retain dimensions for numpy slice

[duncan smith]

Hello,
      I have several arrays that I need to combine elementwise in
various fashions. They are basically probability tables and there is a
mapping of axes to variables. I have code for transposing and reshaping
that aligns the variables / axes so the usual broadcasting rules achieve
the desired objective. But for a specific application I want to avoid
the transposing and reshaping. So I've specified arrays that contain the
full dimensionality (dimensions equal to the total number of variables).
e.g.

Arrays with shape,

[1,3,3] and [2,3,1]

to represent probability tables with variables

[B,C] and [A,B].

One operation that I need that is not elementwise is summing over axes,
but I can use numpy.sum with keepdims=True to retain the appropriate shape.

The problem I have is with slicing. This drops dimensions. Does anyone
know of a solution to this so that I can e.g. take an array with shape
[2,3,1] and generate a slice with shape [2,1,1]? I'm hoping to avoid
having to manually reshape it. Thanks.

Duncan