def get_some_data(real=False):
if not real:
channels = [
'Fp1', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'Ft9', 'Fc5',
'Fc1', 'Fc2', 'Fc6', 'Ft10', 'T7', 'C3', 'Cz', 'C4', 'T8',
'Tp9', 'Cp5', 'Cp1', 'Cp2', 'Cp6', 'Tp10', 'P7', 'P3', 'Pz',
'P4', 'P8', 'O1', 'Oz', 'O2'
]
data = np.random.normal(loc=0,
scale=0.00001,
size=(5000, len(channels))).T
fs = 500
else:
import h5py
from vendor.nfb.pynfb.postprocessing.utils import get_info
with h5py.File(
r'D:\mu_ica\mu_ica\mu_ica_S1_D3_04-21_18-16-03\experiment_data.h5'
) as f:
fs, channels, p_names = get_info(f, [])
data = f['protocol{}/raw_data'.format(
p_names.index('Baseline') + 1)][:].T
from PyQt5.QtWidgets import QApplication
a = QApplication([])
rej, spatial, top = ICADialog.get_rejection(data.T,
channels,
fs,
mode='ica',
states=None)[:3]
data = rej.apply(data.T).T
return data, fs, channels
#data = data.iloc[~get_outliers_mask(data[channels], std=3, iter_numb=2)]
#plt.plot(data[channels] + 1000*np.arange(len(channels)))
#plt.show()
print('ww', sum(get_outliers_mask(data[channels][data['block_number'] < 3])))
# spatial filter (SMR detection)
try:
filt = np.load('ica_{}.npy'.format(experiment))
#filt = np.zeros(len(channels))
#filt[channels.index('C3')] = 1
except FileNotFoundError:
a = QApplication([])
(rej, filt, topo, _unmix, _bandpass, _) = ICADialog.get_rejection(
data[channels][data['block_number'].isin(
[1, 2]
)] #.iloc[~get_outliers_mask(data[channels][data['block_number']<12], std=2)]
,
channels,
fs,
mode='csp')
#(_rej, filt, topo, _unmix, _bandpass, _) = ICADialog.get_rejection(np.concatenate(list(x[y=='Left']) + l1ist(x[y=='Legs'])), channels, fs, mode='csp')
# filt, topography, bandpass, rejections = SelectSSDFilterWidget.select_filter_and_bandpass(np.concatenate(x), ch_names_to_2d_pos(channels), channels, sampling_freq=fs)
np.save('ica_{}.npy'.format(experiment), filt)
data['SMR'] = np.dot(data[channels], filt)
#data = data.iloc[~get_outliers_mask(data[['C3', 'SMR']], std=3, iter_numb=10)]
# temporal filter
data['SMR_band_filt'] = fft_filter(data['SMR'], fs, (11, 13))
data['SMR_env'] = np.abs(signal.hilbert(data['SMR_band_filt']))
data.to_pickle('data-{}.pkl'.format(experiment))
del raw[list(raw.keys())[-1]]
# make csp:
if run_ica:
from PyQt5.QtWidgets import QApplication
ap = QApplication([])
all_keys = [key for key in raw.keys() if 'Left' in key or 'Right' in key or 'Close' in key or 'Open' in key]
first = all_keys[:len(all_keys)//2]
last = all_keys[len(all_keys)//2:]
tops = []
spats = []
fig1, axes = plt.subplots(nrows=2, ncols=2, sharex=True, sharey=False)
for j, data in enumerate([first, last]):
raw_data = np.concatenate([raw[key] for key in data])
rej, spatial, top = ICADialog.get_rejection(raw_data, channels, fs, mode='ica', states=None)[:3]
tops.append(top)
spats.append(spatial)
plot_topomap(top, ch_names_to_2d_pos(channels), axes=axes[j, 0], show=False)
plot_topomap(spatial, ch_names_to_2d_pos(channels), axes=axes[j, 1], show=False)
axes[j, 0].set_xlabel('Topography ({})'.format('before' if j == 0 else 'after'))
axes[j, 1].set_xlabel('Spatial filter ({})'.format('before' if j == 0 else 'after'))
#plt.show()
# plot raw data
ch_plot = ['C3', 'P3', 'ICA']#, 'Pz', 'Fp1']
fig1, axes = plt.subplots(len(ch_plot), ncols=1, sharex=True, sharey=False)
print(axes)
import pylab as plt
from scipy.io import loadmat
from vendor.nfb.pynfb.widgets.helpers import ch_names_to_2d_pos
from vendor.nfb.pynfb.protocols.ssd.topomap_selector_ica import ICADialog
from PyQt5.QtWidgets import QApplication
fs = 258
pre = loadmat(
"C:\\Users\\nsmetanin\\Downloads\\nfb_bci\\wetransfer-07cfaf\\Subj01_POSTdata.mat"
)
channels = [a[0] for a in pre["EEGchanslabels"][0]]
pre = pre["EEGPOSTdata"]
post = loadmat(
"C:\\Users\\nsmetanin\\Downloads\\nfb_bci\\wetransfer-07cfaf\\Subj01_PREdata.mat"
)["EEGPREdata"]
print(pre.shape, post.shape, channels)
# print(ch_names_to_2d_pos(channels))
a = QApplication([])
n_samples = 50
print(pre[:, -n_samples:, 0].shape)
x = np.concatenate([
np.concatenate([pre[:, -n_samples:, k].T for k in range(pre.shape[2])]),
np.concatenate([post[:, :n_samples, k].T for k in range(post.shape[2])]),
])
print(x.shape)
ICADialog.get_rejection(x, channels, fs, mode="csp")
elif j > len(p_names) - 3:
x = preproc(f['protocol{}/raw_data'.format(j + 1)][:], fs,
rejection if reject else None)
print(x.shape)
raw_after = add_data_simple(raw_after, name, x)
xx = np.concatenate([
raw_before['Opened'],
raw_before['Baseline'],
raw_after['Baseline'],
raw_before['Left'],
raw_before['Right'],
raw_after['Left'],
raw_after['Right'],
])
#xx[:, channels.index('C3')] = xx[:, channels.index('C3')]
rejection, spatial, topography, unmixing_matrix, bandpass, _ = ICADialog.get_rejection(
xx, channels, fs, mode='csp', states=None)
from mne.viz import plot_topomap
print(spatial)
fig, axes = plt.subplots(ncols=rejection.topographies.shape[1])
if not isinstance(axes, type(axes1)):
axes = [axes]
for ax, top in zip(axes, rejection.topographies.T):
plot_topomap(top,
ch_names_to_2d_pos(channels),
axes=ax,
show=False)
fig.savefig('csp_S{}_D{}.png'.format(subj, day + 1))
fig.show()
from vendor.nfb.pynfb.signal_processing.helpers import get_outliers_mask
import numpy as np
from PyQt5 import QtGui, QtWidgets
from vendor.nfb.pynfb.protocols.ssd.topomap_selector_ica import ICADialog
fs = 1000
band = (8, 14)
channels = ['Fp1', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'Ft9', 'Fc5', 'Fc1', 'Fc2', 'Fc6', 'Ft10', 'T3', 'C3', 'Cz',
'C4', 'T4', 'Tp9', 'Cp5', 'Cp1', 'Cp2', 'Cp6', 'Tp10', 'T5', 'P3', 'Pz', 'P4', 'T6', 'O1', 'Oz', 'O2']
data = [loadmat(r'C:\Users\Nikolai\Desktop\Liza_diplom_data\Liza_diplom_data\treatment\p25\day2\proba{}.mat'.format(k))['X1Topo'].T for k in range(1, 16)]
df = pd.DataFrame(data=np.concatenate(data), columns=channels)
for ch in['Pz', 'Cz']:
channels.remove(ch)
del df[ch]
df = df.loc[~get_outliers_mask(df[channels])]
#plt.plot(*welch(df['C3'], fs, nperseg=4*fs))
plt.plot(df[channels])
plt.show()
#plt.show()
#df['C3env'] = np.abs(hilbert(fft_filter(df['C3'], fs, band)))
#df['C4env'] = np.abs(hilbert(fft_filter(df['C4'], fs, band)))
#plt.plot(df['C3env']+df['C4env'])
a = QtWidgets.QApplication([])
(rej, filt, topo, _unmix, _bandpass, _) = ICADialog.get_rejection(df.iloc[:fs*60*3], channels, fs)
df['SMR'] = np.dot(df.as_matrix(), filt)
df.to_pickle('p4')
plt.plot(df['SMR'])
plt.show()
def run_ssd(self, row=None, csp=False, ica=False):
if row is None and ica:
row = self.table.ica_buttons.index(self.sender())
elif row is None and not csp:
row = self.table.buttons.index(self.sender())
elif row is None and csp:
row = self.table.csp_buttons.index(self.sender())
ind = self.get_checked_protocols()
print(ind)
x = concatenate([self.x[j] for j in ind[0]])
if csp:
x = concatenate([x] + [self.x[j] for j in ind[1]])
x = dot(x, self.signals[row].rejections.get_prod())
x = x[:, self.channels_mask]
to_all = False
ica_rejection = None
topography = None
if ica:
reply = QtWidgets.QMessageBox.Yes
if len(self.signals[row].rejections) > 0:
reply = QtWidgets.QMessageBox.question(self, 'Warning',
'Changing ICA base selection will '
'invalidate the current rejections (CSP, SSD). '
'Are you sure you want to continue?',
QtWidgets.QMessageBox.Yes, QtWidgets.QMessageBox.No)
if reply == QtWidgets.QMessageBox.Yes:
result = ICADialog.get_rejection(x, self.channels_names, self.sampling_freq,
decomposition=self.ica_unmixing_matrix)
ica_rejection, filter, topography, self.ica_unmixing_matrix, bandpass, to_all = result
rejections = []
elif csp:
rejection, filter, topography, _, bandpass, to_all = ICADialog.get_rejection(x, self.channels_names, self.sampling_freq,
mode='csp', _stimulus_split=self.stimulus_split.isChecked(),
marks=self.marks)
rejections = [rejection] if rejection is not None else []
else:
filter, topography, bandpass, rejections = SelectSSDFilterWidget.select_filter_and_bandpass(x, self.pos,
self.channels_names,
sampling_freq=
self.sampling_freq)
if filter is not None:
filter_copy = np.zeros(len(self.channels_mask))
filter_copy[self.channels_mask] = filter
filter = filter_copy
if topography is not None:
topography_copy = np.zeros(len(self.channels_mask))
topography_copy[self.channels_mask] = topography
topography = topography_copy
if ica_rejection is not None:
ica_rejection = ica_rejection.expand_by_mask(self.channels_mask)
rejections = [rej.expand_by_mask(self.channels_mask) for rej in rejections]
rows = range(len(self.signals)) if to_all else [row]
print(to_all, rows)
for row_ in rows:
if ica_rejection is not None:
self.signals[row_].update_ica_rejection(ica_rejection)
if filter is not None:
self.signals[row_].update_spatial_filter(filter, topography=topography)
if bandpass is not None:
self.signals[row_].update_bandpass(bandpass)
self.signals[row_].update_rejections(rejections, append=True)
modified_flag = len(rejections)>0 or bandpass is not None or filter is not None
self.table.update_row(row_, modified=modified_flag)