make format

test/distributions/dirichlet_tests.jl

@@ -87,4 +87,4 @@ end
             )
         end
     end
-end
+end

test/distributions/distributions_setuptests.jl

@@ -2,50 +2,50 @@ using ExponentialFamily, Distributions, LinearAlgebra, TinyHugeNumbers
 using Test, ForwardDiff, Random, StatsFuns, StableRNGs, FillArrays
 
 import ExponentialFamily:
-    ExponentialFamilyDistribution, 
-    getnaturalparameters, 
-    getconditioner, 
-    compute_logscale, 
-    logpartition, 
-    basemeasure, 
+    ExponentialFamilyDistribution,
+    getnaturalparameters,
+    getconditioner,
+    compute_logscale,
+    logpartition,
+    basemeasure,
     insupport,
-    sufficientstatistics, 
-    fisherinformation, 
-    pack_parameters, 
-    unpack_parameters, 
+    sufficientstatistics,
+    fisherinformation,
+    pack_parameters,
+    unpack_parameters,
     isbasemeasureconstant,
-    ConstantBaseMeasure, 
-    MeanToNatural, 
-    NaturalToMean, 
-    NaturalParametersSpace, 
-    default_prod_rule, 
-    fastcholesky, 
+    ConstantBaseMeasure,
+    MeanToNatural,
+    NaturalToMean,
+    NaturalParametersSpace,
+    default_prod_rule,
+    fastcholesky,
     mirrorlog,
-    deep_eltype, 
-    sampletype, 
-    samplefloattype, 
-    promote_sampletype, 
+    deep_eltype,
+    sampletype,
+    samplefloattype,
+    promote_sampletype,
     promote_samplefloattype,
-    paramfloattype, 
-    convert_paramfloattype, 
+    paramfloattype,
+    convert_paramfloattype,
     FactorizedJoint,
     promote_variate_type,
     invscatter,
     location,
     locationdim
 
-import Distributions: 
-    variate_form, 
-    value_support    
+import Distributions:
+    variate_form,
+    value_support
 
-import SpecialFunctions: 
+import SpecialFunctions:
     logbeta,
     loggamma,
     digamma,
     logfactorial,
     besseli
 
-import HCubature: 
+import HCubature:
     hquadrature
 
 import DomainSets:

test/distributions/erlang_tests.jl

@@ -80,4 +80,4 @@ end
             )
         end
     end
-end
+end

test/distributions/gamma_family/gamma_family_setuptests.jl

@@ -21,4 +21,4 @@ function compare_basic_statistics(left, right)
     @test mean(xtlog, left) ≈ mean(xtlog, right)
 
     return true
-end
+end

test/distributions/gamma_family/gamma_shape_scale_tests.jl

@@ -85,4 +85,4 @@ end
         @test prod(strategy, GammaShapeRate(2, 2), GammaShapeScale(1, 2)) == GammaShapeRate(2, 5 / 2)
         @test prod(strategy, GammaShapeRate(2, 2), GammaShapeScale(2, 2)) == GammaShapeRate(3, 5 / 2)
     end
-end
+end

test/distributions/gamma_inverse_tests.jl

@@ -54,7 +54,7 @@ end
             )
 
             run_test_fisherinformation_against_hessian(d; assume_no_allocations = false, assume_ours_faster = false)
-            run_test_fisherinformation_against_jacobian(d; assume_no_allocations = false, assume_ours_faster = false)
+            run_test_fisherinformation_against_jacobian(d; assume_no_allocations = false)
 
             (α, β) = params(MeanParametersSpace(), d)
 

test/distributions/lognormal_tests.jl

@@ -65,4 +65,4 @@ end
     @test !isproper(NaturalParametersSpace(), LogNormal, [1.0])
     @test !isproper(NaturalParametersSpace(), LogNormal, [-1.0, 0.0])
     @test !isproper(NaturalParametersSpace(), LogNormal, [1.0, 1.0])
-end
+end

test/distributions/mv_normal_wishart_tests.jl

@@ -55,4 +55,4 @@ end
             )
         end
     end
-end
+end

test/distributions/normal_family/normal_family_setuptests.jl

@@ -108,4 +108,4 @@ function check_basic_statistics(left::MultivariateNormalDistributionsFamily, rig
         @test all(weightedmean_invcov(left) .≈ weightedmean_invcov(right))
         @test all(weightedmean_precision(left) .≈ weightedmean_precision(right))
     end
-end
+end

test/distributions/normal_family/normal_family_tests.jl

@@ -334,4 +334,4 @@ end
         @test sort(eigvals(fi_dist)) ≈ sort(abs.(eigvals(approxFisherInformation))) rtol = 1e-1
         @test sort(svd(fi_dist).S) ≈ sort(svd(approxFisherInformation).S) rtol = 1e-1
     end
-end
+end

test/distributions/vonmises_tests.jl

@@ -76,4 +76,4 @@ end
             )
         end
     end
-end
+end

test/distributions/weibull_tests.jl

@@ -81,4 +81,4 @@ end
         @test first(hquadrature(x -> pdf(res, tan(x * pi / 2)) * (pi / 2) * (1 / cos(pi * x / 2))^2, 0.0, 1.0)) ≈
               1.0
     end
-end
+end

test/distributions/wishart_inverse_tests.jl

@@ -221,4 +221,4 @@ end
             )
         end
     end
-end
+end

test/distributions/wishart_tests.jl

@@ -126,4 +126,4 @@ end
             )
         end
     end
-end
+end

test/distributions_setuptests.jl

@@ -3,14 +3,14 @@ using Test, ExponentialFamily, Distributions, StaticArrays, StableRNGs, LinearAl
 
 import Distributions: variate_form, value_support
 
-import ExponentialFamily: 
-    deep_eltype, 
-    sampletype, 
-    samplefloattype, 
-    promote_sampletype, 
+import ExponentialFamily:
+    deep_eltype,
+    sampletype,
+    samplefloattype,
+    promote_sampletype,
     promote_samplefloattype,
-    paramfloattype, 
-    convert_paramfloattype, 
+    paramfloattype,
+    convert_paramfloattype,
     FactorizedJoint
 
 function generate_random_distributions(::Type{V} = Any; seed = abs(rand(Int)), Types = (Float32, Float64)) where {V}

test/exponential_family_setuptests.jl

@@ -70,4 +70,4 @@ ExponentialFamily.join_conditioner(::Type{ArbitraryConditionedDistributionFromEx
 (::MeanToNatural{ArbitraryConditionedDistributionFromExponentialFamily})(params::Tuple, conditioner::Number) = (params[1] + conditioner,)
 (::NaturalToMean{ArbitraryConditionedDistributionFromExponentialFamily})(params::Tuple, conditioner::Number) = (params[1] - conditioner,)
 
-ExponentialFamily.unpack_parameters(::Type{ArbitraryConditionedDistributionFromExponentialFamily}, η) = (η[1],)
+ExponentialFamily.unpack_parameters(::Type{ArbitraryConditionedDistributionFromExponentialFamily}, η) = (η[1],)

test/exponential_family_tests.jl

@@ -241,7 +241,6 @@ end
             @test @inferred(paramfloattype(similar(member, F))) === F
         end
     end
-
 end
 
 @testitem "vague" begin
@@ -252,4 +251,4 @@ end
 
     @test @inferred(vague(ExponentialFamilyDistribution{ArbitraryConditionedDistributionFromExponentialFamily})) isa
           ExponentialFamilyDistribution{ArbitraryConditionedDistributionFromExponentialFamily}
-end
+end

test/prod_setuptests.jl

@@ -37,4 +37,4 @@ Base.convert(::Type{Int}, ::ObjectWithClosedProd2) = 2
 
 struct ADistributionObject <: ContinuousUnivariateDistribution end
 
-prod(::PreserveTypeProd{Distribution}, ::ADistributionObject, ::ADistributionObject) = ADistributionObject()
+prod(::PreserveTypeProd{Distribution}, ::ADistributionObject, ::ADistributionObject) = ADistributionObject()