def __crand(self, keep_simulations):
y = self.y
if keep_simulations:
rGs = np.zeros((self.n, self.permutations))
larger = np.zeros((self.n,))
n_1 = self.n - 1
rid = list(range(n_1))
prange = list(range(self.permutations))
k = self.w.max_neighbors + 1
rids = np.array([np.random.permutation(rid)[0:k] for i in prange])
ids = np.arange(self.w.n)
ido = self.w.id_order
wc = self.__getCardinalities()
if self.w_transform == "r":
den = np.array(wc) + self.star
else:
den = np.ones(self.w.n)
for i in range(self.w.n):
idsi = ids[ids != i]
np.random.shuffle(idsi)
yi_star = y[i] * self.star
wci = wc[i]
rGs_i = (y[idsi[rids[:, 0:wci]]]).sum(1) + yi_star
rGs_i = (np.array(rGs_i) / den[i]) / (self.y_sum - (1 - self.star) * y[i])
if keep_simulations:
rGs[i] = rGs_i
larger[i] = (rGs_i >= self.Gs[i]).sum()
if keep_simulations:
self.rGs = rGs
below = (self.permutations - larger) < larger
larger[below] = self.permutations - larger[below]
self.p_sim = (larger + 1) / (self.permutations + 1)
def __crand(self):
y = self.y
rGs = np.zeros((self.n, self.permutations))
n_1 = self.n - 1
rid = list(range(n_1))
prange = list(range(self.permutations))
k = self.w.max_neighbors + 1
rids = np.array([np.random.permutation(rid)[0:k] for i in prange])
ids = np.arange(self.w.n)
ido = self.w.id_order
wc = self.__getCardinalities()
if self.w_transform == "r":
den = np.array(wc) + self.star
else:
den = np.ones(self.w.n)
for i in range(self.w.n):
idsi = ids[ids != i]
np.random.shuffle(idsi)
yi_star = y[i] * self.star
wci = wc[i]
rGs[i] = (y[idsi[rids[:, 0:wci]]]).sum(1) + yi_star
rGs[i] = (np.array(rGs[i]) / den[i]) / (self.y_sum - (1 - self.star) * y[i])
self.rGs = rGs