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src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/utils/miris.py   xbob.thesis.elshafey2014(Download)
  ubm.acc_statistics(sample, gs)
  ux = numpy.zeros((4,), numpy.float64)
  jfamachine.estimate_ux(gs, ux)
 
  figure = mpl.figure()

src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/tools/JFA.py   xbob.thesis.elshafey2014(Download)
  def _project_jfa(self, projected_ubm):
    projected_jfa = numpy.ndarray(shape=(self.m_ubm.dim_c*self.m_ubm.dim_d,), dtype=numpy.float64)
    model = bob.machine.JFAMachine(self.m_jfabase)
    model.estimate_ux(projected_ubm, projected_jfa)
    return projected_jfa