from numpy import *
FINALTRAINING=[[],[]]
FINALDEV=[[],[]]
import os
TRAINING=[]
DEV=[]
import random
import time


def pooling(image):
        b=ones(image.shape[0])
        for i in range(image.shape[0]):
                mb=[]
                for j in range(image.shape[1]/4):
                        mb.append(image[i,j*4:(j+1)*4].max())
                b=vstack([b,asarray(mb)])
        return b[1:,:]
                        
import matplotlib
matplotlib.use('Agg')
from pylab import *


for i in range(280,502):
	os.chdir('/NAS3/SABIOD/public_data/SCATT_BIRD_50mostE_perfile_april2014_RB_HG/'+str(i))
	m=[]
	b=loadtxt("carres.dat")
	os.chdir('/NAS3/SABIOD/public_data/SCATT_BIRD_50mostE_perfile_april2014_RB_HG_bestSTD_rectangle/'+str(i))
	for j in range(len(b)):
		del m
		m=concatenate((b[j,:68].reshape(-1,68),b[j,68:136].reshape(-1,68),b[j,136:204].reshape(-1,68),b[j,204:].reshape(-1,68)))
		m=transpose(m)
		m=m[2:-2,6:-10]
 		fig = figure()
    		fig.set_size_inches(4, 1)
    		ax = Axes(fig, [0., 0., 1., 1.])
    		ax.set_axis_off()
    		fig.add_axes(ax)
		imshow(m,aspect='auto')
		savefig('classe'+str(i)+'_best'+str(j)+'_std.png',dpi=64)	
	print i
	os.chdir("../")