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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 transform(self, fseries, **kwargs):
 """Compute the time-frequency plane at fixed Q with the most significant tile Parameters fseries : `~gwpy.timeseries.FrequencySeries` the complex FFT of a time-series data set **kwargs other keyword arguments to pass to `QPlane.transform` Returns ------- out : `QGram` signal energies over the time-frequency plane containing the most significant tile N : `int` estimated number of statistically independent tiles See Also -------- QPlane.transform compute the Q-transform over a single time-frequency plane """

        weight = 1 + numpy.log10(self.qrange[1]/self.qrange[0]) / numpy.sqrt(2)
        nind, nplanes, peak, result = (0, 0, 0, None)
        # identify the plane with the loudest tile
        for plane in self:
            nplanes += 1
            nind += sum([1 + row.ntiles * row.deltam for row in plane])
            result = plane.transform(fseries, **kwargs)
            if result.peak['energy'] > peak:
                out = result
                peak = out.peak['energy']
        return (out, nind * weight / nplanes)