Fix defects found in code review

Fix typos, a stray global binding, an empty-argument function stub, dead
extension code, and integer conversion of possibly-fractional sample
weight sums.

Created by generative AI.

Author: oschulz

ext/BATOptimExt.jl

@@ -16,9 +16,6 @@ using StructArrays, ArraysOfArrays
 using AutoDiffOperators: reverse_adtype
 
 
-AbstractModeEstimator(optalg::Optim.AbstractOptimizer) = OptimAlg(optalg)
-Base.convert(::Type{AbstractModeEstimator}, alg::OptimAlg) = alg.optalg
-
 BAT.ext_default(::BAT.PackageExtension{:Optim}, ::Val{:DEFAULT_OPTALG}) = Optim.NelderMead()
 BAT.ext_default(::BAT.PackageExtension{:Optim}, ::Val{:NELDERMEAD_ALG}) = Optim.NelderMead()
 BAT.ext_default(::BAT.PackageExtension{:Optim}, ::Val{:LBFGS_ALG}) = Optim.LBFGS()

ext/BATOptimizationBaseExt.jl

@@ -15,9 +15,6 @@ using DensityInterface, InverseFunctions, FunctionChains
 using AutoDiffOperators: AbstractADType, NoAutoDiff, reverse_adtype
 
 
-AbstractModeEstimator(optalg::Any) = OptimizationAlg(optalg)
-Base.convert(::Type{AbstractModeEstimator}, alg::OptimizationAlg) = alg.optalg
-
 BAT.ext_default(::BAT.PackageExtension{:OptimizationBase}, ::Val{:DEFAULT_OPTALG}) = nothing #Optim.NelderMead()
 
 

src/algotypes/median_estimator.jl

@@ -3,10 +3,8 @@
 """
     abstract type BAT.AbstractMedianEstimator
 
-Abstract type for BAT optimization algorithms.
-
-A typical application for optimization in BAT is mode estimation
-(see [`bat_findmode`](@ref)),
+Abstract type for BAT median estimation algorithms (see
+[`bat_findmedian`](@ref)).
 """
 abstract type AbstractMedianEstimator end
 

src/initvals/initvals.jl

@@ -58,13 +58,13 @@ get_initsrc_from_target(target::AbstractPosteriorMeasure) = get_initsrc_from_tar
 
 
 """
-    get_iid_sampleable_approx()
+    get_iid_sampleable_approx(target)
 
 *BAT-internal, not part of stable public API.*
 
 Obtain a measure from the target that can be sampled to obtain iid samples for a MCMCGlobalProposal.
 """
-function get_iid_sampleable_approx() end
+function get_iid_sampleable_approx end
 
 function get_iid_sampleable_approx(target::AbstractMeasure) 
     if supports_rand(target)

src/integration/bridge_sampling_integration.jl

@@ -50,8 +50,8 @@ function bridge_sampling_integral(
     context::BATContext
     )
 
-    N1 = Int(sum(target_samples.weight))
-    N2 = Int(sum(proposal_samples.weight))
+    N1 = round(Int, sum(target_samples.weight))
+    N2 = round(Int, sum(proposal_samples.weight))
 
     #####################
     # Evaluate integral #

src/measures/bat_dist_measure.jl

@@ -40,7 +40,7 @@ function DensityInterface.logdensityof(m::BATDistMeasure{<:Distribution{Univaria
             # so move an epsilon away from minimum:
             convert(R, logpdf(d, minimum(d) + eps(typeof(v))))
         elseif v ≈ maximum(d)
-            # Likewise at maxiumum:
+            # Likewise at maximum:
             convert(R, logpdf(d, maximum(d) - eps(typeof(v))))
         else
             logd
@@ -69,7 +69,7 @@ function Random.rand(gen::GenContext, m::BATDistMeasure)
 end
 
 _reshape_rand_n_output(x::Any) = x
-x =_reshape_rand_n_output(x::AbstractMatrix) = nestedview(x)
+_reshape_rand_n_output(x::AbstractMatrix) = nestedview(x)
 _reshape_rand_n_output(x::AbstractArray{<:AbstractArray}) = ArrayOfSimilarArrays(x)
 _reshape_rand_n_output(x::ArrayOfSimilarArrays) = x
 

src/measures/bat_measure.jl

@@ -153,7 +153,7 @@ end
 
 *BAT-internal, not part of stable public API.*
 
-Convert a measure-like object `m` supports `rand`.
+Check whether a measure-like object `m` supports `rand`.
 """
 @inline supports_rand(::AbstractMeasure) = false
 @inline supports_rand(::StdMeasure) = true

src/measures/bat_weighted_measure.jl

@@ -86,7 +86,7 @@ ValueShapes.unshaped(m::BATWeightedMeasure) = weightedmeasure(m.logweight, unsha
 
 Returns `(result = new_measure, logweight = logweight)`.
 
-Tries to automatically renormalize `measure` if a maxium log-m value
+Tries to automatically renormalize `measure` if a maximum log-density value
 is available, returns `measure` unchanged otherwise.
 """
 function auto_renormalize(measure::AbstractMeasure)

src/measures/posterior_measure.jl

@@ -21,7 +21,7 @@ end
 
 
 """
-    getlikelihood(posterior::AbstractPosteriorMeasure)::BATDenstiy
+    getlikelihood(posterior::AbstractPosteriorMeasure)::BATDensity
 
 *BAT-internal, not part of stable public API.*
 

src/measures/truncate_batmeasure.jl

@@ -73,7 +73,7 @@ end
 
 
 function truncate_dist_hard(dist::Distributions.Truncated, bounds::Interval)
-    # Note: Assumes that dist is result of trunctate, not of truncate_dist_hard:
+    # Note: Assumes that dist is result of truncated, not of truncate_dist_hard:
     untrunc_dist = dist.untruncated
 
     min_lo = minimum(untrunc_dist)