def calc_shs(self, pattern_id):
pdata = self._data.patterns[pattern_id]
upper = sum(self.__t2(x1, x2) * 2 ** (self.__d1(x1) + self.__d1(x2)) for x1, x2 in combinations(pdata, 2)) +\
sum(self.__d2(x1, x2) * 2 ** (self.__d1(x1) + self.__d1(x2) - 1) for x1, x2 in combinations(pdata, 2)) +\
sum(2 * self.__d1(x) * calc_comb(2 ** (self.__d1(x) - 1), 2) for x in pdata) +\
sum(self.__t1(x) * calc_comb(2 ** self.__d1(x), 2) for x in pdata)
bottom = self._data.features_count * sum(2 ** (self.__d1(x1) + self.__d1(x2)) for x1, x2 in combinations(pdata, 2)) +\
self._data.features_count * sum(calc_comb(2 ** self.__d1(x), 2) for x in pdata)
return (upper, bottom)
def calc_shs(self, pattern_id):
pdata = self._data.patterns[pattern_id]
upper = sum(
self.__distance(x1, x2) for x1, x2 in combinations(pdata, 2))
bottom = calc_comb(len(pdata), 2)
return (upper, bottom)
def calc_shs(self, pattern_id):
pdata = self._data.patterns[pattern_id]
upper = sum(self.__row_distance2(x1, x2) for x1, x2 in combinations(pdata, 2)) +\
sum(self.__row_distance1(x) for x in pdata)
bottom = sum(self.__row_variants(x1) * self.__row_variants(x2) for x1, x2 in combinations(pdata, 2)) +\
sum(calc_comb(self.__row_variants(x), 2) for x in pdata)
return (upper, bottom)
def __row_distance1(self, v):
result = 0
for i in range(self._data.features_count):
result += calc_comb(self.__row_variants(v) / self.__feature_variants(v[i], i), 2) \
* self.__feature_distance2(v[i], v[i], i)
result += self.__row_variants(v) * self.__feature_distance1(v[i], i) \
/ self.__feature_variants(v[i], i)
result = result / self._data.features_count
return result
umi_calculations_full))
#
s_calculations_reduced = 0
s_calculations_full = 0
sx_calculations_reduced = 0
sx_calculations_full = 0
for i in range(len(patterns_keys)):
p_reduced = 0
p_full = 0
for x in data.patterns[patterns_keys[i]]:
p_reduced += 1
p_full += calc_variations(x)
s_calculations_reduced += commonlib.calc_comb(p_reduced, 2)
s_calculations_full += commonlib.calc_comb(p_full, 2)
sx_calculations_reduced += p_reduced
sx_calculations_full += p_full
result.append(('s_calculations_reduced', s_calculations_reduced))
result.append(('s_calculations_full', s_calculations_full))
result.append(
('s_calculations_economy',
(s_calculations_full - s_calculations_reduced) / s_calculations_full))
result.append(('sx_calculations_reduced', sx_calculations_reduced))
result.append(('sx_calculations_full', sx_calculations_full))
result.append(
('sx_calculations_economy',
(sx_calculations_full - sx_calculations_reduced) / sx_calculations_full))