run formatter

Author: simulutions

src/interpolation_caches.jl

@@ -1220,8 +1220,8 @@ function BSplineApprox(
     end
     for k in 2:(n - 1)
         q[ax_u...,
-        k] = u[ax_u..., k] - sc[k, 1] * u[ax_u..., 1] -
-             sc[k, h] * u[ax_u..., end]
+            k] = u[ax_u..., k] - sc[k, 1] * u[ax_u..., 1] -
+                 sc[k, h] * u[ax_u..., end]
     end
     Q = Array{T, N}(undef, size(u)[1:(end - 1)]..., h - 2)
     for i in 2:(h - 1)

src/interpolation_utils.jl

@@ -191,7 +191,8 @@ function cumulative_integral(A::AbstractInterpolation{<:Number}, cache_parameter
     Base.require_one_based_indexing(A.u)
     idxs = cache_parameters ? (1:(length(A.t) - 1)) : (1:0)
     return cumsum(_integral(A, idx, t1, t2)
-    for (idx, t1, t2) in zip(idxs, @view(A.t[begin:(end - 1)]), @view(A.t[(begin + 1):end])))
+    for (idx, t1, t2) in
+        zip(idxs, @view(A.t[begin:(end - 1)]), @view(A.t[(begin + 1):end])))
 end
 
 function get_parameters(A::LinearInterpolation, idx)

test/interpolation_tests.jl

@@ -1027,6 +1027,7 @@ end
     ut1 = Float32[0.1, 0.2, 0.3, 0.4, 0.5]
     ut2 = Float64[0.1, 0.2, 0.3, 0.4, 0.5]
     for u in (ut1, ut2), t in (ut1, ut2)
+
         interp = @inferred(LinearInterpolation(ut1, ut2))
         for xs in (u, t)
             ys = @inferred(interp(xs))
@@ -1109,6 +1110,7 @@ f_cubic_spline = c -> square(CubicSpline, c)
     iszero_allocations(u, t) = iszero(@allocated(DataInterpolations.munge_data(u, t)))
 
     for T in (String, Union{String, Missing}), dims in 1:3
+
         _u0 = convert(Array{T}, reshape(u0, ntuple(i -> i == dims ? 3 : 1, dims)))
 
         u, t = @inferred(DataInterpolations.munge_data(_u0, t0))