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.
9 player_name first_principal_component_of_player's_input_vector second_principal_component ...
10 second_player_name ...
14 from gostyle
import print_vector
, OccurenceVectorGenerator
, Rescale
, PlayerStrategyIdentificator
, PCA
, InputVectorGenerator
15 from itertools
import izip
, count
16 from data_about_players
import Data
18 if __name__
== '__main__':
19 main_pat_filename
= Data
.main_pat_filename
21 players_ignore
= [ 'Cho Tae-hyeon', 'Shao Zhenzhong', 'Wu Songsheng', '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()
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 ivg
= InputVectorGenerator(main_pat_filename
, num_features
)
30 # Create pairs of (input vector, player name)
33 #input_vectors += [ivg( Data.pat_files_folder + name)]
34 input_vectors
+= [[float(occ
) for occ
in ivg(Data
.pat_files_folder
+ name
)]]
36 if len(input_vectors
) == 0:
37 print >>sys
.stderr
, "No input vectors.", main_pat_filename
40 # Create PCA object, trained on input_vectors
41 pca
= PCA(input_vectors
, output_dim
=10)
42 #pca = PCA(input_vectors, reduce=True)
44 # Perform a PCA on input vectors
45 input_vectors
= pca
.process_list_of_vectors(input_vectors
)
47 ### Now we rescale vectors, so that each component fits on -1.0 to 1.0
48 ### this makes a very nice plot!!
51 ### Normalize each component separately
52 # We need to transpose input_vectors - a list of per-player-vector-of-pca-component
53 # to get list of vectors of per-component-vector-of-player-data
54 def transpose(list_of_vectors
):
55 return zip(*list_of_vectors
)
56 input_vectors
= transpose([ r(vector
) for vector
in transpose(input_vectors
)])
58 # prints vectors along with player names
59 for name
,vector
in izip(players
, input_vectors
):
60 # Substitute ' ' by '_' to allow for gnuplot plotting (recognizing columns correctly)
61 name_to_print
= '_'.join(name
.split())
63 for p
, i
in izip(vector
, count()):
64 print name_to_print
, i
+1, p
69 print "\nProjection info:"
70 P
= pca
.get_projection_info()
71 for y
in xrange(1, P
.shape
[0]):
72 for x
in xrange(1, P
.shape
[1]):
73 print y
, x
, P
[y
,x
], ivg
.ovg
.stringof(x
)
76 print >> sys
.stderr
, "\nNow print that by:"
77 print >> sys
.stderr
, 'gnuplot> set xrange[1:%d]'%(pca
.pca
.output_dim
+1)
78 print >> sys
.stderr
, 'gnuplot> plot "./pca.data" using 2:3:1 with labels font "arial,10" left point pt 4 offset 1,0'