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lsl-viewer.py
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lsl-viewer.py
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#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter, lfilter_zi, firwin
from time import sleep
from pylsl import StreamInlet, resolve_byprop
from optparse import OptionParser
import seaborn as sns
from threading import Thread
sns.set(style="whitegrid")
parser = OptionParser()
parser.add_option("-w", "--window",
dest="window", type='float', default=5.,
help="window lenght to display in seconds.")
parser.add_option("-s", "--scale",
dest="scale", type='float', default=100,
help="scale in uV")
parser.add_option("-r", "--refresh",
dest="refresh", type='float', default=0.2,
help="refresh rate in seconds.")
parser.add_option("-f", "--figure",
dest="figure", type='string', default="15x6",
help="window size.")
filt = True
subsample = 2
buf = 12
(options, args) = parser.parse_args()
window = options.window
scale = options.scale
figsize = np.int16(options.figure.split('x'))
print("looking for an EEG stream...")
streams = resolve_byprop('type', 'EEG', timeout=2)
if len(streams) == 0:
raise(RuntimeError("Cant find EEG stream"))
print("Start aquiring data")
class LSLViewer():
def __init__(self, stream, fig, axes, window, scale, dejitter=True):
"""Init"""
self.stream = stream
self.window = window
self.scale = scale
self.dejitter = dejitter
self.inlet = StreamInlet(stream, max_chunklen=buf)
self.filt = True
info = self.inlet.info()
description = info.desc()
self.sfreq = info.nominal_srate()
self.n_samples = int(self.sfreq * self.window)
self.n_chan = info.channel_count()
ch = description.child('channels').first_child()
ch_names = [ch.child_value('label')]
for i in range(self.n_chan):
ch = ch.next_sibling()
ch_names.append(ch.child_value('label'))
self.ch_names = ch_names
fig.canvas.mpl_connect('key_press_event', self.OnKeypress)
fig.canvas.mpl_connect('button_press_event', self.onclick)
self.fig = fig
self.axes = axes
sns.despine(left=True)
self.data = np.zeros((self.n_samples, self.n_chan))
self.times = np.arange(-self.window, 0, 1./self.sfreq)
impedances = np.std(self.data, axis=0)
lines = []
for ii in range(self.n_chan):
line, = axes.plot(self.times[::subsample],
self.data[::subsample, ii] - ii, lw=1)
lines.append(line)
self.lines = lines
axes.set_ylim(-self.n_chan + 0.5, 0.5)
ticks = np.arange(0, -self.n_chan, -1)
axes.set_xlabel('Time (s)')
axes.xaxis.grid(False)
axes.set_yticks(ticks)
ticks_labels = ['%s - %.1f' % (ch_names[ii], impedances[ii])
for ii in range(self.n_chan)]
axes.set_yticklabels(ticks_labels)
self.display_every = int(0.2 / (12/self.sfreq))
# self.bf, self.af = butter(4, np.array([1, 40])/(self.sfreq/2.),
# 'bandpass')
self.bf = firwin(32, np.array([1, 40])/(self.sfreq/2.), width=0.05,
pass_zero=False)
self.af = [1.0]
zi = lfilter_zi(self.bf, self.af)
self.filt_state = np.tile(zi, (self.n_chan, 1)).transpose()
self.data_f = np.zeros((self.n_samples, self.n_chan))
def update_plot(self):
k = 0
while self.started:
samples, timestamps = self.inlet.pull_chunk(timeout=1.0,
max_samples=12)
if timestamps:
if self.dejitter:
timestamps = np.float64(np.arange(len(timestamps)))
timestamps /= self.sfreq
timestamps += self.times[-1] + 1./self.sfreq
self.times = np.concatenate([self.times, timestamps])
self.n_samples = int(self.sfreq * self.window)
self.times = self.times[-self.n_samples:]
self.data = np.vstack([self.data, samples])
self.data = self.data[-self.n_samples:]
filt_samples, self.filt_state = lfilter(
self.bf, self.af,
samples,
axis=0, zi=self.filt_state)
self.data_f = np.vstack([self.data_f, filt_samples])
self.data_f = self.data_f[-self.n_samples:]
k += 1
if k == self.display_every:
if self.filt:
plot_data = self.data_f
elif not self.filt:
plot_data = self.data - self.data.mean(axis=0)
for ii in range(self.n_chan):
self.lines[ii].set_xdata(self.times[::subsample] -
self.times[-1])
self.lines[ii].set_ydata(plot_data[::subsample, ii] /
self.scale - ii)
impedances = np.std(plot_data, axis=0)
ticks_labels = ['%s - %.2f' % (self.ch_names[ii],
impedances[ii])
for ii in range(self.n_chan)]
self.axes.set_yticklabels(ticks_labels)
self.axes.set_xlim(-self.window, 0)
self.fig.canvas.draw()
k = 0
else:
sleep(0.2)
def onclick(self, event):
print((event.button, event.x, event.y, event.xdata, event.ydata))
def OnKeypress(self, event):
if event.key == '/':
self.scale *= 1.2
elif event.key == '*':
self.scale /= 1.2
elif event.key == '+':
self.window += 1
elif event.key == '-':
if self.window > 1:
self.window -= 1
elif event.key == 'd':
self.filt = not(self.filt)
def start(self):
self.started = True
self.thread = Thread(target=self.update_plot)
self.thread.daemon = True
self.thread.start()
def stop(self):
self.started = False
fig, axes = plt.subplots(1, 1, figsize=figsize, sharex=True)
lslv = LSLViewer(streams[0], fig, axes, window, scale)
help_str = """
toggle filter : d
toogle full screen : f
zoom out : /
zoom in : *
increase time scale : -
decrease time scale : +
"""
print(help_str)
lslv.start()
plt.show()
lslv.stop()