python-在numpy 2darray中逐行查找大于阈值的值的索引

我有一个2darray如下.我想通过数组中的每一行找到高于阈值(例如0.7)的值的索引.

items= np.array([[1.,0.40824829,0.03210806,0.29488391,0.,0.5,0.32444284,0.57735027,0.5       ],[0.40824829,1.,0.57675476,0.48154341,0.81649658,0.79471941,0.70710678,0.40824829],[0.03210806,0.42606683,0.92713363,0.834192,0.73848549],[0.29488391,0.52620136,0.51075392,0.20851441,0.44232587],[0.,0.        ],[0.5,0.28867513,[0.32444284,0.93658581,0.22941573,0.81110711],[0.57735027,0.8660254 ],0.73848549,0.44232587,0.81110711,0.8660254,1.        ]])

indices_items = np.argwhere(items>= 0.7)

此(indices_items)返回

array([[0,0],[1,1],5],6],7],[2,2],9],[3,3],[5,8],[6,[7,[8,[9,9]],dtype=int64)

我怎样才能按行获取索引,如下所示？
第0行-> [0]行1- [0,1,5,6,7]行2-> [2,7,9]行3-> [3] row4-> []
#此列表应该为空,因为没有超出阈值的值… 最佳答案 获取带有np.where的行,然后使用np.searchsorted来获取行数组上的间隔索引,并使用它们来拆分col-array-

In [38]: r,c = np.where(items>= 0.7)

In [39]: np.split(c,np.searchsorted(r,range(1,items.shape[0])))
Out[39]: 
[array([0],dtype=int64),array([1,array([2,array([3],array([],2,array([5,dtype=int64)]

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