def convert_to_dataset(obj, *, group="posterior", coords=None, dims=None):
    """Convert a supported object to an xarray dataset.

    This function is idempotent, in that it will return xarray.Dataset functions
    unchanged. Raises `ValueError` if the desired group can not be extracted.

    Note this goes through a DataInference object. See `convert_to_inference_data`
    for more details. Raises ValueError if it can not work out the desired
    conversion.

    Parameters
    ----------
    obj : dict, str, np.ndarray, xr.Dataset, pystan fit, pymc3 trace
        A supported object to convert to InferenceData:
            InferenceData: returns unchanged
            str: Attempts to load the netcdf dataset from disk
            pystan fit: Automatically extracts data
            pymc3 trace: Automatically extracts data
            xarray.Dataset: adds to InferenceData as only group
            dict: creates an xarray dataset as the only group
            numpy array: creates an xarray dataset as the only group, gives the
                         array an arbitrary name
    group : str
        If `obj` is a dict or numpy array, assigns the resulting xarray
        dataset to this group.
    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
    -------
    xarray.Dataset
    """
    inference_data = convert_to_inference_data(obj, group=group, coords=coords, dims=dims)
    dataset = getattr(inference_data, group, None)
    if dataset is None:
        raise ValueError(
            "Can not extract {group} from {obj}! See {filename} for other "
            "conversion utilities.".format(group=group, obj=obj, filename=__file__)
        )
    return dataset
def convert_to_dataset ( obj , * , group = "posterior" , coords = None , dims = None ) : inference_data = convert_to_inference_data ( obj , group = group , coords = coords , dims = dims ) dataset = getattr ( inference_data , group , None ) if dataset is None : raise ValueError ( "Can not extract {group} from {obj}! See {filename} for other " "conversion utilities." . format ( group = group , obj = obj , filename = __file__ ) ) return dataset
Convert a supported object to an xarray dataset.

    This function is idempotent, in that it will return xarray.Dataset functions
    unchanged. Raises `ValueError` if the desired group can not be extracted.

    Note this goes through a DataInference object. See `convert_to_inference_data`
    for more details. Raises ValueError if it can not work out the desired
    conversion.

    Parameters
    ----------
    obj : dict, str, np.ndarray, xr.Dataset, pystan fit, pymc3 trace
        A supported object to convert to InferenceData:
            InferenceData: returns unchanged
            str: Attempts to load the netcdf dataset from disk
            pystan fit: Automatically extracts data
            pymc3 trace: Automatically extracts data
            xarray.Dataset: adds to InferenceData as only group
            dict: creates an xarray dataset as the only group
            numpy array: creates an xarray dataset as the only group, gives the
                         array an arbitrary name
    group : str
        If `obj` is a dict or numpy array, assigns the resulting xarray
        dataset to this group.
    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
    -------
    xarray.Dataset