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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 spectrogram(self, x, n_fft=256, step=None, fs=1., window='hann', color_scale='log', cmap='cubehelix', clim='auto'):
 """Calculate and show a spectrogram Parameters x : array-like 1D signal to operate on. ``If len(x) < n_fft``, x will be zero-padded to length ``n_fft``. n_fft : int Number of FFT points. Much faster for powers of two. step : int | None Step size between calculations. If None, ``n_fft // 2`` will be used. fs : float The sample rate of the data. window : str | None Window function to use. Can be ``'hann'`` for Hann window, or None for no windowing. color_scale : {'linear', 'log'} Scale to apply to the result of the STFT. ``'log'`` will use ``10 * log10(power)``. cmap : str Colormap name. clim : str | tuple Colormap limits. Should be ``'auto'`` or a two-element tuple of min and max values. Returns ------- spec : instance of Spectrogram The spectrogram. See also -------- Image """

        self._configure_2d()
        # XXX once we have axes, we should use "fft_freqs", too
        spec = scene.Spectrogram(x, n_fft, step, fs, window,
                                 color_scale, cmap, clim)
        self.view.add(spec)
        self.view.camera.set_range()
        return spec