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heart_rate.py
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heart_rate.py
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#!/usr/bin/env python
## code by Alexandre Barachant
## modified by Pierre Karashchuk
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, filtfilt
from time import time, sleep
from pylsl import StreamInlet, resolve_byprop
import seaborn as sns
from threading import Thread
from scipy import signal
sns.set(style="whitegrid")
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-w", "--window",
dest="window", type='float', default=6,
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'))
refresh = options.refresh
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 = []
self.rects = self.axes[1].bar(0, 1)
lines = []
for ii in range(self.n_chan):
line, = self.axes[0].plot(self.times[::subsample],
self.data[::subsample, ii] - ii, lw=1)
lines.append(line)
self.lines = lines
# self.text = axes.
self.axes[1].xaxis.grid(False)
self.axes[1].set_xticks([])
self.axes[1].set_ylim([0,120])
self.value = None
self.display_every = int(refresh / (12/self.sfreq))
self.bf, self.af = butter(4, np.array([0.5,20])/(self.sfreq/2.),
'bandpass')
self.low = 10000
self.high = 0
def compute_value(self):
data_f1 = filtfilt(self.bf, self.af, self.data[:, 0])
data_f1 -= np.mean(data_f1)
data_f1 /= np.std(data_f1)
rises = np.where(np.diff(1.0*(np.abs(data_f1) > 2)) == 1)[0]
rr = np.diff(rises)/self.sfreq
print(1/np.mean(rr), rr)
return 60.0/np.mean(rr)
def update_plot(self):
value = self.compute_value()
if np.isnan(value):
return
if self.value is None:
self.value = value
self.value = 0.8 * self.value + 0.2 * value
self.low = min(self.low, self.value)
self.high = max(self.high, self.value)
rect = self.rects.get_children()[0]
rect.set_height(self.value)
self.axes[1].set_ylim([0, 240])
# self.fig.canvas.draw()
# plt.pause(0.01)
def update_lines(self):
if self.filt:
data_f = filtfilt(self.bf, self.af, self.data, axis=0)
else:
data_f = self.data
data_f -= data_f.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(data_f[::subsample, ii] /
self.scale - ii)
impedances = np.std(data_f, axis=0)
self.scale = impedances[0]
ticks_labels = ['%s - %.2f' %
(self.ch_names[ii], impedances[ii])
for ii in range(self.n_chan)]
self.axes[0].set_yticklabels(ticks_labels)
self.axes[0].set_xlim(-self.window, 0)
def update_data_and_plot(self):
k = 0
while self.started:
samples, timestamps = self.inlet.pull_chunk(timeout=1.0,
max_samples=buf)
if timestamps:
self.data = np.vstack([self.data, samples])
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.data = self.data[-self.n_samples:]
self.times = self.times[-self.n_samples:]
k += 1
if k >= self.display_every:
self.update_lines()
self.update_plot()
self.fig.canvas.draw()
plt.pause(0.01)
k = 0
else:
sleep(0.1)
def onclick(self, event):
print((event.button, event.x, event.y, event.xdata, event.ydata))
def OnKeypress(self, event):
if event.key == 'r':
self.low = 10000
self.high = 0
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_data_and_plot)
self.thread.daemon = True
self.thread.start()
def stop(self):
self.started = False
fig, axes = plt.subplots(1, 2, figsize=figsize, sharex=True)
lslv = LSLViewer(streams[0], fig, axes, window, scale)
help_str = """
reset scale: r
increase time scale : -
decrease time scale : +
"""
print(help_str)
lslv.start()
plt.show()
lslv.stop()