class_docstr: State pattern attached to SmartExplainer. This is the base class that only handles matrices
  of local contributions. The multi-class case is tackled in SmartMultiState.
class_docstr_tok: ["State","pattern","attached","to","SmartExplainer",".","This","is","the","base","class","that","only","handles","matrices","of","local","contributions",".","The","multi-class","case","is","tackled","in","SmartMultiState","."]
docstr: Check type of contributions and transform into pd.Dataframe if necessary
  
  Parameters
  ----------
  contributions : pandas.DataFrame or np.ndarray
      Local contributions
  x_init : pandas.DataFrame
      Prediction set.
  
  Returns
  -------
  pandas.DataFrame
      Local contributions on the original feature space (no encoding).
docstr_tok: ["Check","type","of","contributions","and","transform","into","pd.Dataframe","if","necessary","Parameters","--","--","--","--","--","contributions",":","pandas.DataFrame","or","np.ndarray","Local","contributions","x_init",":","pandas.DataFrame","Prediction","set",".","Returns","--","--","--","-","pandas.DataFrame","Local","contributions","on","the","original","feature","space","(","no","encoding",")","."]
code: def validate_contributions(self, contributions, x_init):
      """
      Check type of contributions and transform into pd.Dataframe if necessary
  
      Parameters
      ----------
      contributions : pandas.DataFrame or np.ndarray
          Local contributions
      x_init : pandas.DataFrame
          Prediction set.
  
      Returns
      -------
      pandas.DataFrame
          Local contributions on the original feature space (no encoding).
      """
      if not isinstance(contributions, (np.ndarray, pd.DataFrame)):
          raise ValueError(
              "Type of contributions must be pd.DataFrame or np.ndarray"
          )
      if isinstance(contributions, np.ndarray):
          return pd.DataFrame(
              contributions, columns=x_init.columns, index=x_init.index
          )
      else:
          return contributions
  
imports: import numpy
  import pandas
  from shapash.decomposition.contributions import inverse_transform_contributions
  from shapash.decomposition.contributions import rank_contributions, assign_contributions
  from shapash.manipulation.filters import hide_contributions
  from shapash.manipulation.filters import cap_contributions
  from shapash.manipulation.filters import sign_contributions
  from shapash.manipulation.filters import cutoff_contributions
  from shapash.manipulation.filters import combine_masks
  from shapash.manipulation.mask import compute_masked_contributions
  from shapash.manipulation.mask import init_mask
  from shapash.manipulation.summarize import summarize, compute_features_import, group_contributions
label_desc: Use image node_id 1 for calling the SmartState obj's underlying member method code with example usage: obj.validate_contributions(contributions, x_init) and returns: pd, contributions