about summary refs log tree commit diff
path: root/sourcecodes/parameter_learning/code_backup/readInput.m
diff options
context:
space:
mode:
Diffstat (limited to 'sourcecodes/parameter_learning/code_backup/readInput.m')
-rw-r--r--sourcecodes/parameter_learning/code_backup/readInput.m63
1 files changed, 0 insertions, 63 deletions
diff --git a/sourcecodes/parameter_learning/code_backup/readInput.m b/sourcecodes/parameter_learning/code_backup/readInput.m
deleted file mode 100644
index 891d7f36..00000000
--- a/sourcecodes/parameter_learning/code_backup/readInput.m
+++ /dev/null
@@ -1,63 +0,0 @@
-function [ labels, cases, bnet, node_sizes, data,labelsold] = readInput( dfile, sfile, nnodes, std_flag )
-    %readInput is to be used when reading in a network with a known structure
-    %   
-    %Input:
-	%   dfile  = name of the file containing the data (required)
-    %   sfile = name of the file containing the structure (required)
-    %   nnodes = number of nodes in the network (required)
-    %   std_flag = flag for whether or not to standardize the data.
-    %   (optional-- Default is FALSE)
-    %
-    %   See readInputData.m and readInputStructure.m for description of the
-    %       format of the dfile and sfile, respectively. 
-    %
-    %Output:
-    %   labels = cell array with the names of the nodes.
-    %   cases = cell array with the data.
-    %   bnet = BNT bayesian network with the input structure.
-
-if nargin < 4
-    std_flag = false(1);
-end
-
-    
-% read in the file with the data
-[labelsold,node_sizes,cases, data] = readInputData(dfile,nnodes);
-
-
-% read in the file with the structure
-[dag] = readInputStructure(sfile,labelsold);
-
-
-% check the ordering of the nodes and reorder if necessary
-[labels,cases,dag,node_sizes,ord_flag] = checkStructure(labelsold,cases,dag,node_sizes);
-
-dcount = 0;
-for i = 1:nnodes
-    if node_sizes(i) ~= 1
-        dcount = dcount + 1;
-    end
-end
-discrete = zeros(1,dcount);
-dcount = 0;
-for i = 1:nnodes
-    if node_sizes(i) ~= 1
-        dcount = dcount + 1;
-        discrete(dcount) = i;
-    end
-end
-
-bnet = mk_bnet(dag,node_sizes,'discrete',discrete,'names',labels);
-
-%bnet.dag
-
-checkDiscreteNodes(bnet,cases);
-
-% standardize continuous data to have a mean = 0 and std = 1
-if (std_flag)
-    [cases] = standardizeData(labels,node_sizes,cases);
-end
-        
-
-end
-%  end of readInput.m