\myprogram{{compute\_tau.py}}
          {compute the Kendall's rank correlation coefficient $\tau_b$
          between two rankings.}  {$<$file1$>$ $<$file2$>$}

\mydescription{Compute the Kendall's rank correlation coefficient
           $\tau_b$ between two rankings provided in the input
          files \textit{file1} and \textit{file2}. Each input file
          contains a list of lines, where the n-th line contains the
          value of rank of the n-th node. For instance, \textit{file1}
          and \textit{file2} might contain the ranks of nodes induced
          by the degree sequences of two distinct layers of a
          multiplex.

          However, the program is pretty general and can be used to
          compute the Kendall's rank correlation coefficient between
          any generic pair of rankings.

          N.B.: This implementation takes properly into account rank
          ties.}


\myreturn{The program prints on \texttt{stdout} the value of the
          Kendall's rank correlation coefficient $\tau_b$ between the
          two rankings provided as input. }

\myreference{\refcorrelations

  \refgrowth

  \refnonlinear
}