class_docstr: Implements the log-odds-ratio with an uninformative dirichlet prior from
          Monroe, B. L., Colaresi, M. P., & Quinn, K. M. (2008). Fightin' words: Lexical feature selection and evaluation for identifying the content of political conflict. Political Analysis, 16(4), 372–403.
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docstr: Parameters
  ----------
  X : np.array
          Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
          positive class, while X[:,1] is the negative class. None by default
  
  Returns
  -------
  np.array of p-values
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code: def get_p_vals(self, X):
      """
      Parameters
      ----------
      X : np.array
              Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
              positive class, while X[:,1] is the negative class. None by default
  
      Returns
      -------
      np.array of p-values
  
      """
      # Eqs 19-22
      return z_to_p_val(self.get_zeta_i_j(X))
  
file_path: scattertext/scattertext/termsignificance/LogOddsRatioUninformativeDirichletPrior.py
imports: import numpy
  from scipy.special import ndtr
  from scattertext.termranking import AbsoluteFrequencyRanker
  from scattertext.termsignificance.TermSignificance import TermSignificance
label_desc: Use image node_id 3 for calling the LogOddsRatioUninformativeDirichletPrior obj's underlying member method code with example usage: obj.get_p_vals(X) and returns: z_to_p_val