Although computing the Wasserstein distance is an apparently complex problem, it has been proven 24 that in the one-dimensional case, it can be easily and efficiently solved. Let M and N be the cumulative distribution functions of µ and ν, respectively. For the convenience of notation, let us introduce a set S = {s 1 , s 2 , . . . , s n } being a union of all the points on chemical shift axes of µ and ν. Without loss of generality, we can assume that s i are sorted so that s i < s i+1 . We will denote the intensities of spectra in consecutive points as µ(s i ) and ν(s i ) for i = 1, . . . , n. For those s i that were not originally present in spectrum µ, we will simply set µ(s i ) = 0 and, similarly, for those that were not present in ν, we will set ν(s i ) = 0.