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Fix interaction between precompilation and runtimegeneratedfunctions #93

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merged 2 commits into from
Aug 20, 2022
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Fix interaction between precompilation and runtimegeneratedfunctions #93

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e4f4681
Fix interaction between precompilation and runtimegeneratedfunctions
ChrisRackauckas Aug 20, 2022
75380ea
version bumps
ChrisRackauckas Aug 20, 2022
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6 changes: 4 additions & 2 deletions lib/JumpProblemLibrary/Project.toml
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Original file line number Diff line number Diff line change
@@ -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"]
4 changes: 4 additions & 0 deletions lib/JumpProblemLibrary/src/JumpProblemLibrary.jl
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Original file line number Diff line number Diff line change
@@ -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
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6 changes: 4 additions & 2 deletions lib/ODEProblemLibrary/Project.toml
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Original file line number Diff line number Diff line change
@@ -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"
Expand All @@ -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"]
3 changes: 3 additions & 0 deletions lib/ODEProblemLibrary/src/ODEProblemLibrary.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,9 @@ using LinearAlgebra
using Markdown
using Random

import RuntimeGeneratedFunctions
RuntimeGeneratedFunctions.init(@__MODULE__)

Random.seed!(100)

#ODE Example Problems
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6 changes: 4 additions & 2 deletions lib/SDEProblemLibrary/Project.toml
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Original file line number Diff line number Diff line change
@@ -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"]
8 changes: 6 additions & 2 deletions lib/SDEProblemLibrary/src/SDEProblemLibrary.jl
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Original file line number Diff line number Diff line change
@@ -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,
Expand Down Expand Up @@ -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.
Expand Down