Detailed Description

a default reduced data implementation which stores a data tree object copying the structure of a Greedy.User.IDetailedData.datatree as returned by the greedy algorithm objects.

This is also a DataTree.CreatorDefault object which copies the tree structure of detailed data tree. The user only needs to define how the leaf elements of this reduced data tree storing the actual reduced matrices and vectors shall be constructed. Such leaf elements should be derived from Greedy.User.IReducedDataNode.

See also: Greedy.DataTree.Detailed.INode for more details on the detailed data tree.

Definition at line 19 of file ReducedData.m.

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Public Member Functions
	ReducedData (Greedy.User.IReducedModel rmodel,Greedy.User.IDetailedData detailed_data)
	constructor either constructing a reduced data object from a detailed data object or copying a reduced data object and extracting smaller reduced vectors and matrices. More...

function Greedy.User.ReducedData subset_reduced_data =	extract_reduced_data_subset (Greedy.User.ReducedData rmodel)
	Changes the size of the offline data matrices. More...

function conds =	get_conds ()

function Greedy.User.IReducedDataNode reduced_data_leaf =	get_leaf (Greedy.User.IReducedModel rmodel)
	returns the reduced data tree leaf node for a specific combination of parameters and time indices given by the reduced model. More...

function Greedy.User.IReducedDataNode node =	create_leaf_node (arg_node, basepath, mu_cube, tslice)
	This creates the actual reduced data leafs implementing the Greedy.User.IReducedDataNode interface. More...

Public Member Functions inherited from IReducedData
virtual function IReducedData subset_reduced_data =	extract_reduced_data_subset (rmodel)
	Changes the size of the offline data matrices. More...

Public Member Functions inherited from DataTree.CreatorDefault
function node =	create_tpart_node (t_part_map, initvalues)
	is called on DataTree.PpartNode elements of a DataTree and returns a new p-part node out of it. More...

function node =	create_idmap_node (id_map, initvalues)
	is called on DataTree.IdMapNode elements of a DataTree and returns a new ID mapped node out of it. More...

function node =	create_ppart_node (p_part_map, initvalues)
	is called on DataTree.PpartNode elements of a DataTree and returns a new p-part node out of it. More...

Public Member Functions inherited from DataTree.ICreator
virtual function DataTree.ILeafNode node =	create_leaf_node (DataTree.ILeafNode arg_node, basepath, mu_cube, tslice)
	is called on leaf elements of a DataTree and returns a new leaf out of it. More...

Public Attributes
	N
	number of reduced basis vectors stored in this data node. More...

	M
	number of collateral reduced basis vectors stored in this data node. More...

	Mstrich
	number of collateral reduced basis vectors used for error estimation. More...

DataTree.INode	datatree
	the actual data tree More...

	create_tree_opts
	struct with transient options for the create_leaf_node() method. More...

Protected Member Functions
function	fill_data (Greedy.User.IReducedModel rmodel,IDetailedData detailed_data)
	defines how the datatree member is being filled with data. More...

Constructor & Destructor Documentation

Greedy.User.ReducedData.ReducedData	(	Greedy.User.IReducedModel	rmodel,
		Greedy.User.IDetailedData	detailed_data
	)

constructor either constructing a reduced data object from a detailed data object or copying a reduced data object and extracting smaller reduced vectors and matrices.

The two possible synopsis for this functions

reduced_data = Greeedy.User.ReducedData(rmodel, detailed_data) and

rd_subset = Greeedy.User.ReducedData(rmodel, reduced_data)

        .Greedy.User.ReducedData object to be copied.

Parameters

rmodel	an object describing the reduced numerical scheme. For synopsis (1) it defines via the option bg_descr.reduced_data_constructor the type of the leaf elements in the reduced data tree and for synopsis (2) it defines the size of the reduced matrices and vectors in the copied object by the member variables N, and in case of enabled empirical interpolation also by M and Mstrich.
detailed_data	By default, this is a detailed data object or in case of synposis (2) a

Definition at line 108 of file ReducedData.m.

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Member Function Documentation

function Greedy.User.IReducedDataNode node = Greedy.User.ReducedData.create_leaf_node	(	arg_node,
		basepath,
		mu_cube,
		tslice
	)

This creates the actual reduced data leafs implementing the Greedy.User.IReducedDataNode interface.

Parameters

arg_node	original leaf which shall be used as basis for the creation of a new one.
basepath	path from the root element to the current leaf.
mu_cube	restriction of the parameter as described in Sub-tree definition
tslice	restriction of the time domain as described in Sub-tree definition

Return values

node	the freshly generated leaf element

Note: The arg_node argument can be either a Greedy.User.IDetailedData implementation or a Greedy.User.IReducedDataNode object. (c.f. constructor description for more information on these two variants)

Definition at line 216 of file ReducedData.m.

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function Greedy.User.ReducedData subset_reduced_data = Greedy.User.ReducedData.extract_reduced_data_subset ( Greedy.User.ReducedData rmodel )

Changes the size of the offline data matrices.

Depending on the values of

the size of the offline data matrices is reduced and a copy with the smaller data is returned.

Parameters

rmodel rmodel

Return values

subset_reduced_data a copy of the reduced data with reduced offline matrices and vectors

Definition at line 161 of file ReducedData.m.

function Greedy.User.ReducedData.fill_data	(	Greedy.User.IReducedModel	rmodel,
		IDetailedData	detailed_data
	)

protected

defines how the datatree member is being filled with data.

If not overwritten, this method copies the tree structure of the given detailed data object and computes the reduced matrices and vectors in the leaf elements.

Note: The second arguments does not need to wrap a detailed data tree, as the Greedy.User.IDetailedData objects do. If no tree is given, a reduced data tree with only a root element is created.

Parameters

rmodel	object specifying how the reduced simulations can be computed.
detailed_data	object defining the basis generation algorithm and storage for storing high dimensional data, i.e. dependent on dimension \(H\). This data is necessary for detailed simulations, construction of online matrices, `reduced_data` and reconstruction of reduced simulations.

Optional fields of detailed_data:

datatree — the actual generated data tree

Definition at line 278 of file ReducedData.m.

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function Greedy.User.IReducedDataNode reduced_data_leaf = Greedy.User.ReducedData.get_leaf ( Greedy.User.IReducedModel rmodel )

returns the reduced data tree leaf node for a specific combination of parameters and time indices given by the reduced model.

Parameters

rmodel object specifying how the reduced simulations can be computed.

Return values

reduced_data_leaf object which actually stores the reduced vectors and matrices needed for online simulations.

Required fields of rmodel:

detailed_model — detailed model

Definition at line 181 of file ReducedData.m.

Member Data Documentation

Greedy.User.ReducedData.create_tree_opts

struct with transient options for the create_leaf_node() method.

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

Definition at line 94 of file ReducedData.m.

Greedy.User.ReducedData.datatree

the actual data tree

The leaf elements have are objects of the class type Greedy.User.IReducedDataNode

Definition at line 81 of file ReducedData.m.

Greedy.User.ReducedData.M

number of collateral reduced basis vectors stored in this data node.

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 55 of file ReducedData.m.

Greedy.User.ReducedData.Mstrich

number of collateral reduced basis vectors used for error estimation.

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 67 of file ReducedData.m.

Greedy.User.ReducedData.N

number of reduced basis vectors stored in this data node.

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 43 of file ReducedData.m.

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

rbasis/basisgen/oop/+Greedy/+User/ReducedData.m

Detailed Description

Public Member Functions

Public Attributes

Protected Member Functions

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation