Update README.md
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If more than 10⁵ lines are specified the autocorrelation function won't be computed, as it would take too long.
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The `gaussian.dat` dataset has been generated with numpy, as a proof of concept. It represents a normally distributed set of 5x10⁵ elements with `std = 0.05`. One will notice that the estimate on the error of the central value is greatly improved by all resampling methods.
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energy.dat is an autocorrelated data set, with autocorrelation time of roughly 200. It is useful to see the use of blocking on this dataset as a convenient method to estimate the autocorrelation time (compare the elapsed time on the different methods).
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In the plaquette.dat file there is a small data set (just 1000 samples) and it shows the strenght of using resampling methods to better estimate the error on the central value as opposed to the standard deviation.
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