def query(self, *tags, **kwtags):
"""
:type position_cutoff: float or int
:param position_cutoff: only optimizations with position less than
the cutoff are returned.
"""
opts = super(SequenceDB, self).query(*tags, **kwtags)
position_cutoff = kwtags.pop('position_cutoff',
config.optdb.position_cutoff)
if len(tags) >= 1 and isinstance(tags[0], Query):
#the call to super should have raise an error with a good message
assert len(tags) == 1
if getattr(tags[0], 'position_cutoff', None):
position_cutoff = tags[0].position_cutoff
opts = [o for o in opts if self.__position__[o.name] < position_cutoff]
# We want to sort by position and then if collision by name
# for deterministic optimization. Since Python 2.2, sort is
# stable, so sort by name first, then by position. This give
# the order we want.
opts.sort(key=lambda obj: obj.name)
opts.sort(key=lambda obj: self.__position__[obj.name])
ret = opt.SeqOptimizer(opts, failure_callback=self.failure_callback)
if hasattr(tags[0], 'name'):
ret.name = tags[0].name
return ret
def query(self, *tags, **kwtags):
"""
:type position_cutoff: float or int
:param position_cutoff: only optimizations with position less than
the cutoff are returned.
"""
opts = super(SequenceDB, self).query(*tags, **kwtags)
position_cutoff = kwtags.pop('position_cutoff',
config.optdb.position_cutoff)
if len(tags) >= 1 and isinstance(tags[0], Query):
#the call to super should have raise an error with a good message
assert len(tags) == 1
if getattr(tags[0], 'position_cutoff', None):
position_cutoff = tags[0].position_cutoff
opts = [o for o in opts if self.__position__[o.name] < position_cutoff]
opts.sort(key=lambda obj: self.__position__[obj.name])
ret = opt.SeqOptimizer(opts, failure_callback=self.failure_callback)
if hasattr(tags[0], 'name'):
ret.name = tags[0].name
return ret