pca.py

   1 #!/usr/bin/python
   2 """
   3 This code creates input vectors and performs PCA on it. Each pca'd vector is then printed along with
   4 the player name, suitable e.g. to plot using gnuplot.
   5 """
   6 # not true currently
   7 """
   8 OUTPUT FORMAT
   9 player_name first_principal_component_of_player's_input_vector second_principal_component ...
  10 second_player_name ...
  11 ...
  12 """
  13 import sys
  14 from gostyle import print_vector, OccurenceVectorGenerator, Rescale, PlayerStrategyIdentificator, PCA, InputVectorGenerator
  15 from itertools import izip, count
  16 from data_about_players import Data
  17
  18 if __name__ == '__main__':
  19         main_pat_filename = Data.main_pat_filename
  20         num_features = 500
  21         players_ignore = [ 'Honinbo Shusaku',  'Kuwahara Shusaku', 'Yasuda Shusaku', 'Go Seigen', 'Suzuki Goro', 'Jie Li' ] #, 'Cho Chikun', 'Takemiya Masaki']
  22         players_all = Data.players_all
  23         players = [ p for p in players_all if p not in players_ignore ]
  24         #players = Data.player_vector.keys()
  25
  26         ### Objects creating input and output vectors when called
  27         print >>sys.stderr, "Creating input vector generator from main pat file:", main_pat_filename
  28         i = InputVectorGenerator(main_pat_filename, num_features)
  29
  30         # Create pairs of (input vector, player name)
  31         input_vectors = []
  32         for name in players:
  33                 #input_vectors += [i( Data.pat_files_folder + name)]
  34                 input_vectors += [[float(occ) for occ in i(Data.pat_files_folder + name)]]
  35
  36         if len(input_vectors) == 0:
  37                 print >>sys.stderr, "No input vectors.", main_pat_filename
  38                 sys.exit()
  39
  40         # Create PCA object, trained on input_vectors
  41         pca = PCA(input_vectors, output_dim=10)
  42         #pca = PCA(input_vectors, reduce=True)
  43
  44         # Perform a PCA on input vectors
  45         input_vectors = pca.process_list_of_vectors(input_vectors)
  46
  47         def transpose(list_of_vectors):
  48                 tran = []
  49                 for i in xrange(len(list_of_vectors[0])):
  50                         tran.append([list_of_vectors[j][i] for j in xrange(len(list_of_vectors))])
  51                 return tran
  52
  53         ### Now we rescale vectors, so that each component fits on -1.0 to 1.0
  54         ### this makes a very nice plot!!
  55         r = Rescale(-1.0,1.0)
  56         # Normalize each component separately
  57         input_vectors = transpose([ r(vector) for vector in transpose(input_vectors)])
  58
  59         # prints vectors along with player names
  60         for name,vector in izip(players, input_vectors):
  61                 # Substitute ' ' by '_' to allow for gnuplot plotting (recognizing columns correctly)
  62                 name_to_print = '_'.join(name.split())
  63
  64                 for p, i in izip(vector, count()):
  65                         print name_to_print, i+1, p
  66
  67                 #print name_to_print,
  68                 #print_vector(vector)
  69
  70         print >> sys.stderr, "\nNow print that by:"
  71         print >> sys.stderr, 'gnuplot> set xrange[1:%d]'%(pca.pca.output_dim+1)
  72         print >> sys.stderr, 'gnuplot> plot "./pca.data" using 2:3:1 with labels font "arial,10" left point pt 4 offset 1,0'