Bug fixes, code comments, and minor changes

1 files changed, 151 insertions, 0 deletions

diff --git a/sourcecodes/parameter_learning/code_backup/writeParameters_ev.m b/sourcecodes/parameter_learning/code_backup/writeParameters_ev.m
new file mode 100644
index 00000000..fc24e2e5
--- /dev/null
+++ b/sourcecodes/parameter_learning/code_backup/writeParameters_ev.m
@@ -0,0 +1,151 @@
+function [] = writeParameters_ev(pre,bnet,nnodes,labels,cases,stdevs,means,selectvar,selectdata)
+%Writes a file that contains the parameters of the network after entering evidence.
+
+%Read in original node labels to get node IDs.
+infile = strcat(pre,'continuous_input.txt');
+fin = fopen(infile,'r');
+labelsold = cell(1,nnodes);
+buffer = fgetl(fin);
+for j = 1:nnodes
+    [next,buffer] = strtok(buffer);
+    labelsold{j} = next;
+end
+fclose(fin);
+
+
+evidence = cell(1,nnodes);
+engine = jtree_inf_engine(bnet);
+
+m = size(selectvar,1);
+
+%%Get the types of the nodes.
+typefile = strcat(pre,'type.txt');
+ftype = fopen(typefile,'r');
+types = cell(1,nnodes);
+buffer = fgetl(ftype);
+buffer = fgetl(ftype);
+for j = 1:nnodes
+   [next,buffer] = strtok(buffer);
+   types{j} = uint16(str2num(next));
+end
+
+max_states = 0;
+disc_nodes = 0;
+for j = 1:nnodes
+  if types{j} > max_states
+       max_states = types{j};
+  end
+  if types{j} > 1
+    disc_nodes = disc_nodes + 1;
+  end
+end
+
+%Add 1 to max_states to account for node name
+max_states = max_states + 1;
+
+%%Get mapping of discrete levels.
+levelfile = strcat(pre,'nlevels.txt');
+flevels = fopen(levelfile,'r');
+levels = cell(disc_nodes,max_states);
+ndisc_nodes = 0;
+for i=1:disc_nodes
+	ndisc_nodes = ndisc_nodes + 1;
+buffer = fgetl(flevels);
+for j = 1:max_states
+	  [next,buffer] = strtok(buffer);
+       if j == 1
+	 levels{i,j} = next;
+       else
+%	 levels{i,j} = uint16(str2num(next));
+	 levels{i,j} = next;
+       end
+       if length(buffer) < 1
+        break
+       end
+     end
+end
+
+
+ev_dat = zeros(1,nnodes);
+for i = 1:m,
+    di=selectvar(i,1);
+    ev_dat(di)=selectdata(i,1);
+%Need to standardize evidence for continuous nodes.
+    if bnet.node_sizes(di) == 1,
+        ev_dat(di) = (ev_dat(di) - means{di})/stdevs{di};
+    end
+    evidence{di} = ev_dat(di);
+end
+
+[engine,loglik]=enter_evidence(engine,evidence);
+
+%Open output file.
+filename = strcat(pre,'parameters_ev.txt');
+fileID = fopen(filename,'w');
+
+for i = 1:nnodes
+    for j = 1:nnodes
+	if strcmp(labelsold{i},labels{j});
+            nodeid = j;
+            break
+        end
+    end
+    %%%Print the name of the node
+    fprintf(fileID,'%s\n',labels{nodeid});
+    predict = marginal_nodes(engine,nodeid);
+    if isempty(evidence{nodeid})
+       %%%Print the type of node
+       if bnet.node_sizes(nodeid) == 1;
+           line = 'Continuous parameters considering evidence:\n';
+           fprintf(fileID,line);
+           %line = 'Mean and standard deviation of Gaussian distribution\n';
+           %fprintf(fileID,line);
+	     adj_mu = predict.mu*stdevs{nodeid}+means{nodeid};
+             adj_sigma = stdevs{nodeid}*predict.Sigma;
+             fprintf(fileID,'%6.4f\t%6.4f\n\n',adj_mu,adj_sigma);
+       else
+           line = 'Probability of states considering evidence:\n';
+           fprintf(fileID,line);
+           nodeid2 = 0;
+           for k = 1:ndisc_nodes,
+	     if strcmp(levels{k,1},labels{nodeid}),
+                nodeid2 = k;
+                break
+             end
+            end
+	    for j = 1:bnet.node_sizes(nodeid),
+		%%%For discrete nodes, the state and the percent of that state
+%		fprintf(fileID,'%i\t%6.4f\n',levels{nodeid2,j+1},predict.T(j));
+		fprintf(fileID,'%s\t%6.4f\n',levels{nodeid2,j+1},predict.T(j));
+           end;
+           fprintf(fileID,'\n')
+       end
+   else
+       if bnet.node_sizes(nodeid) == 1;
+          line = 'Evidence was observed for this node. The observed value was:\n';
+          fprintf(fileID,line);  
+          adj_mu = ev_dat(nodeid)*stdevs{nodeid}+means{nodeid};
+          fprintf(fileID,'%6.4f\n\n',adj_mu);
+       else
+          nodeid2 = 0;
+          for k = 1:ndisc_nodes,
+	    if strcmp(levels{k,1},labels{nodeid}),
+               nodeid2 = k;
+               break
+            end
+          end
+	 line = 'Evidence was observed for this node. The observed state was:\n';
+         fprintf(fileID,line);
+         state_ev =   uint16(ev_dat(nodeid));
+%         fprintf(fileID,'%i\n\n',levels{nodeid2,state_ev+1});
+         fprintf(fileID,'%s\n\n',levels{nodeid2,state_ev+1});
+       end
+   end
+end
+
+
+
+fclose(fileID);
+
+end
+