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using ModelingToolkit
using OrdinaryDiffEq, SteadyStateDiffEq
using Plots
using Model
Plots.default(lw=2)
@time "Build system" sys = Model.DEFAULT_SYS
@time "Build problem" sprob = SteadyStateProblem(sys, [])
@time "Solve problem" sol = solve(sprob, DynamicSS(KenCarp47()); abstol=1e-10, reltol=1e-10)
Build system: 0.000002 seconds
Build problem: 12.555432 seconds (13.41 M allocations: 952.779 MiB, 1.63% gc time, 98.53% compilation time: 4% of which was recompilation)
Solve problem: 9.293772 seconds (12.92 M allocations: 844.068 MiB, 5.87% gc time, 99.13% compilation time)
retcode: Success u: 75-element Vector{Float64}: 757.9282315861218 757.7646859421972 0.0009535254056096317 0.14578702763201826 0.0005627036519698699 0.001768090697103198 0.0019545972581952735 0.003025386116134377 0.0023122662341174545 0.9995209545010643 ⋮ 0.12243060253930682 0.12243060407063161 0.12243060564085818 0.12243060725202252 0.1224305602228213 0.12243060890629408 152559.7136489887 12237.348171129053 -67.45826337271653
for (k, v) in zip(unknowns(sys), sol.u)
    println(k, " => ", v, ",")
end
CaNSR(t) => 757.9282315861218,
CaJSR(t) => 757.7646859421972,
PO1RyR(t) => 0.0009535254056096317,
i_y(t) => 0.14578702763201826,
i_IK(t) => 0.0005627036519698699,
i_OK(t) => 0.001768090697103198,
i_CK2(t) => 0.0019545972581952735,
i_CK1(t) => 0.003025386116134377,
i_nKs(t) => 0.0023122662341174545,
i_sslow(t) => 0.9995209545010643,
i_s(t) => 0.9995209402008561,
i_r(t) => 0.007692812653128095,
i_Naj(t) => 0.4556441901647272,
i_Nah(t) => 0.31774891872433614,
i_Nam(t) => 0.02591396876175054,
i_g(t) => 0.5604636703338302,
i_b(t) => 0.003899541794344153,
i_fca(t) => 1.003473703497754,
i_f(t) => 0.9997191635134144,
i_d(t) => 0.00039844738179364776,
CaMKOX(t) => 0.0,
CaMKAOX(t) => 0.0,
CaMKA2(t) => 0.0004532200743927141,
CaMKA(t) => 0.0018124733089989935,
CaMKPOX(t) => 0.0,
CaMKP(t) => 0.0008811854434457344,
CaMKBOX(t) => 0.0,
CaMKB(t) => 0.008031622682517092,
(Cai(t))[43] => 0.1224305610672459,
(Cai(t))[42] => 0.12243056191859003,
(Cai(t))[41] => 0.12243056277715343,
(Cai(t))[40] => 0.1224305636432478,
(Cai(t))[39] => 0.12243056451719743,
(Cai(t))[38] => 0.12243056539933989,
(Cai(t))[37] => 0.12243056629002663,
(Cai(t))[36] => 0.1224305671896238,
(Cai(t))[35] => 0.12243056809851288,
(Cai(t))[34] => 0.12243056901709168,
(Cai(t))[33] => 0.12243056994577506,
(Cai(t))[32] => 0.12243057088499598,
(Cai(t))[31] => 0.1224305718352064,
(Cai(t))[30] => 0.12243057279687834,
(Cai(t))[29] => 0.12243057377050509,
(Cai(t))[28] => 0.12243057475660234,
(Cai(t))[27] => 0.1224305757557095,
(Cai(t))[26] => 0.12243057676839106,
(Cai(t))[25] => 0.12243057779523811,
(Cai(t))[24] => 0.12243057883686985,
(Cai(t))[23] => 0.12243057989393535,
(Cai(t))[22] => 0.12243058096711536,
(Cai(t))[21] => 0.12243058205712422,
(Cai(t))[20] => 0.122430583164712,
(Cai(t))[19] => 0.12243058429066676,
(Cai(t))[18] => 0.12243058543581699,
(Cai(t))[17] => 0.12243058660103417,
(Cai(t))[16] => 0.12243058778723571,
(Cai(t))[15] => 0.12243058899538795,
(Cai(t))[14] => 0.12243059022650937,
(Cai(t))[13] => 0.1224305914816744,
(Cai(t))[12] => 0.12243059276201708,
(Cai(t))[11] => 0.12243059406873534,
(Cai(t))[10] => 0.1224305954030956,
(Cai(t))[9] => 0.1224305967664377,
(Cai(t))[8] => 0.12243059816018023,
(Cai(t))[7] => 0.12243059958582662,
(Cai(t))[6] => 0.12243060104497128,
(Cai(t))[5] => 0.12243060253930682,
(Cai(t))[4] => 0.12243060407063161,
(Cai(t))[3] => 0.12243060564085818,
(Cai(t))[2] => 0.12243060725202252,
(Cai(t))[44] => 0.1224305602228213,
(Cai(t))[1] => 0.12243060890629408,
k_i(t) => 152559.7136489887,
na_i(t) => 12237.348171129053,
vm(t) => -67.45826337271653,

This notebook was generated using Literate.jl.