docstr: Return the decision statistic associated with the test of the
  null hypothesis: (H0) 'contrast equals baseline'
docstr_tok: ["Return","the","decision","statistic","associated","with","the","test","of","the","null","hypothesis",":","(","H0",")","'contrast","equals","baseline","'"]
code: def stat(self, baseline=0.0):
      """
      Return the decision statistic associated with the test of the
      null hypothesis: (H0) 'contrast equals baseline'
      """
      self._baseline = baseline
  
      # Case: one-dimensional contrast ==> t or t**2
      if self.dim == 1:
          # avoids division by zero
          t = (self.effect - baseline) / np.sqrt(
              np.maximum(self.variance, self._tiny)
          )
          if self.type == "F":
              t = t**2
      # Case: F contrast
      elif self.type == "F":
          # F = |t|^2/q ,  |t|^2 = e^t v-1 e
          t = (
              mahalanobis(
                  self.effect - baseline,
                  np.maximum(self.variance, self._tiny),
              )
              / self.dim
          )
      # Case: tmin (conjunctions)
      elif self.type == "tmin":
          vdiag = self.variance.reshape(
              [self.dim**2] + list(self.variance.shape[2:])
          )[:: self.dim + 1]
          t = (self.effect - baseline) / np.sqrt(
              np.maximum(vdiag, self._tiny)
          )
          t = t.min(0)
  
      # Unknown stat
      else:
          raise ValueError("Unknown statistic type")
      self._stat = t
      return t
  
imports: import numpy
  import scipy.stats
  from nipy.algorithms.statistics.utils import z_score
  from ..utils import mahalanobis
  from .None import kalman
label_desc: Use image node_id 3 for calling the contrast obj's underlying member method code with example usage: obj.stat(baseline) and returns: t