lib/bn4r/bn_algorithms.rb in bn4r-0.1.2 vs lib/bn4r/bn_algorithms.rb in bn4r-0.9.0

@@ -43,12 +43,17 @@
   # Intelligence, A Modern Approach", 2nd Edition. pp 511-512
   # 
   # The input are the nodes of the bn ordered by dependencies see nodes_ordered_by_dependencies
   def prior_sample(nodes_ordered = nodes_ordered_by_dependencies)
     sample = Array.new
-    nodes_ordered.each { |v| 
-      value = rand < v.get_probability(true)
+    nodes_ordered.each { |v|
+      value = nil
+      prob = 0.0; r_prob = rand
+      v.outcomes.each { |outcome| 
+        prob += v.get_probability(outcome)
+        value = outcome and break if r_prob < prob
+      }
       v.set_value(value) 
       sample << v.copy
     }
     # leave the bn clear of values.
     nodes_ordered.each { |v| v.clear_value }
@@ -179,10 +184,15 @@
       node_actual = [e] if e.class == BayesNetNode and e.name == v.name
       if !node_actual.nil? and node_actual.size == 1
         value = node_actual[0].value
         w = w * v.get_probability(value)
       else
-        value = rand < v.get_probability(true)
+        rand_sample = rand; i_tmp = 0.0
+        v.outcomes.each { |outcome|
+          value = outcome
+          i_tmp += v.get_probability(value)
+          break if i_tmp > rand_sample          
+        }
       end
       v.set_value(value) 
       sample << v.copy
     }
     
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