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diff --git a/BNW_parameter_learning/readInputData.m b/BNW_parameter_learning/readInputData.m
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+function  [ labels , node_sizes, cases, data] = readInputData( dfile , nnodes )
+	%  readColData  reads data from a file containing data in columns
+	%               that have text titles, and possibly other header text
+	%   
+	%  Input:
+	%     dfile  = name of the file containing the data.(required)
+	%     nnodes  = number of columns in the data file.  (required)
+    %
+    %   Function assumes the following format for the input file:
+    %       1) First line has labels for each of the nodes.  There cannot
+    %              be spaces in any node label.
+    %       2) The next line is the "node_sizes" of the nodes.  If the 
+    %           nodes are discrete, this number will be equal to the number
+    %           of states.  If the nodes are continuous, they should be 
+    %           equal to 1.  The function assumes that any nodes with
+    %           node_size = 1 is continuous.
+    %       3) The rest of the file is numeric data.  The data in the input
+    %               data has the number of columns equal to the number of 
+    %               nodes in the network and the number of rows equal to
+    %               the number of samples.
+    %
+    %
+	%  Output:
+	%     labels = cell array with node (column) labels.
+    %     node_sizes  =  vector with the size of each node
+    %     cases = cell array with the data.  The cases array is transposed
+    %       in comparison with the input data to agree with the format of
+    %       cell data used in BNT.
+
+%  open file for input, include error handling
+fin = fopen(dfile,'r');
+if fin < 0
+   error(['Could not open ',dfile,' for input']);
+end
+
+% Read in first line to get the node labels.
+labels = cell(1,nnodes);
+buffer = fgetl(fin);    %get header line as a string
+for j=1:nnodes
+    [next,buffer] = strtok(buffer);
+    labels{j} = next;
+end
+
+%  Read in the data.  Use the vetorized fscanf function to load all
+%  numerical values into one vector.  Then reshape this vector into a
+%  matrix.
+
+data = fscanf(fin,'%f');  %  Load the numerical values into one long vector
+
+
+
+
+nd = length(data);        %  total number of data points
+nr = nd/nnodes;            %  number of rows; check (next statement) to make sure
+if nr ~= round(nd/nnodes)
+   fprintf(1,'\ndata: nrow = %f\tncol = %d\n',nr,nnodes);
+   fprintf(1,'number of data points = %d does not equal nrow*ncol\n',nd);
+   error('data is not rectangular')
+end
+
+data = reshape(data,nnodes,nr)';   %  have to transpose the reshaped array
+
+
+node_sizes = zeros(1,nnodes);
+for j = 1:nnodes
+    node_sizes(j) = data(1,j);
+end
+
+nr = nr - 1;
+data(1,:) = [];
+cases = cell(nnodes,nr);
+cases(:,:) = num2cell(data');
+
+end
+%  end of readInputData.m
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