def raw_to_spectrum(rawdata):
#print rawdata
#print len(rawdata)
flen = 50
spectrum, relative_spectrum = bin_power(rawdata, range(flen), 512)
#print spectrum
#print relative_spectrum
return spectrum
def raw_to_spectrum(rawdata):
#print rawdata
#print len(rawdata)
flen = 50
spectrum, relative_spectrum = bin_power(rawdata, range(flen), 512)
#print spectrum
#print relative_spectrum
return spectrum
def frame(self, p,window): flen = 50 spectrum, relative_spectrum = bin_power(p.raw_values[-p.buffer_len:], range(flen),512) self.spectra.append(array(relative_spectrum)) if len(self.spectra)>30: self.spectra.pop(0) spectrum = mean(array(self.spectra),axis=0) value = (1-sum(spectrum[3:8]))*100 self.graph.insert_value(time(), value) for i in range(6): pygame.draw.line(window, pygame.Color(0,0,200),(0,400-i*20*3),(600,400-i*20*3), 2) self.graph.draw_graph(window,3.0)
def raw_values_callback(self, raw_values):
""" This function takes the raw values data, in blocks specified by the block size, and
sends it to the sound buffer """
spec,rel_spec = bin_power(raw_values + self.last_raw, [0.5,4,7,9.5,12,21,30], 512)
msg = OSC.OSCMessage("/calcdelta")
msg.append(spec[0])
self.osc_client.send(msg)
msg = OSC.OSCMessage("/calctheta")
msg.append(spec[1])
self.osc_client.send(msg)
msg = OSC.OSCMessage("/calclowbeta")
msg.append(spec[4])
self.osc_client.send(msg)
self.c_low_beta_stab.add_point(spec[4])
msg = OSC.OSCMessage("/calc_low_beta_instability")
msg.append(self.c_low_beta_stab.stability)
self.osc_client.send(msg)
msg = OSC.OSCMessage("/calchighbeta")
msg.append(spec[5])
self.osc_client.send(msg)
self.c_high_beta_stab.add_point(spec[5])
msg = OSC.OSCMessage("/calc_high_beta_instability")
msg.append(self.c_high_beta_stab.stability)
self.osc_client.send(msg)
msg = OSC.OSCMessage("/calclowalpha")
msg.append(spec[2])
self.osc_client.send(msg)
self.c_low_alpha_stab.add_point(spec[2])
msg = OSC.OSCMessage("/calc_low_alpha_instability")
msg.append(self.c_low_alpha_stab.stability)
self.osc_client.send(msg)
msg = OSC.OSCMessage("/calchighalpha")
msg.append(spec[3])
self.osc_client.send(msg)
self.last_raw = raw_values
self.c_high_alpha_stab.add_point(spec[3])
msg = OSC.OSCMessage("/calc_high_alpha_instability")
msg.append(self.c_high_alpha_stab.stability)
self.osc_client.send(msg)
# We're going to try various parameters based on the raw data, from the EEG helpers
eeg_hfd = hfd(raw_values, 10)
eeg_pfd = pfd(raw_values)
msg = OSC.OSCMessage("/eegpfd")
msg.append(eeg_pfd)
self.osc_client.send(msg)
msg = OSC.OSCMessage("/eeghfd")
msg.append(eeg_hfd)
self.osc_client.send(msg)
raw_values = [1. * float(i) / 32768. for i in raw_values]
#print len(raw_values), raw_values
msg = OSC.OSCMessage("/raw_data")
msg.append(raw_values)
self.osc_client.send(msg)
return None
meditation_img = font.render("Meditation", False, redColor)
attention_img = font.render("Attention", False, redColor)
record_baseline = False
while True:
p.update()
#window.blit(background_img,(0,0))
if p.sending_data:
iteration+=1
flen = 50
if len(p.raw_values)>=500:
spectrum, relative_spectrum = bin_power(p.raw_values[-p.buffer_len:], range(flen),512)
spectra.append(array(relative_spectrum))
if len(spectra)>30:
spectra.pop(0)
spectrum = mean(array(spectra),axis=0)
for i in range (flen-1):
value = float(spectrum[i]*1000)
if i<3:
color = deltaColor
elif i<8:
color = thetaColor
elif i<13:
color = alphaColor
elif i<30:
color = betaColor
