Merge pull request #93 from SciML/runtimegenerated

Fix interaction between precompilation and runtimegeneratedfunctions

Author: ChrisRackauckas

lib/JumpProblemLibrary/Project.toml

@@ -1,19 +1,21 @@
 name = "JumpProblemLibrary"
 uuid = "faf0f6d7-8cee-47cb-b27c-1eb80cef534e"
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 Catalyst = "479239e8-5488-4da2-87a7-35f2df7eef83"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
+RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"
 
 [compat]
 Aqua = "0.5"
 Catalyst = "11, 12"
 DiffEqBase = "6"
+RuntimeGeneratedFunctions = "0.5"
 julia = "1.6"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 
 [targets]
-test = ["Aqua"]
+test = ["Aqua"]

lib/JumpProblemLibrary/src/JumpProblemLibrary.jl

@@ -1,6 +1,10 @@
 module JumpProblemLibrary
 
 using DiffEqBase, Catalyst
+
+import RuntimeGeneratedFunctions
+RuntimeGeneratedFunctions.init(@__MODULE__)
+
 # Jump Example Problems
 export prob_jump_dnarepressor, prob_jump_constproduct, prob_jump_nonlinrxs,
 # examples mixing mass action and constant rate jumps

lib/ODEProblemLibrary/Project.toml

@@ -1,6 +1,6 @@
 name = "ODEProblemLibrary"
 uuid = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
@@ -10,17 +10,19 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"
 
 [compat]
 Aqua = "0.5"
 DiffEqBase = "6"
 DiffEqOperators = "4"
 Latexify = "0.15"
 ModelingToolkit = "7,8"
+RuntimeGeneratedFunctions = "0.5"
 julia = "1.6"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 
 [targets]
-test = ["Aqua"]
+test = ["Aqua"]

lib/ODEProblemLibrary/src/ODEProblemLibrary.jl

@@ -9,6 +9,9 @@ using LinearAlgebra
 using Markdown
 using Random
 
+import RuntimeGeneratedFunctions
+RuntimeGeneratedFunctions.init(@__MODULE__)
+
 Random.seed!(100)
 
 #ODE Example Problems

lib/SDEProblemLibrary/Project.toml

@@ -1,20 +1,22 @@
 name = "SDEProblemLibrary"
 uuid = "c72e72a9-a271-4b2b-8966-303ed956772e"
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 Catalyst = "479239e8-5488-4da2-87a7-35f2df7eef83"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
+RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"
 
 [compat]
 Aqua = "0.5"
 Catalyst = "11, 12"
 DiffEqBase = "6"
+RuntimeGeneratedFunctions = "0.5"
 julia = "1.6"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 
 [targets]
-test = ["Aqua"]
+test = ["Aqua"]

lib/SDEProblemLibrary/src/SDEProblemLibrary.jl

@@ -1,6 +1,10 @@
 module SDEProblemLibrary
 
 using DiffEqBase, Catalyst, Markdown
+
+import RuntimeGeneratedFunctions
+RuntimeGeneratedFunctions.init(@__MODULE__)
+
 #SDE Example Problems
 export prob_sde_wave, prob_sde_linear, prob_sde_cubic, prob_sde_2Dlinear,
        prob_sde_lorenz, prob_sde_2Dlinear, prob_sde_additive,
@@ -159,8 +163,8 @@ oval2ModelExample(;largeFluctuations=false,useBigs=false,noiseLevel=1)
 A function which generates the Oval2 Epithelial-Mesenchymal Transition model
 from:
 
-Rackauckas, C., & Nie, Q. (2017). Adaptive methods for stochastic differential equations 
-via natural embeddings and rejection sampling with memory. Discrete and continuous 
+Rackauckas, C., & Nie, Q. (2017). Adaptive methods for stochastic differential equations
+via natural embeddings and rejection sampling with memory. Discrete and continuous
 dynamical systems. Series B, 22(7), 2731.
 
 19 SDEs which are only stiff during transitions between biological states.