def format_data_to_stan()

in pplbench/ppls/stan/noisy_or_topic.py [0:0]

• 6 lines of code
• 2 McCabe index (conditional complexity)

    def format_data_to_stan(self, data: xr.Dataset) -> Dict:
        """
        Take data from the model generator and the previously passed model
        arguments to construct a data dictionary to pass to Stan.
        :param data: A dataset from the model generator
        :returns: a dictionary that can be passed to stan
        """
        # transpose the dataset to ensure that it is the way we expect
        data = data.transpose("sentence", "word")
        assert self.attrs["n"] == 1
        self.attrs["S"] = data.S.values[0]
        self.attrs["tau"] = 0.1
        # note: attrs should already contain n, edge_weight, num_topics and num_words
        return self.attrs