slightly more standardized

Author: dehann

test/manifolds/manifolddiff.jl

@@ -24,17 +24,21 @@ data = [exp(M, p,  σ * rand(M; vector_at=p)) for i in 1:n];
 
 # objective function
 f(M, p) = sum(1 / (2 * n) * distance.(Ref(M), Ref(p), data) .^ 2)
-f_(p) = f(M,p)
+# f_(p) = f(M,p)
 
+# non-manual: intrinsic finite differences gradient
+function grad_f_FD(M,p)
+  f_(p_) = f(M,p_)
+  ManifoldDiff.gradient(M, f_, p, r_backend)
+end
 # manual gradient
 # grad_f(M, p) = sum(1 / n * grad_distance.(Ref(M), data, Ref(p)));
 
-# non-manual: intrinsic finite differences gradient
-grad_f_FD(M,p) = ManifoldDiff.gradient(M, f_, p, r_backend)
 
 # and solve
-m1 = gradient_descent(M, f, grad_f_FD, data[1])
+@time m1 = gradient_descent(M, f, grad_f_FD, data[1])
 
+@info "Basic Manopt test" string(m1')
 @test isapprox(p, m1; atol=0.15)
 
 ##