL},
{ "vecOfLambdaAlphaPhi", _wrap_vecOfLambdaAlphaPhi, METH_VARARGS, "\n"
"vecOfLambdaAlphaPhi(double _lambda, double _alpha, double _phi) -> kvector_t\n"
"BasicVector3D<double> vecOfLambdaAlphaPhi(double _lambda, double _alpha, double _phi)\n"
@@ -12844,6 +13086,7 @@ static swig_type_info _swigt__p_BasicVector3DT_double_t = {"_p_BasicVector3DT_do
static swig_type_info _swigt__p_BasicVector3DT_int_t = {"_p_BasicVector3DT_int_t", "ivector_t *|BasicVector3D< int > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_BasicVector3DT_std__complexT_double_t_t = {"_p_BasicVector3DT_std__complexT_double_t_t", "BasicVector3D< std::complex< double > > *|std::vector< BasicVector3D< std::complex< double > > >::value_type *|cvector_t *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ICloneable = {"_p_ICloneable", "ICloneable *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_ThreadInfo = {"_p_ThreadInfo", "ThreadInfo *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_allocator_type = {"_p_allocator_type", "allocator_type *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_char = {"_p_char", "char *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_difference_type = {"_p_difference_type", "difference_type *", 0, 0, (void*)0, 0};
@@ -12873,6 +13116,7 @@ static swig_type_info *swig_type_initial[] = {
&_swigt__p_BasicVector3DT_int_t,
&_swigt__p_BasicVector3DT_std__complexT_double_t_t,
&_swigt__p_ICloneable,
+ &_swigt__p_ThreadInfo,
&_swigt__p_allocator_type,
&_swigt__p_char,
&_swigt__p_difference_type,
@@ -12902,6 +13146,7 @@ static swig_cast_info _swigc__p_BasicVector3DT_double_t[] = { {&_swigt__p_Basic
static swig_cast_info _swigc__p_BasicVector3DT_int_t[] = { {&_swigt__p_BasicVector3DT_int_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_BasicVector3DT_std__complexT_double_t_t[] = { {&_swigt__p_BasicVector3DT_std__complexT_double_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ICloneable[] = { {&_swigt__p_ICloneable, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_ThreadInfo[] = { {&_swigt__p_ThreadInfo, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_allocator_type[] = { {&_swigt__p_allocator_type, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_char[] = { {&_swigt__p_char, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_difference_type[] = { {&_swigt__p_difference_type, 0, 0, 0},{0, 0, 0, 0}};
@@ -12931,6 +13176,7 @@ static swig_cast_info *swig_cast_initial[] = {
_swigc__p_BasicVector3DT_int_t,
_swigc__p_BasicVector3DT_std__complexT_double_t_t,
_swigc__p_ICloneable,
+ _swigc__p_ThreadInfo,
_swigc__p_allocator_type,
_swigc__p_char,
_swigc__p_difference_type,
diff --git a/auto/Wrap/libBornAgainCore.py b/auto/Wrap/libBornAgainCore.py
index 2f526d6324455d9ac37af5da456fc9efb7636e2f..5cfdd5843da84e2e17017921379177036b6f3c83 100644
--- a/auto/Wrap/libBornAgainCore.py
+++ b/auto/Wrap/libBornAgainCore.py
@@ -3035,206 +3035,6 @@ class SimulationFactoryTemp(object):
# Register SimulationFactoryTemp in _libBornAgainCore:
_libBornAgainCore.SimulationFactoryTemp_swigregister(SimulationFactoryTemp)
-class ParameterSample(object):
- r"""
-
-
- A parameter value with a weight, as obtained when sampling from a distribution.
-
- C++ includes: ParameterSample.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, _value=0., _weight=1.):
- r"""
- __init__(ParameterSample self, double _value=0., double _weight=1.) -> ParameterSample
- ParameterSample::ParameterSample(double _value=0., double _weight=1.)
-
- """
- _libBornAgainCore.ParameterSample_swiginit(self, _libBornAgainCore.new_ParameterSample(_value, _weight))
- value = property(_libBornAgainCore.ParameterSample_value_get, _libBornAgainCore.ParameterSample_value_set, doc=r"""value : double""")
- weight = property(_libBornAgainCore.ParameterSample_weight_get, _libBornAgainCore.ParameterSample_weight_set, doc=r"""weight : double""")
- __swig_destroy__ = _libBornAgainCore.delete_ParameterSample
-
-# Register ParameterSample in _libBornAgainCore:
-_libBornAgainCore.ParameterSample_swigregister(ParameterSample)
-
-class ParameterSampleVector(object):
- r"""Proxy of C++ std::vector< ParameterSample > class."""
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def iterator(self):
- r"""iterator(ParameterSampleVector self) -> SwigPyIterator"""
- return _libBornAgainCore.ParameterSampleVector_iterator(self)
- def __iter__(self):
- return self.iterator()
-
- def __nonzero__(self):
- r"""__nonzero__(ParameterSampleVector self) -> bool"""
- return _libBornAgainCore.ParameterSampleVector___nonzero__(self)
-
- def __bool__(self):
- r"""__bool__(ParameterSampleVector self) -> bool"""
- return _libBornAgainCore.ParameterSampleVector___bool__(self)
-
- def __len__(self):
- r"""__len__(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
- return _libBornAgainCore.ParameterSampleVector___len__(self)
-
- def __getslice__(self, i, j):
- r"""__getslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j) -> ParameterSampleVector"""
- return _libBornAgainCore.ParameterSampleVector___getslice__(self, i, j)
-
- def __setslice__(self, *args):
- r"""
- __setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)
- __setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j, ParameterSampleVector v)
- """
- return _libBornAgainCore.ParameterSampleVector___setslice__(self, *args)
-
- def __delslice__(self, i, j):
- r"""__delslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)"""
- return _libBornAgainCore.ParameterSampleVector___delslice__(self, i, j)
-
- def __delitem__(self, *args):
- r"""
- __delitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i)
- __delitem__(ParameterSampleVector self, PySliceObject * slice)
- """
- return _libBornAgainCore.ParameterSampleVector___delitem__(self, *args)
-
- def __getitem__(self, *args):
- r"""
- __getitem__(ParameterSampleVector self, PySliceObject * slice) -> ParameterSampleVector
- __getitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i) -> ParameterSample
- """
- return _libBornAgainCore.ParameterSampleVector___getitem__(self, *args)
-
- def __setitem__(self, *args):
- r"""
- __setitem__(ParameterSampleVector self, PySliceObject * slice, ParameterSampleVector v)
- __setitem__(ParameterSampleVector self, PySliceObject * slice)
- __setitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, ParameterSample x)
- """
- return _libBornAgainCore.ParameterSampleVector___setitem__(self, *args)
-
- def pop(self):
- r"""pop(ParameterSampleVector self) -> ParameterSample"""
- return _libBornAgainCore.ParameterSampleVector_pop(self)
-
- def append(self, x):
- r"""append(ParameterSampleVector self, ParameterSample x)"""
- return _libBornAgainCore.ParameterSampleVector_append(self, x)
-
- def empty(self):
- r"""empty(ParameterSampleVector self) -> bool"""
- return _libBornAgainCore.ParameterSampleVector_empty(self)
-
- def size(self):
- r"""size(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
- return _libBornAgainCore.ParameterSampleVector_size(self)
-
- def swap(self, v):
- r"""
- swap(ParameterSampleVector self, ParameterSampleVector v)
- void swap(OutputDataIterator< TValue, TContainer > &left, OutputDataIterator< TValue, TContainer > &right)
-
- make Swappable
-
- """
- return _libBornAgainCore.ParameterSampleVector_swap(self, v)
-
- def begin(self):
- r"""begin(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"""
- return _libBornAgainCore.ParameterSampleVector_begin(self)
-
- def end(self):
- r"""end(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"""
- return _libBornAgainCore.ParameterSampleVector_end(self)
-
- def rbegin(self):
- r"""rbegin(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"""
- return _libBornAgainCore.ParameterSampleVector_rbegin(self)
-
- def rend(self):
- r"""rend(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"""
- return _libBornAgainCore.ParameterSampleVector_rend(self)
-
- def clear(self):
- r"""clear(ParameterSampleVector self)"""
- return _libBornAgainCore.ParameterSampleVector_clear(self)
-
- def get_allocator(self):
- r"""get_allocator(ParameterSampleVector self) -> std::vector< ParameterSample >::allocator_type"""
- return _libBornAgainCore.ParameterSampleVector_get_allocator(self)
-
- def pop_back(self):
- r"""pop_back(ParameterSampleVector self)"""
- return _libBornAgainCore.ParameterSampleVector_pop_back(self)
-
- def erase(self, *args):
- r"""
- erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos) -> std::vector< ParameterSample >::iterator
- erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator first, std::vector< ParameterSample >::iterator last) -> std::vector< ParameterSample >::iterator
- """
- return _libBornAgainCore.ParameterSampleVector_erase(self, *args)
-
- def __init__(self, *args):
- r"""
- __init__(ParameterSampleVector self) -> ParameterSampleVector
- __init__(ParameterSampleVector self, ParameterSampleVector other) -> ParameterSampleVector
- __init__(ParameterSampleVector self, std::vector< ParameterSample >::size_type size) -> ParameterSampleVector
- __init__(ParameterSampleVector self, std::vector< ParameterSample >::size_type size, ParameterSample value) -> ParameterSampleVector
- """
- _libBornAgainCore.ParameterSampleVector_swiginit(self, _libBornAgainCore.new_ParameterSampleVector(*args))
-
- def push_back(self, x):
- r"""push_back(ParameterSampleVector self, ParameterSample x)"""
- return _libBornAgainCore.ParameterSampleVector_push_back(self, x)
-
- def front(self):
- r"""front(ParameterSampleVector self) -> ParameterSample"""
- return _libBornAgainCore.ParameterSampleVector_front(self)
-
- def back(self):
- r"""back(ParameterSampleVector self) -> ParameterSample"""
- return _libBornAgainCore.ParameterSampleVector_back(self)
-
- def assign(self, n, x):
- r"""assign(ParameterSampleVector self, std::vector< ParameterSample >::size_type n, ParameterSample x)"""
- return _libBornAgainCore.ParameterSampleVector_assign(self, n, x)
-
- def resize(self, *args):
- r"""
- resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size)
- resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size, ParameterSample x)
- """
- return _libBornAgainCore.ParameterSampleVector_resize(self, *args)
-
- def insert(self, *args):
- r"""
- insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, ParameterSample x) -> std::vector< ParameterSample >::iterator
- insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, std::vector< ParameterSample >::size_type n, ParameterSample x)
- """
- return _libBornAgainCore.ParameterSampleVector_insert(self, *args)
-
- def reserve(self, n):
- r"""reserve(ParameterSampleVector self, std::vector< ParameterSample >::size_type n)"""
- return _libBornAgainCore.ParameterSampleVector_reserve(self, n)
-
- def capacity(self):
- r"""capacity(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
- return _libBornAgainCore.ParameterSampleVector_capacity(self)
- __swig_destroy__ = _libBornAgainCore.delete_ParameterSampleVector
-
-# Register ParameterSampleVector in _libBornAgainCore:
-_libBornAgainCore.ParameterSampleVector_swigregister(ParameterSampleVector)
-
class IntensityData(object):
r"""
@@ -5277,1177 +5077,162 @@ class Rectangle(IShape2D):
# Register Rectangle in _libBornAgainCore:
_libBornAgainCore.Rectangle_swigregister(Rectangle)
-class IDistribution1D(libBornAgainBase.ICloneable, libBornAgainParam.INode):
+class SimulationOptions(object):
r"""
- Interface for one-dimensional distributions.
+ Collect the different options for simulation.
+
+ SimulationOptions
- C++ includes: Distributions.h
+ C++ includes: SimulationOptions.h
"""
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
-
- def __init__(self, *args, **kwargs):
- raise AttributeError("No constructor defined - class is abstract")
__repr__ = _swig_repr
- def clone(self):
- r"""
- clone(IDistribution1D self) -> IDistribution1D
- virtual IDistribution1D* IDistribution1D::clone() const =0
-
- """
- return _libBornAgainCore.IDistribution1D_clone(self)
-
- def probabilityDensity(self, x):
- r"""
- probabilityDensity(IDistribution1D self, double x) -> double
- virtual double IDistribution1D::probabilityDensity(double x) const =0
-
- Returns the distribution-specific probability density for value x.
-
- """
- return _libBornAgainCore.IDistribution1D_probabilityDensity(self, x)
-
- def getMean(self):
- r"""
- getMean(IDistribution1D self) -> double
- virtual double IDistribution1D::getMean() const =0
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.IDistribution1D_getMean(self)
-
- def equidistantSamples(self, *args):
- r"""
- equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits limits=RealLimits()) -> ParameterSampleVector
- std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const
-
- Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
-
- """
- return _libBornAgainCore.IDistribution1D_equidistantSamples(self, *args)
-
- def equidistantSamplesInRange(self, nbr_samples, xmin, xmax):
+ def __init__(self):
r"""
- equidistantSamplesInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> ParameterSampleVector
- std::vector< ParameterSample > IDistribution1D::equidistantSamplesInRange(size_t nbr_samples, double xmin, double xmax) const
-
- Returns equidistant samples from xmin to xmax, weighted with probabilityDensity().
+ __init__(SimulationOptions self) -> SimulationOptions
+ SimulationOptions::SimulationOptions()
"""
- return _libBornAgainCore.IDistribution1D_equidistantSamplesInRange(self, nbr_samples, xmin, xmax)
+ _libBornAgainCore.SimulationOptions_swiginit(self, _libBornAgainCore.new_SimulationOptions())
- def equidistantPoints(self, *args):
+ def isIntegrate(self):
r"""
- equidistantPoints(IDistribution1D self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- virtual std::vector<double> IDistribution1D::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) 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.
+ isIntegrate(SimulationOptions self) -> bool
+ bool SimulationOptions::isIntegrate() const
"""
- return _libBornAgainCore.IDistribution1D_equidistantPoints(self, *args)
+ return _libBornAgainCore.SimulationOptions_isIntegrate(self)
- def equidistantPointsInRange(self, nbr_samples, xmin, xmax):
+ def getMcPoints(self):
r"""
- equidistantPointsInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> vdouble1d_t
- std::vector< double > IDistribution1D::equidistantPointsInRange(size_t nbr_samples, double xmin, double xmax) const
-
- Returns equidistant interpolation points from xmin to xmax.
+ getMcPoints(SimulationOptions self) -> size_t
+ size_t SimulationOptions::getMcPoints() const
"""
- return _libBornAgainCore.IDistribution1D_equidistantPointsInRange(self, nbr_samples, xmin, xmax)
+ return _libBornAgainCore.SimulationOptions_getMcPoints(self)
- def isDelta(self):
+ def setMonteCarloIntegration(self, flag=True, mc_points=50):
r"""
- isDelta(IDistribution1D self) -> bool
- virtual bool IDistribution1D::isDelta() const =0
+ setMonteCarloIntegration(SimulationOptions self, bool flag=True, size_t mc_points=50)
+ void SimulationOptions::setMonteCarloIntegration(bool flag=true, size_t mc_points=50)
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
+ Enables/disables MonetCarlo integration.
- """
- return _libBornAgainCore.IDistribution1D_isDelta(self)
+ Parameters:
+ -----------
- def setUnits(self, units):
- r"""
- setUnits(IDistribution1D self, std::string const & units)
- void IDistribution1D::setUnits(const std::string &units)
+ flag:
+ If true, MonteCarlo integration will be used, otherwise analytical calculations
- Sets distribution units.
+ mc_points:
+ Number of points for MonteCarlo integrator
"""
- return _libBornAgainCore.IDistribution1D_setUnits(self, units)
- __swig_destroy__ = _libBornAgainCore.delete_IDistribution1D
-
-# Register IDistribution1D in _libBornAgainCore:
-_libBornAgainCore.IDistribution1D_swigregister(IDistribution1D)
-
-class DistributionGate(IDistribution1D):
- r"""
-
-
- Uniform distribution function with half width hwhm.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
+ return _libBornAgainCore.SimulationOptions_setMonteCarloIntegration(self, flag, mc_points)
- def __init__(self, *args):
+ def setNumberOfThreads(self, nthreads):
r"""
- __init__(DistributionGate self, vdouble1d_t P) -> DistributionGate
- __init__(DistributionGate self, double min, double max) -> DistributionGate
- __init__(DistributionGate self) -> DistributionGate
- DistributionGate::DistributionGate()
-
- """
- _libBornAgainCore.DistributionGate_swiginit(self, _libBornAgainCore.new_DistributionGate(*args))
+ setNumberOfThreads(SimulationOptions self, int nthreads)
+ void SimulationOptions::setNumberOfThreads(int nthreads)
- def clone(self):
- r"""
- clone(DistributionGate self) -> DistributionGate
- DistributionGate* DistributionGate::clone() const final
+ Sets number of threads to use during the simulation (0 - take the default value from the hardware)
"""
- return _libBornAgainCore.DistributionGate_clone(self)
+ return _libBornAgainCore.SimulationOptions_setNumberOfThreads(self, nthreads)
- def probabilityDensity(self, x):
+ def getNumberOfThreads(self):
r"""
- probabilityDensity(DistributionGate self, double x) -> double
- double DistributionGate::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
+ getNumberOfThreads(SimulationOptions self) -> unsigned int
+ unsigned SimulationOptions::getNumberOfThreads() const
"""
- return _libBornAgainCore.DistributionGate_probabilityDensity(self, x)
+ return _libBornAgainCore.SimulationOptions_getNumberOfThreads(self)
- def getMean(self):
+ def setNumberOfBatches(self, nbatches):
r"""
- getMean(DistributionGate self) -> double
- double DistributionGate::getMean() const final
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.DistributionGate_getMean(self)
+ setNumberOfBatches(SimulationOptions self, int nbatches)
+ void SimulationOptions::setNumberOfBatches(int nbatches)
- def getMin(self):
- r"""
- getMin(DistributionGate self) -> double
- double DistributionGate::getMin() const
+ Sets number of batches to split.
"""
- return _libBornAgainCore.DistributionGate_getMin(self)
+ return _libBornAgainCore.SimulationOptions_setNumberOfBatches(self, nbatches)
- def getMax(self):
+ def getNumberOfBatches(self):
r"""
- getMax(DistributionGate self) -> double
- double DistributionGate::getMax() const
+ getNumberOfBatches(SimulationOptions self) -> unsigned int
+ unsigned SimulationOptions::getNumberOfBatches() const
"""
- return _libBornAgainCore.DistributionGate_getMax(self)
+ return _libBornAgainCore.SimulationOptions_getNumberOfBatches(self)
- def equidistantPoints(self, *args):
+ def getCurrentBatch(self):
r"""
- equidistantPoints(DistributionGate self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionGate::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- Returns list of sample values.
+ getCurrentBatch(SimulationOptions self) -> unsigned int
+ unsigned SimulationOptions::getCurrentBatch() const
"""
- return _libBornAgainCore.DistributionGate_equidistantPoints(self, *args)
+ return _libBornAgainCore.SimulationOptions_getCurrentBatch(self)
- def isDelta(self):
+ def setThreadInfo(self, thread_info):
r"""
- isDelta(DistributionGate self) -> bool
- bool DistributionGate::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionGate_isDelta(self)
+ setThreadInfo(SimulationOptions self, ThreadInfo const & thread_info)
+ void SimulationOptions::setThreadInfo(const ThreadInfo &thread_info)
- def accept(self, visitor):
- r"""
- accept(DistributionGate self, INodeVisitor * visitor)
- void DistributionGate::accept(INodeVisitor *visitor) const final
+ Sets the batch and thread information to be used.
"""
- return _libBornAgainCore.DistributionGate_accept(self, visitor)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionGate
-
-# Register DistributionGate in _libBornAgainCore:
-_libBornAgainCore.DistributionGate_swigregister(DistributionGate)
-
-class DistributionLorentz(IDistribution1D):
- r"""
-
-
- Lorentz distribution with half width hwhm.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
+ return _libBornAgainCore.SimulationOptions_setThreadInfo(self, thread_info)
- def __init__(self, *args):
+ def getHardwareConcurrency(self):
r"""
- __init__(DistributionLorentz self, vdouble1d_t P) -> DistributionLorentz
- __init__(DistributionLorentz self, double mean, double hwhm) -> DistributionLorentz
- __init__(DistributionLorentz self) -> DistributionLorentz
- DistributionLorentz::DistributionLorentz()
+ getHardwareConcurrency(SimulationOptions self) -> unsigned int
+ unsigned SimulationOptions::getHardwareConcurrency() const
"""
- _libBornAgainCore.DistributionLorentz_swiginit(self, _libBornAgainCore.new_DistributionLorentz(*args))
+ return _libBornAgainCore.SimulationOptions_getHardwareConcurrency(self)
- def clone(self):
+ def setIncludeSpecular(self, include_specular):
r"""
- clone(DistributionLorentz self) -> DistributionLorentz
- DistributionLorentz* DistributionLorentz::clone() const final
+ setIncludeSpecular(SimulationOptions self, bool include_specular)
+ void SimulationOptions::setIncludeSpecular(bool include_specular)
"""
- return _libBornAgainCore.DistributionLorentz_clone(self)
+ return _libBornAgainCore.SimulationOptions_setIncludeSpecular(self, include_specular)
- def probabilityDensity(self, x):
+ def includeSpecular(self):
r"""
- probabilityDensity(DistributionLorentz self, double x) -> double
- double DistributionLorentz::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
+ includeSpecular(SimulationOptions self) -> bool
+ bool SimulationOptions::includeSpecular() const
"""
- return _libBornAgainCore.DistributionLorentz_probabilityDensity(self, x)
+ return _libBornAgainCore.SimulationOptions_includeSpecular(self)
- def getMean(self):
+ def setUseAvgMaterials(self, use_avg_materials):
r"""
- getMean(DistributionLorentz self) -> double
- double DistributionLorentz::getMean() const final
-
- Returns the distribution-specific mean.
+ setUseAvgMaterials(SimulationOptions self, bool use_avg_materials)
+ void SimulationOptions::setUseAvgMaterials(bool use_avg_materials)
"""
- return _libBornAgainCore.DistributionLorentz_getMean(self)
+ return _libBornAgainCore.SimulationOptions_setUseAvgMaterials(self, use_avg_materials)
- def getHWHM(self):
+ def useAvgMaterials(self):
r"""
- getHWHM(DistributionLorentz self) -> double
- double DistributionLorentz::getHWHM() const
+ useAvgMaterials(SimulationOptions self) -> bool
+ bool SimulationOptions::useAvgMaterials() const
"""
- return _libBornAgainCore.DistributionLorentz_getHWHM(self)
-
- def equidistantPoints(self, *args):
- r"""
- equidistantPoints(DistributionLorentz self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionLorentz::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- generate list of sample values
-
- """
- return _libBornAgainCore.DistributionLorentz_equidistantPoints(self, *args)
-
- def isDelta(self):
- r"""
- isDelta(DistributionLorentz self) -> bool
- bool DistributionLorentz::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionLorentz_isDelta(self)
-
- def accept(self, visitor):
- r"""
- accept(DistributionLorentz self, INodeVisitor * visitor)
- void DistributionLorentz::accept(INodeVisitor *visitor) const final
-
- """
- return _libBornAgainCore.DistributionLorentz_accept(self, visitor)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionLorentz
-
-# Register DistributionLorentz in _libBornAgainCore:
-_libBornAgainCore.DistributionLorentz_swigregister(DistributionLorentz)
-
-class DistributionGaussian(IDistribution1D):
- r"""
-
-
- Gaussian distribution with standard deviation std_dev.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(DistributionGaussian self, vdouble1d_t P) -> DistributionGaussian
- __init__(DistributionGaussian self, double mean, double std_dev) -> DistributionGaussian
- __init__(DistributionGaussian self) -> DistributionGaussian
- DistributionGaussian::DistributionGaussian()
-
- """
- _libBornAgainCore.DistributionGaussian_swiginit(self, _libBornAgainCore.new_DistributionGaussian(*args))
-
- def clone(self):
- r"""
- clone(DistributionGaussian self) -> DistributionGaussian
- DistributionGaussian* DistributionGaussian::clone() const final
-
- """
- return _libBornAgainCore.DistributionGaussian_clone(self)
-
- def probabilityDensity(self, x):
- r"""
- probabilityDensity(DistributionGaussian self, double x) -> double
- double DistributionGaussian::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
-
- """
- return _libBornAgainCore.DistributionGaussian_probabilityDensity(self, x)
-
- def getMean(self):
- r"""
- getMean(DistributionGaussian self) -> double
- double DistributionGaussian::getMean() const final
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.DistributionGaussian_getMean(self)
-
- def getStdDev(self):
- r"""
- getStdDev(DistributionGaussian self) -> double
- double DistributionGaussian::getStdDev() const
-
- """
- return _libBornAgainCore.DistributionGaussian_getStdDev(self)
-
- def equidistantPoints(self, *args):
- r"""
- equidistantPoints(DistributionGaussian self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionGaussian::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- generate list of sample values
-
- """
- return _libBornAgainCore.DistributionGaussian_equidistantPoints(self, *args)
-
- def isDelta(self):
- r"""
- isDelta(DistributionGaussian self) -> bool
- bool DistributionGaussian::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionGaussian_isDelta(self)
-
- def accept(self, visitor):
- r"""
- accept(DistributionGaussian self, INodeVisitor * visitor)
- void DistributionGaussian::accept(INodeVisitor *visitor) const final
-
- """
- return _libBornAgainCore.DistributionGaussian_accept(self, visitor)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionGaussian
-
-# Register DistributionGaussian in _libBornAgainCore:
-_libBornAgainCore.DistributionGaussian_swigregister(DistributionGaussian)
-
-class DistributionLogNormal(IDistribution1D):
- r"""
-
-
- Log-normal distribution.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(DistributionLogNormal self, vdouble1d_t P) -> DistributionLogNormal
- __init__(DistributionLogNormal self, double median, double scale_param) -> DistributionLogNormal
- DistributionLogNormal::DistributionLogNormal()=delete
-
- """
- _libBornAgainCore.DistributionLogNormal_swiginit(self, _libBornAgainCore.new_DistributionLogNormal(*args))
-
- def clone(self):
- r"""
- clone(DistributionLogNormal self) -> DistributionLogNormal
- DistributionLogNormal* DistributionLogNormal::clone() const final
-
- """
- return _libBornAgainCore.DistributionLogNormal_clone(self)
-
- def probabilityDensity(self, x):
- r"""
- probabilityDensity(DistributionLogNormal self, double x) -> double
- double DistributionLogNormal::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
-
- """
- return _libBornAgainCore.DistributionLogNormal_probabilityDensity(self, x)
-
- def getMean(self):
- r"""
- getMean(DistributionLogNormal self) -> double
- double DistributionLogNormal::getMean() const final
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.DistributionLogNormal_getMean(self)
-
- def getMedian(self):
- r"""
- getMedian(DistributionLogNormal self) -> double
- double DistributionLogNormal::getMedian() const
-
- """
- return _libBornAgainCore.DistributionLogNormal_getMedian(self)
-
- def getScalePar(self):
- r"""
- getScalePar(DistributionLogNormal self) -> double
- double DistributionLogNormal::getScalePar() const
-
- """
- return _libBornAgainCore.DistributionLogNormal_getScalePar(self)
-
- def equidistantPoints(self, *args):
- r"""
- equidistantPoints(DistributionLogNormal self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionLogNormal::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- generate list of sample values
-
- """
- return _libBornAgainCore.DistributionLogNormal_equidistantPoints(self, *args)
-
- def isDelta(self):
- r"""
- isDelta(DistributionLogNormal self) -> bool
- bool DistributionLogNormal::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionLogNormal_isDelta(self)
-
- def accept(self, visitor):
- r"""
- accept(DistributionLogNormal self, INodeVisitor * visitor)
- void DistributionLogNormal::accept(INodeVisitor *visitor) const final
-
- """
- return _libBornAgainCore.DistributionLogNormal_accept(self, visitor)
-
- def setUnits(self, units):
- r"""
- setUnits(DistributionLogNormal self, std::string const & units)
- void DistributionLogNormal::setUnits(const std::string &units)
-
- Sets distribution units.
-
- """
- return _libBornAgainCore.DistributionLogNormal_setUnits(self, units)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionLogNormal
-
-# Register DistributionLogNormal in _libBornAgainCore:
-_libBornAgainCore.DistributionLogNormal_swigregister(DistributionLogNormal)
-
-class DistributionCosine(IDistribution1D):
- r"""
-
-
- Cosine distribution.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(DistributionCosine self, vdouble1d_t P) -> DistributionCosine
- __init__(DistributionCosine self, double mean, double sigma) -> DistributionCosine
- __init__(DistributionCosine self) -> DistributionCosine
- DistributionCosine::DistributionCosine()
-
- """
- _libBornAgainCore.DistributionCosine_swiginit(self, _libBornAgainCore.new_DistributionCosine(*args))
-
- def clone(self):
- r"""
- clone(DistributionCosine self) -> DistributionCosine
- DistributionCosine* DistributionCosine::clone() const final
-
- """
- return _libBornAgainCore.DistributionCosine_clone(self)
-
- def probabilityDensity(self, x):
- r"""
- probabilityDensity(DistributionCosine self, double x) -> double
- double DistributionCosine::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
-
- """
- return _libBornAgainCore.DistributionCosine_probabilityDensity(self, x)
-
- def getMean(self):
- r"""
- getMean(DistributionCosine self) -> double
- double DistributionCosine::getMean() const final
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.DistributionCosine_getMean(self)
-
- def getSigma(self):
- r"""
- getSigma(DistributionCosine self) -> double
- double DistributionCosine::getSigma() const
-
- """
- return _libBornAgainCore.DistributionCosine_getSigma(self)
-
- def equidistantPoints(self, *args):
- r"""
- equidistantPoints(DistributionCosine self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionCosine::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- generate list of sample values
-
- """
- return _libBornAgainCore.DistributionCosine_equidistantPoints(self, *args)
-
- def isDelta(self):
- r"""
- isDelta(DistributionCosine self) -> bool
- bool DistributionCosine::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionCosine_isDelta(self)
-
- def accept(self, visitor):
- r"""
- accept(DistributionCosine self, INodeVisitor * visitor)
- void DistributionCosine::accept(INodeVisitor *visitor) const final
-
- """
- return _libBornAgainCore.DistributionCosine_accept(self, visitor)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionCosine
-
-# Register DistributionCosine in _libBornAgainCore:
-_libBornAgainCore.DistributionCosine_swigregister(DistributionCosine)
-
-class DistributionTrapezoid(IDistribution1D):
- r"""
-
-
- Trapezoidal distribution.
-
- C++ includes: Distributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(DistributionTrapezoid self, vdouble1d_t P) -> DistributionTrapezoid
- __init__(DistributionTrapezoid self, double center, double left, double middle, double right) -> DistributionTrapezoid
- __init__(DistributionTrapezoid self) -> DistributionTrapezoid
- DistributionTrapezoid::DistributionTrapezoid()
-
- """
- _libBornAgainCore.DistributionTrapezoid_swiginit(self, _libBornAgainCore.new_DistributionTrapezoid(*args))
-
- def clone(self):
- r"""
- clone(DistributionTrapezoid self) -> DistributionTrapezoid
- DistributionTrapezoid* DistributionTrapezoid::clone() const final
-
- """
- return _libBornAgainCore.DistributionTrapezoid_clone(self)
-
- def probabilityDensity(self, x):
- r"""
- probabilityDensity(DistributionTrapezoid self, double x) -> double
- double DistributionTrapezoid::probabilityDensity(double x) const final
-
- Returns the distribution-specific probability density for value x.
-
- """
- return _libBornAgainCore.DistributionTrapezoid_probabilityDensity(self, x)
-
- def getMean(self):
- r"""
- getMean(DistributionTrapezoid self) -> double
- double DistributionTrapezoid::getMean() const final
-
- Returns the distribution-specific mean.
-
- """
- return _libBornAgainCore.DistributionTrapezoid_getMean(self)
-
- def getLeftWidth(self):
- r"""
- getLeftWidth(DistributionTrapezoid self) -> double
- double DistributionTrapezoid::getLeftWidth() const
-
- """
- return _libBornAgainCore.DistributionTrapezoid_getLeftWidth(self)
-
- def getMiddleWidth(self):
- r"""
- getMiddleWidth(DistributionTrapezoid self) -> double
- double DistributionTrapezoid::getMiddleWidth() const
-
- """
- return _libBornAgainCore.DistributionTrapezoid_getMiddleWidth(self)
-
- def getRightWidth(self):
- r"""
- getRightWidth(DistributionTrapezoid self) -> double
- double DistributionTrapezoid::getRightWidth() const
-
- """
- return _libBornAgainCore.DistributionTrapezoid_getRightWidth(self)
-
- def equidistantPoints(self, *args):
- r"""
- equidistantPoints(DistributionTrapezoid self, size_t nbr_samples, double sigma_factor, RealLimits limits=RealLimits()) -> vdouble1d_t
- std::vector< double > DistributionTrapezoid::equidistantPoints(size_t nbr_samples, double sigma_factor, const RealLimits &limits=RealLimits()) const
-
- generate list of sample values
-
- """
- return _libBornAgainCore.DistributionTrapezoid_equidistantPoints(self, *args)
-
- def isDelta(self):
- r"""
- isDelta(DistributionTrapezoid self) -> bool
- bool DistributionTrapezoid::isDelta() const final
-
- Returns true if the distribution is in the limit case of a Dirac delta distribution.
-
- """
- return _libBornAgainCore.DistributionTrapezoid_isDelta(self)
-
- def accept(self, visitor):
- r"""
- accept(DistributionTrapezoid self, INodeVisitor * visitor)
- void DistributionTrapezoid::accept(INodeVisitor *visitor) const final
-
- """
- return _libBornAgainCore.DistributionTrapezoid_accept(self, visitor)
- __swig_destroy__ = _libBornAgainCore.delete_DistributionTrapezoid
-
-# Register DistributionTrapezoid in _libBornAgainCore:
-_libBornAgainCore.DistributionTrapezoid_swigregister(DistributionTrapezoid)
-
-class ParameterDistribution(libBornAgainParam.IParameterized):
- r"""
-
-
- A parametric distribution function, for use with any model parameter.
-
- C++ includes: ParameterDistribution.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(ParameterDistribution self, std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double sigma_factor=0.0, RealLimits limits=RealLimits()) -> ParameterDistribution
- __init__(ParameterDistribution self, std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double xmin, double xmax) -> ParameterDistribution
- __init__(ParameterDistribution self, ParameterDistribution other) -> ParameterDistribution
- ParameterDistribution::ParameterDistribution(const ParameterDistribution &other)
-
- """
- _libBornAgainCore.ParameterDistribution_swiginit(self, _libBornAgainCore.new_ParameterDistribution(*args))
- __swig_destroy__ = _libBornAgainCore.delete_ParameterDistribution
-
- def linkParameter(self, par_name):
- r"""
- linkParameter(ParameterDistribution self, std::string par_name) -> ParameterDistribution
- ParameterDistribution & ParameterDistribution::linkParameter(std::string par_name)
-
- """
- return _libBornAgainCore.ParameterDistribution_linkParameter(self, par_name)
-
- def getMainParameterName(self):
- r"""
- getMainParameterName(ParameterDistribution self) -> std::string
- std::string ParameterDistribution::getMainParameterName() const
-
- get the main parameter's name
-
- """
- return _libBornAgainCore.ParameterDistribution_getMainParameterName(self)
-
- def getNbrSamples(self):
- r"""
- getNbrSamples(ParameterDistribution self) -> size_t
- size_t ParameterDistribution::getNbrSamples() const
-
- get number of samples for this distribution
-
- """
- return _libBornAgainCore.ParameterDistribution_getNbrSamples(self)
-
- def getSigmaFactor(self):
- r"""
- getSigmaFactor(ParameterDistribution self) -> double
- double ParameterDistribution::getSigmaFactor() const
-
- get the sigma factor
-
- """
- return _libBornAgainCore.ParameterDistribution_getSigmaFactor(self)
-
- def getDistribution(self, *args):
- r"""
- getDistribution(ParameterDistribution self) -> IDistribution1D
- getDistribution(ParameterDistribution self) -> IDistribution1D
- IDistribution1D * ParameterDistribution::getDistribution()
-
- """
- return _libBornAgainCore.ParameterDistribution_getDistribution(self, *args)
-
- def generateSamples(self):
- r"""
- generateSamples(ParameterDistribution self) -> ParameterSampleVector
- std::vector< ParameterSample > ParameterDistribution::generateSamples() const
-
- generate list of sampled values with their weight
-
- """
- return _libBornAgainCore.ParameterDistribution_generateSamples(self)
-
- def getLinkedParameterNames(self):
- r"""
- getLinkedParameterNames(ParameterDistribution self) -> vector_string_t
- std::vector<std::string> ParameterDistribution::getLinkedParameterNames() const
-
- get list of linked parameter names
-
- """
- return _libBornAgainCore.ParameterDistribution_getLinkedParameterNames(self)
-
- def getLimits(self):
- r"""
- getLimits(ParameterDistribution self) -> RealLimits
- RealLimits ParameterDistribution::getLimits() const
-
- """
- return _libBornAgainCore.ParameterDistribution_getLimits(self)
-
- def getMinValue(self):
- r"""
- getMinValue(ParameterDistribution self) -> double
- double ParameterDistribution::getMinValue() const
-
- """
- return _libBornAgainCore.ParameterDistribution_getMinValue(self)
-
- def getMaxValue(self):
- r"""
- getMaxValue(ParameterDistribution self) -> double
- double ParameterDistribution::getMaxValue() const
-
- """
- return _libBornAgainCore.ParameterDistribution_getMaxValue(self)
-
-# Register ParameterDistribution in _libBornAgainCore:
-_libBornAgainCore.ParameterDistribution_swigregister(ParameterDistribution)
-
-class RangedDistributionGate(object):
- r"""
-
-
- Uniform distribution function.
-
- C++ includes: RangedDistributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(RangedDistributionGate self) -> RangedDistributionGate
- __init__(RangedDistributionGate self, size_t n_samples, double sigma_factor, RealLimits limits=RealLimits::limitless()) -> RangedDistributionGate
- __init__(RangedDistributionGate self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGate
- RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max)
-
- Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-
- """
- _libBornAgainCore.RangedDistributionGate_swiginit(self, _libBornAgainCore.new_RangedDistributionGate(*args))
-
- def clone(self):
- r"""
- clone(RangedDistributionGate self) -> RangedDistributionGate
- RangedDistributionGate * RangedDistributionGate::clone() const override
-
- """
- return _libBornAgainCore.RangedDistributionGate_clone(self)
- __swig_destroy__ = _libBornAgainCore.delete_RangedDistributionGate
-
-# Register RangedDistributionGate in _libBornAgainCore:
-_libBornAgainCore.RangedDistributionGate_swigregister(RangedDistributionGate)
-
-class RangedDistributionLorentz(object):
- r"""
-
-
- Lorentz distribution with median and hwhm.
-
- C++ includes: RangedDistributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(RangedDistributionLorentz self) -> RangedDistributionLorentz
- __init__(RangedDistributionLorentz self, size_t n_samples, double hwhm_factor, RealLimits limits=RealLimits::limitless()) -> RangedDistributionLorentz
- __init__(RangedDistributionLorentz self, size_t n_samples, double hwhm_factor, double min, double max) -> RangedDistributionLorentz
- RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max)
-
- Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, hwhm_factor = 2.0, while the limits are (-inf, +inf).
-
- """
- _libBornAgainCore.RangedDistributionLorentz_swiginit(self, _libBornAgainCore.new_RangedDistributionLorentz(*args))
-
- def clone(self):
- r"""
- clone(RangedDistributionLorentz self) -> RangedDistributionLorentz
- RangedDistributionLorentz * RangedDistributionLorentz::clone() const override
-
- """
- return _libBornAgainCore.RangedDistributionLorentz_clone(self)
- __swig_destroy__ = _libBornAgainCore.delete_RangedDistributionLorentz
-
-# Register RangedDistributionLorentz in _libBornAgainCore:
-_libBornAgainCore.RangedDistributionLorentz_swigregister(RangedDistributionLorentz)
-
-class RangedDistributionGaussian(object):
- r"""
-
-
- Gaussian distribution with standard deviation std_dev.
-
- C++ includes: RangedDistributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(RangedDistributionGaussian self) -> RangedDistributionGaussian
- __init__(RangedDistributionGaussian self, size_t n_samples, double sigma_factor, RealLimits limits=RealLimits::limitless()) -> RangedDistributionGaussian
- __init__(RangedDistributionGaussian self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGaussian
- RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max)
-
- Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-
- """
- _libBornAgainCore.RangedDistributionGaussian_swiginit(self, _libBornAgainCore.new_RangedDistributionGaussian(*args))
-
- def clone(self):
- r"""
- clone(RangedDistributionGaussian self) -> RangedDistributionGaussian
- RangedDistributionGaussian * RangedDistributionGaussian::clone() const override
-
- """
- return _libBornAgainCore.RangedDistributionGaussian_clone(self)
- __swig_destroy__ = _libBornAgainCore.delete_RangedDistributionGaussian
-
-# Register RangedDistributionGaussian in _libBornAgainCore:
-_libBornAgainCore.RangedDistributionGaussian_swigregister(RangedDistributionGaussian)
-
-class RangedDistributionLogNormal(object):
- r"""
-
-
- Log-normal distribution.
-
- C++ includes: RangedDistributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(RangedDistributionLogNormal self) -> RangedDistributionLogNormal
- __init__(RangedDistributionLogNormal self, size_t n_samples, double sigma_factor, RealLimits limits=RealLimits::limitless()) -> RangedDistributionLogNormal
- __init__(RangedDistributionLogNormal self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionLogNormal
- RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max)
-
- Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-
- """
- _libBornAgainCore.RangedDistributionLogNormal_swiginit(self, _libBornAgainCore.new_RangedDistributionLogNormal(*args))
-
- def clone(self):
- r"""
- clone(RangedDistributionLogNormal self) -> RangedDistributionLogNormal
- RangedDistributionLogNormal * RangedDistributionLogNormal::clone() const override
-
- """
- return _libBornAgainCore.RangedDistributionLogNormal_clone(self)
- __swig_destroy__ = _libBornAgainCore.delete_RangedDistributionLogNormal
-
-# Register RangedDistributionLogNormal in _libBornAgainCore:
-_libBornAgainCore.RangedDistributionLogNormal_swigregister(RangedDistributionLogNormal)
-
-class RangedDistributionCosine(object):
- r"""
-
-
- Cosine distribution.
-
- C++ includes: RangedDistributions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self, *args):
- r"""
- __init__(RangedDistributionCosine self) -> RangedDistributionCosine
- __init__(RangedDistributionCosine self, size_t n_samples, double sigma_factor, RealLimits limits=RealLimits::limitless()) -> RangedDistributionCosine
- __init__(RangedDistributionCosine self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionCosine
- RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max)
-
- Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
-
- """
- _libBornAgainCore.RangedDistributionCosine_swiginit(self, _libBornAgainCore.new_RangedDistributionCosine(*args))
-
- def clone(self):
- r"""
- clone(RangedDistributionCosine self) -> RangedDistributionCosine
- RangedDistributionCosine * RangedDistributionCosine::clone() const override
-
- """
- return _libBornAgainCore.RangedDistributionCosine_clone(self)
- __swig_destroy__ = _libBornAgainCore.delete_RangedDistributionCosine
-
-# Register RangedDistributionCosine in _libBornAgainCore:
-_libBornAgainCore.RangedDistributionCosine_swigregister(RangedDistributionCosine)
-
-class SimulationOptions(object):
- r"""
-
-
- Collect the different options for simulation.
-
- SimulationOptions
-
- C++ includes: SimulationOptions.h
-
- """
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self):
- r"""
- __init__(SimulationOptions self) -> SimulationOptions
- SimulationOptions::SimulationOptions()
-
- """
- _libBornAgainCore.SimulationOptions_swiginit(self, _libBornAgainCore.new_SimulationOptions())
-
- def isIntegrate(self):
- r"""
- isIntegrate(SimulationOptions self) -> bool
- bool SimulationOptions::isIntegrate() const
-
- """
- return _libBornAgainCore.SimulationOptions_isIntegrate(self)
-
- def getMcPoints(self):
- r"""
- getMcPoints(SimulationOptions self) -> size_t
- size_t SimulationOptions::getMcPoints() const
-
- """
- return _libBornAgainCore.SimulationOptions_getMcPoints(self)
-
- def setMonteCarloIntegration(self, flag=True, mc_points=50):
- r"""
- setMonteCarloIntegration(SimulationOptions self, bool flag=True, size_t mc_points=50)
- void SimulationOptions::setMonteCarloIntegration(bool flag=true, size_t mc_points=50)
-
- Enables/disables MonetCarlo integration.
-
- Parameters:
- -----------
-
- flag:
- If true, MonteCarlo integration will be used, otherwise analytical calculations
-
- mc_points:
- Number of points for MonteCarlo integrator
-
- """
- return _libBornAgainCore.SimulationOptions_setMonteCarloIntegration(self, flag, mc_points)
-
- def setNumberOfThreads(self, nthreads):
- r"""
- setNumberOfThreads(SimulationOptions self, int nthreads)
- void SimulationOptions::setNumberOfThreads(int nthreads)
-
- Sets number of threads to use during the simulation (0 - take the default value from the hardware)
-
- """
- return _libBornAgainCore.SimulationOptions_setNumberOfThreads(self, nthreads)
-
- def getNumberOfThreads(self):
- r"""
- getNumberOfThreads(SimulationOptions self) -> unsigned int
- unsigned SimulationOptions::getNumberOfThreads() const
-
- """
- return _libBornAgainCore.SimulationOptions_getNumberOfThreads(self)
-
- def setNumberOfBatches(self, nbatches):
- r"""
- setNumberOfBatches(SimulationOptions self, int nbatches)
- void SimulationOptions::setNumberOfBatches(int nbatches)
-
- Sets number of batches to split.
-
- """
- return _libBornAgainCore.SimulationOptions_setNumberOfBatches(self, nbatches)
-
- def getNumberOfBatches(self):
- r"""
- getNumberOfBatches(SimulationOptions self) -> unsigned int
- unsigned SimulationOptions::getNumberOfBatches() const
-
- """
- return _libBornAgainCore.SimulationOptions_getNumberOfBatches(self)
-
- def getCurrentBatch(self):
- r"""
- getCurrentBatch(SimulationOptions self) -> unsigned int
- unsigned SimulationOptions::getCurrentBatch() const
-
- """
- return _libBornAgainCore.SimulationOptions_getCurrentBatch(self)
-
- def setThreadInfo(self, thread_info):
- r"""
- setThreadInfo(SimulationOptions self, ThreadInfo thread_info)
- void SimulationOptions::setThreadInfo(const ThreadInfo &thread_info)
-
- Sets the batch and thread information to be used.
-
- """
- return _libBornAgainCore.SimulationOptions_setThreadInfo(self, thread_info)
-
- def getHardwareConcurrency(self):
- r"""
- getHardwareConcurrency(SimulationOptions self) -> unsigned int
- unsigned SimulationOptions::getHardwareConcurrency() const
-
- """
- return _libBornAgainCore.SimulationOptions_getHardwareConcurrency(self)
-
- def setIncludeSpecular(self, include_specular):
- r"""
- setIncludeSpecular(SimulationOptions self, bool include_specular)
- void SimulationOptions::setIncludeSpecular(bool include_specular)
-
- """
- return _libBornAgainCore.SimulationOptions_setIncludeSpecular(self, include_specular)
-
- def includeSpecular(self):
- r"""
- includeSpecular(SimulationOptions self) -> bool
- bool SimulationOptions::includeSpecular() const
-
- """
- return _libBornAgainCore.SimulationOptions_includeSpecular(self)
-
- def setUseAvgMaterials(self, use_avg_materials):
- r"""
- setUseAvgMaterials(SimulationOptions self, bool use_avg_materials)
- void SimulationOptions::setUseAvgMaterials(bool use_avg_materials)
-
- """
- return _libBornAgainCore.SimulationOptions_setUseAvgMaterials(self, use_avg_materials)
-
- def useAvgMaterials(self):
- r"""
- useAvgMaterials(SimulationOptions self) -> bool
- bool SimulationOptions::useAvgMaterials() const
-
- """
- return _libBornAgainCore.SimulationOptions_useAvgMaterials(self)
- __swig_destroy__ = _libBornAgainCore.delete_SimulationOptions
+ return _libBornAgainCore.SimulationOptions_useAvgMaterials(self)
+ __swig_destroy__ = _libBornAgainCore.delete_SimulationOptions
# Register SimulationOptions in _libBornAgainCore:
_libBornAgainCore.SimulationOptions_swigregister(SimulationOptions)
-class ThreadInfo(object):
- r"""Proxy of C++ ThreadInfo class."""
-
- thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
- __repr__ = _swig_repr
-
- def __init__(self):
- r"""__init__(ThreadInfo self) -> ThreadInfo"""
- _libBornAgainCore.ThreadInfo_swiginit(self, _libBornAgainCore.new_ThreadInfo())
- n_threads = property(_libBornAgainCore.ThreadInfo_n_threads_get, _libBornAgainCore.ThreadInfo_n_threads_set, doc=r"""n_threads : unsigned int""")
- n_batches = property(_libBornAgainCore.ThreadInfo_n_batches_get, _libBornAgainCore.ThreadInfo_n_batches_set, doc=r"""n_batches : unsigned int""")
- current_batch = property(_libBornAgainCore.ThreadInfo_current_batch_get, _libBornAgainCore.ThreadInfo_current_batch_set, doc=r"""current_batch : unsigned int""")
- __swig_destroy__ = _libBornAgainCore.delete_ThreadInfo
-
-# Register ThreadInfo in _libBornAgainCore:
-_libBornAgainCore.ThreadInfo_swigregister(ThreadInfo)
-
class ISample(libBornAgainBase.ICloneable, libBornAgainParam.INode):
r"""
@@ -15563,7 +14348,7 @@ class Simulation(libBornAgainBase.ICloneable, libBornAgainParam.INode):
def addParameterDistribution(self, *args):
r"""
- addParameterDistribution(Simulation self, std::string const & param_name, IDistribution1D distribution, size_t nbr_samples, double sigma_factor=0.0, RealLimits limits=RealLimits())
+ addParameterDistribution(Simulation self, std::string const & param_name, IDistribution1D const & distribution, size_t nbr_samples, double sigma_factor=0.0, RealLimits limits=RealLimits())
addParameterDistribution(Simulation self, ParameterDistribution par_distr)
void Simulation::addParameterDistribution(const ParameterDistribution &par_distr)
@@ -18585,7 +17370,7 @@ class AngularSpecScan(object):
setRelativeWavelengthResolution(AngularSpecScan self, RangedDistribution const & distr, vdouble1d_t rel_dev)
void AngularSpecScan::setRelativeWavelengthResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
- Sets wavelength resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+ Sets wavelength resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
"""
return _libBornAgainCore.AngularSpecScan_setRelativeWavelengthResolution(self, *args)
@@ -18596,7 +17381,7 @@ class AngularSpecScan(object):
setAbsoluteWavelengthResolution(AngularSpecScan self, RangedDistribution const & distr, vdouble1d_t std_dev)
void AngularSpecScan::setAbsoluteWavelengthResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
- Sets wavelength resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+ Sets wavelength resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
"""
return _libBornAgainCore.AngularSpecScan_setAbsoluteWavelengthResolution(self, *args)
@@ -18617,7 +17402,7 @@ class AngularSpecScan(object):
setRelativeAngularResolution(AngularSpecScan self, RangedDistribution const & distr, vdouble1d_t rel_dev)
void AngularSpecScan::setRelativeAngularResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
- Sets angular resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+ Sets angular resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
"""
return _libBornAgainCore.AngularSpecScan_setRelativeAngularResolution(self, *args)
@@ -18628,7 +17413,7 @@ class AngularSpecScan(object):
setAbsoluteAngularResolution(AngularSpecScan self, RangedDistribution const & distr, vdouble1d_t std_dev)
void AngularSpecScan::setAbsoluteAngularResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
- Sets angular resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
+ Sets angular resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the inclination angle axis.
"""
return _libBornAgainCore.AngularSpecScan_setAbsoluteAngularResolution(self, *args)
@@ -18946,7 +17731,7 @@ class QSpecScan(object):
setRelativeQResolution(QSpecScan self, RangedDistribution const & distr, vdouble1d_t rel_dev)
void QSpecScan::setRelativeQResolution(const RangedDistribution &distr, const std::vector< double > &rel_dev)
- Sets qz resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
+ Sets qz resolution values via RangedDistribution and values of relative deviations (that is, rel_dev equals standard deviation divided by the mean value). rel_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
"""
return _libBornAgainCore.QSpecScan_setRelativeQResolution(self, *args)
@@ -18957,7 +17742,7 @@ class QSpecScan(object):
setAbsoluteQResolution(QSpecScan self, RangedDistribution const & distr, vdouble1d_t std_dev)
void QSpecScan::setAbsoluteQResolution(const RangedDistribution &distr, const std::vector< double > &std_dev)
- Sets qz resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
+ Sets qz resolution values via RangedDistribution and values of standard deviations. std_dev can be either single-valued or a numpy array. In the latter case the length of the array should coinside with the length of the qz-axis.
"""
return _libBornAgainCore.QSpecScan_setAbsoluteQResolution(self, *args)
diff --git a/auto/Wrap/libBornAgainParam.py b/auto/Wrap/libBornAgainParam.py
index dcb46ffd9c54cb0b1666f3d837d59119abe00f9f..8db6b9400fbc59f5fad98eba85ba6a7698d75e69 100644
--- a/auto/Wrap/libBornAgainParam.py
+++ b/auto/Wrap/libBornAgainParam.py
@@ -3300,12 +3300,12 @@ class INodeVisitor(object):
visit(INodeVisitor self, ConstantBackground const * arg2)
visit(INodeVisitor self, ConvolutionDetectorResolution const * arg2)
visit(INodeVisitor self, Crystal const * arg2)
- visit(INodeVisitor self, DistributionCosine const * arg2)
- visit(INodeVisitor self, DistributionGate const * arg2)
- visit(INodeVisitor self, DistributionGaussian const * arg2)
- visit(INodeVisitor self, DistributionLogNormal const * arg2)
- visit(INodeVisitor self, DistributionLorentz const * arg2)
- visit(INodeVisitor self, DistributionTrapezoid const * arg2)
+ visit(INodeVisitor self, DistributionCosine arg2)
+ visit(INodeVisitor self, DistributionGate arg2)
+ visit(INodeVisitor self, DistributionGaussian arg2)
+ visit(INodeVisitor self, DistributionLogNormal arg2)
+ visit(INodeVisitor self, DistributionLorentz arg2)
+ visit(INodeVisitor self, DistributionTrapezoid arg2)
visit(INodeVisitor self, FootprintGauss const * arg2)
visit(INodeVisitor self, FootprintSquare const * arg2)
visit(INodeVisitor self, FormFactorAnisoPyramid const * arg2)
@@ -3463,6 +3463,1210 @@ def VisitNodesPostorder(node, visitor):
"""
return _libBornAgainParam.VisitNodesPostorder(node, visitor)
+class IDistribution1D(libBornAgainBase.ICloneable, INode):
+ r"""
+
+
+ Interface for one-dimensional distributions.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+
+ def __init__(self, *args, **kwargs):
+ raise AttributeError("No constructor defined - class is abstract")
+ __repr__ = _swig_repr
+
+ def clone(self):
+ r"""
+ clone(IDistribution1D self) -> IDistribution1D
+ virtual IDistribution1D* IDistribution1D::clone() const =0
+
+ """
+ return _libBornAgainParam.IDistribution1D_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(IDistribution1D self, double x) -> double
+ virtual double IDistribution1D::probabilityDensity(double x) const =0
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.IDistribution1D_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(IDistribution1D self) -> double
+ virtual double IDistribution1D::getMean() const =0
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.IDistribution1D_getMean(self)
+
+ def equidistantSamples(self, *args):
+ r"""
+ equidistantSamples(IDistribution1D self, size_t nbr_samples, double sigma_factor=0., RealLimits const & limits=RealLimits()) -> ParameterSampleVector
+ std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const
+
+ Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity().
+
+ """
+ return _libBornAgainParam.IDistribution1D_equidistantSamples(self, *args)
+
+ def equidistantSamplesInRange(self, nbr_samples, xmin, xmax):
+ r"""
+ equidistantSamplesInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> ParameterSampleVector
+ std::vector< ParameterSample > IDistribution1D::equidistantSamplesInRange(size_t nbr_samples, double xmin, double xmax) const
+
+ Returns equidistant samples from xmin to xmax, weighted with probabilityDensity().
+
+ """
+ return _libBornAgainParam.IDistribution1D_equidistantSamplesInRange(self, nbr_samples, xmin, xmax)
+
+ 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
+
+ Returns equidistant interpolation points, with range computed in distribution-specific way from mean and width parameter, taking into account limits and sigma_factor.
+
+ """
+ return _libBornAgainParam.IDistribution1D_equidistantPoints(self, *args)
+
+ def equidistantPointsInRange(self, nbr_samples, xmin, xmax):
+ r"""
+ equidistantPointsInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> vdouble1d_t
+ std::vector< double > IDistribution1D::equidistantPointsInRange(size_t nbr_samples, double xmin, double xmax) const
+
+ Returns equidistant interpolation points from xmin to xmax.
+
+ """
+ return _libBornAgainParam.IDistribution1D_equidistantPointsInRange(self, nbr_samples, xmin, xmax)
+
+ def isDelta(self):
+ r"""
+ isDelta(IDistribution1D self) -> bool
+ virtual bool IDistribution1D::isDelta() const =0
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.IDistribution1D_isDelta(self)
+
+ def setUnits(self, units):
+ r"""
+ setUnits(IDistribution1D self, std::string const & units)
+ void IDistribution1D::setUnits(const std::string &units)
+
+ Sets distribution units.
+
+ """
+ return _libBornAgainParam.IDistribution1D_setUnits(self, units)
+ __swig_destroy__ = _libBornAgainParam.delete_IDistribution1D
+
+# Register IDistribution1D in _libBornAgainParam:
+_libBornAgainParam.IDistribution1D_swigregister(IDistribution1D)
+
+class DistributionGate(IDistribution1D):
+ r"""
+
+
+ Uniform distribution function with half width hwhm.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionGate self, vdouble1d_t P) -> DistributionGate
+ __init__(DistributionGate self, double min, double max) -> DistributionGate
+ __init__(DistributionGate self) -> DistributionGate
+ DistributionGate::DistributionGate()
+
+ """
+ _libBornAgainParam.DistributionGate_swiginit(self, _libBornAgainParam.new_DistributionGate(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionGate self) -> DistributionGate
+ DistributionGate* DistributionGate::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionGate_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionGate self, double x) -> double
+ double DistributionGate::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionGate_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionGate self) -> double
+ double DistributionGate::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionGate_getMean(self)
+
+ def getMin(self):
+ r"""
+ getMin(DistributionGate self) -> double
+ double DistributionGate::getMin() const
+
+ """
+ return _libBornAgainParam.DistributionGate_getMin(self)
+
+ def getMax(self):
+ r"""
+ getMax(DistributionGate self) -> double
+ double DistributionGate::getMax() const
+
+ """
+ return _libBornAgainParam.DistributionGate_getMax(self)
+
+ 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
+
+ Returns list of sample values.
+
+ """
+ return _libBornAgainParam.DistributionGate_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionGate self) -> bool
+ bool DistributionGate::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionGate_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionGate self, INodeVisitor visitor)
+ void DistributionGate::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionGate_accept(self, visitor)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionGate
+
+# Register DistributionGate in _libBornAgainParam:
+_libBornAgainParam.DistributionGate_swigregister(DistributionGate)
+
+class DistributionLorentz(IDistribution1D):
+ r"""
+
+
+ Lorentz distribution with half width hwhm.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionLorentz self, vdouble1d_t P) -> DistributionLorentz
+ __init__(DistributionLorentz self, double mean, double hwhm) -> DistributionLorentz
+ __init__(DistributionLorentz self) -> DistributionLorentz
+ DistributionLorentz::DistributionLorentz()
+
+ """
+ _libBornAgainParam.DistributionLorentz_swiginit(self, _libBornAgainParam.new_DistributionLorentz(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionLorentz self) -> DistributionLorentz
+ DistributionLorentz* DistributionLorentz::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionLorentz_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionLorentz self, double x) -> double
+ double DistributionLorentz::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionLorentz_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionLorentz self) -> double
+ double DistributionLorentz::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionLorentz_getMean(self)
+
+ def getHWHM(self):
+ r"""
+ getHWHM(DistributionLorentz self) -> double
+ double DistributionLorentz::getHWHM() const
+
+ """
+ return _libBornAgainParam.DistributionLorentz_getHWHM(self)
+
+ 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
+
+ generate list of sample values
+
+ """
+ return _libBornAgainParam.DistributionLorentz_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionLorentz self) -> bool
+ bool DistributionLorentz::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionLorentz_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionLorentz self, INodeVisitor visitor)
+ void DistributionLorentz::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionLorentz_accept(self, visitor)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionLorentz
+
+# Register DistributionLorentz in _libBornAgainParam:
+_libBornAgainParam.DistributionLorentz_swigregister(DistributionLorentz)
+
+class DistributionGaussian(IDistribution1D):
+ r"""
+
+
+ Gaussian distribution with standard deviation std_dev.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionGaussian self, vdouble1d_t P) -> DistributionGaussian
+ __init__(DistributionGaussian self, double mean, double std_dev) -> DistributionGaussian
+ __init__(DistributionGaussian self) -> DistributionGaussian
+ DistributionGaussian::DistributionGaussian()
+
+ """
+ _libBornAgainParam.DistributionGaussian_swiginit(self, _libBornAgainParam.new_DistributionGaussian(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionGaussian self) -> DistributionGaussian
+ DistributionGaussian* DistributionGaussian::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionGaussian_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionGaussian self, double x) -> double
+ double DistributionGaussian::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionGaussian_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionGaussian self) -> double
+ double DistributionGaussian::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionGaussian_getMean(self)
+
+ def getStdDev(self):
+ r"""
+ getStdDev(DistributionGaussian self) -> double
+ double DistributionGaussian::getStdDev() const
+
+ """
+ return _libBornAgainParam.DistributionGaussian_getStdDev(self)
+
+ 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
+
+ generate list of sample values
+
+ """
+ return _libBornAgainParam.DistributionGaussian_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionGaussian self) -> bool
+ bool DistributionGaussian::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionGaussian_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionGaussian self, INodeVisitor visitor)
+ void DistributionGaussian::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionGaussian_accept(self, visitor)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionGaussian
+
+# Register DistributionGaussian in _libBornAgainParam:
+_libBornAgainParam.DistributionGaussian_swigregister(DistributionGaussian)
+
+class DistributionLogNormal(IDistribution1D):
+ r"""
+
+
+ Log-normal distribution.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionLogNormal self, vdouble1d_t P) -> DistributionLogNormal
+ __init__(DistributionLogNormal self, double median, double scale_param) -> DistributionLogNormal
+ DistributionLogNormal::DistributionLogNormal()=delete
+
+ """
+ _libBornAgainParam.DistributionLogNormal_swiginit(self, _libBornAgainParam.new_DistributionLogNormal(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionLogNormal self) -> DistributionLogNormal
+ DistributionLogNormal* DistributionLogNormal::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionLogNormal self, double x) -> double
+ double DistributionLogNormal::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionLogNormal self) -> double
+ double DistributionLogNormal::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_getMean(self)
+
+ def getMedian(self):
+ r"""
+ getMedian(DistributionLogNormal self) -> double
+ double DistributionLogNormal::getMedian() const
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_getMedian(self)
+
+ def getScalePar(self):
+ r"""
+ getScalePar(DistributionLogNormal self) -> double
+ double DistributionLogNormal::getScalePar() const
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_getScalePar(self)
+
+ 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
+
+ generate list of sample values
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionLogNormal self) -> bool
+ bool DistributionLogNormal::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionLogNormal self, INodeVisitor visitor)
+ void DistributionLogNormal::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_accept(self, visitor)
+
+ def setUnits(self, units):
+ r"""
+ setUnits(DistributionLogNormal self, std::string const & units)
+ void DistributionLogNormal::setUnits(const std::string &units)
+
+ Sets distribution units.
+
+ """
+ return _libBornAgainParam.DistributionLogNormal_setUnits(self, units)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionLogNormal
+
+# Register DistributionLogNormal in _libBornAgainParam:
+_libBornAgainParam.DistributionLogNormal_swigregister(DistributionLogNormal)
+
+class DistributionCosine(IDistribution1D):
+ r"""
+
+
+ Cosine distribution.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionCosine self, vdouble1d_t P) -> DistributionCosine
+ __init__(DistributionCosine self, double mean, double sigma) -> DistributionCosine
+ __init__(DistributionCosine self) -> DistributionCosine
+ DistributionCosine::DistributionCosine()
+
+ """
+ _libBornAgainParam.DistributionCosine_swiginit(self, _libBornAgainParam.new_DistributionCosine(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionCosine self) -> DistributionCosine
+ DistributionCosine* DistributionCosine::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionCosine_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionCosine self, double x) -> double
+ double DistributionCosine::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionCosine_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionCosine self) -> double
+ double DistributionCosine::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionCosine_getMean(self)
+
+ def getSigma(self):
+ r"""
+ getSigma(DistributionCosine self) -> double
+ double DistributionCosine::getSigma() const
+
+ """
+ return _libBornAgainParam.DistributionCosine_getSigma(self)
+
+ 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
+
+ generate list of sample values
+
+ """
+ return _libBornAgainParam.DistributionCosine_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionCosine self) -> bool
+ bool DistributionCosine::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionCosine_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionCosine self, INodeVisitor visitor)
+ void DistributionCosine::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionCosine_accept(self, visitor)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionCosine
+
+# Register DistributionCosine in _libBornAgainParam:
+_libBornAgainParam.DistributionCosine_swigregister(DistributionCosine)
+
+class DistributionTrapezoid(IDistribution1D):
+ r"""
+
+
+ Trapezoidal distribution.
+
+ C++ includes: Distributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(DistributionTrapezoid self, vdouble1d_t P) -> DistributionTrapezoid
+ __init__(DistributionTrapezoid self, double center, double left, double middle, double right) -> DistributionTrapezoid
+ __init__(DistributionTrapezoid self) -> DistributionTrapezoid
+ DistributionTrapezoid::DistributionTrapezoid()
+
+ """
+ _libBornAgainParam.DistributionTrapezoid_swiginit(self, _libBornAgainParam.new_DistributionTrapezoid(*args))
+
+ def clone(self):
+ r"""
+ clone(DistributionTrapezoid self) -> DistributionTrapezoid
+ DistributionTrapezoid* DistributionTrapezoid::clone() const final
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_clone(self)
+
+ def probabilityDensity(self, x):
+ r"""
+ probabilityDensity(DistributionTrapezoid self, double x) -> double
+ double DistributionTrapezoid::probabilityDensity(double x) const final
+
+ Returns the distribution-specific probability density for value x.
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_probabilityDensity(self, x)
+
+ def getMean(self):
+ r"""
+ getMean(DistributionTrapezoid self) -> double
+ double DistributionTrapezoid::getMean() const final
+
+ Returns the distribution-specific mean.
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_getMean(self)
+
+ def getLeftWidth(self):
+ r"""
+ getLeftWidth(DistributionTrapezoid self) -> double
+ double DistributionTrapezoid::getLeftWidth() const
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_getLeftWidth(self)
+
+ def getMiddleWidth(self):
+ r"""
+ getMiddleWidth(DistributionTrapezoid self) -> double
+ double DistributionTrapezoid::getMiddleWidth() const
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_getMiddleWidth(self)
+
+ def getRightWidth(self):
+ r"""
+ getRightWidth(DistributionTrapezoid self) -> double
+ double DistributionTrapezoid::getRightWidth() const
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_getRightWidth(self)
+
+ 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
+
+ generate list of sample values
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_equidistantPoints(self, *args)
+
+ def isDelta(self):
+ r"""
+ isDelta(DistributionTrapezoid self) -> bool
+ bool DistributionTrapezoid::isDelta() const final
+
+ Returns true if the distribution is in the limit case of a Dirac delta distribution.
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_isDelta(self)
+
+ def accept(self, visitor):
+ r"""
+ accept(DistributionTrapezoid self, INodeVisitor visitor)
+ void DistributionTrapezoid::accept(INodeVisitor *visitor) const final
+
+ Calls the INodeVisitor's visit method.
+
+ """
+ return _libBornAgainParam.DistributionTrapezoid_accept(self, visitor)
+ __swig_destroy__ = _libBornAgainParam.delete_DistributionTrapezoid
+
+# Register DistributionTrapezoid in _libBornAgainParam:
+_libBornAgainParam.DistributionTrapezoid_swigregister(DistributionTrapezoid)
+
+class ParameterDistribution(IParameterized):
+ r"""
+
+
+ A parametric distribution function, for use with any model parameter.
+
+ C++ includes: ParameterDistribution.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(ParameterDistribution self, std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double sigma_factor=0.0, RealLimits const & limits=RealLimits()) -> ParameterDistribution
+ __init__(ParameterDistribution self, std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double xmin, double xmax) -> ParameterDistribution
+ __init__(ParameterDistribution self, ParameterDistribution other) -> ParameterDistribution
+ ParameterDistribution::ParameterDistribution(const ParameterDistribution &other)
+
+ """
+ _libBornAgainParam.ParameterDistribution_swiginit(self, _libBornAgainParam.new_ParameterDistribution(*args))
+ __swig_destroy__ = _libBornAgainParam.delete_ParameterDistribution
+
+ def linkParameter(self, par_name):
+ r"""
+ linkParameter(ParameterDistribution self, std::string par_name) -> ParameterDistribution
+ ParameterDistribution & ParameterDistribution::linkParameter(std::string par_name)
+
+ """
+ return _libBornAgainParam.ParameterDistribution_linkParameter(self, par_name)
+
+ def getMainParameterName(self):
+ r"""
+ getMainParameterName(ParameterDistribution self) -> std::string
+ std::string ParameterDistribution::getMainParameterName() const
+
+ get the main parameter's name
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getMainParameterName(self)
+
+ def getNbrSamples(self):
+ r"""
+ getNbrSamples(ParameterDistribution self) -> size_t
+ size_t ParameterDistribution::getNbrSamples() const
+
+ get number of samples for this distribution
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getNbrSamples(self)
+
+ def getSigmaFactor(self):
+ r"""
+ getSigmaFactor(ParameterDistribution self) -> double
+ double ParameterDistribution::getSigmaFactor() const
+
+ get the sigma factor
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getSigmaFactor(self)
+
+ def getDistribution(self, *args):
+ r"""
+ getDistribution(ParameterDistribution self) -> IDistribution1D
+ getDistribution(ParameterDistribution self) -> IDistribution1D
+ IDistribution1D * ParameterDistribution::getDistribution()
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getDistribution(self, *args)
+
+ def generateSamples(self):
+ r"""
+ generateSamples(ParameterDistribution self) -> ParameterSampleVector
+ std::vector< ParameterSample > ParameterDistribution::generateSamples() const
+
+ generate list of sampled values with their weight
+
+ """
+ return _libBornAgainParam.ParameterDistribution_generateSamples(self)
+
+ def getLinkedParameterNames(self):
+ r"""
+ getLinkedParameterNames(ParameterDistribution self) -> vector_string_t
+ std::vector<std::string> ParameterDistribution::getLinkedParameterNames() const
+
+ get list of linked parameter names
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getLinkedParameterNames(self)
+
+ def getLimits(self):
+ r"""
+ getLimits(ParameterDistribution self) -> RealLimits
+ RealLimits ParameterDistribution::getLimits() const
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getLimits(self)
+
+ def getMinValue(self):
+ r"""
+ getMinValue(ParameterDistribution self) -> double
+ double ParameterDistribution::getMinValue() const
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getMinValue(self)
+
+ def getMaxValue(self):
+ r"""
+ getMaxValue(ParameterDistribution self) -> double
+ double ParameterDistribution::getMaxValue() const
+
+ """
+ return _libBornAgainParam.ParameterDistribution_getMaxValue(self)
+
+# Register ParameterDistribution in _libBornAgainParam:
+_libBornAgainParam.ParameterDistribution_swigregister(ParameterDistribution)
+
+class RangedDistributionGate(object):
+ r"""
+
+
+ Uniform distribution function.
+
+ C++ includes: RangedDistributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(RangedDistributionGate self) -> RangedDistributionGate
+ __init__(RangedDistributionGate self, size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless()) -> RangedDistributionGate
+ __init__(RangedDistributionGate self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGate
+ RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max)
+
+ Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+
+ """
+ _libBornAgainParam.RangedDistributionGate_swiginit(self, _libBornAgainParam.new_RangedDistributionGate(*args))
+
+ def clone(self):
+ r"""
+ clone(RangedDistributionGate self) -> RangedDistributionGate
+ RangedDistributionGate * RangedDistributionGate::clone() const override
+
+ """
+ return _libBornAgainParam.RangedDistributionGate_clone(self)
+ __swig_destroy__ = _libBornAgainParam.delete_RangedDistributionGate
+
+# Register RangedDistributionGate in _libBornAgainParam:
+_libBornAgainParam.RangedDistributionGate_swigregister(RangedDistributionGate)
+
+class RangedDistributionLorentz(object):
+ r"""
+
+
+ Lorentz distribution with median and hwhm.
+
+ C++ includes: RangedDistributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(RangedDistributionLorentz self) -> RangedDistributionLorentz
+ __init__(RangedDistributionLorentz self, size_t n_samples, double hwhm_factor, RealLimits const & limits=RealLimits::limitless()) -> RangedDistributionLorentz
+ __init__(RangedDistributionLorentz self, size_t n_samples, double hwhm_factor, double min, double max) -> RangedDistributionLorentz
+ RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max)
+
+ Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, hwhm_factor = 2.0, while the limits are (-inf, +inf).
+
+ """
+ _libBornAgainParam.RangedDistributionLorentz_swiginit(self, _libBornAgainParam.new_RangedDistributionLorentz(*args))
+
+ def clone(self):
+ r"""
+ clone(RangedDistributionLorentz self) -> RangedDistributionLorentz
+ RangedDistributionLorentz * RangedDistributionLorentz::clone() const override
+
+ """
+ return _libBornAgainParam.RangedDistributionLorentz_clone(self)
+ __swig_destroy__ = _libBornAgainParam.delete_RangedDistributionLorentz
+
+# Register RangedDistributionLorentz in _libBornAgainParam:
+_libBornAgainParam.RangedDistributionLorentz_swigregister(RangedDistributionLorentz)
+
+class RangedDistributionGaussian(object):
+ r"""
+
+
+ Gaussian distribution with standard deviation std_dev.
+
+ C++ includes: RangedDistributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(RangedDistributionGaussian self) -> RangedDistributionGaussian
+ __init__(RangedDistributionGaussian self, size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless()) -> RangedDistributionGaussian
+ __init__(RangedDistributionGaussian self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGaussian
+ RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max)
+
+ Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+
+ """
+ _libBornAgainParam.RangedDistributionGaussian_swiginit(self, _libBornAgainParam.new_RangedDistributionGaussian(*args))
+
+ def clone(self):
+ r"""
+ clone(RangedDistributionGaussian self) -> RangedDistributionGaussian
+ RangedDistributionGaussian * RangedDistributionGaussian::clone() const override
+
+ """
+ return _libBornAgainParam.RangedDistributionGaussian_clone(self)
+ __swig_destroy__ = _libBornAgainParam.delete_RangedDistributionGaussian
+
+# Register RangedDistributionGaussian in _libBornAgainParam:
+_libBornAgainParam.RangedDistributionGaussian_swigregister(RangedDistributionGaussian)
+
+class RangedDistributionLogNormal(object):
+ r"""
+
+
+ Log-normal distribution.
+
+ C++ includes: RangedDistributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(RangedDistributionLogNormal self) -> RangedDistributionLogNormal
+ __init__(RangedDistributionLogNormal self, size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless()) -> RangedDistributionLogNormal
+ __init__(RangedDistributionLogNormal self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionLogNormal
+ RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max)
+
+ Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+
+ """
+ _libBornAgainParam.RangedDistributionLogNormal_swiginit(self, _libBornAgainParam.new_RangedDistributionLogNormal(*args))
+
+ def clone(self):
+ r"""
+ clone(RangedDistributionLogNormal self) -> RangedDistributionLogNormal
+ RangedDistributionLogNormal * RangedDistributionLogNormal::clone() const override
+
+ """
+ return _libBornAgainParam.RangedDistributionLogNormal_clone(self)
+ __swig_destroy__ = _libBornAgainParam.delete_RangedDistributionLogNormal
+
+# Register RangedDistributionLogNormal in _libBornAgainParam:
+_libBornAgainParam.RangedDistributionLogNormal_swigregister(RangedDistributionLogNormal)
+
+class RangedDistributionCosine(object):
+ r"""
+
+
+ Cosine distribution.
+
+ C++ includes: RangedDistributions.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, *args):
+ r"""
+ __init__(RangedDistributionCosine self) -> RangedDistributionCosine
+ __init__(RangedDistributionCosine self, size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless()) -> RangedDistributionCosine
+ __init__(RangedDistributionCosine self, size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionCosine
+ RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max)
+
+ Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf).
+
+ """
+ _libBornAgainParam.RangedDistributionCosine_swiginit(self, _libBornAgainParam.new_RangedDistributionCosine(*args))
+
+ def clone(self):
+ r"""
+ clone(RangedDistributionCosine self) -> RangedDistributionCosine
+ RangedDistributionCosine * RangedDistributionCosine::clone() const override
+
+ """
+ return _libBornAgainParam.RangedDistributionCosine_clone(self)
+ __swig_destroy__ = _libBornAgainParam.delete_RangedDistributionCosine
+
+# Register RangedDistributionCosine in _libBornAgainParam:
+_libBornAgainParam.RangedDistributionCosine_swigregister(RangedDistributionCosine)
+
+class ParameterSample(object):
+ r"""
+
+
+ A parameter value with a weight, as obtained when sampling from a distribution.
+
+ C++ includes: ParameterSample.h
+
+ """
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def __init__(self, _value=0., _weight=1.):
+ r"""
+ __init__(ParameterSample self, double _value=0., double _weight=1.) -> ParameterSample
+ ParameterSample::ParameterSample(double _value=0., double _weight=1.)
+
+ """
+ _libBornAgainParam.ParameterSample_swiginit(self, _libBornAgainParam.new_ParameterSample(_value, _weight))
+ value = property(_libBornAgainParam.ParameterSample_value_get, _libBornAgainParam.ParameterSample_value_set, doc=r"""value : double""")
+ weight = property(_libBornAgainParam.ParameterSample_weight_get, _libBornAgainParam.ParameterSample_weight_set, doc=r"""weight : double""")
+ __swig_destroy__ = _libBornAgainParam.delete_ParameterSample
+
+# Register ParameterSample in _libBornAgainParam:
+_libBornAgainParam.ParameterSample_swigregister(ParameterSample)
+
+class ParameterSampleVector(object):
+ r"""Proxy of C++ std::vector< ParameterSample > class."""
+
+ thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
+ __repr__ = _swig_repr
+
+ def iterator(self):
+ r"""iterator(ParameterSampleVector self) -> SwigPyIterator"""
+ return _libBornAgainParam.ParameterSampleVector_iterator(self)
+ def __iter__(self):
+ return self.iterator()
+
+ def __nonzero__(self):
+ r"""__nonzero__(ParameterSampleVector self) -> bool"""
+ return _libBornAgainParam.ParameterSampleVector___nonzero__(self)
+
+ def __bool__(self):
+ r"""__bool__(ParameterSampleVector self) -> bool"""
+ return _libBornAgainParam.ParameterSampleVector___bool__(self)
+
+ def __len__(self):
+ r"""__len__(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
+ return _libBornAgainParam.ParameterSampleVector___len__(self)
+
+ def __getslice__(self, i, j):
+ r"""__getslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j) -> ParameterSampleVector"""
+ return _libBornAgainParam.ParameterSampleVector___getslice__(self, i, j)
+
+ def __setslice__(self, *args):
+ r"""
+ __setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)
+ __setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j, ParameterSampleVector v)
+ """
+ return _libBornAgainParam.ParameterSampleVector___setslice__(self, *args)
+
+ def __delslice__(self, i, j):
+ r"""__delslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)"""
+ return _libBornAgainParam.ParameterSampleVector___delslice__(self, i, j)
+
+ def __delitem__(self, *args):
+ r"""
+ __delitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i)
+ __delitem__(ParameterSampleVector self, PySliceObject * slice)
+ """
+ return _libBornAgainParam.ParameterSampleVector___delitem__(self, *args)
+
+ def __getitem__(self, *args):
+ r"""
+ __getitem__(ParameterSampleVector self, PySliceObject * slice) -> ParameterSampleVector
+ __getitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i) -> ParameterSample
+ """
+ return _libBornAgainParam.ParameterSampleVector___getitem__(self, *args)
+
+ def __setitem__(self, *args):
+ r"""
+ __setitem__(ParameterSampleVector self, PySliceObject * slice, ParameterSampleVector v)
+ __setitem__(ParameterSampleVector self, PySliceObject * slice)
+ __setitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, ParameterSample x)
+ """
+ return _libBornAgainParam.ParameterSampleVector___setitem__(self, *args)
+
+ def pop(self):
+ r"""pop(ParameterSampleVector self) -> ParameterSample"""
+ return _libBornAgainParam.ParameterSampleVector_pop(self)
+
+ def append(self, x):
+ r"""append(ParameterSampleVector self, ParameterSample x)"""
+ return _libBornAgainParam.ParameterSampleVector_append(self, x)
+
+ def empty(self):
+ r"""empty(ParameterSampleVector self) -> bool"""
+ return _libBornAgainParam.ParameterSampleVector_empty(self)
+
+ def size(self):
+ r"""size(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
+ return _libBornAgainParam.ParameterSampleVector_size(self)
+
+ def swap(self, v):
+ r"""swap(ParameterSampleVector self, ParameterSampleVector v)"""
+ return _libBornAgainParam.ParameterSampleVector_swap(self, v)
+
+ def begin(self):
+ r"""begin(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"""
+ return _libBornAgainParam.ParameterSampleVector_begin(self)
+
+ def end(self):
+ r"""end(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"""
+ return _libBornAgainParam.ParameterSampleVector_end(self)
+
+ def rbegin(self):
+ r"""rbegin(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"""
+ return _libBornAgainParam.ParameterSampleVector_rbegin(self)
+
+ def rend(self):
+ r"""rend(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"""
+ return _libBornAgainParam.ParameterSampleVector_rend(self)
+
+ def clear(self):
+ r"""clear(ParameterSampleVector self)"""
+ return _libBornAgainParam.ParameterSampleVector_clear(self)
+
+ def get_allocator(self):
+ r"""get_allocator(ParameterSampleVector self) -> std::vector< ParameterSample >::allocator_type"""
+ return _libBornAgainParam.ParameterSampleVector_get_allocator(self)
+
+ def pop_back(self):
+ r"""pop_back(ParameterSampleVector self)"""
+ return _libBornAgainParam.ParameterSampleVector_pop_back(self)
+
+ def erase(self, *args):
+ r"""
+ erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos) -> std::vector< ParameterSample >::iterator
+ erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator first, std::vector< ParameterSample >::iterator last) -> std::vector< ParameterSample >::iterator
+ """
+ return _libBornAgainParam.ParameterSampleVector_erase(self, *args)
+
+ def __init__(self, *args):
+ r"""
+ __init__(ParameterSampleVector self) -> ParameterSampleVector
+ __init__(ParameterSampleVector self, ParameterSampleVector other) -> ParameterSampleVector
+ __init__(ParameterSampleVector self, std::vector< ParameterSample >::size_type size) -> ParameterSampleVector
+ __init__(ParameterSampleVector self, std::vector< ParameterSample >::size_type size, ParameterSample value) -> ParameterSampleVector
+ """
+ _libBornAgainParam.ParameterSampleVector_swiginit(self, _libBornAgainParam.new_ParameterSampleVector(*args))
+
+ def push_back(self, x):
+ r"""push_back(ParameterSampleVector self, ParameterSample x)"""
+ return _libBornAgainParam.ParameterSampleVector_push_back(self, x)
+
+ def front(self):
+ r"""front(ParameterSampleVector self) -> ParameterSample"""
+ return _libBornAgainParam.ParameterSampleVector_front(self)
+
+ def back(self):
+ r"""back(ParameterSampleVector self) -> ParameterSample"""
+ return _libBornAgainParam.ParameterSampleVector_back(self)
+
+ def assign(self, n, x):
+ r"""assign(ParameterSampleVector self, std::vector< ParameterSample >::size_type n, ParameterSample x)"""
+ return _libBornAgainParam.ParameterSampleVector_assign(self, n, x)
+
+ def resize(self, *args):
+ r"""
+ resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size)
+ resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size, ParameterSample x)
+ """
+ return _libBornAgainParam.ParameterSampleVector_resize(self, *args)
+
+ def insert(self, *args):
+ r"""
+ insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, ParameterSample x) -> std::vector< ParameterSample >::iterator
+ insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, std::vector< ParameterSample >::size_type n, ParameterSample x)
+ """
+ return _libBornAgainParam.ParameterSampleVector_insert(self, *args)
+
+ def reserve(self, n):
+ r"""reserve(ParameterSampleVector self, std::vector< ParameterSample >::size_type n)"""
+ return _libBornAgainParam.ParameterSampleVector_reserve(self, n)
+
+ def capacity(self):
+ r"""capacity(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"""
+ return _libBornAgainParam.ParameterSampleVector_capacity(self)
+ __swig_destroy__ = _libBornAgainParam.delete_ParameterSampleVector
+
+# Register ParameterSampleVector in _libBornAgainParam:
+_libBornAgainParam.ParameterSampleVector_swigregister(ParameterSampleVector)
+
class ParameterPoolIterator(object):
diff --git a/auto/Wrap/libBornAgainParam_wrap.cpp b/auto/Wrap/libBornAgainParam_wrap.cpp
index 5f612d3d6646c4c9509433e3e54702d9e16886b1..4c025f205fba1eb18857888854b38fc70f0d2766 100644
--- a/auto/Wrap/libBornAgainParam_wrap.cpp
+++ b/auto/Wrap/libBornAgainParam_wrap.cpp
@@ -3180,115 +3180,126 @@ namespace Swig {
#define SWIGTYPE_p_IAbstractParticle swig_types[80]
#define SWIGTYPE_p_ICloneable swig_types[81]
#define SWIGTYPE_p_IClusteredParticles swig_types[82]
-#define SWIGTYPE_p_IFormFactor swig_types[83]
-#define SWIGTYPE_p_IFormFactorBorn swig_types[84]
-#define SWIGTYPE_p_IFormFactorDecorator swig_types[85]
-#define SWIGTYPE_p_IInterferenceFunction swig_types[86]
-#define SWIGTYPE_p_ILayout swig_types[87]
-#define SWIGTYPE_p_INode swig_types[88]
-#define SWIGTYPE_p_INodeVisitor swig_types[89]
-#define SWIGTYPE_p_IParameterT_double_t swig_types[90]
-#define SWIGTYPE_p_IParameterized swig_types[91]
-#define SWIGTYPE_p_IParticle swig_types[92]
-#define SWIGTYPE_p_IPeakShape swig_types[93]
-#define SWIGTYPE_p_IRotation swig_types[94]
-#define SWIGTYPE_p_ISample swig_types[95]
-#define SWIGTYPE_p_IdentityRotation swig_types[96]
-#define SWIGTYPE_p_Instrument swig_types[97]
-#define SWIGTYPE_p_InterferenceFunction1DLattice swig_types[98]
-#define SWIGTYPE_p_InterferenceFunction2DLattice swig_types[99]
-#define SWIGTYPE_p_InterferenceFunction2DParaCrystal swig_types[100]
-#define SWIGTYPE_p_InterferenceFunction2DSuperLattice swig_types[101]
-#define SWIGTYPE_p_InterferenceFunction3DLattice swig_types[102]
-#define SWIGTYPE_p_InterferenceFunctionFinite2DLattice swig_types[103]
-#define SWIGTYPE_p_InterferenceFunctionFinite3DLattice swig_types[104]
-#define SWIGTYPE_p_InterferenceFunctionHardDisk swig_types[105]
-#define SWIGTYPE_p_InterferenceFunctionNone swig_types[106]
-#define SWIGTYPE_p_InterferenceFunctionRadialParaCrystal swig_types[107]
-#define SWIGTYPE_p_InterferenceFunctionTwin swig_types[108]
-#define SWIGTYPE_p_IsGISAXSDetector swig_types[109]
-#define SWIGTYPE_p_Layer swig_types[110]
-#define SWIGTYPE_p_LayerInterface swig_types[111]
-#define SWIGTYPE_p_LayerRoughness swig_types[112]
-#define SWIGTYPE_p_MesoCrystal swig_types[113]
-#define SWIGTYPE_p_MultiLayer swig_types[114]
-#define SWIGTYPE_p_NodeMeta swig_types[115]
-#define SWIGTYPE_p_OffSpecSimulation swig_types[116]
-#define SWIGTYPE_p_ParaMeta swig_types[117]
-#define SWIGTYPE_p_ParameterPool swig_types[118]
-#define SWIGTYPE_p_Particle swig_types[119]
-#define SWIGTYPE_p_ParticleComposition swig_types[120]
-#define SWIGTYPE_p_ParticleCoreShell swig_types[121]
-#define SWIGTYPE_p_ParticleDistribution swig_types[122]
-#define SWIGTYPE_p_ParticleLayout swig_types[123]
-#define SWIGTYPE_p_PoissonNoiseBackground swig_types[124]
-#define SWIGTYPE_p_RealLimits swig_types[125]
-#define SWIGTYPE_p_RealParameter swig_types[126]
-#define SWIGTYPE_p_RectangularDetector swig_types[127]
-#define SWIGTYPE_p_ResolutionFunction2DGaussian swig_types[128]
-#define SWIGTYPE_p_RotationEuler swig_types[129]
-#define SWIGTYPE_p_RotationX swig_types[130]
-#define SWIGTYPE_p_RotationY swig_types[131]
-#define SWIGTYPE_p_RotationZ swig_types[132]
-#define SWIGTYPE_p_SpecularDetector1D swig_types[133]
-#define SWIGTYPE_p_SpecularSimulation swig_types[134]
-#define SWIGTYPE_p_SphericalDetector swig_types[135]
-#define SWIGTYPE_p_SquareLattice swig_types[136]
-#define SWIGTYPE_p_allocator_type swig_types[137]
-#define SWIGTYPE_p_char swig_types[138]
-#define SWIGTYPE_p_difference_type swig_types[139]
-#define SWIGTYPE_p_double swig_types[140]
-#define SWIGTYPE_p_first_type swig_types[141]
-#define SWIGTYPE_p_int swig_types[142]
-#define SWIGTYPE_p_key_type swig_types[143]
-#define SWIGTYPE_p_long_long swig_types[144]
-#define SWIGTYPE_p_mapped_type swig_types[145]
-#define SWIGTYPE_p_p_PyObject swig_types[146]
-#define SWIGTYPE_p_second_type swig_types[147]
-#define SWIGTYPE_p_short swig_types[148]
-#define SWIGTYPE_p_signed_char swig_types[149]
-#define SWIGTYPE_p_size_type swig_types[150]
-#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_double_t_t swig_types[151]
-#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t swig_types[152]
-#define SWIGTYPE_p_std__allocatorT_INode_const_p_t swig_types[153]
-#define SWIGTYPE_p_std__allocatorT_INode_p_t swig_types[154]
-#define SWIGTYPE_p_std__allocatorT_double_t swig_types[155]
-#define SWIGTYPE_p_std__allocatorT_int_t swig_types[156]
-#define SWIGTYPE_p_std__allocatorT_std__complexT_double_t_t swig_types[157]
-#define SWIGTYPE_p_std__allocatorT_std__pairT_double_double_t_t swig_types[158]
-#define SWIGTYPE_p_std__allocatorT_std__pairT_std__string_const_double_t_t swig_types[159]
-#define SWIGTYPE_p_std__allocatorT_std__string_t swig_types[160]
-#define SWIGTYPE_p_std__allocatorT_std__vectorT_double_std__allocatorT_double_t_t_t swig_types[161]
-#define SWIGTYPE_p_std__allocatorT_std__vectorT_int_std__allocatorT_int_t_t_t swig_types[162]
-#define SWIGTYPE_p_std__allocatorT_unsigned_long_t swig_types[163]
-#define SWIGTYPE_p_std__complexT_double_t swig_types[164]
-#define SWIGTYPE_p_std__functionT_void_fF_t swig_types[165]
-#define SWIGTYPE_p_std__invalid_argument swig_types[166]
-#define SWIGTYPE_p_std__lessT_std__string_t swig_types[167]
-#define SWIGTYPE_p_std__mapT_std__string_double_std__lessT_std__string_t_std__allocatorT_std__pairT_std__string_const_double_t_t_t swig_types[168]
-#define SWIGTYPE_p_std__pairT_double_double_t swig_types[169]
-#define SWIGTYPE_p_std__vectorT_BasicVector3DT_double_t_std__allocatorT_BasicVector3DT_double_t_t_t swig_types[170]
-#define SWIGTYPE_p_std__vectorT_BasicVector3DT_std__complexT_double_t_t_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t_t swig_types[171]
-#define SWIGTYPE_p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t swig_types[172]
-#define SWIGTYPE_p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t swig_types[173]
-#define SWIGTYPE_p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t swig_types[174]
-#define SWIGTYPE_p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t swig_types[175]
-#define SWIGTYPE_p_std__vectorT_double_std__allocatorT_double_t_t swig_types[176]
-#define SWIGTYPE_p_std__vectorT_int_std__allocatorT_int_t_t swig_types[177]
-#define SWIGTYPE_p_std__vectorT_std__complexT_double_t_std__allocatorT_std__complexT_double_t_t_t swig_types[178]
-#define SWIGTYPE_p_std__vectorT_std__pairT_double_double_t_std__allocatorT_std__pairT_double_double_t_t_t swig_types[179]
-#define SWIGTYPE_p_std__vectorT_std__string_std__allocatorT_std__string_t_t swig_types[180]
-#define SWIGTYPE_p_std__vectorT_std__vectorT_double_std__allocatorT_double_t_t_std__allocatorT_std__vectorT_double_std__allocatorT_double_t_t_t_t swig_types[181]
-#define SWIGTYPE_p_std__vectorT_std__vectorT_int_std__allocatorT_int_t_t_std__allocatorT_std__vectorT_int_std__allocatorT_int_t_t_t_t swig_types[182]
-#define SWIGTYPE_p_std__vectorT_unsigned_long_std__allocatorT_unsigned_long_t_t swig_types[183]
-#define SWIGTYPE_p_swig__SwigPyIterator swig_types[184]
-#define SWIGTYPE_p_unsigned_char swig_types[185]
-#define SWIGTYPE_p_unsigned_int swig_types[186]
-#define SWIGTYPE_p_unsigned_long_long swig_types[187]
-#define SWIGTYPE_p_unsigned_short swig_types[188]
-#define SWIGTYPE_p_value_type swig_types[189]
-static swig_type_info *swig_types[191];
-static swig_module_info swig_module = {swig_types, 190, 0, 0, 0, 0};
+#define SWIGTYPE_p_IDistribution1D swig_types[83]
+#define SWIGTYPE_p_IFormFactor swig_types[84]
+#define SWIGTYPE_p_IFormFactorBorn swig_types[85]
+#define SWIGTYPE_p_IFormFactorDecorator swig_types[86]
+#define SWIGTYPE_p_IInterferenceFunction swig_types[87]
+#define SWIGTYPE_p_ILayout swig_types[88]
+#define SWIGTYPE_p_INode swig_types[89]
+#define SWIGTYPE_p_INodeVisitor swig_types[90]
+#define SWIGTYPE_p_IParameterT_double_t swig_types[91]
+#define SWIGTYPE_p_IParameterized swig_types[92]
+#define SWIGTYPE_p_IParticle swig_types[93]
+#define SWIGTYPE_p_IPeakShape swig_types[94]
+#define SWIGTYPE_p_IRotation swig_types[95]
+#define SWIGTYPE_p_ISample swig_types[96]
+#define SWIGTYPE_p_IdentityRotation swig_types[97]
+#define SWIGTYPE_p_Instrument swig_types[98]
+#define SWIGTYPE_p_InterferenceFunction1DLattice swig_types[99]
+#define SWIGTYPE_p_InterferenceFunction2DLattice swig_types[100]
+#define SWIGTYPE_p_InterferenceFunction2DParaCrystal swig_types[101]
+#define SWIGTYPE_p_InterferenceFunction2DSuperLattice swig_types[102]
+#define SWIGTYPE_p_InterferenceFunction3DLattice swig_types[103]
+#define SWIGTYPE_p_InterferenceFunctionFinite2DLattice swig_types[104]
+#define SWIGTYPE_p_InterferenceFunctionFinite3DLattice swig_types[105]
+#define SWIGTYPE_p_InterferenceFunctionHardDisk swig_types[106]
+#define SWIGTYPE_p_InterferenceFunctionNone swig_types[107]
+#define SWIGTYPE_p_InterferenceFunctionRadialParaCrystal swig_types[108]
+#define SWIGTYPE_p_InterferenceFunctionTwin swig_types[109]
+#define SWIGTYPE_p_IsGISAXSDetector swig_types[110]
+#define SWIGTYPE_p_Layer swig_types[111]
+#define SWIGTYPE_p_LayerInterface swig_types[112]
+#define SWIGTYPE_p_LayerRoughness swig_types[113]
+#define SWIGTYPE_p_MesoCrystal swig_types[114]
+#define SWIGTYPE_p_MultiLayer swig_types[115]
+#define SWIGTYPE_p_NodeMeta swig_types[116]
+#define SWIGTYPE_p_OffSpecSimulation swig_types[117]
+#define SWIGTYPE_p_ParaMeta swig_types[118]
+#define SWIGTYPE_p_ParameterDistribution swig_types[119]
+#define SWIGTYPE_p_ParameterPool swig_types[120]
+#define SWIGTYPE_p_ParameterSample swig_types[121]
+#define SWIGTYPE_p_Particle swig_types[122]
+#define SWIGTYPE_p_ParticleComposition swig_types[123]
+#define SWIGTYPE_p_ParticleCoreShell swig_types[124]
+#define SWIGTYPE_p_ParticleDistribution swig_types[125]
+#define SWIGTYPE_p_ParticleLayout swig_types[126]
+#define SWIGTYPE_p_PoissonNoiseBackground swig_types[127]
+#define SWIGTYPE_p_RangedDistribution swig_types[128]
+#define SWIGTYPE_p_RangedDistributionCosine swig_types[129]
+#define SWIGTYPE_p_RangedDistributionGate swig_types[130]
+#define SWIGTYPE_p_RangedDistributionGaussian swig_types[131]
+#define SWIGTYPE_p_RangedDistributionLogNormal swig_types[132]
+#define SWIGTYPE_p_RangedDistributionLorentz swig_types[133]
+#define SWIGTYPE_p_RealLimits swig_types[134]
+#define SWIGTYPE_p_RealParameter swig_types[135]
+#define SWIGTYPE_p_RectangularDetector swig_types[136]
+#define SWIGTYPE_p_ResolutionFunction2DGaussian swig_types[137]
+#define SWIGTYPE_p_RotationEuler swig_types[138]
+#define SWIGTYPE_p_RotationX swig_types[139]
+#define SWIGTYPE_p_RotationY swig_types[140]
+#define SWIGTYPE_p_RotationZ swig_types[141]
+#define SWIGTYPE_p_SpecularDetector1D swig_types[142]
+#define SWIGTYPE_p_SpecularSimulation swig_types[143]
+#define SWIGTYPE_p_SphericalDetector swig_types[144]
+#define SWIGTYPE_p_SquareLattice swig_types[145]
+#define SWIGTYPE_p_allocator_type swig_types[146]
+#define SWIGTYPE_p_char swig_types[147]
+#define SWIGTYPE_p_difference_type swig_types[148]
+#define SWIGTYPE_p_double swig_types[149]
+#define SWIGTYPE_p_first_type swig_types[150]
+#define SWIGTYPE_p_int swig_types[151]
+#define SWIGTYPE_p_key_type swig_types[152]
+#define SWIGTYPE_p_long_long swig_types[153]
+#define SWIGTYPE_p_mapped_type swig_types[154]
+#define SWIGTYPE_p_p_PyObject swig_types[155]
+#define SWIGTYPE_p_second_type swig_types[156]
+#define SWIGTYPE_p_short swig_types[157]
+#define SWIGTYPE_p_signed_char swig_types[158]
+#define SWIGTYPE_p_size_type swig_types[159]
+#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_double_t_t swig_types[160]
+#define SWIGTYPE_p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t swig_types[161]
+#define SWIGTYPE_p_std__allocatorT_INode_const_p_t swig_types[162]
+#define SWIGTYPE_p_std__allocatorT_INode_p_t swig_types[163]
+#define SWIGTYPE_p_std__allocatorT_ParameterSample_t swig_types[164]
+#define SWIGTYPE_p_std__allocatorT_double_t swig_types[165]
+#define SWIGTYPE_p_std__allocatorT_int_t swig_types[166]
+#define SWIGTYPE_p_std__allocatorT_std__complexT_double_t_t swig_types[167]
+#define SWIGTYPE_p_std__allocatorT_std__pairT_double_double_t_t swig_types[168]
+#define SWIGTYPE_p_std__allocatorT_std__pairT_std__string_const_double_t_t swig_types[169]
+#define SWIGTYPE_p_std__allocatorT_std__string_t swig_types[170]
+#define SWIGTYPE_p_std__allocatorT_std__vectorT_double_std__allocatorT_double_t_t_t swig_types[171]
+#define SWIGTYPE_p_std__allocatorT_std__vectorT_int_std__allocatorT_int_t_t_t swig_types[172]
+#define SWIGTYPE_p_std__allocatorT_unsigned_long_t swig_types[173]
+#define SWIGTYPE_p_std__complexT_double_t swig_types[174]
+#define SWIGTYPE_p_std__functionT_void_fF_t swig_types[175]
+#define SWIGTYPE_p_std__invalid_argument swig_types[176]
+#define SWIGTYPE_p_std__lessT_std__string_t swig_types[177]
+#define SWIGTYPE_p_std__mapT_std__string_double_std__lessT_std__string_t_std__allocatorT_std__pairT_std__string_const_double_t_t_t swig_types[178]
+#define SWIGTYPE_p_std__pairT_double_double_t swig_types[179]
+#define SWIGTYPE_p_std__vectorT_BasicVector3DT_double_t_std__allocatorT_BasicVector3DT_double_t_t_t swig_types[180]
+#define SWIGTYPE_p_std__vectorT_BasicVector3DT_std__complexT_double_t_t_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t_t swig_types[181]
+#define SWIGTYPE_p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t swig_types[182]
+#define SWIGTYPE_p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t swig_types[183]
+#define SWIGTYPE_p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t swig_types[184]
+#define SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t swig_types[185]
+#define SWIGTYPE_p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t swig_types[186]
+#define SWIGTYPE_p_std__vectorT_double_std__allocatorT_double_t_t swig_types[187]
+#define SWIGTYPE_p_std__vectorT_int_std__allocatorT_int_t_t swig_types[188]
+#define SWIGTYPE_p_std__vectorT_std__complexT_double_t_std__allocatorT_std__complexT_double_t_t_t swig_types[189]
+#define SWIGTYPE_p_std__vectorT_std__pairT_double_double_t_std__allocatorT_std__pairT_double_double_t_t_t swig_types[190]
+#define SWIGTYPE_p_std__vectorT_std__string_std__allocatorT_std__string_t_t swig_types[191]
+#define SWIGTYPE_p_std__vectorT_std__vectorT_double_std__allocatorT_double_t_t_std__allocatorT_std__vectorT_double_std__allocatorT_double_t_t_t_t swig_types[192]
+#define SWIGTYPE_p_std__vectorT_std__vectorT_int_std__allocatorT_int_t_t_std__allocatorT_std__vectorT_int_std__allocatorT_int_t_t_t_t swig_types[193]
+#define SWIGTYPE_p_std__vectorT_unsigned_long_std__allocatorT_unsigned_long_t_t swig_types[194]
+#define SWIGTYPE_p_swig__SwigPyIterator swig_types[195]
+#define SWIGTYPE_p_unsigned_char swig_types[196]
+#define SWIGTYPE_p_unsigned_int swig_types[197]
+#define SWIGTYPE_p_unsigned_long_long swig_types[198]
+#define SWIGTYPE_p_unsigned_short swig_types[199]
+#define SWIGTYPE_p_value_type swig_types[200]
+static swig_type_info *swig_types[202];
+static swig_module_info swig_module = {swig_types, 201, 0, 0, 0, 0};
#define SWIG_TypeQuery(name) SWIG_TypeQueryModule(&swig_module, &swig_module, name)
#define SWIG_MangledTypeQuery(name) SWIG_MangledTypeQueryModule(&swig_module, &swig_module, name)
@@ -6788,6 +6799,12 @@ SWIGINTERN void std_vector_Sl_std_pair_Sl_double_Sc_double_Sg__Sg__insert__SWIG_
#include "Param/Node/INode.h"
#include "Param/Node/INodeVisitor.h"
+#include "Param/Distrib/Distributions.h"
+#include "Param/Distrib/ParameterDistribution.h"
+#include "Param/Varia/ParameterSample.h"
+#include "Param/Distrib/RangedDistributions.h"
+
+
namespace swig {
template <> struct traits< BasicVector3D< double > > {
@@ -7220,6 +7237,115 @@ SWIGINTERN RealParameter const *ParameterPool___getitem__(ParameterPool const *s
return (*(self))[index];
}
+ namespace swig {
+ template <> struct traits< ParameterSample > {
+ typedef pointer_category category;
+ static const char* type_name() { return"ParameterSample"; }
+ };
+ }
+
+
+ namespace swig {
+ template <> struct traits<std::vector< ParameterSample, std::allocator< ParameterSample > > > {
+ typedef pointer_category category;
+ static const char* type_name() {
+ return "std::vector<" "ParameterSample" "," "std::allocator< ParameterSample >" " >";
+ }
+ };
+ }
+
+SWIGINTERN swig::SwigPyIterator *std_vector_Sl_ParameterSample_Sg__iterator(std::vector< ParameterSample > *self,PyObject **PYTHON_SELF){
+ return swig::make_output_iterator(self->begin(), self->begin(), self->end(), *PYTHON_SELF);
+ }
+SWIGINTERN bool std_vector_Sl_ParameterSample_Sg____nonzero__(std::vector< ParameterSample > const *self){
+ return !(self->empty());
+ }
+SWIGINTERN bool std_vector_Sl_ParameterSample_Sg____bool__(std::vector< ParameterSample > const *self){
+ return !(self->empty());
+ }
+SWIGINTERN std::vector< ParameterSample >::size_type std_vector_Sl_ParameterSample_Sg____len__(std::vector< ParameterSample > const *self){
+ return self->size();
+ }
+SWIGINTERN std::vector< ParameterSample,std::allocator< ParameterSample > > *std_vector_Sl_ParameterSample_Sg____getslice__(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i,std::vector< ParameterSample >::difference_type j){
+ return swig::getslice(self, i, j, 1);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____setslice____SWIG_0(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i,std::vector< ParameterSample >::difference_type j){
+ swig::setslice(self, i, j, 1, std::vector< ParameterSample,std::allocator< ParameterSample > >());
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____setslice____SWIG_1(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i,std::vector< ParameterSample >::difference_type j,std::vector< ParameterSample,std::allocator< ParameterSample > > const &v){
+ swig::setslice(self, i, j, 1, v);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____delslice__(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i,std::vector< ParameterSample >::difference_type j){
+ swig::delslice(self, i, j, 1);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____delitem____SWIG_0(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i){
+ swig::erase(self, swig::getpos(self, i));
+ }
+SWIGINTERN std::vector< ParameterSample,std::allocator< ParameterSample > > *std_vector_Sl_ParameterSample_Sg____getitem____SWIG_0(std::vector< ParameterSample > *self,PySliceObject *slice){
+ Py_ssize_t i, j, step;
+ if( !PySlice_Check(slice) ) {
+ SWIG_Error(SWIG_TypeError, "Slice object expected.");
+ return NULL;
+ }
+ PySlice_GetIndices(SWIGPY_SLICE_ARG(slice), (Py_ssize_t)self->size(), &i, &j, &step);
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type id = i;
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type jd = j;
+ return swig::getslice(self, id, jd, step);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____setitem____SWIG_0(std::vector< ParameterSample > *self,PySliceObject *slice,std::vector< ParameterSample,std::allocator< ParameterSample > > const &v){
+ Py_ssize_t i, j, step;
+ if( !PySlice_Check(slice) ) {
+ SWIG_Error(SWIG_TypeError, "Slice object expected.");
+ return;
+ }
+ PySlice_GetIndices(SWIGPY_SLICE_ARG(slice), (Py_ssize_t)self->size(), &i, &j, &step);
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type id = i;
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type jd = j;
+ swig::setslice(self, id, jd, step, v);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____setitem____SWIG_1(std::vector< ParameterSample > *self,PySliceObject *slice){
+ Py_ssize_t i, j, step;
+ if( !PySlice_Check(slice) ) {
+ SWIG_Error(SWIG_TypeError, "Slice object expected.");
+ return;
+ }
+ PySlice_GetIndices(SWIGPY_SLICE_ARG(slice), (Py_ssize_t)self->size(), &i, &j, &step);
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type id = i;
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type jd = j;
+ swig::delslice(self, id, jd, step);
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____delitem____SWIG_1(std::vector< ParameterSample > *self,PySliceObject *slice){
+ Py_ssize_t i, j, step;
+ if( !PySlice_Check(slice) ) {
+ SWIG_Error(SWIG_TypeError, "Slice object expected.");
+ return;
+ }
+ PySlice_GetIndices(SWIGPY_SLICE_ARG(slice), (Py_ssize_t)self->size(), &i, &j, &step);
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type id = i;
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::difference_type jd = j;
+ swig::delslice(self, id, jd, step);
+ }
+SWIGINTERN std::vector< ParameterSample >::value_type const &std_vector_Sl_ParameterSample_Sg____getitem____SWIG_1(std::vector< ParameterSample > const *self,std::vector< ParameterSample >::difference_type i){
+ return *(swig::cgetpos(self, i));
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg____setitem____SWIG_2(std::vector< ParameterSample > *self,std::vector< ParameterSample >::difference_type i,std::vector< ParameterSample >::value_type const &x){
+ *(swig::getpos(self,i)) = x;
+ }
+SWIGINTERN std::vector< ParameterSample >::value_type std_vector_Sl_ParameterSample_Sg__pop(std::vector< ParameterSample > *self){
+ if (self->size() == 0)
+ throw std::out_of_range("pop from empty container");
+ std::vector< ParameterSample,std::allocator< ParameterSample > >::value_type x = self->back();
+ self->pop_back();
+ return x;
+ }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg__append(std::vector< ParameterSample > *self,std::vector< ParameterSample >::value_type const &x){
+ self->push_back(x);
+ }
+SWIGINTERN std::vector< ParameterSample >::iterator std_vector_Sl_ParameterSample_Sg__erase__SWIG_0(std::vector< ParameterSample > *self,std::vector< ParameterSample >::iterator pos){ return self->erase(pos); }
+SWIGINTERN std::vector< ParameterSample >::iterator std_vector_Sl_ParameterSample_Sg__erase__SWIG_1(std::vector< ParameterSample > *self,std::vector< ParameterSample >::iterator first,std::vector< ParameterSample >::iterator last){ return self->erase(first, last); }
+SWIGINTERN std::vector< ParameterSample >::iterator std_vector_Sl_ParameterSample_Sg__insert__SWIG_0(std::vector< ParameterSample > *self,std::vector< ParameterSample >::iterator pos,std::vector< ParameterSample >::value_type const &x){ return self->insert(pos, x); }
+SWIGINTERN void std_vector_Sl_ParameterSample_Sg__insert__SWIG_1(std::vector< ParameterSample > *self,std::vector< ParameterSample >::iterator pos,std::vector< ParameterSample >::size_type n,std::vector< ParameterSample >::value_type const &x){ self->insert(pos, n, x); }
+
/* ---------------------------------------------------
* C++ director class methods
@@ -42294,6 +42420,7539 @@ fail:
}
+SWIGINTERN PyObject *_wrap_IDistribution1D_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ IDistribution1D *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_clone" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ result = (IDistribution1D *)((IDistribution1D const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "IDistribution1D_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_probabilityDensity" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((IDistribution1D const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_getMean" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ result = (double)((IDistribution1D const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantSamples__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantSamples" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantSamples" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantSamples" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "IDistribution1D_equidistantSamples" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "IDistribution1D_equidistantSamples" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((IDistribution1D const *)arg1)->equidistantSamples(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample,std::allocator< ParameterSample > >(static_cast< const std::vector< ParameterSample,std::allocator< ParameterSample > >& >(result))), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantSamples__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantSamples" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantSamples" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantSamples" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((IDistribution1D const *)arg1)->equidistantSamples(arg2,arg3);
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample,std::allocator< ParameterSample > >(static_cast< const std::vector< ParameterSample,std::allocator< ParameterSample > >& >(result))), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantSamples__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > result;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantSamples" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantSamples" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ result = ((IDistribution1D const *)arg1)->equidistantSamples(arg2);
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample,std::allocator< ParameterSample > >(static_cast< const std::vector< ParameterSample,std::allocator< ParameterSample > >& >(result))), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantSamples(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "IDistribution1D_equidistantSamples", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_IDistribution1D, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_IDistribution1D_equidistantSamples__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_IDistribution1D, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_IDistribution1D_equidistantSamples__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_IDistribution1D, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_IDistribution1D_equidistantSamples__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'IDistribution1D_equidistantSamples'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " IDistribution1D::equidistantSamples(size_t,double,RealLimits const &) const\n"
+ " IDistribution1D::equidistantSamples(size_t,double) const\n"
+ " IDistribution1D::equidistantSamples(size_t) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantSamplesInRange(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ double arg4 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ PyObject *swig_obj[4] ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > result;
+
+ if (!SWIG_Python_UnpackTuple(args, "IDistribution1D_equidistantSamplesInRange", 4, 4, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantSamplesInRange" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantSamplesInRange" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantSamplesInRange" "', 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 '" "IDistribution1D_equidistantSamplesInRange" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = ((IDistribution1D const *)arg1)->equidistantSamplesInRange(arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample,std::allocator< ParameterSample > >(static_cast< const std::vector< ParameterSample,std::allocator< ParameterSample > >& >(result))), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantPoints" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "IDistribution1D_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "IDistribution1D_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((IDistribution1D const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantPoints" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((IDistribution1D const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "IDistribution1D_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_IDistribution1D, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_IDistribution1D_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_IDistribution1D, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_IDistribution1D_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'IDistribution1D_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " IDistribution1D::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " IDistribution1D::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_equidistantPointsInRange(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ double arg4 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ PyObject *swig_obj[4] ;
+ std::vector< double,std::allocator< double > > result;
+
+ if (!SWIG_Python_UnpackTuple(args, "IDistribution1D_equidistantPointsInRange", 4, 4, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_equidistantPointsInRange" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "IDistribution1D_equidistantPointsInRange" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "IDistribution1D_equidistantPointsInRange" "', 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 '" "IDistribution1D_equidistantPointsInRange" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = ((IDistribution1D const *)arg1)->equidistantPointsInRange(arg2,arg3,arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_isDelta" "', argument " "1"" of type '" "IDistribution1D const *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ result = (bool)((IDistribution1D const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_IDistribution1D_setUnits(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ std::string *arg2 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ int res2 = SWIG_OLDOBJ ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "IDistribution1D_setUnits", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IDistribution1D_setUnits" "', argument " "1"" of type '" "IDistribution1D *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ {
+ std::string *ptr = (std::string *)0;
+ res2 = SWIG_AsPtr_std_string(swig_obj[1], &ptr);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "IDistribution1D_setUnits" "', argument " "2"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "IDistribution1D_setUnits" "', argument " "2"" of type '" "std::string const &""'");
+ }
+ arg2 = ptr;
+ }
+ (arg1)->setUnits((std::string const &)*arg2);
+ resultobj = SWIG_Py_Void();
+ if (SWIG_IsNewObj(res2)) delete arg2;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res2)) delete arg2;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_IDistribution1D(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ IDistribution1D *arg1 = (IDistribution1D *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IDistribution1D, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_IDistribution1D" "', argument " "1"" of type '" "IDistribution1D *""'");
+ }
+ arg1 = reinterpret_cast< IDistribution1D * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *IDistribution1D_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_IDistribution1D, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionGate__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionGate *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionGate" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionGate *)new DistributionGate(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGate__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ DistributionGate *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_DistributionGate" "', 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_DistributionGate" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (DistributionGate *)new DistributionGate(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGate__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ DistributionGate *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (DistributionGate *)new DistributionGate();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGate(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionGate", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_DistributionGate__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionGate__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_DistributionGate__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionGate'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionGate::DistributionGate(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionGate::DistributionGate(double,double)\n"
+ " DistributionGate::DistributionGate()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionGate *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_clone" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ result = (DistributionGate *)((DistributionGate const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGate, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionGate_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_probabilityDensity" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGate_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionGate const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_getMean" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ result = (double)((DistributionGate const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_getMin(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_getMin" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ result = (double)((DistributionGate const *)arg1)->getMin();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_getMax(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_getMax" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ result = (double)((DistributionGate const *)arg1)->getMax();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_equidistantPoints" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGate_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionGate_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionGate_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionGate_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionGate const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_equidistantPoints" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGate_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionGate_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionGate const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionGate_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionGate, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionGate_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionGate, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionGate_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionGate_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionGate::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionGate::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_isDelta" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ result = (bool)((DistributionGate const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGate_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionGate_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGate_accept" "', argument " "1"" of type '" "DistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionGate_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionGate const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionGate(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGate *arg1 = (DistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGate, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionGate" "', argument " "1"" of type '" "DistributionGate *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGate * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionGate_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionGate, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionGate_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionLorentz__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionLorentz *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionLorentz" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionLorentz *)new DistributionLorentz(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionLorentz__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ DistributionLorentz *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_DistributionLorentz" "', 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_DistributionLorentz" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (DistributionLorentz *)new DistributionLorentz(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionLorentz__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (DistributionLorentz *)new DistributionLorentz();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionLorentz(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionLorentz", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_DistributionLorentz__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionLorentz__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_DistributionLorentz__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionLorentz'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionLorentz::DistributionLorentz(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionLorentz::DistributionLorentz(double,double)\n"
+ " DistributionLorentz::DistributionLorentz()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionLorentz *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_clone" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ result = (DistributionLorentz *)((DistributionLorentz const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionLorentz_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_probabilityDensity" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLorentz_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionLorentz const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_getMean" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ result = (double)((DistributionLorentz const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_getHWHM(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_getHWHM" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ result = (double)((DistributionLorentz const *)arg1)->getHWHM();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionLorentz_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionLorentz const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionLorentz_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionLorentz const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionLorentz_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionLorentz, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionLorentz_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionLorentz, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionLorentz_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionLorentz_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionLorentz::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionLorentz::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_isDelta" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ result = (bool)((DistributionLorentz const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLorentz_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionLorentz_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLorentz_accept" "', argument " "1"" of type '" "DistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionLorentz_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionLorentz const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionLorentz(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLorentz *arg1 = (DistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLorentz, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionLorentz" "', argument " "1"" of type '" "DistributionLorentz *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLorentz * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionLorentz_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionLorentz, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionLorentz_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionGaussian__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionGaussian *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionGaussian" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionGaussian *)new DistributionGaussian(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGaussian__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ DistributionGaussian *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_DistributionGaussian" "', 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_DistributionGaussian" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (DistributionGaussian *)new DistributionGaussian(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGaussian__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (DistributionGaussian *)new DistributionGaussian();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionGaussian(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionGaussian", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_DistributionGaussian__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionGaussian__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_DistributionGaussian__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionGaussian'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionGaussian::DistributionGaussian(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionGaussian::DistributionGaussian(double,double)\n"
+ " DistributionGaussian::DistributionGaussian()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionGaussian *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_clone" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ result = (DistributionGaussian *)((DistributionGaussian const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionGaussian_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_probabilityDensity" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGaussian_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionGaussian const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_getMean" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ result = (double)((DistributionGaussian const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_getStdDev(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_getStdDev" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ result = (double)((DistributionGaussian const *)arg1)->getStdDev();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionGaussian_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionGaussian const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionGaussian_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionGaussian const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionGaussian_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionGaussian, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionGaussian_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionGaussian, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionGaussian_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionGaussian_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionGaussian::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionGaussian::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_isDelta" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ result = (bool)((DistributionGaussian const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionGaussian_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionGaussian_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionGaussian_accept" "', argument " "1"" of type '" "DistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionGaussian_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionGaussian const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionGaussian(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionGaussian *arg1 = (DistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionGaussian, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionGaussian" "', argument " "1"" of type '" "DistributionGaussian *""'");
+ }
+ arg1 = reinterpret_cast< DistributionGaussian * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionGaussian_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionGaussian, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionGaussian_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionLogNormal__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionLogNormal" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionLogNormal *)new DistributionLogNormal(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionLogNormal__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ DistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_DistributionLogNormal" "', 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_DistributionLogNormal" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (DistributionLogNormal *)new DistributionLogNormal(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionLogNormal(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionLogNormal", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionLogNormal__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_DistributionLogNormal__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionLogNormal'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionLogNormal::DistributionLogNormal(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionLogNormal::DistributionLogNormal(double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionLogNormal *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_clone" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ result = (DistributionLogNormal *)((DistributionLogNormal const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionLogNormal_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_probabilityDensity" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLogNormal_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionLogNormal const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_getMean" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ result = (double)((DistributionLogNormal const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_getMedian(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_getMedian" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ result = (double)((DistributionLogNormal const *)arg1)->getMedian();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_getScalePar(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_getScalePar" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ result = (double)((DistributionLogNormal const *)arg1)->getScalePar();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionLogNormal const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionLogNormal_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionLogNormal const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionLogNormal_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionLogNormal, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionLogNormal_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionLogNormal, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionLogNormal_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionLogNormal_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionLogNormal::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionLogNormal::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_isDelta" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ result = (bool)((DistributionLogNormal const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionLogNormal_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_accept" "', argument " "1"" of type '" "DistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionLogNormal_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionLogNormal const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionLogNormal_setUnits(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ std::string *arg2 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ int res2 = SWIG_OLDOBJ ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionLogNormal_setUnits", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionLogNormal_setUnits" "', argument " "1"" of type '" "DistributionLogNormal *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ {
+ std::string *ptr = (std::string *)0;
+ res2 = SWIG_AsPtr_std_string(swig_obj[1], &ptr);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionLogNormal_setUnits" "', argument " "2"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionLogNormal_setUnits" "', argument " "2"" of type '" "std::string const &""'");
+ }
+ arg2 = ptr;
+ }
+ (arg1)->setUnits((std::string const &)*arg2);
+ resultobj = SWIG_Py_Void();
+ if (SWIG_IsNewObj(res2)) delete arg2;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res2)) delete arg2;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionLogNormal(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionLogNormal *arg1 = (DistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionLogNormal, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionLogNormal" "', argument " "1"" of type '" "DistributionLogNormal *""'");
+ }
+ arg1 = reinterpret_cast< DistributionLogNormal * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionLogNormal_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionLogNormal, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionLogNormal_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionCosine__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionCosine *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionCosine" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionCosine *)new DistributionCosine(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionCosine__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ DistributionCosine *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_DistributionCosine" "', 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_DistributionCosine" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (DistributionCosine *)new DistributionCosine(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionCosine__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ DistributionCosine *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (DistributionCosine *)new DistributionCosine();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionCosine(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionCosine", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_DistributionCosine__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionCosine__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_DistributionCosine__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionCosine'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionCosine::DistributionCosine(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionCosine::DistributionCosine(double,double)\n"
+ " DistributionCosine::DistributionCosine()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionCosine *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_clone" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ result = (DistributionCosine *)((DistributionCosine const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionCosine_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_probabilityDensity" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionCosine_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionCosine const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_getMean" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ result = (double)((DistributionCosine const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_getSigma(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_getSigma" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ result = (double)((DistributionCosine const *)arg1)->getSigma();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_equidistantPoints" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionCosine_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionCosine_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionCosine_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionCosine_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionCosine const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_equidistantPoints" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionCosine_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionCosine_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionCosine const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionCosine_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionCosine, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionCosine_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionCosine, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionCosine_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionCosine_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionCosine::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionCosine::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_isDelta" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ result = (bool)((DistributionCosine const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionCosine_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionCosine_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionCosine_accept" "', argument " "1"" of type '" "DistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionCosine_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionCosine const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionCosine(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionCosine *arg1 = (DistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionCosine, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionCosine" "', argument " "1"" of type '" "DistributionCosine *""'");
+ }
+ arg1 = reinterpret_cast< DistributionCosine * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionCosine_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionCosine, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionCosine_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_DistributionTrapezoid__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< double,std::allocator< double > > arg1 ;
+ DistributionTrapezoid *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< double,std::allocator< double > > *ptr = (std::vector< double,std::allocator< double > > *)0;
+ int res = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "new_DistributionTrapezoid" "', argument " "1"" of type '" "std::vector< double,std::allocator< double > > const""'");
+ }
+ arg1 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (DistributionTrapezoid *)new DistributionTrapezoid(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionTrapezoid, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionTrapezoid__SWIG_1(PyObject *SWIGUNUSEDPARM(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 ;
+ DistributionTrapezoid *result = 0 ;
+
+ 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_DistributionTrapezoid" "', 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_DistributionTrapezoid" "', 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_DistributionTrapezoid" "', 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_DistributionTrapezoid" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (DistributionTrapezoid *)new DistributionTrapezoid(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionTrapezoid, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionTrapezoid__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (DistributionTrapezoid *)new DistributionTrapezoid();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionTrapezoid, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_DistributionTrapezoid(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_DistributionTrapezoid", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_DistributionTrapezoid__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< double,std::allocator< double > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_DistributionTrapezoid__SWIG_0(self, argc, argv);
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ 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_DistributionTrapezoid__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_DistributionTrapezoid'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionTrapezoid::DistributionTrapezoid(std::vector< double,std::allocator< double > > const)\n"
+ " DistributionTrapezoid::DistributionTrapezoid(double,double,double,double)\n"
+ " DistributionTrapezoid::DistributionTrapezoid()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ DistributionTrapezoid *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_clone" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (DistributionTrapezoid *)((DistributionTrapezoid const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_probabilityDensity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+ double result;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionTrapezoid_probabilityDensity", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_probabilityDensity" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionTrapezoid_probabilityDensity" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (double)((DistributionTrapezoid const *)arg1)->probabilityDensity(arg2);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_getMean(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_getMean" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (double)((DistributionTrapezoid const *)arg1)->getMean();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_getLeftWidth(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_getLeftWidth" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (double)((DistributionTrapezoid const *)arg1)->getLeftWidth();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_getMiddleWidth(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_getMiddleWidth" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (double)((DistributionTrapezoid const *)arg1)->getMiddleWidth();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_getRightWidth(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_getRightWidth" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (double)((DistributionTrapezoid const *)arg1)->getRightWidth();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_equidistantPoints__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ RealLimits *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "4"" of type '" "RealLimits const &""'");
+ }
+ arg4 = reinterpret_cast< RealLimits * >(argp4);
+ result = ((DistributionTrapezoid const *)arg1)->equidistantPoints(arg2,arg3,(RealLimits const &)*arg4);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_equidistantPoints__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ size_t arg2 ;
+ double arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ std::vector< double,std::allocator< double > > result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "2"" of type '" "size_t""'");
+ }
+ arg2 = static_cast< size_t >(val2);
+ ecode3 = SWIG_AsVal_double(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "DistributionTrapezoid_equidistantPoints" "', argument " "3"" of type '" "double""'");
+ }
+ arg3 = static_cast< double >(val3);
+ result = ((DistributionTrapezoid const *)arg1)->equidistantPoints(arg2,arg3);
+ resultobj = swig::from(static_cast< std::vector< double,std::allocator< double > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_equidistantPoints(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "DistributionTrapezoid_equidistantPoints", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionTrapezoid, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_DistributionTrapezoid_equidistantPoints__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_DistributionTrapezoid, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[3], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_DistributionTrapezoid_equidistantPoints__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'DistributionTrapezoid_equidistantPoints'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " DistributionTrapezoid::equidistantPoints(size_t,double,RealLimits const &) const\n"
+ " DistributionTrapezoid::equidistantPoints(size_t,double) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_isDelta(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_isDelta" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ result = (bool)((DistributionTrapezoid const *)arg1)->isDelta();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_DistributionTrapezoid_accept(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ INodeVisitor *arg2 = (INodeVisitor *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "DistributionTrapezoid_accept", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "DistributionTrapezoid_accept" "', argument " "1"" of type '" "DistributionTrapezoid const *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2,SWIGTYPE_p_INodeVisitor, 0 | 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "DistributionTrapezoid_accept" "', argument " "2"" of type '" "INodeVisitor *""'");
+ }
+ arg2 = reinterpret_cast< INodeVisitor * >(argp2);
+ ((DistributionTrapezoid const *)arg1)->accept(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_DistributionTrapezoid(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ DistributionTrapezoid *arg1 = (DistributionTrapezoid *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_DistributionTrapezoid, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_DistributionTrapezoid" "', argument " "1"" of type '" "DistributionTrapezoid *""'");
+ }
+ arg1 = reinterpret_cast< DistributionTrapezoid * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *DistributionTrapezoid_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_DistributionTrapezoid, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *DistributionTrapezoid_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::string *arg1 = 0 ;
+ IDistribution1D *arg2 = 0 ;
+ size_t arg3 ;
+ double arg4 ;
+ RealLimits *arg5 = 0 ;
+ int res1 = SWIG_OLDOBJ ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ size_t val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ void *argp5 = 0 ;
+ int res5 = 0 ;
+ ParameterDistribution *result = 0 ;
+
+ if ((nobjs < 5) || (nobjs > 5)) SWIG_fail;
+ {
+ std::string *ptr = (std::string *)0;
+ res1 = SWIG_AsPtr_std_string(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ arg1 = ptr;
+ }
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_IDistribution1D, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ arg2 = reinterpret_cast< IDistribution1D * >(argp2);
+ ecode3 = SWIG_AsVal_size_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "new_ParameterDistribution" "', argument " "3"" of type '" "size_t""'");
+ }
+ arg3 = static_cast< size_t >(val3);
+ ecode4 = SWIG_AsVal_double(swig_obj[3], &val4);
+ if (!SWIG_IsOK(ecode4)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode4), "in method '" "new_ParameterDistribution" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ res5 = SWIG_ConvertPtr(swig_obj[4], &argp5, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res5)) {
+ SWIG_exception_fail(SWIG_ArgError(res5), "in method '" "new_ParameterDistribution" "', argument " "5"" of type '" "RealLimits const &""'");
+ }
+ if (!argp5) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "5"" of type '" "RealLimits const &""'");
+ }
+ arg5 = reinterpret_cast< RealLimits * >(argp5);
+ result = (ParameterDistribution *)new ParameterDistribution((std::string const &)*arg1,(IDistribution1D const &)*arg2,arg3,arg4,(RealLimits const &)*arg5);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NEW | 0 );
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::string *arg1 = 0 ;
+ IDistribution1D *arg2 = 0 ;
+ size_t arg3 ;
+ double arg4 ;
+ int res1 = SWIG_OLDOBJ ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ size_t val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ ParameterDistribution *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ {
+ std::string *ptr = (std::string *)0;
+ res1 = SWIG_AsPtr_std_string(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ arg1 = ptr;
+ }
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_IDistribution1D, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ arg2 = reinterpret_cast< IDistribution1D * >(argp2);
+ ecode3 = SWIG_AsVal_size_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "new_ParameterDistribution" "', argument " "3"" of type '" "size_t""'");
+ }
+ arg3 = static_cast< size_t >(val3);
+ ecode4 = SWIG_AsVal_double(swig_obj[3], &val4);
+ if (!SWIG_IsOK(ecode4)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode4), "in method '" "new_ParameterDistribution" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (ParameterDistribution *)new ParameterDistribution((std::string const &)*arg1,(IDistribution1D const &)*arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NEW | 0 );
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::string *arg1 = 0 ;
+ IDistribution1D *arg2 = 0 ;
+ size_t arg3 ;
+ int res1 = SWIG_OLDOBJ ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ size_t val3 ;
+ int ecode3 = 0 ;
+ ParameterDistribution *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ {
+ std::string *ptr = (std::string *)0;
+ res1 = SWIG_AsPtr_std_string(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ arg1 = ptr;
+ }
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_IDistribution1D, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ arg2 = reinterpret_cast< IDistribution1D * >(argp2);
+ ecode3 = SWIG_AsVal_size_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "new_ParameterDistribution" "', argument " "3"" of type '" "size_t""'");
+ }
+ arg3 = static_cast< size_t >(val3);
+ result = (ParameterDistribution *)new ParameterDistribution((std::string const &)*arg1,(IDistribution1D const &)*arg2,arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NEW | 0 );
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::string *arg1 = 0 ;
+ IDistribution1D *arg2 = 0 ;
+ size_t arg3 ;
+ double arg4 ;
+ double arg5 ;
+ int res1 = SWIG_OLDOBJ ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ size_t val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ double val5 ;
+ int ecode5 = 0 ;
+ ParameterDistribution *result = 0 ;
+
+ if ((nobjs < 5) || (nobjs > 5)) SWIG_fail;
+ {
+ std::string *ptr = (std::string *)0;
+ res1 = SWIG_AsPtr_std_string(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "std::string const &""'");
+ }
+ arg1 = ptr;
+ }
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_IDistribution1D, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "2"" of type '" "IDistribution1D const &""'");
+ }
+ arg2 = reinterpret_cast< IDistribution1D * >(argp2);
+ ecode3 = SWIG_AsVal_size_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "new_ParameterDistribution" "', argument " "3"" of type '" "size_t""'");
+ }
+ arg3 = static_cast< size_t >(val3);
+ ecode4 = SWIG_AsVal_double(swig_obj[3], &val4);
+ if (!SWIG_IsOK(ecode4)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode4), "in method '" "new_ParameterDistribution" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ ecode5 = SWIG_AsVal_double(swig_obj[4], &val5);
+ if (!SWIG_IsOK(ecode5)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode5), "in method '" "new_ParameterDistribution" "', argument " "5"" of type '" "double""'");
+ }
+ arg5 = static_cast< double >(val5);
+ result = (ParameterDistribution *)new ParameterDistribution((std::string const &)*arg1,(IDistribution1D const &)*arg2,arg3,arg4,arg5);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NEW | 0 );
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution__SWIG_4(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ParameterDistribution *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1, SWIGTYPE_p_ParameterDistribution, 0 | 0);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "ParameterDistribution const &""'");
+ }
+ if (!argp1) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterDistribution" "', argument " "1"" of type '" "ParameterDistribution const &""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (ParameterDistribution *)new ParameterDistribution((ParameterDistribution const &)*arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterDistribution(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[6] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_ParameterDistribution", 0, 5, argv))) SWIG_fail;
+ --argc;
+ if (argc == 1) {
+ int _v;
+ int res = SWIG_ConvertPtr(argv[0], 0, SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_ParameterDistribution__SWIG_4(self, argc, argv);
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ int res = SWIG_AsPtr_std_string(argv[0], (std::string**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[1], 0, SWIGTYPE_p_IDistribution1D, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_ParameterDistribution__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ int res = SWIG_AsPtr_std_string(argv[0], (std::string**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[1], 0, SWIGTYPE_p_IDistribution1D, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(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_ParameterDistribution__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+ if (argc == 5) {
+ int _v;
+ int res = SWIG_AsPtr_std_string(argv[0], (std::string**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[1], 0, SWIGTYPE_p_IDistribution1D, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[3], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[4], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_ParameterDistribution__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+ }
+ if (argc == 5) {
+ int _v;
+ int res = SWIG_AsPtr_std_string(argv[0], (std::string**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[1], 0, SWIGTYPE_p_IDistribution1D, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[3], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[4], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_ParameterDistribution__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_ParameterDistribution'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " ParameterDistribution::ParameterDistribution(std::string const &,IDistribution1D const &,size_t,double,RealLimits const &)\n"
+ " ParameterDistribution::ParameterDistribution(std::string const &,IDistribution1D const &,size_t,double)\n"
+ " ParameterDistribution::ParameterDistribution(std::string const &,IDistribution1D const &,size_t)\n"
+ " ParameterDistribution::ParameterDistribution(std::string const &,IDistribution1D const &,size_t,double,double)\n"
+ " ParameterDistribution::ParameterDistribution(ParameterDistribution const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_ParameterDistribution(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_ParameterDistribution" "', argument " "1"" of type '" "ParameterDistribution *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_linkParameter(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ std::string arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[2] ;
+ ParameterDistribution *result = 0 ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterDistribution_linkParameter", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_linkParameter" "', argument " "1"" of type '" "ParameterDistribution *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ {
+ std::string *ptr = (std::string *)0;
+ int res = SWIG_AsPtr_std_string(swig_obj[1], &ptr);
+ if (!SWIG_IsOK(res) || !ptr) {
+ SWIG_exception_fail(SWIG_ArgError((ptr ? res : SWIG_TypeError)), "in method '" "ParameterDistribution_linkParameter" "', argument " "2"" of type '" "std::string""'");
+ }
+ arg2 = *ptr;
+ if (SWIG_IsNewObj(res)) delete ptr;
+ }
+ result = (ParameterDistribution *) &(arg1)->linkParameter(arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getMainParameterName(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::string result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getMainParameterName" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = ((ParameterDistribution const *)arg1)->getMainParameterName();
+ resultobj = SWIG_From_std_string(static_cast< std::string >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getNbrSamples(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ size_t result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getNbrSamples" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = ((ParameterDistribution const *)arg1)->getNbrSamples();
+ resultobj = SWIG_From_size_t(static_cast< size_t >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getSigmaFactor(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getSigmaFactor" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (double)((ParameterDistribution const *)arg1)->getSigmaFactor();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getDistribution__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ IDistribution1D *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getDistribution" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (IDistribution1D *)((ParameterDistribution const *)arg1)->getDistribution();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getDistribution__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ IDistribution1D *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getDistribution" "', argument " "1"" of type '" "ParameterDistribution *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (IDistribution1D *)(arg1)->getDistribution();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_IDistribution1D, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getDistribution(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[2] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterDistribution_getDistribution", 0, 1, argv))) SWIG_fail;
+ --argc;
+ if (argc == 1) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_ParameterDistribution, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterDistribution_getDistribution__SWIG_1(self, argc, argv);
+ }
+ }
+ if (argc == 1) {
+ int _v;
+ void *vptr = 0;
+ int res = SWIG_ConvertPtr(argv[0], &vptr, SWIGTYPE_p_ParameterDistribution, 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterDistribution_getDistribution__SWIG_0(self, argc, argv);
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterDistribution_getDistribution'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " ParameterDistribution::getDistribution() const\n"
+ " ParameterDistribution::getDistribution()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_generateSamples(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_generateSamples" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = ((ParameterDistribution const *)arg1)->generateSamples();
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample,std::allocator< ParameterSample > >(static_cast< const std::vector< ParameterSample,std::allocator< ParameterSample > >& >(result))), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getLinkedParameterNames(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< std::string,std::allocator< std::string > > result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getLinkedParameterNames" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = ((ParameterDistribution const *)arg1)->getLinkedParameterNames();
+ resultobj = swig::from(static_cast< std::vector< std::string,std::allocator< std::string > > >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getLimits(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RealLimits result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getLimits" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = ((ParameterDistribution const *)arg1)->getLimits();
+ resultobj = SWIG_NewPointerObj((new RealLimits(static_cast< const RealLimits& >(result))), SWIGTYPE_p_RealLimits, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getMinValue(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getMinValue" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (double)((ParameterDistribution const *)arg1)->getMinValue();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterDistribution_getMaxValue(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterDistribution *arg1 = (ParameterDistribution *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterDistribution, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterDistribution_getMaxValue" "', argument " "1"" of type '" "ParameterDistribution const *""'");
+ }
+ arg1 = reinterpret_cast< ParameterDistribution * >(argp1);
+ result = (double)((ParameterDistribution const *)arg1)->getMaxValue();
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *ParameterDistribution_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_ParameterDistribution, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *ParameterDistribution_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGate__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ RangedDistributionGate *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (RangedDistributionGate *)new RangedDistributionGate();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGate__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ RealLimits *arg3 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ RangedDistributionGate *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGate" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGate" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "new_RangedDistributionGate" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_RangedDistributionGate" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ arg3 = reinterpret_cast< RealLimits * >(argp3);
+ result = (RangedDistributionGate *)new RangedDistributionGate(arg1,arg2,(RealLimits const &)*arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGate__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ RangedDistributionGate *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGate" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGate" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (RangedDistributionGate *)new RangedDistributionGate(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGate__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ RangedDistributionGate *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGate" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGate" "', 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_RangedDistributionGate" "', 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_RangedDistributionGate" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (RangedDistributionGate *)new RangedDistributionGate(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGate, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGate(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_RangedDistributionGate", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_RangedDistributionGate__SWIG_0(self, argc, argv);
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_RangedDistributionGate__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[2], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_RangedDistributionGate__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_RangedDistributionGate__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_RangedDistributionGate'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " RangedDistributionGate::RangedDistributionGate()\n"
+ " RangedDistributionGate::RangedDistributionGate(size_t,double,RealLimits const &)\n"
+ " RangedDistributionGate::RangedDistributionGate(size_t,double)\n"
+ " RangedDistributionGate::RangedDistributionGate(size_t,double,double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_RangedDistributionGate_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionGate *arg1 = (RangedDistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RangedDistributionGate *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionGate, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "RangedDistributionGate_clone" "', argument " "1"" of type '" "RangedDistributionGate const *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionGate * >(argp1);
+ result = (RangedDistributionGate *)((RangedDistributionGate const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGate, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_RangedDistributionGate(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionGate *arg1 = (RangedDistributionGate *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionGate, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_RangedDistributionGate" "', argument " "1"" of type '" "RangedDistributionGate *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionGate * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *RangedDistributionGate_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_RangedDistributionGate, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *RangedDistributionGate_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLorentz__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ RangedDistributionLorentz *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (RangedDistributionLorentz *)new RangedDistributionLorentz();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLorentz__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ RealLimits *arg3 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ RangedDistributionLorentz *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLorentz" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLorentz" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "new_RangedDistributionLorentz" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_RangedDistributionLorentz" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ arg3 = reinterpret_cast< RealLimits * >(argp3);
+ result = (RangedDistributionLorentz *)new RangedDistributionLorentz(arg1,arg2,(RealLimits const &)*arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLorentz__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ RangedDistributionLorentz *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLorentz" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLorentz" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (RangedDistributionLorentz *)new RangedDistributionLorentz(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLorentz__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ RangedDistributionLorentz *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLorentz" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLorentz" "', 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_RangedDistributionLorentz" "', 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_RangedDistributionLorentz" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (RangedDistributionLorentz *)new RangedDistributionLorentz(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLorentz, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLorentz(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_RangedDistributionLorentz", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_RangedDistributionLorentz__SWIG_0(self, argc, argv);
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_RangedDistributionLorentz__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[2], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_RangedDistributionLorentz__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_RangedDistributionLorentz__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_RangedDistributionLorentz'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " RangedDistributionLorentz::RangedDistributionLorentz()\n"
+ " RangedDistributionLorentz::RangedDistributionLorentz(size_t,double,RealLimits const &)\n"
+ " RangedDistributionLorentz::RangedDistributionLorentz(size_t,double)\n"
+ " RangedDistributionLorentz::RangedDistributionLorentz(size_t,double,double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_RangedDistributionLorentz_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionLorentz *arg1 = (RangedDistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RangedDistributionLorentz *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionLorentz, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "RangedDistributionLorentz_clone" "', argument " "1"" of type '" "RangedDistributionLorentz const *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionLorentz * >(argp1);
+ result = (RangedDistributionLorentz *)((RangedDistributionLorentz const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLorentz, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_RangedDistributionLorentz(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionLorentz *arg1 = (RangedDistributionLorentz *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionLorentz, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_RangedDistributionLorentz" "', argument " "1"" of type '" "RangedDistributionLorentz *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionLorentz * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *RangedDistributionLorentz_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_RangedDistributionLorentz, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *RangedDistributionLorentz_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGaussian__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ RangedDistributionGaussian *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (RangedDistributionGaussian *)new RangedDistributionGaussian();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGaussian__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ RealLimits *arg3 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ RangedDistributionGaussian *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGaussian" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGaussian" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "new_RangedDistributionGaussian" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_RangedDistributionGaussian" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ arg3 = reinterpret_cast< RealLimits * >(argp3);
+ result = (RangedDistributionGaussian *)new RangedDistributionGaussian(arg1,arg2,(RealLimits const &)*arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGaussian__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ RangedDistributionGaussian *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGaussian" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGaussian" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (RangedDistributionGaussian *)new RangedDistributionGaussian(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGaussian__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ RangedDistributionGaussian *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionGaussian" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionGaussian" "', 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_RangedDistributionGaussian" "', 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_RangedDistributionGaussian" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (RangedDistributionGaussian *)new RangedDistributionGaussian(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGaussian, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionGaussian(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_RangedDistributionGaussian", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_RangedDistributionGaussian__SWIG_0(self, argc, argv);
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_RangedDistributionGaussian__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[2], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_RangedDistributionGaussian__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_RangedDistributionGaussian__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_RangedDistributionGaussian'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " RangedDistributionGaussian::RangedDistributionGaussian()\n"
+ " RangedDistributionGaussian::RangedDistributionGaussian(size_t,double,RealLimits const &)\n"
+ " RangedDistributionGaussian::RangedDistributionGaussian(size_t,double)\n"
+ " RangedDistributionGaussian::RangedDistributionGaussian(size_t,double,double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_RangedDistributionGaussian_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionGaussian *arg1 = (RangedDistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RangedDistributionGaussian *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionGaussian, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "RangedDistributionGaussian_clone" "', argument " "1"" of type '" "RangedDistributionGaussian const *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionGaussian * >(argp1);
+ result = (RangedDistributionGaussian *)((RangedDistributionGaussian const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionGaussian, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_RangedDistributionGaussian(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionGaussian *arg1 = (RangedDistributionGaussian *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionGaussian, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_RangedDistributionGaussian" "', argument " "1"" of type '" "RangedDistributionGaussian *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionGaussian * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *RangedDistributionGaussian_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_RangedDistributionGaussian, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *RangedDistributionGaussian_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLogNormal__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ RangedDistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (RangedDistributionLogNormal *)new RangedDistributionLogNormal();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLogNormal__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ RealLimits *arg3 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ RangedDistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLogNormal" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLogNormal" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "new_RangedDistributionLogNormal" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_RangedDistributionLogNormal" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ arg3 = reinterpret_cast< RealLimits * >(argp3);
+ result = (RangedDistributionLogNormal *)new RangedDistributionLogNormal(arg1,arg2,(RealLimits const &)*arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLogNormal__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ RangedDistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLogNormal" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLogNormal" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (RangedDistributionLogNormal *)new RangedDistributionLogNormal(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLogNormal__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ RangedDistributionLogNormal *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionLogNormal" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionLogNormal" "', 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_RangedDistributionLogNormal" "', 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_RangedDistributionLogNormal" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (RangedDistributionLogNormal *)new RangedDistributionLogNormal(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLogNormal, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionLogNormal(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_RangedDistributionLogNormal", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_RangedDistributionLogNormal__SWIG_0(self, argc, argv);
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_RangedDistributionLogNormal__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[2], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_RangedDistributionLogNormal__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_RangedDistributionLogNormal__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_RangedDistributionLogNormal'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " RangedDistributionLogNormal::RangedDistributionLogNormal()\n"
+ " RangedDistributionLogNormal::RangedDistributionLogNormal(size_t,double,RealLimits const &)\n"
+ " RangedDistributionLogNormal::RangedDistributionLogNormal(size_t,double)\n"
+ " RangedDistributionLogNormal::RangedDistributionLogNormal(size_t,double,double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_RangedDistributionLogNormal_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionLogNormal *arg1 = (RangedDistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RangedDistributionLogNormal *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionLogNormal, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "RangedDistributionLogNormal_clone" "', argument " "1"" of type '" "RangedDistributionLogNormal const *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionLogNormal * >(argp1);
+ result = (RangedDistributionLogNormal *)((RangedDistributionLogNormal const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionLogNormal, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_RangedDistributionLogNormal(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionLogNormal *arg1 = (RangedDistributionLogNormal *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionLogNormal, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_RangedDistributionLogNormal" "', argument " "1"" of type '" "RangedDistributionLogNormal *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionLogNormal * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *RangedDistributionLogNormal_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_RangedDistributionLogNormal, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *RangedDistributionLogNormal_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionCosine__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ RangedDistributionCosine *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (RangedDistributionCosine *)new RangedDistributionCosine();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionCosine__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ RealLimits *arg3 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ RangedDistributionCosine *result = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionCosine" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionCosine" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_RealLimits, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "new_RangedDistributionCosine" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_RangedDistributionCosine" "', argument " "3"" of type '" "RealLimits const &""'");
+ }
+ arg3 = reinterpret_cast< RealLimits * >(argp3);
+ result = (RangedDistributionCosine *)new RangedDistributionCosine(arg1,arg2,(RealLimits const &)*arg3);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionCosine__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ RangedDistributionCosine *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionCosine" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionCosine" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (RangedDistributionCosine *)new RangedDistributionCosine(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionCosine__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ size_t arg1 ;
+ double arg2 ;
+ double arg3 ;
+ double arg4 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ double val3 ;
+ int ecode3 = 0 ;
+ double val4 ;
+ int ecode4 = 0 ;
+ RangedDistributionCosine *result = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_RangedDistributionCosine" "', argument " "1"" of type '" "size_t""'");
+ }
+ arg1 = static_cast< size_t >(val1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "new_RangedDistributionCosine" "', 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_RangedDistributionCosine" "', 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_RangedDistributionCosine" "', argument " "4"" of type '" "double""'");
+ }
+ arg4 = static_cast< double >(val4);
+ result = (RangedDistributionCosine *)new RangedDistributionCosine(arg1,arg2,arg3,arg4);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionCosine, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_RangedDistributionCosine(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_RangedDistributionCosine", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_RangedDistributionCosine__SWIG_0(self, argc, argv);
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_double(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_RangedDistributionCosine__SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_ConvertPtr(argv[2], 0, SWIGTYPE_p_RealLimits, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_RangedDistributionCosine__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(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_RangedDistributionCosine__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_RangedDistributionCosine'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " RangedDistributionCosine::RangedDistributionCosine()\n"
+ " RangedDistributionCosine::RangedDistributionCosine(size_t,double,RealLimits const &)\n"
+ " RangedDistributionCosine::RangedDistributionCosine(size_t,double)\n"
+ " RangedDistributionCosine::RangedDistributionCosine(size_t,double,double,double)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_RangedDistributionCosine_clone(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionCosine *arg1 = (RangedDistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ RangedDistributionCosine *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionCosine, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "RangedDistributionCosine_clone" "', argument " "1"" of type '" "RangedDistributionCosine const *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionCosine * >(argp1);
+ result = (RangedDistributionCosine *)((RangedDistributionCosine const *)arg1)->clone();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_RangedDistributionCosine, 0 | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_RangedDistributionCosine(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ RangedDistributionCosine *arg1 = (RangedDistributionCosine *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_RangedDistributionCosine, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_RangedDistributionCosine" "', argument " "1"" of type '" "RangedDistributionCosine *""'");
+ }
+ arg1 = reinterpret_cast< RangedDistributionCosine * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *RangedDistributionCosine_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_RangedDistributionCosine, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *RangedDistributionCosine_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_new_ParameterSample__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double arg2 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ ParameterSample *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_ParameterSample" "', 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_ParameterSample" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ result = (ParameterSample *)new ParameterSample(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSample__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ double arg1 ;
+ double val1 ;
+ int ecode1 = 0 ;
+ ParameterSample *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ ecode1 = SWIG_AsVal_double(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_ParameterSample" "', argument " "1"" of type '" "double""'");
+ }
+ arg1 = static_cast< double >(val1);
+ result = (ParameterSample *)new ParameterSample(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSample__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ ParameterSample *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (ParameterSample *)new ParameterSample();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSample(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_ParameterSample", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_ParameterSample__SWIG_2(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ {
+ int res = SWIG_AsVal_double(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_ParameterSample__SWIG_1(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ 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) {
+ return _wrap_new_ParameterSample__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_ParameterSample'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " ParameterSample::ParameterSample(double,double)\n"
+ " ParameterSample::ParameterSample(double)\n"
+ " ParameterSample::ParameterSample()\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSample_value_set(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterSample *arg1 = (ParameterSample *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSample_value_set", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterSample, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSample_value_set" "', argument " "1"" of type '" "ParameterSample *""'");
+ }
+ arg1 = reinterpret_cast< ParameterSample * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSample_value_set" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ if (arg1) (arg1)->value = arg2;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSample_value_get(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterSample *arg1 = (ParameterSample *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterSample, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSample_value_get" "', argument " "1"" of type '" "ParameterSample *""'");
+ }
+ arg1 = reinterpret_cast< ParameterSample * >(argp1);
+ result = (double) ((arg1)->value);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSample_weight_set(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterSample *arg1 = (ParameterSample *) 0 ;
+ double arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ double val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSample_weight_set", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterSample, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSample_weight_set" "', argument " "1"" of type '" "ParameterSample *""'");
+ }
+ arg1 = reinterpret_cast< ParameterSample * >(argp1);
+ ecode2 = SWIG_AsVal_double(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSample_weight_set" "', argument " "2"" of type '" "double""'");
+ }
+ arg2 = static_cast< double >(val2);
+ if (arg1) (arg1)->weight = arg2;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSample_weight_get(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterSample *arg1 = (ParameterSample *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ double result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterSample, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSample_weight_get" "', argument " "1"" of type '" "ParameterSample *""'");
+ }
+ arg1 = reinterpret_cast< ParameterSample * >(argp1);
+ result = (double) ((arg1)->weight);
+ resultobj = SWIG_From_double(static_cast< double >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_ParameterSample(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ ParameterSample *arg1 = (ParameterSample *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_ParameterSample, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_ParameterSample" "', argument " "1"" of type '" "ParameterSample *""'");
+ }
+ arg1 = reinterpret_cast< ParameterSample * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *ParameterSample_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_ParameterSample, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *ParameterSample_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_iterator(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ PyObject **arg2 = (PyObject **) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ swig::SwigPyIterator *result = 0 ;
+
+ arg2 = &swig_obj[0];
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_iterator" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (swig::SwigPyIterator *)std_vector_Sl_ParameterSample_Sg__iterator(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_swig__SwigPyIterator, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___nonzero__(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___nonzero__" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (bool)std_vector_Sl_ParameterSample_Sg____nonzero__((std::vector< ParameterSample > const *)arg1);
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___bool__(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___bool__" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (bool)std_vector_Sl_ParameterSample_Sg____bool__((std::vector< ParameterSample > const *)arg1);
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___len__(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::size_type result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___len__" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = std_vector_Sl_ParameterSample_Sg____len__((std::vector< ParameterSample > const *)arg1);
+ resultobj = SWIG_From_size_t(static_cast< size_t >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___getslice__(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ std::vector< ParameterSample >::difference_type arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ ptrdiff_t val3 ;
+ int ecode3 = 0 ;
+ PyObject *swig_obj[3] ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *result = 0 ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector___getslice__", 3, 3, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___getslice__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___getslice__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ ecode3 = SWIG_AsVal_ptrdiff_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "ParameterSampleVector___getslice__" "', argument " "3"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg3 = static_cast< std::vector< ParameterSample >::difference_type >(val3);
+ try {
+ result = (std::vector< ParameterSample,std::allocator< ParameterSample > > *)std_vector_Sl_ParameterSample_Sg____getslice__(arg1,arg2,arg3);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setslice____SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ std::vector< ParameterSample >::difference_type arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ ptrdiff_t val3 ;
+ int ecode3 = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___setslice__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___setslice__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ ecode3 = SWIG_AsVal_ptrdiff_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "ParameterSampleVector___setslice__" "', argument " "3"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg3 = static_cast< std::vector< ParameterSample >::difference_type >(val3);
+ try {
+ std_vector_Sl_ParameterSample_Sg____setslice____SWIG_0(arg1,arg2,arg3);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setslice____SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ std::vector< ParameterSample >::difference_type arg3 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ ptrdiff_t val3 ;
+ int ecode3 = 0 ;
+ int res4 = SWIG_OLDOBJ ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___setslice__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___setslice__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ ecode3 = SWIG_AsVal_ptrdiff_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "ParameterSampleVector___setslice__" "', argument " "3"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg3 = static_cast< std::vector< ParameterSample >::difference_type >(val3);
+ {
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *ptr = (std::vector< ParameterSample,std::allocator< ParameterSample > > *)0;
+ res4 = swig::asptr(swig_obj[3], &ptr);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "ParameterSampleVector___setslice__" "', argument " "4"" of type '" "std::vector< ParameterSample,std::allocator< ParameterSample > > const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector___setslice__" "', argument " "4"" of type '" "std::vector< ParameterSample,std::allocator< ParameterSample > > const &""'");
+ }
+ arg4 = ptr;
+ }
+ try {
+ std_vector_Sl_ParameterSample_Sg____setslice____SWIG_1(arg1,arg2,arg3,(std::vector< ParameterSample,std::allocator< ParameterSample > > const &)*arg4);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ if (SWIG_IsNewObj(res4)) delete arg4;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res4)) delete arg4;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setslice__(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector___setslice__", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___setslice____SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = swig::asptr(argv[3], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector___setslice____SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector___setslice__'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::__setslice__(std::vector< ParameterSample >::difference_type,std::vector< ParameterSample >::difference_type)\n"
+ " std::vector< ParameterSample >::__setslice__(std::vector< ParameterSample >::difference_type,std::vector< ParameterSample >::difference_type,std::vector< ParameterSample,std::allocator< ParameterSample > > const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___delslice__(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ std::vector< ParameterSample >::difference_type arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ ptrdiff_t val3 ;
+ int ecode3 = 0 ;
+ PyObject *swig_obj[3] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector___delslice__", 3, 3, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___delslice__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___delslice__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ ecode3 = SWIG_AsVal_ptrdiff_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "ParameterSampleVector___delslice__" "', argument " "3"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg3 = static_cast< std::vector< ParameterSample >::difference_type >(val3);
+ try {
+ std_vector_Sl_ParameterSample_Sg____delslice__(arg1,arg2,arg3);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___delitem____SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___delitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___delitem__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ try {
+ std_vector_Sl_ParameterSample_Sg____delitem____SWIG_0(arg1,arg2);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___getitem____SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ PySliceObject *arg2 = (PySliceObject *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___getitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ {
+ if (!PySlice_Check(swig_obj[1])) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector___getitem__" "', argument " "2"" of type '" "PySliceObject *""'");
+ }
+ arg2 = (PySliceObject *) swig_obj[1];
+ }
+ try {
+ result = (std::vector< ParameterSample,std::allocator< ParameterSample > > *)std_vector_Sl_ParameterSample_Sg____getitem____SWIG_0(arg1,arg2);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setitem____SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ PySliceObject *arg2 = (PySliceObject *) 0 ;
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *arg3 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ int res3 = SWIG_OLDOBJ ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___setitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ {
+ if (!PySlice_Check(swig_obj[1])) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector___setitem__" "', argument " "2"" of type '" "PySliceObject *""'");
+ }
+ arg2 = (PySliceObject *) swig_obj[1];
+ }
+ {
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *ptr = (std::vector< ParameterSample,std::allocator< ParameterSample > > *)0;
+ res3 = swig::asptr(swig_obj[2], &ptr);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "ParameterSampleVector___setitem__" "', argument " "3"" of type '" "std::vector< ParameterSample,std::allocator< ParameterSample > > const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector___setitem__" "', argument " "3"" of type '" "std::vector< ParameterSample,std::allocator< ParameterSample > > const &""'");
+ }
+ arg3 = ptr;
+ }
+ try {
+ std_vector_Sl_ParameterSample_Sg____setitem____SWIG_0(arg1,arg2,(std::vector< ParameterSample,std::allocator< ParameterSample > > const &)*arg3);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ if (SWIG_IsNewObj(res3)) delete arg3;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res3)) delete arg3;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setitem____SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ PySliceObject *arg2 = (PySliceObject *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___setitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ {
+ if (!PySlice_Check(swig_obj[1])) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector___setitem__" "', argument " "2"" of type '" "PySliceObject *""'");
+ }
+ arg2 = (PySliceObject *) swig_obj[1];
+ }
+ try {
+ std_vector_Sl_ParameterSample_Sg____setitem____SWIG_1(arg1,arg2);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___delitem____SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ PySliceObject *arg2 = (PySliceObject *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___delitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ {
+ if (!PySlice_Check(swig_obj[1])) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector___delitem__" "', argument " "2"" of type '" "PySliceObject *""'");
+ }
+ arg2 = (PySliceObject *) swig_obj[1];
+ }
+ try {
+ std_vector_Sl_ParameterSample_Sg____delitem____SWIG_1(arg1,arg2);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ } catch(std::invalid_argument &_e) {
+ SWIG_exception_fail(SWIG_ValueError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___delitem__(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector___delitem__", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ _v = PySlice_Check(argv[1]);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___delitem____SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___delitem____SWIG_0(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector___delitem__'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::__delitem__(std::vector< ParameterSample >::difference_type)\n"
+ " std::vector< ParameterSample >::__delitem__(PySliceObject *)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___getitem____SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ std::vector< ParameterSample >::value_type *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___getitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___getitem__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ try {
+ result = (std::vector< ParameterSample >::value_type *) &std_vector_Sl_ParameterSample_Sg____getitem____SWIG_1((std::vector< ParameterSample > const *)arg1,arg2);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ }
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, 0 | 0 );
+ (void)swig::container_owner<swig::traits<std::vector< ParameterSample >::value_type>::category>::back_reference(resultobj, swig_obj[0]);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___getitem__(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector___getitem__", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ _v = PySlice_Check(argv[1]);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___getitem____SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___getitem____SWIG_1(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector___getitem__'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::__getitem__(PySliceObject *)\n"
+ " std::vector< ParameterSample >::__getitem__(std::vector< ParameterSample >::difference_type) const\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setitem____SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::difference_type arg2 ;
+ std::vector< ParameterSample >::value_type *arg3 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ ptrdiff_t val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector___setitem__" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_ptrdiff_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector___setitem__" "', argument " "2"" of type '" "std::vector< ParameterSample >::difference_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::difference_type >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "ParameterSampleVector___setitem__" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector___setitem__" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg3 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp3);
+ try {
+ std_vector_Sl_ParameterSample_Sg____setitem____SWIG_2(arg1,arg2,(ParameterSample const &)*arg3);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ }
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector___setitem__(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[4] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector___setitem__", 0, 3, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ _v = PySlice_Check(argv[1]);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector___setitem____SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ _v = PySlice_Check(argv[1]);
+ }
+ if (_v) {
+ int res = swig::asptr(argv[2], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector___setitem____SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_ptrdiff_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[2], 0, SWIGTYPE_p_ParameterSample, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector___setitem____SWIG_2(self, argc, argv);
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector___setitem__'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::__setitem__(PySliceObject *,std::vector< ParameterSample,std::allocator< ParameterSample > > const &)\n"
+ " std::vector< ParameterSample >::__setitem__(PySliceObject *)\n"
+ " std::vector< ParameterSample >::__setitem__(std::vector< ParameterSample >::difference_type,std::vector< ParameterSample >::value_type const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_pop(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::value_type result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_pop" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ try {
+ result = std_vector_Sl_ParameterSample_Sg__pop(arg1);
+ } catch(std::out_of_range &_e) {
+ SWIG_exception_fail(SWIG_IndexError, (&_e)->what());
+ }
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample >::value_type(static_cast< const std::vector< ParameterSample >::value_type& >(result))), SWIGTYPE_p_ParameterSample, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_append(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::value_type *arg2 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector_append", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_append" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "ParameterSampleVector_append" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_append" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg2 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp2);
+ std_vector_Sl_ParameterSample_Sg__append(arg1,(ParameterSample const &)*arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSampleVector__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **SWIGUNUSEDPARM(swig_obj)) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *result = 0 ;
+
+ if ((nobjs < 0) || (nobjs > 0)) SWIG_fail;
+ result = (std::vector< ParameterSample > *)new std::vector< ParameterSample >();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSampleVector__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = 0 ;
+ int res1 = SWIG_OLDOBJ ;
+ std::vector< ParameterSample > *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ {
+ std::vector< ParameterSample,std::allocator< ParameterSample > > *ptr = (std::vector< ParameterSample,std::allocator< ParameterSample > > *)0;
+ res1 = swig::asptr(swig_obj[0], &ptr);
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "new_ParameterSampleVector" "', argument " "1"" of type '" "std::vector< ParameterSample > const &""'");
+ }
+ if (!ptr) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterSampleVector" "', argument " "1"" of type '" "std::vector< ParameterSample > const &""'");
+ }
+ arg1 = ptr;
+ }
+ result = (std::vector< ParameterSample > *)new std::vector< ParameterSample >((std::vector< ParameterSample > const &)*arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_NEW | 0 );
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return resultobj;
+fail:
+ if (SWIG_IsNewObj(res1)) delete arg1;
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_empty(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ bool result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_empty" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (bool)((std::vector< ParameterSample > const *)arg1)->empty();
+ resultobj = SWIG_From_bool(static_cast< bool >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_size(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::size_type result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_size" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = ((std::vector< ParameterSample > const *)arg1)->size();
+ resultobj = SWIG_From_size_t(static_cast< size_t >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_swap(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample > *arg2 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector_swap", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_swap" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 );
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "ParameterSampleVector_swap" "', argument " "2"" of type '" "std::vector< ParameterSample > &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_swap" "', argument " "2"" of type '" "std::vector< ParameterSample > &""'");
+ }
+ arg2 = reinterpret_cast< std::vector< ParameterSample > * >(argp2);
+ (arg1)->swap(*arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_begin(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::iterator result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_begin" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (arg1)->begin();
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_end(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::iterator result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_end" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (arg1)->end();
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_rbegin(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::reverse_iterator result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_rbegin" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (arg1)->rbegin();
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::reverse_iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_rend(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::reverse_iterator result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_rend" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (arg1)->rend();
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::reverse_iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_clear(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_clear" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ (arg1)->clear();
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_get_allocator(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ SwigValueWrapper< std::allocator< ParameterSample > > result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_get_allocator" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = ((std::vector< ParameterSample > const *)arg1)->get_allocator();
+ resultobj = SWIG_NewPointerObj((new std::vector< ParameterSample >::allocator_type(static_cast< const std::vector< ParameterSample >::allocator_type& >(result))), SWIGTYPE_p_std__allocatorT_ParameterSample_t, SWIG_POINTER_OWN | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSampleVector__SWIG_2(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample >::size_type arg1 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ std::vector< ParameterSample > *result = 0 ;
+
+ if ((nobjs < 1) || (nobjs > 1)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_ParameterSampleVector" "', argument " "1"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg1 = static_cast< std::vector< ParameterSample >::size_type >(val1);
+ result = (std::vector< ParameterSample > *)new std::vector< ParameterSample >(arg1);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_pop_back(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_pop_back" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ (arg1)->pop_back();
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_resize__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::size_type arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_resize" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector_resize" "', argument " "2"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::size_type >(val2);
+ (arg1)->resize(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_erase__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::iterator arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ swig::SwigPyIterator *iter2 = 0 ;
+ int res2 ;
+ std::vector< ParameterSample >::iterator result;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_erase" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], SWIG_as_voidptrptr(&iter2), swig::SwigPyIterator::descriptor(), 0);
+ if (!SWIG_IsOK(res2) || !iter2) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ } else {
+ swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *iter_t = dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter2);
+ if (iter_t) {
+ arg2 = iter_t->get_current();
+ } else {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ }
+ }
+ result = std_vector_Sl_ParameterSample_Sg__erase__SWIG_0(arg1,arg2);
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_erase__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::iterator arg2 ;
+ std::vector< ParameterSample >::iterator arg3 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ swig::SwigPyIterator *iter2 = 0 ;
+ int res2 ;
+ swig::SwigPyIterator *iter3 = 0 ;
+ int res3 ;
+ std::vector< ParameterSample >::iterator result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_erase" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], SWIG_as_voidptrptr(&iter2), swig::SwigPyIterator::descriptor(), 0);
+ if (!SWIG_IsOK(res2) || !iter2) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ } else {
+ swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *iter_t = dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter2);
+ if (iter_t) {
+ arg2 = iter_t->get_current();
+ } else {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ }
+ }
+ res3 = SWIG_ConvertPtr(swig_obj[2], SWIG_as_voidptrptr(&iter3), swig::SwigPyIterator::descriptor(), 0);
+ if (!SWIG_IsOK(res3) || !iter3) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "3"" of type '" "std::vector< ParameterSample >::iterator""'");
+ } else {
+ swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *iter_t = dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter3);
+ if (iter_t) {
+ arg3 = iter_t->get_current();
+ } else {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_erase" "', argument " "3"" of type '" "std::vector< ParameterSample >::iterator""'");
+ }
+ }
+ result = std_vector_Sl_ParameterSample_Sg__erase__SWIG_1(arg1,arg2,arg3);
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_erase(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[4] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector_erase", 0, 3, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ swig::SwigPyIterator *iter = 0;
+ int res = SWIG_ConvertPtr(argv[1], SWIG_as_voidptrptr(&iter), swig::SwigPyIterator::descriptor(), 0);
+ _v = (SWIG_IsOK(res) && iter && (dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter) != 0));
+ if (_v) {
+ return _wrap_ParameterSampleVector_erase__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ swig::SwigPyIterator *iter = 0;
+ int res = SWIG_ConvertPtr(argv[1], SWIG_as_voidptrptr(&iter), swig::SwigPyIterator::descriptor(), 0);
+ _v = (SWIG_IsOK(res) && iter && (dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter) != 0));
+ if (_v) {
+ swig::SwigPyIterator *iter = 0;
+ int res = SWIG_ConvertPtr(argv[2], SWIG_as_voidptrptr(&iter), swig::SwigPyIterator::descriptor(), 0);
+ _v = (SWIG_IsOK(res) && iter && (dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter) != 0));
+ if (_v) {
+ return _wrap_ParameterSampleVector_erase__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector_erase'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::erase(std::vector< ParameterSample >::iterator)\n"
+ " std::vector< ParameterSample >::erase(std::vector< ParameterSample >::iterator,std::vector< ParameterSample >::iterator)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSampleVector__SWIG_3(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample >::size_type arg1 ;
+ std::vector< ParameterSample >::value_type *arg2 = 0 ;
+ size_t val1 ;
+ int ecode1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ std::vector< ParameterSample > *result = 0 ;
+
+ if ((nobjs < 2) || (nobjs > 2)) SWIG_fail;
+ ecode1 = SWIG_AsVal_size_t(swig_obj[0], &val1);
+ if (!SWIG_IsOK(ecode1)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode1), "in method '" "new_ParameterSampleVector" "', argument " "1"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg1 = static_cast< std::vector< ParameterSample >::size_type >(val1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "new_ParameterSampleVector" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "new_ParameterSampleVector" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg2 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp2);
+ result = (std::vector< ParameterSample > *)new std::vector< ParameterSample >(arg1,(std::vector< ParameterSample >::value_type const &)*arg2);
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_NEW | 0 );
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_new_ParameterSampleVector(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[3] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "new_ParameterSampleVector", 0, 2, argv))) SWIG_fail;
+ --argc;
+ if (argc == 0) {
+ return _wrap_new_ParameterSampleVector__SWIG_0(self, argc, argv);
+ }
+ if (argc == 1) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_new_ParameterSampleVector__SWIG_2(self, argc, argv);
+ }
+ }
+ if (argc == 1) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_ParameterSampleVector__SWIG_1(self, argc, argv);
+ }
+ }
+ if (argc == 2) {
+ int _v;
+ {
+ int res = SWIG_AsVal_size_t(argv[0], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[1], 0, SWIGTYPE_p_ParameterSample, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_new_ParameterSampleVector__SWIG_3(self, argc, argv);
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'new_ParameterSampleVector'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::vector()\n"
+ " std::vector< ParameterSample >::vector(std::vector< ParameterSample > const &)\n"
+ " std::vector< ParameterSample >::vector(std::vector< ParameterSample >::size_type)\n"
+ " std::vector< ParameterSample >::vector(std::vector< ParameterSample >::size_type,std::vector< ParameterSample >::value_type const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_push_back(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::value_type *arg2 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ void *argp2 = 0 ;
+ int res2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector_push_back", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_push_back" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], &argp2, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res2)) {
+ SWIG_exception_fail(SWIG_ArgError(res2), "in method '" "ParameterSampleVector_push_back" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp2) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_push_back" "', argument " "2"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg2 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp2);
+ (arg1)->push_back((std::vector< ParameterSample >::value_type const &)*arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_front(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::value_type *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_front" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (std::vector< ParameterSample >::value_type *) &((std::vector< ParameterSample > const *)arg1)->front();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, 0 | 0 );
+ (void)swig::container_owner<swig::traits<std::vector< ParameterSample >::value_type>::category>::back_reference(resultobj, swig_obj[0]);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_back(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::value_type *result = 0 ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_back" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = (std::vector< ParameterSample >::value_type *) &((std::vector< ParameterSample > const *)arg1)->back();
+ resultobj = SWIG_NewPointerObj(SWIG_as_voidptr(result), SWIGTYPE_p_ParameterSample, 0 | 0 );
+ (void)swig::container_owner<swig::traits<std::vector< ParameterSample >::value_type>::category>::back_reference(resultobj, swig_obj[0]);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_assign(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::size_type arg2 ;
+ std::vector< ParameterSample >::value_type *arg3 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ PyObject *swig_obj[3] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector_assign", 3, 3, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_assign" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector_assign" "', argument " "2"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::size_type >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "ParameterSampleVector_assign" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_assign" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg3 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp3);
+ (arg1)->assign(arg2,(std::vector< ParameterSample >::value_type const &)*arg3);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_resize__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::size_type arg2 ;
+ std::vector< ParameterSample >::value_type *arg3 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_resize" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector_resize" "', argument " "2"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::size_type >(val2);
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "ParameterSampleVector_resize" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_resize" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg3 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp3);
+ (arg1)->resize(arg2,(std::vector< ParameterSample >::value_type const &)*arg3);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_resize(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[4] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector_resize", 0, 3, argv))) SWIG_fail;
+ --argc;
+ if (argc == 2) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ return _wrap_ParameterSampleVector_resize__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[1], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[2], 0, SWIGTYPE_p_ParameterSample, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector_resize__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector_resize'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::resize(std::vector< ParameterSample >::size_type)\n"
+ " std::vector< ParameterSample >::resize(std::vector< ParameterSample >::size_type,std::vector< ParameterSample >::value_type const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_insert__SWIG_0(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::iterator arg2 ;
+ std::vector< ParameterSample >::value_type *arg3 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ swig::SwigPyIterator *iter2 = 0 ;
+ int res2 ;
+ void *argp3 = 0 ;
+ int res3 = 0 ;
+ std::vector< ParameterSample >::iterator result;
+
+ if ((nobjs < 3) || (nobjs > 3)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_insert" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], SWIG_as_voidptrptr(&iter2), swig::SwigPyIterator::descriptor(), 0);
+ if (!SWIG_IsOK(res2) || !iter2) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_insert" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ } else {
+ swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *iter_t = dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter2);
+ if (iter_t) {
+ arg2 = iter_t->get_current();
+ } else {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_insert" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ }
+ }
+ res3 = SWIG_ConvertPtr(swig_obj[2], &argp3, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res3)) {
+ SWIG_exception_fail(SWIG_ArgError(res3), "in method '" "ParameterSampleVector_insert" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp3) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_insert" "', argument " "3"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg3 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp3);
+ result = std_vector_Sl_ParameterSample_Sg__insert__SWIG_0(arg1,arg2,(ParameterSample const &)*arg3);
+ resultobj = SWIG_NewPointerObj(swig::make_output_iterator(static_cast< const std::vector< ParameterSample >::iterator & >(result)),
+ swig::SwigPyIterator::descriptor(),SWIG_POINTER_OWN);
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_insert__SWIG_1(PyObject *SWIGUNUSEDPARM(self), Py_ssize_t nobjs, PyObject **swig_obj) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::iterator arg2 ;
+ std::vector< ParameterSample >::size_type arg3 ;
+ std::vector< ParameterSample >::value_type *arg4 = 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ swig::SwigPyIterator *iter2 = 0 ;
+ int res2 ;
+ size_t val3 ;
+ int ecode3 = 0 ;
+ void *argp4 = 0 ;
+ int res4 = 0 ;
+
+ if ((nobjs < 4) || (nobjs > 4)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_insert" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ res2 = SWIG_ConvertPtr(swig_obj[1], SWIG_as_voidptrptr(&iter2), swig::SwigPyIterator::descriptor(), 0);
+ if (!SWIG_IsOK(res2) || !iter2) {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_insert" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ } else {
+ swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *iter_t = dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter2);
+ if (iter_t) {
+ arg2 = iter_t->get_current();
+ } else {
+ SWIG_exception_fail(SWIG_ArgError(SWIG_TypeError), "in method '" "ParameterSampleVector_insert" "', argument " "2"" of type '" "std::vector< ParameterSample >::iterator""'");
+ }
+ }
+ ecode3 = SWIG_AsVal_size_t(swig_obj[2], &val3);
+ if (!SWIG_IsOK(ecode3)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode3), "in method '" "ParameterSampleVector_insert" "', argument " "3"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg3 = static_cast< std::vector< ParameterSample >::size_type >(val3);
+ res4 = SWIG_ConvertPtr(swig_obj[3], &argp4, SWIGTYPE_p_ParameterSample, 0 | 0);
+ if (!SWIG_IsOK(res4)) {
+ SWIG_exception_fail(SWIG_ArgError(res4), "in method '" "ParameterSampleVector_insert" "', argument " "4"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ if (!argp4) {
+ SWIG_exception_fail(SWIG_ValueError, "invalid null reference " "in method '" "ParameterSampleVector_insert" "', argument " "4"" of type '" "std::vector< ParameterSample >::value_type const &""'");
+ }
+ arg4 = reinterpret_cast< std::vector< ParameterSample >::value_type * >(argp4);
+ std_vector_Sl_ParameterSample_Sg__insert__SWIG_1(arg1,arg2,arg3,(ParameterSample const &)*arg4);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_insert(PyObject *self, PyObject *args) {
+ Py_ssize_t argc;
+ PyObject *argv[5] = {
+ 0
+ };
+
+ if (!(argc = SWIG_Python_UnpackTuple(args, "ParameterSampleVector_insert", 0, 4, argv))) SWIG_fail;
+ --argc;
+ if (argc == 3) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ swig::SwigPyIterator *iter = 0;
+ int res = SWIG_ConvertPtr(argv[1], SWIG_as_voidptrptr(&iter), swig::SwigPyIterator::descriptor(), 0);
+ _v = (SWIG_IsOK(res) && iter && (dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter) != 0));
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[2], 0, SWIGTYPE_p_ParameterSample, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector_insert__SWIG_0(self, argc, argv);
+ }
+ }
+ }
+ }
+ if (argc == 4) {
+ int _v;
+ int res = swig::asptr(argv[0], (std::vector< ParameterSample,std::allocator< ParameterSample > >**)(0));
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ swig::SwigPyIterator *iter = 0;
+ int res = SWIG_ConvertPtr(argv[1], SWIG_as_voidptrptr(&iter), swig::SwigPyIterator::descriptor(), 0);
+ _v = (SWIG_IsOK(res) && iter && (dynamic_cast<swig::SwigPyIterator_T<std::vector< ParameterSample >::iterator > *>(iter) != 0));
+ if (_v) {
+ {
+ int res = SWIG_AsVal_size_t(argv[2], NULL);
+ _v = SWIG_CheckState(res);
+ }
+ if (_v) {
+ int res = SWIG_ConvertPtr(argv[3], 0, SWIGTYPE_p_ParameterSample, SWIG_POINTER_NO_NULL | 0);
+ _v = SWIG_CheckState(res);
+ if (_v) {
+ return _wrap_ParameterSampleVector_insert__SWIG_1(self, argc, argv);
+ }
+ }
+ }
+ }
+ }
+
+fail:
+ SWIG_Python_RaiseOrModifyTypeError("Wrong number or type of arguments for overloaded function 'ParameterSampleVector_insert'.\n"
+ " Possible C/C++ prototypes are:\n"
+ " std::vector< ParameterSample >::insert(std::vector< ParameterSample >::iterator,std::vector< ParameterSample >::value_type const &)\n"
+ " std::vector< ParameterSample >::insert(std::vector< ParameterSample >::iterator,std::vector< ParameterSample >::size_type,std::vector< ParameterSample >::value_type const &)\n");
+ return 0;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_reserve(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ std::vector< ParameterSample >::size_type arg2 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ size_t val2 ;
+ int ecode2 = 0 ;
+ PyObject *swig_obj[2] ;
+
+ if (!SWIG_Python_UnpackTuple(args, "ParameterSampleVector_reserve", 2, 2, swig_obj)) SWIG_fail;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_reserve" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ ecode2 = SWIG_AsVal_size_t(swig_obj[1], &val2);
+ if (!SWIG_IsOK(ecode2)) {
+ SWIG_exception_fail(SWIG_ArgError(ecode2), "in method '" "ParameterSampleVector_reserve" "', argument " "2"" of type '" "std::vector< ParameterSample >::size_type""'");
+ }
+ arg2 = static_cast< std::vector< ParameterSample >::size_type >(val2);
+ (arg1)->reserve(arg2);
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_ParameterSampleVector_capacity(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+ std::vector< ParameterSample >::size_type result;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0 | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "ParameterSampleVector_capacity" "', argument " "1"" of type '" "std::vector< ParameterSample > const *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ result = ((std::vector< ParameterSample > const *)arg1)->capacity();
+ resultobj = SWIG_From_size_t(static_cast< size_t >(result));
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *_wrap_delete_ParameterSampleVector(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *resultobj = 0;
+ std::vector< ParameterSample > *arg1 = (std::vector< ParameterSample > *) 0 ;
+ void *argp1 = 0 ;
+ int res1 = 0 ;
+ PyObject *swig_obj[1] ;
+
+ if (!args) SWIG_fail;
+ swig_obj[0] = args;
+ res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_POINTER_DISOWN | 0 );
+ if (!SWIG_IsOK(res1)) {
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "delete_ParameterSampleVector" "', argument " "1"" of type '" "std::vector< ParameterSample > *""'");
+ }
+ arg1 = reinterpret_cast< std::vector< ParameterSample > * >(argp1);
+ delete arg1;
+ resultobj = SWIG_Py_Void();
+ return resultobj;
+fail:
+ return NULL;
+}
+
+
+SWIGINTERN PyObject *ParameterSampleVector_swigregister(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ PyObject *obj;
+ if (!SWIG_Python_UnpackTuple(args, "swigregister", 1, 1, &obj)) return NULL;
+ SWIG_TypeNewClientData(SWIGTYPE_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, SWIG_NewClientData(obj));
+ return SWIG_Py_Void();
+}
+
+SWIGINTERN PyObject *ParameterSampleVector_swiginit(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+ return SWIG_Python_InitShadowInstance(args);
+}
+
static PyMethodDef SwigMethods[] = {
{ "SWIG_PyInstanceMethod_New", SWIG_PyInstanceMethod_New, METH_O, NULL},
{ "delete_SwigPyIterator", _wrap_delete_SwigPyIterator, METH_O, "delete_SwigPyIterator(SwigPyIterator self)"},
@@ -43621,12 +51280,12 @@ static PyMethodDef SwigMethods[] = {
"INodeVisitor_visit(INodeVisitor self, ConstantBackground const * arg2)\n"
"INodeVisitor_visit(INodeVisitor self, ConvolutionDetectorResolution const * arg2)\n"
"INodeVisitor_visit(INodeVisitor self, Crystal const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionCosine const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionGate const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionGaussian const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionLogNormal const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionLorentz const * arg2)\n"
- "INodeVisitor_visit(INodeVisitor self, DistributionTrapezoid const * arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionCosine arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionGate arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionGaussian arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionLogNormal arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionLorentz arg2)\n"
+ "INodeVisitor_visit(INodeVisitor self, DistributionTrapezoid arg2)\n"
"INodeVisitor_visit(INodeVisitor self, FootprintGauss const * arg2)\n"
"INodeVisitor_visit(INodeVisitor self, FootprintSquare const * arg2)\n"
"INodeVisitor_visit(INodeVisitor self, FormFactorAnisoPyramid const * arg2)\n"
@@ -43769,6 +51428,679 @@ static PyMethodDef SwigMethods[] = {
"void VisitNodesPostorder(const INode &node, INodeVisitor &visitor)\n"
"\n"
""},
+ { "IDistribution1D_clone", _wrap_IDistribution1D_clone, METH_O, "\n"
+ "IDistribution1D_clone(IDistribution1D self) -> IDistribution1D\n"
+ "virtual IDistribution1D* IDistribution1D::clone() const =0\n"
+ "\n"
+ ""},
+ { "IDistribution1D_probabilityDensity", _wrap_IDistribution1D_probabilityDensity, METH_VARARGS, "\n"
+ "IDistribution1D_probabilityDensity(IDistribution1D self, double x) -> double\n"
+ "virtual double IDistribution1D::probabilityDensity(double x) const =0\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "IDistribution1D_getMean", _wrap_IDistribution1D_getMean, METH_O, "\n"
+ "IDistribution1D_getMean(IDistribution1D self) -> double\n"
+ "virtual double IDistribution1D::getMean() const =0\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\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()) -> ParameterSampleVector\n"
+ "std::vector< ParameterSample > IDistribution1D::equidistantSamples(size_t nbr_samples, double sigma_factor=0., const RealLimits &limits=RealLimits()) const\n"
+ "\n"
+ "Returns equidistant samples, using intrinsic parameters, weighted with probabilityDensity(). \n"
+ "\n"
+ ""},
+ { "IDistribution1D_equidistantSamplesInRange", _wrap_IDistribution1D_equidistantSamplesInRange, METH_VARARGS, "\n"
+ "IDistribution1D_equidistantSamplesInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> ParameterSampleVector\n"
+ "std::vector< ParameterSample > IDistribution1D::equidistantSamplesInRange(size_t nbr_samples, double xmin, double xmax) const\n"
+ "\n"
+ "Returns equidistant samples from xmin to xmax, weighted with probabilityDensity(). \n"
+ "\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"
+ "\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"
+ ""},
+ { "IDistribution1D_equidistantPointsInRange", _wrap_IDistribution1D_equidistantPointsInRange, METH_VARARGS, "\n"
+ "IDistribution1D_equidistantPointsInRange(IDistribution1D self, size_t nbr_samples, double xmin, double xmax) -> vdouble1d_t\n"
+ "std::vector< double > IDistribution1D::equidistantPointsInRange(size_t nbr_samples, double xmin, double xmax) const\n"
+ "\n"
+ "Returns equidistant interpolation points from xmin to xmax. \n"
+ "\n"
+ ""},
+ { "IDistribution1D_isDelta", _wrap_IDistribution1D_isDelta, METH_O, "\n"
+ "IDistribution1D_isDelta(IDistribution1D self) -> bool\n"
+ "virtual bool IDistribution1D::isDelta() const =0\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "IDistribution1D_setUnits", _wrap_IDistribution1D_setUnits, METH_VARARGS, "\n"
+ "IDistribution1D_setUnits(IDistribution1D self, std::string const & units)\n"
+ "void IDistribution1D::setUnits(const std::string &units)\n"
+ "\n"
+ "Sets distribution units. \n"
+ "\n"
+ ""},
+ { "delete_IDistribution1D", _wrap_delete_IDistribution1D, METH_O, "delete_IDistribution1D(IDistribution1D self)"},
+ { "IDistribution1D_swigregister", IDistribution1D_swigregister, METH_O, NULL},
+ { "new_DistributionGate", _wrap_new_DistributionGate, METH_VARARGS, "\n"
+ "DistributionGate(vdouble1d_t P)\n"
+ "DistributionGate(double min, double max)\n"
+ "new_DistributionGate() -> DistributionGate\n"
+ "DistributionGate::DistributionGate()\n"
+ "\n"
+ ""},
+ { "DistributionGate_clone", _wrap_DistributionGate_clone, METH_O, "\n"
+ "DistributionGate_clone(DistributionGate self) -> DistributionGate\n"
+ "DistributionGate* DistributionGate::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionGate_probabilityDensity", _wrap_DistributionGate_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionGate_probabilityDensity(DistributionGate self, double x) -> double\n"
+ "double DistributionGate::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionGate_getMean", _wrap_DistributionGate_getMean, METH_O, "\n"
+ "DistributionGate_getMean(DistributionGate self) -> double\n"
+ "double DistributionGate::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionGate_getMin", _wrap_DistributionGate_getMin, METH_O, "\n"
+ "DistributionGate_getMin(DistributionGate self) -> double\n"
+ "double DistributionGate::getMin() const\n"
+ "\n"
+ ""},
+ { "DistributionGate_getMax", _wrap_DistributionGate_getMax, METH_O, "\n"
+ "DistributionGate_getMax(DistributionGate self) -> double\n"
+ "double DistributionGate::getMax() const\n"
+ "\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\n"
+ "\n"
+ "Returns list of sample values. \n"
+ "\n"
+ ""},
+ { "DistributionGate_isDelta", _wrap_DistributionGate_isDelta, METH_O, "\n"
+ "DistributionGate_isDelta(DistributionGate self) -> bool\n"
+ "bool DistributionGate::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionGate_accept", _wrap_DistributionGate_accept, METH_VARARGS, "\n"
+ "DistributionGate_accept(DistributionGate self, INodeVisitor visitor)\n"
+ "void DistributionGate::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "delete_DistributionGate", _wrap_delete_DistributionGate, METH_O, "delete_DistributionGate(DistributionGate self)"},
+ { "DistributionGate_swigregister", DistributionGate_swigregister, METH_O, NULL},
+ { "DistributionGate_swiginit", DistributionGate_swiginit, METH_VARARGS, NULL},
+ { "new_DistributionLorentz", _wrap_new_DistributionLorentz, METH_VARARGS, "\n"
+ "DistributionLorentz(vdouble1d_t P)\n"
+ "DistributionLorentz(double mean, double hwhm)\n"
+ "new_DistributionLorentz() -> DistributionLorentz\n"
+ "DistributionLorentz::DistributionLorentz()\n"
+ "\n"
+ ""},
+ { "DistributionLorentz_clone", _wrap_DistributionLorentz_clone, METH_O, "\n"
+ "DistributionLorentz_clone(DistributionLorentz self) -> DistributionLorentz\n"
+ "DistributionLorentz* DistributionLorentz::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionLorentz_probabilityDensity", _wrap_DistributionLorentz_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionLorentz_probabilityDensity(DistributionLorentz self, double x) -> double\n"
+ "double DistributionLorentz::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionLorentz_getMean", _wrap_DistributionLorentz_getMean, METH_O, "\n"
+ "DistributionLorentz_getMean(DistributionLorentz self) -> double\n"
+ "double DistributionLorentz::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionLorentz_getHWHM", _wrap_DistributionLorentz_getHWHM, METH_O, "\n"
+ "DistributionLorentz_getHWHM(DistributionLorentz self) -> double\n"
+ "double DistributionLorentz::getHWHM() const\n"
+ "\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\n"
+ "\n"
+ "generate list of sample values \n"
+ "\n"
+ ""},
+ { "DistributionLorentz_isDelta", _wrap_DistributionLorentz_isDelta, METH_O, "\n"
+ "DistributionLorentz_isDelta(DistributionLorentz self) -> bool\n"
+ "bool DistributionLorentz::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionLorentz_accept", _wrap_DistributionLorentz_accept, METH_VARARGS, "\n"
+ "DistributionLorentz_accept(DistributionLorentz self, INodeVisitor visitor)\n"
+ "void DistributionLorentz::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "delete_DistributionLorentz", _wrap_delete_DistributionLorentz, METH_O, "delete_DistributionLorentz(DistributionLorentz self)"},
+ { "DistributionLorentz_swigregister", DistributionLorentz_swigregister, METH_O, NULL},
+ { "DistributionLorentz_swiginit", DistributionLorentz_swiginit, METH_VARARGS, NULL},
+ { "new_DistributionGaussian", _wrap_new_DistributionGaussian, METH_VARARGS, "\n"
+ "DistributionGaussian(vdouble1d_t P)\n"
+ "DistributionGaussian(double mean, double std_dev)\n"
+ "new_DistributionGaussian() -> DistributionGaussian\n"
+ "DistributionGaussian::DistributionGaussian()\n"
+ "\n"
+ ""},
+ { "DistributionGaussian_clone", _wrap_DistributionGaussian_clone, METH_O, "\n"
+ "DistributionGaussian_clone(DistributionGaussian self) -> DistributionGaussian\n"
+ "DistributionGaussian* DistributionGaussian::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionGaussian_probabilityDensity", _wrap_DistributionGaussian_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionGaussian_probabilityDensity(DistributionGaussian self, double x) -> double\n"
+ "double DistributionGaussian::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionGaussian_getMean", _wrap_DistributionGaussian_getMean, METH_O, "\n"
+ "DistributionGaussian_getMean(DistributionGaussian self) -> double\n"
+ "double DistributionGaussian::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionGaussian_getStdDev", _wrap_DistributionGaussian_getStdDev, METH_O, "\n"
+ "DistributionGaussian_getStdDev(DistributionGaussian self) -> double\n"
+ "double DistributionGaussian::getStdDev() const\n"
+ "\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\n"
+ "\n"
+ "generate list of sample values \n"
+ "\n"
+ ""},
+ { "DistributionGaussian_isDelta", _wrap_DistributionGaussian_isDelta, METH_O, "\n"
+ "DistributionGaussian_isDelta(DistributionGaussian self) -> bool\n"
+ "bool DistributionGaussian::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionGaussian_accept", _wrap_DistributionGaussian_accept, METH_VARARGS, "\n"
+ "DistributionGaussian_accept(DistributionGaussian self, INodeVisitor visitor)\n"
+ "void DistributionGaussian::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "delete_DistributionGaussian", _wrap_delete_DistributionGaussian, METH_O, "delete_DistributionGaussian(DistributionGaussian self)"},
+ { "DistributionGaussian_swigregister", DistributionGaussian_swigregister, METH_O, NULL},
+ { "DistributionGaussian_swiginit", DistributionGaussian_swiginit, METH_VARARGS, NULL},
+ { "new_DistributionLogNormal", _wrap_new_DistributionLogNormal, METH_VARARGS, "\n"
+ "DistributionLogNormal(vdouble1d_t P)\n"
+ "new_DistributionLogNormal(double median, double scale_param) -> DistributionLogNormal\n"
+ "DistributionLogNormal::DistributionLogNormal()=delete\n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_clone", _wrap_DistributionLogNormal_clone, METH_O, "\n"
+ "DistributionLogNormal_clone(DistributionLogNormal self) -> DistributionLogNormal\n"
+ "DistributionLogNormal* DistributionLogNormal::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_probabilityDensity", _wrap_DistributionLogNormal_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionLogNormal_probabilityDensity(DistributionLogNormal self, double x) -> double\n"
+ "double DistributionLogNormal::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_getMean", _wrap_DistributionLogNormal_getMean, METH_O, "\n"
+ "DistributionLogNormal_getMean(DistributionLogNormal self) -> double\n"
+ "double DistributionLogNormal::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_getMedian", _wrap_DistributionLogNormal_getMedian, METH_O, "\n"
+ "DistributionLogNormal_getMedian(DistributionLogNormal self) -> double\n"
+ "double DistributionLogNormal::getMedian() const\n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_getScalePar", _wrap_DistributionLogNormal_getScalePar, METH_O, "\n"
+ "DistributionLogNormal_getScalePar(DistributionLogNormal self) -> double\n"
+ "double DistributionLogNormal::getScalePar() const\n"
+ "\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\n"
+ "\n"
+ "generate list of sample values \n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_isDelta", _wrap_DistributionLogNormal_isDelta, METH_O, "\n"
+ "DistributionLogNormal_isDelta(DistributionLogNormal self) -> bool\n"
+ "bool DistributionLogNormal::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_accept", _wrap_DistributionLogNormal_accept, METH_VARARGS, "\n"
+ "DistributionLogNormal_accept(DistributionLogNormal self, INodeVisitor visitor)\n"
+ "void DistributionLogNormal::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "DistributionLogNormal_setUnits", _wrap_DistributionLogNormal_setUnits, METH_VARARGS, "\n"
+ "DistributionLogNormal_setUnits(DistributionLogNormal self, std::string const & units)\n"
+ "void DistributionLogNormal::setUnits(const std::string &units)\n"
+ "\n"
+ "Sets distribution units. \n"
+ "\n"
+ ""},
+ { "delete_DistributionLogNormal", _wrap_delete_DistributionLogNormal, METH_O, "delete_DistributionLogNormal(DistributionLogNormal self)"},
+ { "DistributionLogNormal_swigregister", DistributionLogNormal_swigregister, METH_O, NULL},
+ { "DistributionLogNormal_swiginit", DistributionLogNormal_swiginit, METH_VARARGS, NULL},
+ { "new_DistributionCosine", _wrap_new_DistributionCosine, METH_VARARGS, "\n"
+ "DistributionCosine(vdouble1d_t P)\n"
+ "DistributionCosine(double mean, double sigma)\n"
+ "new_DistributionCosine() -> DistributionCosine\n"
+ "DistributionCosine::DistributionCosine()\n"
+ "\n"
+ ""},
+ { "DistributionCosine_clone", _wrap_DistributionCosine_clone, METH_O, "\n"
+ "DistributionCosine_clone(DistributionCosine self) -> DistributionCosine\n"
+ "DistributionCosine* DistributionCosine::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionCosine_probabilityDensity", _wrap_DistributionCosine_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionCosine_probabilityDensity(DistributionCosine self, double x) -> double\n"
+ "double DistributionCosine::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionCosine_getMean", _wrap_DistributionCosine_getMean, METH_O, "\n"
+ "DistributionCosine_getMean(DistributionCosine self) -> double\n"
+ "double DistributionCosine::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionCosine_getSigma", _wrap_DistributionCosine_getSigma, METH_O, "\n"
+ "DistributionCosine_getSigma(DistributionCosine self) -> double\n"
+ "double DistributionCosine::getSigma() const\n"
+ "\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\n"
+ "\n"
+ "generate list of sample values \n"
+ "\n"
+ ""},
+ { "DistributionCosine_isDelta", _wrap_DistributionCosine_isDelta, METH_O, "\n"
+ "DistributionCosine_isDelta(DistributionCosine self) -> bool\n"
+ "bool DistributionCosine::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionCosine_accept", _wrap_DistributionCosine_accept, METH_VARARGS, "\n"
+ "DistributionCosine_accept(DistributionCosine self, INodeVisitor visitor)\n"
+ "void DistributionCosine::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "delete_DistributionCosine", _wrap_delete_DistributionCosine, METH_O, "delete_DistributionCosine(DistributionCosine self)"},
+ { "DistributionCosine_swigregister", DistributionCosine_swigregister, METH_O, NULL},
+ { "DistributionCosine_swiginit", DistributionCosine_swiginit, METH_VARARGS, NULL},
+ { "new_DistributionTrapezoid", _wrap_new_DistributionTrapezoid, METH_VARARGS, "\n"
+ "DistributionTrapezoid(vdouble1d_t P)\n"
+ "DistributionTrapezoid(double center, double left, double middle, double right)\n"
+ "new_DistributionTrapezoid() -> DistributionTrapezoid\n"
+ "DistributionTrapezoid::DistributionTrapezoid()\n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_clone", _wrap_DistributionTrapezoid_clone, METH_O, "\n"
+ "DistributionTrapezoid_clone(DistributionTrapezoid self) -> DistributionTrapezoid\n"
+ "DistributionTrapezoid* DistributionTrapezoid::clone() const final\n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_probabilityDensity", _wrap_DistributionTrapezoid_probabilityDensity, METH_VARARGS, "\n"
+ "DistributionTrapezoid_probabilityDensity(DistributionTrapezoid self, double x) -> double\n"
+ "double DistributionTrapezoid::probabilityDensity(double x) const final\n"
+ "\n"
+ "Returns the distribution-specific probability density for value x. \n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_getMean", _wrap_DistributionTrapezoid_getMean, METH_O, "\n"
+ "DistributionTrapezoid_getMean(DistributionTrapezoid self) -> double\n"
+ "double DistributionTrapezoid::getMean() const final\n"
+ "\n"
+ "Returns the distribution-specific mean. \n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_getLeftWidth", _wrap_DistributionTrapezoid_getLeftWidth, METH_O, "\n"
+ "DistributionTrapezoid_getLeftWidth(DistributionTrapezoid self) -> double\n"
+ "double DistributionTrapezoid::getLeftWidth() const\n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_getMiddleWidth", _wrap_DistributionTrapezoid_getMiddleWidth, METH_O, "\n"
+ "DistributionTrapezoid_getMiddleWidth(DistributionTrapezoid self) -> double\n"
+ "double DistributionTrapezoid::getMiddleWidth() const\n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_getRightWidth", _wrap_DistributionTrapezoid_getRightWidth, METH_O, "\n"
+ "DistributionTrapezoid_getRightWidth(DistributionTrapezoid self) -> double\n"
+ "double DistributionTrapezoid::getRightWidth() const\n"
+ "\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\n"
+ "\n"
+ "generate list of sample values \n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_isDelta", _wrap_DistributionTrapezoid_isDelta, METH_O, "\n"
+ "DistributionTrapezoid_isDelta(DistributionTrapezoid self) -> bool\n"
+ "bool DistributionTrapezoid::isDelta() const final\n"
+ "\n"
+ "Returns true if the distribution is in the limit case of a Dirac delta distribution. \n"
+ "\n"
+ ""},
+ { "DistributionTrapezoid_accept", _wrap_DistributionTrapezoid_accept, METH_VARARGS, "\n"
+ "DistributionTrapezoid_accept(DistributionTrapezoid self, INodeVisitor visitor)\n"
+ "void DistributionTrapezoid::accept(INodeVisitor *visitor) const final\n"
+ "\n"
+ "Calls the INodeVisitor's visit method. \n"
+ "\n"
+ ""},
+ { "delete_DistributionTrapezoid", _wrap_delete_DistributionTrapezoid, METH_O, "delete_DistributionTrapezoid(DistributionTrapezoid self)"},
+ { "DistributionTrapezoid_swigregister", DistributionTrapezoid_swigregister, METH_O, NULL},
+ { "DistributionTrapezoid_swiginit", DistributionTrapezoid_swiginit, METH_VARARGS, NULL},
+ { "new_ParameterDistribution", _wrap_new_ParameterDistribution, METH_VARARGS, "\n"
+ "ParameterDistribution(std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double sigma_factor=0.0, RealLimits const & limits=RealLimits())\n"
+ "ParameterDistribution(std::string const & par_name, IDistribution1D distribution, size_t nbr_samples, double xmin, double xmax)\n"
+ "new_ParameterDistribution(ParameterDistribution other) -> ParameterDistribution\n"
+ "ParameterDistribution::ParameterDistribution(const ParameterDistribution &other)\n"
+ "\n"
+ ""},
+ { "delete_ParameterDistribution", _wrap_delete_ParameterDistribution, METH_O, "\n"
+ "delete_ParameterDistribution(ParameterDistribution self)\n"
+ "ParameterDistribution::~ParameterDistribution()\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_linkParameter", _wrap_ParameterDistribution_linkParameter, METH_VARARGS, "\n"
+ "ParameterDistribution_linkParameter(ParameterDistribution self, std::string par_name) -> ParameterDistribution\n"
+ "ParameterDistribution & ParameterDistribution::linkParameter(std::string par_name)\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getMainParameterName", _wrap_ParameterDistribution_getMainParameterName, METH_O, "\n"
+ "ParameterDistribution_getMainParameterName(ParameterDistribution self) -> std::string\n"
+ "std::string ParameterDistribution::getMainParameterName() const\n"
+ "\n"
+ "get the main parameter's name \n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getNbrSamples", _wrap_ParameterDistribution_getNbrSamples, METH_O, "\n"
+ "ParameterDistribution_getNbrSamples(ParameterDistribution self) -> size_t\n"
+ "size_t ParameterDistribution::getNbrSamples() const\n"
+ "\n"
+ "get number of samples for this distribution \n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getSigmaFactor", _wrap_ParameterDistribution_getSigmaFactor, METH_O, "\n"
+ "ParameterDistribution_getSigmaFactor(ParameterDistribution self) -> double\n"
+ "double ParameterDistribution::getSigmaFactor() const\n"
+ "\n"
+ "get the sigma factor \n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getDistribution", _wrap_ParameterDistribution_getDistribution, METH_VARARGS, "\n"
+ "ParameterDistribution_getDistribution(ParameterDistribution self) -> IDistribution1D\n"
+ "ParameterDistribution_getDistribution(ParameterDistribution self) -> IDistribution1D\n"
+ "IDistribution1D * ParameterDistribution::getDistribution()\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_generateSamples", _wrap_ParameterDistribution_generateSamples, METH_O, "\n"
+ "ParameterDistribution_generateSamples(ParameterDistribution self) -> ParameterSampleVector\n"
+ "std::vector< ParameterSample > ParameterDistribution::generateSamples() const\n"
+ "\n"
+ "generate list of sampled values with their weight \n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getLinkedParameterNames", _wrap_ParameterDistribution_getLinkedParameterNames, METH_O, "\n"
+ "ParameterDistribution_getLinkedParameterNames(ParameterDistribution self) -> vector_string_t\n"
+ "std::vector<std::string> ParameterDistribution::getLinkedParameterNames() const\n"
+ "\n"
+ "get list of linked parameter names \n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getLimits", _wrap_ParameterDistribution_getLimits, METH_O, "\n"
+ "ParameterDistribution_getLimits(ParameterDistribution self) -> RealLimits\n"
+ "RealLimits ParameterDistribution::getLimits() const\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getMinValue", _wrap_ParameterDistribution_getMinValue, METH_O, "\n"
+ "ParameterDistribution_getMinValue(ParameterDistribution self) -> double\n"
+ "double ParameterDistribution::getMinValue() const\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_getMaxValue", _wrap_ParameterDistribution_getMaxValue, METH_O, "\n"
+ "ParameterDistribution_getMaxValue(ParameterDistribution self) -> double\n"
+ "double ParameterDistribution::getMaxValue() const\n"
+ "\n"
+ ""},
+ { "ParameterDistribution_swigregister", ParameterDistribution_swigregister, METH_O, NULL},
+ { "ParameterDistribution_swiginit", ParameterDistribution_swiginit, METH_VARARGS, NULL},
+ { "new_RangedDistributionGate", _wrap_new_RangedDistributionGate, METH_VARARGS, "\n"
+ "RangedDistributionGate()\n"
+ "RangedDistributionGate(size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless())\n"
+ "new_RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGate\n"
+ "RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max)\n"
+ "\n"
+ "Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf). \n"
+ "\n"
+ ""},
+ { "RangedDistributionGate_clone", _wrap_RangedDistributionGate_clone, METH_O, "\n"
+ "RangedDistributionGate_clone(RangedDistributionGate self) -> RangedDistributionGate\n"
+ "RangedDistributionGate * RangedDistributionGate::clone() const override\n"
+ "\n"
+ ""},
+ { "delete_RangedDistributionGate", _wrap_delete_RangedDistributionGate, METH_O, "\n"
+ "delete_RangedDistributionGate(RangedDistributionGate self)\n"
+ "RangedDistributionGate::~RangedDistributionGate() override=default\n"
+ "\n"
+ ""},
+ { "RangedDistributionGate_swigregister", RangedDistributionGate_swigregister, METH_O, NULL},
+ { "RangedDistributionGate_swiginit", RangedDistributionGate_swiginit, METH_VARARGS, NULL},
+ { "new_RangedDistributionLorentz", _wrap_new_RangedDistributionLorentz, METH_VARARGS, "\n"
+ "RangedDistributionLorentz()\n"
+ "RangedDistributionLorentz(size_t n_samples, double hwhm_factor, RealLimits const & limits=RealLimits::limitless())\n"
+ "new_RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max) -> RangedDistributionLorentz\n"
+ "RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max)\n"
+ "\n"
+ "Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, hwhm_factor = 2.0, while the limits are (-inf, +inf). \n"
+ "\n"
+ ""},
+ { "RangedDistributionLorentz_clone", _wrap_RangedDistributionLorentz_clone, METH_O, "\n"
+ "RangedDistributionLorentz_clone(RangedDistributionLorentz self) -> RangedDistributionLorentz\n"
+ "RangedDistributionLorentz * RangedDistributionLorentz::clone() const override\n"
+ "\n"
+ ""},
+ { "delete_RangedDistributionLorentz", _wrap_delete_RangedDistributionLorentz, METH_O, "\n"
+ "delete_RangedDistributionLorentz(RangedDistributionLorentz self)\n"
+ "RangedDistributionLorentz::~RangedDistributionLorentz() override=default\n"
+ "\n"
+ ""},
+ { "RangedDistributionLorentz_swigregister", RangedDistributionLorentz_swigregister, METH_O, NULL},
+ { "RangedDistributionLorentz_swiginit", RangedDistributionLorentz_swiginit, METH_VARARGS, NULL},
+ { "new_RangedDistributionGaussian", _wrap_new_RangedDistributionGaussian, METH_VARARGS, "\n"
+ "RangedDistributionGaussian()\n"
+ "RangedDistributionGaussian(size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless())\n"
+ "new_RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionGaussian\n"
+ "RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max)\n"
+ "\n"
+ "Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf). \n"
+ "\n"
+ ""},
+ { "RangedDistributionGaussian_clone", _wrap_RangedDistributionGaussian_clone, METH_O, "\n"
+ "RangedDistributionGaussian_clone(RangedDistributionGaussian self) -> RangedDistributionGaussian\n"
+ "RangedDistributionGaussian * RangedDistributionGaussian::clone() const override\n"
+ "\n"
+ ""},
+ { "delete_RangedDistributionGaussian", _wrap_delete_RangedDistributionGaussian, METH_O, "\n"
+ "delete_RangedDistributionGaussian(RangedDistributionGaussian self)\n"
+ "RangedDistributionGaussian::~RangedDistributionGaussian() override=default\n"
+ "\n"
+ ""},
+ { "RangedDistributionGaussian_swigregister", RangedDistributionGaussian_swigregister, METH_O, NULL},
+ { "RangedDistributionGaussian_swiginit", RangedDistributionGaussian_swiginit, METH_VARARGS, NULL},
+ { "new_RangedDistributionLogNormal", _wrap_new_RangedDistributionLogNormal, METH_VARARGS, "\n"
+ "RangedDistributionLogNormal()\n"
+ "RangedDistributionLogNormal(size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless())\n"
+ "new_RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionLogNormal\n"
+ "RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max)\n"
+ "\n"
+ "Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf). \n"
+ "\n"
+ ""},
+ { "RangedDistributionLogNormal_clone", _wrap_RangedDistributionLogNormal_clone, METH_O, "\n"
+ "RangedDistributionLogNormal_clone(RangedDistributionLogNormal self) -> RangedDistributionLogNormal\n"
+ "RangedDistributionLogNormal * RangedDistributionLogNormal::clone() const override\n"
+ "\n"
+ ""},
+ { "delete_RangedDistributionLogNormal", _wrap_delete_RangedDistributionLogNormal, METH_O, "\n"
+ "delete_RangedDistributionLogNormal(RangedDistributionLogNormal self)\n"
+ "RangedDistributionLogNormal::~RangedDistributionLogNormal() override=default\n"
+ "\n"
+ ""},
+ { "RangedDistributionLogNormal_swigregister", RangedDistributionLogNormal_swigregister, METH_O, NULL},
+ { "RangedDistributionLogNormal_swiginit", RangedDistributionLogNormal_swiginit, METH_VARARGS, NULL},
+ { "new_RangedDistributionCosine", _wrap_new_RangedDistributionCosine, METH_VARARGS, "\n"
+ "RangedDistributionCosine()\n"
+ "RangedDistributionCosine(size_t n_samples, double sigma_factor, RealLimits const & limits=RealLimits::limitless())\n"
+ "new_RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max) -> RangedDistributionCosine\n"
+ "RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max)\n"
+ "\n"
+ "Initializes Ranged distribution with given number of samples, sigma factor (range in standard deviations to take into account during sample generation) and limits (either RealLimits object or just min and max limits). By default n_samples = 5, sigma_factor = 2.0, while the limits are (-inf, +inf). \n"
+ "\n"
+ ""},
+ { "RangedDistributionCosine_clone", _wrap_RangedDistributionCosine_clone, METH_O, "\n"
+ "RangedDistributionCosine_clone(RangedDistributionCosine self) -> RangedDistributionCosine\n"
+ "RangedDistributionCosine * RangedDistributionCosine::clone() const override\n"
+ "\n"
+ ""},
+ { "delete_RangedDistributionCosine", _wrap_delete_RangedDistributionCosine, METH_O, "\n"
+ "delete_RangedDistributionCosine(RangedDistributionCosine self)\n"
+ "RangedDistributionCosine::~RangedDistributionCosine() override=default\n"
+ "\n"
+ ""},
+ { "RangedDistributionCosine_swigregister", RangedDistributionCosine_swigregister, METH_O, NULL},
+ { "RangedDistributionCosine_swiginit", RangedDistributionCosine_swiginit, METH_VARARGS, NULL},
+ { "new_ParameterSample", _wrap_new_ParameterSample, METH_VARARGS, "\n"
+ "ParameterSample(double _value=0., double _weight=1.)\n"
+ "ParameterSample::ParameterSample(double _value=0., double _weight=1.)\n"
+ "\n"
+ ""},
+ { "ParameterSample_value_set", _wrap_ParameterSample_value_set, METH_VARARGS, "ParameterSample_value_set(ParameterSample self, double value)"},
+ { "ParameterSample_value_get", _wrap_ParameterSample_value_get, METH_O, "ParameterSample_value_get(ParameterSample self) -> double"},
+ { "ParameterSample_weight_set", _wrap_ParameterSample_weight_set, METH_VARARGS, "ParameterSample_weight_set(ParameterSample self, double weight)"},
+ { "ParameterSample_weight_get", _wrap_ParameterSample_weight_get, METH_O, "ParameterSample_weight_get(ParameterSample self) -> double"},
+ { "delete_ParameterSample", _wrap_delete_ParameterSample, METH_O, "delete_ParameterSample(ParameterSample self)"},
+ { "ParameterSample_swigregister", ParameterSample_swigregister, METH_O, NULL},
+ { "ParameterSample_swiginit", ParameterSample_swiginit, METH_VARARGS, NULL},
+ { "ParameterSampleVector_iterator", _wrap_ParameterSampleVector_iterator, METH_O, "ParameterSampleVector_iterator(ParameterSampleVector self) -> SwigPyIterator"},
+ { "ParameterSampleVector___nonzero__", _wrap_ParameterSampleVector___nonzero__, METH_O, "ParameterSampleVector___nonzero__(ParameterSampleVector self) -> bool"},
+ { "ParameterSampleVector___bool__", _wrap_ParameterSampleVector___bool__, METH_O, "ParameterSampleVector___bool__(ParameterSampleVector self) -> bool"},
+ { "ParameterSampleVector___len__", _wrap_ParameterSampleVector___len__, METH_O, "ParameterSampleVector___len__(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"},
+ { "ParameterSampleVector___getslice__", _wrap_ParameterSampleVector___getslice__, METH_VARARGS, "ParameterSampleVector___getslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j) -> ParameterSampleVector"},
+ { "ParameterSampleVector___setslice__", _wrap_ParameterSampleVector___setslice__, METH_VARARGS, "\n"
+ "ParameterSampleVector___setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)\n"
+ "ParameterSampleVector___setslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j, ParameterSampleVector v)\n"
+ ""},
+ { "ParameterSampleVector___delslice__", _wrap_ParameterSampleVector___delslice__, METH_VARARGS, "ParameterSampleVector___delslice__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, std::vector< ParameterSample >::difference_type j)"},
+ { "ParameterSampleVector___delitem__", _wrap_ParameterSampleVector___delitem__, METH_VARARGS, "\n"
+ "ParameterSampleVector___delitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i)\n"
+ "ParameterSampleVector___delitem__(ParameterSampleVector self, PySliceObject * slice)\n"
+ ""},
+ { "ParameterSampleVector___getitem__", _wrap_ParameterSampleVector___getitem__, METH_VARARGS, "\n"
+ "ParameterSampleVector___getitem__(ParameterSampleVector self, PySliceObject * slice) -> ParameterSampleVector\n"
+ "ParameterSampleVector___getitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i) -> ParameterSample\n"
+ ""},
+ { "ParameterSampleVector___setitem__", _wrap_ParameterSampleVector___setitem__, METH_VARARGS, "\n"
+ "ParameterSampleVector___setitem__(ParameterSampleVector self, PySliceObject * slice, ParameterSampleVector v)\n"
+ "ParameterSampleVector___setitem__(ParameterSampleVector self, PySliceObject * slice)\n"
+ "ParameterSampleVector___setitem__(ParameterSampleVector self, std::vector< ParameterSample >::difference_type i, ParameterSample x)\n"
+ ""},
+ { "ParameterSampleVector_pop", _wrap_ParameterSampleVector_pop, METH_O, "ParameterSampleVector_pop(ParameterSampleVector self) -> ParameterSample"},
+ { "ParameterSampleVector_append", _wrap_ParameterSampleVector_append, METH_VARARGS, "ParameterSampleVector_append(ParameterSampleVector self, ParameterSample x)"},
+ { "ParameterSampleVector_empty", _wrap_ParameterSampleVector_empty, METH_O, "ParameterSampleVector_empty(ParameterSampleVector self) -> bool"},
+ { "ParameterSampleVector_size", _wrap_ParameterSampleVector_size, METH_O, "ParameterSampleVector_size(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"},
+ { "ParameterSampleVector_swap", _wrap_ParameterSampleVector_swap, METH_VARARGS, "ParameterSampleVector_swap(ParameterSampleVector self, ParameterSampleVector v)"},
+ { "ParameterSampleVector_begin", _wrap_ParameterSampleVector_begin, METH_O, "ParameterSampleVector_begin(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"},
+ { "ParameterSampleVector_end", _wrap_ParameterSampleVector_end, METH_O, "ParameterSampleVector_end(ParameterSampleVector self) -> std::vector< ParameterSample >::iterator"},
+ { "ParameterSampleVector_rbegin", _wrap_ParameterSampleVector_rbegin, METH_O, "ParameterSampleVector_rbegin(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"},
+ { "ParameterSampleVector_rend", _wrap_ParameterSampleVector_rend, METH_O, "ParameterSampleVector_rend(ParameterSampleVector self) -> std::vector< ParameterSample >::reverse_iterator"},
+ { "ParameterSampleVector_clear", _wrap_ParameterSampleVector_clear, METH_O, "ParameterSampleVector_clear(ParameterSampleVector self)"},
+ { "ParameterSampleVector_get_allocator", _wrap_ParameterSampleVector_get_allocator, METH_O, "ParameterSampleVector_get_allocator(ParameterSampleVector self) -> std::vector< ParameterSample >::allocator_type"},
+ { "ParameterSampleVector_pop_back", _wrap_ParameterSampleVector_pop_back, METH_O, "ParameterSampleVector_pop_back(ParameterSampleVector self)"},
+ { "ParameterSampleVector_erase", _wrap_ParameterSampleVector_erase, METH_VARARGS, "\n"
+ "ParameterSampleVector_erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos) -> std::vector< ParameterSample >::iterator\n"
+ "ParameterSampleVector_erase(ParameterSampleVector self, std::vector< ParameterSample >::iterator first, std::vector< ParameterSample >::iterator last) -> std::vector< ParameterSample >::iterator\n"
+ ""},
+ { "new_ParameterSampleVector", _wrap_new_ParameterSampleVector, METH_VARARGS, "\n"
+ "ParameterSampleVector()\n"
+ "ParameterSampleVector(ParameterSampleVector other)\n"
+ "ParameterSampleVector(std::vector< ParameterSample >::size_type size)\n"
+ "new_ParameterSampleVector(std::vector< ParameterSample >::size_type size, ParameterSample value) -> ParameterSampleVector\n"
+ ""},
+ { "ParameterSampleVector_push_back", _wrap_ParameterSampleVector_push_back, METH_VARARGS, "ParameterSampleVector_push_back(ParameterSampleVector self, ParameterSample x)"},
+ { "ParameterSampleVector_front", _wrap_ParameterSampleVector_front, METH_O, "ParameterSampleVector_front(ParameterSampleVector self) -> ParameterSample"},
+ { "ParameterSampleVector_back", _wrap_ParameterSampleVector_back, METH_O, "ParameterSampleVector_back(ParameterSampleVector self) -> ParameterSample"},
+ { "ParameterSampleVector_assign", _wrap_ParameterSampleVector_assign, METH_VARARGS, "ParameterSampleVector_assign(ParameterSampleVector self, std::vector< ParameterSample >::size_type n, ParameterSample x)"},
+ { "ParameterSampleVector_resize", _wrap_ParameterSampleVector_resize, METH_VARARGS, "\n"
+ "ParameterSampleVector_resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size)\n"
+ "ParameterSampleVector_resize(ParameterSampleVector self, std::vector< ParameterSample >::size_type new_size, ParameterSample x)\n"
+ ""},
+ { "ParameterSampleVector_insert", _wrap_ParameterSampleVector_insert, METH_VARARGS, "\n"
+ "ParameterSampleVector_insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, ParameterSample x) -> std::vector< ParameterSample >::iterator\n"
+ "ParameterSampleVector_insert(ParameterSampleVector self, std::vector< ParameterSample >::iterator pos, std::vector< ParameterSample >::size_type n, ParameterSample x)\n"
+ ""},
+ { "ParameterSampleVector_reserve", _wrap_ParameterSampleVector_reserve, METH_VARARGS, "ParameterSampleVector_reserve(ParameterSampleVector self, std::vector< ParameterSample >::size_type n)"},
+ { "ParameterSampleVector_capacity", _wrap_ParameterSampleVector_capacity, METH_O, "ParameterSampleVector_capacity(ParameterSampleVector self) -> std::vector< ParameterSample >::size_type"},
+ { "delete_ParameterSampleVector", _wrap_delete_ParameterSampleVector, METH_O, "delete_ParameterSampleVector(ParameterSampleVector self)"},
+ { "ParameterSampleVector_swigregister", ParameterSampleVector_swigregister, METH_O, NULL},
+ { "ParameterSampleVector_swiginit", ParameterSampleVector_swiginit, METH_VARARGS, NULL},
{ NULL, NULL, 0, NULL }
};
@@ -43782,12 +52114,129 @@ static PyMethodDef SwigMethods_proxydocs[] = {
static void *_p_RealParameterTo_p_IParameterT_double_t(void *x, int *SWIGUNUSEDPARM(newmemory)) {
return (void *)((IParameter< double > *) ((RealParameter *) x));
}
+static void *_p_DistributionCosineTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionCosine *) x));
+}
static void *_p_INodeTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
return (void *)((IParameterized *) ((INode *) x));
}
+static void *_p_DistributionLorentzTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionLorentz *) x));
+}
+static void *_p_ParameterDistributionTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) ((ParameterDistribution *) x));
+}
+static void *_p_DistributionGaussianTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionGaussian *) x));
+}
+static void *_p_IDistribution1DTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *) ((IDistribution1D *) x));
+}
+static void *_p_DistributionGateTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionGate *) x));
+}
+static void *_p_DistributionTrapezoidTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionTrapezoid *) x));
+}
+static void *_p_DistributionLogNormalTo_p_IParameterized(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IParameterized *) (INode *)(IDistribution1D *) ((DistributionLogNormal *) x));
+}
+static void *_p_RangedDistributionCosineTo_p_RangedDistribution(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((RangedDistribution *) ((RangedDistributionCosine *) x));
+}
+static void *_p_RangedDistributionLorentzTo_p_RangedDistribution(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((RangedDistribution *) ((RangedDistributionLorentz *) x));
+}
+static void *_p_RangedDistributionGaussianTo_p_RangedDistribution(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((RangedDistribution *) ((RangedDistributionGaussian *) x));
+}
+static void *_p_RangedDistributionGateTo_p_RangedDistribution(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((RangedDistribution *) ((RangedDistributionGate *) x));
+}
+static void *_p_RangedDistributionLogNormalTo_p_RangedDistribution(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((RangedDistribution *) ((RangedDistributionLogNormal *) x));
+}
+static void *_p_RangedDistributionGateTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (RangedDistribution *) ((RangedDistributionGate *) x));
+}
+static void *_p_DistributionGateTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionGate *) x));
+}
+static void *_p_IDistribution1DTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) ((IDistribution1D *) x));
+}
+static void *_p_DistributionTrapezoidTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionTrapezoid *) x));
+}
+static void *_p_RangedDistributionGaussianTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (RangedDistribution *) ((RangedDistributionGaussian *) x));
+}
+static void *_p_DistributionGaussianTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionGaussian *) x));
+}
static void *_p_ParameterPoolTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
return (void *)((ICloneable *) ((ParameterPool *) x));
}
+static void *_p_RangedDistributionCosineTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (RangedDistribution *) ((RangedDistributionCosine *) x));
+}
+static void *_p_DistributionCosineTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionCosine *) x));
+}
+static void *_p_RangedDistributionLorentzTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (RangedDistribution *) ((RangedDistributionLorentz *) x));
+}
+static void *_p_DistributionLorentzTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionLorentz *) x));
+}
+static void *_p_RangedDistributionLogNormalTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (RangedDistribution *) ((RangedDistributionLogNormal *) x));
+}
+static void *_p_DistributionLogNormalTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) (IDistribution1D *) ((DistributionLogNormal *) x));
+}
+static void *_p_RangedDistributionTo_p_ICloneable(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((ICloneable *) ((RangedDistribution *) x));
+}
+static void *_p_DistributionCosineTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionCosine *) x));
+}
+static void *_p_DistributionLorentzTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionLorentz *) x));
+}
+static void *_p_DistributionGaussianTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionGaussian *) x));
+}
+static void *_p_IDistribution1DTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) ((IDistribution1D *) x));
+}
+static void *_p_DistributionGateTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionGate *) x));
+}
+static void *_p_DistributionTrapezoidTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionTrapezoid *) x));
+}
+static void *_p_DistributionLogNormalTo_p_INode(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((INode *) (IDistribution1D *) ((DistributionLogNormal *) x));
+}
+static void *_p_DistributionCosineTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionCosine *) x));
+}
+static void *_p_DistributionLorentzTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionLorentz *) x));
+}
+static void *_p_DistributionGaussianTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionGaussian *) x));
+}
+static void *_p_DistributionGateTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionGate *) x));
+}
+static void *_p_DistributionTrapezoidTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionTrapezoid *) x));
+}
+static void *_p_DistributionLogNormalTo_p_IDistribution1D(void *x, int *SWIGUNUSEDPARM(newmemory)) {
+ return (void *)((IDistribution1D *) ((DistributionLogNormal *) x));
+}
static swig_type_info _swigt__p_Attributes = {"_p_Attributes", "Attributes *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_BasicLattice = {"_p_BasicLattice", "BasicLattice *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_BasicVector3DT_double_t = {"_p_BasicVector3DT_double_t", "std::vector< BasicVector3D< double > >::value_type *|kvector_t *|BasicVector3D< double > *", 0, 0, (void*)0, 0};
@@ -43871,6 +52320,7 @@ static swig_type_info _swigt__p_HexagonalLattice = {"_p_HexagonalLattice", "Hexa
static swig_type_info _swigt__p_IAbstractParticle = {"_p_IAbstractParticle", "IAbstractParticle *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ICloneable = {"_p_ICloneable", "ICloneable *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_IClusteredParticles = {"_p_IClusteredParticles", "IClusteredParticles *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_IDistribution1D = {"_p_IDistribution1D", "IDistribution1D *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_IFormFactor = {"_p_IFormFactor", "IFormFactor *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_IFormFactorBorn = {"_p_IFormFactorBorn", "IFormFactorBorn *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_IFormFactorDecorator = {"_p_IFormFactorDecorator", "IFormFactorDecorator *", 0, 0, (void*)0, 0};
@@ -43906,13 +52356,21 @@ static swig_type_info _swigt__p_MultiLayer = {"_p_MultiLayer", "MultiLayer *", 0
static swig_type_info _swigt__p_NodeMeta = {"_p_NodeMeta", "NodeMeta *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_OffSpecSimulation = {"_p_OffSpecSimulation", "OffSpecSimulation *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParaMeta = {"_p_ParaMeta", "ParaMeta *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_ParameterDistribution = {"_p_ParameterDistribution", "ParameterDistribution *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParameterPool = {"_p_ParameterPool", "ParameterPool *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_ParameterSample = {"_p_ParameterSample", "std::vector< ParameterSample >::value_type *|ParameterSample *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_Particle = {"_p_Particle", "Particle *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParticleComposition = {"_p_ParticleComposition", "ParticleComposition *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParticleCoreShell = {"_p_ParticleCoreShell", "ParticleCoreShell *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParticleDistribution = {"_p_ParticleDistribution", "ParticleDistribution *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_ParticleLayout = {"_p_ParticleLayout", "ParticleLayout *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_PoissonNoiseBackground = {"_p_PoissonNoiseBackground", "PoissonNoiseBackground *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistribution = {"_p_RangedDistribution", "RangedDistribution *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistributionCosine = {"_p_RangedDistributionCosine", "RangedDistributionCosine *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistributionGate = {"_p_RangedDistributionGate", "RangedDistributionGate *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistributionGaussian = {"_p_RangedDistributionGaussian", "RangedDistributionGaussian *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistributionLogNormal = {"_p_RangedDistributionLogNormal", "RangedDistributionLogNormal *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_RangedDistributionLorentz = {"_p_RangedDistributionLorentz", "RangedDistributionLorentz *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_RealLimits = {"_p_RealLimits", "RealLimits *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_RealParameter = {"_p_RealParameter", "RealParameter *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_RectangularDetector = {"_p_RectangularDetector", "RectangularDetector *", 0, 0, (void*)0, 0};
@@ -43943,6 +52401,7 @@ static swig_type_info _swigt__p_std__allocatorT_BasicVector3DT_double_t_t = {"_p
static swig_type_info _swigt__p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t = {"_p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t", "std::allocator< BasicVector3D< std::complex< double > > > *|std::vector< BasicVector3D< std::complex< double > > >::allocator_type *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__allocatorT_INode_const_p_t = {"_p_std__allocatorT_INode_const_p_t", "std::vector< INode const * >::allocator_type *|std::allocator< INode const * > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__allocatorT_INode_p_t = {"_p_std__allocatorT_INode_p_t", "std::vector< INode * >::allocator_type *|std::allocator< INode * > *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_std__allocatorT_ParameterSample_t = {"_p_std__allocatorT_ParameterSample_t", "std::vector< ParameterSample >::allocator_type *|std::allocator< ParameterSample > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__allocatorT_double_t = {"_p_std__allocatorT_double_t", "std::vector< double >::allocator_type *|std::allocator< double > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__allocatorT_int_t = {"_p_std__allocatorT_int_t", "std::vector< int >::allocator_type *|std::allocator< int > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__allocatorT_std__complexT_double_t_t = {"_p_std__allocatorT_std__complexT_double_t_t", "std::allocator< std::complex< double > > *|std::vector< std::complex< double > >::allocator_type *", 0, 0, (void*)0, 0};
@@ -43963,6 +52422,7 @@ static swig_type_info _swigt__p_std__vectorT_BasicVector3DT_std__complexT_double
static swig_type_info _swigt__p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t = {"_p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t", "std::vector< INode const *,std::allocator< INode const * > > *|std::vector< INode const * > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t = {"_p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t", "std::vector< INode *,std::allocator< INode * > > *|std::vector< INode * > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t = {"_p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t", "std::vector< ParaMeta,std::allocator< ParaMeta > > *", 0, 0, (void*)0, 0};
+static swig_type_info _swigt__p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t = {"_p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t", "std::vector< ParameterSample,std::allocator< ParameterSample > > *|std::vector< ParameterSample > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t = {"_p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t", "std::vector< RealParameter *,std::allocator< RealParameter * > > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__vectorT_double_std__allocatorT_double_t_t = {"_p_std__vectorT_double_std__allocatorT_double_t_t", "std::vector< double,std::allocator< double > > *|std::vector< double > *", 0, 0, (void*)0, 0};
static swig_type_info _swigt__p_std__vectorT_int_std__allocatorT_int_t_t = {"_p_std__vectorT_int_std__allocatorT_int_t_t", "std::vector< int,std::allocator< int > > *|std::vector< int > *", 0, 0, (void*)0, 0};
@@ -44063,6 +52523,7 @@ static swig_type_info *swig_type_initial[] = {
&_swigt__p_IAbstractParticle,
&_swigt__p_ICloneable,
&_swigt__p_IClusteredParticles,
+ &_swigt__p_IDistribution1D,
&_swigt__p_IFormFactor,
&_swigt__p_IFormFactorBorn,
&_swigt__p_IFormFactorDecorator,
@@ -44098,13 +52559,21 @@ static swig_type_info *swig_type_initial[] = {
&_swigt__p_NodeMeta,
&_swigt__p_OffSpecSimulation,
&_swigt__p_ParaMeta,
+ &_swigt__p_ParameterDistribution,
&_swigt__p_ParameterPool,
+ &_swigt__p_ParameterSample,
&_swigt__p_Particle,
&_swigt__p_ParticleComposition,
&_swigt__p_ParticleCoreShell,
&_swigt__p_ParticleDistribution,
&_swigt__p_ParticleLayout,
&_swigt__p_PoissonNoiseBackground,
+ &_swigt__p_RangedDistribution,
+ &_swigt__p_RangedDistributionCosine,
+ &_swigt__p_RangedDistributionGate,
+ &_swigt__p_RangedDistributionGaussian,
+ &_swigt__p_RangedDistributionLogNormal,
+ &_swigt__p_RangedDistributionLorentz,
&_swigt__p_RealLimits,
&_swigt__p_RealParameter,
&_swigt__p_RectangularDetector,
@@ -44135,6 +52604,7 @@ static swig_type_info *swig_type_initial[] = {
&_swigt__p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t,
&_swigt__p_std__allocatorT_INode_const_p_t,
&_swigt__p_std__allocatorT_INode_p_t,
+ &_swigt__p_std__allocatorT_ParameterSample_t,
&_swigt__p_std__allocatorT_double_t,
&_swigt__p_std__allocatorT_int_t,
&_swigt__p_std__allocatorT_std__complexT_double_t_t,
@@ -44155,6 +52625,7 @@ static swig_type_info *swig_type_initial[] = {
&_swigt__p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t,
&_swigt__p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t,
&_swigt__p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t,
+ &_swigt__p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t,
&_swigt__p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t,
&_swigt__p_std__vectorT_double_std__allocatorT_double_t_t,
&_swigt__p_std__vectorT_int_std__allocatorT_int_t_t,
@@ -44253,17 +52724,18 @@ static swig_cast_info _swigc__p_FormFactorWeighted[] = { {&_swigt__p_FormFactor
static swig_cast_info _swigc__p_GISASSimulation[] = { {&_swigt__p_GISASSimulation, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_HexagonalLattice[] = { {&_swigt__p_HexagonalLattice, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IAbstractParticle[] = { {&_swigt__p_IAbstractParticle, 0, 0, 0},{0, 0, 0, 0}};
-static swig_cast_info _swigc__p_ICloneable[] = { {&_swigt__p_ICloneable, 0, 0, 0}, {&_swigt__p_ParameterPool, _p_ParameterPoolTo_p_ICloneable, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_ICloneable[] = { {&_swigt__p_RangedDistributionGate, _p_RangedDistributionGateTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionGate, _p_DistributionGateTo_p_ICloneable, 0, 0}, {&_swigt__p_IDistribution1D, _p_IDistribution1DTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionTrapezoid, _p_DistributionTrapezoidTo_p_ICloneable, 0, 0}, {&_swigt__p_ICloneable, 0, 0, 0}, {&_swigt__p_RangedDistributionGaussian, _p_RangedDistributionGaussianTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionGaussian, _p_DistributionGaussianTo_p_ICloneable, 0, 0}, {&_swigt__p_ParameterPool, _p_ParameterPoolTo_p_ICloneable, 0, 0}, {&_swigt__p_RangedDistributionCosine, _p_RangedDistributionCosineTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionCosine, _p_DistributionCosineTo_p_ICloneable, 0, 0}, {&_swigt__p_RangedDistributionLorentz, _p_RangedDistributionLorentzTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionLorentz, _p_DistributionLorentzTo_p_ICloneable, 0, 0}, {&_swigt__p_RangedDistributionLogNormal, _p_RangedDistributionLogNormalTo_p_ICloneable, 0, 0}, {&_swigt__p_DistributionLogNormal, _p_DistributionLogNormalTo_p_ICloneable, 0, 0}, {&_swigt__p_RangedDistribution, _p_RangedDistributionTo_p_ICloneable, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IClusteredParticles[] = { {&_swigt__p_IClusteredParticles, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_IDistribution1D[] = { {&_swigt__p_DistributionCosine, _p_DistributionCosineTo_p_IDistribution1D, 0, 0}, {&_swigt__p_DistributionLorentz, _p_DistributionLorentzTo_p_IDistribution1D, 0, 0}, {&_swigt__p_DistributionGaussian, _p_DistributionGaussianTo_p_IDistribution1D, 0, 0}, {&_swigt__p_IDistribution1D, 0, 0, 0}, {&_swigt__p_DistributionGate, _p_DistributionGateTo_p_IDistribution1D, 0, 0}, {&_swigt__p_DistributionTrapezoid, _p_DistributionTrapezoidTo_p_IDistribution1D, 0, 0}, {&_swigt__p_DistributionLogNormal, _p_DistributionLogNormalTo_p_IDistribution1D, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IFormFactor[] = { {&_swigt__p_IFormFactor, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IFormFactorBorn[] = { {&_swigt__p_IFormFactorBorn, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IFormFactorDecorator[] = { {&_swigt__p_IFormFactorDecorator, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IInterferenceFunction[] = { {&_swigt__p_IInterferenceFunction, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ILayout[] = { {&_swigt__p_ILayout, 0, 0, 0},{0, 0, 0, 0}};
-static swig_cast_info _swigc__p_INode[] = { {&_swigt__p_INode, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_INode[] = { {&_swigt__p_INode, 0, 0, 0}, {&_swigt__p_DistributionCosine, _p_DistributionCosineTo_p_INode, 0, 0}, {&_swigt__p_DistributionLorentz, _p_DistributionLorentzTo_p_INode, 0, 0}, {&_swigt__p_DistributionGaussian, _p_DistributionGaussianTo_p_INode, 0, 0}, {&_swigt__p_IDistribution1D, _p_IDistribution1DTo_p_INode, 0, 0}, {&_swigt__p_DistributionGate, _p_DistributionGateTo_p_INode, 0, 0}, {&_swigt__p_DistributionTrapezoid, _p_DistributionTrapezoidTo_p_INode, 0, 0}, {&_swigt__p_DistributionLogNormal, _p_DistributionLogNormalTo_p_INode, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_INodeVisitor[] = { {&_swigt__p_INodeVisitor, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IParameterT_double_t[] = { {&_swigt__p_IParameterT_double_t, 0, 0, 0}, {&_swigt__p_RealParameter, _p_RealParameterTo_p_IParameterT_double_t, 0, 0},{0, 0, 0, 0}};
-static swig_cast_info _swigc__p_IParameterized[] = { {&_swigt__p_INode, _p_INodeTo_p_IParameterized, 0, 0}, {&_swigt__p_IParameterized, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_IParameterized[] = { {&_swigt__p_DistributionCosine, _p_DistributionCosineTo_p_IParameterized, 0, 0}, {&_swigt__p_INode, _p_INodeTo_p_IParameterized, 0, 0}, {&_swigt__p_DistributionLorentz, _p_DistributionLorentzTo_p_IParameterized, 0, 0}, {&_swigt__p_ParameterDistribution, _p_ParameterDistributionTo_p_IParameterized, 0, 0}, {&_swigt__p_DistributionGaussian, _p_DistributionGaussianTo_p_IParameterized, 0, 0}, {&_swigt__p_IParameterized, 0, 0, 0}, {&_swigt__p_IDistribution1D, _p_IDistribution1DTo_p_IParameterized, 0, 0}, {&_swigt__p_DistributionGate, _p_DistributionGateTo_p_IParameterized, 0, 0}, {&_swigt__p_DistributionTrapezoid, _p_DistributionTrapezoidTo_p_IParameterized, 0, 0}, {&_swigt__p_DistributionLogNormal, _p_DistributionLogNormalTo_p_IParameterized, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IParticle[] = { {&_swigt__p_IParticle, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IPeakShape[] = { {&_swigt__p_IPeakShape, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_IRotation[] = { {&_swigt__p_IRotation, 0, 0, 0},{0, 0, 0, 0}};
@@ -44290,13 +52762,21 @@ static swig_cast_info _swigc__p_MultiLayer[] = { {&_swigt__p_MultiLayer, 0, 0,
static swig_cast_info _swigc__p_NodeMeta[] = { {&_swigt__p_NodeMeta, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_OffSpecSimulation[] = { {&_swigt__p_OffSpecSimulation, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParaMeta[] = { {&_swigt__p_ParaMeta, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_ParameterDistribution[] = { {&_swigt__p_ParameterDistribution, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParameterPool[] = { {&_swigt__p_ParameterPool, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_ParameterSample[] = { {&_swigt__p_ParameterSample, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_Particle[] = { {&_swigt__p_Particle, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParticleComposition[] = { {&_swigt__p_ParticleComposition, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParticleCoreShell[] = { {&_swigt__p_ParticleCoreShell, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParticleDistribution[] = { {&_swigt__p_ParticleDistribution, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_ParticleLayout[] = { {&_swigt__p_ParticleLayout, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_PoissonNoiseBackground[] = { {&_swigt__p_PoissonNoiseBackground, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistribution[] = { {&_swigt__p_RangedDistributionCosine, _p_RangedDistributionCosineTo_p_RangedDistribution, 0, 0}, {&_swigt__p_RangedDistribution, 0, 0, 0}, {&_swigt__p_RangedDistributionLorentz, _p_RangedDistributionLorentzTo_p_RangedDistribution, 0, 0}, {&_swigt__p_RangedDistributionGaussian, _p_RangedDistributionGaussianTo_p_RangedDistribution, 0, 0}, {&_swigt__p_RangedDistributionGate, _p_RangedDistributionGateTo_p_RangedDistribution, 0, 0}, {&_swigt__p_RangedDistributionLogNormal, _p_RangedDistributionLogNormalTo_p_RangedDistribution, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistributionCosine[] = { {&_swigt__p_RangedDistributionCosine, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistributionGate[] = { {&_swigt__p_RangedDistributionGate, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistributionGaussian[] = { {&_swigt__p_RangedDistributionGaussian, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistributionLogNormal[] = { {&_swigt__p_RangedDistributionLogNormal, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_RangedDistributionLorentz[] = { {&_swigt__p_RangedDistributionLorentz, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_RealLimits[] = { {&_swigt__p_RealLimits, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_RealParameter[] = { {&_swigt__p_RealParameter, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_RectangularDetector[] = { {&_swigt__p_RectangularDetector, 0, 0, 0},{0, 0, 0, 0}};
@@ -44327,6 +52807,7 @@ static swig_cast_info _swigc__p_std__allocatorT_BasicVector3DT_double_t_t[] = {
static swig_cast_info _swigc__p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t[] = { {&_swigt__p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__allocatorT_INode_const_p_t[] = { {&_swigt__p_std__allocatorT_INode_const_p_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__allocatorT_INode_p_t[] = { {&_swigt__p_std__allocatorT_INode_p_t, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_std__allocatorT_ParameterSample_t[] = { {&_swigt__p_std__allocatorT_ParameterSample_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__allocatorT_double_t[] = { {&_swigt__p_std__allocatorT_double_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__allocatorT_int_t[] = { {&_swigt__p_std__allocatorT_int_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__allocatorT_std__complexT_double_t_t[] = { {&_swigt__p_std__allocatorT_std__complexT_double_t_t, 0, 0, 0},{0, 0, 0, 0}};
@@ -44347,6 +52828,7 @@ static swig_cast_info _swigc__p_std__vectorT_BasicVector3DT_std__complexT_double
static swig_cast_info _swigc__p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t[] = { {&_swigt__p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t[] = { {&_swigt__p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t[] = { {&_swigt__p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t, 0, 0, 0},{0, 0, 0, 0}};
+static swig_cast_info _swigc__p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t[] = { {&_swigt__p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t[] = { {&_swigt__p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__vectorT_double_std__allocatorT_double_t_t[] = { {&_swigt__p_std__vectorT_double_std__allocatorT_double_t_t, 0, 0, 0},{0, 0, 0, 0}};
static swig_cast_info _swigc__p_std__vectorT_int_std__allocatorT_int_t_t[] = { {&_swigt__p_std__vectorT_int_std__allocatorT_int_t_t, 0, 0, 0},{0, 0, 0, 0}};
@@ -44447,6 +52929,7 @@ static swig_cast_info *swig_cast_initial[] = {
_swigc__p_IAbstractParticle,
_swigc__p_ICloneable,
_swigc__p_IClusteredParticles,
+ _swigc__p_IDistribution1D,
_swigc__p_IFormFactor,
_swigc__p_IFormFactorBorn,
_swigc__p_IFormFactorDecorator,
@@ -44482,13 +52965,21 @@ static swig_cast_info *swig_cast_initial[] = {
_swigc__p_NodeMeta,
_swigc__p_OffSpecSimulation,
_swigc__p_ParaMeta,
+ _swigc__p_ParameterDistribution,
_swigc__p_ParameterPool,
+ _swigc__p_ParameterSample,
_swigc__p_Particle,
_swigc__p_ParticleComposition,
_swigc__p_ParticleCoreShell,
_swigc__p_ParticleDistribution,
_swigc__p_ParticleLayout,
_swigc__p_PoissonNoiseBackground,
+ _swigc__p_RangedDistribution,
+ _swigc__p_RangedDistributionCosine,
+ _swigc__p_RangedDistributionGate,
+ _swigc__p_RangedDistributionGaussian,
+ _swigc__p_RangedDistributionLogNormal,
+ _swigc__p_RangedDistributionLorentz,
_swigc__p_RealLimits,
_swigc__p_RealParameter,
_swigc__p_RectangularDetector,
@@ -44519,6 +53010,7 @@ static swig_cast_info *swig_cast_initial[] = {
_swigc__p_std__allocatorT_BasicVector3DT_std__complexT_double_t_t_t,
_swigc__p_std__allocatorT_INode_const_p_t,
_swigc__p_std__allocatorT_INode_p_t,
+ _swigc__p_std__allocatorT_ParameterSample_t,
_swigc__p_std__allocatorT_double_t,
_swigc__p_std__allocatorT_int_t,
_swigc__p_std__allocatorT_std__complexT_double_t_t,
@@ -44539,6 +53031,7 @@ static swig_cast_info *swig_cast_initial[] = {
_swigc__p_std__vectorT_INode_const_p_std__allocatorT_INode_const_p_t_t,
_swigc__p_std__vectorT_INode_p_std__allocatorT_INode_p_t_t,
_swigc__p_std__vectorT_ParaMeta_std__allocatorT_ParaMeta_t_t,
+ _swigc__p_std__vectorT_ParameterSample_std__allocatorT_ParameterSample_t_t,
_swigc__p_std__vectorT_RealParameter_p_std__allocatorT_RealParameter_p_t_t,
_swigc__p_std__vectorT_double_std__allocatorT_double_t_t,
_swigc__p_std__vectorT_int_std__allocatorT_int_t_t,