Documentation for Release 2024.1

Solving Odes

This tutorial is automatically generated from TestSolvingOdesTutorial.hpp at revision 8011c551be09. Note that the code is given in full at the bottom of the page.

In this tutorial we show how Chaste can be used to solve an ODE system

The following header files need to be included. First we include the header needed to define this class as a test suite.

#include <cxxtest/TestSuite.h>

In some early versions of Boost this file has to be included first so that the name of the ODE solver used can be written to result files.

#include "CheckpointArchiveTypes.hpp"

We will use a simple forward Euler solver to solve the ODE, so the following needs to be included.

#include "EulerIvpOdeSolver.hpp"

All the ODE solvers take in a concrete ODE system class, which is user-defined and must inherit from the following class, which defines an ODE interface.

#include "AbstractOdeSystem.hpp"

In order to define useful information about the ODE system conveniently, such as the names and units of variables, and suggested initial conditions, we need the following header.

#include "OdeSystemInformation.hpp"

This test doesn’t support being run on multiple processes, so we need this header to prevent race conditions when writing files.

#include "FakePetscSetup.hpp"

Defining the ODE classes

Let us solve the ODE $\frac{dy}{dt} = y^2 +t^2$, with $y(0) = 1$. To do so, we have to define our own ODE class, inheriting from AbstractOdeSystem, which implements the EvaluateYDerivatives() method.

class MyOde : public AbstractOdeSystem
{
public:

The constructor does very little. It calls the base constructor, passing the number of state variables in the ODE system (here, 1, i.e. y is a 1d vector). It also sets the object to use to retrieve system information (see later).

    MyOde() : AbstractOdeSystem(1)
    {
        mpSystemInfo = OdeSystemInformation<MyOde>::Instance();
    }

The ODE solvers will repeatedly call a method called EvaluateYDerivatives, which needs to be implemented in this concrete class. This takes in the time, a std::vector of y values (in this case, of size 1), and a reference to a std::vector in which the derivative(s) should be filled in by the method…

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {

…so we set rDY[0] to be $y^2 + t^2$.

        rDY[0] = rY[0]*rY[0] + time*time;
    }
};

The following template specialisation defines the information for this ODE system. Note that we use the ODE system class that we have just defined as a template parameter

template<>
void OdeSystemInformation<MyOde>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(0.0);

    this->mInitialised = true;
}

That would be all that is needed to solve this ODE. However, rather than solving up to a fixed time, suppose we wanted to solve until some function of y (and t) reached a certain value, e.g. let’s say we wanted to solve the ODE until y reached 2.5. To do this, we have to define a stopping event, by overriding the method CalculateStoppingEvent from AbstractOdeSystem. For this, let us define a new class, inheriting from the above class (i.e. representing the same ODE) but with a stopping event defined.

Note that we do not define separate ODE system information for this class - it uses that defined in the base class MyOde, since it represents the same ODE.

class MyOdeWithStoppingEvent : public MyOde
{
public:

All we have to do is implement the following function. This is defined in the base class (AbstractOdeSystem), where it always returns false, and here we override it to return true if $y \geq 2.5$

    bool CalculateStoppingEvent(double time, const std::vector<double>& rY)
    {
        return (rY[0]>=2.5);
    }
};

The following class will make more sense when solving with state variables is discussed. It is another ODE class which sets up a ‘state variable’. Note that this is done in the constructor, and the EvaluateYDerivatives method is identical to before.

class MyOdeUsingStateVariables : public AbstractOdeSystem
{
public:
    MyOdeUsingStateVariables() : AbstractOdeSystem(1)
    {
        mpSystemInfo = OdeSystemInformation<MyOdeUsingStateVariables>::Instance();
        mStateVariables.push_back(1.0);
    }

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {
        rDY[0] = rY[0]*rY[0] + time*time;
    }
};

This time we do need to define the ODE system information.

template<>
void OdeSystemInformation<MyOdeUsingStateVariables>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(1.0);

    this->mInitialised = true;
}

This class is another simple ODE class, just as an example of how a 2d ODE is solved. Here we solve the ODE $\frac{dy_1}{dt} = y_2, \frac{dy_2}{dt} = (y_1)^2$ (which represents the second-order ODE $\frac{d^2y}{dt^2} = y^2$).

class My2dOde : public AbstractOdeSystem
{
public:
    My2dOde() : AbstractOdeSystem(2)
    {
        mpSystemInfo = OdeSystemInformation<My2dOde>::Instance();
    }

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {
        rDY[0] = rY[1];
        rDY[1] = rY[0]*rY[0];
    }
};

Again we need to define the ODE system information.

template<>
void OdeSystemInformation<My2dOde>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(1.0);

    this->mVariableNames.push_back("ydot");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(0.0);

    this->mInitialised = true;
}

The Tests

Standard ODE solving

Now we can define the test, in which the ODEs are solved.

class TestSolvingOdesTutorial: public CxxTest::TestSuite
{
public:
    void TestSolvingOdes()
    {

First, create an instance of the ODE class to be solved.

        MyOde my_ode;

Next, create a solver.

        EulerIvpOdeSolver euler_solver;

We will need to provide an initial condition, which needs to be a std::vector.

        std::vector<double> initial_condition;
        initial_condition.push_back(1.0);

Then, just call Solve, passing in a pointer to the ODE, the initial condition, the start time, end time, the solving timestep, and sampling timestep (how often we want the solution stored in the returned OdeSolution object). Here we solve from 0 to 1, with a timestep of 0.01 but a sampling timestep of 0.1. The return value is an object of type OdeSolution (which is basically just a list of times and solutions).

        OdeSolution solutions = euler_solver.Solve(&my_ode, initial_condition, 0, 1, 0.01, 0.1);

Let’s look at the results, which can be obtained from the OdeSolution object using the methods rGetTimes() and rGetSolutions(), which return a std::vector and a std::vector of std::vectors respectively.

        for (unsigned i=0; i<solutions.rGetTimes().size(); i++)
        {

The [0] here is because we are getting the zeroth component of y (a 1-dimensional vector).

            std::cout << solutions.rGetTimes()[i] << " " << solutions.rGetSolutions()[i][0] << "\n";
        }

Alternatively, we can print the solution directly to a file, using the WriteToFile method on the OdeSolution class.

        solutions.WriteToFile("SolvingOdesTutorial", "my_ode_solution", "sec");

Two files are written

my_ode_solution.dat contains the results (a header line, then one column for time and one column per variable)
my_ode_solution.info contains information for reading the data back, a line about the ODE solver ("ODE SOLVER: EulerIvpOdeSolver") and provenance information.

We can see from the printed out results that y goes above 2.5 somewhere just before 0.6. To solve only up until y=2.5, we can solve the ODE that has the stopping event defined, using the same solver as before.

        MyOdeWithStoppingEvent my_ode_stopping;

Note: when a std::vector is passed in as an initial condition to a Solve call, it gets updated as the solve takes place. Therefore, if we want to use the same initial condition again, we have to reset it back to 1.0.

        initial_condition[0] = 1.0;
        solutions = euler_solver.Solve(&my_ode_stopping, initial_condition, 0, 1, 0.01, 0.1);

We can check with the solver that it stopped because of the stopping event, rather than because it reached to end time.

        TS_ASSERT(euler_solver.StoppingEventOccurred());

Finally, let’s print the time of the stopping event (to the nearest dt or so).

        std::cout << "Stopping event occurred at t="<<solutions.rGetTimes().back()<<"\n";
    }

ODE solving using state variables

In this second test, we show how to do an alternative version of ODE solving, which does not involve passing in initial conditions and returning an OdeSolution. The AbstractOdeSystem class has a member variable called the state variable vector, which can be used to hold the solution, and will be updated if a particular version of Solve is called. This can be useful for embedding ODE models in a bigger system, since the ODE models will then always contain their current solution state.

    void TestOdeSolvingUsingStateVariable()
    {

Define an instance of the ODE. See the class definition above. Note that this ODE has a variable called mStateVariables, which has been set to be a vector of size one, containing the value 1.0.

        MyOdeUsingStateVariables my_ode_using_state_vars;

To solve updating the state variable, just call the appropriate method on a chosen solver. Note that no initial condition is required, no OdeSolution is returned, and no sampling timestep is given.

        EulerIvpOdeSolver euler_solver;
        euler_solver.SolveAndUpdateStateVariable(&my_ode_using_state_vars, 0.0, 1.0, 0.01);

To see what the solution was at the end, we have to use the state variable.

        std::cout << "Solution at end time = " << my_ode_using_state_vars.rGetStateVariables()[0] << "\n";
    }

Solving n-dimensional ODEs

Finally, here’s a simple test showing how to solve a 2d ODE using the first method. All that is different is the initial condition has be a vector of length 2, and returned solution is of length 2 at every timestep.

    void TestWith2dOde()
    {
        My2dOde my_2d_ode;
        EulerIvpOdeSolver euler_solver;

Define the initial condition for each state variable.

        std::vector<double> initial_condition;
        initial_condition.push_back(1.0);
        initial_condition.push_back(0.0);

Solve, and print the solution as [time, y1, y2].

        OdeSolution solutions = euler_solver.Solve(&my_2d_ode, initial_condition, 0, 1, 0.01, 0.1);
        for (unsigned i=0; i<solutions.rGetTimes().size(); i++)
        {
            std::cout << solutions.rGetTimes()[i] << " "
                      << solutions.rGetSolutions()[i][0] << " "
                      << solutions.rGetSolutions()[i][1] << "\n";
        }
    }
};

Full code

#include <cxxtest/TestSuite.h>

#include "CheckpointArchiveTypes.hpp"
#include "EulerIvpOdeSolver.hpp"
#include "AbstractOdeSystem.hpp"
#include "OdeSystemInformation.hpp"

#include "FakePetscSetup.hpp"

class MyOde : public AbstractOdeSystem
{
public:
    MyOde() : AbstractOdeSystem(1)
    {
        mpSystemInfo = OdeSystemInformation<MyOde>::Instance();
    }

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {
        rDY[0] = rY[0]*rY[0] + time*time;
    }
};

template<>
void OdeSystemInformation<MyOde>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(0.0);

    this->mInitialised = true;
}

class MyOdeWithStoppingEvent : public MyOde
{
public:
    bool CalculateStoppingEvent(double time, const std::vector<double>& rY)
    {
        return (rY[0]>=2.5);
    }
};

class MyOdeUsingStateVariables : public AbstractOdeSystem
{
public:
    MyOdeUsingStateVariables() : AbstractOdeSystem(1)
    {
        mpSystemInfo = OdeSystemInformation<MyOdeUsingStateVariables>::Instance();
        mStateVariables.push_back(1.0);
    }

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {
        rDY[0] = rY[0]*rY[0] + time*time;
    }
};

template<>
void OdeSystemInformation<MyOdeUsingStateVariables>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(1.0);

    this->mInitialised = true;
}

class My2dOde : public AbstractOdeSystem
{
public:
    My2dOde() : AbstractOdeSystem(2)
    {
        mpSystemInfo = OdeSystemInformation<My2dOde>::Instance();
    }

    void EvaluateYDerivatives(double time, const std::vector<double>& rY,
                              std::vector<double>& rDY)
    {
        rDY[0] = rY[1];
        rDY[1] = rY[0]*rY[0];
    }
};

template<>
void OdeSystemInformation<My2dOde>::Initialise()
{
    this->mVariableNames.push_back("y");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(1.0);

    this->mVariableNames.push_back("ydot");
    this->mVariableUnits.push_back("dimensionless");
    this->mInitialConditions.push_back(0.0);

    this->mInitialised = true;
}

class TestSolvingOdesTutorial: public CxxTest::TestSuite
{
public:
    void TestSolvingOdes()
    {
        MyOde my_ode;
        EulerIvpOdeSolver euler_solver;
        std::vector<double> initial_condition;
        initial_condition.push_back(1.0);
        OdeSolution solutions = euler_solver.Solve(&my_ode, initial_condition, 0, 1, 0.01, 0.1);
        for (unsigned i=0; i<solutions.rGetTimes().size(); i++)
        {
            std::cout << solutions.rGetTimes()[i] << " " << solutions.rGetSolutions()[i][0] << "\n";
        }

        solutions.WriteToFile("SolvingOdesTutorial", "my_ode_solution", "sec");
        MyOdeWithStoppingEvent my_ode_stopping;

        initial_condition[0] = 1.0;
        solutions = euler_solver.Solve(&my_ode_stopping, initial_condition, 0, 1, 0.01, 0.1);
        TS_ASSERT(euler_solver.StoppingEventOccurred());
        std::cout << "Stopping event occurred at t="<<solutions.rGetTimes().back()<<"\n";
    }

    void TestOdeSolvingUsingStateVariable()
    {
        MyOdeUsingStateVariables my_ode_using_state_vars;

        EulerIvpOdeSolver euler_solver;
        euler_solver.SolveAndUpdateStateVariable(&my_ode_using_state_vars, 0.0, 1.0, 0.01);

        std::cout << "Solution at end time = " << my_ode_using_state_vars.rGetStateVariables()[0] << "\n";
    }

    void TestWith2dOde()
    {
        My2dOde my_2d_ode;
        EulerIvpOdeSolver euler_solver;

        std::vector<double> initial_condition;
        initial_condition.push_back(1.0);
        initial_condition.push_back(0.0);

        OdeSolution solutions = euler_solver.Solve(&my_2d_ode, initial_condition, 0, 1, 0.01, 0.1);
        for (unsigned i=0; i<solutions.rGetTimes().size(); i++)
        {
            std::cout << solutions.rGetTimes()[i] << " "
                      << solutions.rGetSolutions()[i][0] << " "
                      << solutions.rGetSolutions()[i][1] << "\n";
        }
    }
};

Solving Nonlinear Pdes

Solving Odes

Solving Odes

In this tutorial we show how Chaste can be used to solve an ODE system#

Defining the ODE classes#

The Tests#

Standard ODE solving#

ODE solving using state variables#

Solving n-dimensional ODEs#

Full code#

In this tutorial we show how Chaste can be used to solve an ODE system

Defining the ODE classes

The Tests

Standard ODE solving

ODE solving using state variables

Solving n-dimensional ODEs

Full code