def METHOD_NAME(self):
    ### use a sin-gaussian as a signal
    sigt = TimeSeries(self.sig2, self.del_t)
    sig_tilde = make_frequency_series(sigt)
    del_f = sig_tilde.get_delta_f()
    psd = FrequencySeries(self.Psd, del_f)
    flow = self.low_frequency_cutoff
    with _context:
        hautocor, hacorfr, hnrm = matched_filter_core(self.htilde, self.htilde, psd=psd, \
                    low_frequency_cutoff=flow, high_frequency_cutoff=self.fmax)
        hautocor = hautocor * float(np.real(1./hautocor[0]))
        snr, cor, nrm = matched_filter_core(self.htilde, sig_tilde, psd=psd, \
                    low_frequency_cutoff=flow, high_frequency_cutoff=self.fmax)
    hacor = Array(hautocor.real(), copy=True)
    indx = np.array([301440, 301450, 301460])
    snr = snr*nrm
    with _context:
       dof, achisq, indices= \
           autochisq_from_precomputed(snr, snr, hacor, indx, stride=3,
                                      num_points=20)
    obt_snr = abs(snr[indices[1]])
    obt_ach = achisq[1]
    self.assertTrue(obt_snr > 12.0 and obt_snr < 15.0)
    self.assertTrue(obt_ach > 6.8e3)
    self.assertTrue(achisq[0] > 6.8e3)
    self.assertTrue(achisq[2] > 6.8e3)