ParameterSampling.Random Class Reference

Detailed Description

Parameter sampling class producing randomly distributed parameter samples in sparameter space \({\cal M}\).

Definition at line 18 of file Random.m.

Inheritance diagram for ParameterSampling.Random:

Collaboration diagram for ParameterSampling.Random:

Public Member Functions
	Random (nparameters, seed, log_distribution)
	constructor More...
function this =	init_sample (IDetailedModel dmodel)
	initializes the parameter sampling object More...
function size =	size ()
	returns the number of parameter vectors in this sampling More...
Public Member Functions inherited from ParameterSampling.Interface
function please_init =	init_required ()
	returns a boolean indicating whether the object is fully functional, or must be initialized by a call to init_sample(). More...

Public Attributes
	sample
	matrix storing the parameter vectors in the parameter samples as row vectors. More...
	ranges
	cell vector with min and max values for each parameter component
	seed
	a random seed for initialization of the random generator (Default = random value initialized with clock)
	nparameters = 100
	number of parameters in the sample More...
	log_distribution = false
	boolean value determining whether a logarithmic function shall be applied on the uniform distribution of the parameter samples. More...
Public Attributes inherited from ParameterSampling.Interface
	sample
	matrix storing the parameter vectors in the parameter samples as row vectors. More...

Static Public Attributes
static const	method = "twister"
	string specifying the random generator to be used More...

Additional Inherited Members
Protected Attributes inherited from ParameterSampling.Interface
	init_done = false
	boolean indicating whether the object has already been initialized by a call of init_sample(). More...

Constructor & Destructor Documentation

ParameterSampling.Random.Random	(		nparameters,
			seed,
			log_distribution
	)

constructor

Parameters

nparameters	number of parameters in the sample Default: 100
seed	a random seed for initialization of the random generator (Default = random value initialized with clock)
log_distribution	boolean value determining whether a logarithmic function shall be applied on the uniform distribution of the parameter samples. Default: false

Definition at line 92 of file Random.m.

Member Function Documentation

function this = ParameterSampling.Random.init_sample ( IDetailedModel  dmodel )

virtual

initializes the parameter sampling object

Parameters

dmodel

object specifying how the high dimensional data can be computed.

This method initializes the random number generator with the given seed.

Implements ParameterSampling.Interface.

Definition at line 115 of file Random.m.

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function size = ParameterSampling.Random.size ( )

virtual

returns the number of parameter vectors in this sampling

Return values

size	sample size

Implements ParameterSampling.Interface.

Definition at line 130 of file Random.m.

Member Data Documentation

ParameterSampling.Random.log_distribution = false

boolean value determining whether a logarithmic function shall be applied on the uniform distribution of the parameter samples.

Default: false

Definition at line 79 of file Random.m.

ParameterSampling.Random.method = "twister"

static

string specifying the random generator to be used

Default: "twister"

Definition at line 42 of file Random.m.

ParameterSampling.Random.nparameters = 100

number of parameters in the sample

Default: 100

Definition at line 70 of file Random.m.

ParameterSampling.Random.sample

matrix storing the parameter vectors in the parameter samples as row vectors.

Note

This property has the MATLAB attribute Dependent set to true.

This property has non-standard access specifiers: SetAccess = Private, GetAccess = Public

Matlab documentation of property attributes.

[readonly]

Definition at line 28 of file Random.m.

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

• rbasis/basisgen/oop/+ParameterSampling/Random.m