Data container reductions - #1515

I had a chat with @paskino about this. We decided that:

1. The accumulation should always happen at 64bit, we can remove this as an option for the user.
2. The return data container dtype should be the same as the input dtype. Again this is not something we should expose as an argument.
3. The reductions can return an AcquisitionData or ImageData when this is passed to out. In this instance we will check that the array is the expected size and dtype, we will not check or update the geometry. In practise this will mean doing the reduction, getting the numpy array and then using out.fill(), we cannot use out.aray directly as it will (probably) be the wrong dtype to accumulate in to.

Hello @gfardell and @paskino, just thinking about point 2:

2. The return data container dtype should be the same as the input dtype. Again this is not something we should expose as an argument.

do you think this should also be the case for ints? Especially for mean that might not be intuitive

The link hasn't rendered nicely in the documentation - but I'm not sure it's necessary or adds much. Maybe for min and max should enforce the same data type as the input. For mean I think you could just say the accumulated 64bit data will be cast to the output data type.

The link hasn't rendered nicely in the documentation - but I'm not sure it's necessary or adds much. Maybe for min and max should enforce the same data type as the input. For mean I think you could just say the accumulated 64bit data will be cast to the output data type.

This should be rendering correctly now. I think it makes sense to keep the same behaviour for min and max because we might want to be able to pass a different data type to out, so we don't want to enforce the same data type as the input.