analysis of training data, proper eval for only 1 legal move, enabled…

… go search depth X

.gitignore

@@ -129,3 +129,8 @@ main_config.py
 # avoid pushing log-files generated by uci-communication
 CrazyAra-log.txt
 score-log.txt
+
+# avoid pushing dataset files used for visualization
+crazyara_lichess_dataset.pgn
+crazyara_lichess_dataset_stats.csv
+

DeepCrazyhouse/src/domain/agent/player/MCTSAgent.py

@@ -332,8 +332,10 @@ def _expand_root_node_single_move(self, state, legal_moves):
         :return:
         """
 
-        # set value 0 as a dummy value
-        value = 0
+        # request the value prediction for the current position
+        state_planes = state.get_state_planes()
+        [value, _] = self.nets[0].predict_single(state_planes)
+        # we can create the move probability vector without the NN this time
         p_vec_small = np.array([1], np.float32)
 
         # create a new root node
@@ -382,6 +384,10 @@ def _expand_root_node_single_move(self, state, legal_moves):
             # connect the child to the root
             self.root_node.child_nodes[0] = child_node
 
+            # assign the value of the root node as the q-value for the child
+            # here we must invert the invert the value because it's the value prediction of the next state
+            self.root_node.q[0] = -value
+
     def _run_mcts_search(self, state):
         """
         Runs a new or continues the mcts on the current search tree.
@@ -785,3 +791,11 @@ def update_movetime(self, time_ms_per_move):
         :return:
         """
         self.movetime_ms = time_ms_per_move
+
+    def set_max_search_depth(self, max_search_depth: int):
+        """
+        Assigns a new maximum search depth for the next search
+        :param max_search_depth: Specifier of the search depth
+        :return:
+        """
+        self.max_search_depth = max_search_depth

DeepCrazyhouse/src/preprocessing/PGN2PlanesConverter.py

@@ -261,6 +261,37 @@ def _filter_pgn_thread(self, queue, pgn):
         queue.put(batch_black_won)
         queue.put(batch_draw)
 
+    def filter_all_pgns(self):
+        """
+        Filters out all games based on the given conditions in the constructor and returns all games in
+        :return: lst_all_pgn_sel: List of selected games in String-IO format
+                 lst_nb_games_sel: Number of selected games for each pgn file
+                 lst_batch_white_won: Number of white wins in each pgn file
+                 lst_black_won: Number of black wins in each pgn file
+                 lst_draw_won: Number of draws in each pgn file
+        """
+
+        total_games_exported = 0
+
+        lst_all_pgn_sel = []
+        lst_nb_games_sel = []
+        lst_batch_white_won = []
+        lst_batch_black_won = []
+        lst_batch_draw = []
+
+        pgns = os.listdir(self._import_dir)
+        for pgn_name in pgns:
+            self._pgn_name = pgn_name
+            all_pgn_sel, nb_games_sel, batch_white_won, batch_black_won, batch_draw = self.filter_pgn()
+            lst_all_pgn_sel.append(all_pgn_sel)
+            lst_nb_games_sel.append(nb_games_sel)
+            lst_batch_white_won.append(batch_white_won)
+            lst_batch_black_won.append(batch_black_won)
+            lst_batch_draw.append(batch_draw)
+
+        return lst_all_pgn_sel, lst_nb_games_sel, lst_batch_white_won, lst_batch_black_won, lst_batch_draw
+
+
     def convert_all_pgns_to_planes(self):
         """
         Master function which calls convert_pgn_to_planes() for all available pgns in the import directory