Merge branch 'master' into remove-parameterizedfunctions

Author: ChrisRackauckas

Project.toml

@@ -184,7 +184,6 @@ julia = "1.10"
 
 [extras]
 AlgebraicMultigrid = "2169fc97-5a83-5252-b627-83903c6c433c"
-Calculus = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
 DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
@@ -198,8 +197,6 @@ ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
 ODEProblemLibrary = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-PoissonRandom = "e409e4f3-bfea-5376-8464-e040bb5c01ab"
-Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecursiveFactorization = "f2c3362d-daeb-58d1-803e-2bc74f2840b4"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
@@ -214,4 +211,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["Calculus", "ComponentArrays", "Symbolics", "AlgebraicMultigrid", "IncompleteLU", "DiffEqCallbacks", "DifferentiationInterface", "DiffEqDevTools", "ODEProblemLibrary", "ElasticArrays", "ExplicitImports", "InteractiveUtils", "JLArrays", "PoissonRandom", "Printf", "Random", "ReverseDiff", "SafeTestsets", "SparseArrays", "Statistics", "StructArrays", "Test", "Unitful", "ModelingToolkit", "Pkg", "NLsolve", "RecursiveFactorization", "SparseConnectivityTracer", "SparseMatrixColorings"]
+test = ["ComponentArrays", "Symbolics", "AlgebraicMultigrid", "IncompleteLU", "DiffEqCallbacks", "DifferentiationInterface", "DiffEqDevTools", "ODEProblemLibrary", "ElasticArrays", "ExplicitImports", "InteractiveUtils", "JLArrays", "Random", "ReverseDiff", "SafeTestsets", "SparseArrays", "Statistics", "StructArrays", "Test", "Unitful", "ModelingToolkit", "Pkg", "NLsolve", "RecursiveFactorization", "SparseConnectivityTracer", "SparseMatrixColorings"]

test/enzyme/autodiff_events.jl

@@ -1,5 +1,5 @@
 using SciMLSensitivity
-using OrdinaryDiffEq, OrdinaryDiffEqCore, Calculus, Test
+using OrdinaryDiffEq, OrdinaryDiffEqCore, FiniteDiff, Test
 using Zygote
 
 function f(du, u, p, t)
@@ -26,7 +26,7 @@ function test_f(p)
     solve(_prob, Tsit5(), abstol = 1e-14, reltol = 1e-14, callback = cb,
     save_everystep = false).u[end]
 end
-findiff = Calculus.finite_difference_jacobian(test_f, p)
+findiff = FiniteDiff.finite_difference_jacobian(test_f, p)
 findiff
 
 using ForwardDiff

test/interface/ad_tests.jl

@@ -1,5 +1,5 @@
 using Test
-using OrdinaryDiffEq, OrdinaryDiffEqCore, Calculus, ForwardDiff, FiniteDiff, LinearAlgebra, ADTypes, DifferentiationInterface
+using OrdinaryDiffEq, OrdinaryDiffEqCore, ForwardDiff, FiniteDiff, LinearAlgebra, ADTypes, DifferentiationInterface
 
 function f(du, u, p, t)
     du[1] = -p[1]
@@ -21,7 +21,7 @@ for x in 0:0.001:5
     end
     p = [2.0, x]
     called = false
-    findiff = Calculus.finite_difference_jacobian(test_f, p)
+    findiff = FiniteDiff.finite_difference_jacobian(test_f, p)
     @test called
     called = false
     fordiff = ForwardDiff.jacobian(test_f, p)
@@ -48,7 +48,7 @@ for x in 2.1:0.001:5
         solve!(integrator).u[end]
     end
     p = [2.0, x]
-    findiff = Calculus.finite_difference_jacobian(test_f2, p)
+    findiff = FiniteDiff.finite_difference_jacobian(test_f2, p)
     @test called
     called = false
     fordiff = ForwardDiff.jacobian(test_f2, p)
@@ -70,7 +70,7 @@ function test_f2(p)
 end
 
 p = [2.0, x]
-findiff = Calculus.finite_difference_jacobian(test_f2,p)
+findiff = FiniteDiff.finite_difference_jacobian(test_f2,p)
 @test called
 called = false
 fordiff = ForwardDiff.jacobian(test_f2,p)
@@ -106,7 +106,7 @@ for x in 1.0:0.001:2.5
         solve!(integrator).u[end]
     end
 
-    findiff = Calculus.finite_difference_jacobian(test_lotka, p)
+    findiff = FiniteDiff.finite_difference_jacobian(test_lotka, p)
     @test called
     called = false
     fordiff = ForwardDiff.jacobian(test_lotka, p)

test/interface/enums.jl

@@ -1,4 +1,16 @@
-using OrdinaryDiffEq, PoissonRandom
+using OrdinaryDiffEq, Random
+
+# Simple Poisson random number generator using Knuth's algorithm
+function pois_rand(λ::Float64)
+    L = exp(-λ)
+    k = 0
+    p = 1.0
+    while p > L
+        k += 1
+        p *= rand()
+    end
+    return k - 1
+end
 
 function rate_to_proportion(r::Float64, t::Float64)
     1 - exp(-r * t)

test/regression/ode_dense_tests.jl

@@ -1,14 +1,14 @@
 using OrdinaryDiffEq, Test, DiffEqBase
 using OrdinaryDiffEqCore
-using ForwardDiff, Printf
+using ForwardDiff
 import ODEProblemLibrary: prob_ode_linear,
                           prob_ode_2Dlinear,
                           prob_ode_bigfloatlinear, prob_ode_bigfloat2Dlinear
 # use `PRINT_TESTS = true` to print the tests, including results
 const PRINT_TESTS = false
 print_results(x) =
     if PRINT_TESTS
-        @printf("%s \n", x)
+        println(x)
     end
 
 # points and storage arrays used in the interpolation tests