Standard Dynamic Module Library

This chapter overviews:

An incomplete list of classes available as the Standard Dynamic Module Library, and, Some usage the classes in the Standard Dynamic Module Library. This chapter briefly describes the Standard Dynamic Module Library distributed with APP. If the system is installed correctly, the classes provided by the library can be used without any special procedure.

This chapter is not meant to be a complete reference. To know more about the classes defined in the library, see the E-Cell3 Standard Dynamic Module Library Reference Manual (under preparation).

Steppers

There are three direct sub-classes of STEPPER: DifferentialStepper, DiscreteEventStepper, DiscreteTimeStepper

DifferentialSteppers

General-purpose DifferentialStepper classes

The following STEPPER classes implement general-purpose ordinary differential equation solvers. Basically these classes must work well with any simple continuous PROCESS classes.

  • ODE45Stepper

    This STEPPER implements Dormand-Prince 5(4)7M algorithm for ODE systems.

    In most cases this STEPPER is the best general purpose solver for ODE models.

  • ODE23Stepper

    This STEPPER implements Fehlberg 2(3) algorithm for ODE systems.

    Try this STEPPER if other part of the model has smaller timescales. This STEPPER can be used for a moderately stiff systems of differential equations.

  • FixedODE1Stepper

    A DifferentialStepper without adaptive stepsizing mechanism. The solution of this STEPPER is first order.

    This stepper calls process() method of each PROCESS just once in a single step.

    Although this STEPPER is not suitable for high-accuracy solution of smooth continuous systems of differential equations, its simplicity of the algorithm is sometimes useful.

S-System and GMA Steppers

FIXME: need description here.

DiscreteEventSteppers

  • DiscreteEventStepper

    This STEPPER is used to conduct discrete event simulations. This STEPPER should be used in combination with subclasses of DiscreteEventProcess.

    This STEPPER uses its PROCESS objects as event generators. The procedure of this STEPPER for initialize() method is like this:

    1. updateStepInterval() method of its all DiscreteEventProcess objects.
    2. Find a PROCESS with the least scheduled time (top process). The scheduled time is calculated as: ( current time ) + ( StepInterval of the process ).
    3. Reschedule itself to the scheduled time of the top process.

    step() method of this STEPPER is as follows:

    1. Call process() method of the current top process.
    2. Calls updateStepInterval() method of the top process and all dependent processes of the top process, and update scheduled times for those processes to find the new top process.
    3. Lastly the STEPPER reschedule itself to the scheduled time of the new top process.

    The procedure for interrupt() method of this class is the same as that for initialize(). FIXME: need to explain about TimeScale property.

  • NRStepper

    This is an alias to the DiscreteEventStepper. This class can be used as an implementation of Gillespie-Gibson algorithm.

    To conduct the Gillespie-Gibson simulation, use this class of STEPPER in combination with GillespieProcess class. GillespieProcess is a subclass of DiscreteEventProcess.

DiscreteTimeStepper

  • DiscreteTimeStepper

    This STEPPER steps with a fixed interval. For example, StepInterval property of this STEPPER is set to 0.1, this STEPPER steps every 0.1 seconds.

    When this STEPPER steps, it calls process() of all of its PROCESS instances. To change this behavior, create a subclass.

    This STEPPER ignores incoming interruptions from other STEPPERs.

PassiveStepper

  • PassiveStepper

    This STEPPER never steps spontaneously (step interval = infinity). Instead, this STEPPER steps upon interruption. In other words, this STEPPER steps everytime immediately after a dependent STEPPER steps.

    When this STEPPER steps, it calls process() of all of its PROCESS instances. To change this behavior, create a subclass.

Process classes

Continuous Process classes

Differential equation-based Process classes

The following PROCESS classes are straightforward implementations of differential equations, and can be used with the general-purpose DifferentialSteppers such as ODE45Stepper, ODE23Stepper, and FixedODE1Stepper.

In the current version, most of the classes represent certain reaction rate equations. Of course it is not limited to chemical and biochemical simulations.

  • CatalyzedMassActionFluxProcess
  • DecayFluxProcess
  • IsoUniUniFluxProcess
  • MassActionProcess
  • MichaelisUniUniProcess
  • MichaelisUniUniReversibleProcess
  • OrderedBiBiFluxProcess
  • OrderedBiUniFluxProcess
  • OrderedUniBiFluxProcess
  • PingPongBiBiFluxProcess
  • RandomBiBiFluxProcess
  • RandomBiUniFluxProcess
  • RandomUniBiFluxProcess

Other continuous Process classes

  • PythonFluxProcess
  • SSystemProcess

Discrete Process classes

  • GammaProcess

    Under development.

  • GillespieProcess

    This PROCESS must be used with a Gillespie-type STEPPER, such as NRStepper.

  • RapidEquilibriumProcess

Other Process classes

  • PythonProcess

Variable classes

  • Variable

    A standard class to represent a state variable.