RandomSampler Selects Samples many random parameters. More...

Detailed Description

RandomSampler Selects Samples many random parameters.

Author: Daniel Wirtz

Date: 2011-10-11

New in 0.7:: (Daniel Wirtz, 2013-02-22) Added a new property Spacing to also allow for logarithmical sampling over the parameter ranges.

New in 0.5:: (Daniel Wirtz, 2011-10-11) Added this class (former version renamed to WeightedRandomSampler)

Definition at line 18 of file RandomSampler.m.

Public Member Functions
	RandomSampler ()

function matrix < double > samples =	performSampling (params)
	Randomly generates input samples by choosing params and time parameter by chance. More...

Public Member Functions inherited from sampling.BaseSampler
function samples =	generateSamples (models.BaseFullModel model)

virtual function samples =	performSampling ()
	Template method for actual sampling. More...

Public Member Functions inherited from KerMorObject
	KerMorObject ()
	Constructs a new KerMor object. More...

function	display ()
	disp(object2str(this)); More...

function bool =	eq (B)
	Checks equality of two KerMor objects. More...

function bool =	ne (B)
	Checks if two KerMorObjects are different. More...

function cn =	getClassName ()
	Returns the simple class name of this object without packages. More...

Public Member Functions inherited from DPCMObject
	DPCMObject ()
	Creates a new DPCM object. More...

	DPCMObject ()

Static Public Member Functions
static function res =	test_DomainSampling ()
	setup parameter domain etc domain are all points in unit square with norm > 0.7 More...

Static Public Member Functions inherited from sampling.BaseSampler
static function res =	test_SubsetSampling ()
	setup parameter domain etc domain are all points in unit square with norm > 0.7 More...

Public Attributes
	Samples = 30
	The number of samples to take. More...

integer	Seed = "[]"
	The seed for the random number generator. More...

Public Attributes inherited from sampling.BaseSampler
sampling.Domain	Domain = "[]"
	A domain from which the produced/generated samples may come from. Use in subclasses at the sampling.BaseSampler.performSampling method. More...

Public Attributes inherited from DPCMObject
	WorkspaceVariableName = ""
	The workspace variable name of this class. Optional. More...

	ID = "[]"
	An ID that allows to uniquely identify this DPCMObject (at least within the current MatLab session/context). More...

	PropertiesChanged = "[]"
	The Dictionary containing all the property settings as key/value pairs. More...

Public Attributes inherited from handle
	addlistener
	Creates a listener for the specified event and assigns a callback function to execute when the event occurs. More...

	notify
	Broadcast a notice that a specific event is occurring on a specified handle object or array of handle objects. More...

	delete
	Handle object destructor method that is called when the object's lifecycle ends. More...

	disp
	Handle object disp method which is called by the display method. See the MATLAB disp function. More...

	display
	Handle object display method called when MATLAB software interprets an expression returning a handle object that is not terminated by a semicolon. See the MATLAB display function. More...

	findobj
	Finds objects matching the specified conditions from the input array of handle objects. More...

	findprop
	Returns a meta.property objects associated with the specified property name. More...

	fields
	Returns a cell array of string containing the names of public properties. More...

	fieldnames
	Returns a cell array of string containing the names of public properties. See the MATLAB fieldnames function. More...

	isvalid
	Returns a logical array in which elements are true if the corresponding elements in the input array are valid handles. This method is Sealed so you cannot override it in a handle subclass. More...

	eq
	Relational functions example. See details for more information. More...

	transpose
	Transposes the elements of the handle object array. More...

	permute
	Rearranges the dimensions of the handle object array. See the MATLAB permute function. More...

	reshape
	hanges the dimensions of the handle object array to the specified dimensions. See the MATLAB reshape function. More...

	sort
	ort the handle objects in any array in ascending or descending order. More...

Static Protected Member Functions
static function obj =	loadobj (obj)

Static Protected Member Functions inherited from sampling.BaseSampler
static function obj =	loadobj (obj, from)

Static Protected Member Functions inherited from DPCMObject
static function obj =	loadobj (obj, from)
	Re-register any registered change listeners! More...

static function obj =	loadobj (obj, from)

Additional Inherited Members
Protected Member Functions inherited from KerMorObject
function	checkType (obj, type)
	Object typechecker. More...

Protected Member Functions inherited from DPCMObject
function	registerProps (varargin)
	Call this method at any class that defines DPCM observed properties. More...

function	registerProps (varargin)

Constructor & Destructor Documentation

sampling.RandomSampler.RandomSampler ( )

Definition at line 72 of file RandomSampler.m.

References DPCMObject.registerProps().

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Member Function Documentation

static function obj = sampling.RandomSampler.loadobj ( obj )

staticprotected

Definition at line 196 of file RandomSampler.m.

function matrix< double > samples = sampling.RandomSampler.performSampling ( params )

Randomly generates input samples by choosing params and time parameter by chance.

Parameters

model the full or reduced model

Return values

samples the randomly chosen parameters, number of rows equal to number of model's parameters, number of columns as specified in property Samples

Definition at line 89 of file RandomSampler.m.

References sampling.Domain.filter(), sampling.Domain.Points, Samples, Seed, handle.sort, and t.

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function res = sampling.RandomSampler.test_DomainSampling ( )

static

setup parameter domain etc domain are all points in unit square with norm > 0.7

Definition at line 166 of file RandomSampler.m.

References all(), and Norm.L2().

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Member Data Documentation

sampling.RandomSampler.Samples = 30

The number of samples to take.

Property class critical:: Determines how many parameter samples are taken and thus directly the offline computation time and model approximation quality.

Default: 30

Note: This property has the MATLAB attribute SetObservable set to true.; Matlab documentation of property attributes.; This property has custom functionality when its value is changed.

Definition at line 36 of file RandomSampler.m.

Referenced by sampling.WeightedRandomSampler.performSampling(), and performSampling().

sampling.RandomSampler.Seed = "[]"

The seed for the random number generator.

If empty, a seed computed from the cputime is used.

Property class optional:: Set to empty for new choices on every run.

Default: []

Note: This property has the MATLAB attribute SetObservable set to true.; Matlab documentation of property attributes.

Definition at line 52 of file RandomSampler.m.

Referenced by performSampling().

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

core/+sampling/RandomSampler.m

Detailed Description

Public Member Functions

Static Public Member Functions

Public Attributes

Static Protected Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation