function y = pred_tree(tree, X)%% Predict using a tree structure returned from grow_tree.%% Predict the outputs from a tree given some inputs (X).% The tree will have been returned from the the utility% grow_tree (or from the methods rbf_rt_1 or rbf_rt_2).%% For further details of the function see:%%  'Matlab Routines for RBF Networks', 1999.% prog = 'pred_tree';% Check arguments.if nargin ~= 2  error([prog ': needs two arguments'])endif ~isstruct(tree)  error([prog ': first arg (tree) needs to be a struct'])endif ~(isnumeric(X) & ndims(X) == 2)  error([prog ': second arg (X) needs to be a numerical matrix'])end% Check dimensionality.[d,p] = size(X);if tree.d ~= d  error([prog ': tree and inputs do not share same dimension'])end% Recurse down the tree.y = downTree(tree, X, 1);function y = downTree(t, X, k)% Which node are we at?n = t.node(k);% Are we at a terminal node?if isempty(n.split)  % Give these inputs the node's average value.    y = n.ave * ones(size(X,2),1);  else    % Divide.  s = n.split;  l = find(X(s.dim,:) <= s.val);  r = find(X(s.dim,:) > s.val);      % Recurse.  yl = downTree(t, X(:,l), s.l);  yr = downTree(t, X(:,r), s.r);      % Recombine.  y = zeros(size(X,2),1);  y(l) = yl;  y(r) = yr;    end