Sigmoid clustering

Simple idea:

function SigmoidCluster1d(samples::Vector, k_max::Int)
	sort!(samples)
	ret = Vector{Vector{Float64}}(undef, k_max)
	for k in 1:k_max
		quant_idxs = get_k_quantile_idxs(samples, k)
		# Group the samples by index
		groups = [samples[idx_range] for idx_range in quant_idxs]
		# Get centers
		ret[k] = [mean(group) for group in groups]
	end
	return ret
end
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