test_data_tree.m

function ok = test_data_tree
  ok = true;

  %% TPartDataNode test
  tpart_map1 = [0 5 7 10];
  tpart_map2 = [0 2 7 10];

  tpart_init1 = arrayfun(@(x) DataTree.DummyLeafNode(x), [1 2 3], 'UniformOutput', false);
  tpart_init2 = arrayfun(@(x) DataTree.DummyLeafNode(x), [4 5 6], 'UniformOutput', false);

  tpart1 = DataTree.TpartNode(tpart_map1, tpart_init1, 1);
  tpart2 = DataTree.TpartNode(tpart_map2, tpart_init2, 1);

  %% first IdMapDataNode
  idmap = {'id1', 'id2'};
  initvalues = {tpart1, tpart2};

  idnode1 = DataTree.IdMapNode(idmap, initvalues);

  %% second IdMapDataNode (note the nesting of idmaps)
  idmap2 = {idmap, 'id3'};

  idnode2 = DataTree.DummyLeafNode(7);

  idnode3 = DataTree.IdMapNode(idmap2, {idnode1, idnode2});

  display(idnode3);
%  keyboard

  ok = ok & (get(idnode3,[idnode3.get_index('id2', [], 3),1]) == 5);
  ok = ok & (get(idnode3,[idnode3.get_index('id1', [], 3),1]) == 1);
  ok = ok & (get(idnode3,[idnode3.get_index('id2', [], 6.999),1]) == 5);
  ok = ok & (get(idnode3,[idnode3.get_index('id2', [], 7),1]) == 6);
  ok = ok & (get(idnode3,[idnode3.get_index('id2', [], 10),1]) == 6);
  ok = ok & (get(idnode3,[idnode3.get_index('id2', [], 9),1]) == 6);

  %% test the MergedTreeCreatorIf
  % here e.g. detailed data containers could be used for initialization
  merger1     = DataTree.DummyMerger({'id1'});
  mergedtree1 = merger1.merge(idnode2, idnode1);
  ok = ok & (isequal(get(mergedtree1,[mergedtree1.get_index('id1',[],3),1]), '7+1'));
  ok = ok & (isequal(get(mergedtree1,[mergedtree1.get_index('id2',[],3),1]), '7+1'));
  merger2     = DataTree.DummyMerger({'id1','id2'});
  mergedtree2 = merger2.merge(idnode2, idnode1);
  ok = ok & (isequal(get(mergedtree2,[mergedtree2.get_index('id1',[],3),1]), '7+1'));
  ok = ok & (isequal(get(mergedtree2,[mergedtree2.get_index('id2',[],3),1]), '7+5'));
%  ok = ok & (get(
  %  filter = [];
  %  construct(mdatatree, filter);

end

%% Two applications for MergedTreeCreator:
%    - combine (1) ei ops with rb and (2) compute rb overlaps
%       1.   merge at RBEIDetailedData.gen_reduced_data for each id in ei part
%            using "id regions, tpart_regions, mu_part_regions".
%       1.1. in new nodes link to reduced_data of ei and rb
%       1.2. compute merged data from detailed_data from ei and rb
%
%       2.   merge at TPartDetailedData.gen_reduced_data for each right_overlap
%            using "tpart_regions, mu_part_regions". The id should always be
%            the same.
%       2.1. in new nodes link to reduced_data of left and right intervals
%       2.2. compute merged data from detailed_data from left and right rb
%
% So we can and need assume, that indices in reduced_data are the same as in detailed_data