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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def values(self, stilde, template, psd, snrv, snr_norm, bchisq, bchisq_dof, indices):
 """ Calculate sine-Gaussian chisq Parameters stilde: pycbc.types.Frequencyseries The overwhitened strain template: pycbc.types.Frequencyseries The waveform template being analyzed psd: pycbc.types.Frequencyseries The power spectral density of the data snrv: numpy.ndarray The peak unnormalized complex SNR values snr_norm: float The normalization factor for the snr bchisq: numpy.ndarray The Bruce Allen power chisq values for these triggers bchisq_dof: numpy.ndarray The degrees of freedom of the Bruce chisq indics: numpy.ndarray The indices of the snr peaks. Returns ------- chisq: Array Chisq values, one for each sample index """

        if not self.do:
            return None

        if template.params.template_hash not in self.params:
            return numpy.ones(len(snrv))
        values = self.params[template.params.template_hash].split(',')

        # Get the chisq bins to use as the frequency reference point
        bins = self.cached_chisq_bins(template, psd)

        # This is implemented slowly, so let's not call it often, OK?
        chisq = numpy.ones(len(snrv))
        for i, snrvi in enumerate(snrv):
            #Skip if newsnr too low
            snr = abs(snrvi * snr_norm)
            nsnr = ranking.newsnr(snr, bchisq[i] / bchisq_dof[i])
            if nsnr < self.snr_threshold:
                continue

            N = (len(template) - 1) * 2
            dt = 1.0 / (N * template.delta_f)
            kmin = int(template.f_lower / psd.delta_f)
            time = float(template.epoch) + dt * indices[i]
            # Shift the time of interest to be centered on 0
            stilde_shift = apply_fseries_time_shift(stilde, -time)

            # Only apply the sine-Gaussian in a +-50 Hz range around the
            # central frequency
            qwindow = 50
            chisq[i] = 0

            # Estimate the maximum frequency up to which the waveform has
            # power by approximating power per frequency
            # as constant over the last 2 chisq bins. We cannot use the final
            # chisq bin edge as it does not have to be where the waveform
            # terminates.
            fstep = (bins[-2] - bins[-3])
            fpeak = (bins[-2] + fstep) * template.delta_f

            # This is 90% of the Nyquist frequency of the data
            # This allows us to avoid issues near Nyquist due to resample
            # Filtering
            fstop = len(stilde) * stilde.delta_f * 0.9

            dof = 0
            # Calculate the sum of SNR^2 for the sine-Gaussians specified
            for descr in values:
                # Get the q and frequency offset from the descriptor
                q, offset = descr.split('-')
                q, offset = float(q), float(offset)
                fcen = fpeak + offset
                flow = max(kmin * template.delta_f, fcen - qwindow)
                fhigh = fcen + qwindow

                # If any sine-gaussian tile has an upper frequency near
                # nyquist return 1 instead.
                if fhigh > fstop:
                    return numpy.ones(len(snrv))

                kmin = int(flow / template.delta_f)
                kmax = int(fhigh / template.delta_f)

                #Calculate sine-gaussian tile
                gtem = sinegauss.fd_sine_gaussian(1.0, q, fcen, flow,
                                      len(template) * template.delta_f,
                                      template.delta_f).astype(numpy.complex64)
                gsigma = sigma(gtem, psd=psd,
                                     low_frequency_cutoff=flow,
                                     high_frequency_cutoff=fhigh)
                #Calculate the SNR of the tile
                gsnr = (gtem[kmin:kmax] * stilde_shift[kmin:kmax]).sum()
                gsnr *= 4.0 * gtem.delta_f / gsigma
                chisq[i] += abs(gsnr)**2.0
                dof += 2
            if dof == 0:
                chisq[i] = 1
            else:
                chisq[i] /= dof
        return chisq