Added error messages to engine IO and pass move to neural networks.

10 files changed, 143 insertions, 61 deletions

diff --git a/imago/engine/core.py b/imago/engine/core.py
index 810b851..4028bb3 100644
--- a/imago/engine/core.py
+++ b/imago/engine/core.py
@@ -47,6 +47,7 @@ class GameEngine:
         """Plays in the vertex passed as argument"""
         if vertex == "pass":
             self.gameState.passForPlayer(color)
+            self.da.forceNextMove(vertex)
             return
         row = vertex[0]
         col = vertex[1]
@@ -56,7 +57,7 @@ class GameEngine:
     def genmove(self, color):
         """Returns a list representing coordinates of the board in the form (row, col)."""
         coords = self.da.pickMove()
-        self.play(color, [coords[0], coords[1]])
+        self.play(color, coords)
         return coords
 
     def undo(self):
diff --git a/imago/engine/decisionAlgorithmFactory.py b/imago/engine/decisionAlgorithmFactory.py
index bd86864..094a816 100644
--- a/imago/engine/decisionAlgorithmFactory.py
+++ b/imago/engine/decisionAlgorithmFactory.py
@@ -5,7 +5,7 @@ from imago.engine.monteCarlo import MCTS
 from imago.engine.keras.keras import Keras
 
 class DecisionAlgorithms(Enum):
-    RANDOM = enumAuto()
+    #RANDOM = enumAuto()
     MONTECARLO = enumAuto()
     KERAS = enumAuto()
 
diff --git a/imago/engine/imagoIO.py b/imago/engine/imagoIO.py
index 6ada674..9b3e367 100644
--- a/imago/engine/imagoIO.py
+++ b/imago/engine/imagoIO.py
@@ -9,6 +9,10 @@ def _response(text=""):
     print("= %s" % text)
     print()
 
+def _responseError(text=""):
+    print("? %s" % text)
+    print()
+
 def protocol_version(_):
     """Version of the GTP Protocol"""
     _response("2")
@@ -51,30 +55,36 @@ class ImagoIO:
 
     def start(self):
         """Starts reading commands interactively."""
-        while True:
-            input_tokens = input().split()
-
-            if input_tokens[0] == "quit":
-                sys.exit(0)
-
-            command = None
-            for comm in self.commands_set:
-                if comm.__name__ == input_tokens[0]:
-                    command = comm
-
-            if command is not None:
-                arguments = input_tokens[1:]
-                #print("[DEBUG]:Selected command: %s; args: %s" % (command, arguments))
-                command(arguments)
-            else:
-                print("unknown command")
+        try:
+            while True:
+                input_tokens = input().split()
+
+                if len(input_tokens) == 0:
+                    continue
+
+                if input_tokens[0] == "quit":
+                    sys.exit(0)
+
+                command = None
+                for comm in self.commands_set:
+                    if comm.__name__ == input_tokens[0]:
+                        command = comm
+
+                if command is not None:
+                    arguments = input_tokens[1:]
+                    #print("[DEBUG]:Selected command: %s; args: %s" % (command, arguments))
+                    command(arguments)
+                else:
+                    _responseError("unknown command")
+        except Exception as err:
+            _responseError("An uncontrolled error ocurred. The error was: %s" % err)
 
     def known_command(self, args):
         """True if command is known, false otherwise"""
         if len(args) != 1:
-            print ("Wrong number of args.")
-            print ("Usage: known_command COMMAND_NAME")
-            sys.exit(0)
+            _responseError("Wrong number of arguments.")
+            _responseError("Usage: known_command COMMAND_NAME")
+            return
         out = "false"
         for c in self.commands_set:
             if c.__name__ == args[0]:
@@ -94,8 +104,9 @@ class ImagoIO:
         It is wise to call clear_board after this command.
         """
         if len(args) != 1:
-            print("Error - Wrong n of args")
-            sys.exit(1)
+            _responseError("Wrong number of arguments")
+            _responseError("Usag. boardsize <newSize>")
+            return
         size = int(args[0])
         self.gameEngine.setBoardsize(size)
         _response()
@@ -110,8 +121,9 @@ class ImagoIO:
     def komi(self, args):
         """Sets a new value of komi."""
         if len(args) != 1:
-            print("Error - Wrong n of args")
-            sys.exit(1)
+            _responseError("Wrong number of arguments")
+            _responseError("Usage: komi <newKomi>")
+            return
         komi = float(args[0])
         self.gameEngine.setKomi(komi)
         _response()
@@ -121,8 +133,9 @@ class ImagoIO:
             These vertices follow the GTP specification.
         """
         if len(args) != 1:
-            print("Error - Wrong n of args")
-            sys.exit(1)
+            _responseError("Wrong number of arguments")
+            _responseError("Usage: fixed_handicap <count>")
+            return
         stones = float(args[0])
         vertices = self.gameEngine.setFixedHandicap(stones)
         out = getCoordsText(vertices[0][0], vertices[0][1])
@@ -141,8 +154,9 @@ class ImagoIO:
     def play(self, args):
         """A stone of the requested color is played at the requested vertex."""
         if len(args) != 2:
-            print("Error - Wrong n of args")
-            sys.exit(1)
+            _responseError("Wrong number of arguments.")
+            _responseError("Usage: play <color> <vertex>")
+            return
         move = parseHelpers.parseMove(args, self.gameEngine.gameState.size)
         self.gameEngine.play(move.color, move.vertex)
         _response()
@@ -150,8 +164,9 @@ class ImagoIO:
     def genmove(self, args):
         """A stone of the requested color is played where the engine chooses."""
         if len(args) != 1:
-            print("Error - Wrong n of args")
-            sys.exit(1)
+            _responseError("Wrong number of arguments.")
+            _responseError("Usage: genmove <color>")
+            return
         color = parseHelpers.parseColor(args[0])
         output = parseHelpers.vertexToString(self.gameEngine.genmove(color),
                 self.gameEngine.gameState.size)
diff --git a/imago/engine/keras/convNeuralNetwork.py b/imago/engine/keras/convNeuralNetwork.py
index 9d97586..638e2fe 100644
--- a/imago/engine/keras/convNeuralNetwork.py
+++ b/imago/engine/keras/convNeuralNetwork.py
@@ -38,7 +38,7 @@ class ConvNeuralNetwork(NeuralNetwork):
             ),
             Flatten(),
             Dense(
-                units=81,
+                units=82,
                 activation='softmax'
             ),
         ])
diff --git a/imago/engine/keras/initialDenseNeuralNetwork.py b/imago/engine/keras/initialDenseNeuralNetwork.py
new file mode 100644
index 0000000..dfe8379
--- /dev/null
+++ b/imago/engine/keras/initialDenseNeuralNetwork.py
@@ -0,0 +1,28 @@
+"""Dense neural network."""
+
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import Dense
+from tensorflow.keras.optimizers import Adam
+
+from imago.engine.keras.neuralNetwork import NeuralNetwork
+
+defaultModelFile = 'models/imagoDenseKerasModel.h5'
+
+class DenseNeuralNetwork(NeuralNetwork):
+
+    def _initModel(self, boardSize=NeuralNetwork.DEF_BOARD_SIZE):
+        model = Sequential([
+            Dense(units=16, activation='relu', input_shape=(boardSize,boardSize)),
+            Dense(units=32, activation='relu'),
+            Dense(units=boardSize, activation='softmax')
+        ])
+
+        model.summary()
+
+        model.compile(
+                optimizer=Adam(learning_rate=0.0001),
+                loss='categorical_crossentropy',
+                metrics=['accuracy']
+            )
+
+        return model
diff --git a/imago/engine/keras/keras.py b/imago/engine/keras/keras.py
index 0668cd1..00b06d7 100644
--- a/imago/engine/keras/keras.py
+++ b/imago/engine/keras/keras.py
@@ -18,7 +18,10 @@ class Keras(DecisionAlgorithm):
 
     def forceNextMove(self, coords):
         """Selects given move as next move."""
-        self.currentMove = self.currentMove.addMoveByCoords(coords)
+        if coords == "pass":
+            self.currentMove = self.currentMove.addPass()
+        else:
+            self.currentMove = self.currentMove.addMoveByCoords(coords)
 
     def pickMove(self):
         """Returns a move to play."""
diff --git a/imago/engine/keras/neuralNetwork.py b/imago/engine/keras/neuralNetwork.py
index d0eb4ae..7eddb9d 100644
--- a/imago/engine/keras/neuralNetwork.py
+++ b/imago/engine/keras/neuralNetwork.py
@@ -81,7 +81,7 @@ class NeuralNetwork:
 
     def _boardToPlayerContext(self, board, player):
         """Converts the board to a 3D matrix with two representations of the board, one
-        marking the player's stones and the oter marking the opponent's stones."""
+        marking the player's stones and the other marking the opponent's stones."""
         boardRows = len(board)
         boardCols = len(board[0])
         contextBoard = numpy.zeros((boardRows, boardCols, 2), dtype = float)
@@ -95,14 +95,19 @@ class NeuralNetwork:
         return contextBoard
 
     def _movesToTargets(self, moves):
-        """Converts the moves to 2D matrices with values zero except for a one on the
-        played vertex."""
+        """Converts the moves to 2D matrices with values zero except for a one indicating
+        the played move."""
         targets = []
+        targetsSize = self.boardSize * self.boardSize + 1 # Each vertex + 1 for pass
         for move in moves:
             if len(move.nextMoves) == 0:
                 continue
-            target = numpy.zeros(self.boardSize * self.boardSize, dtype = float)
-            target[move.nextMoves[0].getRow() * self.boardSize + move.nextMoves[0].getCol()] = 1
+            target = numpy.zeros(targetsSize, dtype = float)
+            nextMove = move.nextMoves[0]
+            if nextMove.isPass:
+                target[-1] = 1
+            else:
+                target[nextMove.getRow() * self.boardSize + nextMove.getCol()] = 1
             targets.append(target.tolist())
         return targets
 
@@ -110,11 +115,12 @@ class NeuralNetwork:
         """Uses the model's predict function to pick the highest valued vertex to play."""
 
         predictionVector = self._predict(gameMove, player)[0]
-        prediction = numpy.zeros((self.boardSize, self.boardSize))
+        predictionBoard = numpy.zeros((self.boardSize, self.boardSize))
         for row in range(self.boardSize):
             for col in range(self.boardSize):
-                prediction[row][col] = predictionVector[row * self.boardSize + col]
-        self.saveHeatmap(prediction)
+                predictionBoard[row][col] = predictionVector[row * self.boardSize + col]
+        predictionPass = predictionVector[-1]
+        self.saveHeatmap(predictionBoard, predictionPass)
 
         # Search the highest valued vertex which is also playable
         playableVertices = gameMove.getPlayableVertices()
@@ -123,11 +129,13 @@ class NeuralNetwork:
         hCol = -1
         for row in range(self.boardSize):
             for col in range(self.boardSize):
-                if prediction[row][col] > highest and (row, col) in playableVertices:
+                if predictionBoard[row][col] > highest and (row, col) in playableVertices:
                     hRow = row
                     hCol = col
-                    highest = prediction[row][col]
+                    highest = predictionBoard[row][col]
 
+        if highest < predictionPass:
+            return "pass"
         return [hRow, hCol]
 
     def _predict(self, gameMove, player):
@@ -139,29 +147,42 @@ class NeuralNetwork:
                 batch_size = 1,
                 verbose = 2)
 
-    def saveHeatmap(self, data):
+    def saveHeatmap(self, data, passChance):
         rows = len(data)
         cols = len(data[0])
 
-        fig, ax = pyplot.subplots()
-        im = ax.imshow(data, cmap="YlGn")
+        fig, (axBoard, axPass) = pyplot.subplots(1, 2, gridspec_kw={'width_ratios': [9, 1]})
+        imBoard = axBoard.imshow(data, cmap="YlGn")
+        axPass.imshow([[passChance]], cmap="YlGn", norm=imBoard.norm)
 
-        # Show all ticks and label them with the respective list entries
-        ax.set_xticks(numpy.arange(cols))
-        ax.set_xticklabels(self._getLetterLabels(cols))
-        ax.set_yticks(numpy.arange(rows))
-        ax.set_yticklabels(numpy.arange(rows, 0, -1))
+        # Tick and label the board
+        axBoard.set_xticks(numpy.arange(cols))
+        axBoard.set_xticklabels(self._getLetterLabels(cols))
+        axBoard.set_yticks(numpy.arange(rows))
+        axBoard.set_yticklabels(numpy.arange(rows, 0, -1))
+
+        # Label the pass chance
+        axPass.set_xticks([0])
+        axPass.set_yticks([])
+        axPass.set_xticklabels(["Pass"])
 
         # Loop over data dimensions and create text annotations.
-        textColorThreshold = 0.35
+        textColorThreshold = data.max() / 2
         for row in range(rows):
             for col in range(cols):
                 textColor = ("k" if data[row, col] < textColorThreshold else "w")
-                ax.text(col, row, "%.2f"%(data[row, col]),
+                axBoard.text(col, row, "%.2f"%(data[row, col]),
                                ha="center", va="center", color=textColor)
 
-        ax.set_title("Heat map of move likelihood")
+        textColor = ("k" if passChance < textColorThreshold else "w")
+        axPass.text(0, 0, "%.2f"%(passChance),
+                       ha="center", va="center", color=textColor)
+
+        pyplot.suptitle("Heat map of move likelihood")
+        #axBoard.set_title("Heat map of move likelihood")
         fig.tight_layout()
+
+        #pyplot.show()
         pyplot.savefig("heatmaps/heatmap_%s_%s_%d.png" %
                 (
                     self.NETWORK_ID,
diff --git a/imago/engine/monteCarlo.py b/imago/engine/monteCarlo.py
index 81bee1d..0587cfc 100644
--- a/imago/engine/monteCarlo.py
+++ b/imago/engine/monteCarlo.py
@@ -14,6 +14,8 @@ class MCTS(DecisionAlgorithm):
 
     def forceNextMove(self, coords):
         """Selects given move as next move."""
+        if coords == "pass":
+            raise NotImplementedError("Pass not implemented for MCTS algorithm.")
         for node in self.root.children:
             if (node.move.getRow() == coords[0]
             and node.move.getCol() == coords[1]):
diff --git a/imago/engine/parseHelpers.py b/imago/engine/parseHelpers.py
index 59e0496..fd5ea63 100644
--- a/imago/engine/parseHelpers.py
+++ b/imago/engine/parseHelpers.py
@@ -51,7 +51,9 @@ def parseVertex(text, boardSize):
     if not re.match("^[A-HJ-Z][1-9][0-9]*$", text):
         if text == "PASS":
             return "pass"
-        return ParseCodes.ERROR
+        raise RuntimeError(
+                "Unable to transform string %s to vertex. Wrong format."
+                % text)
 
     vertexCol = ord(text[0])
     # Column 'I' does not exist
@@ -63,7 +65,9 @@ def parseVertex(text, boardSize):
 
     if (vertexCol < 0 or vertexRow < 0
         or vertexCol >= boardSize or vertexRow >= boardSize):
-        return ParseCodes.ERROR
+        raise RuntimeError(
+                "Unable to transform string %s to vertex. Maps to [%d, %d], which is out of board bounds (size %d)"
+                % (text, vertexCol, vertexRow, boardSize))
 
     return [vertexRow, vertexCol]
 
@@ -76,9 +80,13 @@ def vertexToString(vertex, boardSize):
     if vertex == "pass":
         return "pass"
     if len(vertex) != 2:
-        return ParseCodes.ERROR
+        raise RuntimeError(
+                "Unable to transform vertex %s to string. Too many elements."
+                % str(vertex))
     if vertex[0] >= boardSize or vertex[1] >= boardSize or vertex[0] < 0 or vertex[1] < 0:
-        return ParseCodes.ERROR
+        raise RuntimeError(
+                "Unable to transform vertex %s to string. Vertex out of board bounds (size %d)"
+                % (str(vertex), boardSize))
 
     vertexRow = boardSize - vertex[0]
     vertexCol = ord('A') + vertex[1]
diff --git a/imago/sgfParser/astNode.py b/imago/sgfParser/astNode.py
index ff0c517..41629ce 100644
--- a/imago/sgfParser/astNode.py
+++ b/imago/sgfParser/astNode.py
@@ -5,7 +5,7 @@ from imago.data.enums import Player
 
 class ASTNode:
     """Abstract Syntax Tree Node of SGF parser"""
-    def __init__(self, children=None, leaf=None, props=None):
+    def __init__(self, children=None, props=None):
         if children:
             self.children = children
         else:
@@ -14,7 +14,6 @@ class ASTNode:
             self.props = props
         else:
             self.props = []
-        self.leaf = leaf
 
     def addToSequence(self, move):
         """Appends a move to the last of the sequence started by this move"""
@@ -104,6 +103,11 @@ class ASTNode:
                 gameMove = previousMove.addPassForPlayer(player)
         for child in self.children:
             child.toGameMoveTree(previousMove=gameMove)
+        # Add a couple passes at the end of the match since they are not usually recorded
+        if len(self.children) == 0 and not gameMove.isPass:
+            nextMove = gameMove.addPass()
+            nextMove.addPass()
+
         return gameMove
 
     def hasProperty(self, propertyName):