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SciML · Feb 14, 2024 · 5095877 · 5095877
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Showing 9 changed files with 38 additions and 29 deletions.
diff --git a/ext/DataInterpolationsChainRulesCoreExt.jl b/ext/DataInterpolationsChainRulesCoreExt.jl
@@ -2,11 +2,13 @@ module DataInterpolationsChainRulesCoreExt
 
 if isdefined(Base, :get_extension)
     using DataInterpolations: _interpolate, derivative, AbstractInterpolation,
-        LagrangeInterpolation, AkimaInterpolation, BSplineInterpolation, BSplineApprox
+                              LagrangeInterpolation, AkimaInterpolation,
+                              BSplineInterpolation, BSplineApprox
     using ChainRulesCore
 else
     using ..DataInterpolations: _interpolate, derivative, AbstractInterpolation,
-        LagrangeInterpolation, AkimaInterpolation, BSplineInterpolation, BSplineApprox
+                                LagrangeInterpolation, AkimaInterpolation,
+                                BSplineInterpolation, BSplineApprox
     using ..ChainRulesCore
 end
 
@@ -15,7 +17,7 @@ function ChainRulesCore.rrule(::typeof(_interpolate),
             LagrangeInterpolation,
             AkimaInterpolation,
             BSplineInterpolation,
-            BSplineApprox,
+            BSplineApprox
         },
         t::Number)
     deriv = derivative(A, t)

diff --git a/ext/DataInterpolationsOptimExt.jl b/ext/DataInterpolationsOptimExt.jl
@@ -2,8 +2,9 @@ module DataInterpolationsOptimExt
 
 using DataInterpolations
 import DataInterpolations: munge_data,
-    Curvefit, CurvefitCache, _interpolate, get_show, derivative, ExtrapolationError,
-    integral, IntegralNotFoundError
+                           Curvefit, CurvefitCache, _interpolate, get_show, derivative,
+                           ExtrapolationError,
+                           integral, IntegralNotFoundError
 
 isdefined(Base, :get_extension) ? (using Optim, ForwardDiff) :
 (using ..Optim, ..ForwardDiff)

diff --git a/ext/DataInterpolationsRegularizationToolsExt.jl b/ext/DataInterpolationsRegularizationToolsExt.jl
@@ -2,7 +2,8 @@ module DataInterpolationsRegularizationToolsExt
 
 using DataInterpolations
 import DataInterpolations: munge_data,
-    _interpolate, RegularizationSmooth, get_show, derivative, integral
+                           _interpolate, RegularizationSmooth, get_show, derivative,
+                           integral
 using LinearAlgebra
 
 isdefined(Base, :get_extension) ? (import RegularizationTools as RT) :
@@ -243,7 +244,8 @@ end
 #                               wls::Symbol, d::Int=2; λ::Real=1.0, alg::Symbol=:gcv_svd)
 
 """ Solve for the smoothed dependent variables and create spline interpolator """
-function _reg_smooth_solve(u::AbstractVector, t̂::AbstractVector, d::Int, M::AbstractMatrix,
+function _reg_smooth_solve(
+        u::AbstractVector, t̂::AbstractVector, d::Int, M::AbstractMatrix,
         Wls½::AbstractMatrix, Wr½::AbstractMatrix, λ::Real, alg::Symbol, extrapolate::Bool)
     λ = float(λ) # `float` expected by RT
     D = _derivative_matrix(t̂, d)

diff --git a/src/DataInterpolations.jl b/src/DataInterpolations.jl
@@ -51,8 +51,8 @@ function Base.showerror(io::IO, e::IntegralNotFoundError)
 end
 
 export LinearInterpolation, QuadraticInterpolation, LagrangeInterpolation,
-    AkimaInterpolation, ConstantInterpolation, QuadraticSpline, CubicSpline,
-    BSplineInterpolation, BSplineApprox
+       AkimaInterpolation, ConstantInterpolation, QuadraticSpline, CubicSpline,
+       BSplineInterpolation, BSplineApprox
 
 # added for RegularizationSmooth, JJS 11/27/21
 ### Regularization data smoothing and interpolation
@@ -106,7 +106,7 @@ struct CurvefitCache{
     algType,
     pminType,
     FT,
-    T,
+    T
 } <: AbstractInterpolation{FT, T}
     u::uType
     t::tType
@@ -139,7 +139,6 @@ end
 
 export Curvefit
 
-
 # Deprecated April 2020
 export ZeroSpline
 

diff --git a/src/interpolation_caches.jl b/src/interpolation_caches.jl
@@ -173,8 +173,9 @@ function QuadraticSpline(u::uType, t; extrapolate = false) where {uType <: Abstr
     d_tmp = ones(eltype(t), s)
     du = zeros(eltype(t), s - 1)
     tA = Tridiagonal(dl, d_tmp, du)
-    d_ = map(i -> i == 1 ? zeros(eltype(t), size(u[1])) :
-                  2 // 1 * (u[i] - u[i - 1]) / (t[i] - t[i - 1]),
+    d_ = map(
+        i -> i == 1 ? zeros(eltype(t), size(u[1])) :
+             2 // 1 * (u[i] - u[i - 1]) / (t[i] - t[i - 1]),
         1:s)
     d = transpose(reshape(reduce(hcat, d_), :, s))
     z_ = reshape(transpose(tA \ d), size(u[1])..., :)
@@ -213,8 +214,9 @@ function CubicSpline(u::uType,
     typed_zero = zero(6(u[begin + 2] - u[begin + 1]) / h[begin + 2] -
                       6(u[begin + 1] - u[begin]) / h[begin + 1])
 
-    d = map(i -> i == 1 || i == n + 1 ? typed_zero :
-                 6(u[i + 1] - u[i]) / h[i + 1] - 6(u[i] - u[i - 1]) / h[i],
+    d = map(
+        i -> i == 1 || i == n + 1 ? typed_zero :
+             6(u[i + 1] - u[i]) / h[i + 1] - 6(u[i] - u[i - 1]) / h[i],
         1:(n + 1))
     z = tA \ d
     CubicSpline{true}(u, t, h[1:(n + 1)], z, extrapolate)
@@ -228,8 +230,9 @@ function CubicSpline(u::uType, t; extrapolate = false) where {uType <: AbstractV
     d_tmp = 2 .* (h[1:(n + 1)] .+ h[2:(n + 2)])
     du = h[2:(n + 1)]
     tA = Tridiagonal(dl, d_tmp, du)
-    d_ = map(i -> i == 1 || i == n + 1 ? zeros(eltype(t), size(u[1])) :
-                  6(u[i + 1] - u[i]) / h[i + 1] - 6(u[i] - u[i - 1]) / h[i],
+    d_ = map(
+        i -> i == 1 || i == n + 1 ? zeros(eltype(t), size(u[1])) :
+             6(u[i + 1] - u[i]) / h[i + 1] - 6(u[i] - u[i - 1]) / h[i],
         1:(n + 1))
     d = transpose(reshape(reduce(hcat, d_), :, n + 1))
     z_ = reshape(transpose(tA \ d), size(u[1])..., :)

diff --git a/src/interpolation_utils.jl b/src/interpolation_utils.jl
@@ -41,8 +41,9 @@ function munge_data(u::AbstractVector, t::AbstractVector)
     Tu = Base.nonmissingtype(eltype(u))
     Tt = Base.nonmissingtype(eltype(t))
     @assert length(t) == length(u)
-    non_missing_indices = collect(i for i in 1:length(t)
-                                      if !ismissing(u[i]) && !ismissing(t[i]))
+    non_missing_indices = collect(i
+    for i in 1:length(t)
+    if !ismissing(u[i]) && !ismissing(t[i]))
     newu = Tu.([u[i] for i in non_missing_indices])
     newt = Tt.([t[i] for i in non_missing_indices])
 
@@ -53,8 +54,9 @@ function munge_data(U::StridedMatrix, t::AbstractVector)
     TU = Base.nonmissingtype(eltype(U))
     Tt = Base.nonmissingtype(eltype(t))
     @assert length(t) == size(U, 2)
-    non_missing_indices = collect(i for i in 1:length(t)
-                                      if !any(ismissing, U[:, i]) && !ismissing(t[i]))
+    non_missing_indices = collect(i
+    for i in 1:length(t)
+    if !any(ismissing, U[:, i]) && !ismissing(t[i]))
     newUs = [TU.(U[:, i]) for i in non_missing_indices]
     newt = Tt.([t[i] for i in non_missing_indices])
 

diff --git a/test/interpolation_tests.jl b/test/interpolation_tests.jl
@@ -360,7 +360,7 @@ end
 
     @testset "Matrix case" for u in [
         [1.0 2.0 0.0 1.0; 1.0 2.0 0.0 1.0],
-        ["B" "C" "A" "B"; "B" "C" "A" "B"],
+        ["B" "C" "A" "B"; "B" "C" "A" "B"]
     ]
         A = ConstantInterpolation(u, t, dir = :right; extrapolate = true)
         @test A(0.5) == u[:, 1]
@@ -609,7 +609,7 @@ end
         0.9836755196317837,
         0.8833959853995836,
         0.3810348276782708,
-        0.048062978598861855,
+        0.048062978598861855
     ]
     us = A.(ts)
     @test vs ≈ us

diff --git a/test/regularization.jl b/test/regularization.jl
@@ -56,7 +56,7 @@ tolerance = 1e-3
         0.1392761732695201,
         -0.3312498167413961,
         -0.6673268474631847,
-        -0.9370342562716745,
+        -0.9370342562716745
     ]
     @test isapprox(A.û, ans, rtol = tolerance)
     @test isapprox(A.(tₒ), ans, rtol = tolerance)
@@ -81,7 +81,7 @@ end
         0.05281575111822609,
         -0.5333542714497277,
         -0.8406745098604134,
-        -1.0983391396173634,
+        -1.0983391396173634
     ]
     @test isapprox(A.û, ans, rtol = tolerance)
     @test isapprox(A.(tₒ), ans, rtol = tolerance)
@@ -102,7 +102,7 @@ end
         0.09102085384961625,
         -0.5640882848240228,
         -0.810519277110118,
-        -1.1159124134900906,
+        -1.1159124134900906
     ]
     @test isapprox(A.û, ans, rtol = tolerance)
     @test isapprox(A.(tₒ), ans, rtol = tolerance)
@@ -126,7 +126,7 @@ end
         0.04756024028728636,
         -0.5301034620974782,
         -0.8408107101140526,
-        -1.1058428573417736,
+        -1.1058428573417736
     ]
     @test isapprox(A.û, ans, rtol = tolerance)
     @test isapprox(A.(tₒ), ans, rtol = tolerance)
@@ -173,7 +173,7 @@ end
         -0.676806367664006,
         -0.8587832527770329,
         -1.0443430843364814,
-        -1.2309001260104093,
+        -1.2309001260104093
     ]
     @test isapprox(A.û, ans, rtol = tolerance)
     @test isapprox(A.(t̂), ans, rtol = tolerance)

diff --git a/test/show.jl b/test/show.jl
@@ -16,7 +16,7 @@ x = [1.0, 2.0, 3.0, 4.0, 5.0]
         LinearInterpolation(x, t),
         AkimaInterpolation(x, t),
         QuadraticSpline(x, t),
-        CubicSpline(x, t),
+        CubicSpline(x, t)
     ]
     test_show_line.(methods)
 end