merging

dtree_synth.py

@@ -22,6 +22,7 @@ def load_positive_examples(file_name: str) -> List[Tuple[float, ...]]:
     truth_samples_seq = [(t, [s for s in raw_samples if not any(np.isnan(s))])
                          for t, raw_samples in truth_samples_seq]
     # Convert from sampled states and percepts to positive examples for learning
+    
     return [
         s for _, samples in truth_samples_seq for s in samples
     ]
@@ -82,6 +83,7 @@ def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
         past_candidate_list.append(candidate_dnf)
         # QUERYING TEACHER IF THERE ARE NEGATIVE EXAMPLES
         print(f"number of paths: {len(candidate_dnf)}")
+        
         negative_examples = []
         for candidate in candidate_dnf:
             result = teacher.check(candidate)
@@ -112,7 +114,10 @@ def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
             print("we are done!")
             return past_candidate_list
 
+        #if k == 2:
+        #    exit(0)
     print("Reached max iteration %d." % num_max_iterations)
+    
     return []