class_docstr: Encapsulate PyJAGS specific logic.
class_docstr_tok: ["Encapsulate","PyJAGS","specific","logic","."]
code: def _pyjags_samples_to_xarray(
      self, pyjags_samples: tp.Mapping[str, np.ndarray]
  ) -> tp.Tuple[xarray.Dataset, xarray.Dataset]:
      data, data_warmup = get_draws(
          pyjags_samples=pyjags_samples,
          warmup_iterations=self.warmup_iterations,
          warmup=self.save_warmup,
      )
  
      return (
          dict_to_dataset(
              data,
              library=self.pyjags,
              coords=self.coords,
              dims=self.dims,
          ),
          dict_to_dataset(
              data_warmup,
              library=self.pyjags,
              coords=self.coords,
              dims=self.dims,
          ),
      )
  
imports: import typing
  from collections import OrderedDict
  from collections.abc import Iterable
  import numpy
  import xarray
  from .inference_data import InferenceData
  from ..rcparams import rcParams
  from .base import dict_to_dataset
label_desc: Use image node_id 2 for calling the PyJAGSConverter obj's underlying member method code with example usage: obj._pyjags_samples_to_xarray(pyjags_samples) and returns: dict_to_dataset,  dict_to_dataset