On the latest version of the documentation, the follo

The vectorised version left us with <a class="commit-link" href="https://github.com/Ju

Missing docstring for loglikelihood about distributions.jl HOT 3 OPEN

cgarling commented on June 11, 2024

Missing docstring for loglikelihood

from distributions.jl.

Comments (3)

mschauer commented on June 11, 2024

The vectorised version left us with d6985ad#diff-c185a88dade2ce18f68ff0130b5626734ed3cdb341bf5765dbb008fd8a6d91a0

loglikelihood(::UnivariateDistribution, ::Real) should have a docstring though, did it get lost there?

from distributions.jl.

cgarling commented on June 11, 2024

I am unfortunately not a git wizard but it looks to me like the relevant method definition is

Distributions.jl/src/univariates.jl

Lines 329 to 330 in f33af97

 # loglikelihood for `Real` 

 Base.@propagate_inbounds loglikelihood(d::UnivariateDistribution, x::Real) = logpdf(d, x)

for which I do not see a docstring.

from distributions.jl.

cgarling commented on June 11, 2024

P.S. It looks like pdf(::MultivariateDistribution, ::AbstractArray) and logpdf(::MultivariateDistribution, ::AbstractArray) are also included in the documentation but do not exist. I don't use the multivariate models much so I'm not sure what changed, but if I had to guess maybe these are the correct methods now?

Distributions.jl/src/common.jl

Lines 198 to 234 in f33af97

 """ 

  pdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N} 

 Evaluate the probability density function of `d` at `x`. 

 This function checks if the size of `x` is compatible with distribution `d`. This check can 

 be disabled by using `@inbounds`. 

 # Implementation 

 Instead of `pdf` one should implement `_pdf(d, x)` which does not have to check the size of 

 `x`. However, since the default definition of `pdf(d, x)` falls back to `logpdf(d, x)` 

 usually it is sufficient to implement `logpdf`. 

 See also: [`logpdf`](@ref). 

 """ 

 @inline function pdf( 

 d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M} 

 ) where {N,M} 

 if M == N 

 @boundscheck begin 

 size(x) == size(d) || 

 throw(DimensionMismatch("inconsistent array dimensions")) 

 end 

 return _pdf(d, x) 

 else 

 @boundscheck begin 

 M > N || 

 throw(DimensionMismatch( 

 "number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)" 

 )) 

 ntuple(i -> size(x, i), Val(N)) == size(d) || 

 throw(DimensionMismatch("inconsistent array dimensions")) 

 end 

 return @inbounds map(Base.Fix1(pdf, d), eachvariate(x, variate_form(typeof(d)))) 

 end 

 end

Distributions.jl/src/common.jl

Lines 240 to 275 in f33af97

 """ 

  logpdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N} 

 Evaluate the logarithm of the probability density function of `d` at `x`. 

 This function checks if the size of `x` is compatible with distribution `d`. This check can 

 be disabled by using `@inbounds`. 

 # Implementation 

 Instead of `logpdf` one should implement `_logpdf(d, x)` which does not have to check the 

 size of `x`. 

 See also: [`pdf`](@ref). 

 """ 

 @inline function logpdf( 

 d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M} 

 ) where {N,M} 

 if M == N 

 @boundscheck begin 

 size(x) == size(d) || 

 throw(DimensionMismatch("inconsistent array dimensions")) 

 end 

 return _logpdf(d, x) 

 else 

 @boundscheck begin 

 M > N || 

 throw(DimensionMismatch( 

 "number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)" 

 )) 

 ntuple(i -> size(x, i), Val(N)) == size(d) || 

 throw(DimensionMismatch("inconsistent array dimensions")) 

 end 

 return @inbounds map(Base.Fix1(logpdf, d), eachvariate(x, variate_form(typeof(d)))) 

 end 

 end

from distributions.jl.

Missing docstring for loglikelihood about distributions.jl HOT 3 OPEN

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	# loglikelihood for `Real`
	Base.@propagate_inbounds loglikelihood(d::UnivariateDistribution, x::Real) = logpdf(d, x)

	"""
	pdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N}

	Evaluate the probability density function of `d` at `x`.

	This function checks if the size of `x` is compatible with distribution `d`. This check can
	be disabled by using `@inbounds`.

	# Implementation

	Instead of `pdf` one should implement `_pdf(d, x)` which does not have to check the size of
	`x`. However, since the default definition of `pdf(d, x)` falls back to `logpdf(d, x)`
	usually it is sufficient to implement `logpdf`.

	See also: [`logpdf`](@ref).
	"""
	@inline function pdf(
	d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M}
	) where {N,M}
	if M == N
	@boundscheck begin
	size(x) == size(d) \|\|
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return _pdf(d, x)
	else
	@boundscheck begin
	M > N \|\|
	throw(DimensionMismatch(
	"number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)"
	))
	ntuple(i -> size(x, i), Val(N)) == size(d) \|\|
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return @inbounds map(Base.Fix1(pdf, d), eachvariate(x, variate_form(typeof(d))))
	end
	end

	"""
	logpdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N}

	Evaluate the logarithm of the probability density function of `d` at `x`.

	This function checks if the size of `x` is compatible with distribution `d`. This check can
	be disabled by using `@inbounds`.

	# Implementation

	Instead of `logpdf` one should implement `_logpdf(d, x)` which does not have to check the
	size of `x`.

	See also: [`pdf`](@ref).
	"""
	@inline function logpdf(
	d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M}
	) where {N,M}
	if M == N
	@boundscheck begin
	size(x) == size(d) \|\|
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return _logpdf(d, x)
	else
	@boundscheck begin
	M > N \|\|
	throw(DimensionMismatch(
	"number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)"
	))
	ntuple(i -> size(x, i), Val(N)) == size(d) \|\|
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return @inbounds map(Base.Fix1(logpdf, d), eachvariate(x, variate_form(typeof(d))))
	end
	end