diff --git a/src/triangle.jl b/src/triangle.jl
index e8f50ae..54c91e4 100644
--- a/src/triangle.jl
+++ b/src/triangle.jl
@@ -47,6 +47,13 @@ axes(P::TriangleWeight{T}) where T = (Inclusion(UnitTriangle{T}()),)
 
 Base.summary(io::IO, P::TriangleWeight) = print(io, "x^$(P.a)*y^$(P.b)*(1-x-y)^$(P.c) on the unit triangle")
 
+function getindex(P::TriangleWeight{T}, xy::StaticVector{2}) where T
+    x,y = xy
+    convert(T, x^P.a * y^P.b * (1-x-y)^P.c)
+end
+
+orthogonalityweight(P::JacobiTriangle) = TriangleWeight(P.a, P.b, P.c)
+
 @simplify function *(Dx::PartialDerivative{1}, P::JacobiTriangle)
     a,b,c = P.a,P.b,P.c
     n = mortar(Fill.(oneto(∞),oneto(∞)))
diff --git a/test/test_triangle.jl b/test/test_triangle.jl
index 86aa461..0ae0646 100644
--- a/test/test_triangle.jl
+++ b/test/test_triangle.jl
@@ -333,4 +333,14 @@ import MultivariateOrthogonalPolynomials: tri_forwardrecurrence, grid, TriangleR
         C = P¹ \ (L * P)
         @test C[1:10,1:10] ≈ A[1:10,1:10] - B[1:10,1:10]
     end
+
+    @testset "Weighted" begin
+        P¹ = JacobiTriangle(1,1,1)
+        W = Weighted(P¹)
+        @test W[SVector(0.1,0.2),1:5] ≈ 0.1 * 0.2 * (1 - 0.1 - 0.2) * P¹[SVector(0.1,0.2),1:5]
+        xy = axes(W,1)
+        ∂ˣ = PartialDerivative{1}(xy)
+        P = JacobiTriangle()
+        P \ W
+    end
 end