def bcg_filt_pca_nh(x, ts, m=1024, k=20):
"""Filter BCG-artifacts from simultaneous recordings of EEG and fMRI using PCA
(principal component analysis), but in local neighborhood"""
assert len(x.shape) in [1, 2], "x must be a 1d- or 2d-array"
if len(x.shape) == 1:
x = x.reshape((x.shape[0], 1))
x = _highpass(x, Fs=Fs)
window = n.hanning(m)
#Other possibilities for window:
#n.ones((m),"d")
#n.hamming(m)
#n.bartlett(m)
ts_bcg = ts
for ch_num in range(x.shape[1]):
if debug:
print "Get all BCG-artifacts of channel %i in one array" % ch_num
bcgs = n.zeros((m, len(ts_bcg)), "d")
for i in range(bcgs.shape[1]):
#print eeg[ts_bcg[i]-m/2:ts_bcg[i]+m/2,14].shape
try:
bcgs[:, i] = x[ts_bcg[i] - m / 2:ts_bcg[i] + m / 2, ch_num]
except ValueError, e:
print "Value Error, probably shape missmatch", e
if debug:
print "Find nearest neighbors"
neighbors = find_n_nearest_neighbors(bcgs.T, k)
for i in range(bcgs.shape[1]):
boolslice = n.zeros((bcgs.shape[1]), n.bool)
for ni, neighbor in enumerate(neighbors[i]):
boolslice[neighbor] = True
NH = bcgs[:, boolslice]
components = pcafilt.unmix(NH)
for k in range(components.shape[1]):
if components[:, k].std() > 100.0: #acc > 0.03:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (
ch_num, k, components[:, k].std(),
abs(components[:, k]).mean()), "removed"
components[:, k] = n.zeros(components[:, k].shape, "d")
else:
if k == 0:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (
ch_num, k, components[:, k].std(),
abs(components[:, k]).mean()), "not removed"
NH = pcafilt.mix(components)
try:
x[ts_bcg[i] - m / 2:ts_bcg[i] + m / 2, ch_num] = NH[:, 0]
except ValueError, e:
print "Value Error, probably shape missmatch", e
def bcg_filt_pca_nh(x,ts,m=1024,k=20):
"""Filter BCG-artifacts from simultaneous recordings of EEG and fMRI using PCA
(principal component analysis), but in local neighborhood"""
assert len(x.shape) in [1,2], "x must be a 1d- or 2d-array"
if len(x.shape) == 1:
x=x.reshape((x.shape[0],1))
x = _highpass(x,Fs=Fs)
window = n.hanning(m)
#Other possibilities for window:
#n.ones((m),"d")
#n.hamming(m)
#n.bartlett(m)
ts_bcg = ts
for ch_num in range(x.shape[1]):
if debug:
print "Get all BCG-artifacts of channel %i in one array" % ch_num
bcgs = n.zeros((m,len(ts_bcg)),"d")
for i in range(bcgs.shape[1]):
#print eeg[ts_bcg[i]-m/2:ts_bcg[i]+m/2,14].shape
try:
bcgs[:,i] = x[ts_bcg[i]-m/2:ts_bcg[i]+m/2,ch_num]
except ValueError,e:
print "Value Error, probably shape missmatch", e
if debug:
print "Find nearest neighbors"
neighbors = find_n_nearest_neighbors(bcgs.T,k)
for i in range(bcgs.shape[1]):
boolslice = n.zeros((bcgs.shape[1]),n.bool)
for ni,neighbor in enumerate(neighbors[i]):
boolslice[neighbor] = True
NH = bcgs[:,boolslice]
components = pcafilt.unmix(NH)
for k in range(components.shape[1]):
if components[:,k].std()>100.0:#acc > 0.03:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (ch_num,k,components[:,k].std(), abs(components[:,k]).mean()), "removed"
components[:,k] = n.zeros(components[:,k].shape,"d")
else:
if k==0:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (ch_num,k,components[:,k].std(), abs(components[:,k]).mean()), "not removed"
NH = pcafilt.mix(components)
try:
x[ts_bcg[i]-m/2:ts_bcg[i]+m/2,ch_num] = NH[:,0]
except ValueError,e:
print "Value Error, probably shape missmatch", e
def bcg_filt_pca(x, ts, m=1024, Fs=1000.0):
"""Filter BCG-artifacts from simultaneous recordings of EEG and fMRI using PCA
(principal component analysis)"""
assert len(x.shape) in [1, 2], "x must be a 1d- or 2d-array"
if len(x.shape) == 1:
x = x.reshape((x.shape[0], 1))
x = _highpass(x, Fs=Fs)
window = n.hanning(m)
#Other possibilities for window:
#n.ones((m),"d")
#n.hamming(m)
#n.bartlett(m)
ts_bcg = ts
for ch_num in range(x.shape[1]):
if debug:
print "Get all BCG-artifacts of channel %i in one array" % ch_num
bcgs = n.zeros((m, len(ts_bcg)), "d")
for i in range(bcgs.shape[1]):
#print eeg[ts_bcg[i]-m/2:ts_bcg[i]+m/2,14].shape
try:
bcgs[:, i] = x[ts_bcg[i] - m / 2:ts_bcg[i] + m / 2, ch_num]
except ValueError, e:
print "Value Error, probably shape missmatch", e
components = pcafilt.unmix(bcgs)
for k in range(components.shape[1]):
if components[:, k].std() > 100.0: #acc > 0.03:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (
ch_num, k, components[:, k].std(), abs(
components[:, k]).mean()), "removed"
components[:, k] = n.zeros(components[:, k].shape, "d")
else:
if k == 0:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (
ch_num, k, components[:, k].std(),
abs(components[:, k]).mean()), "not removed"
bcgs = pcafilt.mix(components)
for i in range(bcgs.shape[1]):
try:
x[ts_bcg[i] - m / 2:ts_bcg[i] + m / 2, ch_num] = bcgs[:, i]
except ValueError, e:
print "Value Error, probably shape missmatch", e
def bcg_filt_pca(x,ts,m=1024,Fs=1000.0):
"""Filter BCG-artifacts from simultaneous recordings of EEG and fMRI using PCA
(principal component analysis)"""
assert len(x.shape) in [1,2], "x must be a 1d- or 2d-array"
if len(x.shape) == 1:
x=x.reshape((x.shape[0],1))
x = _highpass(x,Fs=Fs)
window = n.hanning(m)
#Other possibilities for window:
#n.ones((m),"d")
#n.hamming(m)
#n.bartlett(m)
ts_bcg = ts
for ch_num in range(x.shape[1]):
if debug:
print "Get all BCG-artifacts of channel %i in one array" % ch_num
bcgs = n.zeros((m,len(ts_bcg)),"d")
for i in range(bcgs.shape[1]):
#print eeg[ts_bcg[i]-m/2:ts_bcg[i]+m/2,14].shape
try:
bcgs[:,i] = x[ts_bcg[i]-m/2:ts_bcg[i]+m/2,ch_num]
except ValueError,e:
print "Value Error, probably shape missmatch", e
components = pcafilt.unmix(bcgs)
for k in range(components.shape[1]):
if components[:,k].std()>100.0:#acc > 0.03:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (ch_num,k,components[:,k].std(), abs(components[:,k]).mean()), "removed"
components[:,k] = n.zeros(components[:,k].shape,"d")
else:
if k==0:
if debug:
print "Channel %i, Component %i, std %f, mean(abs) %f" % (ch_num,k,components[:,k].std(), abs(components[:,k]).mean()), "not removed"
bcgs = pcafilt.mix(components)
for i in range(bcgs.shape[1]):
try:
x[ts_bcg[i]-m/2:ts_bcg[i]+m/2,ch_num] = bcgs[:,i]
except ValueError,e:
print "Value Error, probably shape missmatch", e