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