added a uniform distribution over a collection of objects #19
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rejuvyesh
requested changes
Jun 3, 2019
src/distributions/uniform.jl
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| function pdf(d::Uniform, s) | ||
| d._set = something(d._set, Set(d.collection)) | ||
| if s in d._set | ||
| return 1/length(d.collection) |
src/distributions/uniform.jl
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| Uniform(c) = Uniform{typeof(c), eltype(c)}(c, nothing) | ||
| Uniform(c::Set) = Uniform{typeof(c), eltype(c)}(c, c) | ||
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| rand(rng::AbstractRNG, d::Uniform) = rand(rng, d.collection) |
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Unclear about the rationale here. If you are allowing for non-sets and converting it into sets and giving them equal weights, then how can you sample uniformly from the collection which might have multiple instances of the same and therefore higher weight?
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Yeah, thanks, I need to redesign this.
Pull Request Test Coverage Report for Build 87
💛 - Coveralls |
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@rejuvyesh do you think it's good now? |
rejuvyesh
requested changes
Jun 6, 2019
src/distributions/uniform.jl
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| # mean(d::Uniform) = mean(d.set) | ||
| # mode(d::Uniform) = mode(d.set) | ||
| # | ||
| # function weighted_iterator(d::Uniform) |
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One question is naming. This clashes with
Distributions.Uniform. Another option would beUniformCat. I thinkUniformis better, but could be persuaded otherwise.