diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..f64771e --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,13 @@ +repos: +- repo: https://github.com/astral-sh/ruff-pre-commit + # Ruff version. + rev: v0.12.1 + hooks: + # Run the linter. + - id: ruff-check + # Run the formatter. + - id: ruff-format +- repo: https://github.com/astral-sh/uv-pre-commit + rev: 0.7.17 + hooks: + - id: uv-lock \ No newline at end of file diff --git a/README.md b/README.md index 39d11a0..f7a63fc 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ # SHAPE: Shape Habits Analysis and Personalized Evaluation -SHAPE is an app to play Go with AI feedback, specifically designed to point out typical bad habits for your current skill level. +SHAPE is a Go app with AI feedback, designed to help you identify and correct common mistakes based on your skill level. -This is an experimental project, and is unlikely to ever become very polished. +![SHAPE Application Screenshot](assets/screenshot.png) ## Quick Start @@ -14,39 +14,60 @@ uvx goshape The first time you run this, `uv` will automatically download the package, create a virtual environment, and install all dependencies. -When the application starts for the first time, it will check for the required KataGo models in `~/.katrain/`. If they are not found, a dialog will appear to guide you through downloading them. +When the application starts for the first time, it will also check for the required KataGo models in `~/.katrain/`. If they are not found, a dialog will appear to guide you through downloading them. -## Manual +## Features -The most important settings are: +- **Personalized Mistake Analysis**: The AI feedback is tailored to your rank, flagging mistakes that are relevant to your level. +- **Interactive Board**: A clean, responsive Go board with heatmap visualizations. +- **Detailed AI Feedback**: An analysis tab shows the score graph and KataGo's top move considerations. +- **Configurable Opponent**: Play against an AI opponent with customizable rank, style, and behavior. +- **SGF Support**: Save and load games, or copy/paste SGF data from the clipboard. -- Current Rank: Your current Go skill level, which determines which mistakes are considered "typical" for your level. -- Target Rank: The skill level you want to aim for. Even if a move is a huge mistake, if it was a mistake still common at that level, it won't be considered relevant. -- Opponent: The type and level of the AI opponent. - - This supports modern, pre-alphago style, and historical professional style. - - Like the feedback, it is likely to be somewhat weaker than actual professionals or high-dan players. +## How to Use -The game will automatically halt when a typical mistake is made by you, allowing you to analyze, undo, or just continue. +The main window is divided into the board on the left and a control panel with three tabs on the right. -Keep in mind that the techniques used are more likely to be helpful up to low-dan levels, and may not be helpful at all at high levels. +### Board Controls -### Heatmap +Underneath the board, you will find the main game controls: +- **Pass**: Pass your turn. +- **Undo**: Go back one move. This button is only active when there are moves to undo. +- **Redo**: Go forward one move. This button is only active when you have undone moves. +- **AI Move**: Force the AI to make a move, even if it is your turn. -The policy heatmap shows the probability of the top moves being made for your current rank, target rank, and AI. -Note that a move being probable does not mean it is a good move. -You can select multiple heatmaps to get a blended view, where size/number is the average probability, and the color is the average rank (current, target, AI). +### The "Play" Tab +This is the main control center for your game. -## TODO list from Gemini +- **Game Control**: + - **Play as**: Choose to play as Black or White. + - **Opponent Controls**: Force the AI to move or enable **Auto-play** for the AI to play automatically when it's its turn. +- **Player Settings**: + - **Current Rank**: Your current Go skill level. This is used to determine which mistakes are typical for you. + - **Target Rank**: The skill level you want to aim for. Mistakes common at this level won't be flagged. + - **Opponent**: The type and level of the AI opponent. This supports modern, pre-AlphaGo style, and historical professional styles. +- **Heatmap**: Visualize the AI's preferred moves for different player models (Current Rank, Target Rank, AI, and Opponent). You can select multiple heatmaps to get a blended view. +- **Info Panel**: A collapsible panel (shortcut: `Ctrl+0`) that shows detailed statistics about the last move. -Based on a code review, here are some suggested areas for improvement: +### The "AI Analysis" Tab -### High Impact -- **User-Friendly Errors (`main.py`):** Show GUI dialogs for errors instead of crashing the application. +This tab provides feedback from the AI. +- **Score Graph**: A graph showing the score progression over the course of the game. The Y-axis is centered at 0, with a dashed line indicating an even game. +- **Top Moves**: A table showing KataGo's top 5 recommended moves for the current position, including win rate, score lead, and visits. +- **Deeper AI Analysis**: A button to request a much deeper analysis (more visits) for the current position. -### Medium Impact -- **Refactor `GameNode` (`game_logic.py`):** Extract board state and rule logic into a separate `Board` class to simplify `GameNode` and improve modularity. +### The "Settings" Tab -### Low Impact -- **Code Clarity (`game_logic.py`):** Improve code readability. +This tab allows you to fine-tune the AI's behavior. + +- **Policy Sampling**: These settings affect the AI's move selection and the heatmap visualization. Tooltips are provided in the app for detailed explanations. + - **Top K**: Considers only the top K moves. + - **Top P**: Considers moves from the smallest set whose cumulative probability exceeds P. + - **Min P**: Considers only moves with a probability of at least P times the probability of the best move. +- **Analysis Settings**: + - **Visits**: The number of playouts the AI will perform for its analysis. Higher values lead to stronger play but require more processing time. +- **Mistake Feedback**: These settings determine when the game will automatically halt. The game halts if the mistake size is above the configured threshold **AND** either of the probability conditions are met. + +Keep in mind that the techniques used are more likely to be helpful up to low-dan levels, and may not be as effective at high-dan or professional levels. diff --git a/pyproject.toml b/pyproject.toml index b9d143c..0f6b3ed 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,16 +1,16 @@ [project] name = "goshape" -version = "0.1.0" +version = "0.2.0" description = "Shape Habits Analysis and Personalized Evaluation" authors = [{name = "Sander Land"}] readme = "README.md" requires-python = ">=3.10,<3.14" dependencies = [ "PySide6>=6.5.0", - "pyqtgraph>=0.13.7", "pysgf>=0.9.0", "numpy>=2.1.2", "httpx>=0.25.0", + "matplotlib>=3.5.0", ] [dependency-groups] @@ -22,6 +22,7 @@ dev = [ [project.scripts] goshape = "shape.main:main" +shape = "shape.main:main" [tool.hatch.build.targets.wheel] packages = ["shape"] diff --git a/shape/game_logic.py b/shape/game_logic.py index 18bafd9..d2aa9d5 100644 --- a/shape/game_logic.py +++ b/shape/game_logic.py @@ -42,8 +42,10 @@ def sample( if prob > 0 ] if self.pass_prob > 0 and not exclude_pass: - moves.append(("pass", self.pass_prob, None)) + moves.append((Move(coords=None), self.pass_prob, self.pass_prob)) moves.sort(key=lambda x: x[1], reverse=True) + if not moves: + return [], "no_moves" highest_prob = moves[0][1] top_moves = [] total_prob = 0 @@ -95,8 +97,10 @@ class GameNode(SGFNode): def __init__(self, parent: "GameNode | None" = None, properties=None, move=None): super().__init__(parent, properties, move) if parent: - assert move is not None - self.board_state = self._board_state_after_move(parent.board_state, move) + if move: + self.board_state = self._board_state_after_move(parent.board_state, move) + else: + self.board_state = copy.deepcopy(parent.board_state) else: bx, by = self.board_size self.board_state: list[list[str | None]] = [[None for _ in range(bx)] for _ in range(by)] @@ -104,6 +108,27 @@ def __init__(self, parent: "GameNode | None" = None, properties=None, move=None) self.ai_move_requested = False # flag to indicate if ai move was manually requested self.autoplay_halted_reason: str | None = None # flag to indicate if autoplay was automatically halted + def _recalculate_board_states(self): + if self.parent: + assert isinstance(self.parent, GameNode) + if self.move: + self.board_state = self._board_state_after_move(self.parent.board_state, self.move) + else: + self.board_state = copy.deepcopy(self.parent.board_state) + else: + bx, by = self.board_size + self.board_state: list[list[str | None]] = [[None for _ in range(bx)] for _ in range(by)] + + for child in self.children: + assert isinstance(child, GameNode) + child._recalculate_board_states() + + def get_last_node(self): + node = self + while node.children: + node = node.children[0] + return node + @property def square_board_size(self) -> int: bx, by = self.board_size @@ -111,7 +136,7 @@ def square_board_size(self) -> int: return bx def game_ended(self) -> bool: - return self.is_pass and self.parent.is_pass + return self.parent is not None and self.is_pass and self.parent.is_pass def delete_child(self, child: "GameNode"): self.children = [c for c in self.children if c is not child] @@ -202,7 +227,10 @@ def analysis_requested(self, key: str | None): def get_analysis(self, key: str | None, parent: bool = False) -> Analysis | None: if parent: - return self.parent.get_analysis(key) if self.parent else None + if not self.parent: + return None + assert isinstance(self.parent, GameNode) + return self.parent.get_analysis(key) analysis = self.analyses.get(key) return None if analysis is Analysis.REQUESTED else analysis @@ -210,6 +238,7 @@ def mistake_size(self) -> float | None: current_analysis = self.get_analysis(None) parent_analysis = None if self.parent: + assert isinstance(self.parent, GameNode) parent_analysis = self.parent.get_analysis(None) if not current_analysis or not parent_analysis: @@ -233,7 +262,7 @@ def __init__(self): self.new_game() def new_game(self, board_size=19, **rules): - self.current_node = GameNode(properties={"RU": "JP", "KM": 6.5, "SZ": board_size, **rules}) + self.current_node: GameNode = GameNode(properties={"RU": "JP", "KM": 6.5, "SZ": board_size, **rules}) def __getattr__(self, attr): if not hasattr(self.current_node, attr): @@ -243,23 +272,64 @@ def __getattr__(self, attr): def make_move(self, move: Move) -> bool: if not self.current_node._is_valid_move(move): return False - self.current_node = self.current_node.play(move) + new_node = self.current_node.play(move) + assert isinstance(new_node, GameNode) + self.current_node = new_node return True def undo_move(self, n: int = 1): while (n := n - 1) >= 0 and self.current_node.parent: + assert isinstance(self.current_node.parent, GameNode) self.current_node = self.current_node.parent def redo_move(self, n: int = 1): while (n := n - 1) >= 0 and self.current_node.children: + assert isinstance(self.current_node.children[0], GameNode) self.current_node = self.current_node.children[0] def get_score_history(self) -> list[tuple[int, float]]: - nodes = self.current_node.nodes_from_root - return [(node.depth, ai_analysis.ai_score()) for node in nodes if (ai_analysis := node.get_analysis(None))] + """Returns a list of (move_number, score) tuples.""" + history = [] + node = self.current_node + while node: + analysis = node.get_analysis(None) + if analysis and analysis.ai_score() is not None: + score = analysis.ai_score() + if score is not None: + move_number = getattr(node, "move_number", 0) + history.append((move_number, score)) + if not node.parent: + break + assert isinstance(node.parent, GameNode) + node = node.parent + return list(reversed(history)) + + def get_full_history(self) -> list[GameNode]: + history = [] + node = self.current_node + while node: + history.append(node) + if not node.parent: + break + assert isinstance(node.parent, GameNode) + node = node.parent + return list(reversed(history)) def export_sgf(self, player_names): - return self.current_node.root.sgf() + root_node = self.get_full_history()[0] + root_node.properties["PB"] = player_names.get("B", "Black") + root_node.properties["PW"] = player_names.get("W", "White") + return root_node.sgf() def import_sgf(self, sgf_data: str): - self.current_node = ShapeSGF.parse(sgf_data) + try: + parsed_sgf_root = ShapeSGF.parse(sgf_data) + assert isinstance(parsed_sgf_root, GameNode) + parsed_sgf_root._recalculate_board_states() + last_node = parsed_sgf_root.get_last_node() + assert isinstance(last_node, GameNode) + self.current_node = last_node + return True + except Exception as e: + logger.error(f"Failed to import SGF: {e}") + return False diff --git a/shape/main.py b/shape/main.py index 7012e74..f9208c9 100644 --- a/shape/main.py +++ b/shape/main.py @@ -1,8 +1,9 @@ import argparse import signal import sys +import traceback -from PySide6.QtWidgets import QApplication +from PySide6.QtWidgets import QApplication, QMessageBox from shape.katago.engine import KataGoEngine from shape.ui.main_window import MainWindow @@ -13,28 +14,41 @@ signal.signal(signal.SIGINT, signal.SIG_DFL) # hard exit on SIGINT +def show_error_dialog(exc_type, exc_value, exc_tb): + """Show a dialog for unhandled exceptions.""" + tb_str = "".join(traceback.format_exception(exc_type, exc_value, exc_tb)) + error_message = f"An unexpected error occurred:\n\n{exc_value}\n\nTraceback:\n{tb_str}" + logger.error(error_message) + + # Ensure QApplication instance exists + if QApplication.instance() is None: + _ = QApplication(sys.argv) + + msg_box = QMessageBox() + msg_box.setIcon(QMessageBox.Icon.Critical) + msg_box.setText("An unexpected error occurred.") + msg_box.setInformativeText(str(exc_value)) + msg_box.setDetailedText(tb_str) + msg_box.setWindowTitle("Error") + msg_box.exec() + sys.exit(1) + + class SHAPEApp: def __init__(self): self.app = QApplication(sys.argv) self.main_window = MainWindow() - try: - self.katago = KataGoEngine() - except Exception as e: - self.show_error(f"Failed to initialize KataGo engine: {e}") - sys.exit(1) - + self.katago = KataGoEngine() self.main_window.set_engine(self.katago) def run(self): self.main_window.show() return self.app.exec() - def show_error(self, message): - logger.error(message) - def main(): + sys.excepthook = show_error_dialog parser = argparse.ArgumentParser(description="SHAPE: Shape Habits Analysis and Personalized Evaluation") parser.parse_args() diff --git a/shape/ui/board_view.py b/shape/ui/board_view.py index 863f924..588ba1e 100644 --- a/shape/ui/board_view.py +++ b/shape/ui/board_view.py @@ -24,7 +24,7 @@ def interpolate_color(color1, color2, ratio): class BoardView(QWidget): - WOOD_COLOR = QColor(220, 179, 92) + WOOD_COLOR = QColor(210, 180, 140) # Tan color for the board PLAYER_POLICY_COLOR = QColor(20, 200, 20) TARGET_POLICY_COLOR = QColor(0, 100, 0) AI_POLICY_COLOR = QColor(0, 0, 139) @@ -36,37 +36,23 @@ def sizeHint(self): def __init__(self, main_window, parent=None): super().__init__(parent) self.main_window = main_window - self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding) + self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Preferred) self.setMinimumSize(400, 400) + def heightForWidth(self, width): + return width + + def hasHeightForWidth(self): + return True + def calculate_dimensions(self, board_size): self.board_size = board_size - cell_size_h = self.width() / (board_size + 0.5) # n-1 grid, 1 l 0.5 r - cell_size_v = self.height() / (board_size + 1.05) # n-1 grid, 0.5 coord 0.5 btn - self.cell_size = min(cell_size_h, cell_size_v) - self.margin_left = self.cell_size - self.margin_top = self.cell_size * 0.5 - self.margin_bottom = self.cell_size + # The container is square, so we can use either width or height + size = min(self.width(), self.height()) + self.cell_size = size / (board_size + 1) + self.margin_left = (self.width() - (board_size - 1) * self.cell_size) / 2 + self.margin_top = (self.height() - (board_size - 1) * self.cell_size) / 2 self.stone_size = self.cell_size * 0.95 - self.nav_buttons = [ - ("⏮", lambda: self.main_window.on_prev_move(1000), 1.3), - ("⏪", lambda: self.main_window.on_prev_move(5), 1.3), - ("◀", lambda: self.main_window.on_prev_move(), 0.9), - ("pass", lambda: self.main_window.on_pass_move(), 1.0), - ("▶", lambda: self.main_window.on_next_move(), 0.9), - ("⏩", lambda: self.main_window.on_next_move(5), 1.3), - ("⏭", lambda: self.main_window.on_next_move(1000), 1.3), - ] - button_width = self.width() / (2 * len(self.nav_buttons)) - self.nav_rects = [ - QRectF( - self.width() * 0.25 + i * button_width, - (board_size + 0.275) * self.cell_size, - button_width, - self.margin_bottom, - ) - for i in range(len(self.nav_buttons)) - ] self.coord_font_size = max(int(self.cell_size / 3), 8) def intersection_coords(self, col, row) -> QPointF: @@ -79,11 +65,11 @@ def paintEvent(self, event): self.calculate_dimensions(self.main_window.game_logic.square_board_size) painter = QPainter(self) - painter.setRenderHint(QPainter.Antialiasing, True) - painter.setRenderHint(QPainter.SmoothPixmapTransform, True) + painter.setRenderHint(QPainter.RenderHint.Antialiasing, True) + painter.setRenderHint(QPainter.RenderHint.SmoothPixmapTransform, True) self.draw_board(painter) - self.draw_coordinates_and_nav(painter) + self.draw_coordinates(painter) self.draw_star_points(painter) heatmap_settings = self.main_window.control_panel.get_heatmap_settings() @@ -94,12 +80,13 @@ def paintEvent(self, event): self.draw_game_status(painter) def draw_board(self, painter): + painter.fillRect(self.rect(), self.WOOD_COLOR) + if self.main_window.game_logic.current_node.autoplay_halted_reason: - color = QColor(self.WOOD_COLOR.red() + 20, self.WOOD_COLOR.green() - 40, self.WOOD_COLOR.blue() - 20) - else: - color = self.WOOD_COLOR - painter.fillRect(self.rect(), color) - painter.setPen(QPen(QColor(0, 0, 0, 180), 1)) + overlay_color = QColor(255, 0, 0, 30) # Semi-transparent red overlay + painter.fillRect(self.rect(), overlay_color) + + painter.setPen(QPen(QColor(0, 0, 0, 100), 1)) # Softer grid lines for i in range(self.board_size): painter.drawLine(self.intersection_coords(0, i), self.intersection_coords(self.board_size - 1, i)) painter.drawLine(self.intersection_coords(i, 0), self.intersection_coords(i, self.board_size - 1)) @@ -108,7 +95,7 @@ def draw_board(self, painter): painter.drawRect(QRectF(self.margin_left, self.margin_top, grid_size, grid_size)) def draw_star_points(self, painter): - painter.setBrush(QBrush(Qt.black)) + painter.setBrush(QBrush(Qt.GlobalColor.black)) for col, row in self.get_star_points(): painter.drawEllipse(self.intersection_coords(col, row), 3, 3) @@ -124,56 +111,50 @@ def draw_stones(self, board_state, painter): center = self.intersection_coords(*last_move.coords) outline_color = QColor(240, 240, 240, 180) if last_move.player == "B" else QColor(50, 50, 50, 180) painter.setPen(QPen(outline_color, 2)) - painter.setBrush(Qt.NoBrush) + painter.setBrush(Qt.BrushStyle.NoBrush) painter.drawEllipse(center, self.stone_size / 4, self.stone_size / 4) def draw_stone(self, painter, row, col, color): center = self.intersection_coords(col, row) - gradient = QRadialGradient(center.x() - self.stone_size / 4, center.y() - self.stone_size / 4, self.stone_size) + gradient = QRadialGradient(center.x() - self.stone_size / 3, center.y() - self.stone_size / 3, self.stone_size) if color == "B": - gradient.setColorAt(0, QColor(80, 80, 80)) - gradient.setColorAt(0.5, Qt.black) - gradient.setColorAt(1, QColor(10, 10, 10)) + gradient.setColorAt(0, QColor(100, 100, 100)) + gradient.setColorAt(0.5, QColor(20, 20, 20)) + gradient.setColorAt(1, Qt.GlobalColor.black) else: - gradient.setColorAt(0, QColor(230, 230, 230)) - gradient.setColorAt(0.5, Qt.white) + gradient.setColorAt(0, Qt.GlobalColor.white) + gradient.setColorAt(0.5, QColor(235, 235, 235)) gradient.setColorAt(1, QColor(200, 200, 200)) painter.setBrush(QBrush(gradient)) - painter.setPen(Qt.NoPen) + painter.setPen(QPen(QColor(50, 50, 50, 100), 0.5)) # Softer stone outline painter.drawEllipse(center, self.stone_size / 2, self.stone_size / 2) - def draw_coordinates_and_nav(self, painter): - font = QFont("Arial", self.coord_font_size, QFont.Bold) + def draw_coordinates(self, painter): + font = QFont("Arial", self.coord_font_size, QFont.Weight.Bold) painter.setFont(font) painter.setPen(QColor(0, 0, 0)) for i in range(self.board_size): bottom_box = self.intersection_coords(i - 0.5, -0.5) painter.drawText( QRectF(bottom_box.x(), bottom_box.y(), self.cell_size, self.cell_size * 0.5), - Qt.AlignHCenter | Qt.AlignTop, + Qt.AlignmentFlag.AlignHCenter | Qt.AlignmentFlag.AlignTop, Move.GTP_COORD[i], ) left_box = self.intersection_coords(-1, i + 0.5) painter.drawText( QRectF(left_box.x(), left_box.y(), self.cell_size * 0.5, self.cell_size), - Qt.AlignVCenter | Qt.AlignRight, + Qt.AlignmentFlag.AlignVCenter | Qt.AlignmentFlag.AlignRight, str(i + 1), ) - for (text, _, size_adj), nav_rect in zip(self.nav_buttons, self.nav_rects, strict=False): - painter.setFont(QFont("Arial", self.coord_font_size * size_adj, QFont.Bold)) - painter.drawText(nav_rect, Qt.AlignCenter, text) def mousePressEvent(self, event): - for (_, callback, _), rect in zip(self.nav_buttons, self.nav_rects, strict=False): - if rect.contains(event.pos()): - callback() - return - col = round((event.x() - self.margin_left) / self.cell_size) - row = round((event.y() - self.margin_top) / self.cell_size) + col = round((event.pos().x() - self.margin_left) / self.cell_size) + row = round((event.pos().y() - self.margin_top) / self.cell_size) + row = self.board_size - row - 1 if 0 <= col < self.board_size and 0 <= row < self.board_size: - self.main_window.make_move((col, self.board_size - row - 1)) + self.main_window.make_move((col, row)) def get_star_points(self): star_points = { @@ -217,7 +198,7 @@ def draw_heatmap(self, painter, policy, sampling_settings): rank_gradient = np.tile(np.linspace(0, 2, self.board_size), (self.board_size, 1)).T heatmap_mean_prob = np.append(prob_gradient.ravel(), 0) heatmap_mean_rank = np.append(rank_gradient.ravel(), 0) - sampling_settings = {"min_p": 0} + sampling_settings["min_p"] = 0.0 if heatmap_mean_prob is not None: top_moves, _ = PolicyData(heatmap_mean_prob).sample( @@ -238,7 +219,7 @@ def draw_heatmap_points(self, painter, top_moves, show_text=True): text = "" if rel_prob < 0.01 else f"{prob * 100:.0f}" painter.setBrush(QBrush(color)) - painter.setPen(QPen(Qt.black)) + painter.setPen(QPen(Qt.GlobalColor.black)) square_size = self.cell_size * size painter.drawRect(QRectF(x - square_size / 2, y - square_size / 2, square_size, square_size)) @@ -249,7 +230,7 @@ def draw_heatmap_points(self, painter, top_moves, show_text=True): painter.setPen(QColor(200, 200, 200)) painter.drawText( QRectF(x - self.cell_size / 2, y - self.cell_size / 2, self.cell_size, self.cell_size), - Qt.AlignCenter, + Qt.AlignmentFlag.AlignCenter, text, ) @@ -277,20 +258,16 @@ def draw_game_status(self, painter): painter.setFont(font) painter.setPen(QColor(0, 0, 0)) text_rect = QRectF(0, 0, self.width(), self.margin_top) - painter.drawText(text_rect, Qt.AlignCenter, message) + painter.drawText(text_rect, Qt.AlignmentFlag.AlignCenter, message) def keyPressEvent(self, event): - if event.key() == Qt.Key_Left: - if event.modifiers() & Qt.ShiftModifier: - self.main_window.on_prev_move(5) - else: - self.main_window.on_prev_move() - elif event.key() == Qt.Key_Right: - if event.modifiers() & Qt.ShiftModifier: - self.main_window.on_next_move(5) - else: - self.main_window.on_next_move() - elif event.key() == Qt.Key_Space: + if self.main_window.game_logic.game_ended(): + return + if event.key() == Qt.Key.Key_Left: + self.main_window.on_prev_move() + elif event.key() == Qt.Key.Key_Right: + self.main_window.on_next_move() + elif event.key() == Qt.Key.Key_P: self.main_window.on_pass_move() else: super().keyPressEvent(event) diff --git a/shape/ui/main_window.py b/shape/ui/main_window.py index 1736e67..c945ac9 100644 --- a/shape/ui/main_window.py +++ b/shape/ui/main_window.py @@ -11,7 +11,9 @@ QMainWindow, QMenu, QMenuBar, + QPushButton, QStatusBar, + QStyle, QTabWidget, QVBoxLayout, QWidget, @@ -37,7 +39,7 @@ def __init__(self): self.katago_engine = None self.game_logic = GameLogic() self.setWindowTitle("SHAPE - Play Go with AI Feedback") - self.setFocusPolicy(Qt.StrongFocus) + self.setFocusPolicy(Qt.FocusPolicy.StrongFocus) self.setup_ui() self.connect_signals() @@ -69,6 +71,12 @@ def connect_signals(self): self.control_panel.settings_updated.connect(self.update_state) self.update_state_main_thread.connect(self.update_state) + # Connect new buttons + self.pass_button.clicked.connect(self.on_pass_move) + self.undo_button.clicked.connect(lambda: self.on_prev_move()) + self.redo_button.clicked.connect(lambda: self.on_next_move()) + self.ai_move_button.clicked.connect(self.request_ai_move) + def update_state(self): self.update_state_timer.start(100) # 100ms debounce @@ -92,6 +100,10 @@ def _update_state(self): tab.update_ui() self.board_view.update() + # Update button states + self.undo_button.setEnabled(self.game_logic.current_node.parent is not None) + self.redo_button.setEnabled(len(self.game_logic.current_node.children) > 0) + def maybe_make_ai_move(self, current_node, human_profiles, current_analysis, next_player_human): if ( not current_node.children and self.control_panel.is_auto_play_enabled() and not next_player_human @@ -246,23 +258,50 @@ def setup_ui(self): self.setCentralWidget(central_widget) main_layout = QHBoxLayout(central_widget) - main_layout.setContentsMargins(0, 0, 0, 0) - main_layout.setSpacing(0) - - self.board_view = BoardView(self) - self.board_view.setFocusPolicy(Qt.StrongFocus) - self.board_view.installEventFilter(self) - main_layout.addWidget(self.board_view, 5) + main_layout.setContentsMargins(5, 5, 5, 5) + main_layout.setSpacing(5) - # Create a container for the right panel with proper margins - right_panel_container = QWidget() - right_panel_layout = QVBoxLayout(right_panel_container) - right_panel_layout.setContentsMargins(0, 12, 0, 0) - right_panel_layout.addWidget(self.create_right_panel_tabs()) + # Left panel with board and buttons + left_panel = QWidget() + left_layout = QVBoxLayout(left_panel) + left_layout.setContentsMargins(0, 0, 0, 0) + left_layout.setSpacing(5) - main_layout.addWidget(right_panel_container, 3) - - self.setMinimumSize(1200, 800) + # Board view with square aspect ratio + self.board_view = BoardView(self) + left_layout.addWidget(self.board_view, stretch=1) + + # Add control buttons below the board with fixed height + button_widget = QWidget() + button_widget.setFixedHeight(50) # Fixed height for buttons + button_layout = QHBoxLayout(button_widget) + button_layout.setContentsMargins(0, 0, 0, 0) + + self.pass_button = QPushButton("Pass") + self.pass_button.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_DialogCloseButton)) + self.undo_button = QPushButton("Undo") + self.undo_button.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_ArrowBack)) + self.redo_button = QPushButton("Redo") + self.redo_button.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_ArrowForward)) + self.ai_move_button = QPushButton("AI Move") + self.ai_move_button.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_ComputerIcon)) + + button_layout.addWidget(self.pass_button) + button_layout.addWidget(self.undo_button) + button_layout.addWidget(self.redo_button) + button_layout.addWidget(self.ai_move_button) + left_layout.addWidget(button_widget) + + main_layout.addWidget(left_panel, stretch=1) + + # Right panel with fixed width + right_panel = self.create_right_panel_tabs() + right_panel.setFixedWidth(400) # Fixed width for right panel + main_layout.addWidget(right_panel) + + # Set window constraints for proper aspect ratio + self.setMinimumSize(1000, 700) + self.resize(1200, 800) def create_right_panel_tabs(self): tab_widget = QTabWidget() @@ -271,19 +310,23 @@ def create_right_panel_tabs(self): play_tab = QWidget() self.control_panel = ControlPanel(self) play_tab.setLayout(self.control_panel) - tab_widget.addTab(play_tab, "Play") + tab_widget.addTab(play_tab, self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPlay), "Play") # AI Analysis tab ai_analysis_tab = QWidget() self.analysis_panel = AnalysisPanel(self) ai_analysis_tab.setLayout(self.analysis_panel) - tab_widget.addTab(ai_analysis_tab, "AI Analysis") + tab_widget.addTab( + ai_analysis_tab, self.style().standardIcon(QStyle.StandardPixmap.SP_ComputerIcon), "AI Analysis" + ) # Settings tab settings_tab = QWidget() self.config_panel = ConfigPanel(self) settings_tab.setLayout(self.config_panel) - tab_widget.addTab(settings_tab, "Settings") + tab_widget.addTab( + settings_tab, self.style().standardIcon(QStyle.StandardPixmap.SP_FileDialogDetailedView), "Settings" + ) return tab_widget def create_status_bar(self): @@ -337,11 +380,33 @@ def create_menu_bar(self): def on_pass_move(self): self.make_move(None) + def resizeEvent(self, event): + """Constrain window resizing to maintain proper aspect ratio""" + super().resizeEvent(event) + + # Get the new size + new_size = event.size() + width = new_size.width() + height = new_size.height() + + # Calculate the board area (total width minus right panel) + board_area_width = width - 400 # Right panel fixed width + + # The board should be square, so calculate required height + # Board height + buttons (50) + margins and menu/status bar (~100) + required_height = board_area_width + 150 + + # If the height is too different from required, adjust it + if abs(height - required_height) > 50: # Allow some tolerance + self.resize(width, required_height) + def eventFilter(self, obj, event): - if obj == self.board_view and event.type() == QEvent.Wheel: - if event.angleDelta().y() > 0: - self.on_prev_move() - elif event.angleDelta().y() < 0: - self.on_next_move() - return True + if event.type() == QEvent.Type.Wheel: + if self.board_view.underMouse(): + delta = event.angleDelta().y() + if delta > 0: + self.on_prev_move() + elif delta < 0: + self.on_next_move() + return True return super().eventFilter(obj, event) diff --git a/shape/ui/tab_analysis.py b/shape/ui/tab_analysis.py index 7cedfa4..62b85b5 100644 --- a/shape/ui/tab_analysis.py +++ b/shape/ui/tab_analysis.py @@ -1,4 +1,13 @@ -import pyqtgraph as pg +import os + +# Set Qt API before importing matplotlib +os.environ["QT_API"] = "pyside6" + +import matplotlib + +matplotlib.use("Qt5Agg") +from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas +from matplotlib.figure import Figure from PySide6.QtCore import Qt from PySide6.QtWidgets import ( QHeaderView, @@ -32,11 +41,15 @@ def create_widgets(self): self.top_moves_table = self.create_top_moves_table() self.addWidget(self.top_moves_table) - self.graph_widget = pg.PlotWidget() - self.graph_widget.setBackground("w") - self.graph_widget.setLabel("left", "Score") - self.graph_widget.showGrid(x=True, y=True, alpha=0.3) - self.addWidget(self.graph_widget) + # Create matplotlib figure and canvas + self.figure = Figure(figsize=(8, 4)) + self.canvas = FigureCanvas(self.figure) + self.axes = self.figure.add_subplot(111) + self.axes.set_xlabel("Move Number") + self.axes.set_ylabel("Score") + self.axes.grid(True, alpha=0.3) + self.figure.tight_layout() + self.addWidget(self.canvas) self.addStretch(1) extra_visits_button = QPushButton("Deeper AI Analysis") @@ -55,9 +68,9 @@ def on_extra_visits(self): def create_top_moves_table(self): table = QTableWidget(5, 4) table.setHorizontalHeaderLabels(["Move", "B Win Rate", "B Score", "Visits"]) - table.horizontalHeader().setSectionResizeMode(QHeaderView.Stretch) - table.setEditTriggers(QTableWidget.NoEditTriggers) - table.setFocusPolicy(Qt.NoFocus) + table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) + table.setEditTriggers(QTableWidget.EditTrigger.NoEditTriggers) + table.setFocusPolicy(Qt.FocusPolicy.NoFocus) table.setMinimumHeight(300) return table @@ -95,7 +108,29 @@ def clear(self): self.top_moves_table.clearContents() def update_graph(self, scores: list[tuple[int, float]]): + if not scores: + scores = [(0, 0.0)] + moves, filtered_values = zip(*scores, strict=False) - self.graph_widget.plot(moves, filtered_values, pen=pg.mkPen(color="b", width=2), clear=True) - self.graph_widget.setYRange(min(filtered_values) - 0.1, max(filtered_values) + 0.1) - self.graph_widget.setXRange(0, max(1, len(moves) - 1)) + + # Clear the plot and redraw + self.axes.clear() + self.axes.plot(moves, filtered_values, "b-o", linewidth=2, markersize=6) + self.axes.set_xlabel("Move Number") + self.axes.set_ylabel("Score") + self.axes.grid(True, alpha=0.3) + + # Add dashed horizontal line at score=0 + self.axes.axhline(y=0, color="gray", linestyle="--", alpha=0.7) + + # Set x-axis from 0 to max move number (no padding) + max_move = max(moves) if moves else 0 + self.axes.set_xlim(0, max(1, max_move)) + + # Center y-axis on 0 + y_min, y_max = min(filtered_values), max(filtered_values) + y_abs_max = max(abs(y_min), abs(y_max), 0.5) # Minimum range of 1.0 total + self.axes.set_ylim(-y_abs_max, y_abs_max) + + # Refresh the canvas + self.canvas.draw() diff --git a/shape/ui/tab_config.py b/shape/ui/tab_config.py index 4fa06ae..4e51bba 100644 --- a/shape/ui/tab_config.py +++ b/shape/ui/tab_config.py @@ -1,6 +1,8 @@ +from PySide6.QtCore import Qt +from PySide6.QtWidgets import QFormLayout, QGroupBox, QHBoxLayout, QLabel, QVBoxLayout + from shape.ui.ui_utils import ( SettingsTab, - create_config_section, create_double_spin_box, create_spin_box, ) @@ -8,39 +10,116 @@ class ConfigPanel(SettingsTab): def create_widgets(self): + self.insertSpacing(0, 10) + # --- Policy Sampling Group --- + policy_group = QGroupBox("Policy Sampling") + policy_layout = QFormLayout(policy_group) + + policy_explanation = QLabel( + "Controls how the AI opponent samples moves to simulate a human player. This does not affect the main analysis engine." + ) + policy_explanation.setWordWrap(True) + policy_layout.addRow(policy_explanation) + self.top_k = create_spin_box(1, 100, 50) + self.top_k.setToolTip("Consider only the top K moves with the highest probability.") + policy_layout.addRow("Top K:", self.top_k) + self.top_p = create_double_spin_box(0.1, 1.0, 1.0, 0.05) + self.top_p.setToolTip("Considers moves from the smallest set whose cumulative probability exceeds P.") + policy_layout.addRow("Top P:", self.top_p) + self.min_p = create_double_spin_box(0.0, 1.0, 0.05, 0.01) - self.addWidget( - create_config_section( - "Policy Sampling Settings", - { - "Top K:": self.top_k, - "Top P:": self.top_p, - "Min P:": self.min_p, - }, - note="These settings affect both opponent move selection and the heatmap visualization.", - ) + self.min_p.setToolTip( + "Consider only moves with a probability of at least P times the probability of the best move." ) + policy_layout.addRow("Min P:", self.min_p) + + self.addWidget(policy_group) + + # --- Analysis Settings Group --- + analysis_group = QGroupBox("Analysis Settings") + analysis_layout = QFormLayout(analysis_group) + + analysis_explanation = QLabel( + "Controls the AI's strength for board analysis and for when it's asked to play the best move (not sampling)." + ) + analysis_explanation.setWordWrap(True) + analysis_layout.addRow(analysis_explanation) + self.visits = create_spin_box(8, 1024, 24) - self.addWidget(create_config_section("Analysis Settings", {"Visits:": self.visits})) + self.visits.setToolTip("The number of playouts the AI will perform. Higher values are stronger but slower.") + analysis_layout.addRow("Visits:", self.visits) + + self.addWidget(analysis_group) + + # --- Mistake Feedback Group --- + mistake_group = QGroupBox("Mistake Feedback Settings") + v_layout = QVBoxLayout(mistake_group) + + explanation = QLabel("Halt auto-play if the last human move was a mistake where:") + explanation.setWordWrap(True) + v_layout.addWidget(explanation) + + # Mistake size + h_layout_mistake = QHBoxLayout() + h_layout_mistake.addSpacing(20) + h_layout_mistake.addWidget(QLabel("Mistake size >")) self.mistake_size_spinbox = create_spin_box(0, 100, 1) + self.mistake_size_spinbox.setToolTip("The minimum score loss for a move to be considered a mistake.") + h_layout_mistake.addWidget(self.mistake_size_spinbox) + h_layout_mistake.addWidget(QLabel("points")) + h_layout_mistake.addStretch() + v_layout.addLayout(h_layout_mistake) + + and_label = QLabel("AND one of the following is true:") + and_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + v_layout.addWidget(and_label) + + # Probabilities + v_layout_probs = QVBoxLayout() + v_layout_probs.setContentsMargins(20, 0, 0, 0) # Indent the whole block + + # Target rank + h_layout_target = QHBoxLayout() + h_layout_target.addWidget(QLabel("Move's rank probability <")) self.target_rank_spinbox = create_spin_box(0, 100, 20) + self.target_rank_spinbox.setToolTip("Halt if the move is very unlikely for the target rank.") + h_layout_target.addWidget(self.target_rank_spinbox) + h_layout_target.addWidget(QLabel("%")) + h_layout_target.addStretch() + v_layout_probs.addLayout(h_layout_target) + + or_label = QLabel("OR") + or_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + v_layout_probs.addWidget(or_label) + + # Policy prob + h_layout_policy = QHBoxLayout() + h_layout_policy.addWidget(QLabel("Move's policy probability <")) self.max_probability_spinbox = create_spin_box(0, 5, 1) - self.addWidget( - create_config_section( - "Mistake Feedback Settings. Halt if:", - { - "Mistake size > (points)": self.mistake_size_spinbox, - "Either Target rank probability < (%)": self.target_rank_spinbox, - "Or Max policy probability < (%)": self.max_probability_spinbox, - }, - ) - ) + self.max_probability_spinbox.setToolTip("Halt if the move is not among the top moves considered by any policy.") + h_layout_policy.addWidget(self.max_probability_spinbox) + h_layout_policy.addWidget(QLabel("%")) + h_layout_policy.addStretch() + v_layout_probs.addLayout(h_layout_policy) + + v_layout.addLayout(v_layout_probs) + + self.addWidget(mistake_group) + self.addStretch(1) def connect_signals(self): - for widget in [self.top_k, self.top_p, self.min_p, self.visits]: + for widget in [ + self.top_k, + self.top_p, + self.min_p, + self.visits, + self.mistake_size_spinbox, + self.target_rank_spinbox, + self.max_probability_spinbox, + ]: widget.valueChanged.connect(self.on_settings_changed) def get_ai_strength(self): diff --git a/shape/ui/tab_main_control.py b/shape/ui/tab_main_control.py index bf477e4..49cca3d 100644 --- a/shape/ui/tab_main_control.py +++ b/shape/ui/tab_main_control.py @@ -62,7 +62,9 @@ def create_game_control_box(self): self.player_color.buttons()[0].setChecked(True) self.auto_play_checkbox = QCheckBox("Auto-play", checked=True) + self.auto_play_checkbox.setToolTip("When checked, the opponent will automatically play its move.") self.ai_move_button = QPushButton("Force Move (Ctrl+Enter)") + self.ai_move_button.setToolTip("Request an immediate move from the opponent, even if it's your turn.") self.ai_move_button.setShortcut("Ctrl+Enter") layout.addWidget(QLabel("Opponent:"), 1, 0) layout.addWidget(self.ai_move_button, 1, 1) @@ -81,12 +83,18 @@ def create_player_settings_group(self): self.rank_dropdowns = {} layout.addWidget(QLabel("Current Rank:"), 0, 0) self.rank_dropdowns["current"] = QComboBox() + self.rank_dropdowns["current"].setToolTip( + "Your current Go skill level. This is used to determine which mistakes are typical for you." + ) self.populate_rank_combo(self.rank_dropdowns["current"], "3k") layout.addWidget(self.rank_dropdowns["current"], 0, 1) # Target Rank layout.addWidget(QLabel("Target Rank:"), 0, 2) self.rank_dropdowns["target"] = QComboBox() + self.rank_dropdowns["target"].setToolTip( + "The skill level you want to aim for. Mistakes common at this level won't be flagged." + ) self.populate_rank_combo(self.rank_dropdowns["target"], "2d") layout.addWidget(self.rank_dropdowns["target"], 0, 3) @@ -94,7 +102,7 @@ def create_player_settings_group(self): layout.addWidget(QLabel("Opponent:"), 1, 0) self.opponent_type_combo = QComboBox() self.opponent_type_combo.addItems(["Rank", "Pre-AZ", "Pro"]) - + self.opponent_type_combo.setToolTip("Select the type of AI opponent.") layout.addWidget(self.opponent_type_combo, 1, 1) self.opponent_pro_combo = QComboBox() @@ -110,7 +118,9 @@ def create_player_settings_group(self): layout.addWidget(self.opponent_rank_preaz_combo, 1, 2, 1, 2) # Heatmap settings - layout.addWidget(QLabel("Heatmap:"), 3, 0) + heatmap_label = QLabel("Heatmap:") + heatmap_label.setToolTip("Visualize the AI's preferred moves for different player models.") + layout.addWidget(heatmap_label, 3, 0) heatmap_layout = QHBoxLayout() heatmap_layout.setSpacing(2) # Reduce spacing between heatmap buttons diff --git a/tests/test_game_logic_extended.py b/tests/test_game_logic_extended.py new file mode 100644 index 0000000..9ae3ce7 --- /dev/null +++ b/tests/test_game_logic_extended.py @@ -0,0 +1,75 @@ +import numpy as np + +from shape.game_logic import GameLogic, Move, PolicyData + + +def test_policy_data_sample_top_k(): + policy = list(np.linspace(0.1, 0.01, 9)) # 3x3 board + policy_data = policy + [0.0] # pass + p = PolicyData(policy_data) + moves, reason = p.sample(top_k=5) + assert reason == "top_k" + assert len(moves) == 5 + assert moves[0][1] > moves[1][1] + + +def test_policy_data_sample_top_p(): + policy = [0.5, 0.3, 0.1, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0] # 3x3 board + policy_data = policy + [0.0] # pass + p = PolicyData(np.array(policy_data)) + moves, reason = p.sample(top_p=0.8) + assert reason == "top_p" + assert len(moves) == 2 + + +def test_policy_data_sample_min_p(): + policy = [0.5, 0.3, 0.1, 0.05, 0.05, 0.0, 0.0, 0.0, 0.0] # 3x3 board + policy_data = policy + [0.0] + p = PolicyData(np.array(policy_data)) + moves, reason = p.sample(min_p=0.3) + assert reason == "min_p" + assert len(moves) == 2 + assert moves[0][1] == 0.5 + assert moves[1][1] == 0.3 + + +def test_game_logic_capture_single_stone(): + game = GameLogic() + game.new_game(board_size=5) + game.make_move(Move(coords=(1, 1), player="B")) + game.make_move(Move(coords=(0, 1), player="W")) + game.make_move(Move(coords=(2, 2), player="B")) # filler + game.make_move(Move(coords=(1, 0), player="W")) + game.make_move(Move(coords=(3, 3), player="B")) # filler + game.make_move(Move(coords=(2, 1), player="W")) + game.make_move(Move(coords=(4, 4), player="B")) # filler + # Now W plays at (1,2) to capture B at (1,1) + assert game.board_state[1][1] == "B" + game.make_move(Move(coords=(1, 2), player="W")) + assert game.board_state[1][1] is None # B stone captured + + +def test_sgf_import_export(): + game = GameLogic() + game.new_game(board_size=9) + game.make_move(Move(coords=(4, 4), player="B")) + game.make_move(Move(coords=(3, 3), player="W")) + sgf_data = game.export_sgf(player_names={"B": "Human", "W": "AI"}) + + new_game = GameLogic() + assert new_game.import_sgf(sgf_data) + assert new_game.board_size == (9, 9) + assert new_game.current_node.move is not None + assert new_game.current_node.move.coords == (3, 3) + assert new_game.current_node.parent is not None + assert new_game.current_node.parent.move is not None + assert new_game.current_node.parent.move.coords == (4, 4) + assert new_game.board_state[4][4] == "B" + assert new_game.board_state[3][3] == "W" + + # Test with pass + game.make_move(Move(coords=None, player="B")) + sgf_data_pass = game.export_sgf(player_names={"B": "Human", "W": "AI"}) + assert "B[]" in sgf_data_pass or "B[tt]" in sgf_data_pass + assert new_game.import_sgf(sgf_data_pass) + assert new_game.current_node.is_pass diff --git a/uv.lock b/uv.lock index dddf34b..48d45ce 100644 --- a/uv.lock +++ b/uv.lock @@ -1,6 +1,6 @@ version = 1 revision = 2 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