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

def bins(self,bins=None,units=None,conversion_function=convert_time,resolution=None,scale=None):
        """
            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
        """
        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)