smp.smooth
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| smp.smooth [2010/10/27 16:30] – typo jochen | smp.smooth [2010/10/27 16:32] – jochen | ||
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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). | ||
smp.smooth.txt · Last modified: 2010/10/28 00:09 by jochen