Hi all,

I have the following `arviz.InferenceData`

-object:

```
fit = az.from_pystan(
posterior=fit,
posterior_model=model,
coords={
'driver': list(drivers_idx.keys()),
'team': list(teams_idx.keys()),
'circuit': list(circuits_idx.keys())
},
dims={
'theta': ['driver'],
'tau': ['team'],
'phi': ['team', 'circuit']
}
)
```

Basically, `theta`

represent the skill of a driver (for example Max Verstappen), `tau`

represent the skill of a team (Red Bull) and `phi`

represent the circuit-specific skill of a team (Red Bull on Circuit of Monaco.

I want to create a matrix of shape *(n_teams, n_circuits)* of posterior means of `phi`

- `tau`

. How do I make sure that the pairwise subtraction is done based on the shared `team`

-coords?

Can this matrix be seen as a correlation matrix or which additional steps are needed to create one?

The goal is to measure the similarity between the circuits.