33 namespace distributionModels
49 minValue_(
readScalar(distributionModelDict_.lookup(
"minValue"))),
50 maxValue_(
readScalar(distributionModelDict_.lookup(
"maxValue"))),
51 d_(
readScalar(distributionModelDict_.lookup(
"d"))),
52 n_(
readScalar(distributionModelDict_.lookup(
"n")))
61 minValue_(p.minValue_),
62 maxValue_(p.maxValue_),
78 scalar
K = 1.0 -
exp(-
pow((maxValue_ - minValue_)/d_, n_));
80 scalar
x = minValue_ + d_*
::pow(-
log(1.0 - y*K), 1.0/n_);
dimensionedScalar log(const dimensionedScalar &ds)
Random & rndGen_
Reference to the random number generator.
A list of keyword definitions, which are a keyword followed by any number of values (e...
virtual scalar sample() const
Sample the distributionModel.
CGAL::Exact_predicates_exact_constructions_kernel K
Macros for easy insertion into run-time selection tables.
Type sample01()
Advance the state and return a sample of a given type from a.
dimensionedScalar exp(const dimensionedScalar &ds)
RosinRammler(const dictionary &dict, Random &rndGen)
Construct from components.
bool readScalar(const char *buf, doubleScalar &s)
Read whole of buf as a scalar. Return true if successful.
defineTypeNameAndDebug(exponential, 0)
Rosin-Rammler distributionModel.
dimensionedScalar pow(const dimensionedScalar &ds, const dimensionedScalar &expt)
virtual scalar minValue() const
Return the minimum value.
virtual ~RosinRammler()
Destructor.
virtual scalar meanValue() const
Return the mean value.
A library of runtime-selectable distribution models.
virtual scalar maxValue() const
Return the maximum value.
addToRunTimeSelectionTable(distributionModel, exponential, dictionary)