def train_(self, d):
if self.ftype == 0:
self.T = channel_temporal_offsets(d.data, self.k)
elif self.ftype == 1:
data = np.mean(erp(d).data, axis=2)
self.T = channel_temporal_offsets(data, self.k)
else:
raise ValueError('Operation not supported on covariance data')
SpatialBlur.train_(self, d)
def __init__(self, sigma, k, ftype=1):
SpatialBlur.__init__(self, sigma, ftype)
self.k = range(-k, k)
