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: Rank contributions line by line and build a reference dictionary to the prediction set.
  
  Parameters
  ----------
  contributions : pandas.DataFrame
      Local contributions to sort.
  x_init : pandas.DataFrame
      Prediction set.
  
  Returns
  -------
  pandas.DataFrame
      Local contributions sorted by decreasing absolute values.
  pandas.DataFrame
      Input features sorted by decreasing contributions absolute values.
  pandas.DataFrame
      Input features names sorted for each observation
      by decreasing contributions absolute values.
docstr_tok: ["Rank","contributions","line","by","line","and","build","a","reference","dictionary","to","the","prediction","set",".","Parameters","--","--","--","--","--","contributions",":","pandas.DataFrame","Local","contributions","to","sort",".","x_init",":","pandas.DataFrame","Prediction","set",".","Returns","--","--","--","-","pandas.DataFrame","Local","contributions","sorted","by","decreasing","absolute","values",".","pandas.DataFrame","Input","features","sorted","by","decreasing","contributions","absolute","values",".","pandas.DataFrame","Input","features","names","sorted","for","each","observation","by","decreasing","contributions","absolute","values","."]
code: def rank_contributions(self, contributions, x_init):
      """
      Rank contributions line by line and build a reference dictionary to the prediction set.
  
      Parameters
      ----------
      contributions : pandas.DataFrame
          Local contributions to sort.
      x_init : pandas.DataFrame
          Prediction set.
  
      Returns
      -------
      pandas.DataFrame
          Local contributions sorted by decreasing absolute values.
      pandas.DataFrame
          Input features sorted by decreasing contributions absolute values.
      pandas.DataFrame
          Input features names sorted for each observation
          by decreasing contributions absolute values.
      """
      return rank_contributions(contributions, x_init)
  
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 4 for calling the SmartState obj's underlying member method code with example usage: obj.rank_contributions(contributions, x_init) and returns: rank_contributions