Merge pull request #144 from SciML/ChrisRackauckas-patch-4

Fix depwarns

Author: ChrisRackauckas

Project.toml

@@ -36,7 +36,7 @@ RecipesBase = "1"
 RecursiveArrayTools = "2, 3"
 RootedTrees = "2"
 SDEProblemLibrary = "0.1"
-SciMLBase = "2"
+SciMLBase = "2.52.2"
 Statistics = "1"
 StochasticDelayDiffEq = "1"
 StochasticDiffEq = "6"

src/DiffEqDevTools.jl

@@ -1,6 +1,7 @@
 module DiffEqDevTools
 
 using DiffEqBase, RecipesBase, RecursiveArrayTools, DiffEqNoiseProcess, StructArrays
+using NLsolve, LinearAlgebra, RootedTrees
 
 using LinearAlgebra, Distributed
 

src/benchmark.jl

@@ -284,7 +284,8 @@ function WorkPrecision(prob, alg, abstols, reltols, dts = nothing;
                 end
             else
                 # Unsuccessful retcode, give NaN time
-                errors[i] = Dict(:l∞ => NaN, :L2 => NaN, :final => NaN, :l2 => NaN, :L∞ => NaN)
+                errors[i] = Dict(
+                    :l∞ => NaN, :L2 => NaN, :final => NaN, :l2 => NaN, :L∞ => NaN)
                 times[i] = NaN
             end
         end

src/tableau_info.jl

@@ -1,4 +1,3 @@
-using NLsolve, LinearAlgebra, RootedTrees
 """
 `Base.length(tab::ODERKTableau)`
 
@@ -48,7 +47,7 @@ function RootedTrees.residual_order_condition(tab::ODERKTableau, order::Int,
         end
     else
         resid = mapreduce(reducer, RootedTreeIterator(order)) do t
-            mapper(residual_order_condition(t, A, b, c))
+            mapper(residual_order_condition(t, RungeKuttaMethod(A, b, c)))
         end
     end
     return resid

test/analyticless_convergence_tests.jl

@@ -74,7 +74,7 @@ seed = 100
 Random.seed!(seed)
 seeds = rand(UInt, numtraj)
 ensemble_prob = EnsembleProblem(prob;
-    output_func = (sol, i) -> (h2(sol[end][1]), false),
+    output_func = (sol, i) -> (h2(sol[1, end]), false),
     prob_func = prob_func)
 sim = test_convergence(dts, ensemble_prob, DRI1(), save_everystep = false,
     trajectories = numtraj, save_start = false, adaptive = false,

test/analyticless_stochastic_wp.jl

@@ -74,7 +74,7 @@ seed = 100
 Random.seed!(seed)
 seeds = rand(UInt, numtraj)
 ensemble_prob = EnsembleProblem(prob;
-    output_func = (sol, i) -> (h2(sol[end][1]), false),
+    output_func = (sol, i) -> (h2(sol[1, end]), false),
     prob_func = prob_func)
 
 reltols = 1.0 ./ 4.0 .^ (1:4)