""" ============= Chess Masters ============= An example of the MultiDiGraph clas The function chess_pgn_graph reads a collection of chess matches stored in the specified PGN file (PGN ="Portable Game Notation"). Here the (compressed) default file:: chess_masters_WCC.pgn.bz2 contains all 685 World Chess Championship matches from 1886--1985. (data from http://chessproblem.my-free-games.com/chess/games/Download-PGN.php) The `chess_pgn_graph()` function returns a `MultiDiGraph` with multiple edges. Each node is the last name of a chess master. Each edge is directed from white to black and contains selected game info. The key statement in `chess_pgn_graph` below is:: G.add_edge(white, black, game_info) where `game_info` is a `dict` describing each game. """ import matplotlib.pyplot as plt import networkx as nx # tag names specifying what game info should be # stored in the dict on each digraph edge game_details = ["Event", "Date", "Result", "ECO", "Site"] def chess_pgn_graph(pgn_file="chess_masters_WCC.pgn.bz2"): """Read chess games in pgn format in pgn_file. Filenames ending in .gz or .bz2 will be uncompressed. Return the MultiDiGraph of players connected by a chess game. Edges contain game data in a dict. """ import bz2 G = nx.MultiDiGraph() game = {} datafile = bz2.BZ2File(pgn_file) lines = (line.decode().rstrip("\r\n") for line in datafile) for line in lines: if line.startswith("["): tag, value = line[1:-1].split(" ", 1) game[str(tag)] = value.strip('"') else: # empty line after tag set indicates # we finished reading game info if game: white = game.pop("White") black = game.pop("Black") G.add_edge(white, black, **game) game = {} return G G = chess_pgn_graph() ngames = G.number_of_edges() nplayers = G.number_of_nodes() print(f"Loaded {ngames} chess games between {nplayers} players\n") # identify connected components # of the undirected version H = G.to_undirected() Gcc = [H.subgraph(c) for c in nx.connected_components(H)] if len(Gcc) > 1: print("Note the disconnected component consisting of:") print(Gcc[1].nodes()) # find all games with B97 opening (as described in ECO) openings = {game_info["ECO"] for (white, black, game_info) in G.edges(data=True)} print(f"\nFrom a total of {len(openings)} different openings,") print("the following games used the Sicilian opening") print('with the Najdorff 7...Qb6 "Poisoned Pawn" variation.\n') for (white, black, game_info) in G.edges(data=True): if game_info["ECO"] == "B97": print(white, "vs", black) for k, v in game_info.items(): print(" ", k, ": ", v) print("\n") # make new undirected graph H without multi-edges H = nx.Graph(G) # edge width is proportional number of games played edgewidth = [] for (u, v, d) in H.edges(data=True): edgewidth.append(len(G.get_edge_data(u, v))) # node size is proportional to number of games won wins = dict.fromkeys(G.nodes(), 0.0) for (u, v, d) in G.edges(data=True): r = d["Result"].split("-") if r[0] == "1": wins[u] += 1.0 elif r[0] == "1/2": wins[u] += 0.5 wins[v] += 0.5 else: wins[v] += 1.0 try: pos = nx.nx_agraph.graphviz_layout(H) except ImportError: pos = nx.spring_layout(H, iterations=20) plt.rcParams["text.usetex"] = False plt.figure(figsize=(8, 8)) nx.draw_networkx_edges(H, pos, alpha=0.3, width=edgewidth, edge_color="m") nodesize = [wins[v] * 50 for v in H] nx.draw_networkx_nodes(H, pos, node_size=nodesize, node_color="w", alpha=0.4) nx.draw_networkx_edges(H, pos, alpha=0.4, node_size=0, width=1, edge_color="k") nx.draw_networkx_labels(H, pos, font_size=14) font = {"fontname": "Helvetica", "color": "k", "fontweight": "bold", "fontsize": 14} plt.title("World Chess Championship Games: 1886 - 1985", font) # change font and write text (using data coordinates) font = {"fontname": "Helvetica", "color": "r", "fontweight": "bold", "fontsize": 14} plt.text( 0.5, 0.97, "edge width = # games played", horizontalalignment="center", transform=plt.gca().transAxes, ) plt.text( 0.5, 0.94, "node size = # games won", horizontalalignment="center", transform=plt.gca().transAxes, ) plt.axis("off") plt.show()