code: 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
docs: 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