Support DelayCoevolve

Project.toml

@@ -1,7 +1,7 @@
 name = "DelaySSAToolkit"
 uuid = "d39380a9-d0d7-4ae6-ae63-0e8d8b7efa9e"
 authors = ["Xiaoming Fu"]
-version = "0.2.3"
+version = "0.2.4"
 
 [deps]
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
@@ -18,7 +18,7 @@ StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 UnPack = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
 
 [compat]
-Catalyst = "12.0"
+    Catalyst = "12.0"
 DataStructures = "0.17, 0.18"
 DiffEqBase = "6.45"
 DocStringExtensions = "0.8, 0.9"
@@ -34,6 +34,9 @@ julia = "1.6, 1.7, 1.8"
 [extras]
 Catalyst = "479239e8-5488-4da2-87a7-35f2df7eef83"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [targets]
 test = ["Test"]

README.md

@@ -4,9 +4,9 @@
 |:-----------------:|:----------------:|:----------------:|
 | [![doc dev badge]][doc dev link] | [![ci badge]][ci link] [![cov badge]][cov link] | [![download badge]][download link]| -->
 
-| **Documentation** | **Build Status** |
-|:-----------------:|:----------------:|
-| [![doc dev badge]][doc dev link] | [![ci badge]][ci link] [![cov badge]][cov link] |
+| **Documentation** | **Build Status** | **Code Style** |
+|:-----------------:|:----------------:|:----------------:|
+| [![doc dev badge]][doc dev link] | [![ci badge]][ci link] [![cov badge]][cov link] | [![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
 
 [doc dev badge]: https://img.shields.io/badge/docs-dev-blue.svg
 [doc dev link]: https://palmtree2013.github.io/DelaySSAToolkit.jl/dev/

docs/make.jl

@@ -1,41 +1,39 @@
 using DelaySSAToolkit
 using Documenter
 
-DocMeta.setdocmeta!(DelaySSAToolkit, :DocTestSetup, :(using DelaySSAToolkit); recursive=true)
+DocMeta.setdocmeta!(DelaySSAToolkit, :DocTestSetup, :(using DelaySSAToolkit);
+                    recursive = true)
 
 makedocs(;
-    modules=[DelaySSAToolkit],
-    authors="Xiaoming Fu",
-    repo="https://github.com/palmtree2013/DelaySSAToolkit.jl/blob/{commit}{path}#{line}",
-    sitename="DelaySSAToolkit.jl",
-    format=Documenter.HTML(;
-        mathengine=Documenter.Writers.HTMLWriter.MathJax2(),
-        prettyurls=get(ENV, "CI", "false") == "true",
-        canonical="https://palmtree2013.github.io/DelaySSAToolkit.jl",
-        assets=String[],
-    ),
-    pages=[
-        "Home" => "index.md",
-        "Tutorials" => [
-            "tutorials/tutorials.md", 
-            "tutorials/bursty.md",
-            "tutorials/delay_degradation.md",
-            "tutorials/heterogeneous_delay.md",
-            "tutorials/delay_oscillator.md",
-            "tutorials/stochastic_delay.md",
-        ],
-        "Algorithm" => [
-            "algorithms/notations.md",      
-            "algorithms/delayrejection.md",      
-            "algorithms/delaydirect.md",
-            "algorithms/delaymnrm.md", 
-        ],
-        "Theory" => "theory.md",
-        "API" => "api.md",
-    ],
-)
+         modules = [DelaySSAToolkit],
+         authors = "Xiaoming Fu",
+         repo = "https://github.com/palmtree2013/DelaySSAToolkit.jl/blob/{commit}{path}#{line}",
+         sitename = "DelaySSAToolkit.jl",
+         format = Documenter.HTML(;
+                                  mathengine = Documenter.Writers.HTMLWriter.MathJax2(),
+                                  prettyurls = get(ENV, "CI", "false") == "true",
+                                  canonical = "https://palmtree2013.github.io/DelaySSAToolkit.jl",
+                                  assets = String[]),
+         pages = [
+             "Home" => "index.md",
+             "Tutorials" => [
+                 "tutorials/tutorials.md",
+                 "tutorials/bursty.md",
+                 "tutorials/delay_degradation.md",
+                 "tutorials/heterogeneous_delay.md",
+                 "tutorials/delay_oscillator.md",
+                 "tutorials/stochastic_delay.md",
+             ],
+             "Algorithm" => [
+                 "algorithms/notations.md",
+                 "algorithms/delayrejection.md",
+                 "algorithms/delaydirect.md",
+                 "algorithms/delaymnrm.md",
+             ],
+             "Theory" => "theory.md",
+             "API" => "api.md",
+         ])
 
 deploydocs(;
-    repo="github.com/palmtree2013/DelaySSAToolkit.jl",
-    devbranch="main",
-)
+           repo = "github.com/palmtree2013/DelaySSAToolkit.jl",
+           devbranch = "main")

docs/src/index.md

@@ -20,8 +20,8 @@ DelaySSAToolkit.jl is a tool developed on top of [JumpProcesses.jl](https://gith
 
 DelaySSAToolkit can be installed through the Julia package manager:
 ```julia
-]add DelaySSAToolkit
-using DelaySSAToolkit
+using Pkg
+Pkg.add("DelaySSAToolkit")
 ```
 and you might need to run
 ```julia

docs/src/tutorials/heterogeneous_delay.md

@@ -78,9 +78,6 @@ ensprob2 = EnsembleProblem(jprob, prob_func = prob_func)
 Note that a simulation of $10^4$ samples with very high production number (up to ~1000 for X and ~3000 for Y) only takes few minutes on a laptop:
 ```julia-repl
 julia> @time ens2 = solve(ensprob2, SSAStepper(), EnsembleThreads(), trajectories = 10^4)
-
- 78.925908 seconds (249.65 M allocations: 28.632 GiB, 6.60% gc time)
-EnsembleSolution Solution of length 10000 with uType
 ```
 Here we plot the histogram of the number of unfinished reactant $X$s in the delay channel.
 

examples/bursty.jl

@@ -9,66 +9,70 @@ begin # construct reaction network
     @parameters a b t
     @variables X(t)
     burst_sup = 30
-    rxs = [Reaction(a*b^i/(1+b)^(i+1),nothing,[X],nothing,[i]) for i in 1:burst_sup]
+    rxs = [Reaction(a * b^i / (1 + b)^(i + 1), nothing, [X], nothing, [i])
+           for i in 1:burst_sup]
     rxs = vcat(rxs)
-    @named rs = ReactionSystem(rxs,t,[X],[a,b])
+    @named rs = ReactionSystem(rxs, t, [X], [a, b])
 end
 
 # convert the ReactionSystem to a JumpSystem
-jumpsys = convert(JumpSystem, rs, combinatoric_ratelaws=false)
+jumpsys = convert(JumpSystem, rs, combinatoric_ratelaws = false)
 
 u0 = [0]
 de_chan0 = [[]]
-tf = 200.
-tspan = (0,tf)
+tf = 200.0
+tspan = (0, tf)
 ps = [0.0282, 3.46]
-dprob = DiscreteProblem(jumpsys,u0,tspan,ps)
-τ = 130.
+dprob = DiscreteProblem(jumpsys, u0, tspan, ps)
+τ = 130.0
 
 delay_trigger_affect! = []
 for i in 1:burst_sup
     push!(delay_trigger_affect!, function (integrator, rng)
-    append!(integrator.de_chan[1], fill(τ, i))
-    end)
+              append!(integrator.de_chan[1], fill(τ, i))
+          end)
 end
 delay_trigger_affect!
 delay_trigger = Dict([Pair(i, delay_trigger_affect![i]) for i in 1:burst_sup])
-delay_complete = Dict(1=>[1=>-1])
+delay_complete = Dict(1 => [1 => -1])
 delay_interrupt = Dict()
-alg = DelayRejection()
+# alg = DelayRejection()
+alg = DelayCoevolve()
 
 delayjumpset = DelayJumpSet(delay_trigger, delay_complete, delay_interrupt)
-jprob = DelayJumpProblem(jumpsys, dprob, alg, delayjumpset, de_chan0, save_positions=(true, true),  save_delay_channel = false)
+jprob = DelayJumpProblem(jumpsys, dprob, alg, delayjumpset, de_chan0,
+                         save_positions = (true, true), save_delay_channel = false)
 # saveat = 0:1:tf
 seed = 4
 @time sol = solve(jprob, SSAStepper(), seed = seed)
 
-
 ensprob = EnsembleProblem(jprob)
-@time ens = solve(ensprob, SSAStepper(), EnsembleSerial(), trajectories=1e5)
+@time ens = solve(ensprob, SSAStepper(), EnsembleSerial(), trajectories = 1e5)
 
 # Check with the exact probability distribution
 using TaylorSeries
-function taylor_coefficients(NT::Int,at_x,gen::Function)
+function taylor_coefficients(NT::Int, at_x, gen::Function)
     Q = zeros(NT)
-    taylor_gen = taylor_expand(u->gen(u),at_x,order=NT)
+    taylor_gen = taylor_expand(u -> gen(u), at_x, order = NT)
     for j in 1:NT
-        Q[j] = taylor_gen[j-1]
+        Q[j] = taylor_gen[j - 1]
     end
     return Q
 end
-function delay_bursty(params,NT::Int)
+function delay_bursty(params, NT::Int)
     a, b, τ, t = params
-    gen1(u) = exp(a*b*min(τ,t)*u/(1-b*u))
-    taylor_coefficients(NT,-1,gen1)
+    gen1(u) = exp(a * b * min(τ, t) * u / (1 - b * u))
+    taylor_coefficients(NT, -1, gen1)
 end
 
-
 using Catalyst.EnsembleAnalysis
-using Plots; theme(:vibrant)
+using Plots;
+theme(:vibrant);
 sol_end = componentwise_vectors_timepoint(ens, tf)
-histogram(sol_end,bins=0:1:60,normalize=:pdf, label = "Delay SSA",fillalpha = 0.6, linecolor = :orange)
+histogram(sol_end, bins = 0:1:60, normalize = :pdf, label = "Delay SSA", fillalpha = 0.6,
+          linecolor = :orange)
 
-sol_exact = delay_bursty([ps;130;200], 61)
-fig = plot!(0:60,sol_exact, linewidth = 3, label = "Exact solution", fmt=:svg, xlabel = "# of products", ylabel = "Probability")
+sol_exact = delay_bursty([ps; 130; 200], 61)
+fig = plot!(0:60, sol_exact, linewidth = 3, label = "Exact solution", fmt = :svg,
+            xlabel = "# of products", ylabel = "Probability")
 # savefig(fig, "docs/src/assets/bursty.svg")

examples/delay_degradation.jl

@@ -10,75 +10,75 @@
 # x_I(t)= 0<=t<=τ ? C*β/(a-γ)*((1-exp(-γ*t))/γ - (1-exp(-a*t))/a) : C*β/a*((1-exp(-γ*τ))/γ + exp(-a*t)*(1-exp(-(a-γ)τ))/(a-γ))
 # where a = β + γ
 
-
 using Catalyst
-using DelaySSAToolkit 
+using DelaySSAToolkit
 
 rn = @reaction_network begin
-   C, 0 --> Xₐ
-   γ, Xₐ --> 0
-   β, Xₐ --> Xᵢ 
-   γ, Xᵢ --> 0
+    C, 0 --> Xₐ
+    γ, Xₐ --> 0
+    β, Xₐ --> Xᵢ
+    γ, Xᵢ --> 0
 end C γ β
 
 jumpsys = convert(JumpSystem, rn, combinatoric_ratelaws = false)
 
 u0 = [0, 0]
 tf = 30
-saveat = .1
+saveat = 0.1
 de_chan0 = [[]]
-C, γ, β = [2., 0.1, 0.5]
+C, γ, β = [2.0, 0.1, 0.5]
 p = [C, γ, β]
-tspan = (0.,tf)
+tspan = (0.0, tf)
 # aggregatoralgo = DelayRejection()
 # aggregatoralgo = DelayMNRM()
 aggregatoralgo = DelayDirect()
 # aggregatoralgo = DelayDirectCR()
 dprob = DiscreteProblem(u0, tspan, p)
 
-τ = 15.
+τ = 15.0
 delay_trigger_affect! = function (integrator, rng)
-   append!(integrator.de_chan[1], τ)
+    append!(integrator.de_chan[1], τ)
 end
-delay_trigger = Dict(3=>delay_trigger_affect!)
-delay_complete = Dict(1=>[2=>-1]) 
+delay_trigger = Dict(3 => delay_trigger_affect!)
+delay_complete = Dict(1 => [2 => -1])
 delay_affect! = function (integrator, rng)
     i = rand(rng, 1:length(integrator.de_chan[1]))
-    deleteat!(integrator.de_chan[1],i)
+    deleteat!(integrator.de_chan[1], i)
 end
-delay_interrupt = Dict(4=>delay_affect!) 
-delaysets = DelayJumpSet(delay_trigger,delay_complete,delay_interrupt)
-djprob = DelayJumpProblem(jumpsys, dprob, aggregatoralgo,  delaysets, de_chan0, save_positions = (false, false), save_delay_channel =false)
-sol1 =@time solve(djprob, SSAStepper(), seed = 2, saveat =0.1)
-
-
+delay_interrupt = Dict(4 => delay_affect!)
+delaysets = DelayJumpSet(delay_trigger, delay_complete, delay_interrupt)
+djprob = DelayJumpProblem(jumpsys, dprob, aggregatoralgo, delaysets, de_chan0,
+                          save_positions = (false, false), save_delay_channel = false)
+sol1 = @time solve(djprob, SSAStepper(), seed = 2, saveat = 0.1)
 
 ens_prob = EnsembleProblem(djprob)
 Sample_size = Int(10^4)
-@time ens = solve(ens_prob, SSAStepper(),EnsembleThreads(),trajectories = Sample_size, saveat = .1)
+@time ens = solve(ens_prob, SSAStepper(), EnsembleThreads(), trajectories = Sample_size,
+                  saveat = 0.1)
 
-
-using Plots, DiffEqBase; theme(:vibrant)
-plot(ens[1], label = ["X_A" "X_I"], fmt =:svg)
+using Plots, DiffEqBase;
+theme(:vibrant);
+plot(ens[1], label = ["X_A" "X_I"], fmt = :svg)
 # savefig("docs/src/assets/delay_degradation1.svg")
 
-
-a = β + γ 
-x_A(t) = C/a*(1-exp(-a*t))
-x_I(t)= 0<=t<=τ ? C*β/(a-γ)*((1-exp(-γ*t))/γ - (1-exp(-a*t))/a) : C*β/a*((1-exp(-γ*τ))/γ + exp(-a*t)*(1-exp((a-γ)τ))/(a-γ))
-
+a = β + γ
+x_A(t) = C / a * (1 - exp(-a * t))
+function x_I(t)
+    0 <= t <= τ ? C * β / (a - γ) * ((1 - exp(-γ * t)) / γ - (1 - exp(-a * t)) / a) :
+    C * β / a * ((1 - exp(-γ * τ)) / γ + exp(-a * t) * (1 - exp((a - γ)τ)) / (a - γ))
+end
 
 using StatsBase
 using Catalyst.EnsembleAnalysis
-tsm(t) = Catalyst.EnsembleAnalysis.timepoint_mean(ens,t)
+tsm(t) = Catalyst.EnsembleAnalysis.timepoint_mean(ens, t)
 
 mean_A(t) = tsm(t)[1]
 mean_I(t) = tsm(t)[2]
 timestamps = 0:0.1:tf
-plot(timestamps,x_A.(timestamps),linewidth=3, label = "X_A Exact", xlabel = "Time", ylabel = "# of X_A")
-plot!(timestamps,mean_A.(timestamps),linewidth=3,line=:dash, label =  "X_A SSA")
-plot!(timestamps,x_I.(timestamps),linewidth=3, label = "X_I Exact")
-plot!(timestamps,mean_I.(timestamps),linewidth=3,line=:dash, legend = :topleft, label = "X_I SSA")
+plot(timestamps, x_A.(timestamps), linewidth = 3, label = "X_A Exact", xlabel = "Time",
+     ylabel = "# of X_A")
+plot!(timestamps, mean_A.(timestamps), linewidth = 3, line = :dash, label = "X_A SSA")
+plot!(timestamps, x_I.(timestamps), linewidth = 3, label = "X_I Exact")
+plot!(timestamps, mean_I.(timestamps), linewidth = 3, line = :dash, legend = :topleft,
+      label = "X_I SSA")
 # savefig("docs/src/assets/delay_degradation2.svg")
-
-