def __init__(self, port, receiver_ip, receiver_port, user):
ServerThread.__init__(self, port)
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.receiver_ip = receiver_ip
self.receiver_port = receiver_port
self.server = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.user = user
def __init__(self, port, receiver_ip, receiver_port, user):
ServerThread.__init__(self, port)
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.receiver_ip = receiver_ip
self.receiver_port = receiver_port
self.server = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.user = user
def __init__(self, port=18000, slhost='127.0.0.1:9951', **kwargs):
ServerThread.__init__(self, port, **kwargs)
self.ping = False
self.tempo = 120
self.prefix = 'osc.udp://'
self.slhost = self.prefix + slhost
self.host = self.prefix + '127.0.0.1:' + str(port)
def __init__(self, server, destport=10024, srcport=11111, debug=False, **kwargs):
"""Class initialiser."""
self.timeout = self.settable['timeout'] = 500
self.server = self.settable['server'] = server
self.destport = self.settable['destport'] = destport
# add built-in custom command shortcuts
self.shortcuts.update({
'/': 'osc',
})
# add built-in custom command aliases
kwargs.setdefault('use_ipython', True)
super().__init__(**kwargs)
self.aliases.update({
'mute': 'osc /lr/mix/on 0',
'unmute': 'osc /lr/mix/on 1',
'mainvol': '/lr/mix/fader',
})
self.srcport = srcport
self.debug = debug
self.osc_commands = parse_commands()
self.osc_command_names = sorted([cmd.address.lstrip('/')
for cmd in self.osc_commands.values()])
self.queue = queue.Queue()
self.osc = ServerThread(self.srcport)
self.osc.add_method(None, None, self.osc_recv)
# hooks
self.register_preloop_hook(self.start_osc_server)
self.register_postloop_hook(self.stop_osc_server)
def __init__(self, name='osc2midi', midi='jack', port=9999, target=None):
ServerThread.__init__(self, port)
self.events = {
'CTRL': CtrlEvent,
'NOTEON': NoteOnEvent,
'NOTEOFF': NoteOffEvent,
'PROGRAM': ProgramEvent,
'PITCHBEND': PitchbendEvent,
'AFTERTOUCH': AftertouchEvent,
'SYSEX': SysExEvent
}
self.eventTypes = []
self.name = name
self.midi = midi
self.midiPorts = {
'in' : [name + '_in'],
'out': [name + '_out']
}
if type(target) == int:
self.target = '127.0.0.1:' + str(target)
elif type(target) == str:
self.target = target
else:
self.target = None
midiServer.config(
backend = self.midi,
client_name = self.name,
in_ports = self.midiPorts['in'],
out_ports = self.midiPorts['out']
)
def __init__(self,
incoming,
outgoing,
sparseOutput=None,
config={},
device_source='Muse',
software_source='muselsl',
debug_outputs=True,
verbose=False):
self.incoming = incoming
self.outgoing = outgoing
self.eeg_chunk_length = 12
self.threshold = 30
self.conc_level = 50
self.inc = 2
self._osc_server = ServerThread(incoming['port'])
print('OSC server initialized at port {}.'.format(incoming['port']))
if not isinstance(self.outgoing, tuple):
self.outgoing = [self.outgoing]
self._output_threads = []
for out in self.outgoing:
self._output_threads.append(Address(out['address'], out['port']))
print('OSC client initialized at {}:{}.'.format(
out['address'], out['port']))
self._init_processing(config)
self.incremented_value = 50
def __init__(self, muse_port, muse_id, server):
self.muse_port = muse_port
self.muse_id = muse_id
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
logger.info('Muse %s connected to museIO on port %s' % (muse_id, muse_port))
# configure the Spacebrew client
self.brew = SpacebrewApp(muse_id, server=server)
self.osc_paths = [
'/muse/eeg',
'/muse/eeg/quantization',
# '/muse/eeg/dropped_samples',
'/muse/acc',
# '/muse/acc/dropped_samples',
'/muse/batt',
# '/muse/drlref',
#'/muse/elements/raw_fft0',
#'/muse/elements/raw_fft1',
#'/muse/elements/raw_fft2',
#'/muse/elements/raw_fft3',
'/muse/elements/low_freqs_absolute',
'/muse/elements/delta_absolute',
'/muse/elements/theta_absolute',
'/muse/elements/alpha_absolute',
'/muse/elements/beta_absolute',
'/muse/elements/gamma_absolute',
#'/muse/elements/delta_relative',
#'/muse/elements/theta_relative',
#'/muse/elements/alpha_relative',
#'/muse/elements/beta_relative',
#'/muse/elements/gamma_relative',
#'/muse/elements/delta_session_score',
#'/muse/elements/theta_session_score',
#'/muse/elements/alpha_session_score',
#'/muse/elements/beta_session_score',
#'/muse/elements/gamma_session_score',
'/muse/elements/touching_forehead',
'/muse/elements/horseshoe',
'/muse/elements/is_good',
'/muse/elements/blink',
'/muse/elements/jaw_clench',
'/muse/elements/experimental/concentration',
'/muse/elements/experimental/mellow'
]
for osc_path in self.osc_paths:
spacebrew_name = self.calculate_spacebrew_name(osc_path)
self.brew.add_publisher(spacebrew_name, 'string')
logger.debug('Spacebrew publisher %s added for muse with ID %s' % (spacebrew_name, self.muse_id))
# Connect to spacebrew
self.brew.start()
logger.debug('Initialization completed for muse with ID %s' % self.muse_id)
def add_method(self, oscSetup ): that = self def action( path, args ): data = dict(zip(oscSetup.names,args)) data['_path'] = path oscSetup.callback( data ) that.callback( data ) ServerThread.add_method( self, oscSetup.path, oscSetup.types, action )
def __init__(self, name, signaler, daemon_address, debug):
ServerThread.__init__(self)
self.name = name
self.signaler = signaler
self.daemon_address = daemon_address
self.debug = debug
self.server_capabilities = ""
global instance
instance = self
def send(self, target, *message):
"""
Send osc message over udp
"""
if target.isdigit():
target = '127.0.0.1:' + target
if 'osc.udp://' not in target:
target = 'osc.udp://' + target
ServerThread.send(self, target, *message)
def send(self, target, *message):
"""
Send osc message over udp
"""
if target.isdigit():
target = '127.0.0.1:' + target
if 'osc.udp://' not in target:
target = 'osc.udp://' + target
ServerThread.send(self, target, *message)
def __init__(self):
self.acc_lock = th.RLock()
self.acc_list = []
self.blink_lock = th.RLock()
self.blink_list = deque()
self.jaw_lock = th.RLock()
self.jaw_list = deque()
self.senstate_lock = th.RLock()
self.senstate = []
ServerThread.__init__(self, 5001)
def __init__(self, namespace, **kwargs):
"""
Server contructor
Args:
namespace (str): osc method addresses will be prefixed with /namespace
disabled with an empty string
"""
ServerThread.__init__(self, reg_methods=False, **kwargs)
self.namespace = namespace if namespace == '' or namespace[0] == '/' else '/' + namespace
self.osc_methods = {}
self.add_method(None, None, self.route_osc)
def __init__(self, muse_port, muse_id, server):
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
# configure the Spacebrew client
self.brew = SpacebrewApp(muse_id, server=server)
self.osc_paths = [
{'address': "/muse/eeg", 'arguments': 4},
{'address': "/muse/eeg/quantization", 'arguments': 4},
{'address': "/muse/eeg/dropped_samples", 'arguments': 1},
{'address': "/muse/acc", 'arguments': 3},
{'address': "/muse/acc/dropped_samples", 'arguments': 1},
{'address': "/muse/batt", 'arguments': 4},
{'address': "/muse/drlref", 'arguments': 2},
{'address': "/muse/elements/low_freqs_absolute", 'arguments': 4},
{'address': "/muse/elements/delta_absolute", 'arguments': 4},
{'address': "/muse/elements/theta_absolute", 'arguments': 4},
{'address': "/muse/elements/alpha_absolute", 'arguments': 4},
{'address': "/muse/elements/beta_absolute", 'arguments': 4},
{'address': "/muse/elements/gamma_absolute", 'arguments': 4},
{'address': "/muse/elements/delta_relative", 'arguments': 4},
{'address': "/muse/elements/theta_relative", 'arguments': 4},
{'address': "/muse/elements/alpha_relative", 'arguments': 4},
{'address': "/muse/elements/beta_relative", 'arguments': 4},
{'address': "/muse/elements/gamma_relative", 'arguments': 4},
{'address': "/muse/elements/delta_session_score", 'arguments': 4},
{'address': "/muse/elements/theta_session_score", 'arguments': 4},
{'address': "/muse/elements/alpha_session_score", 'arguments': 4},
{'address': "/muse/elements/beta_session_score", 'arguments': 4},
{'address': "/muse/elements/gamma_session_score", 'arguments': 4},
{'address': "/muse/elements/touching_forehead", 'arguments': 1},
{'address': "/muse/elements/horseshoe", 'arguments': 4},
{'address': "/muse/elements/is_good", 'arguments': 4},
{'address': "/muse/elements/blink", 'arguments': 1},
{'address': "/muse/elements/jaw_clench", 'arguments': 1},
{'address': "/muse/elements/experimental/concentration", 'arguments': 1},
{'address': "/muse/elements/experimental/mellow", 'arguments': 1}
]
self.paths = [path['address'] for path in self.osc_paths]
for path in self.paths:
spacebrew_name = path.split('/')[-1]
self.brew.add_publisher(spacebrew_name, "string")
# connect to spacebrew
self.brew.start()
def __init__(self, namespace, **kwargs):
"""
Server contructor
Args:
namespace (str): osc method addresses will be prefixed with /namespace
disabled with an empty string
"""
ServerThread.__init__(self, reg_methods=False, **kwargs)
self.namespace = namespace if namespace == '' or namespace[
0] == '/' else '/' + namespace
self.osc_methods = {}
self.add_method(None, None, self.route_osc)
def __init__(self, muse_port, began_at):
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
self.began_at = began_at
self.osc_paths = [
{'address': "/muse/eeg", 'arguments': 4},
{'address': "/muse/eeg/quantization", 'arguments': 4},
{'address': "/muse/eeg/dropped_samples", 'arguments': 1},
{'address': "/muse/acc", 'arguments': 3},
{'address': "/muse/acc/dropped_samples", 'arguments': 1},
{'address': "/muse/batt", 'arguments': 4},
{'address': "/muse/drlref", 'arguments': 2},
{'address': "/muse/elements/low_freqs_absolute", 'arguments': 4},
{'address': "/muse/elements/delta_absolute", 'arguments': 4},
{'address': "/muse/elements/theta_absolute", 'arguments': 4},
{'address': "/muse/elements/alpha_absolute", 'arguments': 4},
{'address': "/muse/elements/beta_absolute", 'arguments': 4},
{'address': "/muse/elements/gamma_absolute", 'arguments': 4},
{'address': "/muse/elements/delta_relative", 'arguments': 4},
{'address': "/muse/elements/theta_relative", 'arguments': 4},
{'address': "/muse/elements/alpha_relative", 'arguments': 4},
{'address': "/muse/elements/beta_relative", 'arguments': 4},
{'address': "/muse/elements/gamma_relative", 'arguments': 4},
{'address': "/muse/elements/delta_session_score", 'arguments': 4},
{'address': "/muse/elements/theta_session_score", 'arguments': 4},
{'address': "/muse/elements/alpha_session_score", 'arguments': 4},
{'address': "/muse/elements/beta_session_score", 'arguments': 4},
{'address': "/muse/elements/gamma_session_score", 'arguments': 4},
{'address': "/muse/elements/touching_forehead", 'arguments': 1},
{'address': "/muse/elements/horseshoe", 'arguments': 4},
{'address': "/muse/elements/is_good", 'arguments': 4},
{'address': "/muse/elements/blink", 'arguments': 1},
{'address': "/muse/elements/jaw_clench", 'arguments': 1},
{'address': "/muse/elements/experimental/concentration", 'arguments': 1},
{'address': "/muse/elements/experimental/mellow", 'arguments': 1}
]
self.paths = [path['address'] for path in self.osc_paths]
class qlcStopper(object):
def __init__(self, port, qlcappport):
self.port = port
if self.port is not None:
self.server = ServerThread(self.port)
self.server.register_methods(self)
self.server.start()
@make_method('/Stop', None)
def allStopQlc(self, path, args):
for path in paths:
self.server.send(qlcappport, path, 0)
class FFTServer():
def __init__(self,
incoming,
outgoing,
sparseOutput=None,
config={},
device_source='Muse',
software_source='muselsl',
debug_outputs=True,
verbose=False):
self.incoming = incoming
self.outgoing = outgoing
self.eeg_chunk_length = 12
self.threshold = 30
self.conc_level = 50
self.inc = 2
self._osc_server = ServerThread(incoming['port'])
print('OSC server initialized at port {}.'.format(incoming['port']))
if not isinstance(self.outgoing, tuple):
self.outgoing = [self.outgoing]
self._output_threads = []
for out in self.outgoing:
self._output_threads.append(Address(out['address'], out['port']))
print('OSC client initialized at {}:{}.'.format(
out['address'], out['port']))
self._init_processing(config)
self.incremented_value = 50
def _init_processing(self, config):
DEFAULT_CONFIG = {
'fs': 256.,
'n_channels': 5,
'raw_buffer_len': 3 * 256,
'filt_buffer_len': 3 * 256,
'window_len': 256,
'step': int(256 / 10),
'filter': ([1], [1]),
'filter_bank': {},
'psd_window_len': 256.,
'psd_buffer_len': 10
}
config = {**DEFAULT_CONFIG, **config}
self.fs = config['fs']
self.n_channels = config['n_channels']
self.eeg_ch_remap = None
self.n_channels = 4
raw_buffer_len = int(config['raw_buffer_len'])
filt_buffer_len = int(config['filt_buffer_len'])
self.eeg_buffer = ut.NanBuffer(raw_buffer_len, self.n_channels)
self.filt_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
self.hpfilt_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
self.smooth_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
if config['filter']:
if isinstance(config['filter'], tuple):
b = config['filter'][0]
a = config['filter'][1]
elif isinstance(config['filter'], dict):
b, a = ut.get_filter_coeff(self.fs, **config['filter'])
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.bandpass_filt = {'b': b, 'a': a, 'zi': zi}
if config['hpfilter']:
b = config['hpfilter'][0]
a = config['hpfilter'][1]
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.hp_filt = {'b': b, 'a': a, 'zi': zi}
if config['lpfilter']:
b = config['lpfilter'][0]
a = config['lpfilter'][1]
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.lp_filt = {'b': b, 'a': a, 'zi': zi}
if config['filter_bank']:
self.filter_bank = {}
for name, coeff in config['filter_bank'].items():
zi = np.tile(signal.lfilter_zi(coeff[0], coeff[1]),
(self.n_channels, 1)).T
self.filter_bank[name] = {
'b': coeff[0],
'a': coeff[1],
'zi': zi
}
self.window_len = int(config['window_len'])
self.step = int(config['step'])
psd_buffer_len = int(config['psd_buffer_len'])
self.psd_buffer = ut.CircularBuffer(psd_buffer_len, 129,
self.n_channels)
decayRate = 0.997
self.hists = {
'delta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 50),
min_count=80,
decay=decayRate),
'theta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 30),
min_count=80,
decay=decayRate),
'alpha':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 20),
min_count=80,
decay=decayRate),
'beta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 10),
min_count=80,
decay=decayRate),
'gamma':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 10),
min_count=80,
decay=decayRate)
}
self.firstWindowProc = True
def _update_eeg_liblo_osc(self, path, args):
sample = np.array(args).reshape(1, -1)
self._process_eeg(sample[:, :self.n_channels], 0)
def _process_eeg(self, samples, timestamp):
self.eeg_buffer.update(samples)
filt_samples = samples
if config['filter']:
filt_samples, self.bandpass_filt['zi'] = signal.lfilter(
self.bandpass_filt['b'],
self.bandpass_filt['a'],
samples,
axis=0,
zi=self.bandpass_filt['zi'])
self.filt_eeg_buffer.update(filt_samples)
if config['hpfilter']:
filt_samples, self.hp_filt['zi'] = signal.lfilter(
self.hp_filt['b'],
self.hp_filt['a'],
filt_samples,
axis=0,
zi=self.hp_filt['zi'])
self.hpfilt_eeg_buffer.update(filt_samples)
if config['lpfilter']:
smooth_eeg_samples, self.lp_filt['zi'] = signal.lfilter(
self.lp_filt['b'],
self.lp_filt['a'],
filt_samples,
axis=0,
zi=self.lp_filt['zi'])
else:
smooth_eeg_samples = filt_samples
self.smooth_eeg_buffer.update(smooth_eeg_samples)
if config['filter_bank']:
filter_bank_samples = {}
for name, filt_dict in self.filter_bank.items():
filter_bank_samples[name], self.filter_bank[name][
'zi'] = signal.lfilter(filt_dict['b'],
filt_dict['a'],
filt_samples,
axis=0,
zi=self.filter_bank[name]['zi'])
low_freq_chs = filter_bank_samples['delta'][0, [
0, 2
]] #+ filter_bank_samples['theta'][0, [0, 1]]
window = self.smooth_eeg_buffer.extract(self.window_len)
if self.smooth_eeg_buffer.pts % 3 == 0:
self._send_output_vec(smooth_eeg_samples, timestamp, 'muse/eeg')
if self.eeg_buffer.pts > self.step:
self.eeg_buffer.pts = 0
if config['lpfilter']:
window = self.smooth_eeg_buffer.extract(self.window_len)
psd_raw_buffer = self.eeg_buffer.extract(self.window_len)
psd, f = ut.fft_continuous(psd_raw_buffer,
n=int(self.fs),
psd=True,
log='psd',
fs=self.fs,
window='hamming')
self.psd_buffer.update(np.expand_dims(psd, axis=0))
mean_psd = np.nanmean(self.psd_buffer.extract(), axis=0)
bandPowers, bandNames = ut.compute_band_powers(mean_psd,
f,
relative=True)
ratioPowers, ratioNames = ut.compute_band_ratios(bandPowers)
if (self.firstWindowProc):
self.band_powers = bandPowers
self.band_names = bandNames
self.ratio_powers = ratioPowers
self.ratio_names = ratioNames
self.scores = np.zeros((len(self.band_names), self.n_channels))
self.firstWindowProc = False
for i, (name, hist) in enumerate(self.hists.items()):
self.band_powers = bandPowers
self.ratio_powers = ratioPowers
self.combine_bands = ut.get_combined_bands(self.band_powers)
self.concentration = ut.compute_concentration(
ut.get_combined_bands(self.band_powers))
if self.conc_level >= 0 and self.conc_level <= 98:
self.conc_level += ut.concentration_incrementer(
ut.compute_concentration(
ut.get_combined_bands(self.band_powers)),
self.threshold)
band_names = ['delta', 'theta', 'alpha', 'beta', 'gamma']
self._send_bands(self.combine_bands, timestamp, band_names)
self._send_outputs(self.band_powers, timestamp, 'bands')
self._send_outputs(self.ratio_powers, timestamp, 'ratios')
self._send_float(self.concentration, timestamp, 'concentration')
print(self.concentration)
self._send_float(100 - self.concentration, timestamp, 'arousal')
self._send_float(self.conc_level, timestamp,
'concentration_incremented')
self._send_float(100 - self.conc_level, timestamp,
'arousal_incremented')
def inc_inc(self, num):
self.incremented_value += num
def _send_outputs(self, output, timestamp, name):
for out in self._output_threads:
for c in range(self.n_channels):
new_output = [('f', x) for x in output[:, c]]
message = Message('/{}{}'.format(name, c), *new_output)
send(out, message)
def _send_output_vec(self, output, timestamp, name):
for out in self._output_threads:
new_output = [('f', x) for x in output[0, :]]
message = Message('/{}'.format(name), *new_output)
send(out, message)
def _send_output(self, output, timestamp, name):
for out in self._output_threads:
if (np.array(output).size == 1):
new_output = [('f', np.asscalar(output))]
message = Message('/{}'.format(name), *new_output)
send(out, message)
def _send_float(self, output, timestamp, name):
for out in self._output_threads:
new_output = [('f', output)]
message = Message('/{}'.format(name), *new_output)
send(out, message)
def _send_bands(self, output, timestamp, names):
for out in self._output_threads:
for i in range(5):
new_output = [('f', output[i])]
message = Message('/{}'.format(names[i]), *new_output)
send(out, message)
def start(self):
self.started = True
self._osc_server.add_method('/muse/eeg', None,
self._update_eeg_liblo_osc)
self._osc_server.start()
def stop(self):
self.started = False
def __init__(self,
incoming,
outgoing,
sparseOutput=None,
config={},
device_source='Muse',
software_source='muselsl',
debug_outputs=True,
verbose=False):
self.incoming = incoming
self.outgoing = outgoing
self.sparseOutput = sparseOutput
self.device_source = device_source
self.software_source = software_source
self.debug_outputs = debug_outputs
self.verbose = verbose
self.eeg_chunk_length = 12
# 1. Initialize inlet
if isinstance(self.incoming, str): # LSL inlet
print('Looking for the {} stream...'.format(incoming))
self._stream = resolve_byprop('type', incoming, timeout=2)
if len(self._stream) == 0:
raise (RuntimeError('Can\'t find {} stream.'.format(incoming)))
print('Aquiring data from the \'{}\' stream...'.format(incoming))
self._inlet = StreamInlet(self._stream[0],
max_chunklen=self.eeg_chunk_length)
self._info_in = self._inlet.info()
else: # OSC port
if USE_LIBLO:
self._osc_server = ServerThread(incoming['port'])
print('OSC server initialized at port {}.'.format(
incoming['port']))
else:
self._dispatcher = dispatcher.Dispatcher()
print('python-osc dispatcher initialized.')
# 2. Initialize outlets
if not isinstance(self.outgoing, tuple):
self.outgoing = [self.outgoing]
self._output_threads = []
for out in self.outgoing:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
elif isinstance(out, dict): # OSC port
if USE_LIBLO:
self._output_threads.append(
Address(out['address'], out['port']))
else:
raise NotImplementedError
# self._client = udp_client.SimpleUDPClient(
# outgoing['address'], outgoing['port'])
print('OSC client initialized at {}:{}.'.format(
out['address'], out['port']))
if (self.sparseOutput != None):
if not isinstance(self.sparseOutput, tuple):
self.sparseOutput = [self.sparseOutput]
self._sparseOutput_threads = []
for out in self.sparseOutput:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
elif isinstance(out, dict): # OSC port
if USE_LIBLO:
self._sparseOutput_threads.append(
Address(out['address'], out['port']))
else:
raise NotImplementedError
print('OSC sparse output client initialized at {}:{}.'.
format(out['address'], out['port']))
# 3. Initialize internal buffers and variables
self._init_processing(config)
t = 0
def print_diff():
global t, error, bpm
if t == 0:
t = time()
return
if bpm != seq.bpm:
bpm = seq.bpm
error = 0
t = time()
return
nt = time()
error += 60. / bpm - (nt - t)
t = nt
print("Cumulated error: %s%.3f ms (%5.2f" %
(' ' if str(error)[0] != '-' else '', round(1000000 * error) / 1000,
abs(100 * error / (60. / bpm))) + "%) at " + str(bpm) + " bpm")
sequencer_monitor = ServerThread(port=9900)
sequencer_monitor.add_method('/tic', None, print_diff)
sequencer_monitor.start()
seq.send(':/Sequencer/Sequence/Enable', 'metronom')
seq.play()
seq.start()
class XAirCmdApp(cmd.Cmd):
allow_cli_args = False
abbrev = True
intro = "Enter OSC command (Control-C or Control-D to quit)..."
prompt = 'xair> '
# legalChars = u'/' + cmd.Cmd.legalChars
def __init__(self, server, destport=10024, srcport=11111, debug=False, **kwargs):
"""Class initialiser."""
self.timeout = self.settable['timeout'] = 500
self.server = self.settable['server'] = server
self.destport = self.settable['destport'] = destport
# add built-in custom command shortcuts
self.shortcuts.update({
'/': 'osc',
})
# add built-in custom command aliases
kwargs.setdefault('use_ipython', True)
super().__init__(**kwargs)
self.aliases.update({
'mute': 'osc /lr/mix/on 0',
'unmute': 'osc /lr/mix/on 1',
'mainvol': '/lr/mix/fader',
})
self.srcport = srcport
self.debug = debug
self.osc_commands = parse_commands()
self.osc_command_names = sorted([cmd.address.lstrip('/')
for cmd in self.osc_commands.values()])
self.queue = queue.Queue()
self.osc = ServerThread(self.srcport)
self.osc.add_method(None, None, self.osc_recv)
# hooks
self.register_preloop_hook(self.start_osc_server)
self.register_postloop_hook(self.stop_osc_server)
def osc_recv(self, path, args, types, addr):
log.debug("OSC RECV (%s, %s): %s %s [%s]", addr.hostname, addr.port, path,
types, ", ".join(repr(arg) for arg in args))
self.queue.put((path, args, types, addr))
def do_osc(self, line):
if not line:
return self.help_osc()
try:
oscaddr, rawargs = line.split(None, 1)
except ValueError:
oscaddr = line
rawargs = ''
oscaddr = '/' + oscaddr.lstrip('/')
# ~ if not oscaddr.startswith('/'):
# ~ self.perror("OSC address must start with a slash", traceback_war=False)
# ~ return
oscargs = []
for arg in shlex.split(rawargs, posix=False):
if arg.strip():
try:
oscargs.append(ast.literal_eval(arg))
except: # noqa:E722
oscargs.append(arg)
log.debug("OSC SEND -> (%s, %s): %s %s", self.server, self.destport, oscaddr,
"".join("%r" % arg for arg in oscargs))
self.osc.send((self.server, self.destport), oscaddr, *oscargs)
try:
path, args, types, addr = self.queue.get(timeout=self.timeout / 1000)
except queue.Empty:
self.p_warn("No reply within timeout ({:d} msec).".format(self.timeout))
else:
self.p_ok("{} {} [{}]".format(path, types, ", ".join(repr(arg) for arg in args)))
def help_osc(self):
self.poutput("osc ADDR [arg1 [arg2] ... [argn]]")
def complete_osc(self, text, line, begidx, endidx):
log.debug((text, line, begidx, endidx))
#if not text.startswith('/'):
# text = '/' + text
return self.delimiter_complete(text, line, begidx, endidx, self.osc_command_names, '/')
def p_ok(self, msg):
self.poutput(msg, color=Fore.GREEN)
def p_warn(self, msg):
self.poutput(msg, color=Fore.YELLOW)
def start_osc_server(self) -> None:
self.osc.start()
def stop_osc_server(self) -> None:
self.osc.stop()
self.poutput('')
def postparse(self, parse_result) -> None:
log.debug("postparse: %r", list(parse_result))
return parse_result
def __init__(self,port=5001): ServerThread.__init__(self, port)
def __init__(self, muse_port, callback_functions): ServerThread.__init__(self, muse_port) self.callback_functions = callback_functions
def __init__(self, host, mode):
ServerThread.__init__(self, 8998 + int(random() * 9000), mode)
self.host = host
def stop(self):
ServerThread.stop(self)
midiServer.quit()
class qlcDelayer(object):
def __init__(self, port, qlcappport):
self.port = port
if self.port is not None:
self.server = ServerThread(self.port)
self.server.register_methods(self)
self.server.start()
@make_method(None, 'i')
def sendToQlc(self, path, args):
sleep(.001)
self.server.send(qlcappport, path, args[0])
@make_method(None, 'fff') # /BC/1 R G B
@make_method(None, 'iii') # /BC/1 R G B
def sendToQlcRgb(self, path, args):
if '/Segment' in path:
sleep(.001)
self.server.send(qlcappport, path.replace('/Segment', '/Red/Segment'), args[0])
self.server.send(qlcappport, path.replace('/Segment', '/Green/Segment'), args[1])
self.server.send(qlcappport, path.replace('/Segment', '/Blue/Segment'), args[2])
def __init__(self, muse_port, muse_id, server):
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
# configure the Spacebrew client
self.brew = SpacebrewApp(muse_id, server=server)
self.osc_paths = [{
'address': "/muse/eeg",
'arguments': 4
}, {
'address': "/muse/eeg/quantization",
'arguments': 4
}, {
'address': "/muse/eeg/dropped_samples",
'arguments': 1
}, {
'address': "/muse/acc",
'arguments': 3
}, {
'address': "/muse/acc/dropped_samples",
'arguments': 1
}, {
'address': "/muse/batt",
'arguments': 4
}, {
'address': "/muse/drlref",
'arguments': 2
}, {
'address': "/muse/elements/low_freqs_absolute",
'arguments': 4
}, {
'address': "/muse/elements/delta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/theta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/alpha_absolute",
'arguments': 4
}, {
'address': "/muse/elements/beta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/gamma_absolute",
'arguments': 4
}, {
'address': "/muse/elements/delta_relative",
'arguments': 4
}, {
'address': "/muse/elements/theta_relative",
'arguments': 4
}, {
'address': "/muse/elements/alpha_relative",
'arguments': 4
}, {
'address': "/muse/elements/beta_relative",
'arguments': 4
}, {
'address': "/muse/elements/gamma_relative",
'arguments': 4
}, {
'address': "/muse/elements/delta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/theta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/alpha_session_score",
'arguments': 4
}, {
'address': "/muse/elements/beta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/gamma_session_score",
'arguments': 4
}, {
'address': "/muse/elements/touching_forehead",
'arguments': 1
}, {
'address': "/muse/elements/horseshoe",
'arguments': 4
}, {
'address': "/muse/elements/is_good",
'arguments': 4
}, {
'address': "/muse/elements/blink",
'arguments': 1
}, {
'address': "/muse/elements/jaw_clench",
'arguments': 1
}, {
'address': "/muse/elements/experimental/concentration",
'arguments': 1
}, {
'address': "/muse/elements/experimental/mellow",
'arguments': 1
}]
self.paths = [path['address'] for path in self.osc_paths]
for path in self.paths:
spacebrew_name = path.split('/')[-1]
self.brew.add_publisher(spacebrew_name, "string")
# connect to spacebrew
self.brew.start()
def __init__(self, muse_port, callback_functions):
ServerThread.__init__(self, muse_port)
self.callback_functions = callback_functions
def __init__(self, ip, port, start_muse_io, callback_functions):
ServerThread.__init__(self, port)
self.callback_functions = callback_functions
if start_muse_io:
_start_muse_io(port)
])
error = 0
t = 0
def print_diff():
global t, error, bpm
if t == 0:
t = time()
return
if bpm != seq.bpm:
bpm=seq.bpm
error = 0
t = time()
return
nt = time()
error += 60. / bpm - (nt - t)
t = nt
print("Cumulated error: %s%.3f ms (%5.2f" % (' ' if str(error)[0]!='-' else '',round(1000000 * error)/1000, abs(100 * error / (60. / bpm))) + "%) at " + str(bpm) + " bpm")
sequencer_monitor = ServerThread(port=9900)
sequencer_monitor.add_method('/tic', None, print_diff)
sequencer_monitor.start()
seq.send(':/Sequencer/Sequence/Enable', 'metronom')
seq.play()
seq.start()
def __init__(self, port, qlcappport):
self.port = port
if self.port is not None:
self.server = ServerThread(self.port)
self.server.register_methods(self)
self.server.start()
class FFTServer():
"""Server to receive EEG data and stream classifier outputs.
Attributes:
See args.
Args:
incoming (str or dict): incoming data stream. If provided as a
string, look for an LSL stream with the corresponding type. If
provided as dict with fields `address` and `port`, open an OSC
port at that address and port.
outgoing (str or dict): outgoing data stream. If provided as a
string, stream to an LSL stream with the corresponding type. If
provided as dict with fields `address` and `port`, stream to an
OSC port at that address and port.
Keyword Args:
config (dict): dictionary containing the configuration and
preprocessing parameters, e.g. (these are the default values):
config = {'fs': 256.,
'n_channels': 4,
'raw_buffer_len': 3 * fs,
'filt_buffer_len': 3 * fs,
'window_len': fs,
'step': int(fs / 10),
'filter': ([1], [1]),
'psd_window_len': 256.,
'psd_buffer_len': 10}
device_source (str): Device from which the data is coming from.
'muse' or 'vive'
streaming_source (str): Software source of the data stream:
'muselsl'
'musedirect'
'musemonitor'
debug_outputs (bool): if True, send debug outputs (not used by VR
experience)
verbose (bool): if True, print status whenever new data is
received or sent.
"""
def __init__(self,
incoming,
outgoing,
sparseOutput=None,
config={},
device_source='Muse',
software_source='muselsl',
debug_outputs=True,
verbose=False):
self.incoming = incoming
self.outgoing = outgoing
self.sparseOutput = sparseOutput
self.device_source = device_source
self.software_source = software_source
self.debug_outputs = debug_outputs
self.verbose = verbose
self.eeg_chunk_length = 12
# 1. Initialize inlet
if isinstance(self.incoming, str): # LSL inlet
print('Looking for the {} stream...'.format(incoming))
self._stream = resolve_byprop('type', incoming, timeout=2)
if len(self._stream) == 0:
raise (RuntimeError('Can\'t find {} stream.'.format(incoming)))
print('Aquiring data from the \'{}\' stream...'.format(incoming))
self._inlet = StreamInlet(self._stream[0],
max_chunklen=self.eeg_chunk_length)
self._info_in = self._inlet.info()
else: # OSC port
if USE_LIBLO:
self._osc_server = ServerThread(incoming['port'])
print('OSC server initialized at port {}.'.format(
incoming['port']))
else:
self._dispatcher = dispatcher.Dispatcher()
print('python-osc dispatcher initialized.')
# 2. Initialize outlets
if not isinstance(self.outgoing, tuple):
self.outgoing = [self.outgoing]
self._output_threads = []
for out in self.outgoing:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
elif isinstance(out, dict): # OSC port
if USE_LIBLO:
self._output_threads.append(
Address(out['address'], out['port']))
else:
raise NotImplementedError
# self._client = udp_client.SimpleUDPClient(
# outgoing['address'], outgoing['port'])
print('OSC client initialized at {}:{}.'.format(
out['address'], out['port']))
if (self.sparseOutput != None):
if not isinstance(self.sparseOutput, tuple):
self.sparseOutput = [self.sparseOutput]
self._sparseOutput_threads = []
for out in self.sparseOutput:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
elif isinstance(out, dict): # OSC port
if USE_LIBLO:
self._sparseOutput_threads.append(
Address(out['address'], out['port']))
else:
raise NotImplementedError
print('OSC sparse output client initialized at {}:{}.'.
format(out['address'], out['port']))
# 3. Initialize internal buffers and variables
self._init_processing(config)
def _init_processing(self, config):
"""Initialize internal buffers and variables for EEG processing.
Args:
config (dict): dictionary containing various parameters. See
DEFAULT_CONFIG below for default values.
fs (float): sampling frequency
n_channels (int): number of channels
raw_buffer_len (int): raw data buffer length
filt_buffer_len (int): filtered data buffer length
window_len (int): processing window length
step (int): number of samples between two consecutive
windows to process
filter (tuple or dict): filtering parameters. If provided
as a tuple, the first and second elements should be
the `b` and `a` coefficients of a filter. If provided
as a dictionary, the fields `order`, `l_freq`, `h_freq`
and `method` are required; the function
pre.get_filter_coeff() will then be used to compute the
coefficients.
If None, don't use a filter (windows will be extracted
from the raw buffer).
psd_window_len (int): length of the window to use for PSD
psd_buffer_len (int): PSD buffer length
"""
DEFAULT_CONFIG = {
'fs': 256.,
'n_channels': 5,
'raw_buffer_len': 3 * 256,
'filt_buffer_len': 3 * 256,
'window_len': 256,
'step': int(256 / 10),
'filter': ([1], [1]),
'filter_bank': {},
'psd_window_len': 256.,
'psd_buffer_len': 10
}
config = {**DEFAULT_CONFIG, **config}
self.fs = config['fs']
self.n_channels = config['n_channels']
# Initialize EEG channel remapping parameters
self.eeg_ch_remap = None
if self.device_source.lower() == 'vive':
self.eeg_ch_remap = [3, 1, 2, 3, 4]
self.n_channels = 5
if self.software_source.lower() == 'musedirect':
self.eeg_ch_remap[-1] = 5
self.n_channels = 5
if self.device_source.lower() == 'leroy':
self.eeg_ch_remap = None
self.n_channels = 4
if self.device_source.lower() == 'muse':
self.eeg_ch_remap = None
self.n_channels = 4
if self.device_source.lower() == 'vivehr':
self.eeg_ch_remap = [3, 1, 2, 3, 0]
self.n_channels = 5
# Initialize the EEG buffers
raw_buffer_len = int(config['raw_buffer_len'])
filt_buffer_len = int(config['filt_buffer_len'])
self.eeg_buffer = ut.NanBuffer(raw_buffer_len, self.n_channels)
self.filt_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
self.hpfilt_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
self.smooth_eeg_buffer = ut.CircularBuffer(filt_buffer_len,
self.n_channels)
self.eyeH_buffer = ut.CircularBuffer(100, 1)
# Initialize the EEG filter
if config['filter']:
if isinstance(config['filter'], tuple):
b = config['filter'][0]
a = config['filter'][1]
elif isinstance(config['filter'], dict):
b, a = ut.get_filter_coeff(self.fs, **config['filter'])
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.bandpass_filt = {'b': b, 'a': a, 'zi': zi}
if config['hpfilter']:
b = config['hpfilter'][0]
a = config['hpfilter'][1]
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.hp_filt = {'b': b, 'a': a, 'zi': zi}
if config['lpfilter']:
b = config['lpfilter'][0]
a = config['lpfilter'][1]
zi = np.tile(signal.lfilter_zi(b, a), (self.n_channels, 1)).T
self.lp_filt = {'b': b, 'a': a, 'zi': zi}
# Initialize the filter bank
if config['filter_bank']:
self.filter_bank = {}
for name, coeff in config['filter_bank'].items():
zi = np.tile(signal.lfilter_zi(coeff[0], coeff[1]),
(self.n_channels, 1)).T
self.filter_bank[name] = {
'b': coeff[0],
'a': coeff[1],
'zi': zi
}
# Initialize processing parameters
self.window_len = int(config['window_len'])
self.step = int(config['step'])
# Initialize processing buffers
psd_buffer_len = int(config['psd_buffer_len'])
self.psd_buffer = ut.CircularBuffer(psd_buffer_len, 129,
self.n_channels)
# Initialize scoring histograms
decayRate = 0.997
self.hists = {
'delta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 50),
min_count=80,
decay=decayRate),
'theta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 30),
min_count=80,
decay=decayRate),
'alpha':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 20),
min_count=80,
decay=decayRate),
'beta':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 10),
min_count=80,
decay=decayRate),
'gamma':
ut.Histogram(1000,
self.n_channels,
bounds=(0, 10),
min_count=80,
decay=decayRate)
}
self.eyeH_hist = ut.Histogram(500,
1,
bounds=(0, 10000),
min_count=80,
decay=decayRate)
self.emg_hist = ut.Histogram(500,
1,
bounds=(0, 10),
min_count=80,
decay=decayRate)
self.blinkwait = 0
self.blink = 0
self.firstWindowProc = True
self.band_names = 0
self.band_powers = 0
self.ratio_powers = 0
self.ratio_names = 0
# Used for calm score
self.slow_calm_score = 0
self.slow_alpha_score = 0
self.eye_mov_percent_buffer = ut.CircularBuffer(256, 1)
self.slow_calm_score_buffer = ut.CircularBuffer(512, 1)
self.increments_buffer = ut.CircularBuffer(512, 1)
self.low_freq_chs_buffer = ut.CircularBuffer(150, 2)
self.low_freq_chs_std = 1
######################################################################
# BODY Motion Processing, Accelerometer, Gyro
raw_buffer_len = 150
filt_buffer_len = 150
self.acc_window_len = 50
self.acc_buffer = ut.NanBuffer(raw_buffer_len, 3)
self.filt0_buffer = ut.CircularBuffer(filt_buffer_len, 3)
self.heart_buffer = ut.CircularBuffer(150, 1)
self.breath_buffer = ut.CircularBuffer(500, 1)
# Initialize the Body Filters
if config['filter0']:
b = config['filter0'][0]
a = config['filter0'][1]
zi = np.tile(signal.lfilter_zi(b, a), (3, 1)).T
self.filter0 = {'b': b, 'a': a, 'zi': zi}
if config['filter1']:
b = config['filter1'][0]
a = config['filter1'][1]
zi = np.tile(signal.lfilter_zi(b, a), (3, 1)).T
self.filter1 = {'b': b, 'a': a, 'zi': zi}
if config['filter2']:
b = config['filter2'][0]
a = config['filter2'][1]
zi = signal.lfilter_zi(b, a)
self.filter2 = {'b': b, 'a': a, 'zi': zi}
if config['filter3']:
b = config['filter3'][0]
a = config['filter3'][1]
zi = np.tile(signal.lfilter_zi(b, a), (3, 1)).T
self.filter3 = {'b': b, 'a': a, 'zi': zi}
if config['filter4']:
b = config['filter4'][0]
a = config['filter4'][1]
zi = signal.lfilter_zi(b, a)
self.filter4 = {'b': b, 'a': a, 'zi': zi}
if config['filter5']:
b = config['filter5'][0]
a = config['filter5'][1]
zi = signal.lfilter_zi(b, a)
self.filter5 = {'b': b, 'a': a, 'zi': zi}
if config['filter6']:
b = config['filter6'][0]
a = config['filter6'][1]
zi = signal.lfilter_zi(b, a)
self.filter6 = {'b': b, 'a': a, 'zi': zi}
if config['filter7']:
b = config['filter7'][0]
a = config['filter7'][1]
zi = signal.lfilter_zi(b, a)
self.filter7 = {'b': b, 'a': a, 'zi': zi}
def _update_eeg_liblo_osc(self, path, args):
"""Collect new EEG data point(s) from pyliblo OSC and process.
Args:
path (str): OSC path listened to
args (list): received values
"""
if self.verbose:
print('Receiving OSC packet!')
sample = np.array(args).reshape(1, -1)
self._process_eeg(sample[:, :self.n_channels], 0)
def _update_eeg_python_osc(self, unused_addr, args, *chs):
"""Collect new EEG data point(s) from python-osc and process.
Args:
path (str): OSC path listened to
args (list): received values
"""
if self.verbose:
print('Receiving OSC packet!')
sample = np.array(chs).reshape(1, -1)
self._process_eeg(sample[:, :self.n_channels], 0)
def _update_acc_liblo_osc(self, path, args):
if self.verbose:
print('Receiving ACC packet!')
sample = np.array(args).reshape(1, -1)
self._process_acc(sample[:, :3], 0)
def _update_gyro_liblo_osc(self, path, args):
if self.verbose:
print('Receiving GYRO packet!')
sample = np.array(args).reshape(1, -1)
self._process_gyro(sample[:, :3], 0)
def _process_eeg(self, samples, timestamp):
"""Process EEG.
Process EEG. Includes buffering, filtering, windowing and pipeline.
Args:
samples (numpy.ndarray): new EEG samples to process
timestamp (float): timestamp
Returns:
output (scalar): output of the pipeline
"""
# Re-map
if self.eeg_ch_remap:
samples = samples[:, self.eeg_ch_remap]
self.eeg_buffer.update(samples)
self._send_outputs(samples, timestamp, 'raw_eeg')
# Apply filtes
filt_samples = samples
if config['filter']:
filt_samples, self.bandpass_filt['zi'] = signal.lfilter(
self.bandpass_filt['b'],
self.bandpass_filt['a'],
samples,
axis=0,
zi=self.bandpass_filt['zi'])
# self._send_filtered_eeg(filt_samples, timestamp)
self.filt_eeg_buffer.update(filt_samples)
if config['hpfilter']:
filt_samples, self.hp_filt['zi'] = signal.lfilter(
self.hp_filt['b'],
self.hp_filt['a'],
filt_samples,
axis=0,
zi=self.hp_filt['zi'])
self.hpfilt_eeg_buffer.update(filt_samples)
if config['lpfilter']:
smooth_eeg_samples, self.lp_filt['zi'] = signal.lfilter(
self.lp_filt['b'],
self.lp_filt['a'],
filt_samples,
axis=0,
zi=self.lp_filt['zi'])
if self.debug_outputs:
self._send_output_vec(smooth_eeg_samples, timestamp,
'smooth_eeg')
else:
smooth_eeg_samples = filt_samples
self.smooth_eeg_buffer.update(smooth_eeg_samples)
if config['filter_bank']:
filter_bank_samples = {}
for name, filt_dict in self.filter_bank.items():
filter_bank_samples[name], self.filter_bank[name]['zi'] = \
signal.lfilter(filt_dict['b'], filt_dict['a'],
filt_samples, axis=0,
zi=self.filter_bank[name]['zi'])
low_freq_chs = filter_bank_samples['delta'][0, [
0, 2
]] #+ filter_bank_samples['theta'][0, [0, 1]]
window = self.smooth_eeg_buffer.extract(self.window_len)
eegEarWindow = window[:, 3] #data from right ear Channel
#eye movement computed from the difference between two frontal channels
eyewindow = self.smooth_eeg_buffer.extract(200)
eegFLWindow = eyewindow[:, 1]
eegFRWindow = eyewindow[:, 2]
# norm_diff_eyes = eegFLWindow[-1] - eegFRWindow[-1]*np.nanstd(eegFLWindow, axis=0)/np.nanstd(eegFRWindow, axis=0)
# eyeH = np.reshape([np.square(norm_diff_eyes)], (1, 1))
#find blinks in the left eegEarWindow
blinkVal = ut.blink_template_match(eegEarWindow)
if (blinkVal > 100000 and self.blink == 0):
self.blink = 50
self.blinkwait = 350
else:
if (self.blinkwait > 0):
self.blinkwait -= 1
if (self.blink > 0):
self.blink -= 1
# LONGER-TERM CALM SCORE based on Saccadic Eye Movement
eye_mov_percent = np.reshape(
np.percentile(eegFLWindow - eegFRWindow, 90), (1, 1))
self.eye_mov_percent_buffer.update(eye_mov_percent)
remap_eye_mov_percent = ut.sigmoid(
self.eye_mov_percent_buffer.extract().mean(), 0.5, -10, 0)
max_value = 1
incr_decr = remap_eye_mov_percent < 0.2
inc = self.increments_buffer.extract().mean()
dpoints_per_second = 0.0005
if incr_decr:
self.slow_calm_score += dpoints_per_second * inc # 1/max([max_value - self.slow_calm_score, 1])
else:
self.slow_calm_score -= dpoints_per_second * inc * 4 #0.7 # (self.slow_calm_score)/1280
self.increments_buffer.update(np.reshape(incr_decr, (1, 1)))
if self.slow_calm_score > max_value:
self.slow_calm_score = max_value
elif self.slow_calm_score < 0:
self.slow_calm_score = 0
self.slow_calm_score_buffer.update(
np.reshape(self.slow_calm_score, (1, 1)))
# Send outputs at a reduced sampling rate
if self.smooth_eeg_buffer.pts % 3 == 0:
self._send_output_vec(smooth_eeg_samples, timestamp, 'muse/eeg')
if (self.blink > 0):
self._send_output(np.array([[1]]), timestamp, 'blink')
else:
self._send_output(np.array([[0]]), timestamp, 'blink')
self._send_output(blinkVal / 300000, timestamp, 'blinkVal')
self._send_output(remap_eye_mov_percent, timestamp, 'saccad')
self._send_output(
np.reshape(self.slow_calm_score_buffer.extract().mean(),
(1, 1)), timestamp, 'calm') # slow_calm_score
self._send_output(low_freq_chs / self.low_freq_chs_std + 0.5,
timestamp, 'low_freq_chs')
# process and send output at every step. usually about every 1/10s
if self.eeg_buffer.pts > self.step:
self.eeg_buffer.pts = 0
# Get filtered EEG window
if config['lpfilter']:
window = self.smooth_eeg_buffer.extract(self.window_len)
else:
window = self.eeg_buffer.extract(self.window_len)
psd_raw_buffer = self.eeg_buffer.extract(self.window_len)
# Get average PSD
psd, f = ut.fft_continuous(psd_raw_buffer,
n=int(self.fs),
psd=True,
log='psd',
fs=self.fs,
window='hamming')
self.psd_buffer.update(np.expand_dims(psd, axis=0))
mean_psd = np.nanmean(self.psd_buffer.extract(), axis=0)
# find variance of eegWindow for Bad Signal detact
eegVar = np.nanvar(window, axis=0)
self._send_output_vec(eegVar.reshape(1, self.n_channels),
timestamp, 'hsi')
if (self.sparseOutput != None):
#send channel varience for signal quality indication at source Raspberry Pi
#send(Address('10.0.0.14','1234'), "/hsi", eegVar[0],eegVar[1],eegVar[2],eegVar[3])
self._send_sparseOutput_vec(eegVar.reshape(1, self.n_channels),
timestamp, 'hsi')
# Get band powers and ratios
bandPowers, bandNames = ut.compute_band_powers(mean_psd,
f,
relative=False)
ratioPowers, ratioNames = ut.compute_band_ratios(bandPowers)
if (self.firstWindowProc):
self.band_powers = bandPowers
self.band_names = bandNames
self.ratio_powers = ratioPowers
self.ratio_names = ratioNames
self.scores = np.zeros((len(self.band_names), self.n_channels))
self.firstWindowProc = False
if (eegVar.mean() < 300
and self.blinkwait == 0): #threshold for good data
for i, (name, hist) in enumerate(self.hists.items()):
self.band_powers = bandPowers
self.ratio_powers = ratioPowers
#send good data indicator based on mean eegWindow variance and blinkwait
self._send_output(np.array([[1]]), timestamp,
'goodData') #good data
else:
self._send_output(np.array([[0]]), timestamp,
'goodData') #good data
self._send_outputs(self.band_powers, timestamp, 'bands')
self._send_outputs(self.ratio_powers, timestamp, 'ratios')
mask = ((f >= 30) & (f < 50))
self.low_freq_chs_buffer.update(np.reshape(low_freq_chs, (1, -1)))
self.low_freq_chs_std = self.low_freq_chs_buffer.extract().std(
axis=0)
emg_power = np.mean(mean_psd[mask, 0],
axis=0) #HF power of right ear
self._send_output(np.array([np.sqrt(emg_power) / 2]), timestamp,
'emg')
def _process_acc(self, samples, timestamp):
self._send_output_vec(samples, 0, 'muse/acc')
self.acc_buffer.update(samples)
window = self.acc_buffer.extract(self.acc_window_len)
timestamps = np.linspace(0, 1 / 50 * self.acc_window_len,
self.acc_window_len)
new_fs = 250
timestamps_upsampled = np.arange(timestamps[0], timestamps[-1],
1 / new_fs)
f = interpolate.interp1d(timestamps,
window,
kind='cubic',
axis=0,
fill_value=np.nan,
assume_sorted=True)
window_upsampled = f(timestamps_upsampled)
for t in range(timestamps_upsampled.size - 5,
timestamps_upsampled.size):
if self.debug_outputs:
self._send_output(window_upsampled[t], 0, 'upsamp')
upsample = np.array(window_upsampled[t]).reshape(1, 3)
filt_samples, self.filter0['zi'] = signal.lfilter(
self.filter0['b'],
self.filter0['a'],
upsample,
axis=0,
zi=self.filter0['zi'])
self.filt0_buffer.update(filt_samples)
if self.debug_outputs:
self._send_outputs(filt_samples, 0, 'filter0')
filt_samples, self.filter1['zi'] = signal.lfilter(
self.filter1['b'],
self.filter1['a'],
filt_samples,
axis=0,
zi=self.filter1['zi'])
if self.debug_outputs:
self._send_outputs(filt_samples, 0, 'filter1')
filt_samples = np.sqrt(np.sum(filt_samples**2, axis=1))
if self.debug_outputs:
self._send_output(filt_samples, 0, 'filter1L2')
heart_samples, self.filter2['zi'] = signal.lfilter(
self.filter2['b'],
self.filter2['a'],
filt_samples,
axis=0,
zi=self.filter2['zi'])
if self.debug_outputs:
self._send_output(heart_samples, 0, 'filter2')
breathfilt_samples, self.filter3['zi'] = signal.lfilter(
self.filter3['b'],
self.filter3['a'],
upsample,
axis=0,
zi=self.filter3['zi'])
if self.debug_outputs:
self._send_outputs(breathfilt_samples, 0, 'filter3')
self.heart_buffer.update(heart_samples.reshape(1, 1))
heartbuf = self.heart_buffer.extract(150)
heartbufMin = heartbuf.min()
heartbufMax = heartbuf.max()
heart = np.reshape(
(heartbuf[-1] - heartbufMin) / (heartbufMax - heartbufMin), (1, 1))
self._send_output(heart, 0, 'heart')
breathSmooth = breathfilt_samples[0, 2].reshape(1, )
if self.debug_outputs:
self._send_output(breathSmooth, 0, 'breathRaw')
breathSmooth, self.filter4['zi'] = signal.lfilter(
self.filter4['b'],
self.filter4['a'],
breathSmooth,
axis=0,
zi=self.filter4['zi'])
if self.debug_outputs:
self._send_output(breathSmooth, 0, 'breathSmooth')
breathNorm, self.filter5['zi'] = signal.lfilter(self.filter5['b'],
self.filter5['a'],
breathSmooth,
axis=0,
zi=self.filter5['zi'])
if self.debug_outputs:
self._send_output(breathNorm, 0, 'breathNorm')
breathFast, self.filter6['zi'] = signal.lfilter(self.filter6['b'],
self.filter6['a'],
breathSmooth,
axis=0,
zi=self.filter6['zi'])
if self.debug_outputs:
self._send_output(breathFast, 0, 'breathFast')
breathLow, self.filter7['zi'] = signal.lfilter(self.filter7['b'],
self.filter7['a'],
breathSmooth,
axis=0,
zi=self.filter7['zi'])
if self.debug_outputs:
self._send_output(breathLow, 0, 'breathLow')
self.breath_buffer.update(breathLow.reshape(1, 1))
breathbuf = self.breath_buffer.extract(1000)
breathbufMin = breathbuf.min()
breathbufMax = breathbuf.max()
breath = np.reshape(
(breathbuf[-1] - breathbufMin) / (breathbufMax - breathbufMin),
(1, 1))
self._send_output(breath, 0, 'breath')
def _process_gyro(self, samples, timestamp):
self._send_output_vec(samples, 0, 'muse/gyro')
def _send_outputs(self, output, timestamp, name):
"""Send pipeline outputs through the LSL or OSC stream.
Args:
output (scalar): output of the pipeline
timestamp (float): timestamp
"""
for out in self._output_threads:
if isinstance(out, str): # LSL outlet
self._outlet.push_sample([output], timestamp=timestamp)
else: # OSC output stream
if USE_LIBLO:
for c in range(self.n_channels):
new_output = [('f', x) for x in output[:, c]]
message = Message('/{}{}'.format(name, c), *new_output)
#send(out, Bundle(timestamp, message))
send(out, message)
else:
for c in range(self.n_channels):
self._client.send_message('/{}{}'.format(name, c),
output[:, c])
if self.verbose:
print('Output: {}'.format(output))
def _send_output_vec(self, output, timestamp, name):
"""Send pipeline outputs through the LSL or OSC stream.
Args:
output (scalar): output of the pipeline
timestamp (float): timestamp
"""
for out in self._output_threads:
if isinstance(out, str): # LSL outlet
self._outlet.push_sample([output], timestamp=timestamp)
else: # OSC output stream
if USE_LIBLO:
new_output = [('f', x) for x in output[0, :]]
message = Message('/{}'.format(name), *new_output)
# send(out, Bundle(timestamp, message))
send(out, message)
if self.verbose:
print('Output: {}'.format(output))
def _send_sparseOutput_vec(self, output, timestamp, name):
"""Send pipeline outputs through the LSL or OSC stream.
Args:
output (scalar): output of the pipeline
timestamp (float): timestamp
"""
for out in self._sparseOutput_threads:
if isinstance(out, str): # LSL outlet
self._outlet.push_sample([output], timestamp=timestamp)
else: # OSC output stream
if USE_LIBLO:
new_output = [('f', x) for x in output[0, :]]
message = Message('/{}'.format(name), *new_output)
#send(out, Bundle(timestamp, message))
send(out, message)
if self.verbose:
print('sparseOutput: {}'.format(output))
def _send_output(self, output, timestamp, name):
"""Send pipeline outputs through the LSL or OSC stream.
NOT PER CHANNEL
Args:
output (scalar): output of the pipeline
timestamp (float): timestamp
"""
for out in self._output_threads:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
# self._outlet.push_sample([output], timestamp=timestamp)
else: # OSC output stream
if USE_LIBLO:
if (np.array(output).size == 1):
new_output = [('f', np.asscalar(output))]
message = Message('/{}'.format(name), *new_output)
else:
new_output = [('f', x) for x in output[:]]
message = Message('/{}'.format(name), *new_output)
# send(out, Bundle(timestamp, message))
send(out, message)
else:
raise NotImplementedError
# self._client.send_message(}{}'.format(name),output[:])
if self.verbose:
print('Output: {}'.format(output))
def _send_sparseOutput(self, output, timestamp, name):
for out in self._sparseOutput_threads:
if isinstance(out, str): # LSL outlet
raise NotImplementedError
else: # OSC output stream
if USE_LIBLO:
if (np.array(output).size == 1):
new_output = [('f', np.asscalar(output))]
message = Message('/{}'.format(name), *new_output)
else:
new_output = [('f', x) for x in output[:]]
message = Message('/{}'.format(name), *new_output)
#send(out, Bundle(timestamp, message))
send(out, message)
else:
raise NotImplementedError
if self.verbose:
print('spareOutput: {}'.format(output))
def start(self):
"""Start receiving and processing EEG data.
"""
self.started = True
if isinstance(self.incoming, str): # LSL inlet
self.eeg_thread = Thread(target=self._update_eeg_lsl)
self.eeg_thread.daemon = True
self.eeg_thread.start()
else: # OSC input stream
if USE_LIBLO:
self._osc_server.add_method('/muse/eeg', None,
self._update_eeg_liblo_osc)
self._osc_server.add_method('/muse/acc', None,
self._update_acc_liblo_osc)
self._osc_server.add_method('/muse/gyro', None,
self._update_gyro_liblo_osc)
self._osc_server.start()
else:
self._dispatcher.map('Person2/eeg',
self._update_eeg_python_osc, 'EEG')
self._osc_server = osc_server.ThreadingOSCUDPServer(
('127.0.0.1', self.incoming['port']), self._dispatcher)
print('OSC server initialized at port {}.'.format(
self.incoming['port']))
self._server_thread = Thread(
target=self._osc_server.serve_forever)
self._server_thread.start()
def stop(self):
"""
"""
self.started = False
if isinstance(self.incoming, dict):
if not USE_LIBLO:
self._server_thread.shutdown()
def start(self):
ServerThread.start(self)
midiServer.run(midiServer.Call(self.processMIDI))
def __init__(self, parent, mode):
ServerThread.__init__(self, 8087, mode)
self.fParent = parent
def __init__( self, callback ): self.callback = callback ServerThread.__init__(self, 5001)
def __init__(self, host, mode):
ServerThread.__init__(self, 8998 + int(random()*9000), mode)
self.host = host
def __init__(self, muse_port, client_ip, client_port):
ServerThread.__init__(self, muse_port)
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.client_ip = client_ip
self.client_port = client_port
def __init__(self, parent, mode):
ServerThread.__init__(self, 8087, mode)
self.fParent = parent
def __init__(self, muse_port, muse_id, server):
self.muse_port = muse_port
self.muse_id = muse_id
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
logger.info('Muse %s connected to museIO on port %s' %
(muse_id, muse_port))
# configure the Spacebrew client
self.brew = SpacebrewApp(muse_id, server=server)
self.osc_paths = [
'/muse/eeg',
'/muse/eeg/quantization',
# '/muse/eeg/dropped_samples',
'/muse/acc',
# '/muse/acc/dropped_samples',
'/muse/batt',
# '/muse/drlref',
#'/muse/elements/raw_fft0',
#'/muse/elements/raw_fft1',
#'/muse/elements/raw_fft2',
#'/muse/elements/raw_fft3',
'/muse/elements/low_freqs_absolute',
'/muse/elements/delta_absolute',
'/muse/elements/theta_absolute',
'/muse/elements/alpha_absolute',
'/muse/elements/beta_absolute',
'/muse/elements/gamma_absolute',
#'/muse/elements/delta_relative',
#'/muse/elements/theta_relative',
#'/muse/elements/alpha_relative',
#'/muse/elements/beta_relative',
#'/muse/elements/gamma_relative',
#'/muse/elements/delta_session_score',
#'/muse/elements/theta_session_score',
#'/muse/elements/alpha_session_score',
#'/muse/elements/beta_session_score',
#'/muse/elements/gamma_session_score',
'/muse/elements/touching_forehead',
'/muse/elements/horseshoe',
'/muse/elements/is_good',
'/muse/elements/blink',
'/muse/elements/jaw_clench',
'/muse/elements/experimental/concentration',
'/muse/elements/experimental/mellow'
]
for osc_path in self.osc_paths:
spacebrew_name = self.calculate_spacebrew_name(osc_path)
self.brew.add_publisher(spacebrew_name, 'string')
logger.debug('Spacebrew publisher %s added for muse with ID %s' %
(spacebrew_name, self.muse_id))
# Connect to spacebrew
self.brew.start()
logger.debug('Initialization completed for muse with ID %s' %
self.muse_id)
def __init__(self, muse_port, began_at):
# Configuring the Muse OSC client
ServerThread.__init__(self, muse_port)
self.began_at = began_at
self.osc_paths = [{
'address': "/muse/eeg",
'arguments': 4
}, {
'address': "/muse/eeg/quantization",
'arguments': 4
}, {
'address': "/muse/eeg/dropped_samples",
'arguments': 1
}, {
'address': "/muse/acc",
'arguments': 3
}, {
'address': "/muse/acc/dropped_samples",
'arguments': 1
}, {
'address': "/muse/batt",
'arguments': 4
}, {
'address': "/muse/drlref",
'arguments': 2
}, {
'address': "/muse/elements/low_freqs_absolute",
'arguments': 4
}, {
'address': "/muse/elements/delta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/theta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/alpha_absolute",
'arguments': 4
}, {
'address': "/muse/elements/beta_absolute",
'arguments': 4
}, {
'address': "/muse/elements/gamma_absolute",
'arguments': 4
}, {
'address': "/muse/elements/delta_relative",
'arguments': 4
}, {
'address': "/muse/elements/theta_relative",
'arguments': 4
}, {
'address': "/muse/elements/alpha_relative",
'arguments': 4
}, {
'address': "/muse/elements/beta_relative",
'arguments': 4
}, {
'address': "/muse/elements/gamma_relative",
'arguments': 4
}, {
'address': "/muse/elements/delta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/theta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/alpha_session_score",
'arguments': 4
}, {
'address': "/muse/elements/beta_session_score",
'arguments': 4
}, {
'address': "/muse/elements/gamma_session_score",
'arguments': 4
}, {
'address': "/muse/elements/touching_forehead",
'arguments': 1
}, {
'address': "/muse/elements/horseshoe",
'arguments': 4
}, {
'address': "/muse/elements/is_good",
'arguments': 4
}, {
'address': "/muse/elements/blink",
'arguments': 1
}, {
'address': "/muse/elements/jaw_clench",
'arguments': 1
}, {
'address': "/muse/elements/experimental/concentration",
'arguments': 1
}, {
'address': "/muse/elements/experimental/mellow",
'arguments': 1
}]
self.paths = [path['address'] for path in self.osc_paths]
