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Merge pull request #112 from shahriariravanian/master
README updated with using DifferentialEquations.jl instead of OrdinaryDiffEq.jl
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Project.toml

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name = "CellMLToolkit"
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uuid = "03cb29e0-1ef4-4721-aa24-cf58a006576f"
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authors = ["Shahriar Iravanian <siravan@svtsim.com>"]
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version = "2.11.0"
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version = "2.11.1"
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[deps]
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EzXML = "8f5d6c58-4d21-5cfd-889c-e3ad7ee6a615"

README.md

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```Julia
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sol = solve(prob, dtmax=1.0)
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plot(sol, idxs=8) # 8 is the index of membrane₊V
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plot(sol, idxs=7) # 7 is the index of membrane₊V
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```
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For the next example, we chose a complex model to stress the ODE solvers: [the O'Hara-Rudy left ventricular model](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002061). This model has 49 state variables, is very stiff, and is prone to oscillation. In the previous versions of this document, we used `CVODE_BDF` from the Sundial suite (`using Sundials`) to solve this problem. Fortunatelly, DifferentialEquations.jl has advanced signigficantly such that an efficient and pure Julia solution to the O'Hara-Rudy model is possible.
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```julia
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ml = CellModel("models/noble_1962/Noble_1962.cellml")
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prob = ODEProblem(ml, tspan)
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sol = solve(prob, TRBDF2(), dtmax = 0.5)
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sol = solve(prob, dtmax=0.5)
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```
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Note that the syntax is exactly the same as before. However, the list of the imported files are printed during `CellModel` generation:
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Same as before, we can plot the output as
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```julia
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plot(sol, idxs = 2)
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plot(sol, idxs=2)
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```
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![](figures/noble_1962.png)

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