Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 12]

CAllRenderData	Collects all data source settings for all possible combinations:
CANSYS_Mechanical_DSDAT_Settings	Settings for ANSYS DS.DAT exporter
CApproximateFMOP	An algorithm that computes new field samples from input parameters and FMOP models
CApproximateMOP	An algorithm that computes new field samples from input parameters and FMOP models
CApproximateRandomField	Algorithm that computes new field samples from amplitudes and random field model
CArchive	Encapsulates I/O functions for Matrix
CCancelBase	CancelBase provides an Interface to incorporate cancelling of computations in different ways
CClassTraits< CreateMOP >
CCoarseRigidTransformation	This algorithms automatically transformates one structure to the center of origin of the other. The center of origin is defined by the boundary surface of both structures
CCoarseRotation	This algorithms automatically rotates one structure to the center of origin of the other
CCoarseTranslation	This algorithms automatically translates one structure to the center of origin of the other
CCoD	Reference implementation for a quality metric for MOP models
CCoD_adj	Reference implementation for a quality metric for MOP models
CCompatibleMeshMapper	Imports data from a compatible mesh
CComputeAbsoluteMaxima	Struct which collects settings for ComputeAbsoluteMaxima
CComputeAbsoluteMinima	Struct which collects settings for ComputeAbsoluteMinima
CComputeAmplitudes	Decomposition of one or multiple random fields
CComputeCoefficientOfDetermination	Struct which collects settings for computing the Coefficient Of Determination
CComputeCorrelation	Struct which collects settings for computeCorrelation
CComputeCoV	Struct which collects settings for ComputeCoV
CComputeMax	Struct which collects settings for ComputeMax
CComputeMaxProbability	Struct which collects settings for ComputeMaxProbability
CComputeMean	Struct which collects settings for ComputeMean
CComputeMeanMissing	Struct which collects settings for ComputeMean
CComputeMeanPlusSigma	Struct which collects settings for computing 'mean+ k * sigma'
CComputeMin	Struct which collects settings for ComputeMin
CComputeMinProbability	Struct which collects settings for ComputeMinProbability
CComputeNodalCoorDeviation	Struct which collects settings for computeNodalCoorDeviation
CComputeProbabilitySigmaInterval	Struct which collects settings for probability of sigma intervals, i.e. of P( mean + lsigma <= X < mean + usigma)
CComputeQualityCapabilityCp	Struct which collects settings for QCS/Cp
CComputeQualityCapabilityCpk	Struct which collects settings for QCS/Cpk
CComputeQuantile	Struct which collects settings for QCS/Cpk
CComputeQuantileInverse	Struct which collects settings for inverse quantile computation (not-exceedance probability)
CComputeRandomFieldErrors	Decomposition of one or multiple random fields
CComputeRange	Struct which collects settings for ComputeRange
CComputeRelativeError	Computes the relative accuracy between two quantities given using $\epsilon = \frac{x_{\mbox{other}}}{x_{\mbox{ref}}}$ If set, the relative error is computed using $\epsilon = \frac{x_{\mbox{other}}-x_{\mbox{ref}}}{max_i \|x_{\mbox{ref}}\|_i }$
CComputeRelativeMaxima	Struct which collects settings for ComputeRelativeMaxima
CComputeRelativeMinima	Struct which collects settings for ComputeRelativeMinima
CComputeRPCA	Perform Robust Principal Component Analysis While traditional PCA is very sensitive to data corruption or outliers, RPCA is, as its name implies, robust to data corruption under surprisingly broad conditions. RPCA attempts to split a given matrix M into two matrices S and L: M = L + S where L is a low-rank matrix and S is a sparse matrix of random errors (of arbitrary magnitude and random sign). In the context of SoS, each column vector of M might be a particular field design. Without any prior knowledge about outliers, RPCA is then able to separate correlations between field designs (L) from outliers (S). Security camera footage is a good example, following the M = L + S data model: L represents the slowly changing background, while S represents walking people. See https://arxiv.org/abs/0912.3599 for more examples and a precise definition of the conditions, for RPCA to deliver good results. By default, ComputeRPCA creates two new quantity idents named RPCA[] (L) and RPCAError[] (S). Disable the creation of RPCAError by setting the createRPCAError member variable to false. The algorithm attempts to recover L and S by running the Principal Component Pursuit bi-objective optimization program:
CComputeSingleObjectPerObject	Base class for algorithms that apply a simple algorithm to obtain a single object from another object
CComputeSingleObjectPerSample	Base class for algorithms that apply a simple algorithm to obtain a single object from a single set of samples
CComputeStddev	Struct which collects settings for ComputeStddev
CComputeStdErrorOfMean	Struct which collects settings for computing the standard error of mean estimator
CComputeStdErrorOfVariance	Struct which collects settings for computing the standard error of the variance estimator
CComputeVariance	Struct which collects settings for ComputeVariance
CConvertToElement	Struct which collects settings for convertToElement
CConvertToNode	Struct which collects settings for convertToNode
CCoorTransformationBase	An abstract base class that provides a generic API for different methods that apply rigid coordinate transformations
CCoP	Reference implementation for a quality metric for MOP models
CCopyFilledData	Struct which collects settings for CopyFilledData
CCreateCustomModel	This class creates a custom model definable in python. It is able to register an instance derived of CreateCustomModelInterface. This registered instance may then be accessed just like any other model. It may also be serialized and de-serialized
CCreateCustomModelInterface	This class is exported as an director class through SWIG allowing the python context to define derivations from it. A user is then able to implement her own classes satisfying this interface and then being used with the MOP framework
CCreateFMOP	Creates a FMOP
CCreateKrigingModel	Defines a Kriging Model Used Properties:
CCreateLegacyMOPModel	Defines a LegacyMOPModel. This type of model wraps the old MOP and makes it accessible to The MOP framework. Used Properties:
CCreateLegacyMOQModel	Defines a LegacyMOPModel This type of model wraps the old MOQ and makes it accessible to The MOP framework. Used Properties:
CCreateMLSModel	Defines a Moving Least Squares type model Used Properties:
CCreateModelBase	API for all MOP3 model creation classes
CCreateMOP	Creates a FMOP
CCreatePolynomialModel	Defines a PolynomialModel Used Properties:
CCreateRangeBase	Base class to the Ranges. Ranges can be defined and computed into a JsonValue
CCreateRangeEnum	The Enum-Range defines a range for a given enum-type and stores this range as a list of values
CCreateRangeList	The List-Range defines a range for a given type from a list of values and stores this list
CCreateRangeMinMax	The Min-Max-Range defines a range for a given type with a minimum value and a maximum value
CCreateRangeMinMaxWithAuto	The Min-Max-Auto-Range defines a range for a given type with a minimum value and a maximum value together with a special value "auto" that may be used differently in certain situations
CCreateRangeNone	The "None"-Range gives no range at all
CCreateRBFModel	Defines a RBF Model Used Properties:
CCreateScalarMOP	Creation/Configuration class for the ScalarMOP CreateScalarMOP may be given a number of Model Configurations (CreateModelBase). By calling compute all relevant models are scheduled and trained based on these Configuration. The resulting MOP object is the returned
CCreateScalarMOP2	Simple interface encapsulating the external Dynardo MOP C-interface. Used to build and solve a MOP problem given an input and ouput Matrix respectively
CCreateSimpleTrainingPlan	This class is used to create training plans for the ScalarMOP competition. It sets up data according to an sample analysis to allow efficient training of the samples. It provides functions to access and cleanup the prepared data
CCreateSimulationArchive	A struct collecting export information for random field simulation data
CCustomModel
CCustomModelInterface	This class provides an API for the CustomModels to be implemented in Python. It is exported as an director through SWIG and the user will be able to derive from it in Python
CCustomModelTester	This class can be used in python context to check if all Interface functions of a custom model are implemented correctly
CDataModelReporter	This class provies all information in Json format about the available functionality in the AutoML framework
CDataObjectContainer	A general container for vector data
CDataObjectIdentMap	A map of data objects of same type being associated with single string idents
CDataObjectKey	Key (ident) of a data object in generic containers
CDataObjectPtr	A shared pointer wrapper for data objects
CDataObjectToGraphicsIndices	Class that collects data that is required to transfer the data from a DataObject to the vertices of the OpenGL scene
CDataObjectVector	A vector of DataObjectPtr
CDesignProjectionErrorReport	The DesignProjectionError struct
CDistanceField	Distance field for an unstructured grid
►CDynainFileParser	Settings for the Dynain exporter
CParsedData	Contains information that was found in the parsed file
CElement	Repesents the geometry of a finite element within a mesh
CElementTemporalEditInfo	Collects information to be used for faster FEM mesh creation
CEnumTraits< DependencyType >
CEnumTraits< ParameterImportance >
CEnumTraits< TrainingPlanType >
CExportCSV	Exports scalar data to a CSV file
CExportCSVField	Exports SoS field data to a CSV text file
CExportCSVScalar	Exports scalar data to a CSV file
CExportDesigns	A struct collecting export information for various design directories
CExportGeometry	Defines the interface for exporting a deformed geometry to a file The coordinates to be exported are either:
CExportItemInfo	Defines a single data item which was may be exported to a single existing output file. It encapsulates information being found on this data item in the specific file. It can further be configured to be exported
CExportOptiSLangBinaryScalars	Stores settings for export to optiSLang bin file
CExportReferenceDesign	Defines information on imported data and files given a reference design This class contains settings for an example design directory (the base_path). These settings include file formats, data items to be imported etc
CExportScriptForComputingAmplitudesFromField	A struct collecting import information for generating a script that converts field data into random field amplitudes
CExportSignalsSettings	Stores settings for export signals to a couple of CSV files
CExportToMOP	A struct collecting export information for FMOP/F-CoP in optiSLang
CExternalRandomFieldModel	Provides random field models
CExtractAboveThreshold	Struct which collects settings for extractAboveThreshold
CExtractBelowThreshold	Struct which collects settings for extractBelowThreshold
CExtractExtremalScalars	An abstract base class to compute the extremal scalar quantity per design from all field indices given in indices as well as for all field quantities found within the dataobject filter
CExtractMaximumScalars	Computes and creates the maximum scalar quantity per selection for a field quantity selection defined by a dataobject filter and a set of part and item indices
CExtractMinimumScalars	Computes and creates the minimum scalar quantity per selection for a field quantity selection defined by a dataobject filter and a set of part and item indices
CExtractMissingDataFlags	Struct which collects settings for ExtractMissingDataFlags
CExtractScalars	Creates as many scalar quantites as samples for all field indices given in indices as well as all field quantities found within the dataobject filter
CExtractScalarsFromQuantity	Struct which collects settings for extractAboveThreshold
CFineRigidTransformation	Tries to match a source point cloud with a reference point cloud using the coarse transformation (see Coarse) as pre-alignment step and the Iterative Closes Point Algorithm (see ICP) afterwards as fine adjustment
CFMOPContainer	Container storing all Field data models
CFMOPGroup	Group of random fields belonging together (either a single random field, or multiple cross-correlated fields)
CFMU
CFreeFormVariationModel	Provides random field models
CGenerateRandomFields	Algorithm that computes new field samples from amplitudes and scatter shapes The algorithm is essentially the same is the class FieldDesignsFromAmplitudes, but it is based on the data structures stored in class RandomFieldContainer
CGridMeshMapper	Imports data from an incompatible GRID (signal, pixel, voxel)
CImportCoP	Imports CoP values of amplitudes from CSV file
CImportCSV	A class collecting import information for a csv file
CImportDesigns	A class collecting import information for various design directories
CImportItemInfo	Defines a data item which was found in an input file
CImportOMDB	Stores settings for loading optiSLang omdb files. Limited to scalar parameters and responses
CImportOptiSLangBinary	Stores settings for loading optiSLang binary files
CImportOptiSLangSignal	Sets up an SoS project for a single user defined optiSLang 3 signal identifier
CImportSRBProject	Import a Twin Builder Static ROM Builder (SRB) project. Expects a valid SRB project directory as input
CIncompatibleMeshMapper	Imports data from an incompatible mesh
CIncompatibleMeshMapperByProjection	Imports data from an incompatible mesh
CIndexMapper	Accessor for indices in global vectors and matrices
CJsonValue	Simple wrapper class to jsoncpp that make working with SWIG more convenient
CKrigingModel
CLoadDataBaseSettings	Stores settings for loadDataBase()
CMacroArg	Function argument of a macro
CMacroExporter	Export Statistics on Structures macross built with the MacroBuilder and export the resulting workflow as a Functional Mockup Unit (FMU), for further use e.g. in Ansys OptiSLang
CMacroFunction	Definition of a single macro
CMacroManager	Stores a set of macro definitions MacroManager is a common::Sender. Listeners can register themselves at Senders. MacroManager calls its senders when Macros are changed/added/removed
CMatrix	Standard matrix class
CMatrixBlock	A generic view onto parts of a Matrix
CMatrixCWise	Coefficient wise access to Matrix
CMatrixEigenSym	Eigen decomposition of symmetric matrices
CMeshAssembly	Describes a finite element mesh
CMeshMapper_Ray	Imports data from an incompatible mesh
CMeshMapperBase	An abstract base class that provides a generic API for different methods that import matching or non-matching meshes and their data
CMeshMorpherSettings	Class containing global settings for mesh morphing
CMetaStructure	Defines a meta structure which contains all data that is used to create a finite element mesh
CMLSModel
CModelBase	Class all model-types derive from Models are already built and valid
CModifyMeshBase	Base settings that are provided for all modifier classes that change mesh coorsinates
CMOP	Group of random fields belonging together (either a single random field, or multiple cross-correlated fields)
CMOPContainer	Container storing all Field data models
CMultivariateDistributionTypes	Encalsulates ENUM constants defining supported distribution types
CMUMPS	Solver for sparse matrices using MUMPS
CNeutralCoorTransformation	A dummy implementation which does no rigid transformation but implements the complete API
CP2VolumeMeshMapper	Imports data from an incompatible GRID (signal, pixel, voxel)
CParameter	This class provides functions to work with a singleton parameter of the givien type
CParameterContainer	This class provides functions to work with a list/container parameter of the givien type
CPiecewiseConstantModel	Provides random field models
CPolynomialModel
CPrepareRandomFieldSimulation	A struct collecting export information for random field simulation data
CPropertyBase	Property base class used to have a common interface to handle properties and kept them in a container. See: PropertyList
CPropertyList	Container class for handling properties Uses templates to easily find and cast configurations of different types
CPropertyUserBase	This class provies a unified acces to use the MOP frameworks property system. Just derive your class from it if you need proeprties
CQualityMeasureBase	API for different quality metrics for MOP models
CRandomFieldContainer	Container storing all random field decompositions
CRandomFieldData	Random field data for analysis and simulation for a single random field
CRandomFieldDecompositionFromSamples	Decomposition of one or multiple random fields
CRandomFieldGroup	A group of random fields belonging together (either a single random field, or multiple cross-correlated fields)
CRandomFieldModel	Provides random field models
CRBFModel
CRealList	Convenience class for Lua (std::list<number>)
CReconstructData	Data reconstruction of missing data items using one or multiple random fields
CReferenceDesign	Defines information on imported data and files given a reference design
CRenderData	Defines the source of visible data
CReplaceAboveThreshold	Struct which collects settings for ReplaceAboveThreshold
CReplaceBelowThreshold	Struct which collects settings for ReplaceBelowThreshold
CResiduals	The estimator class creates an abstraction for classes the QualityMeasure may be evaluated for in the MOP framework. It abstracts the essential data necessary in an quality measurement which can be done based on Three information: Approximation: This is data estimated using any approximation type CrossValidation: This is data that is estimated explicitly using cross-validation sets generated by the MOP handler AdjustmentCoefficient: This is a value in the range 1,...,N where N is the number of samples provided to the Estimator
CResidualsBase	The Residuals class creates an abstraction for classes the QualityMeasure may be evaluated for in the MOP framework. It abstracts the essential data necessary in an quality measurement which can be done based on Three information: approximationResiduals: This is data estimated using any approximation type crossValidationResiduals: This is data that is estimated explicitly using cross-validation sets generated by the MOP handler adjustmentCoefficient: This is a value in the range 1,...,N where N is the number of samples provided to the Estimator
CSaveDataBaseSettings	Stores settings for saveDataBase()
CScalarMOP	This is only a sketch of the possible ScalarMOPApproximate API Implementation shall be refined if more information is available
CScalarMOP2	Represents a ScalarMOP2
CScene	A class for 3D visualization of a structure Additionally, it can display palettes and text annotations as well as rich text labels. Internally, a representation in terms of triangles only is used. Qt separation: This class contains no functionality relying on Qt classes. All methods using Qt classes are virtual and have no implementation, calling DYNARDO_LOG_WARN instead. Their implementation is done in SceneQt, part of the sos_qt_extensions module. Class Scene is NO QObject, but SceneQt is. Instances of Scene or SceneQt are created with application_makeScene(), implemented in the sos_qt_extensions or sos_noqt_extensions module respectively
CSceneManager	A manager class for 3D visualization of a structure
CSerializableTraits	This header provides a unified way to handle the Json serialization of parameters of different types. Each parameter is stored in an expressive way defining the Type, Range, Value and Multiplicity (Signlton/List) of the serialize object. This is achieved by having a traits class being defined for the parameters Type. Some standard definitions for ints, uints, numbers, strings are available but for serializing custom enums you would typically define this yourself. When de-/serializing a parameter of this type you the would only call the load/save functions depending on single/container parameters
CSerializableTraits< ParameterImportance >
CSimpleCancel
CSimpleTrainingPlan	TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model A model is trained for a set of outputs
CSparseLU	Base class of LU solvers. It already implements the standard LU decomposition
CSparseMatrix	Encapsulates sparse matrix classes and algorithms
CSparseSolver	The base class for sparse solvers. It provides a unified interface which can be used by generic algorithms
CStructure	The central data structure for SoS
CSymSparseMatrix	Symmetric sparse matrix class with selfadjoint storage
CTMumpsInterface< float >	Wrapper for the single precision MUMPS C API
CTMumpsInterface< number >	Wrapper for the number precision MUMPS C API
CTrainingPlanBase	TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model
CValueType	Represents a type of value and a set of properties. ValueType is intended to be associated with a set of floating point data values. It stores information (the value type and named value attributes) about data values. It provides conversion routines between its associated floating point data values and value type
CValueTypeBool	Identifies a set of values as boolean and an associated set of optional attributes. It provides conversion routines between floating point and string representation
CValueTypeDouble	Identifies a set of values as number precision floating points values and an associated set of optional attributes (for instance minimum and maximum value). It provides conversion routines between floating point and string representation
CValueTypeEnum	Identifies a set of values as an enumration of strings type and an associated set of optional attributes (for instance minimum and maximum value). It provides conversion routines between floating point and string representation
CValueTypeInt	Identifies a set of values as integer values and an associated set of optional attributes (for instance minimum and maximum value). It provides conversion routines between floating point and string representation
CValueTypeManager	Keeps track of all unique ValueTypes. Required to create new ValueType shared resource instances. Script example:
CVertexValues	Data containing information about the field data in simplified form
CVerticesNormalsVisibility	Data containing information about the structure in simplified form

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