使用一堆12维点（见下文），我正在尝试用SciPy生成一个ConvexHull。
这是可行的，但我得到的方法太多了，11022确切地说，许多方程都是精确的重复。
我可以使用NumPy删除重复项（这会将其减少到大约20（！）个等式），但由于我还想访问.neighbors，我害怕搞砸索引。
知道为什么会这样吗？这是一个错误吗？
点数组：
[[ 1. 1. 1. 0. 1. 1. 1. 0. 1. 0. 0. 0.]
[ 1. 1. 0. 0. 1. 0. 0. 0. 1. 1. 1. 0.]
[ 1. 1. 1. 1. 1. 0. 0. 0. 0. 1. 0. 0.]
[ 1. 1. 0. 1. 0. 0. 0. 0. 0. 0. 1. 1.]
[ 1. 1. 1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
[ 1. 1. 0. 1. 1. 0. 0. 0. 0. 0. 1. 0.]
[ 1. 1. 1. 1. 0. 1. 1. 0. 0. 0. 0. 1.]
[ 1. 1. 1. 1. 1. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 1. 0. 1. 1. 0. 0. 1. 0. 0. 0.]
[ 1. 1. 0. 0. 0. 1. 0. 0. 1. 0. 1. 1.]
[ 1. 1. 0. 1. 0. 1. 1. 1. 0. 0. 1. 1.]
[ 1. 1. 1. 0. 0. 1. 1. 0. 1. 0. 0. 1.]
[ 1. 1. 1. 0. 0. 0. 0. 0. 1. 1. 0. 1.]
[ 1. 1. 0. 0. 1. 1. 1. 0. 1. 0. 1. 0.]
[ 1. 1. 1. 0. 1. 0. 0. 0. 1. 0. 0. 0.]
[ 1. 1. 0. 1. 1. 0. 1. 1. 0. 1. 1. 0.]
[ 1. 1. 0. 0. 0. 0. 1. 0. 1. 1. 1. 1.]
[ 1. 1. 1. 0. 1. 1. 1. 1. 1. 0. 0. 0.]
[ 1. 1. 0. 0. 1. 0. 1. 1. 1. 1. 1. 0.]
[ 1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 0. 0. 0. 1. 1. 1. 1. 0. 1. 1.]
[ 1. 1. 0. 1. 0. 1. 0. 0. 0. 0. 1. 1.]
[ 1. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 1.]
[ 1. 1. 1. 0. 0. 0. 1. 1. 1. 1. 0. 1.]
[ 1. 1. 0. 1. 0. 0. 1. 0. 0. 1. 1. 1.]
[ 1. 1. 0. 1. 1. 0. 0. 0. 0. 1. 1. 0.]
[ 1. 1. 1. 0. 1. 0. 1. 0. 1. 1. 0. 0.]
[ 1. 1. 0. 0. 1. 1. 1. 1. 1. 0. 1. 0.]
[ 1. 1. 1. 1. 1. 0. 1. 1. 0. 1. 0. 0.]
[ 1. 1. 1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 0. 1. 1. 1. 0. 0. 0. 0. 1. 0.]
[ 1. 1. 1. 1. 1. 0. 1. 0. 0. 1. 0. 0.]
[ 1. 1. 1. 1. 0. 0. 0. 0. 0. 1. 0. 1.]
[ 1. 1. 1. 0. 0. 0. 0. 0. 1. 0. 0. 0.]
[ 1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]
[ 1. 1. 0. 1. 1. 1. 1. 0. 0. 0. 1. 0.]
[ 1. 1. 0. 1. 0. 1. 1. 0. 0. 0. 1. 1.]
[ 1. 1. 1. 0. 1. 0. 1. 1. 1. 1. 0. 0.]
[ 1. 1. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1.]
[ 1. 1. 1. 1. 0. 0. 1. 0. 0. 1. 0. 1.]
[ 1. 1. 1. 1. 0. 1. 0. 0. 0. 0. 0. 1.]
[ 1. 1. 1. 0. 0. 1. 1. 1. 1. 0. 0. 1.]
[ 1. 1. 0. 0. 1. 1. 0. 0. 1. 0. 1. 0.]
[ 1. 1. 1. 1. 1. 1. 1. 0. 0. 0. 0. 0.]
[ 1. 1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1.]
[ 1. 1. 0. 1. 1. 0. 1. 0. 0. 1. 1. 0.]
[ 1. 1. 0. 1. 1. 1. 1. 1. 0. 0. 1. 0.]
[ 1. 1. 0. 0. 1. 0. 1. 0. 1. 1. 1. 0.]
[ 1. 1. 1. 0. 0. 0. 1. 0. 1. 1. 0. 1.]
[ 1. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0.]
[ 1. 1. 1. 0. 1. 0. 0. 0. 1. 1. 0. 0.]
[ 1. 1. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1.]
[ 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 1. 1. 0. 1. 1. 1. 0. 0. 0. 1.]
[ 1. 1. 1. 0. 0. 1. 0. 0. 1. 0. 0. 1.]
[ 1. 1. 0. 0. 0. 1. 1. 0. 1. 0. 1. 1.]
[ 1. 1. 1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 1. 0. 0. 0. 0. 0. 1. 0. 0. 1.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0.]
[ 1. 1. 0. 1. 0. 0. 1. 1. 0. 1. 1. 1.]
[ 1. 1. 1. 1. 0. 0. 1. 1. 0. 1. 0. 1.]
[ 1. 1. 0. 0. 1. 0. 0. 0. 1. 0. 1. 0.]
[ 1. 1. 1. 1. 0. 0. 0. 0. 0. 0. 0. 1.]]