Classes
class	Algorithm
	Algorithm is an abstract AnalysisObject that is the base class for all OpenStudioAlgorithms and DakotaAlgorithms. More...

class	AlgorithmOptions
	AlgorithmOptions defines the basic options that all Algorithms are assumed to have, that is, a maximum number of iterations and a maximum number of simulations. More...

class	Analysis
	Analysis is a AnalysisObject that contains an entire analysis. More...

struct	AnalysisJSONLoadResult

class	AnalysisObject
	AnalysisObject is the base class for all major classes in the openstudio::analysis namespace. More...

struct	AnalysisSerializationOptions

class	AnalysisSerializationScope
	Enum to indicate how much of the analysis should be written out to JSON. More...

class	BetaDistribution
	BetaDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	BinomialDistribution
	BinomialDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	ContinuousVariable
	A ContinuousVariable is an InputVariable whose value is a real number, perhaps restricted to lie within some bounds. More...

class	DakotaAlgorithm
	DakotaAlgorithm is an Algorithm that works with the third-party software package DAKOTA (http://dakota.sandia.gov/software.html) to generate new data points. More...

class	DakotaAlgorithmOptions
	DakotaAlgorithmOptions is an AlgorithmOptions class for DakotaAlgorithms. More...

class	DakotaFunctionType
	List of function types DAKOTA expects us to evaluate. More...

class	DakotaParametersFile
	DakotaParametersFile is an interface to the files that DAKOTA drops on the filesystem to indicate that we should create and run a new DataPoint. More...

class	DataPoint
	DataPoint is an AnalysisObject that describes a single simulation run/to be run for a given Analysis. More...

class	DataPointRunType
	List of DataPoint run types. More...

class	DDACEAlgorithm
	DDACEAlgorithm is a DakotaAlgorithm that implements dakotaInFileDescription so as to specify a particular Distributed Design and Analysis for Computer Experiments (DDACE) method and related options. More...

class	DDACEAlgorithmOptions
	DDACEAlgorithmOptions is a DakotaAlgorithmOptions class that defines options specific to DDACEAlgorithm. More...

class	DDACEAlgorithmType
	Lists the types of sampling methods offered by the DDACE libary. More...

class	DesignOfExperiments
	DesignOfExperiments is an OpenStudioAlgorithm. More...

class	DesignOfExperimentsOptions
	DesignOfExperimentsOptions is an AlgorithmOptions class for use with DesignOfExperiments. More...

class	DesignOfExperimentsType

class	DiscreteVariable
	A DiscreteVariable is an InputVariable whose value is a finite list of values mappable to a range of integers. More...

class	ExponentialDistribution
	ExponentialDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	FrechetDistribution
	FrechetDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	FSUDaceAlgorithm
	FSUDaceAlgorithm is a DakotaAlgorithm that implements dakotaInFileDescription so as to specify a particular Florida State University Design and Analysis of Computer Experiments method and related options. More...

class	FSUDaceAlgorithmOptions
	FSUDaceAlgorithmOptions is a DakotaAlgorithmOptions class that defines options specific to FSUDaceAlgorithm. More...

class	FSUDaceAlgorithmType
	Lists the types of sampling methods offered by the FSU Dace libary. More...

class	FSUDaceCvtTrialType
	Lists the types of trials that may be used with the FSUDaceAlgorithmType::cvt. More...

class	Function
	Function is an abstract AnalysisObject that registers a set of Variables whose values can be retrieved from a DataPoint, and requires classes derived from it to implement Function::getValue. More...

class	GammaDistribution
	GammaDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	GenericUncertaintyDescription
	GenericUncertaintyDescription is an UncertaintyDescription interface for use by APIs and for serialization/deserialization. More...

class	GeometricDistribution
	GeometricDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	GumbelDistribution
	GumbelDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	HistogramBinDistribution
	HistogramBinDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	HistogramPointDistribution
	HistogramPointDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	HypergeometricDistribution
	HypergeometricDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	InputVariable

class	LinearFunction
	LinearFunction is a Function of the form a1x1 + a2x2 + ... More...

class	LognormalDistribution
	LognormalDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	LoguniformDistribution
	LoguniformDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	Measure
	Measure is an AnalysisObject that defines one particular value of a DiscreteVariable. More...

class	MeasureGroup
	MeasureGroup is an DiscreteVariable that takes on discrete values, each of which is described by a Measure. More...

class	NegativeBinomialDistribution
	NegativeBinomialDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	NormalDistribution
	NormalDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	NullMeasure
	NullMeasure is a Measure that does not change the input model in any way. More...

class	OpenStudioAlgorithm
	OpenStudioAlgorithm is an Algorithm whose logic is directly encoded in the implementation of createNextIteration. More...

class	OptimizationDataPoint
	OptimizationDataPoint is a DataPoint for use with OptimizationProblems . More...

struct	OptimizationDataPointObjectiveFunctionLess
	Predicate struct for comparing OptimizationDataPoints by objective function value. More...

class	OptimizationProblem
	OptimizationProblem is a Problem that has objective functions in addition to variables, response functions, and a simulation workflow. More...

class	OutputAttributeVariable
	OutputAttributeVariable is an OutputVariable that accesses attributes written to XML as part of a simulation post-processing step. More...

class	OutputVariable

class	ParameterStudyAlgorithm
	ParameterStudyAlgorithm is a DakotaAlgorithm that implements dakotaInFileDescription so as to specify a particular Parameter Study method and related options. More...

class	ParameterStudyAlgorithmOptions
	ParameterStudyAlgorithmOptions is a DakotaAlgorithmOptions that defines options specific to ParameterStudyAlgorithm. More...

class	ParameterStudyAlgorithmType
	Lists the types of sampling methods offered by the Parameter Study library. More...

class	PoissonDistribution
	PoissonDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a discrete variable. More...

class	Problem
	Problem is an AnalysisObject that contains a (building energy) problem formulation stated as a vector of workflow steps (input variables or runmanager::WorkItems), and a vector of response functions. More...

class	PSUADEDaceAlgorithm
	PSUADEDaceAlgorithm is a DakotaAlgorithm that implements dakotaInFileDescription so as to specify a particular Problem Solving Environment for Uncertainty Analysis and Design Exploration Morris One-At-A-Time method and related options. More...

class	PSUADEDaceAlgorithmOptions
	PSUADEDaceAlgorithmOptions is a DakotaAlgorithmOptions that defines options specific to PSUADEDaceAlgorithm. More...

class	RubyContinuousVariable
	RubyContinuousVariable is a ContinuousVariable. More...

class	RubyMeasure
	RubyMeasure is a Measure that modifies a model (OSM or IDF file) using a Ruby script. More...

class	SamplingAlgorithm
	SamplingAlgorithm is a DakotaAlgorithm that implements dakotaInFileDescription so as to specify a particular Sampling method and related options. More...

class	SamplingAlgorithmOptions
	SamplingAlgorithmOptions is a DakotaAlgorithmOptions class that defines options specific to SamplingAlgorithm. More...

class	SamplingAlgorithmRNGType
	Lists the types of pseudo-random number generators that may be used with the Sampling library. More...

class	SamplingAlgorithmSampleType
	Lists the types of sampling methods offered by the Sampling libary. More...

class	SequentialSearch
	SequentialSearch is an OpenStudioAlgorithm that can be used to solve OptimizationProblems with two objective functions and discrete variables. More...

class	SequentialSearchOptions
	SequentialSearchOptions is an options class for SequentialSearch, derived from AlgorithmOptions. More...

class	TriangularDistribution
	TriangularDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	UncertaintyDescription
	UncertaintyDescription is an abstract base class that can be used to append uncertainty information to a Variable. More...

class	UncertaintyDescriptionType
	List of all the uncertainty types supported by DAKOTA. More...

class	UncertaintyType
	List of uncertainty types. More...

class	UniformDistribution
	UniformDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	Variable
	Variable is an AnalysisObject that serves as a base class for InputVariable and OutputVariable. More...

class	VariableValueType
	List of variable numeric types. More...

class	WeibullDistribution
	WeibullDistribution is an UncertaintyDescription that can apply aleatory uncertainty to a continuous variable. More...

class	WorkflowStep
	WorkflowStep is an AnalysisObject that describes an individual step in a Problem's overall Workflow. More...

struct	WorkflowStepJob
	WorkflowStepJob is a structure for articulating the detailed runtime results associated with each WorkflowStep as executed for a particular DataPoint. More...

Typedefs
typedef boost::optional < AnalysisSerializationScope >	OptionalAnalysisSerializationScope

typedef boost::optional < DakotaFunctionType >	OptionalDakotaFunctionType

typedef boost::optional < DataPointRunType >	OptionalDataPointRunType

typedef boost::optional < DDACEAlgorithmType >	OptionalDDACEAlgorithmType

typedef boost::optional < DesignOfExperimentsType >	OptionalDesignOfExperimentsType

typedef boost::optional < FSUDaceAlgorithmType >	OptionalFSUDaceAlgorithmType

typedef boost::optional < FSUDaceCvtTrialType >	OptionalFSUDaceCvtTrialType

typedef boost::optional < ParameterStudyAlgorithmType >	OptionalParameterStudyAlgorithmType

typedef boost::optional < SamplingAlgorithmRNGType >	OptionalSamplingAlgorithmRNGType

typedef boost::optional < SamplingAlgorithmSampleType >	OptionalSamplingAlgorithmSampleType

typedef boost::optional < UncertaintyDescriptionType >	OptionalUncertaintyDescriptionType

typedef boost::optional < UncertaintyType >	OptionalUncertaintyType

typedef boost::optional < VariableValueType >	OptionalVariableValueType

typedef std::vector < UncertaintyDescriptionType >	UncertaintyDescriptionTypeVector

Functions
std::ostream &	operator<< (std::ostream &os, const DesignOfExperimentsType &e)

std::ostream &	operator<< (std::ostream &os, const DakotaFunctionType &e)

std::ostream &	operator<< (std::ostream &os, const SamplingAlgorithmSampleType &e)

std::ostream &	operator<< (std::ostream &os, const FSUDaceAlgorithmType &e)

std::ostream &	operator<< (std::ostream &os, const ParameterStudyAlgorithmType &e)

std::ostream &	operator<< (std::ostream &os, const DDACEAlgorithmType &e)

std::ostream &	operator<< (std::ostream &os, const VariableValueType &e)

std::ostream &	operator<< (std::ostream &os, const AnalysisSerializationScope &e)

std::ostream &	operator<< (std::ostream &os, const SamplingAlgorithmRNGType &e)

std::ostream &	operator<< (std::ostream &os, const FSUDaceCvtTrialType &e)

std::ostream &	operator<< (std::ostream &os, const DataPointRunType &e)

std::ostream &	operator<< (std::ostream &os, const UncertaintyType &e)

std::ostream &	operator<< (std::ostream &os, const UncertaintyDescriptionType &e)

bool	saveJSON (const std::vector< DataPoint > &dataPoints, const openstudio::path &p, bool overwrite=false)
	Save a vector of DataPoints to a JSON file. More...

std::vector< DataPoint >	toDataPointVector (const openstudio::path &jsonFilepath)
	Deserialize JSON file of a vector of DataPoints. More...

std::vector< DataPoint >	toDataPointVector (const std::string &json)
	Deserialize JSON string of a vector of DataPoints. More...

std::vector< DataPoint >	toDataPointVector (std::istream &json)

std::string	toJSON (const std::vector< DataPoint > &dataPoints)
	Print a vector of DataPoints to std::string in JSON format. More...

std::ostream &	toJSON (const std::vector< DataPoint > &dataPoints, std::ostream &os)

Typedef Documentation

typedef boost::optional< AnalysisSerializationScope > openstudio::analysis::OptionalAnalysisSerializationScope

typedef boost::optional< DakotaFunctionType > openstudio::analysis::OptionalDakotaFunctionType

typedef boost::optional< DataPointRunType > openstudio::analysis::OptionalDataPointRunType

typedef boost::optional< DDACEAlgorithmType > openstudio::analysis::OptionalDDACEAlgorithmType

typedef boost::optional< DesignOfExperimentsType > openstudio::analysis::OptionalDesignOfExperimentsType

typedef boost::optional< FSUDaceAlgorithmType > openstudio::analysis::OptionalFSUDaceAlgorithmType

typedef boost::optional< FSUDaceCvtTrialType > openstudio::analysis::OptionalFSUDaceCvtTrialType

typedef boost::optional< ParameterStudyAlgorithmType > openstudio::analysis::OptionalParameterStudyAlgorithmType

typedef boost::optional< SamplingAlgorithmRNGType > openstudio::analysis::OptionalSamplingAlgorithmRNGType

typedef boost::optional< SamplingAlgorithmSampleType > openstudio::analysis::OptionalSamplingAlgorithmSampleType

typedef boost::optional< UncertaintyDescriptionType > openstudio::analysis::OptionalUncertaintyDescriptionType

typedef boost::optional< UncertaintyType > openstudio::analysis::OptionalUncertaintyType

typedef boost::optional< VariableValueType > openstudio::analysis::OptionalVariableValueType

typedef std::vector<UncertaintyDescriptionType> openstudio::analysis::UncertaintyDescriptionTypeVector

Function Documentation

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const DesignOfExperimentsType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const DakotaFunctionType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const SamplingAlgorithmSampleType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const FSUDaceAlgorithmType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const ParameterStudyAlgorithmType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const DDACEAlgorithmType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const VariableValueType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const AnalysisSerializationScope &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const SamplingAlgorithmRNGType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const FSUDaceCvtTrialType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const DataPointRunType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const UncertaintyType &	e
	)

inline

std::ostream& openstudio::analysis::operator<<	(	std::ostream &	os,
		const UncertaintyDescriptionType &	e
	)

inline

bool openstudio::analysis::saveJSON	(	const std::vector< DataPoint > &	dataPoints,
		const openstudio::path &	p,
		bool	overwrite = `false`
	)

Save a vector of DataPoints to a JSON file.

Used for batch upload to openstudio-server.

std::vector<DataPoint> openstudio::analysis::toDataPointVector ( const openstudio::path & jsonFilepath )

Deserialize JSON file of a vector of DataPoints.

std::vector<DataPoint> openstudio::analysis::toDataPointVector ( const std::string & json )

Deserialize JSON string of a vector of DataPoints.

std::vector<DataPoint> openstudio::analysis::toDataPointVector ( std::istream & json )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

std::string openstudio::analysis::toJSON ( const std::vector< DataPoint > & dataPoints )

Print a vector of DataPoints to std::string in JSON format.

Used for batch upload to openstudio-server.

std::ostream& openstudio::analysis::toJSON	(	const std::vector< DataPoint > &	dataPoints,
		std::ostream &	os
	)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Classes

Typedefs

Functions

Typedef Documentation

Function Documentation