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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 interpolate(self, df):
 """Interpolate this `FrequencySeries` to a new resolution. Parameters df : `float` desired frequency resolution of the interpolated `FrequencySeries`, in Hz Returns ------- out : `FrequencySeries` the interpolated version of the input `FrequencySeries` See Also -------- numpy.interp for the underlying 1-D linear interpolation scheme """

        f0 = self.f0.decompose().value
        N = (self.size - 1) * (self.df.decompose().value / df) + 1
        fsamples = numpy.arange(0, numpy.rint(N), dtype=self.dtype) * df + f0
        out = type(self)(numpy.interp(fsamples, self.frequencies.value,
                                      self.value))
        out.__array_finalize__(self)
        out.f0 = f0
        out.df = df
        return out