Set low tolerances

SciML · Jul 29, 2019 · 849214f · 849214f
1 parent bc84520
commit 849214f
Showing 1 changed file with 6 additions and 6 deletions.
diff --git a/test/differentiation.jl b/test/differentiation.jl
@@ -13,14 +13,14 @@ h(p, t) = [p[4]]
   function test(p)
     prob = DDEProblem(f, [p[5]], h, eltype(p).((0.0, 20.0)), copy(p);
                       constant_lags = [p[2]])
-    sol = solve(prob, MethodOfSteps(Tsit5()))
+    sol = solve(prob, MethodOfSteps(Tsit5()); abstol = 1e-14, reltol = 1e-14)
     diff = @. sol[1, :] - 10 * exp(-sol.t)
     dot(diff, diff)
   end
 
   p = [1.0, 1.0, 1.0, 0.0, 1.0]
   findiff = Calculus.finite_difference(test, p)
-  fordiff = ForwardDiff.gradient(test, p)
+  fordiff = @test_logs (:warn, r"^dt <= dtmin") ForwardDiff.gradient(test, p)
 
   @test_broken findiff ≈ fordiff
 end
@@ -29,12 +29,12 @@ end
   function test(p)
     prob = DDEProblem(f, [p[5]], h, eltype(p).((0.0, 20.0)), copy(p);
                       constant_lags = [p[2]])
-    solve(prob, MethodOfSteps(Tsit5())).u[end]
+    solve(prob, MethodOfSteps(Tsit5()); abstol = 1e-14, reltol = 1e-14).u[end]
   end
 
   p = [1.0, 1.0, 1.0, 0.0, 1.0]
   findiff = Calculus.finite_difference_jacobian(test, p)
-  fordiff = ForwardDiff.jacobian(test, p)
+  fordiff = @test_logs (:warn, r"^dt <= dtmin") ForwardDiff.jacobian(test, p)
 
   @test_broken findiff ≈ fordiff
 end
@@ -43,14 +43,14 @@ end
   function test(p)
     prob = DDEProblem(f, [p[5]], h, eltype(p).((0.0, 20.0)), copy(p);
                       constant_lags = [p[2]])
-    sol = solve(prob, MethodOfSteps(Tsit5()))
+    sol = solve(prob, MethodOfSteps(Tsit5()); abstol = 1e-14, reltol = 1e-14)
     diff = @. sol[1, :] - 10 * exp(-sol.t)
     dot(diff, diff)
   end
 
   p = [1.0, 1.0, 1.0, 0.0, 1.0]
   findiff = Calculus.finite_difference_hessian(test, p)
-  fordiff = ForwardDiff.hessian(test, p)
+  fordiff = @test_logs (:warn, r"^dt <= dtmin") ForwardDiff.hessian(test, p)
 
   @test_broken findiff ≈ fordiff
 end