约谈之后,OTA模式站上十字路口

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This step rapidly finds the optimal sequence of border points and shortcuts to get from your start cluster's periphery to your target cluster's periphery. It's incredibly fast because it's ignoring all the tiny roads within intermediate clusters.

The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:

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