1045860141

Committed 19 Jul 2021 - 16:14 coverage: 60.0% (-17.8%) from 77.778%

Build Type

github

Committed by GitHub

Commit Message

Merge 226539b8a into cdc031c57

Pull Request Pull Request #8: Loosen MvNormal and add StatsBase inheritance

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1 of 7 new or added lines in 2 files covered. (14.29%)

12 of 20 relevant lines covered (60.0%)

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66.67

/src/KLDivergences.jl

module KLDivergences

using Distributions: StatsBase
using Distributions
using LinearAlgebra
using PDMats
using Distances
using SpecialFunctions
using StatsBase: StatsBase, kldivergence


export KL, kldivergence

"""
    KL(p::Distribution, q::Distribution) -> T
    KL(p::Distribution, q::Distribution, n_samples::Int) -> T

Return the KL divergence of  KL(p||q), either by sampling or analytically
"""
KL

StatsBase.kldivergence(p::Sampleable, q::Sampleable) = KL(p, q)

KLbase(p, q, x) = logpdf(p, x) - logpdf(q, x)

## Generic fallback for multivariate Distributions
function KL(p::UnivariateDistribution, q::UnivariateDistribution, n_samples = 1_000)
    return mean(x->KLbase(p, q, x), rand(p, n_samples))
end

function KL(p::MultivariateDistribution, q::MultivariateDistribution, n_samples = 1_000)
    length(p) == length(q) ||
        throw(DimensionMismatch("Dimensions of p and q do not match"))
    return mean(x->KLbase(p, q, x), eachcol(rand(p, n_samples)))
end

function symmetricKL(p, q)
    return KL(p, q) + KL(q, p)
end

include("univariate.jl")
include("multivariate.jl")

end

1	module KLDivergences
2
3	using Distributions: StatsBase
4	using Distributions
5	using LinearAlgebra
6	using PDMats
7	using Distances
8	using SpecialFunctions
9	using StatsBase: StatsBase, kldivergence
10
11
12	export KL, kldivergence
13
14	"""
15	KL(p::Distribution, q::Distribution) -> T
16	KL(p::Distribution, q::Distribution, n_samples::Int) -> T
17
18	Return the KL divergence of KL(p\|\|q), either by sampling or analytically
19	"""
20	KL
21
NEW 22	StatsBase.kldivergence(p::Sampleable, q::Sampleable) = KL(p, q)	!
23
24	KLbase(p, q, x) = logpdf(p, x) - logpdf(q, x)	5,412,048×
25
26	## Generic fallback for multivariate Distributions
27	function KL(p::UnivariateDistribution, q::UnivariateDistribution, n_samples = 1_000)
28	return mean(x->KLbase(p, q, x), rand(p, n_samples))	3,612,162×
29	end
30
31	function KL(p::MultivariateDistribution, q::MultivariateDistribution, n_samples = 1_000)
32	length(p) == length(q) \|\|	12×
33	throw(DimensionMismatch("Dimensions of p and q do not match"))
34	return mean(x->KLbase(p, q, x), eachcol(rand(p, n_samples)))	900,009×
35	end
36
37	function symmetricKL(p, q)
38	return KL(p, q) + KL(q, p)	!
39	end
40
41	include("univariate.jl")
42	include("multivariate.jl")
43
44	end

theogf / KLDivergences.jl / 1045860141

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