def __init__(self, normalise_seconds = True):
self.dir_path = '/Users/Jonathan/Dropbox/EEG/'
self.annotation_file = 'seizures_Rat8_20-271015.xlsx'
self.normalise_seconds = True
annotations = pd.read_excel(self.dir_path+self.annotation_file, index_col=False)
annotations.columns = ['fname','start','end']
#self.annotations = annotations.dropna(axis=0, how='all')
fname = annotations.iloc[1,0]
start = annotations.iloc[1,1]
end = annotations.iloc[1,2]
duration = start - end
print start,end,duration,file
fname = 'M1445362612.ndf'
ndf = NDFLoader(self.dir_path+'ndf/'+fname, print_meta=True)
ndf.load(8)
np.set_printoptions(precision=3, suppress = True)
ictal_time = ndf.time[(ndf.time >= start) & (ndf.time <= end)]
ictal_data = ndf.data[(ndf.time >= start) & (ndf.time <= end)]
plt.plot(ictal_time,ictal_data)
#plt.plot(ndf.time[:5120], ndf.data[:5120])
plt.show()
def _load_ictal_raw(self):
self.f = h5py.File('ictal_file.hdf5', 'w')
# only going to load a ndf with max of two seizures in it - will fail with three!
for i in xrange(self.annotations.shape[0]):
#for i in xrange(1):
fname = self.annotations.iloc[i, 0]
start = self.annotations.iloc[i, 1]
end = self.annotations.iloc[i, 2]
print fname, end, start
ndf = NDFLoader(self.dir_path + 'ndf/' + fname, print_meta=True)
ndf.load(8)
ndf.glitch_removal(plot_glitches=False, print_output=True)
ndf.correct_sampling_frequency()
np.set_printoptions(precision=3, suppress=True)
ictal_time = ndf.time[(ndf.time >= start) & (ndf.time <= end)]
ictal_data = ndf.data[(ndf.time >= start) & (ndf.time <= end)]
#print ictal_data.shape[0]
#print ictal_time.shape
try:
self.fname_dset = self.f.create_dataset(
fname, (ictal_data.shape[0], 2), dtype='float')
except:
self.fname_dset = self.f.create_dataset(
fname + '_' + str(2), (ictal_data.shape[0], 2),
dtype='float')
self.fname_dset[:, 0] = ictal_time
self.fname_dset[:, 1] = ictal_data
