docs: def add_continuous_annotations(self, x, y, colourName='Purple', colour='#c832ff', name='', view=None, vscale=None, presentationName=None):
          """
          add a continous annotation layer
  
          Args:
            x (float iterable): temporal indices of the dataset
            y (float iterable): values of the dataset
  
          Kwargs:
            view (<DOM Element: view>): environment view used to display the spectrogram, if set to None, a new view is created
  
          Returns:
            <DOM Element: view>: the view used to store the spectrogram
  
          """
          
          model = self.data.appendChild(self.doc.createElement('model'))
          imodel = self.nbdata
          
          for atname, atval in [('id', imodel + 1),
                                ('dataset', imodel),
                                ('name', name),
                                ('sampleRate', self.samplerate),
                                ('start', int(min(x) * self.samplerate)),
                                ('end', int(max(x) * self.samplerate)),
                                ('type', 'sparse'),
                                ('dimensions', '2'),
                                ('resolution', '1'),
                                ('notifyOnAdd', 'true'),
                                ('minimum', min(y)),
                                ('maximum', max(y)),
                                ('units', '')
                                ]:
              model.setAttribute(atname, str(atval))
  
          # dataset = self.data.appendChild(self.doc.createElement('dataset'))
          # dataset.setAttribute('id', str(imodel))
          # dataset.setAttribute('dimensions', '2')
          # self.nbdata += 2
          
          # datasetnode = SVDataset2D(self.doc, str(imodel), self.samplerate)
          # datasetnode.set_data_from_iterable(map(int, np.array(x) * self.samplerate), y)
          # data = dataset.appendChild(datasetnode)
          dataset = self.data.appendChild(SVDataset2D(self.doc, str(imodel), self.samplerate))
          dataset.set_data_from_iterable(map(int, np.array(x) * self.samplerate), y)
          self.nbdata += 2
  
          ###### add layers
          valruler = self.__add_time_ruler()
          vallayer = self.__add_val_layer(imodel + 1)
          vallayer.setAttribute('colourName', colourName)
          vallayer.setAttribute('colour', colour)
          if presentationName:
              vallayer.setAttribute('presentationName', presentationName)
          if vscale is None:
              vallayer.setAttribute('verticalScale', '0')
              vallayer.setAttribute('scaleMinimum', str(min(y)))
              vallayer.setAttribute('scaleMaximum', str(max(y)))
          else:
              vallayer.setAttribute('verticalScale', '0')
              vallayer.setAttribute('scaleMinimum', str(vscale[0]))
              vallayer.setAttribute('scaleMaximum', str(vscale[1]))
  
          if view is None:
              view = self.__add_view()
          self.__add_layer_reference(view, valruler)
          self.__add_layer_reference(view, vallayer)
          return view