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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换句话说，这封信确认的是“增长正在发生”，但尚未证明“利润已经稳定”。规模叙事正在加速，商业模型仍在验证期。
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time.sleep(2 ** attempt) # 指数退避