def from_cmdstan(
    posterior=None,
    *,
    posterior_predictive=None,
    prior=None,
    prior_predictive=None,
    observed_data=None,
    observed_data_var=None,
    log_likelihood=None,
    coords=None,
    dims=None
):
    """Convert CmdStan data into an InferenceData object.

    Parameters
    ----------
    posterior : List[str]
        List of paths to output.csv files.
        CSV file can be stacked csv containing all the chains

            cat output*.csv > combined_output.csv

    posterior_predictive : str, List[Str]
        Posterior predictive samples for the fit. If endswith ".csv" assumes file.
    prior : List[str]
        List of paths to output.csv files
        CSV file can be stacked csv containing all the chains.

            cat output*.csv > combined_output.csv

    prior_predictive : str, List[Str]
        Prior predictive samples for the fit. If endswith ".csv" assumes file.
    observed_data : str
        Observed data used in the sampling. Path to data file in Rdump format.
    observed_data_var : str, List[str]
        Variable(s) used for slicing observed_data. If not defined, all
        data variables are imported.
    log_likelihood : str
        Pointwise log_likelihood for the data.
    coords : dict[str, iterable]
        A dictionary containing the values that are used as index. The key
        is the name of the dimension, the values are the index values.
    dims : dict[str, List(str)]
        A mapping from variables to a list of coordinate names for the variable.

    Returns
    -------
    InferenceData object
    """
    return CmdStanConverter(
        posterior=posterior,
        posterior_predictive=posterior_predictive,
        prior=prior,
        prior_predictive=prior_predictive,
        observed_data=observed_data,
        observed_data_var=observed_data_var,
        log_likelihood=log_likelihood,
        coords=coords,
        dims=dims,
    ).to_inference_data()
Convert CmdStan data into an InferenceData object.

    Parameters
    ----------
    posterior : List[str]
        List of paths to output.csv files.
        CSV file can be stacked csv containing all the chains

            cat output*.csv > combined_output.csv

    posterior_predictive : str, List[Str]
        Posterior predictive samples for the fit. If endswith ".csv" assumes file.
    prior : List[str]
        List of paths to output.csv files
        CSV file can be stacked csv containing all the chains.

            cat output*.csv > combined_output.csv

    prior_predictive : str, List[Str]
        Prior predictive samples for the fit. If endswith ".csv" assumes file.
    observed_data : str
        Observed data used in the sampling. Path to data file in Rdump format.
    observed_data_var : str, List[str]
        Variable(s) used for slicing observed_data. If not defined, all
        data variables are imported.
    log_likelihood : str
        Pointwise log_likelihood for the data.
    coords : dict[str, iterable]
        A dictionary containing the values that are used as index. The key
        is the name of the dimension, the values are the index values.
    dims : dict[str, List(str)]
        A mapping from variables to a list of coordinate names for the variable.

    Returns
    -------
    InferenceData object