# Path: brain.py
# def cochlear(filename, stride, rate, db=-40, ears=1, a_1=-0.995, apply_filter=1, suffix='cochlear'):
#     original_rate, data = wavfile.read(filename)
#     assert data.dtype == np.int16
#     data = data / float(2**15)
#     if original_rate != rate:
#         data = resample(data, float(rate)/original_rate, 'sinc_best')
#     data = data*10**(db/20)
#     utils.array_to_csv('{}-audio.txt'.format(filename), data)
#     call(['./carfac-cmd', filename, str(len(data)), str(ears), str(rate), str(stride), str(a_1), str(apply_filter), suffix])
#     naps = utils.csv_to_array(filename+suffix)
#     return np.sqrt(np.maximum(0, naps)/np.max(naps))
# 
# Path: brain.py
# NUMBER_OF_BRAINS = 5


import os
import wave
import csv
import time
import re
import linecache
import sys
import cPickle as pickle
import zlib
import random
import multiprocessing as mp
import threading
import glob
import fcntl
import json
import sched
import datetime
import numpy as np
import zmq
import scipy.fftpack
import cv2
import IO
        import matplotlib.pyplot as plt
    import Oger
    import mdp
from subprocess import call
from scipy.io import wavfile
from sklearn.covariance import EmpiricalCovariance, MinCovDet
from scipy.stats import itemfreq
from brain import cochlear
from brain import NUMBER_OF_BRAINS
    from scipy.io import wavfile
        output.flush()
                        
class LoggerProcess(mp.Process):
    ''' File to write log over ZMQ socket. '''
    def run(self):
        my_logger = Logger() # Must be in run, not __init__
        sys.stdout = my_logger
        sys.stderr = my_logger

        me = mp.current_process()
        print '{} PID {}'.format(me.name, me.pid)
        AliveNotifier(me)
        
        mp.Process.run(self)
        
class MyProcess(mp.Process):
    def run(self):
        AliveNotifier(mp.current_process())
        
        mp.Process.run(self)

def brain_name():
    return 'BRAIN_{}'.format(time.strftime('%Y_%m_%d_%H_%M_%S'))
        
def find_last_valid_brain():
    files = glob.glob('BRAIN_*')
    files.sort(key=os.path.getmtime, reverse=True)
    for f in files[::NUMBER_OF_BRAINS]:
        stem = f[:f.find('.')] # We know the filename is BRAIN_XXXX.FACE RESPONDER etc
        try: 

# Path: brain.py
# def cochlear(filename, stride, rate, db=-40, ears=1, a_1=-0.995, apply_filter=1, suffix='cochlear'):
#     original_rate, data = wavfile.read(filename)
#     assert data.dtype == np.int16
#     data = data / float(2**15)
#     if original_rate != rate:
#         data = resample(data, float(rate)/original_rate, 'sinc_best')
#     data = data*10**(db/20)
#     utils.array_to_csv('{}-audio.txt'.format(filename), data)
#     call(['./carfac-cmd', filename, str(len(data)), str(ears), str(rate), str(stride), str(a_1), str(apply_filter), suffix])
#     naps = utils.csv_to_array(filename+suffix)
#     return np.sqrt(np.maximum(0, naps)/np.max(naps))
# 
# Path: brain.py
# NUMBER_OF_BRAINS = 5


# Path: utils.py
import os
import wave
import csv
import time
import re
import linecache
import sys
import cPickle as pickle
import zlib
import random
import multiprocessing as mp
import threading
import glob
import fcntl
import json
import sched
import datetime
import numpy as np
import zmq
import scipy.fftpack
import cv2
import IO
        import matplotlib.pyplot as plt
    import Oger
    import mdp
from subprocess import call
from scipy.io import wavfile
from sklearn.covariance import EmpiricalCovariance, MinCovDet
from scipy.stats import itemfreq
from brain import cochlear
from brain import NUMBER_OF_BRAINS
    from scipy.io import wavfile

        output.flush()
                        
class LoggerProcess(mp.Process):
    ''' File to write log over ZMQ socket. '''
    def run(self):
        my_logger = Logger() # Must be in run, not __init__
        sys.stdout = my_logger
        sys.stderr = my_logger

        me = mp.current_process()
        print '{} PID {}'.format(me.name, me.pid)
        AliveNotifier(me)
        
        mp.Process.run(self)
        
class MyProcess(mp.Process):
    def run(self):
        AliveNotifier(mp.current_process())
        
        mp.Process.run(self)

def brain_name():
    return 'BRAIN_{}'.format(time.strftime('%Y_%m_%d_%H_%M_%S'))
        
def find_last_valid_brain():
    files = glob.glob('BRAIN_*')
    files.sort(key=os.path.getmtime, reverse=True)
    for f in files[::NUMBER_OF_BRAINS]:
        stem = f[:f.find('.')] # We know the filename is BRAIN_XXXX.FACE RESPONDER etc
        try: 

            if len([ load(candidate) for candidate in glob.glob('{}*'.format(stem)) ]) == NUMBER_OF_BRAINS: