Files and test files for the thinTree. To be debugged.
jdurand7
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% /* ----------------------------------------------------------------------------
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%
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% * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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% * Atlanta, Georgia 30332-0415
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% * All Rights Reserved
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% * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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%
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% * See LICENSE for the license information
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%
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% * -------------------------------------------------------------------------- */
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%
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% /**
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% * @file testThinBayesTree.cpp
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% * @brief Test of binary tree
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% * @date Sep 14, 2012
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% * @author Frank Dellaert
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% * @author Jean-Guillaume Durand
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% */
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%% Run the tests
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import gtsam.*
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bayesTree = thinBayesTree(3,2);
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EQUALITY('7 = bayesTree.size', 7, bayesTree.size);
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% /* ----------------------------------------------------------------------------
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%
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% * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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% * Atlanta, Georgia 30332-0415
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% * All Rights Reserved
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% * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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%
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% * See LICENSE for the license information
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%
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% * -------------------------------------------------------------------------- */
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%
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% /**
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% * @file testThinTree.cpp
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% * @brief Test of binary tree
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% * @date Sep 13, 2012
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% * @author Frank Dellaert
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% * @author Jean-Guillaume Durand
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% */
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%% Clear working space
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clc, close all, clear all;
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%% Create different trees for our example
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import gtsam.*
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t0 = thinTree(2,1);
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t1 = thinTree(3,2);
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% Add contents in it
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% TODO
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%% Create the set of expected output TestValues
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expectedNumberOfNodes0 = 3;
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expectedNumberOfNodes1 = 7;
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expectedParentsOf6in1 = [3 1];
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expectedParentsOf7in1 = [3 1];
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%% Run the tests
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% Tree depth
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%TODO
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% Number of parents for each node
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%TODO
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% Number of elements
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EQUALITY('expectedNumberOfNodes0,t0.getNumberOfElements', expectedNumberOfNodes0,t0.getNumberOfElements);
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EQUALITY('expectedNumberOfNodes1,t1.getNumberOfElements', expectedNumberOfNodes1,t1.getNumberOfElements);
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% Parents linking
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EQUALITY('expectedParentsOf6in1,t1.getParents(6)', expectedParentsOf6in1,t1.getParents(6));
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EQUALITY('expectedParentsOf7in1,t1.getParents(7)', expectedParentsOf7in1,t1.getParents(7));
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% Adding an element
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bn = thinTreeBayesNet(3,2);
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EQUALITY('7 = bn.size', 7, bn.size);
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% /* ----------------------------------------------------------------------------
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%
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% * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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% * Atlanta, Georgia 30332-0415
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% * All Rights Reserved
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% * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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%
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% * See LICENSE for the license information
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%
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% * -------------------------------------------------------------------------- */
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%
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% /**
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% * @file testThinTree.cpp
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% * @brief Test of binary tree
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% * @date Sep 13, 2012
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% * @author Frank Dellaert
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% * @author Jean-Guillaume Durand
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% */
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%% Run the tests
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import gtsam.*
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bayesNet = thinTreeBayesNet(3,2);
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EQUALITY('7 = bayesNet.size', 7, bayesNet.size);
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function bayesTree = thinBayesTree(depth, width)
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import gtsam.*
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bayesNet = thinTreeBayesNet(depth, width);
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bayesTree = GaussianBayesTree(bayesNet);
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end
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classdef thinTree
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% Attributes
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properties (SetAccess = private)
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nodes = { [] }; % Array of the nodes
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depth = 0; % Depth of the tree
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w = 0 % Number of parents for each node
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links = []; % The matrix representing the links between the nodes
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end
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% Methods
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methods
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% Constructor
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function [obj root_ID] = thinTree(d, w)
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% If 0 input arguments, assume d = 1 and w = 1
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if nargin < 1
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[obj root_ID] = thinTree(1, 1);
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return
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end
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% If 1 input argument, assume w = 1
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if nargin < 1
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[obj root_ID] = thinTree(d, 1);
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return
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end
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% Else
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if w > d-1
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error('MATLAB:thinTree:thinTree', ...
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'Cannot have %d parents on a binary tree of depth %d. You must have nParents < %d here.\n', w, d, d);
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end
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root_ID = 1;
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obj.nodes = cell(2^d - 1,1); % Creation of the d^2 empty cells
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obj.depth = d;
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obj.w = w;
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obj.links = eye(2^d - 1); % Creation of the links matrix
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% Link the cells
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end
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% Function to add a content for a specific node
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function [obj] = addContent(obj, content, nodeID)
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obj.nodes{nodeID} = content;
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return
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end
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% Function to return the ID's of a node's parents
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function ids = getParents(obj, nodeID)
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% Initialisation
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ids = zeros(1,obj.w);
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node = nodeID;
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% Loop on w, the number of parents associated to one node
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for i=1:obj.w
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ids(i) = floor(node/2);
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node = floor(node/2);
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end
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% Return
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return
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end
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% Accessors
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function output = getDepth(obj)
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output = obj.depth;
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return
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end
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function output = getW(obj)
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output = obj.w;
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return
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end
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function output = getNumberOfElements(obj)
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output = 2^obj.depth - 1;
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end
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end % Methods
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end % Class
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function [bayesNet, tree] = thinTreeBayesNet(d,w)
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import gtsam.*
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bayesNet = GaussianBayesNet;
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tree = thinTree(3,2);
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% Filling the tree
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% Creation of the root
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gc = gtsam.GaussianConditional(1, 5*rand(1), 5*rand(1), 3*rand(1));
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% Getting it into the GaussianBayesNet
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bayesNet.push_front(gc);
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for i=1:2^tree.getNumberOfElements()
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% Getting the parents of that node
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parents = tree.getParents(i);
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% Create and link the corresponding GaussianConditionals
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if tree.getW == 1
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% Creation of the GaussianConditional
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gc = gtsam.GaussianConditional(parents(1), 5*rand(1), 5*rand(1));
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% Getting it into the GaussianBayesNet
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bayesNet.push_front(gc);
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% Getting it in the thinTree
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t = tree.addContent({gc,parents}, i);
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elseif tree.getW == 2
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% Creation of the GaussianConditional
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gc = gtsam.GaussianConditional(parents(2), 5*rand(1), 5*rand(1), parents(1), 5*rand(1), 5*rand(1));
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% Getting it into the GaussianBayesNet
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bayesNet.push_front(gc);
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% Getting it in the thinTree
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t = tree.addContent({gc,parents}, i);
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end
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end
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end
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