QA: run_qa v1.6 form + ExplicitImports

Project.toml

@@ -5,17 +5,20 @@ repo = "https://github.com/SciML/SimpleDiffEq.jl.git"
 
 [deps]
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
+FastBroadcast = "7034ab61-46d4-4ed7-9d0f-46aef9175898"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 
 [compat]
-DiffEqBase = "6.194.0, 7"
-ExplicitImports = "1.14.0"
+DiffEqBase = "7"
+FastBroadcast = "0.3, 0.4, 1, 2"
 JLArrays = "0.1, 0.2, 0.3"
+LinearAlgebra = "1"
 MuladdMacro = "0.2.4"
 OrdinaryDiffEq = "6.106.0, 7"
 OrdinaryDiffEqLowOrderRK = "1, 2"
@@ -25,13 +28,13 @@ Parameters = "0.12, 0.13"
 RecursiveArrayTools = "3.37.0, 4"
 Reexport = "1.2.2"
 SafeTestsets = "0.1"
-SciMLTesting = "1"
+SciMLBase = "3.27"
+SciMLTesting = "1.6"
 StaticArrays = "1.9.14"
 Test = "1"
 julia = "1.10"
 
 [extras]
-ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
 JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 OrdinaryDiffEqLowOrderRK = "1344f307-1e59-4825-a18e-ace9aa3fa4c6"
@@ -42,4 +45,4 @@ SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["ExplicitImports", "JLArrays", "OrdinaryDiffEq", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqTsit5", "OrdinaryDiffEqVerner", "SafeTestsets", "SciMLTesting", "Test"]
+test = ["JLArrays", "OrdinaryDiffEq", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqTsit5", "OrdinaryDiffEqVerner", "SafeTestsets", "SciMLTesting", "Test"]

src/SimpleDiffEq.jl

@@ -4,14 +4,15 @@ module SimpleDiffEq
 
     using Reexport: @reexport
     using MuladdMacro: @muladd
+    @reexport using FastBroadcast: @..
     @reexport using DiffEqBase: DiffEqBase, ODEProblem, SDEProblem, DiscreteProblem,
         isinplace, reinit!, ODE_DEFAULT_NORM,
-        set_t!, solve, step!, init, @..,
+        set_t!, solve, step!, init, isdiscrete
+    @reexport using SciMLBase: SciMLBase, build_solution, is_diagonal_noise,
+        AbstractSDEAlgorithm, AbstractODEAlgorithm,
         AbstractODEIntegrator, DEIntegrator, ConstantInterpolation,
-        __init, __solve, build_solution, has_analytic,
-        calculate_solution_errors!, is_diagonal_noise,
-        AbstractSDEAlgorithm, AbstractODEAlgorithm, isdiscrete, SciMLBase
-    import DiffEqBase.SciMLBase: allows_arbitrary_number_types, allowscomplex, isautodifferentiable, isadaptive
+        __init, __solve, has_analytic, calculate_solution_errors!
+    import SciMLBase: allows_arbitrary_number_types, allowscomplex, isautodifferentiable, isadaptive
     # `derivative_discontinuity!` was introduced in DiffEqBase v7 / SciMLBase v3,
     # replacing the older `u_modified!`. Support both branches so the package can
     # be used with either DiffEqBase v6 or v7.

src/euler/euler.jl

@@ -47,7 +47,7 @@ struct SimpleEuler <: AbstractSimpleDiffEqODEAlgorithm end
 export SimpleEuler
 
 mutable struct SimpleEulerIntegrator{IIP, S, T, P, F} <:
-    DiffEqBase.AbstractODEIntegrator{SimpleEuler, IIP, S, T}
+    SciMLBase.AbstractODEIntegrator{SimpleEuler, IIP, S, T}
     f::F             # ..................................... Equations of motion
     uprev::S         # .......................................... Previous state
     u::S             # ........................................... Current state
@@ -71,7 +71,7 @@ DiffEqBase.isinplace(::SEI{IIP}) where {IIP} = IIP
 #                                Initialization
 ################################################################################
 
-function DiffEqBase.__init(
+function SciMLBase.__init(
         prob::ODEProblem, alg::SimpleEuler;
         dt = error("dt is required for this algorithm"), kwargs...
     )
@@ -85,7 +85,7 @@ function DiffEqBase.__init(
     )
 end
 
-function DiffEqBase.__solve(
+function SciMLBase.__solve(
         prob::ODEProblem, alg::SimpleEuler;
         dt = error("dt is required for this algorithm"), kwargs...
     )
@@ -107,10 +107,10 @@ function DiffEqBase.__solve(
         us[i + 1] = _copy(integ.u)
     end
 
-    sol = DiffEqBase.build_solution(prob, alg, ts, us, calculate_error = false)
+    sol = SciMLBase.build_solution(prob, alg, ts, us, calculate_error = false)
 
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol;
         timeseries_errors = true,
         dense_errors = false

src/euler/gpueuler.jl

@@ -70,13 +70,13 @@ export GPUSimpleEuler
         us[i] = u
     end
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, SArray(us),
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )

src/euler/loopeuler.jl

@@ -47,7 +47,7 @@ export LoopEuler
 
 # Out-of-place
 # No caching, good for static arrays, bad for arrays
-@muladd function DiffEqBase.__solve(
+@muladd function SciMLBase.__solve(
         prob::ODEProblem{uType, tType, false},
         alg::LoopEuler;
         dt = error("dt is required for this algorithm"),
@@ -92,13 +92,13 @@ export LoopEuler
 
     !save_everystep && save_end && (us[end] = u)
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, us,
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )
@@ -107,7 +107,7 @@ end
 
 # In-place
 # Good for mutable objects like arrays
-# Use DiffEqBase.@.. for simd ivdep
+# Use @.. for simd ivdep
 @muladd function DiffEqBase.solve(
         prob::ODEProblem{uType, tType, true},
         alg::LoopEuler;
@@ -147,19 +147,19 @@ end
     for i in 2:length(ts)
         t = ts[i]
         f(k, u, p, t)
-        DiffEqBase.@.. u = u + dt * k
+        @.. u = u + dt * k
         save_everystep && (us[i] = copy(u))
     end
 
     !save_everystep && save_end && (us[end] = u)
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, us,
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )

src/euler_maruyama.jl

@@ -31,7 +31,7 @@ sol = solve(prob, SimpleEM(), dt = 0.01)
 
 - [`SDEProblem`](@ref) for problem setup
 """
-struct SimpleEM <: DiffEqBase.AbstractSDEAlgorithm end
+struct SimpleEM <: SciMLBase.AbstractSDEAlgorithm end
 export SimpleEM
 
 @muladd function DiffEqBase.solve(
@@ -76,7 +76,7 @@ export SimpleEM
         end
     end
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, t, u,
         calculate_error = false
     )
@@ -97,9 +97,9 @@ end
     tspan = prob.tspan
     p = prob.p
     ftmp = zero(u0)
-    gtmp = DiffEqBase.is_diagonal_noise(prob) ? zero(u0) : zero(prob.noise_rate_prototype)
-    gtmp2 = DiffEqBase.is_diagonal_noise(prob) ? nothing : zero(u0)
-    dW = DiffEqBase.is_diagonal_noise(prob) ? zero(u0) :
+    gtmp = SciMLBase.is_diagonal_noise(prob) ? zero(u0) : zero(prob.noise_rate_prototype)
+    gtmp2 = SciMLBase.is_diagonal_noise(prob) ? nothing : zero(u0)
+    dW = SciMLBase.is_diagonal_noise(prob) ? zero(u0) :
         false .* prob.noise_rate_prototype[1, :]
 
     @inbounds begin
@@ -116,15 +116,15 @@ end
         g(gtmp, uprev, p, tprev)
         @. dW = randn(eltype(dW))
 
-        if DiffEqBase.is_diagonal_noise(prob)
-            DiffEqBase.@.. u[i] = uprev + ftmp * dt + sqdt * gtmp * dW
+        if SciMLBase.is_diagonal_noise(prob)
+            @.. u[i] = uprev + ftmp * dt + sqdt * gtmp * dW
         else
             mul!(gtmp2, gtmp, dW)
-            DiffEqBase.@.. u[i] = uprev + ftmp * dt + sqdt * gtmp2
+            @.. u[i] = uprev + ftmp * dt + sqdt * gtmp2
         end
     end
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, t, u,
         calculate_error = false
     )

src/functionmap.jl

@@ -37,7 +37,7 @@ export SimpleFunctionMap
 SciMLBase.isdiscrete(alg::SimpleFunctionMap) = true
 
 # ConstantCache version
-function DiffEqBase.__solve(
+function SciMLBase.__solve(
         prob::DiffEqBase.DiscreteProblem{uType, tupType, false},
         alg::SimpleFunctionMap;
         calculate_values = true, kwargs...
@@ -57,15 +57,15 @@ function DiffEqBase.__solve(
             u[i] = f(u[i - 1], p, t[i])
         end
     end
-    return sol = DiffEqBase.build_solution(
+    return sol = SciMLBase.build_solution(
         prob, alg, t, u, dense = false,
-        interp = DiffEqBase.ConstantInterpolation(t, u),
+        interp = SciMLBase.ConstantInterpolation(t, u),
         calculate_error = false
     )
 end
 
 # Cache version
-function DiffEqBase.__solve(
+function SciMLBase.__solve(
         prob::DiscreteProblem{uType, tupType, true},
         alg::SimpleFunctionMap;
         calculate_values = true, kwargs...
@@ -86,9 +86,9 @@ function DiffEqBase.__solve(
             f(u[i], u[i - 1], p, t[i])
         end
     end
-    return sol = DiffEqBase.build_solution(
+    return sol = SciMLBase.build_solution(
         prob, alg, t, u, dense = false,
-        interp = DiffEqBase.ConstantInterpolation(t, u),
+        interp = SciMLBase.ConstantInterpolation(t, u),
         calculate_error = false
     )
 end
@@ -97,7 +97,7 @@ end
 
 # Integrator version
 mutable struct DiscreteIntegrator{F, IIP, uType, tType, P, S} <:
-    DiffEqBase.DEIntegrator{SimpleFunctionMap, IIP, uType, tType}
+    SciMLBase.DEIntegrator{SimpleFunctionMap, IIP, uType, tType}
     f::F
     u::uType
     t::tType
@@ -108,12 +108,12 @@ mutable struct DiscreteIntegrator{F, IIP, uType, tType, P, S} <:
     tdir::tType
 end
 
-function DiffEqBase.__init(
+function SciMLBase.__init(
         prob::DiscreteProblem,
         alg::SimpleFunctionMap;
         kwargs...
     )
-    sol = DiffEqBase.__solve(prob, alg; calculate_values = false)
+    sol = SciMLBase.__solve(prob, alg; calculate_values = false)
     F = typeof(prob.f)
     IIP = isinplace(prob)
     uType = typeof(prob.u0)

src/rk4/gpurk4.jl

@@ -78,13 +78,13 @@ export GPUSimpleRK4
         us[i] = u
     end
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, SArray(us),
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )

src/rk4/looprk4.jl

@@ -47,7 +47,7 @@ export LoopRK4
 
 # Out-of-place
 # No caching, good for static arrays, bad for arrays
-@muladd function DiffEqBase.__solve(
+@muladd function SciMLBase.__solve(
         prob::ODEProblem{uType, tType, false},
         alg::LoopRK4;
         dt = error("dt is required for this algorithm"),
@@ -100,13 +100,13 @@ export LoopRK4
 
     !save_everystep && save_end && (us[end] = u)
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, us,
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )
@@ -115,7 +115,7 @@ end
 
 # In-place
 # Good for mutable objects like arrays
-# Use DiffEqBase.@.. for simd ivdep
+# Use @.. for simd ivdep
 @muladd function DiffEqBase.solve(
         prob::ODEProblem{uType, tType, true},
         alg::LoopRK4;
@@ -162,25 +162,25 @@ end
         uprev .= u
         t = ts[i]
         f(k1, u, p, t)
-        DiffEqBase.@.. u = uprev + dt * half * k1
+        @.. u = uprev + dt * half * k1
         f(k2, u, p, t + half * dt)
-        DiffEqBase.@.. u = uprev + dt * half * k2
+        @.. u = uprev + dt * half * k2
         f(k3, u, p, t + half * dt)
-        DiffEqBase.@.. u = uprev + dt * k3
+        @.. u = uprev + dt * k3
         f(k4, u, p, t + dt)
-        DiffEqBase.@.. u = uprev + dt * sixth * (k1 + 2k2 + 2k3 + k4)
+        @.. u = uprev + dt * sixth * (k1 + 2k2 + 2k3 + k4)
         save_everystep && (us[i] = copy(u))
     end
 
     !save_everystep && save_end && (us[end] = u)
 
-    sol = DiffEqBase.build_solution(
+    sol = SciMLBase.build_solution(
         prob, alg, ts, us,
         k = nothing, stats = nothing,
         calculate_error = false
     )
-    DiffEqBase.has_analytic(prob.f) &&
-        DiffEqBase.calculate_solution_errors!(
+    SciMLBase.has_analytic(prob.f) &&
+        SciMLBase.calculate_solution_errors!(
         sol; timeseries_errors = true,
         dense_errors = false
     )