d55bad55b6a9e97f800c97c73038bc5ed8d4b31f,arviz/data/io_pystan.py,PyStanConverter,prior_to_xarray,#PyStanConverter#,201

Before Change

                    values = np.expand_dims(values, -1)
                else:
                    values = np.expand_dims(values, 0)
            values = np.swapaxes(values, 0, 1)
            data[key] = values
        return dict_to_dataset(data, library=self.pystan, coords=self.coords, dims=self.dims)

    @requires("fit")
    @requires("observed_data")

After Change

        if prior_predictive is None:
            prior_predictive = []
        elif isinstance(prior_predictive, str):
            prior_predictive = [prior_predictive]

        ignore = prior_predictive + ["lp__"]

        data = get_draws(prior, ignore=ignore)

Instances