Where the color indicates the normalized distance to the closest neighbor. For most of the points it's fine (1), but as there are 15 missing samples, some points are more distant from others. When one plots the generated samples over the number of iterations you get: The problem is: I doubt that it's possible to get all 100 samples in a reasonable time. so the desired result seems hardly obtainable. Please see this answer more as an encouragement than a solution.īy combining 1-D latin hypercube samples (LHS), you can make a full set of LHS for regular grid in higher order dimension. MATLAB LATIN HYPERCUBE SAMPLING CODE FULL For example, imagine 3X3 LHS (ie 2-D and 3 divisions). First, you just make 1-D LHS for regular grid. And then, combine the 1-D LHS to make 2-D LHS. LHS for 3-D can also be created using the same method(by combining 2-D LHS). Generally, the number of possible LHS is N x ((M-1)!)^(M-1). The following code shows LHS for 3-D and 10 divisions. MATLAB LATIN HYPERCUBE SAMPLING CODE CODE It takes 0.Conditioned Latin Hypercube Sampling (cLHS) is a type of stratified random sampling that accurately represents the variability of environmental covariates in feature space.
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