diff options
Diffstat (limited to 'BNW_parameter_learning/prepareInput.m')
| -rw-r--r-- | BNW_parameter_learning/prepareInput.m | 21 |
1 files changed, 18 insertions, 3 deletions
diff --git a/BNW_parameter_learning/prepareInput.m b/BNW_parameter_learning/prepareInput.m index 28a06c15..84d2ae17 100644 --- a/BNW_parameter_learning/prepareInput.m +++ b/BNW_parameter_learning/prepareInput.m @@ -39,6 +39,8 @@ function [ ] = prepareInput( pre ) % 8-12) ???ban.txt, ???white.txt, ???k.txt, ???thr.txt, and % ???parent.txt: Files with default values for structure learning. % + % It is called by the run_prep_input script in the 'sourcecodes' directory. + % open file for input, include error handling dfile=strcat(pre,'continuous_input_orig.txt'); @@ -81,28 +83,36 @@ for j = 1:nnodes levels{j} = size(states{j},1); end +reason = cell(1,nnodes); %Now do some checks to see if nodes are discrete or continuous for j = 1:nnodes % If there are 3 or less unique values, I will assume that the node is discrete. if levels{j} < 4; + reason{j} = "It was determined to be discrete because there are a small number (<4) of possible values."; continue % If there are as many unique values as a third of the number of cases, % I will assume that the node is continuous. elseif levels{j} > ncases/3; levels{j} = 1; + reason{j} = "It was determined to be continuous because there are a large number of possible values compared to the number of cases."; + continue % If there are more than twenty unique values, % I will assume that the node is continuous. elseif levels{j} > 20; levels{j} = 1; + reason{j} = "It was determined to be continuous because there are many (>20) possible values."; + continue % Otherwise, I will scan through the individual values. % If any of the values contain a '.', I will assume it is continuous. else + reason{j} = "It was determined to be discrete by default."; period_test = 0; column = data(:,j); k = 1; while period_test == 0 period_test = sum(cell2mat(strfind(column(k),"."))); if period_test != 0; + reason{j} = "This variable was determined to be continuous because there were several possible values and at least one value contained a period(.)."; levels{j} = 1; end k++; @@ -131,6 +141,7 @@ if max_disc > min_cont labels_old = labels; data_old = data; states_old = states; + reason_old = reason; new_order = {}; for i=1:nnodes if levels_old{i} > 1 @@ -145,10 +156,12 @@ if max_disc > min_cont labels = {}; levels = {}; states = {}; + reason = {}; for i =1:nnodes labels{i} = labels_old{new_order{i}}; levels{i} = levels_old{new_order{i}}; states{i} = states_old{new_order{i}}; + reason{i} = reason_old{new_order{i}}; for j=1:ncases data{j,i} = data_old{j,new_order{i}}; end @@ -228,19 +241,21 @@ descfile = strcat(pre,'input_desc.txt'); dout = fopen(descfile,'w'); fprintf(dout,['As loaded, the input file had the following properties:\n\n']); dout = fopen(descfile,'a'); -fprintf(dout,'There are %i variables and %i cases(rows)\n',size(labels,2),ncases); +fprintf(dout,'There are %i variables and %i cases(rows).\n',size(labels,2),ncases); fprintf(dout,'The variable names are:\n'); fprintf(dout,'%s\t',labels{1:end-1}); fprintf(dout,'%s\n\n',labels{end}); for i=1:nnodes if levels{i} == 1 - fprintf(dout,'%s is a continuous variable\n',labels{i}); + fprintf(dout,'%s is a continuous variable.\n',labels{i}); + fprintf(dout,'%s\n',reason{i}); column = str2double(data(:,i)); colmean = mean(column); colstd = std(column); fprintf(dout,'It has a mean of %6.3f and a standard deviation of %6.3f\n\n',mean(column),std(column)) else - fprintf(dout,'%s is a discrete variable with %i states\n',labels{i},levels{i}); + fprintf(dout,'%s is a discrete variable with %i states.\n',labels{i},levels{i}); + fprintf(dout,'%s\n',reason{i}); fprintf(dout,'The states are: '); fprintf(dout,'%s ',states{i}{1:end-1}); fprintf(dout,'%s\n\n',states{i}{end}); |