Hoshen–Kopelman algorithm: Difference between revisions

Revision as of 12:50, 20 October 2023

Revision as of 13:23, 2 March 2025

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</gallery>||<gallery>

Occupied_Grids_P_%3D_0.64.png | {{center|'''Figure (b)'''}}

</gallery>|| Consider <code>5x5</code> grids in figurefigures (a) and (b).<br /> In figure (a), the probability of occupancy is <code>p = 6/25 = 0.24</code>.<br /> In figure (b), the probability of occupancy is <code>p = 16/25 = 0.64</code>.

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== Example ==

Consider the following example. The dark cells in the grid in <code>figureFigure (ac)</code> represent that they are occupied and the white ones are empty. So by running H–K algorithm on this input we would get the output as shown in <code>figureFigure (bd)</code> with all the clusters labeled.

The algorithm processes the input grid, cell by cell, as follows: Let's say that grid is a two-dimensional array.

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| <gallery>

H-K algorithm Input.png | {{center|'''Figure (ac)'''}}

</gallery>||<gallery>

H-K algorithm output.png | {{center|'''Figure (bd)'''}}

</gallery>|| Consider <code>6x6</code> grids in figure (ac) and (bd).<br /> Figure (ac), This is the input to the Hoshen–Kopelman algorithm.<br /> Figure (b), This is the output of the algorithm with all the clusters labeled.

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