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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 coherence_spectrogram(self, other, stride, fftlength=None, overlap=None, window='hann', nproc=1):
 """Calculate the coherence spectrogram between this `TimeSeries` and other. Parameters other : `TimeSeries` the second `TimeSeries` in this CSD calculation stride : `float` number of seconds in single PSD (column of spectrogram) fftlength : `float` number of seconds in single FFT 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 nproc : `int` number of parallel processes to use when calculating individual coherence spectra. Returns ------- spectrogram : `~gwpy.spectrogram.Spectrogram` time-frequency coherence spectrogram as generated from the input time-series. """

        from ..spectrogram.coherence import from_timeseries
        return from_timeseries(self, other, stride, fftlength=fftlength,
                               overlap=overlap, window=window,
                               nproc=nproc)