code: def from_netcdf(
      filename, *, engine="h5netcdf", group_kwargs=None, regex=False
  ):
      """Load netcdf file back into an arviz.InferenceData.
  
      Parameters
      ----------
      filename : str
          name or path of the file to load trace
      engine : {"h5netcdf", "netcdf4"}, default "h5netcdf"
          Library used to read the netcdf file.
      group_kwargs : dict of {str: dict}
          Keyword arguments to be passed into each call of :func:`xarray.open_dataset`.
          The keys of the higher level should be group names or regex matching group
          names, the inner dicts re passed to ``open_dataset``.
          This feature is currently experimental
      regex : str
          Specifies where regex search should be used to extend the keyword arguments.
  
      Returns
      -------
          InferenceData object
  
      Notes
      -----
      By default, the datasets of the InferenceData object will be lazily loaded instead
      of loaded into memory. This behaviour is regulated by the value of
      ``az.rcParams["data.load"]``.
      """
      if group_kwargs is None:
          group_kwargs = {}
      return InferenceData.from_netcdf(
          filename,
          engine=engine,
          group_kwargs=group_kwargs,
          regex=regex,
      )
  
imports: from .converters import convert_to_inference_data
  from .inference_data import InferenceData
label_desc: Use image node_id 1 for calling a global function with example usage: from_netcdf(filename) and returns: InferenceData