def apex(self):
if self._apex is None:
n = self._degree
partitions = filter(lambda x: (len(x) + n) % 2 == 0, Partitions(n))
self._apex = numeric.sort_and_filter(
[reduce(numeric.lcm, partition) for partition in partitions])
return self._apex
def apex(self):
if self._apex is None:
n = self._degree
partitions = filter(lambda x: (len(x) + n) % 2 == 0, Partitions(n))
self._apex = numeric.sort_and_filter(
[reduce(numeric.lcm, partition) for partition in partitions])
return self._apex
def apex(self):
if self._apex is None:
n = self._degree
partitions = [x for x in Partitions(n) if (len(x) + n) % 2 == 0]
self._apex = numeric.sort_and_filter(
[reduce(numeric.lcm, partition) for partition in partitions])
return self._apex
def apex(self):
if self._apex is None:
func = spectra.exceptional_spectra.get(self._name, lambda *arg: [])
self._apex = numeric.sort_and_filter(func(self._field))
return self._apex
def apex(self):
if self._apex is None:
func = spectra.exceptional_spectra.get(self._name, lambda *arg: [])
self._apex = numeric.sort_and_filter(func(self._field))
return self._apex
