Arquivos
emotion-classification/cPickleparser.py
T
2014-11-21 18:52:56 +05:30

46 linhas
1.3 KiB
Python

import cPickle
import os.path
from multiprocessing import Pool
import sys
def main():
nLabel, nTrial, nUser, nChannel, nTime = 4, 40, 32, 40, 8064
#new_array = [[[None] *w for i in range(h)] for j in range(l)]
print "Program started"+"\n"
fout_data = open("data/features_raw.dat",'w')
fout_labels0 = open("data/labels_0.dat",'w')
fout_labels1 = open("data/labels_1.dat",'w')
fout_labels2 = open("data/labels_2.dat",'w')
fout_labels3 = open("data/labels_3.dat",'w')
for i in range(nUser):#4, 40, 32, 40, 8064
if(i%8 == 0):
if i < 10:
name = '%0*d' % (2,i+1)
else:
name = i+1
fname = "data/raw/s"+str(name)+".dat"
x = cPickle.load(open(fname, 'rb'))
print fname
for tr in range(nTrial):
if(tr%1 == 0):
for dat in range(nTime):
if(dat%32 == 0):
for ch in range(nChannel):
#fout_data.write(str(ch+1) + " ");
fout_data.write(str(x['data'][tr][ch][dat]) + " ");
fout_labels0.write(str(x['labels'][tr][0]) + "\n");
fout_labels1.write(str(x['labels'][tr][1]) + "\n");
fout_labels2.write(str(x['labels'][tr][2]) + "\n");
fout_labels3.write(str(x['labels'][tr][3]) + "\n");
fout_data.write("\n");
fout_labels0.close()
fout_labels1.close()
fout_labels2.close()
fout_labels3.close()
fout_data.close()
print "\n"+"Print Successful"
if __name__ == "__main__":
main()