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ReactiveBayes · Jan 30, 2025 · 630acaf · 630acaf · bvdmitri · Jan 30, 2025
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diff --git a/src/rules/binomial_polya/y.jl b/src/rules/binomial_polya/y.jl
@@ -11,7 +11,7 @@ using ExponentialFamily.LogExpFunctions
     else
         n_samples = getn_samples(meta)
         βsamples = rand(meta.rng, q_β, n_samples)
-        p_avg = mapreduce(βsample -> logistic(dot(x, βsample)), +, eachcol(βsamples))/n_samples
+        p_avg = mapreduce(βsample -> logistic(dot(x, βsample)), +, eachcol(βsamples)) / n_samples
         return Binomial(n, p_avg)
     end
-end
+end
diff --git a/test/rules/binomial_polya/y_tests.jl b/test/rules/binomial_polya/y_tests.jl
@@ -8,12 +8,12 @@
         q_x = PointMass([0.1, 0.2])
         q_n = PointMass(5)
         q_β = MvNormalWeightedMeanPrecision([3.0, -1.0], diageye(2))
-        
+
         # Test with default meta
         pred_dist = @call_rule BinomialPolya(:y, Marginalisation) (q_x = q_x, q_n = q_n, q_β = q_β, meta = nothing)
         @test pred_dist isa Binomial
         @test ntrials(pred_dist) == 5
-        
+
         # Test with Monte Carlo sampling
         meta = BinomialPolyaMeta(1000, MersenneTwister(42))
         pred_dist_mc = @call_rule BinomialPolya(:y, Marginalisation) (q_x = q_x, q_n = q_n, q_β = q_β, meta = meta)
@@ -23,6 +23,4 @@
 
         @test pred_dist_mc.p ≈ pred_dist.p atol = 1e-2
     end
-
 end
-