def mark_by_threshold(dataset, DV='MEG', threshold=2e-12, above=False, below=None,
target='accept'):
"""
Marks epochs based on a threshold criterion (any sensor exceeding the
threshold at any time)
above: True, False, None
How to mark segments that exceed the threshold: True->good;
False->bad; None->don't change
below:
Same as ``above`` but for segments that do not exceed the threshold
threshold : float
The threshold value.
1.25e-11: detect saturated channels
2e-12: conservative final rejection
target : factor or str
Factor (or its name) in which the result is stored. If ``var`` is
a string and the dataset does not contain that factor, it is
created.
"""
if isinstance(DV, basestring):
DV = dataset[DV]
# get the factor on which to store results
if _data.isfactor(target) or _data.isvar(target):
assert len(target) == dataset.N
elif isinstance(target, basestring):
if target in dataset:
target = dataset[target]
else:
x = _np.ones(dataset.N, dtype=bool)
target = _data.var(x, name=target)
dataset.add(target)
else:
raise ValueError("target needs to be a factor")
# do the thresholding
if _data.isndvar(DV):
for ID in xrange(dataset.N):
data = DV[ID]
v = _np.max(_np.abs(data.x))
if v > threshold:
if above is not None:
target[ID] = above
elif below is not None:
target[ID] = below
else:
for ID in xrange(dataset.N):
v = DV[ID]
if v > threshold:
if above is not None:
target[ID] = above
elif below is not None:
target[ID] = below
def __repr__(self):
args = [self.Y.name, self.X.name]
rpr = "celltable(%s)"
if self.match is not None:
args.append("match=%s" % self.match.name)
if self.sub is not None:
if _data.isvar(self.sub):
args.append("sub=%s" % self.sub.name)
else:
indexes = " ".join(str(i) for i in self.sub[:4])
args.append("sub=[%s...]" % indexes)
return rpr % (", ".join(args))
