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chessAnalyzer/Chess-Coordinate-Trainer-master/Data/data.txt

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chessAnalyzer/Chess-Coordinate-Trainer-master/Icons/CCT.ico

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+#!/usr/bin/env python3
+
+def graph(pgn, engine, location):
+    import chess.pgn
+    print('Loading everything...')
+
+    # for i in range(1, 3):
+    act_game = chess.pgn.read_game(open(pgn))
+
+    headers = chess.pgn.read_headers(open(pgn))
+
+    print('Analyzing this game_in_question: ' + headers["Event"] + " | " + headers["White"] +
+          " - " + headers["Black"] + "  " + headers["Result"] +
+          " | " + headers["Date"])
+
+    # import chess.engine
+    #
+    # engine = chess.engine.SimpleEngine.popen_uci("C:/Users/iitda/Chess_analysis/stockfish_9_x64.exe")
+
+    import chess.engine
+
+    engine = chess.engine.SimpleEngine.popen_uci(engine)
+
+    board = act_game.board()
+    board.fen()
+
+    import numpy as np
+
+    print('Making functions...')
+
+    def fentotensor(inputstr):
+        pieces_str = "PNBRQK"
+        pieces_str += pieces_str.lower()
+        pieces = set(pieces_str)
+        valid_spaces = set(range(1, 9))
+        pieces_dict = {pieces_str[0]: 1, pieces_str[1]: 2, pieces_str[2]: 3, pieces_str[3]: 4,
+                       pieces_str[4]: 5, pieces_str[5]: 6,
+                       pieces_str[6]: -1, pieces_str[7]: -2, pieces_str[8]: -3, pieces_str[9]: -4,
+                       pieces_str[10]: -5, pieces_str[11]: -6}
+
+        boardtensor = np.zeros((8, 8, 6))
+
+        inputliste = inputstr.split()
+        rownr = 0
+        colnr = 0
+        for i, c in enumerate(inputliste[0]):
+            if c in pieces:
+                boardtensor[rownr, colnr, np.abs(pieces_dict[c]) - 1] = np.sign(pieces_dict[c])
+                colnr = colnr + 1
+            elif c == '/':  # new row
+                rownr = rownr + 1
+                colnr = 0
+            elif int(c) in valid_spaces:
+                colnr = colnr + int(c)
+            else:
+                raise ValueError("invalid fenstr at index: {} char: {}".format(i, c))
+
+        return boardtensor
+
+    def countpieces(fen):
+        boardtensor = fentotensor(fen)
+        count = np.sum(np.abs(boardtensor))
+        return count
+
+    # print(countpieces(board.fen()))
+    countpieces(board.fen())
+
+    # print(fentotensor(board.fen()))
+
+    def pawnending(fen):
+        boardtensor = fentotensor(fen)
+        counts_1 = np.sum(np.abs(boardtensor), axis=(0, 1))
+        if counts_1[1] == 0 and counts_1[2] == 0 and counts_1[3] == 0 and counts_1[4] == 0:
+            return True
+        else:
+            return False
+
+    def rookending(fen):
+        boardtensor = fentotensor(fen)
+        counts_2 = np.sum(np.abs(boardtensor), axis=(0, 1))
+        if counts_2[1] == 0 and counts_2[2] == 0 and counts_2[4] == 0 and counts_2[3] > 0:
+            return True
+        else:
+            return False
+
+    # Register a standard info handler.
+    # info_handler = chess.uci.InfoHandler()
+    # engine.info_handlers.append(info_handler)
+
+    counts = {"movecount": [], "scores": [], "check": [], "bestdiff": [], "pawnending": [], "rookending": []}
+
+    # Iterate through all moves and play them on a board.
+    board = act_game.board()
+
+    print('Analyzing game_in_question...')
+
+    for move in act_game.mainline_moves():
+        board.push(move)
+        cnt = len([i for i in board.legal_moves])
+        counts["movecount"].append(cnt)
+        counts["check"].append(board.is_check())
+        counts["pawnending"].append(pawnending(board.fen()))
+        counts["rookending"].append(rookending(board.fen()))
+
+        # Start a search.
+        info = engine.analyse(board, chess.engine.Limit(time=0.1))
+        if board.turn == chess.WHITE:
+            counts["scores"].append(int(str(info["score"].white().score(mate_score=10000))) / 100)
+        else:
+            counts["scores"].append(int(str(info["score"].white().score(mate_score=10000))) / 100)
+        nextmovescores = []
+
+        for mov in board.legal_moves:
+            board.push(mov)
+            info = engine.analyse(board, chess.engine.Limit(time=0.02))
+            if board.turn == chess.WHITE:
+                if str(info["score"].white().score(mate_score=10000)) is not None:
+                    try:
+                        nextmovescores.append(int(str(info["score"].white().score(mate_score=10000))))
+                    except:
+                        nextmovescores.append(+99)
+            elif board.turn == chess.BLACK:
+                if str(info["score"].white().score(mate_score=10000)) is not None:
+                    try:
+                        nextmovescores.append(int(str(info["score"].white().score(mate_score=10000))))
+                    except:
+                        nextmovescores.append(-99)
+            board.pop()
+
+        if len(nextmovescores) > 1:
+            nextmovescores.sort(reverse=True)
+            counts["bestdiff"].append(nextmovescores[0] - nextmovescores[1])
+        else:
+            counts["bestdiff"].append(0)
+
+    engine.quit()
+
+    import plotly
+    import plotly.graph_objs as go
+
+    print('Creating graph...')
+
+    # username = 'iitdanand' # Replace with YOUR USERNAME
+    # api_key = 'SxRczLKT7c4RV4QStrMu' # Replace with YOUR API KEY
+
+    # auth = HTTPBasicAuth(username, api_key)
+
+    # py.sign_in('iitdanand', 'SxRczLKT7c4RV4QStrMu')
+
+    # py.sign_in('PythonAPI', 'SxRczLKT7c4RV4QStrMu')
+
+    checkcolor = ['red' if i else 'white' for i in counts["check"]]
+    checknr = [i for (i, s) in enumerate(counts["check"]) if s]
+    bubble = [s / 2 for s in counts["movecount"]]
+    best = [np.log(s + 1) for s in counts["bestdiff"]]
+
+    rookcolor = ['blue' if i else 'white' for i in counts["rookending"]]
+    pawncolor = ['green' if i else 'white' for i in counts["pawnending"]]
+
+    shapes = []
+    lists = [checkcolor, rookcolor, pawncolor]
+    for (i, list_num) in enumerate(lists):
+        shapes = shapes + [
+            dict(
+                type='rect',
+                # x-reference is assigned to the x-values
+                xref='x',
+                # y-reference is assigned to the plot paper [0,1]
+                yref='paper',
+                x0=i,
+                y0=0,
+                x1=i + 1,
+                y1=1,
+                fillcolor=s,
+                opacity=0.2,
+                line=dict(
+                    width=0,
+                )
+            )
+            for (i, s) in enumerate(list_num)]
+
+    annotations = [dict(
+        xref='x',
+        yref='paper',
+        x=s,
+        y=(0.05 + i * 0.2) % 1,
+        text='Check!',
+        opacity=0.8,
+        xanchor='left',
+        showarrow=False,
+        ax=20,
+        ay=-30,
+        font=dict(
+            family='Courier New, monospace',
+            size=16,
+            color='red'
+        ),
+    )
+        for (i, s) in enumerate(checknr)]
+
+    # print(counts_1["scores"])
+
+    trace1 = go.Scatter(
+        mode='markers+lines',
+        y=counts["scores"],
+        name='Scores',
+
+        line=dict(
+            color='black',
+            width=4,
+        ),
+        marker=dict(
+            size=bubble,
+            line=dict(color='rgb(231, 99, 250)', width=1),
+            cmax=max(best),
+            cmin=min(best),
+            color=best,
+            colorbar=dict(title='Criticality'),
+            colorscale='Jet'
+        )
+    )
+
+    data = [trace1]
+
+    ht = headers["Event"] + " || " + headers["White"] + " - " + headers["Black"] + "  " + \
+         headers["Result"] + " || " + headers["Date"]
+
+    layout = dict(title=ht,
+                  xaxis=dict(title='Half Move'),
+                  yaxis=dict(title='Score'),
+                  shapes=shapes,
+                  annotations=annotations
+                  )
+
+    fig = {
+        'data': data,
+        'layout': layout,
+    }
+
+    # plotly.plot(fig, filename='chessviz{}'.format('New2'), kind=)
+    plotly.offline.plot(fig, filename=location.format(headers["White"] + ' vs ' + headers["Black"]))