Adds Velocity, ShearStress, StressDiagonal, observables

[harveydevereux]

This adds a Velocity observable capable of averaging over supplied components x, y, z and atom lists. The behaviour is abstracted so also for stress we can obtain shear stress correlations $\langle \sigma_{xy}\sigma_{xy}\rangle+\langle \sigma_{yz}\sigma_{yz}\rangle+\langle \sigma_{zx}\sigma_{zx}\rangle$ with the built in ShearStress === Stress(['xy', 'yz', 'zx'])

• ci tests now test against post-process vaf, dependent on changes to it post_process uses full correlation, fix filter_atoms #284 .

• I used the ShearStress observable to get experimental viscosity for LiF which could be an example perhaps along with the VAF.

• still need to fix the docs/ update the developer guide.

• perhaps we could have a helper function to create Velocity-Velocity correlations from a structure (say, creating correlation_kwargs for different atom types automatically). As it stands Observable does not attach to a particular atoms object and so does not have this information at construction. Except implicitly via atoms: list[int].

• Velocity can take a SliceLike or list[int]. So open-ended ranges can be specified i.e. slice(0, None), but also non-monotonic, decreasing or whatever sequences can be specified that cannot be represented as a slice.

[ElliottKasoar]

Looks like a good start, thanks @harveydevereux!

I suspect I knew a lot of the answers to my questions when we discussed this when you started, but maybe it's helpful coming to it with fresh eyes, so we can make things as clear as possible.

[ElliottKasoar]

Not really work for this PR as such, but how easy would it be to integrate/use these in post processing, rather than on-the-fly calculations?

[harveydevereux]

Not really work for this PR as such, but how easy would it be to integrate/use these in post processing, rather than on-the-fly calculations?

All it needs is to be called on some sequence of atoms objects. But if you are post-processing why not just use post-process? The only advantage of these is they extract the data from Atoms in this case

[ElliottKasoar]

All it needs is to be called on some sequence of atoms objects. But if you are post-processing why not just use post-process? The only advantage of these is they extract the data from Atoms in this case

Most significantly, I'm thinking about how easy it is to extend postprocess to observables we've defined, but aren't supported yet.

At the moment we can only do RDFs and VAFs, so if we didn't calculate any other observable on the fly, we might still want to be able to use an Observable.

It could also fit into unifying the interfaces e.g. for the VAF, depending on how their efficiencies compare, which would avoid questions about their consistency any time we make a change.

[harveydevereux]

This will show the inherited member self.components in the apidoc in e.g. Velocity and Stress and solve missing py:obj references.

CF https://stackoverflow.com/questions/5516032/docstring-inheritance-for-properties-using-sphinxs-autodoc