Support wrapping a Java-side block of memory allocated off-heap to Python

With `ByteBuffer.allocateDirect` you can allocate memory off-heap in Java, which can then be shared with other processes. We want to easy manufacturing of numpy arrays and xarrays that wrap this sort of off-heap memory, so that you can directly change data in Python that originated in Java (by some definition of "originated"—since it's off-heap).

In #73, @hanslovsky wrote:
> should be possible already, albeit I don't think there is a convenience method for that. Things may have changed since I was last involved with imglyb (it was still pyjnius back then), but there is/was a way to generate ImgLib2 ArrayImgs backed by native memory and you can then simply pass that pointer into a numpy array.

See also https://github.com/imglib/imglib2-cache-python

Start by reviewing the ByteBuffer.allocateDirect use case in this issue, then read issue #73 and the linked imglib2-cache-python project for existing native-memory and pointer-handling approaches. The payload names no implementation files or tests; done would mean a documented, tested way to create NumPy or xarray views over Java off-heap memory.

Written by the indexing model from the issue text.