class_docstr: Stan sampling wrapper base class.
  
  See the documentation on  :class:`~arviz.SamplingWrapper` for a more detailed
  description. An example of ``PyStanSamplingWrapper`` usage can be found
  in the :ref:`pystan_refitting` notebook. For usage examples of other wrappers
  see the user guide pages on :ref:`wrapper_guide`.
  
  Warnings
  --------
  Sampling wrappers are an experimental feature in a very early stage. Please use them
  with caution.
  
  See Also
  --------
  SamplingWrapper
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docstr: Select a subset of the observations in idata_orig.
  
  **Not implemented**: This method must be implemented on a model basis.
  It is documented here to show its format and call signature.
  
  Parameters
  ----------
  idx
      Indexes to separate from the rest of the observed data.
  
  Returns
  -------
  modified_observed_data : dict
      Dictionary containing both excluded and included data but properly divided
      in the different keys. Passed to ``data`` argument of ``model.sampling``.
  excluded_observed_data : str
      Variable name containing the pointwise log likelihood data of the excluded
      data. As PyStan cannot call C++ functions and log_likelihood__i is already
      calculated *during* the simultion, instead of the value on which to evaluate
      the likelihood, ``log_likelihood__i`` expects a string so it can extract the
      corresponding data from the InferenceData object.
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code: def sel_observations(self, idx):
      """Select a subset of the observations in idata_orig.
  
      **Not implemented**: This method must be implemented on a model basis.
      It is documented here to show its format and call signature.
  
      Parameters
      ----------
      idx
          Indexes to separate from the rest of the observed data.
  
      Returns
      -------
      modified_observed_data : dict
          Dictionary containing both excluded and included data but properly divided
          in the different keys. Passed to ``data`` argument of ``model.sampling``.
      excluded_observed_data : str
          Variable name containing the pointwise log likelihood data of the excluded
          data. As PyStan cannot call C++ functions and log_likelihood__i is already
          calculated *during* the simultion, instead of the value on which to evaluate
          the likelihood, ``log_likelihood__i`` expects a string so it can extract the
          corresponding data from the InferenceData object.
      """
      raise NotImplementedError(
          "sel_observations must be implemented on a model basis"
      )
  
file_path: arviz/arviz/wrappers/wrap_stan.py
imports: from typing import Union
  from ..data import from_cmdstanpy, from_pystan
  from .base import SamplingWrapper
label_desc: Use image node_id 1 for calling the StanSamplingWrapper obj's underlying member method code with example usage: obj.sel_observations(idx) without return types