def __init__(self, template, shrinkage='oas', center=True):
SpatialFilter.__init__(self, 1)
self.template = template
self.template = np.asarray(template).flatten()[:, np.newaxis]
self.center = center
if center:
self.template -= self.template.mean()
if shrinkage == 'oas':
self.cov = OAS
elif shrinkage == 'lw':
self.cov = LedoitWolf
elif shrinkage == 'none':
self.cov = EmpiricalCovariance
elif type(shrinkage) == float or type(shrinkage) == int:
self.cov = ShrunkCovariance(shrinkage=shrinkage)
def apply_(self, d):
if self.center:
d = DataSet(d.data - d.data.mean(axis=0), default=d)
d = baseline(d)
return SpatialFilter.apply_(self, d)
