class_docstr: Class to compute the empirical null normal fit to the data.
  
  The data which is used to estimate the FDR, assuming a Gaussian null
  from Schwartzmann et al., NeuroImage 44 (2009) 71--82
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docstr: Initialize an empirical null normal object.
  
  Parameters
  -----------
  x : 1D ndarray
      The data used to estimate the empirical null.
docstr_tok: ["Initialize","an","empirical","null","normal","object",".","Parameters","--","--","--","--","--","-","x",":","1D","ndarray","The","data","used","to","estimate","the","empirical","null","."]
code: def __init__(self, x):
      """Initialize an empirical null normal object.
  
      Parameters
      -----------
      x : 1D ndarray
          The data used to estimate the empirical null.
      """
      x = np.reshape(x, (-1))
      self.x = np.sort(x)
      self.n = np.size(x)
      self.learned = 0
  
file_path: nipy/nipy/algorithms/statistics/empirical_pvalue.py
imports: import numpy
  import scipy.stats
  from numpy.linalg import pinv
label_desc: Use image node_id 1 to create a new NormalEmpiricalNull object  with example: obj = NormalEmpiricalNull(x)