def merge_same(self): #合并关联密度吸引点
uf = UnionFind(self.n)
for i in range(self.n):
for j in range(i + 1, self.n):
if dist(self.attrs[i], self.attrs[j]) < 2 * DELTA:
uf.merge(i, j)
uf.arrange()
new_attrs = []
for position in uf.pos:
new_attrs.append(self.attrs[position])
self.attrs = new_attrs
for i in range(self.n):
self.bel.append(uf.sid[i])
def merge_cluster(self): #合并簇
uf = UnionFind(len(self.attrs))
is_higher = [self.f_gauss(p) >= XI for p in self.ps]
for i in range(self.n):
for j in range(i + 1, self.n):
if self.bel[i] != self.bel[j] \
and is_higher[i] \
and is_higher[j] \
and (not self.is_out[self.bel[i]]) \
and (not self.is_out[self.bel[j]]) \
and dist(self.ps[i], self.ps[j]) < K:
uf.merge(self.bel[i], self.bel[j])
uf.arrange()
for i in range(len(self.attrs)):
self.cluster_id.append(uf.sid[i])
