Looks like there are some errors in copying your code to question.

But I suspect there’s a known problem with indexing:

```
In [73]: a=np.zeros((2,3,4)); b=np.ones((3,4)); I=np.array([0,1])
```

Make `I`

2 elements. Indexing `b`

gives the expected (3,2) shape. 3 rows from the slice, 2 columns from `I`

indexing

```
In [74]: b[:,I].shape
Out[74]: (3, 2)
```

But with 3d `a`

we get the transpose.

```
In [75]: a[0,:,I].shape
Out[75]: (2, 3)
```

and assignment would produce an error

```
In [76]: b[:,I]=a[0,:,I]
...
ValueError: array is not broadcastable to correct shape
```

It’s putting the 2 element dimension defined by `I`

first, and the 3 element from `:`

second. It’s a case of mixed advanced indexing that has been discussed earlier – and there’s a bug issue as well. (I’ll have to look those up).

You are probably using a newer `numpy`

(or `scipy`

) and getting a different error message.

It’s documented that indexing with two arrays or lists, and slice in the middle, puts the slice at the end, e.g.

```
In [86]: a[[[0],[0],[1],[1]],:,[0,1]].shape
Out[86]: (4, 2, 3)
```

The same thing is happening with `a[0,:,[0,1]]`

. But there’s a good argument that it shouldn’t be this way.

As to a fix, you could transpose a value, or change the indexing

```
In [88]: b[:,I]=a[0:1,:,I]
In [90]: b[:,I]=a[0,:,I].T
In [91]: b
Out[91]:
array([[ 0., 0., 1., 1.],
[ 0., 0., 1., 1.],
[ 0., 0., 1., 1.]])
In [92]: b[:,I]=a[0][:,I]
```

https://github.com/numpy/numpy/issues/7030

https://github.com/numpy/numpy/pull/6256