ENH: Overlap-add processing for maxwell filter

[larsoner]

Algorithms that process data in sequential temporal windows benefit from overlap-add processing to reduce edge artifacts. OTP in our codebase already uses this. This PR adds that to maxwell_filter for tSSS and for movement compensation (which is trickier because the windows / estimation points themselves have variable duration / timing).

The MF code changes will be hard to review 😞 Fortunately, the maxwell_filter tests we have are pretty extensive, so we can sleep well at night knowing they still pass with very few modifications. And we see some improvements in tests with what will be the new defaults in 1.11. In some ways I think the code actually gets a bit clearer by the use of classes, for example for movement compensation / head position a class makes sense because the head position is a state you want to keep track of and get information / data / methods for. That way not all aspects are controlled by a monolithic, multi-indented function like now -- there is still a multi-indented monster, but its content is much more limited and thus easier to follow.

@drammock one point for debate is whether we should actually make the new defaults "smooth" (via deprecation) as currently implemented here. In theory and in my testing they are indeed better, but they will make us more different from standard maxwell filtering. But I think the gain in data SNR is probably worth it.