From c7fc4513ccc6e7ef8d166834e5c31cf5288b585d Mon Sep 17 00:00:00 2001
From: Ronny Bergmann <git@ronnybergmann.net>
Date: Sat, 23 Dec 2023 15:58:28 +0100
Subject: [PATCH] Fix statistics tests.

---
 src/Manifolds.jl           | 3 ++-
 src/manifolds/Euclidean.jl | 7 +++++--
 test/statistics.jl         | 4 ++--
 3 files changed, 9 insertions(+), 5 deletions(-)

diff --git a/src/Manifolds.jl b/src/Manifolds.jl
index 6267506d0e..89c466e728 100644
--- a/src/Manifolds.jl
+++ b/src/Manifolds.jl
@@ -797,9 +797,10 @@ export ×,
     convert,
     complex_dot,
     decorated_manifold,
-    default_vector_transport_method,
+    default_approximation_method,
     default_inverse_retraction_method,
     default_retraction_method,
+    default_vector_transport_method,
     det_local_metric,
     differential_canonical_project,
     differential_canonical_project!,
diff --git a/src/manifolds/Euclidean.jl b/src/manifolds/Euclidean.jl
index 2abf194cc5..f5a5b3a69a 100644
--- a/src/manifolds/Euclidean.jl
+++ b/src/manifolds/Euclidean.jl
@@ -115,7 +115,10 @@ function check_vector(M::Euclidean{N,𝔽}, p, X; kwargs...) where {N,𝔽}
 end
 
 default_approximation_method(::Euclidean, ::typeof(mean)) = EfficientEstimator()
-default_approximation_method(::Euclidean, ::typeof(median), ::Number) = EfficientEstimator()
+function default_approximation_method(::Euclidean, ::typeof(median), ::Type{<:Number})
+    return EfficientEstimator()
+end
+
 function default_approximation_method(::Euclidean, ::typeof(median), ::Array{T,0}) where {T}
     return EfficientEstimator()
 end
@@ -610,7 +613,7 @@ function Statistics.median(
 end
 function Statistics.median(
     ::Union{Euclidean{TypeParameter{Tuple{}}},Euclidean{Tuple{}}},
-    x::AbstractVector{<:Number},
+    x::AbstractVector,
     w::AbstractWeights,
     ::EfficientEstimator;
     kwargs...,
diff --git a/test/statistics.jl b/test/statistics.jl
index b64f8a8758..09c50f9da3 100644
--- a/test/statistics.jl
+++ b/test/statistics.jl
@@ -133,7 +133,7 @@ function test_median(
         y = isnothing(method) ? median(M, x; kwargs...) : median(M, x, method; kwargs...)
         @test is_point(M, y; atol=10^-9)
         if yexp !== nothing
-            @test isapprox(M, y, yexp; atol=10^-5)
+            @test isapprox(M, y, yexp; atol=5 * 10^-5)
         end
     end
 
@@ -797,7 +797,7 @@ end
         x = [normalize(randn(rng, 3)) for _ in 1:10]
         w = pweights([rand(rng) for _ in 1:length(x)])
         m = normalize(median(Euclidean(3), x, w))
-        mg = median(S, x, w, ExtrinsicEstimation(EfficientEstimator()))
+        mg = median(S, x, w, ExtrinsicEstimation(CyclicProximalPointEstimation()))
         @test isapprox(S, m, mg)
     end