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: Initialize a True mask for the dataset.
  
  Parameters
  ----------
  s_contrib: pd.DataFrame
      Matrix with both positive and negative values
  value: bool
      Value used for initialize the mask
  
  Returns
  -------
  pd.Dataframe
      mask initialized
docstr_tok: ["Initialize","a","True","mask","for","the","dataset",".","Parameters","--","--","--","--","--","s_contrib",":","pd.DataFrame","Matrix","with","both","positive","and","negative","values","value",":","bool","Value","used","for","initialize","the","mask","Returns","--","--","--","-","pd.Dataframe","mask","initialized"]
code: def init_mask(self, s_contrib, value=True):
      """
      Initialize a True mask for the dataset.
  
      Parameters
      ----------
      s_contrib: pd.DataFrame
          Matrix with both positive and negative values
      value: bool
          Value used for initialize the mask
  
      Returns
      -------
      pd.Dataframe
          mask initialized
      """
      return init_mask(s_contrib, value)
  
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 12 for calling the SmartState obj's underlying member method code with example usage: obj.init_mask(s_contrib, value) and returns: init_mask