def _tcorrel(self, nstep=<NUM_LIT:100>, **kwargs):
t = self.array[<NUM_LIT:0>,::nstep]<EOL>r = gromacs.collections.Collection([numkit.timeseries.tcorrel(t, Y, nstep=<NUM_LIT:1>, **kwargs) for Y in self.array[<NUM_LIT:1>:,::nstep]])<EOL>return r<EOL>
Correlation "time" of data.

        The 0-th column of the data is interpreted as a time and the
        decay of the data is computed from the autocorrelation
        function (using FFT).

        .. SeeAlso:: :func:`numkit.timeseries.tcorrel`