smp.smooth

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smp.smooth [2010/10/27 18:32] jochen |
smp.smooth [2010/10/28 02:09] (current) jochen updated the algorithm description to reflect an update in code |
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In other words, the central kernel weight remains with the old value and the remainder to 1 is split across the next neighbors according to the kernel weight given by their distance to the vertex. This approach takes both the neighborhood and the distance of vertices into account. | In other words, the central kernel weight remains with the old value and the remainder to 1 is split across the next neighbors according to the kernel weight given by their distance to the vertex. This approach takes both the neighborhood and the distance of vertices into account. | ||

- | After the smoothing is performed, the mean of the map is adjusted to reflect the original mean value (to counter rounding errors if a high number of iterations was used), **if and only if** the standard deviation is not smaller than 0.1 times the mean (for most skewed maps this is the case). | + | After the smoothing is performed, the mean of the map is adjusted to reflect the original mean value (to counter rounding errors if a high number of iterations was used), **if and only if** the standard deviation is not smaller than the sum (for most skewed maps this is the case). |

smp.smooth.txt ยท Last modified: 2010/10/28 02:09 by jochen