Unpickle saved results without stan model, pystan

Modeling
2

Hi,

Yes, one should save the model with the fit. (Model is actually a python module and you need to load it for the fit)

There are a couple of ways.

I recommend that you split model compilation and fitting.

stan_model = pystan.StanModel(file=model_path)

outputs = []
for ...:
    fit = stan_model.sampling(data=...)
    outputs.append(fit)

# you can use compression too
import gzip
with gzip.open(...pickle.gz, "wb") as f:
    pickle.dump({"model" : stan_model, "outputs" : outputs})

This was assuming you use the same model for each fit; if not true, compile new model in a for loop and move model + fit together

.append([model, output])

And you can then just pickle the output list.

There are a couple of different ways to save the fit info too: arviz.InferenceData == NetCDF or pandas.DataFrame

import arviz as az
idata = az.from_pystan(fit)
idata.to_netcdf(path)
# latest summary info (updated rhat + ess)
az.summary(idata) # or az.summary(fit)
# plotting
az.plot_pair(idata)

https://arviz-devs.github.io/arviz/

# pandas
dataframe = fit.to_dataframe()
dataframe.to_csv(path)

To load data from old fits that don’t have the model saved, see https://pystan.readthedocs.io/en/latest/unpickling_fit_without_model.html

I recommend that you then save these values with arviz, because the model is not really related to the fit, so any additional calculation could be wrong.

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