Introducing bayeux

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If you want to use this with Bambi just call model.build() and then use model.backend.model in the bx.Model.from_pymc call like this:

dist = pm.Normal.dist(mu=100, sigma=30)

draws = pm.draw(dist, draws=1000, random_seed=1000)

df = pd.DataFrame(data=draws, columns=['heights'])

formula = bmb.Formula('heights ~ 1')

model = bmb.Model(formula=formula, family='gaussian', data=df)

model.build()

bx_model = bx.Model.from_pymc(model.backend.model)

idata = bx_model.mcmc.numpyro_nuts(seed=jax.random.key(0))

az.summary(idata)
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