code: def highpass(self, frequency, gpass=2, gstop=30, fstop=None, type='iir',
                   filtfilt=True, **kwargs):
          
          # design filter
          filt = filter_design.highpass(frequency, self.sample_rate,
                                        fstop=fstop, gpass=gpass, gstop=gstop,
                                        analog=False, type=type, **kwargs)
          # apply filter
          return self.filter(*filt, filtfilt=filtfilt)
docs: Filter this `TimeSeries` with a high-pass filter.
  
          Parameters
          ----------
          frequency : `float`
              high-pass corner frequency
  
          gpass : `float`
              the maximum loss in the passband (dB).
  
          gstop : `float`
              the minimum attenuation in the stopband (dB).
  
          fstop : `float`
              stop-band edge frequency, defaults to `frequency * 1.5`
  
          type : `str`
              the filter type, either ``'iir'`` or ``'fir'``
  
          **kwargs
              other keyword arguments are passed to
              :func:`gwpy.signal.filter_design.highpass`
  
          Returns
          -------
          hpseries : `TimeSeries`
              a high-passed version of the input `TimeSeries`
  
          See Also
          --------
          gwpy.signal.filter_design.highpass
              for details on the filter design
          TimeSeries.filter
              for details on how the filter is applied
  
          .. note::
  
             When using `scipy < 0.16.0` some higher-order filters may be
             unstable. With `scipy >= 0.16.0` higher-order filters are
             decomposed into second-order-sections, and so are much more stable.