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ver 2.4.3
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@shahriariravanian
shahriariravanian authored Apr 18, 2021
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2 changes: 1 addition & 1 deletion Project.toml
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name = "CellMLToolkit"
uuid = "03cb29e0-1ef4-4721-aa24-cf58a006576f"
authors = ["Shahriar Iravanian <[email protected]>"]
version = "2.4.2"
version = "2.4.3"

[deps]
EzXML = "8f5d6c58-4d21-5cfd-889c-e3ad7ee6a615"
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38 changes: 35 additions & 3 deletions README.md
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Expand Up @@ -28,7 +28,7 @@ To install, run
plot(sol, vars=(1,3))
```

Note that `model` is a directory of the CellMLToolkit package. You can find its path as
Note that `model` is a directory of the CellMLToolkit package. You can find its path as

```Julia
model_root = joinpath(splitdir(pathof(CellMLToolkit))[1], "..", "models")
Expand All @@ -41,7 +41,7 @@ and then
prob = read_cellml(model_path, (0,100.0))
```

# Tutorial
## Tutorial

The models directory contains a few CellML model examples. Let's start with a simple one, the famous Lorenz equations!

Expand Down Expand Up @@ -145,7 +145,7 @@ The rest is the same as before.
plot(sol, vars=8) # 8 is the index of membrane₊V
```

For the last 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. The best solver for this model is `CVODE_BDF` from the Sundial suite.
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. The best solver for this model is `CVODE_BDF` from the Sundial suite.

```Julia
using Sundials
Expand All @@ -158,3 +158,35 @@ For the last example, we chose a complex model to stress the ODE solvers: [the O
```

![](figures/ohara_rudy.png)

## Multi-file Models (Import)

CellML specification allows for multi-file models. In these models, the top level CellML XML file imports components from other CellML files, which in turn may import from other files. CellMLToolkit supports this functionality. It assumes that *the top-level file and all the imported files reside in the same directory*. `models/noble_1962` contained one such example:

```julia
ml = CellModel("models/noble_1962/Noble_1962.cellml")
prob = ODEProblem(ml, tspan)
sol = solve(prob, TRBDF2(), dtmax=0.5)
```

Note that the syntax is exactly the same as before. However, the list of the imported files are printed during `CellModel` generation:

```
[ Info: importing Noble62_Na_channel.cellml
[ Info: importing Noble62_units.cellml
[ Info: importing Noble62_K_channel.cellml
[ Info: importing Noble62_units.cellml
[ Info: importing Noble62_L_channel.cellml
[ Info: importing Noble62_units.cellml
[ Info: importing Noble62_units.cellml
[ Info: importing Noble62_parameters.cellml
[ Info: importing Noble62_units.cellml
```

Same as before, we can plot the output as

```julia
plot(sol, vars=2)
```

![](figures/noble_1962.png)
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60 changes: 60 additions & 0 deletions models/noble_1962/BlueSkyCatastrophy.cellml
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<?xml version='1.0'?>
<model name="van_der_pol_model" xmlns="http://www.cellml.org/cellml/1.1#" xmlns:cellml="http://www.cellml.org/cellml/1.1#">
<component name="main">
<variable initial_value="0" name="t" units="dimensionless"/>
<variable initial_value="0.9" name="x" units="dimensionless"/>
<variable initial_value="0.4" name="y" units="dimensionless"/>
<variable initial_value="0.2645" name="A" units="dimensionless"/>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<apply>
<eq/>
<apply>
<diff/>
<bvar>
<ci>t</ci>
</bvar>
<ci>x</ci>
</apply>
<ci>y</ci>
</apply>
<apply>
<eq/>
<apply>
<diff/>
<bvar>
<ci>t</ci>
</bvar>
<ci>y</ci>
</apply>
<apply>
<plus/>
<apply>
<minus/>
<apply>
<minus/>
<ci>x</ci>
<apply>
<power/>
<ci>x</ci>
<cn cellml:units="dimensionless">3</cn>
</apply>
</apply>
<apply>
<times/>
<cn cellml:units="dimensionless">0.25</cn>
<ci>y</ci>
</apply>
</apply>
<apply>
<times/>
<ci>A</ci>
<apply>
<sin/>
<ci>t</ci>
</apply>
</apply>
</apply>
</apply>
</math>
</component>
</model>
84 changes: 84 additions & 0 deletions models/noble_1962/BlueSkyCatastrophy.sedml
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<?xml version='1.0' encoding='UTF-8'?>
<sedML level="1" version="2" xmlns="http://sed-ml.org/sed-ml/level1/version2" xmlns:cellml="http://www.cellml.org/cellml/1.1#">
<listOfSimulations>
<uniformTimeCourse id="simulation1" initialTime="0" numberOfPoints="50000" outputEndTime="500" outputStartTime="0">
<algorithm kisaoID="KISAO:0000019">
<listOfAlgorithmParameters>
<algorithmParameter kisaoID="KISAO:0000211" value="1e-07"/>
<algorithmParameter kisaoID="KISAO:0000475" value="BDF"/>
<algorithmParameter kisaoID="KISAO:0000481" value="true"/>
<algorithmParameter kisaoID="KISAO:0000476" value="Newton"/>
<algorithmParameter kisaoID="KISAO:0000477" value="Dense"/>
<algorithmParameter kisaoID="KISAO:0000480" value="0"/>
<algorithmParameter kisaoID="KISAO:0000415" value="500"/>
<algorithmParameter kisaoID="KISAO:0000467" value="0"/>
<algorithmParameter kisaoID="KISAO:0000478" value="Banded"/>
<algorithmParameter kisaoID="KISAO:0000209" value="1e-07"/>
<algorithmParameter kisaoID="KISAO:0000479" value="0"/>
</listOfAlgorithmParameters>
</algorithm>
</uniformTimeCourse>
</listOfSimulations>
<listOfModels>
<model id="model" language="urn:sedml:language:cellml.1_1" source="BlueSkyCatastrophy.cellml"/>
</listOfModels>
<listOfTasks>
<repeatedTask id="repeatedTask" range="once" resetModel="true">
<listOfRanges>
<vectorRange id="once">
<value> 1 </value>
</vectorRange>
</listOfRanges>
<listOfSubTasks>
<subTask order="1" task="task1"/>
</listOfSubTasks>
</repeatedTask>
<task id="task1" modelReference="model" simulationReference="simulation1"/>
</listOfTasks>
<listOfDataGenerators>
<dataGenerator id="xDataGenerator1_1">
<listOfVariables>
<variable id="xVariable1_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='t']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> xVariable1_1 </ci>
</math>
</dataGenerator>
<dataGenerator id="yDataGenerator1_1">
<listOfVariables>
<variable id="yVariable1_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='x']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> yVariable1_1 </ci>
</math>
</dataGenerator>
<dataGenerator id="xDataGenerator2_1">
<listOfVariables>
<variable id="xVariable2_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='x']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> xVariable2_1 </ci>
</math>
</dataGenerator>
<dataGenerator id="yDataGenerator2_1">
<listOfVariables>
<variable id="yVariable2_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='y']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> yVariable2_1 </ci>
</math>
</dataGenerator>
</listOfDataGenerators>
<listOfOutputs>
<plot2D id="plot1">
<listOfCurves>
<curve id="curve1_1" logX="false" logY="false" xDataReference="xDataGenerator1_1" yDataReference="yDataGenerator1_1"/>
</listOfCurves>
</plot2D>
<plot2D id="plot2">
<listOfCurves>
<curve id="curve2_1" logX="false" logY="false" xDataReference="xDataGenerator2_1" yDataReference="yDataGenerator2_1"/>
</listOfCurves>
</plot2D>
</listOfOutputs>
</sedML>
33 changes: 33 additions & 0 deletions models/noble_1962/Firstorder.cellml
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<?xml version='1.0'?>
<model name="first_order_model" xmlns="http://www.cellml.org/cellml/1.1#" xmlns:cellml="http://www.cellml.org/cellml/1.1#">
<component name="main">
<variable initial_value="0" name="t" units="dimensionless"/>
<variable initial_value="5" name="y" units="dimensionless"/>
<variable initial_value="1" name="a" units="dimensionless"/>
<variable initial_value="2" name="b" units="dimensionless"/>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<apply>
<eq/>
<apply>
<diff/>
<bvar>
<ci>t</ci>
</bvar>
<ci>y</ci>
</apply>
<apply>
<plus/>
<apply>
<times/>
<apply>
<minus/>
<ci>a</ci>
</apply>
<ci>y</ci>
</apply>
<ci>b</ci>
</apply>
</apply>
</math>
</component>
</model>
4 changes: 4 additions & 0 deletions models/noble_1962/Firstorder.rst
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Exponential decay: A simple first order ODE
-------------------------------------------

Used as the simplest example of a first order differential equation, this model consists of a `single equation <Firstorder.cellml/cellml_math>`_. One of the simulation experiments for this model described in the tutorial can be obtained by loading the `corresponding SED-ML document <Firstorder.sedml>`__ into OpenCOR and executing the simulation - which can be achived by choosing the **Launch with OpenCOR** link from the *Views Available* listing.
63 changes: 63 additions & 0 deletions models/noble_1962/Firstorder.sedml
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<?xml version='1.0' encoding='UTF-8'?>
<sedML level="1" version="2" xmlns="http://sed-ml.org/sed-ml/level1/version2" xmlns:cellml="http://www.cellml.org/cellml/1.1#">
<listOfSimulations>
<uniformTimeCourse id="simulation1" initialTime="0" numberOfPoints="100" outputEndTime="10" outputStartTime="0">
<algorithm kisaoID="KISAO:0000019">
<listOfAlgorithmParameters>
<algorithmParameter kisaoID="KISAO:0000211" value="1e-07"/>
<algorithmParameter kisaoID="KISAO:0000475" value="BDF"/>
<algorithmParameter kisaoID="KISAO:0000481" value="true"/>
<algorithmParameter kisaoID="KISAO:0000476" value="Newton"/>
<algorithmParameter kisaoID="KISAO:0000477" value="Dense"/>
<algorithmParameter kisaoID="KISAO:0000480" value="0"/>
<algorithmParameter kisaoID="KISAO:0000415" value="500"/>
<algorithmParameter kisaoID="KISAO:0000467" value="0"/>
<algorithmParameter kisaoID="KISAO:0000478" value="Banded"/>
<algorithmParameter kisaoID="KISAO:0000209" value="1e-07"/>
<algorithmParameter kisaoID="KISAO:0000479" value="0"/>
</listOfAlgorithmParameters>
</algorithm>
</uniformTimeCourse>
</listOfSimulations>
<listOfModels>
<model id="model" language="urn:sedml:language:cellml.1_1" source="Firstorder.cellml"/>
</listOfModels>
<listOfTasks>
<repeatedTask id="repeatedTask" range="once" resetModel="true">
<listOfRanges>
<vectorRange id="once">
<value> 1 </value>
</vectorRange>
</listOfRanges>
<listOfSubTasks>
<subTask order="1" task="task1"/>
</listOfSubTasks>
</repeatedTask>
<task id="task1" modelReference="model" simulationReference="simulation1"/>
</listOfTasks>
<listOfDataGenerators>
<dataGenerator id="xDataGenerator1_1">
<listOfVariables>
<variable id="xVariable1_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='t']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> xVariable1_1 </ci>
</math>
</dataGenerator>
<dataGenerator id="yDataGenerator1_1">
<listOfVariables>
<variable id="yVariable1_1" target="/cellml:model/cellml:component[@name='main']/cellml:variable[@name='y']" taskReference="repeatedTask"/>
</listOfVariables>
<math xmlns="http://www.w3.org/1998/Math/MathML">
<ci> yVariable1_1 </ci>
</math>
</dataGenerator>
</listOfDataGenerators>
<listOfOutputs>
<plot2D id="plot1">
<listOfCurves>
<curve id="curve1_1" logX="false" logY="false" xDataReference="xDataGenerator1_1" yDataReference="yDataGenerator1_1"/>
</listOfCurves>
</plot2D>
</listOfOutputs>
</sedML>
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Registration pull request created: JuliaRegistries/General/34646

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v2.4.3 -m "<description of version>" fd8495394c6fa757c0302dc48559203a6d7c2e44
git push origin v2.4.3

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