下面是一个使用boolean indexing
的方法 -
m,n = a.shape
out = a[np.arange(n) != np.array(k)[:,None]].reshape(m,-1)
如果你想与np.delete
坚持,你可以计算线性指标,然后删除那些压扁输入数组后,像这样 -
m,n = a.shape
del_idx = np.arange(n)*m + k
out = np.delete(a.ravel(),del_idx,axis=0).reshape(m,-1)
样品运行 -
In [94]: a
Out[94]:
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
In [95]: k = [0, 2, 1]
In [96]: m,n = a.shape
In [97]: a[np.arange(n) != np.array(k)[:,None]].reshape(m,-1)
Out[97]:
array([[2, 3],
[4, 5],
[7, 9]])
In [98]: del_idx = np.arange(n)*m + k
In [99]: np.delete(a.ravel(),del_idx,axis=0).reshape(m,-1)
Out[99]:
array([[2, 3],
[4, 5],
[7, 9]])
好奇,如果解决方案发布这里适合你吗? – Divakar