数字数组索引2D矩阵-NumPyarrayindexinga2Dmatrix

I've a little issue while working on same big data. But for now, let's assume I've got an NumPy array filled with zeros

我在处理大数据的时候有个小问题。现在，假设我有一个满是0的NumPy数组

>>> x = np.zeros((3,3))
>>> x
array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.]])

Now I want to change some of these zeros with specific values. I've given the index of the cells I want to change.

现在我想用特定的值来改变其中的一些0。我已经给出了要改变的单元格的索引。

>>> y = np.array([[0,0],[1,1],[2,2]])
>>> y 
array([[0, 0],
       [1, 1],
       [2, 2]])

And I've got an array with the desired (for now random) numbers, as follow

我得到了一个具有期望(现在是随机的)数字的数组，如下所示

>>> z = np.array(np.random.rand(3))
>>> z
array([ 0.04988558,  0.87512891,  0.4288157 ])

So now I thought I can do the following:

所以现在我想我可以做以下的事:

>>> x[y] = z

But than it's filling the whole array like this

而不是像这样填满整个数组

>>> x
array([[ 0.04988558,  0.87512891,  0.4288157 ],
       [ 0.04988558,  0.87512891,  0.4288157 ],
       [ 0.04988558,  0.87512891,  0.4288157 ]])

But I was hoping to get

但我希望得到。

>>> x
array([[ 0.04988558,           0,          0 ],
       [          0,  0.87512891,          0 ],
       [          0,           0,  0.4288157 ]])

EDIT

编辑

Now I've used a diagonal index, but what in the case my index is not just diagonal. I was hoping following works:

现在我用了一个对角指数，但在这个情况下，我的索引不仅仅是对角线。我希望接下来的工作:

>>> y = np.array([[0,1],[1,2],[2,0]])
>>> x[y] = z
>>> x
>>> x
array([[          0,  0.04988558,          0 ],
       [          0,           0, 0.87512891 ],
          0.4288157,           0,          0 ]])

But it's filling whole array just like above

但是它像上面一样填充了整个数组

1 个解决方案

x[np.array([0,1,2])]

x[np.array([0,0],[1,1],[2,2]])]

x[np.array([0,1,2]), np.array([0,1,2])]

x[np.array([0,1,2]), np.array([0,1,2])] = 1

x[np.array([0,1,2]), np.array([1,2,0])]