code: def normalize(self, axis):
          
          axis = self.get_axis_number(axis)
          sum_along_axis = np.sum(self.histogram, axis=axis)
          # Don't do anything for subspaces without any entries -- this avoids nans everywhere
          sum_along_axis[sum_along_axis == 0] = 1
          hist = self.histogram / sum_along_axis[self._simsalabim_slice(axis)]
          return Histdd.from_histogram(hist,
                                       bin_edges=self.bin_edges,
                                       axis_names=self.axis_names)
docs: Returns new histogram where all values along axis (in one bin of the other axes) sum to 1