Chess MastersΒΆ

../../_images/chess_masters1.png

[source code]

#!/usr/bin/env python

"""
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.

"""
#    Copyright (C) 2006-2010 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

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


if __name__ == '__main__':
    import networkx as nx


    G=chess_pgn_graph()

    ngames=G.number_of_edges()
    nplayers=G.number_of_nodes()

    print("Loaded %d chess games between %d players\n"\
                   % (ngames,nplayers))

    # identify connected components
    # of the undirected version
    Gcc=list(nx.connected_component_subgraphs(G.to_undirected()))
    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=set([game_info['ECO']
                  for (white,black,game_info) in G.edges(data=True)])
    print("\nFrom a total of %d different openings,"%len(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")


    try:
        import matplotlib.pyplot as plt
    except ImportError:
        import sys
        print("Matplotlib needed for drawing. Skipping")
        sys.exit(0)

    # 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.graphviz_layout(H)
    except:
        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,fontsize=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.savefig("chess_masters.png",dpi=75)
    print("Wrote chess_masters.png")
    plt.show() # display