OfflineRelaxAndMoveMindwave.py

#coding: latin-1
#
# Run me with frameworkpython inside a virtual environment.
# Or install the environment.yml for Anaconda.

# This program uses Mindawave object to connect using bluetooth to Mindwave
# and get the raw eeg signals from there.
# 
# It also plot the signal using matplotlib.
#
# Fs = 128

import socket,select
import json

import time, datetime, sys

import matplotlib.pyplot as plt

import sys

import pyaudio
volume = 0.5     # range [0.0, 1.0]
fs = 44100       # sampling rate, Hz, must be integer
duration = 0.01   # in seconds, may be float
fwave = 440.0        # sine frequency, Hz, may be float

p = pyaudio.PyAudio()

stream = p.open(format=pyaudio.paFloat32,
                channels=1,
                rate=fs,
                output=True)

lamdalength = 10
Fs=128
show=False

# Please provide the number of sample points to take
if (len(sys.argv) > 1):
    samplepoints = int(sys.argv[1])
else:
    samplepoints = Fs*lamdalength


# def windowing(window, N):
#     if len(window)>=N:
#     if not False:
#         awindow = np.asarray( window )
#         fullsignal = fullsignal + window
#         afullsignal = np.asarray( fullsignal )

#         if (len(fullsignal) > 0):
#             awindow = awindow - afullsignal.mean(0)

#         o1 = psd(awindow[:,0])
#         o2 = psd(awindow[:,1])

#         print (o1, o2)

#         features.append( [o1, o2] )

#     # Slide window
#     window = window[N/2:N]
#     #window = window[1:N]

print ('Please remove the VGA connection that sometimes interfere with Mindwave')

import numpy as np
import mindwave, time

from pydub import AudioSegment
from pydub.playback import play

song = AudioSegment.from_wav("BoatHonk.wav")
explosion = AudioSegment.from_wav("explosion.wav")

import matplotlib.image as mpimg

import sys
# insert at 1, 0 is the script path (or '' in REPL)
sys.path.insert(1, '../python-sumo/')

from interface import SumoController

from Plotter import Plotter

#headset = mindwave.Headset('/dev/tty.MindWaveMobile-DevA','ef47')
headset = mindwave.OfflineHeadset()

time.sleep(2)

plotter = Plotter(500,-500,500)

attention = 0
meditation = 0
eeg = 0


ts = time.time()
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d-%H-%M-%S')
filename = './data/eeg.'+st+'.dat'
f = open(filename, 'w')

window = []
N = 128
signaleeg = []
mistakes = 0

plt.title("Entrenamiento...")
try:
    while (headset.poor_signal > 5):
        print ("Headset signal noisy %d. Adjust the headset and the earclip." % (headset.poor_signal))

    print ("Writing %d seconds output to %s" % (lamdalength,filename))
    for i in range(0,samplepoints):
        #time.sleep(.01)
        headset.dequeue()
        (count,eeg, attention, meditation, blink) = (headset.count, headset.raw_value, headset.attention, headset.meditation, headset.blink)

        window.append( int(eeg) )
        signaleeg.append( int (eeg) )

        if len(window) > N:
            window = window[N/2:N]

        awindow = np.asarray(window)
        #blink = np.sum(np.abs(awindow[0:N/2]))

        plotter.plotdata( [eeg, 0, 0, blink])
        #plotter.plotdata( [eeg, 0, 0])
        samples = (np.sin(2*np.pi*np.arange(fs*duration)*(fwave+int(eeg))/fs)).astype(np.float32)
        stream.write(volume*samples)

        ts = time.time()
        st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d-%H-%M-%S.%f')
        f.write( str(ts) + ' ' + str(count) + ' ' + str(eeg) + ' ' + str(attention) + ' ' + str(meditation) + ' ' + str(blink) + '\n')

finally:
    pass

        
asignaleeg = np.asarray( signaleeg )
meanval = np.mean( signaleeg )
stdval = np.std( signaleeg )

print(meanval)
print(stdval)

headset.close()
headset.setupfile()

print("Ready to continue...")
sys.stdin.read(1)

plt.title("A Relajarse !!!!")
try:
    while (headset.poor_signal > 5):
        print ("Headset signal noisy %d. Adjust the headset and the earclip." % (headset.poor_signal))

    print ("Writing %d seconds output to %s" % (lamdalength,filename))
    for i in range(0,samplepoints):
        #time.sleep(.01)
        headset.dequeue()
        (count,eeg, attention, meditation, blink) = (headset.count, headset.raw_value, headset.attention, headset.meditation, headset.blink)

        window.append( int(eeg) )
        signaleeg.append( int (eeg) )

        if len(window) > N:
            window = window[N/2:N]

        awindow = np.asarray(window)
        #blink = np.sum(np.abs(awindow[0:N/2]))

        threshold = meanval+stdval

        plotter.plotdata( [eeg, threshold, 0, blink])
        #plotter.plotdata( [eeg, 0, 0])

        if (int(eeg)>int(threshold)):
            mistakes = mistakes + 1
            play(song)

        if (mistakes>3):
            play(explosion)
            print("Press a key. Endgame")
            sys.stdin.read(1)
            quit()

        ts = time.time()
        st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d-%H-%M-%S.%f')
        f.write( str(ts) + ' ' + str(count) + ' ' + str(eeg) + ' ' + str(attention) + ' ' + str(meditation) + ' ' + str(blink) + '\n')


finally:
    headset.stop()
    f.close()


if (False):
    controller = SumoController()
    controller.move(100, duration=0.5)
    controller.store_pic()

sys.stdin.read(1)