worldNLR-class

worldNLR

<p>The <code>worldNLR</code> class is the union of the <code>worldMatrix</code> and <code>worldArray</code>
classes. Mostly used for building function purposes.</p>

Build and run spatially explicit
agent-based models using only the R platform. 'NetLogoR' follows the same
framework as the 'NetLogo' software
(Wilensky, 1999 <http://ccl.northwestern.edu/netlogo/>) and is a translation
in R of the structure and functions of 'NetLogo'.
'NetLogoR' provides new R classes to define model agents and functions to
implement spatially explicit agent-based models in the R environment.
This package allows benefiting of the fast and easy coding phase from the
highly developed 'NetLogo' framework, coupled with the versatility, power
and massive resources of the R software.
Examples of three models (Ants <http://ccl.northwestern.edu/netlogo/models/Ants>,
Butterfly (Railsback and Grimm, 2012) and Wolf-Sheep-Predation
<http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation>) written using
'NetLogoR' are available. The 'NetLogo' code of the original version of these
models is provided alongside.
A programming guide inspired from the 'NetLogo' Programming Guide
(<https://ccl.northwestern.edu/netlogo/docs/programming.html>) and a dictionary
of 'NetLogo' primitives (<https://ccl.northwestern.edu/netlogo/docs/dictionary.html>)
equivalences are also available.
NOTE: To increment 'time', these functions can use a for loop or can be
integrated with a discrete event simulator, such as 'SpaDES'
(<https://cran.r-project.org/package=SpaDES>).
The suggested package 'fastshp' can be installed with
'install.packages("fastshp", repos = "https://rforge.net", type = "source")'.

Eliot J B

NetLogoR

Build and Run Spatially Explicit Agent-Based Models

Sarah Bauduin

Eliot J B McIntire

Alex M Chubaty

Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada 

worldNLR-class function

The <code>worldNLR</code> class — worldNLR-class

The <code>worldNLR</code> class

worldNLR-class: The `worldNLR` class

Description

Arguments