Simulation: R6 class Create and represent a Simulation object
In ABM: Agent Based Model Simulation Framework
Simulation R Documentation
R6 class Create and represent a Simulation object
Description
The Simulation class inherits the Population class. So a simulation
manages agents and their contact. Thus, the class also inherits the
Agent class. So a simulation can have its own state, and events attached
(scheduled) to it. In addition, it also manages all the transitions, using
its addTransition method. ASt last, it maintains loggers, which
record (or count) the state changes, and report their values at specified
times.
Super classes
ABM::R6Agent -> ABM::R6Population -> R6Simulation
Methods
Public methods
-
-
-
-
-
-
Inherited methods
Method new()
Usage
Simulation$new(simulation = 0, initializer = NULL)
Arguments
simulationcan be either an external pointer pointing to
a population object returned from newSimulation, or an integer
specifying the population size, or a list
initializera function or NULL
Details
If simulation is a number (the population size), then initializer
can be a function that take the index of an agent and return its initial
state. If it is a list, the length is the population size, and each element
corresponds to the initial state of an agent (with the same index).
Run the simulation
Method run()
Usage
Simulation$run(time)
Arguments
timethe time points to return the logger values.
Details
the returned list can be coerced into a data.frame object
which first column is time, and other columns are logger results,
each row corresponds to a time point.
The Simulation object first collect and log the states from all
agents in the simulation, then set the current time to the time of
the first event, then call the resume method to actually run it.
Continue running the simulation
Returns
a list of numeric vectors, with time and values reported
by all logger.
Method resume()
Usage
Simulation$resume(time)
Arguments
timethe time points to return the logger values.
Details
the returned list can be coerced into a data.frame object
which first column is time, and other columns are logger results,
each row corresponds to a time point.
The Simulation object repetitively handle the events until the the
last time point in "time" is reached. ASt each time point, the
logger states are collected in put in a list to return.
Add a logger to the simulation
Returns
a list of numeric vectors, with time and values reported
by all logger.
Method addLogger()
Usage
Simulation$addLogger(logger)
Arguments
logger, an external pointer returned by functions like
newCounter or newStateLogger.
Details
without adding a logger, there will be no useful simulation
results returned.
Add a transition to the simulation
Returns
the simulation object itself (invisible)
Method addTransition()
Usage
Simulation$addTransition(
rule,
waiting.time,
to_change_callback = NULL,
changed_callback = NULL
)
Arguments
ruleis a formula that gives the transition rule
waiting.timeeither an external pointer to a WaitingTime object
such as one returned by newExpWaitingTime or newGammaWaitingTime, or
a function (see the details section)
to_change_callbackthe R callback function to determine if
the change should occur. See the details section.
changed_callbackthe R callback function after the change
happened. See the details section.
Details
If waiting.time is a function then it should take exactly one
argument time, which is a numeric value holding the current value, and
return a single numeric value for the waiting time (i.e., should not add
time).
Formula can be used to specify either a spontaneous
transition change, or a transition caused by a contact.
A spontaneous transition has the form from -> to, where from and
to are state specifications. It is either a variable name holding
a state (R list) or the list itself. The list can also be specified
by state(...) instead of list(...)
For a spontaneous transition, the callback functions take the
following two arguments
time: the current time in the simulation
agent: the agent who initiate the contact, an external pointer
A transition caused by contact, the formula needs to specify the
states of both the agent who initiate the contact and the contact
agent. The two states are connected by a + sign, the one before the
sign is the initiator, and the one after the sign is the contact.
The transition must be associated with a Contact object, using
a ~ operator. The Contact object must be specified by a variable name
that hold the external pointer to the object (created by e.g.,
the newRandomMixing function) For example, suppose S=list("S"),
I=list("I"), and m=newRandomMixing(sim), then a possible rule
specifying an infectious agent contacting a susceptible agent causing
it to become exposed can be
specified by
I + S -> I + list("E") ~ m
For a transition caused by a contact, the callback functions take
the third argument:
3. contact: the contact agent, an external pointer
Returns
the simulation object itself (invisible)
Method clone()
The objects of this class are cloneable with this method.
Usage
Simulation$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
ABM documentation built on April 4, 2025, 1:44 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| Simulation | R Documentation |
R6 class Create and represent a Simulation object
Description
The Simulation class inherits the Population class. So a simulation
manages agents and their contact. Thus, the class also inherits the
Agent class. So a simulation can have its own state, and events attached
(scheduled) to it. In addition, it also manages all the transitions, using
its addTransition method. ASt last, it maintains loggers, which
record (or count) the state changes, and report their values at specified
times.
Super classes
ABM::R6Agent -> ABM::R6Population -> R6Simulation
Methods
Public methods
Inherited methods
Method new()
Usage
Simulation$new(simulation = 0, initializer = NULL)
Arguments
simulationcan be either an external pointer pointing to a population object returned from newSimulation, or an integer specifying the population size, or a list
initializera function or NULL
Details
If simulation is a number (the population size), then initializer can be a function that take the index of an agent and return its initial state. If it is a list, the length is the population size, and each element corresponds to the initial state of an agent (with the same index). Run the simulation
Method run()
Usage
Simulation$run(time)
Arguments
timethe time points to return the logger values.
Details
the returned list can be coerced into a data.frame object which first column is time, and other columns are logger results, each row corresponds to a time point.
The Simulation object first collect and log the states from all agents in the simulation, then set the current time to the time of the first event, then call the resume method to actually run it.
Continue running the simulation
Returns
a list of numeric vectors, with time and values reported by all logger.
Method resume()
Usage
Simulation$resume(time)
Arguments
timethe time points to return the logger values.
Details
the returned list can be coerced into a data.frame object which first column is time, and other columns are logger results, each row corresponds to a time point.
The Simulation object repetitively handle the events until the the last time point in "time" is reached. ASt each time point, the logger states are collected in put in a list to return. Add a logger to the simulation
Returns
a list of numeric vectors, with time and values reported by all logger.
Method addLogger()
Usage
Simulation$addLogger(logger)
Arguments
logger,an external pointer returned by functions like newCounter or newStateLogger.
Details
without adding a logger, there will be no useful simulation results returned. Add a transition to the simulation
Returns
the simulation object itself (invisible)
Method addTransition()
Usage
Simulation$addTransition( rule, waiting.time, to_change_callback = NULL, changed_callback = NULL )
Arguments
ruleis a formula that gives the transition rule
waiting.timeeither an external pointer to a WaitingTime object such as one returned by newExpWaitingTime or newGammaWaitingTime, or a function (see the details section)
to_change_callbackthe R callback function to determine if the change should occur. See the details section.
changed_callbackthe R callback function after the change happened. See the details section.
Details
If waiting.time is a function then it should take exactly one argument time, which is a numeric value holding the current value, and return a single numeric value for the waiting time (i.e., should not add time).
Formula can be used to specify either a spontaneous transition change, or a transition caused by a contact.
A spontaneous transition has the form from -> to, where from and to are state specifications. It is either a variable name holding a state (R list) or the list itself. The list can also be specified by state(...) instead of list(...)
For a spontaneous transition, the callback functions take the following two arguments
time: the current time in the simulation
agent: the agent who initiate the contact, an external pointer
A transition caused by contact, the formula needs to specify the states of both the agent who initiate the contact and the contact agent. The two states are connected by a + sign, the one before the
sign is the initiator, and the one after the sign is the contact. The transition must be associated with a Contact object, using a ~ operator. The Contact object must be specified by a variable name that hold the external pointer to the object (created by e.g., the newRandomMixing function) For example, suppose S=list("S"), I=list("I"), and m=newRandomMixing(sim), then a possible rule specifying an infectious agent contacting a susceptible agent causing it to become exposed can be specified by
I + S -> I + list("E") ~ m
For a transition caused by a contact, the callback functions take the third argument: 3. contact: the contact agent, an external pointer
Returns
the simulation object itself (invisible)
Method clone()
The objects of this class are cloneable with this method.
Usage
Simulation$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.