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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 asd(self, fftlength=None, overlap=None, window='hann', method=DEFAULT_FFT_METHOD, **kwargs):
 """Calculate the ASD `FrequencySeries` of this `TimeSeries` Parameters fftlength : `float` number of seconds in single FFT, defaults to a single FFT covering the full duration overlap : `float`, optional number of seconds of overlap between FFTs, defaults to the recommended overlap for the given window (if given), or 0 window : `str`, `numpy.ndarray`, optional window function to apply to timeseries prior to FFT, see :func:`scipy.signal.get_window` for details on acceptable formats method : `str`, optional FFT-averaging method, see *Notes* for more details Returns ------- psd : `~gwpy.frequencyseries.FrequencySeries` a data series containing the PSD. See also -------- TimeSeries.psd Notes ----- The accepted ``method`` arguments are: - ``'bartlett'`` : a mean average of non-overlapping periodograms - ``'median'`` : a median average of overlapping periodograms - ``'welch'`` : a mean average of overlapping periodograms """

        return self.psd(method=method, fftlength=fftlength, overlap=overlap,
                        window=window, **kwargs) ** (1/2.)