Refactor match numpyro prior dim names with numpyro posterior

[Cab14bacc]

depends on #63

This renames the prior and prior predictive dataset dim names such that it matches the posterior dim names.
The posterior is computed with: return extract(from_numpyro(mcmc), group="posterior", keep_dataset=True).
arviz_base.from_numpyro calls arviz_base.io_numpyro.infer_dims to infer the dim names by grabbing plate dims and event dims.
This implementation directly uses arviz_base.io_numpyro.infer_dims

For example this numpyro model has plate defined by J

def eight_schools_cauchy_prior(J, sigma, y=None):
    mu = numpyro.sample("mu", dist.Normal(0, 5))
    tau = numpyro.sample("tau", dist.HalfCauchy(5))
    with numpyro.plate("J", J):
        theta = numpyro.sample("theta", dist.Normal(mu, tau))
    numpyro.sample("y", dist.Normal(theta, sigma), obs=y)

After simuk runs the simulation loop, the prior will have generated a dim called theta_dim_0, where as the posterior with from_numpyro will have the same dim with name J. Thus, we rename the prior and prior predictive so that it has the same dim names as the posterior.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 95.95%. Comparing base (74f2de3) to head (d0bc52f).

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #64      +/-   ##
==========================================
+ Coverage   95.90%   95.95%   +0.05%     
==========================================
  Files           7        7              
  Lines         635      643       +8     
==========================================
+ Hits          609      617       +8     
  Misses         26       26              

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.