Deleting parameter learning folder

There was an extra folder with the Matlab/Octave parameter learning files. These were out of date, so I deleted them and kept the versions in the sourcecoades directory.

1 files changed, 0 insertions, 86 deletions

diff --git a/BNW_parameter_learning/Predictmultiple.m b/BNW_parameter_learning/Predictmultiple.m
deleted file mode 100644
index 019488a3..00000000
--- a/BNW_parameter_learning/Predictmultiple.m
+++ /dev/null
@@ -1,86 +0,0 @@
-function Predictmultiple(pre)

-% Predictmultiple is used when predicting the impact of entering

-%    evidence on the network. The 'multiple' part refers to 

-%    it working when evidence for multiple nodes is entered.

-%

-% The input is 'pre'-- the prefix for the network and data

-%      in BNW. It reads information from several files from BNW. 

-%

-% The output is ???net_figure_new.txt. It also calls 

-%      writeParameters_ev to write the parameter file.

-%

-% It is called by the run_octave_evd file in the 'sourcecodes' directory.

-

-

-

-dfile=strcat(pre,'structure_input.txt');

-sfile=dfile;

-dfile=strcat(pre,'continuous_input.txt');

-nnodefile=strcat(pre,'nnode.txt');

-

-fnnode = fopen(nnodefile,'r');

-nnodes = fscanf(fnnode,'%d');

-

-Std_flag=true;

-[labels,cases,bnet]=readInput(dfile,sfile,nnodes,Std_flag);

-

-[bnet]=parameterLearning(bnet,cases);

-

-fvarfile=strcat(pre,'var.txt');

-fvar = fopen(fvarfile,'r');                         

-select_var_new = fscanf(fvar,'%d');

-

-fvardfile=strcat(pre,'vardata.txt');

-fvard = fopen(fvardfile,'r');

-select_var_data_new = fscanf(fvard,'%f');

-

-means_orig = cell(1,nnodes);

-stdevs_orig = cell(1,nnodes);

-labels_orig = cell(1,nnodes);

-%Read in original means and standard deviations

-mapfile = strcat(pre,'map.txt');

-fmap = fopen(mapfile,'r');

-for i=1:nnodes

-    buffer = fgetl(mapfile);

-    temp = cell(1,3);

-    for j=1:3

-        [next,buffer] = strtok(buffer);

-        temp{j} = next;

-    end

-    labels_orig{i} = temp{1};

-    means_orig{i} = str2num(temp{3});

-    stdevs_orig{i} = str2num(temp{2});

-end

-fclose(fmap);

-

-%Need to map the means and stdevs to the correct labels

-means = cell(1,nnodes);

-stdevs = cell(1,nnodes);

-%Read in labels in new order.

-labelsnew = cell(1,nnodes);

-mapdatafile = strcat(pre,'mapdata.txt');

-fmapdata = fopen(mapdatafile,'r');

-buffer = fgetl(fmapdata);

-for i = 1:nnodes

-    [next,buffer ] = strtok(buffer);

-    labelsnew{i} = next;

-end

-fclose(fmapdata);

-for i = 1:nnodes

-    for j = 1:nnodes

-       if strcmp(labelsnew{i},labels_orig{j})

-          means{i} = means_orig{j};

-          stdevs{i} = stdevs_orig{j};

-          break

-       end

-    end

-end

-

-

-filename=strcat(pre,'net_figure_new.txt');

-

-drawFigureM(nnodes,bnet,labels,filename,cases,stdevs,means,select_var_new,select_var_data_new);

-

-writeParameters_ev(pre,bnet,nnodes,labels,cases,stdevs,means,select_var_new,select_var_data_new);

-

-end