distributionModel Class Reference

A library of runtime-selectable distribution models. More...

Inheritance diagram for distributionModel:

Collaboration diagram for distributionModel:

Public Member Functions
	TypeName ("distributionModel")
	Runtime type information. More...
	declareRunTimeSelectionTable (autoPtr, distributionModel, dictionary,(const dictionary &dict, Random &rndGen),(dict, rndGen))
	Declare runtime constructor selection table. More...
	distributionModel (const word &name, const dictionary &dict, Random &rndGen)
	Construct from dictionary. More...
	distributionModel (const distributionModel &p)
	Construct copy. More...
virtual autoPtr< distributionModel >	clone () const =0
	Construct and return a clone. More...
virtual	~distributionModel ()
	Destructor. More...
virtual scalar	sample () const =0
	Sample the distributionModel. More...
virtual scalar	minValue () const =0
	Return the minimum value. More...
virtual scalar	maxValue () const =0
	Return the maximum value. More...
virtual scalar	meanValue () const =0
	Return the maximum value. More...

Static Public Member Functions
static autoPtr< distributionModel >	New (const dictionary &dict, Random &rndGen)
	Selector. More...

Protected Member Functions
virtual void	check () const
	Check that the distribution model is valid. More...

Protected Attributes
const dictionary	distributionModelDict_
	Coefficients dictionary. More...
Random &	rndGen_
	Reference to the random number generator. More...

Detailed Description

A library of runtime-selectable distribution models.

Returns a sampled value given the expectation (nu) and variance (sigma^2)

Current distribution models include:

• exponential
• fixedValue
• general
• multi-normal
• normal
• Rosin-Rammler
• Mass-based Rosin-Rammler
• uniform

The distributionModel is tabulated in equidistant nPoints, in an interval. These values are integrated to obtain the cumulated distribution model, which is then used to change the distribution from unifrom to the actual distributionModel.

Source files

• distributionModel.H
• distributionModel.C
• distributionModelNew.C

Definition at line 70 of file distributionModel.H.

Constructor & Destructor Documentation

distributionModel() [1/2]

distributionModel	(	const word &	name,
		const dictionary &	dict,
		Random &	rndGen
	)

Construct from dictionary.

Definition at line 65 of file distributionModel.C.

distributionModel() [2/2]

distributionModel

(

const distributionModel &

p

)

Construct copy.

Definition at line 77 of file distributionModel.C.

~distributionModel()

~distributionModel ( )

virtual

Destructor.

Definition at line 88 of file distributionModel.C.

Member Function Documentation

check()

void check ( ) const

protectedvirtual

Check that the distribution model is valid.

Definition at line 41 of file distributionModel.C.

References Foam::abort(), Foam::FatalError, FatalErrorInFunction, distributionModel::maxValue(), distributionModel::minValue(), Foam::nl, and Foam::type().

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TypeName()

TypeName

(

"distributionModel"

)

Runtime type information.

declareRunTimeSelectionTable()

declareRunTimeSelectionTable	(	autoPtr	,
		distributionModel	,
		dictionary	,
		(const dictionary &dict, Random &rndGen)	,
		(dict, rndGen)
	)

Declare runtime constructor selection table.

clone()

virtual autoPtr<distributionModel> clone ( ) const

pure virtual

Construct and return a clone.

Implemented in general, binned, massRosinRammler, multiNormal, normal, RosinRammler, exponential, uniform, and fixedValue.

New()

Foam::autoPtr< Foam::distributionModel > New ( const dictionary &  dict, Random &  rndGen  )

static

Selector.

Definition at line 34 of file distributionModelNew.C.

References dict, Foam::endl(), Foam::exit(), Foam::FatalIOError, FatalIOErrorInLookup, Foam::Info, and rndGen.

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sample()

virtual scalar sample ( ) const

pure virtual

Sample the distributionModel.

Implemented in general, binned, massRosinRammler, multiNormal, normal, RosinRammler, exponential, uniform, and fixedValue.

minValue()

virtual scalar minValue ( ) const

pure virtual

Return the minimum value.

Implemented in general, binned, massRosinRammler, multiNormal, normal, RosinRammler, exponential, uniform, and fixedValue.

Referenced by distributionModel::check().

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maxValue()

virtual scalar maxValue ( ) const

pure virtual

Return the maximum value.

Implemented in general, binned, massRosinRammler, multiNormal, normal, RosinRammler, exponential, uniform, and fixedValue.

Referenced by distributionModel::check().

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meanValue()

virtual scalar meanValue ( ) const

pure virtual

Return the maximum value.

Implemented in general, binned, massRosinRammler, multiNormal, normal, RosinRammler, exponential, uniform, and fixedValue.

Member Data Documentation

distributionModelDict_

const dictionary distributionModelDict_

protected

Coefficients dictionary.

Definition at line 78 of file distributionModel.H.

rndGen_

Random& rndGen_

protected

Reference to the random number generator.

Definition at line 81 of file distributionModel.H.

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The documentation for this class was generated from the following files:

• src/lagrangian/distributionModels/distributionModel/distributionModel.H
• src/lagrangian/distributionModels/distributionModel/distributionModel.C
• src/lagrangian/distributionModels/distributionModel/distributionModelNew.C