working on old example for deterministic tictactoe, problem with placeholder and output generation

examples/tictactoe/completetesting.py

@@ -52,7 +52,8 @@ class CompleteTicTacToeTester(AbstractTester):
                 model.move(action)
                 if output not in model.outputs():
                     self._logger.info("Found a counterexample: "
-                                      + str(ce) + " output: "+str(output))
+                                      + str(ce) + " output: "+str(output)+
+                                      " not in " + str(model.outputs()))
 
                     self._teacher.reset()
                     model.reset()

examples/tictactoe/learn.py

@@ -45,7 +45,7 @@ import helpers.bisimulation as bi
 
 import csv
 
-logging.basicConfig(level=logging.INFO)
+logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
 HOST = 'localhost'

examples/tictactoe/tictacoracle.py

@@ -43,7 +43,7 @@ class TicTacToeOracle(AbstractOracle):
         if len(outputs) > 0:
             return True
         else:
-            # Check trace, if it has more outputs or more imputs in a row,
+            # Check trace, if it has more outputs or more inputs in a row,
             # then return True
             if trace == ():
                 return False

examples/tictactoe/tictacpurpose.py

@@ -58,23 +58,23 @@ class TicTacToeOutputPurpose(Purpose):
         if (trace != None and len(trace) > 0 and trace[-1] not in inputs):
             return set(['delta'])
         else:
-            if (outputs != None and len(outputs) > 0):
-                return outputs
-            else:
+            #if (outputs != None and len(outputs) > 0):
+            #    return outputs
+            #else:
                 # In this SUL we have many outputs (>4000)
                 # for this reason we use a placeholder
                 # We also need a way to compare a set of outputs with the
                 # placeholder
-                return 'PLACEHOLDER'
+           return set(['PLACEHOLDER'])
 
     def isIncluded(self, set1, set2):
-        if set2 == 'PLACEHOLDER':
+        if 'PLACEHOLDER' in set2:
             return True
         else:
-            if set1 == 'PLACEHOLDER':
+            if 'PLACEHOLDER' in set1:
                 return False
             else:
                 return set1.issubset(set2)
 
     def allOutputs(self):
-        return set(itertools.product('XO_', repeat=9))
+        return set(map(''.join, itertools.product('XO_', repeat=9)))

examples/tictactoe/tictacteacher.py

@@ -42,7 +42,7 @@ class TicTacToeTeacher(AbstractTeacher):
         self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
         self._socket.connect((host, port))
 
-        self._outputs = set(itertools.product('XO_', repeat=9))
+        self._outputs = set(map(''.join, itertools.product('XO_', repeat=9)))
 
         # counter for inputs:
         self._count = 0

learning/learning.py

@@ -318,7 +318,7 @@ class LearningAlgorithm:
     def getHypothesis(self, chaos=False):
         # If table is not closed, ERROR
         if self._table.isNotGloballyClosed():
-            self._logger.error("Tried to get hypotheses with table not closed")
+            self._logger.warning("Trying to create a model from a not closed table")
             return None, None
         # Get equivalence classes
         rows = self._table.getEquivalenceClasses(chaos)
@@ -330,7 +330,7 @@ class LearningAlgorithm:
         # assign to each equivalence class a state number
         # start with equivalence class of empty trace to 0
         # TODO: is () always the representative of an equivalence class?
-        # NO
+        # NO, we might have more than one row representing (). TODO: FIX
         rowForEmpty = ()
         # search for the representative for ()
         for row in rows:
@@ -338,6 +338,8 @@ class LearningAlgorithm:
             # private. Change to public, or add a public version
             if self._table._moreSpecificRow(row, rowForEmpty, chaos):
                 rowForEmpty = row
+                self._logger.debug("Creating " + ("HPlus" if chaos else "HMinus") 
+                + ": Row representing (): " + str(row))
                 break
 
         assignments = {rowForEmpty:0}
@@ -351,7 +353,7 @@ class LearningAlgorithm:
         for row in rows:
             enabledOuptuts = self._table.getOutputs(row)
             allLabels = self._getAllLabels(row, enabledOuptuts)
-
+            self._logger.debug("All labels: "+ str(allLabels))
             for label in allLabels:
                 # create row and search it in the table
                 extension = row + (label,)
@@ -408,6 +410,8 @@ class LearningAlgorithm:
         if self._outputPurpose != None:
             enabledOutputs = self._outputPurpose.getEnabled(row)
         allLabels = enabledInputs.union(enabledOutputs)
+        self._logger.debug("enabledInputs: "+ str(enabledInputs))
+        self._logger.debug("enabledOutputs: "+ str(enabledOutputs))
         return allLabels
 
     # Generate DOT files for hypotheses. hyp = hMinus|hPlus|both

learning/observationtable.py

@@ -753,7 +753,7 @@ class Table:
         outputs1 = self._entries[th.flatten(row1,self._quiescence)][0]
         outputs2 = self._entries[th.flatten(row2,self._quiescence)][0]
 
-        # If they enable the same inputs, check each entry.
+        # Check each entry.
         for column in self._columns:
             entry1 = th.flatten(row1 + column, self._quiescence)
             entry2 = th.flatten(row2 + column, self._quiescence)