code: def bins(self,bins=None,units=None,conversion_function=convert_time,resolution=None,scale=None):
          
          if scale in ['log'] or (scale is None and self.scale in ['log']):
              return self.logspace_bins(bins=bins,units=units,conversion_function=conversion_function,resolution=resolution)
          #if scale in ['lin','linear'] or (scale is None and self.scale in ['lin','linear']):
          return self.linspace_bins(bins=bins,units=units,conversion_function=conversion_function,resolution=resolution)
docs: Computes adequat binning for the dimension (between the values).
  
                  bins: number of bins or None
                  units: str or None
                  conversion_function: function to convert units to other units
                  resolution: step size or None
                  scale: 'lin','log' or None
                      a spike container can also use 'unique', but not the LabelDimension itself!
                      if the LabelDimension.scale is 'unique', .bins() will return a linear spacing