Percolation Theory is a problem under the Graph Theory researches.
In statistical physics and mathematics, percolation theory describes the behavior of a network when nodes or links are removed.
In this project we have a NxN grid initialized with open sites(white blocks), closed sites(black blocks), and one random open site with water in it(coloured blue).
In every frame time, a random closed site is opened and program checks whether water percolates towards bottom of the grid. <br / >
doesPercolate() function establish this process.
If it returns true, program (open site numbers / total site numbers) is pushed to a threshold array.
By repeating this computation experiment T times and averaging the results, we obtain a more accurate estimate of the percolation threshold. Let xt be the fraction of open sites in computational experiment t. The sample mean x¯¯¯
provides an estimate of the Percolation Threshold; the sample standard deviation s; measures the sharpness of the threshold.
Finally we can find the Confidence Interval and plot the threshold function as Sigmoid Function .
In addition to this process, as we plot the sigmoid function, this function can be used to make prediction if grid does percolate or not by logistic regression.