class_docstr: Encapsulate Dictionary specific logic.
class_docstr_tok: ["Encapsulate","Dictionary","specific","logic","."]
code: def __init__(
      self,
      *,
      posterior=None,
      posterior_predictive=None,
      predictions=None,
      sample_stats=None,
      log_likelihood=None,
      prior=None,
      prior_predictive=None,
      sample_stats_prior=None,
      observed_data=None,
      constant_data=None,
      predictions_constant_data=None,
      warmup_posterior=None,
      warmup_posterior_predictive=None,
      warmup_predictions=None,
      warmup_log_likelihood=None,
      warmup_sample_stats=None,
      save_warmup=None,
      index_origin=None,
      coords=None,
      dims=None,
      pred_dims=None,
      pred_coords=None,
      attrs=None,
      **kwargs,
  ):
      self.posterior = posterior
      self.posterior_predictive = posterior_predictive
      self.predictions = predictions
      self.sample_stats = sample_stats
      self.log_likelihood = log_likelihood
      self.prior = prior
      self.prior_predictive = prior_predictive
      self.sample_stats_prior = sample_stats_prior
      self.observed_data = observed_data
      self.constant_data = constant_data
      self.predictions_constant_data = predictions_constant_data
      self.warmup_posterior = warmup_posterior
      self.warmup_posterior_predictive = warmup_posterior_predictive
      self.warmup_predictions = warmup_predictions
      self.warmup_log_likelihood = warmup_log_likelihood
      self.warmup_sample_stats = warmup_sample_stats
      self.save_warmup = (
          rcParams["data.save_warmup"]
          if save_warmup is None
          else save_warmup
      )
      self.coords = (
          coords
          if pred_coords is None
          else pred_coords
          if coords is None
          else {**coords, **pred_coords}
      )
      self.index_origin = index_origin
      self.coords = coords
      self.dims = dims
      self.pred_dims = dims if pred_dims is None else pred_dims
      self.attrs = {} if attrs is None else attrs
      self.attrs.pop("created_at", None)
      self.attrs.pop("arviz_version", None)
      self._kwargs = kwargs
  
imports: import warnings
  from typing import Optional
  from ..rcparams import rcParams
  from .base import dict_to_dataset, requires
  from .inference_data import WARMUP_TAG, InferenceData
label_desc: Use image node_id 1 to create a new DictConverter object  with example: obj = DictConverter()