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alexandrebarachant committed Jan 27, 2017
1 parent b8b1922 commit 19d47fc
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2 changes: 2 additions & 0 deletions README.md
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# Muse LSL

This is a collection of script to use the muse 2016 BLE headset with LSL.
3 changes: 1 addition & 2 deletions lsl-record.py
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"""Test."""
#!/usr/bin/env python
import numpy as np
import pandas as pd
from time import time, strftime, gmtime
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res = np.concatenate(res, axis=0)
timestamps = np.array(timestamps)
res = np.c_[timestamps, res]
print res.shape
data = pd.DataFrame(data=res, columns=['timestamps'] + ch_names)

data['Marker'] = 0
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7 changes: 3 additions & 4 deletions lsl-viewer.py
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"""Test."""
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, filtfilt
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(options, args) = parser.parse_args()

figsize = np.int16(options.figure.split('x'))
print figsize

print("looking for an EEG stream...")
streams = resolve_byprop('type', 'EEG', timeout=2)
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k += 1
dur = time() - t_init
data = np.concatenate(res, axis=0)
print data.shape

if options.avgref:
data -= np.atleast_2d(data.mean(1)).T
ffts = np.abs(np.fft.fft(data[:, 0:], n=128, axis=0))
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lines = []
impedances = np.log(ffts[ix_noise].mean(0)) / np.log(ffts[ix_signal].mean(0))
print impedances

for i, ix in enumerate(picks):
line, = axes.plot(time[::subsample],
data[::subsample, ix] - (i * options.scale * 2),
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