chore: format

SciML · Mar 5, 2024 · fd1b4a8 · fd1b4a8
1 parent 2e05ec1
commit fd1b4a8
Show file tree

Hide file tree

Showing 2 changed files with 7 additions and 5 deletions.
diff --git a/src/DataInterpolations.jl b/src/DataInterpolations.jl
@@ -29,7 +29,9 @@ include("show.jl")
 
 (interp::AbstractInterpolation)(t::Number) = _interpolate(interp, t)
 (interp::AbstractInterpolation)(t::Number, i::Integer) = _interpolate(interp, t, i)
-(interp::AbstractInterpolation)(t::AbstractVector) = interp(similar(t, promote_type(eltype(interp), eltype(t))), t)
+function (interp::AbstractInterpolation)(t::AbstractVector)
+    interp(similar(t, promote_type(eltype(interp), eltype(t))), t)
+end
 function (interp::AbstractInterpolation)(u::AbstractVector, t::AbstractVector)
     iguess = firstindex(interp.t)
     @inbounds for i in eachindex(u, t)

diff --git a/test/derivative_tests.jl b/test/derivative_tests.jl
@@ -223,11 +223,11 @@ end
 @testset "Jacobian tests" begin
     u = rand(5)
     t = 0:4
-    interp = LinearInterpolation(u, t,extrapolate=true)
-    grad1 = ForwardDiff.derivative(interp,2.4)
+    interp = LinearInterpolation(u, t, extrapolate = true)
+    grad1 = ForwardDiff.derivative(interp, 2.4)
 
-    myvec = rand(20).*4.0
+    myvec = rand(20) .* 4.0
     interp(myvec)
 
-    grad = ForwardDiff.jacobian(interp,myvec)
+    grad = ForwardDiff.jacobian(interp, myvec)
 end