Interface.m

classdef Interface < handle
  % %Interface class for all kind of reduced basis generation algorithms
  %
  %

  properties (Abstract, SetAccess=private, Dependent)

    % string specifying the detailed data produced by this basis generation
    % algorithm object.
    %
    % This should be one of
    %  - 'ei'   : for empirical interpolation basis
    %  - 'rb'   : for reduced basis
    %  - 'eirb' : for combination fo empirical interpolation and reduced basis
    generated_basis_type;

    % This is an id string inherited by the underlying extension algorithm
    % object implementing a Greedy.Plugin.Interface.
    %
    % At the moment this id is not used.
    id;
  end


  properties (SetAccess = protected)
    % control variable of type boolean variable controlling whether check
    % points shall be created after every reduced basis extension step.
    enable_checkpointing = true;
  end

  methods

    function summ = horzcat(varargin)
    % function summ = horzcat(varargin)
    % combines an arbitrary number of basis generation algorithms
    %
    % This constructs a Greedy.Combined object from a horizontal
    % concatenation of basis generation objects.
    %
    % Example usage:
    %  @code
    %  sum = [ [ ei_greedy1, ei_greedy2, ei_greedy3 ], rb_greedy ];
    %  @endcode
    %
    % Return values:
    %   summ: the constructed object of type Greedy.Combined
      summ = Greedy.Combined(varargin{:});
    end

    %function this = set.Mstrich(this, value)
    %  this.model.Mstrich = value;
    %  if this.model.Mstrich == 0
    %    this.model.enable_error_estimator = false;
    %  else
    %    this.model.enable_error_estimator = true;
    %  end
    %end


    function detailed_data = gen_detailed_data(this, rmodel, detailed_data, checkpoint)
      % function detailed_data = gen_detailed_data(this, rmodel, detailed_data, [checkpoint])
      % main entry function construction the detailed data tree storing the
      % reduced basis functions.
      %
      % This method starts the reduced basis generation process, by calling the
      % abstract interface methods init_basis() and basis_extension()
      % subsequently. If enable_checkpointing is set to 'true', checkpoint
      % shall be created periodically storing all data necessary to resume from
      % this point in the algorithm, when the checkpoint is given as the
      % optional third argument.
      %
      % Parameters:
      %  rmodel:        object of type IReducedModel providing descriptions of
      %                 the entire model needed for basis generation.
      %  detailed_data: either a struct containing high dimensional model data
      %                 needed to execute detailed simulations or an object of
      %                 type Greedy.DataTree.Detailed.INode in case of resume from a
      %                 checkpoint.
      %  checkpoint: object of type Greedy.Checkpoint specifying a given point in the
      %              algorithm where it basis generation can be resumed.
      %
      % Return values:
      %  detailed_data: object of type Greedy.DataTree.Detailed.INode storing the reduced
      %                 basis information in the leaf nodes and information on
      %                 the reduced basis generation in every node.
      if nargin == 3 || isempty(checkpoint)
        checkpoint = Greedy.Checkpoint;
      end
      % is the initially generated reduced basis not yet stored in detailed_data?
      if ~get(checkpoint, 'init_basis_computed', false)
        prepare(this, rmodel, detailed_data);
        detailed_data = init_basis(this, rmodel, detailed_data);
      end
      checkpoint = checkpoint.store(rmodel, detailed_data, 'gen_detailed_data', struct('init_basis_computed', true));
      detailed_data = basis_extension(this, rmodel, detailed_data, checkpoint.child([]));
      rmodel.N = get_rb_size(detailed_data);
      %rmodel.M = get_ei_size(detailed_data) - rmodel.Mstrich;
    end


  end

  methods (Abstract)

    % initialization routine for basis extension
    %
    % This method is run by the gen_detailed_data() method before the execution
    % of the init_basis() methods and should be used for preparation purposes,
    % like
    %  - initialization of the training and validation parameter space and
    %  - caching detailed simulations if necessary.
    prepare(this, rmodel, model_data);

    % construction of an initial reduced basis
    %
    % This method is called at the beginning of the gen_detailed_data() method
    % right after a call to prepare(). It should be used to construct an
    % initial reduced basis, e.g. approximating the initial value functions in
    % case of evolution problems.
    %
    % Return values:
    %  detailed_data: object of type Greedy.DataTree.Detailed.INode storing the reduced
    %                 basis information in the leaf nodes and information on
    %                 the reduced basis generation in every node.
    detailed_data = init_basis(this, rmodel, model_data);

    % basis extension routine
    %
    % This method is run by the gen_detailed_data() method at the very end, and
    % shall actually construct the reduced basis.
    %
    % Parameter values:
    %   checkpoint: an object of type GreedyCheckpoint used for
    %               checkpointing.
    %
    % Return values:
    %  detailed_data: object of type Greedy.DataTree.Detailed.INode storing the reduced
    %                 basis information in the leaf nodes and information on
    %                 the reduced basis generation in every node.
    detailed_data = basis_extension(this, rmodel, detailed_data, checkpoint);

    % error indication routine
    %    [max_errs, max_err_sequence, max_mu_index] = error_indicators(this, detailed_data, parameter_set, reuse_reduced_data);


  end

  methods (Hidden = true)
    function value = get_generated_basis_type(this)
      % function value = get_generated_basis_type(this)
      % returns the #generated_basis_type property. Why???
      value = this.generated_basis_type;
    end
  end

end