NetLogo 6.0.4 User Manual Net Logo

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The NetLogo 6.0.4 User Manual

Table of Contents
Table of Contents
What is NetLogo?
Features

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How to reference
Acknowledgments
NetLogo license
Commercial licenses
NetLogo User Manual license
Open source
Third party licenses

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Scala
MersenneTwisterFast
Colt
Config
Apache Commons Codec (TM)
Flexmark
JHotDraw
JOGL
Matrix3D
ASM
Log4j
PicoContainer
Parboiled
RSyntaxTextArea
JCodec
Java-Objective-C Bridge
Webcam-capture
Guava
Gephi
R Extension
JNA

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What's new?
Version 6.0.4 (May 2018)
Feature Changes
Bugfixes
Documentation Changes
Model Changes

Version 6.0.3 (March 2018)
Feature Changes
Documentation Changes
Bugfixes
Extension Changes
Documentation Changes
Model Changes

Version 6.0.2 (August 2017)
Feature Changes
Bugfixes
Extension Changes
Documentation Changes
Model Changes

Version 6.0.1 (March 2017)
Feature Changes
Bugfixes
Extension Changes
Documentation Changes
Models

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Version 6.0 (December 2016)
Feature Changes
Bugfixes
Language Changes
Extension Changes
Operating System Support
Documentation Changes
Internationalization Changes
Models

Version 5.3.1 (February 2016)
Feature Changes
Extension Changes
Bugfixes

Version 5.3 (December 2015)
Feature Changes
Extension Changes

Version 5.2.1 (September 2015)
Extensions
New features
Bug fixes
Model changes

Version 5.2.0 (April 2015)
Extensions
New features
Bug fixes
Model changes

Version 5.1.0 (July 2014)
Version 5.0.4 (March 2013)
Version 5.0 (February 2012)
Version 4.1.3 (April 2011)
Version 4.1 (December 2009)
Version 4.0 (September 2007)
Version 3.1 (April 2006)
Version 3.0 (September 2005)
Version 2.1 (December 2004)
Version 2.0.2 (August 2004)
Version 2.0 (December 2003)
Version 1.3 (June 2003)
Version 1.2 (March 2003)
Version 1.1 (July 2002)
Version 1.0 (April 2002)

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System Requirements

Application Requirements

Windows
Mac OS X
Linux

3D Requirements
32-bit or 64-bit?

Contacting Us
Web site
Feedback, questions, etc.
Reporting bugs
Open source

Sample Model: Party
At a Party
Challenge

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Thinking with models
What’s next?

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Tutorial #1: Models

Sample Model: Wolf Sheep Predation
Controlling the Model: Buttons
Controlling speed: Speed Slider
Adjusting Settings: Sliders and Switches
Gathering Information: Plots and Monitors
Plots
Monitors

Controlling the View
Models Library
Sample Models
Curricular Models
Code Examples
HubNet Activities

What’s Next?

Tutorial #2: Commands
Sample Model: Traffic Basic
Command Center
Working with colors
Agent Monitors and Agent Commanders
What’s Next?

Tutorial #3: Procedures
Agents and procedures
Making the setup button
Switching to tick-based view updates
Making the go button
Experimenting with commands
Patches and variables
Turtle variables
Monitors
Switches and labels
More procedures
Plotting
Tick counter
Some more details
What’s next?
Appendix: Complete code

Interface Guide
Menus
Chart: NetLogo menus

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Tabs
International Usage

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Character sets
Languages
Support for translators

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Interface Tab Guide
Working with interface elements
Chart: Interface Toolbar
The 2D and 3D views
Manipulating the 3D View

Command Center
Reporters

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Accessing previous commands
Clearing
Arranging

Plots
Plot Pens

Sliders
Agent Monitors

Info Tab
Editing
Headings
Input

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Paragraphs

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Example
Formatted

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Italicized and bold text

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Example
Formatted

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Ordered lists

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Example
Formatted

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Unordered lists
Example
Formatted

Links
Automatic links
Links with text
Local links

Images
Example
Formatted
Local images

Block quotations
Example
Formatted

Code

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Example
Formatted

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Code blocks

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Example
Formatted

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Superscripts and subscripts
Example
Formatted

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Notes on usage
Other features

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Code Tab Guide

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Checking for Errors
Find & Replace
Automatic Indentation
More Editing Options
Included Files Menu

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Programming Guide

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Agents
Procedures
Variables
Tick counter

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When to tick

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Fractional ticks

Colors
Ask
Agentsets
Special agentsets
Agentsets and lists

Breeds
Link breeds

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Buttons
Lists
Math
Random numbers

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Auxiliary generator
Local randomness

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Turtle shapes
Link shapes
View updates
Continuous updates
Tick-based updates
Choosing a mode
Frame rate

Plotting
Plotting points
Plot commands
Other kinds of plots
Histograms
Clearing and resetting
Ranges and auto scaling
Using a Legend
Temporary plot pens
set-current-plot and set-current-plot-pen
Conclusion

Strings
Output
How Output Primitives Differ

File I/O
Movies
Perspective
Drawing
Topology
Links
Anonymous procedures
Anonymous procedure primitives
Anonymous procedure inputs
Anonymous procedures and strings
Concise syntax
Anonymous procedures as closures
Nonlocal exits
Anonymous procedures and extensions
Limitations
What is Optional?
Code example

Ask-Concurrent
User Interaction Primitives
What does “Halt” mean?

Tie
Multiple source files
Syntax
Colors

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Notice
Keywords
Identifiers
Scope
Comments
Structure
Commands and reporters
Compared to other Logos

Transition Guide

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Changes for NetLogo 6.0.3

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Arduino Extension Changes
CF Extension Changes

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Changes for NetLogo 6.0

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Tasks replaced by Anonymous Procedures
Link reporters overhauled to be more consistent and flexible
Removal of Applets
Changes to the NetLogo User Interface
Nobody Not Permitted as a Chooser Value
Breeds must have singular and plural names
Removal of “Movie” Prims
Improved Name Collision Detection
Removal of hubnet-set-client-interface
Improved & Updated Extensions API
Add range primitive

Changes for NetLogo 5.2
hsb primitives
GoGo extension

Changes for NetLogo 5.0
Plotting
Tick counter
Unicode characters
Info tabs
Model speed
List performance
Extensions API

Changes for NetLogo 4.1
Combining set and of

Changes for NetLogo 4.0
Who numbering
Turtle creation: randomized vs. “ordered”
Adding strings and lists
The -at primitives
Links
New “of” syntax
Serial ask
Tick counter
View update modes
Speed slider
Numbers
Agentset building
RGB Colors
Tie

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Changes for NetLogo 3.1

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Agentsets
Wrapping
Random turtle coordinates

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Shapes Editor Guide
Getting started
Importing shapes

Creating and editing turtle shapes
Tools

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Previews
Overlapping shapes
Undo
Colors
Other buttons
Shape design
Keeping a shape

Creating and editing link shapes
Changing link shape properties

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Using shapes in a model

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BehaviorSpace Guide

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What is BehaviorSpace?

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Why BehaviorSpace?

How It Works
Managing experiment setups
Creating an experiment setup
Special primitives for BehaviorSpace experiments
Running an experiment

Advanced Usage
Running from the command line
Setting up experiments in XML
Adjusting JVM Parameters
Controlling API

System Dynamics Guide
What is the NetLogo System Dynamics Modeler?
Basic Concepts
Sample Models

How it Works
Diagram Tab
Code Tab
The System Dynamics Modeler and NetLogo

Tutorial: Wolf-Sheep Predation
Step 1: Sheep Reproduction
Step 2: NetLogo Integration
Step 3: Wolf Predation

HubNet Guide
Understanding HubNet

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NetLogo
HubNet Architecture

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Computer HubNet

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Activities
Clients
Requirements
Starting an activity
HubNet Control Center
Troubleshooting
Known Limitations

Teacher workshops
HubNet Authoring Guide
Running HubNet in headless mode
Getting help

HubNet Authoring Guide
Coding HubNet activities

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Setup
Receiving messages from clients
Sending messages to clients
Examples

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How to make a client interface

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View updates on the clients
Clicking in the view on clients
Customizing the client’s view
Plot updates on the clients

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Modeling Commons Guide

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Introduction
Modeling Commons Accounts
Uploading Models

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Upload A New Model
Upload A Child Of An Existing Model (“forking”)

Updating An Existing Model

Logging
Starting logging
Mac OS X or Windows
Linux and others

Using logging
Where logs are stored
How to configure the logging output

Advanced Configuration

Controlling Guide
Mathematica Link
What can I do with it?
Installation
Usage
Known Issues
Source code
Credits

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NetLogo 3D

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Introduction

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3D Worlds
The observer and the 3D view
Custom Shapes

Tutorial
Step 1: Depth
Step 2: Turtle Movement
Step 3: Observer Movement

Dictionary
Commands and Reporters
Built-In Variables
Primitives
at-points4.1
distancexyz4.1 distancexyz-nowrap4.1
dz4.1
face facexyz4.1
left4.1
link-pitch4.1.2
load-shapes-3d4.1
max-pzcor4.1 min-pzcor4.1
neighbors4.1 neighbors64.1
orbit-down4.1 orbit-left4.1 orbit-right4.1 orbit-up4.1
__oxcor __oycor __ozcor
patch4.1
patch-at4.1
patch-at-heading-pitch-and-distance4.1
pitch
pzcor
random-pzcor4.1

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random-zcor4.1
right4.1
roll
roll-left4.1
roll-right4.1
setxyz4.1
tilt-down4.1 tilt-up4.1
towards-pitch4.1 towards-pitch-nowrap4.1
towards-pitch-xyz4.1 towards-pitch-xyz-nowrap4.1
turtles-at4.1 -at
world-depth4.1
zcor
zoom4.1

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Extensions Guide

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Using Extensions

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Where extensions are located

NetLogo Arduino Extension
Using
Notes
Compatibility
Questions

Primitives
arduino:primitives
arduino:ports
arduino:open
arduino:close
arduino:get
arduino:write-string
arduino:write-int
arduino:write-byte
arduino:is-open?
arduino:debug-to-arduino
arduino:debug-from-arduino

NetLogo Array Extension
Using
When to Use
Example use of Array Extension

Primitives
array:from-list
array:item
array:set
array:length
array:to-list

NetLogo Bitmap Extension
Using
What does the Bitmap Extension do?
Getting started

Primitives
bitmap:average-color
bitmap:channel
bitmap:copy-to-drawing
bitmap:copy-to-pcolors
bitmap:difference-rgb
bitmap:export
bitmap:from-view
bitmap:to-grayscale
bitmap:height
bitmap:import
bitmap:scaled
bitmap:width

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NetLogo Cf Extension
Primitives
cf:ifelse
cf:ifelse-value

NetLogo Csv Extension
Common use cases and examples
Read a file all at once
Read a file one line at a time
Read a file one line per tick
Write a file

Primitives
Formatting NetLogo data as CSV
Parsing CSV input to NetLogo data
csv:from-row
csv:from-string
csv:from-file
csv:to-row
csv:to-string
csv:to-file

NetLogo Gis Extension
Using
How to use
Known Issues
Credits

Primitives
RasterDataset Primitives
Dataset Primitives
VectorDataset Primitives
Coordinate System Primitives
Drawing Primitives
gis:set-transformation
gis:set-transformation-ds
gis:set-world-envelope
gis:set-world-envelope-ds
gis:world-envelope
gis:envelope-of
gis:envelope-union-of
gis:load-coordinate-system
gis:set-coordinate-system
gis:load-dataset
gis:store-dataset
gis:type-of
gis:patch-dataset
gis:turtle-dataset
gis:link-dataset
gis:shape-type-of
gis:property-names
gis:feature-list-of
gis:vertex-lists-of
gis:centroid-of
gis:location-of
gis:property-value
gis:find-features
gis:find-one-feature
gis:find-less-than
gis:find-greater-than
gis:find-range
gis:property-minimum
gis:property-maximum
gis:apply-coverage
gis:coverage-minimum-threshold

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gis:set-coverage-minimum-threshold
gis:coverage-maximum-threshold
gis:set-coverage-maximum-threshold
gis:intersects?
gis:contains?
gis:contained-by?
gis:have-relationship?
gis:relationship-of
gis:intersecting
gis:width-of
gis:height-of
gis:raster-value
gis:set-raster-value
gis:minimum-of
gis:maximum-of
gis:sampling-method-of
gis:set-sampling-method
gis:raster-sample
gis:raster-world-envelope
gis:create-raster
gis:resample
gis:convolve
gis:apply-raster
gis:drawing-color
gis:set-drawing-color
gis:draw
gis:fill
gis:paint
gis:import-wms-drawing

NetLogo Gogo Extension
Usage
Changes
Primitives
Other Outputs
Utilities
General
Sensors
Outputs and Servos
gogo:primitives
gogo:howmany-gogos
gogo:talk-to-output-ports
gogo:set-output-port-power
gogo:output-port-on
gogo:output-port-off
gogo:output-port-clockwise
gogo:output-port-counterclockwise
gogo:set-servo
gogo:led
gogo:beep
gogo:read-sensors
gogo:read-sensor
gogo:read-all
gogo:send-bytes

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NetLogo Ls Extension

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LevelSpace fundamentals

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Headless and Interactive Models
Keeping Track of Models
A general use case: Asking and Reporting
A general use case: Inter-Model Interactions
A general Usecase: Tidying up “Dead” Child Models

Citing LevelSpace in Research

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Primitives
Commanding and Reporting
Logic and Control
Opening and Closing Models
ls:create-models
ls:create-interactive-models
ls:close
ls:reset
ls:ask
ls:of
ls:report
ls:with
ls:let
ls:assign
ls:models
ls:show
ls:show-all
ls:hide
ls:hide-all
ls:path-of
ls:name-of
ls:model-exists?
ls:random-seed

NetLogo Matrix Extension
Using
When to Use
How to Use
Example

Primitives
Matrix creation and conversion to/from lists
Advanced features
Matrix data retrieval and manipulation
Math operations
matrix:make-constant
matrix:make-identity
matrix:from-row-list
matrix:from-column-list
matrix:to-row-list
matrix:to-column-list
matrix:copy
matrix:pretty-print-text
matrix:get
matrix:get-row
matrix:get-column
matrix:set
matrix:set-row
matrix:set-column
matrix:swap-rows
matrix:swap-columns
matrix:set-and-report
matrix:dimensions
matrix:submatrix
matrix:map
matrix:times-scalar
matrix:times
matrix:*
matrix:times-element-wise
matrix:plus-scalar
matrix:plus
matrix:+
matrix:minus
matrix:-

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matrix:inverse
matrix:transpose
matrix:real-eigenvalues
matrix:imaginary-eigenvalues
matrix:eigenvectors
matrix:det
matrix:rank
matrix:trace
matrix:solve
matrix:forecast-linear-growth
matrix:forecast-compound-growth
matrix:forecast-continuous-growth
matrix:regress

NetLogo Nw Extension
Usage
Special agentsets vs normal agentsets

A note regarding floating point calculations
Performance
Primitives
Generators
Path and Distance
Clusterer/Community Detection
Context Management
Import and Export
Centrality Measures
Clustering Measures
nw:set-context
nw:get-context
nw:with-context
nw:turtles-in-radius
nw:turtles-in-reverse-radius
nw:distance-to
nw:weighted-distance-to
nw:path-to
nw:turtles-on-path-to
nw:weighted-path-to
nw:turtles-on-weighted-path-to
nw:mean-path-length
nw:mean-weighted-path-length
nw:betweenness-centrality
nw:eigenvector-centrality
nw:page-rank
nw:closeness-centrality
nw:weighted-closeness-centrality
nw:clustering-coefficient
nw:modularity
nw:bicomponent-clusters
nw:weak-component-clusters
nw:louvain-communities
nw:maximal-cliques
nw:biggest-maximal-cliques
nw:generate-preferential-attachment
nw:generate-random
nw:generate-watts-strogatz
nw:generate-small-world
nw:generate-lattice-2d
nw:generate-ring
nw:generate-star
nw:generate-wheel
nw:save-matrix
nw:load-matrix
nw:save-graphml

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nw:load-graphml
nw:load
nw:save

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NetLogo Palette Extension

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Using the Palette Extension
Getting Started

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What colors should I use ?
Should I use a continuous color gradient or just a discrete color set ?
Example Models
Further Reading

Primitives
palette:scale-gradient
palette:scale-scheme
palette:scheme-colors
palette:scale-gradient

References

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NetLogo Profiler Extension

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Using the Profiler Extension

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How to use
Example

Primitives
profiler:calls
profiler:exclusive-time
profiler:inclusive-time
profiler:start
profiler:stop
profiler:reset
profiler:report

NetLogo R Extension
Using
Some Tips

Installing
Installing R
Configuring the R extension
Determining r.home and jri.home.paths
Windows-Specific Installation Steps

Primitives

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r:clear
r:clearLocal
r:eval
r:__evaldirect
r:gc
r:get
r:interactiveShell
r:put
r:putagent
r:putagentdf
r:putdataframe
r:putlist
r:putnamedlist
r:setPlotDevice
r:stop

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Troubleshooting

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Loading R packages fails
After changing the working directory in R (e.g. with setwd()) NetLogo doesn’t find the extension
Specific error code list

Citation
Copyright and License

NetLogo Rnd Extension

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Usage
A note about performance
Primitives
AgentSet Primitives
List Primitives
rnd:weighted-one-of
rnd:weighted-n-of
rnd:weighted-n-of-with-repeats
rnd:weighted-one-of-list
rnd:weighted-n-of-list
rnd:weighted-n-of-list-with-repeats

NetLogo Sound Extension
Using
How to Use
MIDI support

Primitives

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sound:drums
sound:instruments
sound:play-drum
sound:play-note
sound:play-note-later

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Drum Names
Instrument Names

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NetLogo Table Extension
Using
When to Use
Example
Manipulating Tables
Key Restrictions

Primitives
table:clear
table:counts
table:group-agents
table:group-items
table:from-list
table:get
table:get-or-default
table:has-key?
table:keys
table:length
table:make
table:put
table:remove
table:to-list
table:values

NetLogo Vid Extension
Concepts
Video Source
Source Lifecycle
Video Recorder

Primitives
vid:camera-names
vid:camera-open
vid:camera-select
vid:movie-select
vid:movie-open
vid:movie-open-remote
vid:close
vid:start
vid:stop

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vid:status
vid:capture-image
vid:set-time
vid:show-player
vid:hide-player
vid:record-view
vid:record-interface
vid:record-source
vid:recorder-status
vid:start-recorder
vid:save-recording

NetLogo View2.5d Extension
How to Use
Incorporating Into Models
Feedback

Primitives
view2.5d:patch-view
view2.5d:decorate-patch-view
view2.5d:undecorate-patch-view
view2.5d:turtle-view
view2.5d:update-all-patch-views
view2.5d:update-patch-view
view2.5d:update-turtle-view
view2.5d:get-z-scale
view2.5d:set-z-scale
view2.5d:set-turtle-stem-thickness
view2.5d:get-observer-angles
view2.5d:set-observer-angles
view2.5d:get-observer-xy-focus
view2.5d:set-observer-xy-focus
view2.5d:get-observer-distance
view2.5d:set-observer-distance
view2.5d:remove-patch-view
view2.5d:remove-turtle-view
view2.5d:remove-all-patch-views
view2.5d:remove-all-turtle-views
view2.5d:count-windows

FAQ (Frequently Asked Questions)
General
Why is it called NetLogo?
How do I cite NetLogo or HubNet in a publication?
How do I cite a model from the Models Library in a publication?
Where and when was NetLogo created?
What programming language was NetLogo written in?
What’s the relationship between StarLogo and NetLogo?
Under what license is NetLogo released? Is the source code available?
Do you offer any workshops or other training opportunities for NetLogo?
Are there any NetLogo textbooks?
Is NetLogo available in other languages besides English?
Is NetLogo compiled or interpreted?
Has anyone built a model of ?
Are NetLogo models runs scientifically reproducible?
Will NetLogo and NetLogo 3D remain separate?
Can I run NetLogo on my phone or tablet?

Downloading
Can I have multiple versions of NetLogo installed at the same time?
I’m on a UNIX system and I can’t untar the download. Why?
How do I install NetLogo unattended?

Running
Can I run NetLogo from a CD, a network drive, or a USB drive?
Why is NetLogo so much slower when I unplug my Windows laptop?
Why does NetLogo bundle Java?

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How come NetLogo won’t start up on my Linux machine?
When I try to install NetLogo on Windows, I see “Windows protected your PC”
When I try to start NetLogo on Windows I get an error “The JVM could not be started”. Help!
NetLogo won’t start on Mac OS Sierra (or later)
NetLogo won’t start on Windows or crashes suddenly on Mac OS Sierra
Can I run NetLogo from the command line, without the GUI?
Does NetLogo take advantage of multiple processors?
Can I distribute NetLogo model runs across a cluster or grid of computers?
Is there any way to recover lost work if NetLogo crashes or freezes?
Why is HubNet Discovery Not Working?

Usage

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When I move the speed slider all the way to the right, why does my model seem to stop?
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Can I use the mouse to “paint” in the view?
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How big can my model be? How many turtles, patches, procedures, buttons, and so on can my model contain?
Can I use GIS data in NetLogo?
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My model runs slowly. How can I speed it up?
364
Can I have more than one model open at a time?
364
Can I change the choices in a chooser on the fly?
364
Can I divide the code for my model up into several files?
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Programming

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How does the NetLogo language differ from other Logos?
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How come my model from an earlier NetLogo doesn’t work right?
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How do I take the negative of a number?
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My turtle moved forward 1, but it’s still on the same patch. Why?
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How do I keep my turtles on patch centers?
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patch-ahead 1 is reporting the same patch my turtle is already standing on. Why?
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How do I give my turtles “vision”?
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Can agents sense what’s in the drawing layer?
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I’m getting numbers like 0.10000000004 and 0.799999999999 instead of 0.1 and 0.8. Why?
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The documentation says that random-float 1 might return 0 but will never return 1. What if I want 1 to be included?
How can I keep two turtles from occupying the same patch?
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How can I find out if a turtle is dead?
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Does NetLogo have arrays?
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Does NetLogo have hash tables or associative arrays?
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How can I use different patch “neighborhoods” (circular, Von Neumann, Moore, etc.)?
366
How can I convert an agentset to a list of agents, or vice versa?
366
How do I stop foreach?
367
I’m trying to make a list. Why do I keep getting the error “Expected a constant”?
367

BehaviorSpace
Why are the rows in my BehaviorSpace table results out of order?
How do I measure runs every n ticks?
I’m varying a global variable I declared in the Code tab, but it doesn’t work. Why?

NetLogo 3D
Does NetLogo work with my stereoscopic device?

Extensions
I’m writing an extension. Why does the compiler say it can’t find org.nlogo.api?

NetLogo Dictionary
Categories
Turtle-related
Patch-related
Link-related
Agentset
Color
Control flow and logic
Anonymous Procedures
World
Perspective
HubNet
Input/output
File
List
String

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Mathematical
Plotting
BehaviorSpace
System

Built-In Variables

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Turtles
Patches
Links
Other

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Keywords
Constants

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Mathematical Constants
Boolean Constants
Color Constants

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abs1.0
acos1.3
all?4.0
and1.0
any?2.0
approximate-hsb4.0
approximate-rgb4.0
Arithmetic Operators +1.0 *1.0 -1.0 /1.0 ^1.0 <1.0 >1.0 =1.0 !=1.0 <=1.0 >=1.0
asin1.3
ask1.0
ask-concurrent4.0
at-points1.0
atan1.0
autoplot?1.0
auto-plot-off1.0 auto-plot-on1.0

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back1.0 bk1.0
base-colors4.0
beep2.1
behaviorspace-experiment-name5.2
behaviorspace-run-number4.1.1
both-ends4.0
breed
breed
but-first1.0 butfirst1.0 bf1.0 but-last1.0 butlast1.0 bl1.0

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can-move?3.1
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carefully2.1
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ceiling1.0
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clear-all1.0 ca1.0
375
clear-all-plots1.0
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clear-drawing3.0 cd3.0
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clear-globals5.2
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clear-links4.0
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clear-output1.0
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clear-patches1.0 cp1.0
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clear-plot
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clear-ticks5.0
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clear-turtles1.0 ct1.0
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color
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cos1.0
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count1.0
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create-ordered-turtles4.0 cro4.0
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create--to create--to create--from create--from create--with create-with create-link-to4.0 create-links-to4.0 create-link-from4.0 create-links-from4.0 create-link-with4.0
create-links-with4.0
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create-turtles1.0 crt1.0
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create-temporary-plot-pen1.1

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date-and-time3.0
die1.0
diffuse1.0
diffuse41.0
directed-link-breed
display1.0
distance1.0
distancexy1.0
downhill1.0 downhill41.0
dx1.0 dy1.0

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empty?1.0
end
end14.0
end24.0
error5.0
error-message2.1
every1.0
exp1.0
export-view3.0 export-interface2.0 export-output1.0 export-plot1.0 export-all-plots1.2.1 export-world1.0
extensions
extract-hsb1.0
extract-rgb1.0

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facexy3.0
file-at-end?2.0
file-close2.0
file-close-all2.0
file-delete2.0
file-exists?2.0
file-flush4.0
file-open2.0
file-print2.0
file-read2.0
file-read-characters2.0
file-read-line2.0
file-show2.0
file-type2.0
file-write2.0
filter1.3
first1.0
floor1.0
follow3.0
follow-me3.0
foreach1.3
forward1.0 fd1.0
fput1.0

G
globals

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hatch1.0
heading
hidden?
hide-link4.0
hide-turtle1.0 ht1.0
histogram1.0
home1.0
hsb1.0
hubnet-broadcast1.1
hubnet-broadcast-clear-output4.1

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hubnet-broadcast-message4.1
hubnet-clear-override4.1 hubnet-clear-overrides4.1
hubnet-clients-list5.0
hubnet-enter-message?1.2.1
hubnet-exit-message?1.2.1
hubnet-fetch-message1.1
hubnet-kick-client5.0
hubnet-kick-all-clients5.0
hubnet-message1.1
hubnet-message-source1.1
hubnet-message-tag1.1
hubnet-message-waiting?1.1
hubnet-reset1.1
hubnet-reset-perspective4.1
hubnet-send1.1
hubnet-send-clear-output4.1
hubnet-send-follow4.1
hubnet-send-message4.1
hubnet-send-override4.1
hubnet-send-watch4.1

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ifelse1.0
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ifelse-value2.0
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import-drawing3.0
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import-pcolors3.0
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import-pcolors-rgb4.0
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import-world1.0
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in-cone3.0
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in--neighbor? in-link-neighbor?4.0
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in--neighbors in-link-neighbors4.0
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in--from in-link-from4.0
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__includes4.0
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in-radius1.0
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insert-item6.0.2
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inspect1.1
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int1.0
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is-agent?1.2.1 is-agentset?1.2.1 is-anonymous-command?6.0 is-anonymous-reporter?6.0 is-boolean?1.2.1 isdirected-link?4.0 is-link?4.0 is-link-set?4.0 is-list?1.0 is-number?1.2.1 is-patch?1.2.1 is-patch-set?4.0 is-string?1.0
is-turtle?1.2.1 is-turtle-set?4.0 is-undirected-link?4.0
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item1.0
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jump1.0

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label
label-color
last1.0
layout-circle4.0
layout-radial4.0
layout-spring4.0
layout-tutte4.0
left1.0 lt1.0
length1.0
let2.1
link4.0
link-heading4.0
link-length4.0
link-set4.0
link-shapes4.0
links4.0
links-own
list1.0
ln1.0

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400

log1.0
loop1.0
lput1.0

M
map1.3
max1.0
max-n-of4.0
max-one-of1.0
max-pxcor3.1 max-pycor3.1
mean1.0
median1.0
member?1.0
min1.0
min-n-of4.0
min-one-of1.0
min-pxcor3.1 min-pycor3.1
mod1.0
modes2.0
mouse-down?1.0
mouse-inside?3.0
mouse-xcor1.0 mouse-ycor1.0
move-to4.0
my- my-links4.0
my-in- my-in-links4.0
my-out- my-out-links4.0
myself1.0

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n-of3.1
n-values2.0
neighbors1.1 neighbors41.1
-neighbors link-neighbors4.0
-neighbor? link-neighbor?4.0
netlogo-version3.0
netlogo-web?5.2
new-seed3.0
no-display1.0
nobody
no-links4.0
no-patches4.0
not1.0
no-turtles4.0

O
of4.0
one-of1.0
or1.0
other4.0
other-end4.0
out--neighbor? out-link-neighbor?4.0
out--neighbors out-link-neighbors4.0
out--to out-link-to4.0
output-print2.1 output-show2.1 output-type2.1 output-write2.1

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406
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patch1.0
patch-ahead2.0
patch-at1.0
patch-at-heading-and-distance2.0
patch-here1.0
patch-left-and-ahead2.0 patch-right-and-ahead2.0
patch-set4.0
patch-size4.1
patches1.0
patches-own
pcolor

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411
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411

pen-down1.0 pd1.0 pen-erase3.0 pe3.0 pen-up1.0 pu1.0
pen-mode
pen-size
plabel
plabel-color
plot1.0
plot-name1.0
plot-pen-exists?4.0
plot-pen-down1.0 plot-pen-up1.0
plot-pen-reset1.0
plotxy1.0
plot-x-min1.0 plot-x-max1.0 plot-y-min1.0 plot-y-max1.0
position1.0
precision1.0
print1.0
pxcor pycor

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413
413

413
random1.0
random-float2.0
random-exponential1.2.1 random-gamma2.0 random-normal1.2.1 random-poisson1.2.1
random-pxcor3.1 random-pycor3.1
random-seed1.0
random-xcor3.1 random-ycor3.1
range6.0
read-from-string1.1
reduce1.3
remainder1.2.1
remove1.0
remove-duplicates1.0
remove-item2.0
repeat1.0
replace-item1.0
report1.0
reset-perspective3.0 rp3.0
reset-ticks4.0
reset-timer1.0
resize-world4.1
reverse1.0
rgb1.0
ride3.0
ride-me3.0
right1.0 rt1.0
round1.0
run1.3 runresult1.3

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419
scale-color1.0
self1.3
; (semicolon)
sentence1.0 se1.0
set1.0
set-current-directory2.0
set-current-plot1.0
set-current-plot-pen1.0
set-default-shape1.0
set-histogram-num-bars1.0
__set-line-thickness
set-patch-size4.1
set-plot-background-color6.0.2
set-plot-pen-color1.0
set-plot-pen-interval1.0
set-plot-pen-mode1.0
setup-plots5.0
set-plot-x-range1.0 set-plot-y-range1.0

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setxy1.0
shade-of?1.0
shape
shapes2.1
show1.0
show-turtle1.0 st1.0
show-link4.0
shuffle2.0
sin1.0
size
sort1.0
sort-by1.3
sort-on5.0
sprout1.0
sqrt1.0
stamp1.0
stamp-erase3.1
standard-deviation1.0
startup
stop1.0
stop-inspecting5.2
stop-inspecting-dead-agents5.2
subject3.0
sublist2.1 substring1.0
subtract-headings2.1
sum1.0

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thickness
tick4.0
tick-advance4.0
ticks4.0
tie4.0
tie-mode
timer1.0
to
to-report
towards1.0
towardsxy1.0
turtle1.0
turtle-set4.0
turtles1.0
turtles-at1.0
turtles-here1.0
turtles-on2.0
turtles-own
type1.0

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430
undirected-link-breed
untie4.0
update-plots5.0
uphill1.0 uphill41.0
user-directory3.1
user-file3.1
user-new-file3.1
user-input1.1
user-message1.1
user-one-of3.1
user-yes-or-no?2.0

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variance1.0

W
wait1.0

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watch3.0
watch-me3.0
while1.0
who
with1.0
-with link-with4.0
with-max2.1
with-min2.1
with-local-randomness4.0
without-interruption1.1
word1.0
world-width3.1 world-height3.1
wrap-color1.0
write2.0

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xor1.0

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ycor

->
->6.0

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What is NetLogo?

NetLogo is a programmable modeling environment for simulating natural and social
phenomena. It was authored by Uri Wilensky in 1999 and has been in continuous
development ever since at the Center for Connected Learning and Computer-Based
Modeling.
NetLogo is particularly well suited for modeling complex systems developing over time.
Modelers can give instructions to hundreds or thousands of “agents” all operating
independently. This makes it possible to explore the connection between the micro-level
behavior of individuals and the macro-level patterns that emerge from their interaction.
NetLogo lets students open simulations and “play” with them, exploring their behavior under
various conditions. It is also an authoring environment which enables students, teachers and
curriculum developers to create their own models. NetLogo is simple enough for students and
teachers, yet advanced enough to serve as a powerful tool for researchers in many fields.
NetLogo has extensive documentation and tutorials. It also comes with the Models Library, a
large collection of pre-written simulations that can be used and modified. These simulations
address content areas in the natural and social sciences including biology and medicine,
physics and chemistry, mathematics and computer science, and economics and social
psychology. Several model-based inquiry curricula using NetLogo are available and more are
under development.
NetLogo is the next generation of the series of multi-agent modeling languages including
StarLogo and StarLogoT. NetLogo runs on the Java Virtual Machine, so it works on all major
platforms (Mac, Windows, Linux, et al). It is run as a desktop application. Command line
operation is also supported.

Features
System:
Free, open source
Cross-platform: runs on Mac, Windows, Linux, et al
International character set support
Programming:
Fully programmable

Approachable syntax
Language is Logo dialect extended to support agents
Mobile agents (turtles) move over a grid of stationary agents (patches)
Link agents connect turtles to make networks, graphs, and aggregates
Large vocabulary of built-in language primitives
Double precision floating point math
First-class function values (aka anonymous procedures, closures, lambda)
Runs are reproducible cross-platform
Environment:
Command center for on-the-fly interaction
Interface builder w/ buttons, sliders, switches, choosers, monitors, text boxes,
notes, output area
Info tab for annotating your model with formatted text and images
HubNet: participatory simulations using networked devices
Agent monitors for inspecting and controlling agents
Export and import functions (export data, save and restore state of model, make a
movie)
BehaviorSpace, an open source tool used to collect data from multiple parallel
runs of a model
System Dynamics Modeler
NetLogo 3D for modeling 3D worlds
Headless mode allows doing batch runs from the command line
Display and visualization:
Line, bar, and scatter plots
Speed slider lets you fast forward your model or see it in slow motion
View your model in either 2D or 3D
Scalable and rotatable vector shapes
Turtle and patch labels
APIs:
controlling API allows embedding NetLogo in a script or application
extensions API allows adding new commands and reporters to the NetLogo
language; open source example extensions are included

How to reference
If you use or refer to NetLogo in a publication, we ask that you cite it. The correct citation is:
Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected
Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
For HubNet, cite: Wilensky, U. & Stroup, W., 1999. HubNet.
http://ccl.northwestern.edu/netlogo/hubnet.html. Center for Connected Learning and
Computer-Based Modeling, Northwestern University. Evanston, IL.
For models in the Models Library, the correct citation is included in the "Credits and
References" section of each model's Info tab.

Acknowledgments
The CCL gratefully acknowledges two decades of support for our NetLogo work. The original
support came from the National Science Foundation -- grant numbers REC-9814682 and
REC-0126227. Further support has come from REC-0003285, REC-0115699, DRL-0196044,
CCF-ITR-0326542, DRL-REC/ROLE-0440113, SBE-0624318, EEC-0648316, IIS-0713619,
DRL-RED-9552950, DRL-REC-9632612, and DRL-DRK12-1020101, IIS-1441552, CNS1441016, CNS-1441041, CNS-1138461, IIS-1438813, IIS-1147621, DRL-REC-1343873, IIS1438813, IIS-1441552, CNS-1441041, IIS-1546120, DRL-1546122, DRL-1614745 and DRL1640201. Additional support came from the Spencer Foundation, Texas Instruments, the
Brady Fund, the Murphy fund, and the Northwestern Institute on Complex Systems.

NetLogo license
Copyright 1999-2018 by Uri Wilensky.
This program is free software; you can redistribute it and/or modify it under the terms of the
GNU General Public License as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program;
if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
02110-1301, USA.

Commercial licenses
Commercial licenses are also available. To inquire about commercial licenses, please contact
Uri Wilensky at uri@northwestern.edu.

NetLogo User Manual license
Copyright 1999-2018 by Uri Wilensky.

The NetLogo User Manual by Uri Wilensky is licensed under a Creative Commons AttributionShareAlike 3.0 Unported License.

Open source
The NetLogo source code is hosted at https://github.com/NetLogo/NetLogo. Contributions
from interested users are welcome.

Third party licenses
Scala
Much of NetLogo is written in the Scala language and uses the Scala standard libraries. The
license for Scala is as follows:

Copyright (c) 2002 - EPFL
Copyright (c) 2011 - Lightbend, Inc.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
Neither the name of the EPFL nor the names of its contributors may be
used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

MersenneTwisterFast
For random number generation, NetLogo uses the MersenneTwisterFast class by Sean Luke.
The copyright for that code is as follows:

Copyright (c) 2003 by Sean Luke.
Portions copyright (c) 1993 by Michael Lecuyer.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
Neither the name of the copyright owners, their employers, nor the names
of its contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNERS OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Colt
Parts of NetLogo (specifically, the random-gamma primitive) are based on code from the Colt
library (http://acs.lbl.gov/~hoschek/colt/). The copyright for that code is as follows:

Copyright 1999 CERN - European Organization for Nuclear Research. Permission
to use, copy, modify, distribute and sell this software and its documentation
for any purpose is hereby granted without fee, provided that the above
copyright notice appear in all copies and that both that copyright notice and
this permission notice appear in supporting documentation. CERN makes no
representations about the suitability of this software for any purpose. It is
provided "as is" without expressed or implied warranty.

Config
NetLogo uses the Typesafe "Config" library. Copyright (C) 2011-2012 Typesafe Inc.
http://typesafe.com The Config library is licensed under the Apache 2.0 License. You may
obtain a copy of the license at http://www.apache.org/licenses/LICENSE-2.0.

Apache Commons Codec (TM)
The NetLogo compiler uses a digest method from the Apache Commons Codec (TM) library.
Apache Commons Codec (TM) is copyright and trademark 2002-2014 the Apache Software
Foundation. It is licensed under the Apache 2.0 License. You may obtain a copy of the license
at http://www.apache.org/licenses/LICENSE-2.0.

Flexmark
NetLogo uses the Flexmark library (and extensions) for the info tab. The copyright and license
are as follows:

source and binary forms, with or without modification, are permitted provided
that the following conditions are met: * Redistributions of source code must
retain the above copyright notice, this list of conditions and the following
disclaimer. * Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution. THIS
SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

JHotDraw
For the system dynamics modeler, NetLogo uses the JHotDraw library, which is Copyright (c)
1996, 1997 by IFA Informatik and Erich Gamma. The library is covered by the GNU LGPL
(Lesser General Public License). The text of that license is included in the "docs" folder which
accompanies the NetLogo download, and is also available from
http://www.gnu.org/copyleft/lesser.html .

JOGL
For 3D graphics rendering, NetLogo uses JOGL, a Java API for OpenGL, and Gluegen, an
automatic code generation tool. For more information about JOGL and Gluegen, see
jogamp.org/. Both libraries are distributed under the BSD license:

Copyright 2010 JogAmp Community. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY JogAmp Community ``AS IS'' AND ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
EVENT SHALL JogAmp Community OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
The views and conclusions contained in the software and documentation are
those of the authors and should not be interpreted as representing official
policies, either expressed or implied, of JogAmp Community.
You can address the JogAmp Community via: Web http://jogamp.org/
Forum/Mailinglist http://forum.jogamp.org Chatrooms IRC irc.freenode.net
#jogamp Jabber conference.jabber.org room: jogamp (deprecated!) Repository
http://jogamp.org/git/ Email mediastream _at_ jogamp _dot_ org

Matrix3D
For 3D matrix operations, NetLogo uses the Matrix3D class. It is distributed under the
following license:

Copyright (c) 1994-1996 Sun Microsystems, Inc. All Rights Reserved.
Sun grants you ("Licensee") a non-exclusive, royalty free, license to use,
modify and redistribute this software in source and binary code form, provided
that i) this copyright notice and license appear on all copies of the
software; and ii) Licensee does not utilize the software in a manner which is
disparaging to Sun.
This software is provided "AS IS," without a warranty of any kind. ALL EXPRESS
OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY IMPLIED
WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NONINFRINGEMENT, ARE HEREBY EXCLUDED. SUN AND ITS LICENSORS SHALL NOT BE LIABLE
FOR ANY DAMAGES SUFFERED BY LICENSEE AS A RESULT OF USING, MODIFYING OR
DISTRIBUTING THE SOFTWARE OR ITS DERIVATIVES. IN NO EVENT WILL SUN OR ITS
LICENSORS BE LIABLE FOR ANY LOST REVENUE, PROFIT OR DATA, OR FOR DIRECT,
INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR PUNITIVE DAMAGES, HOWEVER
CAUSED AND REGARDLESS OF THE THEORY OF LIABILITY, ARISING OUT OF THE USE OF OR
INABILITY TO USE SOFTWARE, EVEN IF SUN HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
This software is not designed or intended for use in on-line control of
aircraft, air traffic, aircraft navigation or aircraft communications; or in
the design, construction, operation or maintenance of any nuclear facility.
Licensee represents and warrants that it will not use or redistribute the
Software for such purposes.

ASM
For Java bytecode generation, NetLogo uses the ASM library. It is distributed under the
following license:

Copyright (c) 2000-2011 INRIA, France Telecom. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holders nor the names of its contributors
may be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Log4j
For logging, NetLogo uses the Log4j library. The copyright and license for the library are as
follows:

Copyright 2007 The Apache Software Foundation
Licensed under the Apache License, Version 2.0 (the "License"); you may not
use this file except in compliance with the License. You may obtain a copy of
the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations under
the License.

PicoContainer
For dependency injection, NetLogo uses the PicoContainer library. The copyright and license
for the library are as follows:

Copyright (c) 2004-2011, PicoContainer Organization All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
Neither the name of the PicoContainer Organization nor the names of its
contributors may be used to endorse or promote products derived from this
software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Parboiled
For reading models, NetLogo uses the Parboiled library. The copyright and license for
Parboiled are as follows:

This software is licensed under the Apache 2 license, quoted below. Copyright

© 2009-2013 Mathias Doenitz http://parboiled2.org Copyright © 2013 Alexander
Myltsev Licensed under the Apache License, Version 2.0 (the "License"); you
may not use this file except in compliance with the License. You may obtain a
copy of the License at [http://www.apache.org/licenses/LICENSE-2.0] Unless
required by applicable law or agreed to in writing, software distributed under
the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.

RSyntaxTextArea
The NetLogo editor uses the RSyntaxTextArea library. The copyright and license are as
follows:

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met: *
Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer. * Redistributions in binary
form must reproduce the above copyright notice, this list of conditions and
the following disclaimer in the documentation and/or other materials provided
with the distribution. * Neither the name of the author nor the names of its
contributors may be used to endorse or promote products derived from this
software without specific prior written permission. THIS SOFTWARE IS PROVIDED
BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
EVENT SHALL ©RIGHT HOLDER& BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.

JCodec
The NetLogo vid extension makes use of the JCodec library. The copyright and license for
JCodec are as follows:

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer. Redistributions in binary
form must reproduce the above copyright notice, this list of conditions and
the following disclaimer in the documentation and/or other materials provided
with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.

Java-Objective-C Bridge

NetLogo on Mac OS X makes use of the Java-Objective-C Bridge library. This library was
created by Steve Hannah and is distributed under the Apache 2.0 license, available at
https://www.apache.org/licenses/LICENSE-2.0.

Webcam-capture
The NetLogo vid extension makes use of the Webcam-capture library. The copyright and
license for Webcam-capture are as follows:
The MIT License (MIT) Copyright (c) 2012 - 2015 Bartosz Firyn and Contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions: The above copyright
notice and this permission notice shall be included in all copies or
substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS",
WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Guava
The NetLogo ls extension makes use of the Guava library. Guava is released under the
Apache License 2.0 (http://www.apache.org/licenses/LICENSE-2.0)

Gephi
The nw extension makes use of the Gephi library. Gephi is licensed under the following terms:

Gephi Dual License Header and License Notice
The Gephi Consortium elects to use only the GNU General Public License version
3 (GPL) for any software where a choice of GPL license versions are made
available with the language indicating that GPLv3 or any later version may be
used, or where a choice of which version of the GPL is applied is unspecified.
For more information on the license please see: the Gephi License FAQs.
License headers are available on http://www.opensource.org/licenses/CDDL-1.0
and http://www.gnu.org/licenses/gpl.html.

R Extension
The NetLogo R Extension is licensed under the following terms:

The R extension is Copyright (C) 2009-2016 Jan C. Thiele and Copyright (C)
2016 Uri Wilensky / The Center for Connected Learning. NetLogo-R-Extension is
free software; you can redistribute it and/or modify it under the terms of the
GNU General Public License as published by the Free Software Foundation;
either version 2 of the License, or (at your option) any later version. This

program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
A PARTICULAR PURPOSE. See the GNU General Public License for more details. You
should have received a copy of the GNU General Public License along with
NetLogo-R-Extension (located in GPL.txt). If not, see
http://www.gnu.org/licenses.

JNA
The NetLogo R Extension makes use of the JNA library. The JNA library is licensed under the
following terms:

This copy of JNA is licensed under the Apache (Software) License, version 2.0
("the License"). See the License for details about distribution rights, and
the specific rights regarding derivate works. You may obtain a copy of the
License at: http://www.apache.org/licenses/

What's new?
NetLogo 6.0.4 User Manual

The following is a condensed history. Detailed release notes are on GitHub.
For help running models made in old versions, see theTransition Guide.

Version 6.0.4 (May 2018)
Feature Changes
NetLogo now supports the Portuguese language.
BehaviorSpace allows optionally disabling plots and the view when running
experiments.

Bugfixes
Updated the bundled Java 8, which should resolve an issue with NetLogo failing to start
on Windows computers.
Fixed a numerical error with the range primitive.
Fixed a bug with link lookup when using more than two link breeds.
Comment and uncomment code hotkeys should work with NetLogo include source files.
Added a better error message when a web browser couldn’t be launched for any reason.

Documentation Changes
Document that resize-world only kills all turtles when coordinates really change.

Model Changes
New Curricular Models
Mind the Gap Curriculum
MTG 1 Equal Opportunities HubNet
MTG 2 Random Assignment HubNet
MTG 3 Feedback Loop HubNet

Revised Sample Models
Blood Sugar Regulation: Updated statistical sampling procedures
Flocking: Changed default vision to 5.0 patches
Rumor Mill: Fixed a minor bug with the spread statistics in early ticks

Revised Code Examples
Flocking (Perspective Demo): Changed default vision to 5.0 patches

Revised Curricular Models

GenEvo - GenEvo 1: Fixed save screenshot bug on Windows machines
GenEvo - GenEvo 2: Fixed save screenshot bug on Windows machines
GenEvo - GenEvo 3: Fixed save screenshot bug on Windows machines

Revised Alternative Visualizations
Flocking (Alternative Visualizations): Changed default vision to 5.0 patches

Version 6.0.3 (March 2018)
Feature Changes
Improve the look & feel of Agent Monitor windows.
The procedures menu in the code tab now has a search field and actively filters
procedure names as the user types. This should improve navigation speed for large
models with lots of procedures. There is also now a hotkey to access this menu: Ctrl-G
on Windows and Linux, and Cmd-G on MacOS.
Increase the speed of the diffusion primitive and make the diffusion operation
symmetric.
NetLogo enforces that plot names are unique and that pen names are per-plot unique
without taking capitalization into account. This avoids certain cases where set-currentplot and set-current-plot-pen primitives would set the plot or pen to something
different than the user intended because names differed in capitalization only.
Models with existing plots and pens which have the same name without taking
capitalization into account will be automatically converted on first open in 6.0.3.
We are planning on adding the ability to have multiple conditional branches toifelse
and ifelse-value . However, as this is a fairly substantial change to the core language,
we have implemented it in the cf extension for testing. See the cf documentation for
information about the new syntax.

Documentation Changes
Add a table to the Output section of the Programming Guide specifying how the various
output primitives differ in whether they print the calling agent, whether they print a
newline, and whether they can be read back into NetLogo.

Bugfixes
Anonymous procedures appearing inside ask blocks inside repeat blocks now close
over unique copies of let-variables introduced in the repeat block.
Fix a longstanding HubNet bug in which HubNet would sometimes crash as a large
number of users joined.
Fix HubNet discovery when the HubNet server is run on a Mac.
When switching from the code tab to the interface tab, the cursor switches to the
command center. This prevents typed commands or copy/paste keyboard shortcuts
from affecting the code tab.
Turtles draw trails when moving backwards (regression in NetLogo 6.0.1).
Smooth Code Tab scrolling.
BehaviorSpace now only applies standard CSV string escaping (doubling of double
quotes) to string outputs in result files. It used to apply NetLogo style string escaping

(backslashes in front of special characters) and then apply CSV escaping on top of that.
The new behavior is consistent with the RFC 4180 specification and the current
behavior of the csv extension.
The Behaviorspace dialog appears centered in the NetLogo window.
Due to changes introduced in Java, certain dialogs in NetLogo 6.0.1 would appear
under the dialog that created them instead of on top. These dialogs now appear on top
of the dialog that created them.
Non-code changes to the System Dynamics modeler are pulled in on every recompile
(prior to this, changes like newly-disconnected flows were sometimes not taken into
account on recompiles).
The system dynamics code tab adjusts itself to match the size of the system dynamics
window.
NetLogo 3D loads and saves system dynamics.
Fixes an error raised in 3D when the world was cleared following setting a patch-color
to an RGB list.
Miscellaneous small changes to the format of exported worlds. NetLogo 6.0.3 should be
able to import worlds exported by older versions of NetLogo and older versions of
NetLogo should be able to import worlds exported by NetLogo 6.0.3.
The “others” execute bit is set for the netlogo-headless.sh script in the Linux installer
package.

Extension Changes
accepts a min-degree parameter, specifying the
number of links each new turtle preferentially creates to existing turtles.
The arduino extension (and the related sketch and model in the library) have been
updated to allow the arduino to send strings back to NetLogo. Two new debug
primitives have also been added to help troubleshoot interaction between NetLogo and
the arduino.
The verbose cf extension conditional syntax as been replaced with straight-forward
generalizations of the ifelse and ifelse-value primitives. The syntax is much simpler
and these primitives run much faster than the old constructs.
The ls extension has much less overhead for calling out to single models, making
constructs like ask turtles [ ls:ask my-model [ run-something ] ] much faster.
The ls extension now seeds the child model RNG based on the parent model RNG at
model creation. Furthermore, and ls:random-seed primitive has been introduced, so an
entire model system can be seeded simultaneously. This makes it possible to have
reproducible runs when using LevelSpace.
The ls:let primitive now handles scoping properly.
ls:assign has been added to LevelSpace to make assigning globals of child models
easier.
nw:generate-preferential-attachment

Documentation Changes
Clarify documentation around __includes by providing examples.
Fix a broken link in the dictionary.
Update the Windows unattended installation directions in the FAQ.

Model Changes
New Sample Models:
Bidding Market

Blood Sugar Regulation
Rock Paper Scissors
Vision Evolution

New Curricular Models
NIELS - Current in a Wire HubNet

New HubNet Activities:
Current in a Wire HubNet (same as above)

Revised Code Examples:
Extension: The example model and sketch have been updated to reflect new
features in the extension
sound Extension – Sound Workbench: Minor GUI updates
sound Extension – Percussion Workbench: Minor GUI updates
File Input Example: Fixed a bug in the save-patch-data template procedure
Lottery Example: Corrected Related Models from Preferential Attachment to the Rnd
Example Model in the Info Tab
Info Tab Example: Corrected reference from pegdown to flexmark in the Info Tab
arduino

Revised Curricular Models:
BEAGLE Evolution - Fish Tank Genetic Drift: Update duplicate plot-pen names and
resize plots
GenEvo - GenEvo 4: Replaced usage of cf:when with nested ifelses
Lattice Land - Lattice Land Explore: Fixed bug when deleting a segment that didn’t
exist.
Lattice Land - Lattice Land Triangles Dissection: Fixed bug when deleting a segment
that didn’t exist.
NIELS - Electrostatics: All turtles are now particles and each particle has a charge;
Changed particle coloring; Updated Info Tab and some variable names to reflect later
NIELS models
Urban Suite - Tijuana Bordertowns: Minor Info Tab updates.

Revised Sample Models:
Artificial Anasazi: Update broken URLs in Info Tab
Autumn: Update broken URLs in Info Tab
HIV: The AIDS model has been renamed to HIV†
Color Fractions: Removed direct reference to dead web page in Info Tab
Fairy Circles: Update URLs in Info Tab
Fur: Update broken URLs in Info Tab
Hex Cell Aggregation: Update broken URLs in Info Tab
Ising: Update broken URLs in Info Tab
Kicked Rotators: Update broken URLs in Info Tab
Language Change: Update URLs in Info Tab
Lennard-Jones: Added citation in the Info tab
Lightning: Update URLs in Info Tab.
L-System Fractals: Update broken URLs in Info Tab

Membrane Formation: Update broken URLs in Info Tab
Moth: Update URLs in Info Tab
Party: Fix incorrect comment on turtle headings.
PD Basic: Minor GUI updates
Segregation: Update broken URLs in Info Tab. Update color scheme for color blindness.
Minor GUI updates. Minor Info Tab updates.
Sugarscape 1 Immediate Growback: Fixed “Wealth distribution” histogram bug (turtle
with max sugar was not displayed)
Sugarscape 2 Constant Growback: Fixed “Wealth distribution” histogram bug (turtle
with max sugar was not displayed)
Sugarscape 3 Wealth Distribution: Fixed “Wealth distribution” histogram bug (turtle
with max sugar was not displayed)

Revised IABM Models:
Arduino Example: The example model and sketch have been updated to reflect new
features in the extension (same as above)
Segregation Simple Extension 1: Update broken URLs in Info Tab
Segregation Simple Extension 2: Update broken URLs in Info Tab
Segregation Simple Extension 3: Update broken URLs in Info Tab
Segregation Simple: Update broken URLs in Info Tab

† - Models Updated to Correctly Reference the HIV Model
Alternative Visualizations
Virus - Alternative Visualization
Virus - Circle Visualization
Curricular Models
epiDEM Basic
epiDEM Travel and Control
IABM Models
Spread of Disease
Sample Models:
Disease Solo
Virus
Rumor Mill

Version 6.0.2 (August 2017)
Feature Changes
The autosuggest functionality introduced in NetLogo 6 will now display extension
primitive names.
A new insert-item primitive was added to the language. It works similarly toreplaceitem, but without removing the item at the specified index.
A new set-plot-background-color primitive was added to the language. It can be used
in plotting code to set the background color of the plot.
Behaviorsearch’s user interface has been updated. It now uses the JavaFX UI toolkit for
a more modern look and feel.

Bugfixes

The 6.0.1 autoconverter would error when converting tasks with exactly one argument
(from 5.3.1 and earlier models only). The conversion would be correct, but it was
confusing. This has now been remedied and the autoconverter will correctly convert
models from 5.3.1 and earlier without erroring on single-argument tasks.
Fix a bug where extensions weren’t located properly when in a path relative to the
model.
Help browser now opens in 64-bit Windows.
Fix a speed regression for the import-world primitive introduced in 6.0.
If an unexpected reporter block is passed to with when used with other, the error will
now reflect that the block is unsuitable for with instead of other.
When sort-by receives an unsuitable reporter block from the user it now shows a useful
error instead of a cryptic stack trace.
String representations of anonymous procedures now show the arguments of those
anonymous procedures
When working in an nls file, switching to a different tab will compile the nls file.
Display error label on nls file when the code it contains causes an error.
Some users were unable to open NetLogo 6 and 6.0.1 in Mac OS Sierra. We’ve
changed our signing process in 6.0.2 to attempt to fix this problem. We are continuing to
track this issue to determine whether our fix was effective. More information (including a
partial workaround for the problem) is available here.

Extension Changes
Fixed a bug in gis:patch-dataset introduced in NetLogo 6.
The table extension has new table:group-agents and table:group-items primitives
which can be used to build a table of grouped agents and items by supplying an
anonymous reporter.

Documentation Changes
Clarify when various parts of the anonymous procedure syntax are optional.
Fix a few small documentation bugs around foreach .
Clarify relationship between speed and update modality in the “View Updates” section of
the programming guide.

Model Changes
New Sample Models:
Chaos in a Box
Fairy Circles
SmoothLife

New Curricular Models:
Lattice Land Curriculum
Lattice Land - Triangles Explore
Lattice Land - Triangles Dissection

Revised Sample Models:

Anisogamy: New color scheme. Adds BehaviorSpace experiments.
Ethnocentrism: Now cross-listed as an Evolutionary model.
Fireworks: Rename fireworks to max-fireworks and enforce a minimum of 1.
GenJam - Duple: Minor info tab updates.
Wolf Sheep Predation: Revised to better clarify the grass? construct and code.

Revised Curricular Models:
Connected Chemistry:
Connected Chemistry 1: Fix NetLogo Web incompatibility.
Connected Chemistry 3: Update minimum number of particles to 2.
Connected Chemistry 8: Minor code updates. Small change to default values.

Revised HubNet Activities:
Gridlock HubNet: Minor code updates.

Revised Code Examples:
Info Tab Example: Corrected formatting of un/ordered lists example.
LS Extension – Model Visualizer and Plotter Example: Updated code dependencies for
WSP.
LS Extension – Model Interactions Example: Updated code dependencies for WSP.

Version 6.0.1 (March 2017)
Feature Changes
Brackets are required around anonymous procedure reporters only when there are two
or more arguments. For instance [ [x] -> x ] can now be written [ x -> x ] . Note this
change makes it possible to create models in NetLogo 6.0.1 that will not run in NetLogo
6.0. If you plan to use your model in NetLogo 6.0, be sure to include brackets around
anonymous procedure arguments. For a short period after the release, models which
use unbracketed lambda arguments may not work on netlogoweb.org.

Bugfixes
The NetLogo code editor navigates and indents models much more quickly and
efficiently than in NetLogo 6.0.
The NetLogo 5-to-6 autoconverter now ignores commented-out code.
The behavior of layout-radial in NetLogo 6 did not match the 5.3.1 behavior. This has
been corrected and layout-radial should be identical between NetLogo 6.0.1 and
NetLogo 5.3.1
NetLogo 6 raised a NullPointerException when numbers became too large for NetLogo
to handle. This is now properly displayed to the user as a number out of bounds error.
Improved performance of models which use let and anonymous procedures together.
Reloading a model now clears global variables.
Clearer warning dialogs when opening an older version of a NetLogo 2D file in NetLogo
3D.
Using foreach improperly in the Command Center will display the same error as it would
if used improperly in the code tab.

Extremely long anonymous procedures no longer cause an exception when compiled.
in-radius is no longer pathologically slow on agentsets created usingwith.

Extension Changes
A new primitive, table:values has been added to the table extension.
The R extension has been updated to take full advantage of the JavaGD R library using
r:setPlotDevice.
Users can now supply a path to the R extension by configuring the value of r.lib.paths in
the user.properties file.
Fixed a LevelSpace bug preventing interactive models from using nls files.
Fixed a LevelSpace bug causing NetLogo to lock up when trying to load a nonexistent
file as an interactive model.

Documentation Changes
The system dynamics tutorial now instructs the user to set thedt to a value which gives
stable behavior
The documentation for follow, ride, and watch has been clarified to indicate that calling
one undoes highlights and perspective changes caused by the other
The documentation for = and != indicates that they work with extension objects.
Several examples have been added to sort clarifying the behavior of sort on lists
featuring different types of objects.
A new section on User Interface primitives has been added to the programming guide
which discusses the behavior of the “Halt” button in the various user interaction dialogs.
Incorrect example code for foreach and reduce has been corrected.

Models
All models have been updated to reflect the new optional nature of brackets for zero/one
argument anonymous procedures. This resulted in changes to 108 models.
All models have been updated to reflect the availability of the new range primitive. This
resulted in changes to 12 models.

New Sample Model
GenJam - Duple

New Curricular Model
Lattice Land curriculum:
Lattice Land Explore

Revised Sample Models
PD 2 Person Iterated: info tab updates and extensive fixes for the code.
Party: fixed bug where a monitor covered a plot.
Signaling Game: info tab updates.

Revised Curricular Models
GenEvo curriculum:
GenEvo 1 Genetic Switch: info tab updates and new graduated method of
displaying lacZ concentration.
GenEvo 2 Genetic Drift: info tab updates and interface tweaks. New model
preview.
GenEvo 3 Genetic Drift and Natural Selection: info tab updates and interface
tweaks.
GenEvo 4 Competition: info tab updates.
Genetic Switch - Synthetic Biology has been renamed and is now Synthetic
Biology - Genetic Switch. It also received info tab updates and a few interface
changes.

Version 6.0 (December 2016)
Feature Changes
The NetLogo code editor now offers autocompletion support. Simply press the Control
key and the spacebar at the same time while typing a word and you will see a list of
similar NetLogo primitives as suggestions.
The NetLogo code editor offers the option to “fold” procedures to make navigating large
models simpler.
NetLogo supports multi-level agent-based modeling with the LevelSpace extension
Line numbering can be enabled in the NetLogo code editor by choosing “Show Line
Numbers” from the “Preferences” dialog. This dialog can be opened by selecting
“NetLogo” > “Preferences” in Mac, or “Tools” > “Preferences” on Linux or Windows.
The view resizing arrows have been removed and the tick counter has been relocated
under the speed slider.
When editing NetLogo code, users can right-click a variable name or primitive and
choose “Show Usage” to see all usages of that name in the file.
When editing NetLogo code, users can right-click a variable name and choose “Jump to
Declaration” to see where in the file that variable is declared.
The NetLogo interface editor now supports “Undo” for widget addition, deletion, and
movement.
NetLogo can export code to HTML with code-colorization by choosing “Export Code” in
the “Export” section of the “File” menu.
The look and feel of NetLogo on Mac OS X has changed significantly. NetLogo is now
using the Oracle-supplied Java look and feel as opposed to a third-party look and feel
used in prior versions.
Plots use a random number generator independent of the main-model random number
generator.
Model Preview Commands can be edited through the GUI by choosing “Preview
Commands Editor” in the “Tools” menu. Those commands generate the preview image
that appears when you upload your model to the Modeling Commons.
NetLogo displays a more helpful error message when a program fails due to an “out of
memory” error.
NetLogo and its bundled extensions are now compiled against Java 8 and Scala 2.12.
NetLogo has upgraded the ASM bytecode library to enable generation of Java 8
bytecode.

Bugfixes

primitives now work the same way for breeded and unbreeded links.
Resizing the world in NetLogo 3D no longer causes a black view.
Fixed error caused by right-clicking a widget while dragging.
Improved error message when a user-defined procedure shadows a breed procedure.
neighbors4 and neighbors no longer report agentsets containing the same patch more
than once.
*-link-neighbor?

Language Changes
Support for plural-only breed names (e.g., breed [mice] ) has been removed. Write breed
[mice mouse] instead.
Tasks have been replaced by anonymous procedures. Tasks made use of ? variables
which were confusing for novices and difficult to read for experts. Additionally, tasks
could not refer to the task variables of a containing task. Anonymous procedures may
have named arguments which can be accessed by inner anonymous tasks. Upon first
opening a NetLogo 5 model in NetLogo 6, tasks like task [ ?1 + ?2 ] will be
automatically converted to [ [?1 ?2] -> ?1 + ?2 ] . See the the transition guide for
more information.
Link reporters have been overhauled to be more consistent and flexible
The task primitive is no longer supported.
Breed names that conflict with language primitives are now disallowed. For instance,
breed [strings string] is now disallowed since it makes is-string? ambiguous.
The compiler errors on duplicated breed singular names.
The compiler detects a greater number of type errors, for instancenot pxcor now raises
a compiler error instead of erroring at runtime.
set-plot-pen-color now accepts RGB lists as arguments.
The hubnet-set-client-interface primitive has been removed.
The various primitives starting with movie- have been removed, as has the movie
encoder. They have been replaced with the new vid extension. The transition guide
provides more details and information.
The __change-language primitive has been removed. You can now change the User
Interface Language through the preferences dialog, which can be found by choosing
“Preferences…” in the “NetLogo” menu (Mac OS X) or in the “Tools” menu (all other
platforms).
The string representation of anonymous procedures displays the body of the
anonymous procedure.

Extension Changes
NetLogo 6.0 comes with three new, bundled extensions: LevelSpacels, the vid
extension for video manipulation, and the enhanced visualization extension view2.5d.
ls enables multi-level agent-based modeling in NetLogo.
The Extensions API has been updated from 5.0 to 6.0. This means that all non-bundled
extensions will need to be updated to use the new API. Extensions written for NetLogo
5 will not work in NetLogo 6. If you’re an extension author, seethe extension author
transition guide for 6.0 for more information. If you regularly use extensions you may
want to contact their authors to inform them a new version of NetLogo is on the way and
they may want to update their extensions.
arduino:get (in the arduino extension) correctly reports values from Windows 64-bit
machines. In prior versions it would only report some values correctly.
Several new features have been added to thenw extension:
Added community detection using the Louvain method
Added modularity measurement
Added Watts-Strogatz small-world network generation

Made other network generation algorithms easier to layout
Weighted primitives now take symbolic variable names instead of strings. Seethe
transition guide for more information.
The qtj extension is no longer bundled with NetLogo. Users are encouraged to make
use of the new vid extension.
The new vid extension is now bundled with NetLogo, combining features of the lateqtj
extension and the movie primitives.
The network extension is no longer bundled with NetLogo. Users are encouraged to use
the nw extension (https://ccl.northwestern.edu/netlogo/docs/nw.html), which has been
bundled with NetLogo for some time.
The gogo-serial extension is no longer bundled with NetLogo. Users are encouraged to
transition to the newer gogo extension, which uses HID to communicate with the GoGo
board.

Operating System Support
NetLogo will now be used to open .nlogo links in PowerPoint and other programs on
Microsoft Windows.
The NetLogo binaries on Mac OS X are installed as runnable by any user.
NetLogo in Mac OS X will not use “App Nap” while running. This keeps simulations
running at full speed when NetLogo is in the background.
The NetLogo controlling API has changed since NetLogo 5. Programs that rely on the
controlling API (such as BehaviorSearch) will not work until they have been changed to
match the new API.

Documentation Changes
New documentation for anonymous procedures
The NetLogo tutorial screenshots have been updated to correspond to the new Mac OS
X Look and Feel.
The NetLogo dictionary displays the version in which each primitive was introduced next
to that primitive.
A Spanish translation of the NetLogo dictionary is availablehere

Internationalization Changes
A new Spanish translation of the NetLogo dictionary is availableas part of the NetLogo
manual.
Language preferences can be changed by using the new “Preferences” menu instead of
the __change-language primitive.
A Japanese localization for NetLogo is now available and included with the standard
download.
The Chinese translation for NetLogo has been updated.

Models
New Sample Models:
Kicked Rotator
Kicked Rotators
Mammoths, a legacy StarLogoT model, has been converted to NetLogo.

New Curricular Models:
GenEvo 1 Genetic Switch
GenEvo 2 Genetic Drift
GenEvo 3 Genetic Drift and Natural Selection
GenEvo 4 Competition

New Code Examples:
Movie Playing Example (vid extension)
Movie Recording Example (vid extension)
Video Camera Example (vid extension)
Network Extension General Demo (nw extension)
Model Interactions Example (ls extension)
Model Loader Example (ls extension)
Model Visualizer and Plotter Example (ls extension)

Promoted Models (improved and no longer “unverified”):
ProbLab Genetics
Traffic 2 Lanes

Revised Sample Models:
Giant Component: added text in the info tab.
Team Assembly: removed unused switch widget.
Traffic Basic, Traffic Grid, Traffic Intersection: revised info tab.
Voting: stopped the model when voting stabilizes.
Wealth Distribution: fixed typos in info tab, improved code formatting.

Revised HubNet Activities:
Bug Hunters Competition HubNet, Critter Designers HubNet, Fish Spotters HubNet:
removed unnecessary call to hubnet-set-client-interface .
Gridlock HubNet, Gridlock Alternate HubNet: revised info tab.

Revised Curricular Models:
DNA Replication Fork: fixed a a monitor and runtime error when using a time limit.

Revised IABM models:
Agentset Efficiency: clarified description of go-2 in info tab.
Agentset Ordering: fixed typos in into tab.
Arduino Example: improved model to demonstrate both directions of communication
with the Arduino.
Heroes and Cowards: removed extra text in info tab.
Preferential Attachment Simple: removed extra pen in plot and extra “layout” button.
Random Network: made sure that the number of links is never too big for the number of
nodes.

Segregation Simple Extension 1, 2 and 3: fixed number-of-ethnicities slider to avoid
runtime errors.
Traffic Basic Adaptive Individuals, Traffic Basic Utility, Traffic Grid Goal: revised info tab.
Traffic Basic Adaptive: revised info tab, clarified comment in adaptive-go procedure.
Voting Component Verification: stopped the model when voting stabilizes.
Voting Sensitivity Analysis: improved code for stopping the model when voting
stabilizes.

Revised Code Examples:
GoGoMonitorSerial, GoGoMonitorSimpleSerial: removed the models, as the gogoserial and qtj extensions are no longer bundled.
Random Network Example: made sure that the number of links is never too big for the
number of nodes.
Since the QuickTime extension (qtj) has been replaced by the vid extension, the
following models have been converted to use the vid extension:
Movie Example, replaced by Movie Recording Example
QuickTime Movie Example, replaced by Movie Playing Example
QuickTime Camera Example, replaced by Video Camera Example

Demoted model:
El Farol Network Congestion, a previously “unverified” model, has been moved to the
NetLogo User Community Models

Version 5.3.1 (February 2016)
Feature Changes
Mathematica Link is now included and has been tested to work with Mathematica 10.
A link to Introduction to Agent-Based Modelling has been added to the “Help” menu.

Extension Changes
The gogo extension now prompts the user for the location of Java upon opening. This
version of Java is used to launch the gogo hid daemon.
The correct version of the network extension is now bundled, which will open properly
Bundles the cf extension, which adds match, case, and select primitives.

Bugfixes
Corrects a bug where turtles wrapping around a torus-shaped world with pen down
would sometimes cause NetLogo to loop infinitely.
Fixes a bug where buttons would appear to remain pressed after a right click on Mac.
Fixes a bug where pressing the right mouse button while dragging would confuse the
mouse-down? primitive.
Fixes agent type-checking of tasks (bug appeared in 5.2.1).
link-neighbor? now returns true if and only if the neighbor is connected through an
undirected link.
Documentation fixes for my-links and mean primitives.

Version 5.3 (December 2015)
Feature Changes
Java 8 is now bundled with all versions of NetLogo, this removes the need for a
separate Java 6 installation on Mac OS X
Separate 32-bit and 64-bit versions are available for both Windows and Linux
The Windows installer is now an msi instead of an exe
javax.media.opengl is no longer supported in Java 8, it has been replaced by
com.jogamp.opengl
Mathematica Link is not distributed due to Java version changes

Extension Changes
A minor update to the nw extension makes nw:weighted-path-to behave as
documented.
Most extensions should continue to work without change unless they rely on
javax.media.opengl, which was renamed in the updated version of JOGL.

Version 5.2.1 (September 2015)
Extensions
An included Arduino extension for use with Arduino boards

New features
New file menu item to export models to NetLogo Web

Bug fixes
BehaviorSpace output type preference is now remembered
Output widget font is now saved at the proper size when zoomed
Reporter tasks are now evaluated in variable context
runresult arguments now only get evaluated once
The last used directory is now remembered on Linux
Whitespace is now stripped from models when saving
New Sample Models: Artificial Anasazi, Bacteria Food Hunt, Bacteria Hunt Speeds,
BeeSmart - Hive Finding, Bug Hunt Disruptions, Bug Hunt Environmental Changes, Bug
Hunt Predators and Invasive Species - Two Regions, Hydrogen Diffusion 3D, LennardJones, Paths
There are 46 new models in the new IABM Textbook folder: Turtles Circling Simple,
Ants Simple, Heroes and Cowards, Life Simple, Simple Economy, 4 DLA extensions, 4
El Farol Extensions, 4 Fire Extensions, 4 Segregation Extensions, 5 Wolf Sheep
Extensions, Agentset Efficiency, Agentset Ordering, Communication-T-T Network
Example, Preferential Attachment Simple, Random Network, Traffic Basic Adaptive,
Traffic Basic Utility, Traffic Grid Goal, Spread of Disease, Voting Component
Verification, Voting Sensitivity Analysis, Arduino Example, Disease With Android

Avoidance HubNet, Example HubNet, Run Example, Run Result Example, Simple
Machine Learning, Simple Viral Marketing, Ticket Sales, Sandpile Simple
New models in the new Alternate Visualizations folder: Ethnocentrism - Alternative
Visualization, Flocking - Alternative Visualizations, Heat Diffusion - Alternative
visualization, Virus - Alternative Visualization, Virus - Circle Visualization
Promoted models: Honeycomb, Minority Game
Many other bugfixes and upgrades

Model changes
Improved Sample Models: Altruism, Ant Lines, Artificial Anasazi, Cooperation,
Daisyworld, Divide the Cake, Heat Diffusion, Hydrogen Diffusion 3D, Lennard-Jones, NBodies, PD Basic Evolutionary, Sandpile, Robby the Robot, Segregation, Simple
Kinetics 2 and 3, Traffic Grid, GridLock HubNet, GridLock HubNet Alternate
Revised Curricular Models: 4 Block Stalagmites, 4 Block Two Stalagmites, Bug Hunter
Competition HubNet, Fish Spotters HubNet, Ising, Tijuana Bordertowns, Urban Suite Tijuana Bordertowns,
Revised Code Examples: Lottery Example, self Example, Network Import Example
Revised IABM Textbook models: Simple Economy, Fire Simple Extension 2 and 3,
Segregation Simple, 1, 2 and 3, Agentset Efficiency, Preferential Attachment Simple,
Random Network, Traffic Basic Adaptive, Run Example, Traffic Grid Goal,
New IABM Textbook model: Traffic Basic Adaptive Individuals

Version 5.2.0 (April 2015)
Extensions
An included CSV extension to read and write CSV files
An included Palette extension to map different values to colors
The previous gogo extension has been removed. It has been replaced with two different
gogo extensions, gogo and gogo-serial. The extensions work with different hardware.
The gogo extension works with the new style HID-interface gogo boards and the gogoserial extension works with the old-style serial-interface gogo boards
Upgrade to the network extension including the following changes:
Support for many more file types, including GEXF, GDF, GML, Pajek NET,
UCINET DL, and Netdraw VNA
Fixed bugs with GraphML support
Improved documentation

New features
New primitive netlogo-web? added to test whether you are currently running in NetLogo
Web
New primitive behaviorspace-experiment-name added allowing you to get the name of
the currently running experiment
New primitive stop-inspecting to stop inspecting agents
New primitive stop-inspecting-dead-agents and menu item to stop inspecting dead
agents
__includes keyword now enables the Includes button when given an empty
hooks added for extensions to write custom log messages

Bug fixes

user-one-of will now signal an error earlier when provided an empty list of choices
hsb, extract-hsb, and approximate-hsb have been updated to represent true hsb

conventions
new deprecated primitives __hsb-old, __extract-hsb-old, and __approximate-hsb-old
work as the old hsb primitives did when older models using the hsb primitives are
opened in NetLogo 5.2, they will be auto-converted to use the deprecated primitives
extract-hsb – fixed bug where it didn’t work correctly on rgb lists

Model changes
New Sample Models: Artificial Anasazi, Bacteria Food Hunt, Bacteria Hunt Speeds,
BeeSmart - Hive Finding, Bug Hunt Disruptions, Bug Hunt Environmental Changes, Bug
Hunt Predators and Invasive Species - Two Regions, Hydrogen Diffusion 3D, LennardJones, Paths
There are 46 new models in the new IABM Textbook folder: Turtles Circling Simple,
Ants Simple, Heroes and Cowards, Life Simple, Simple Economy, 4 DLA extensions, 4
El Farol Extensions, 4 Fire Extensions, 4 Segregation Extensions, 5 Wolf Sheep
Extensions, Agentset Efficiency, Agentset Ordering, Communication-T-T Network
Example, Preferential Attachment Simple, Random Network, Traffic Basic Adaptive,
Traffic Basic Utility, Traffic Grid Goal, Spread of Disease, Voting Component
Verification, Voting Sensitivity Analysis, Arduino Example, Disease With Android
Avoidance HubNet, Example HubNet, Run Example, Run Result Example, Simple
Machine Learning, Simple Viral Marketing, Ticket Sales, Sandpile Simple
New models in the new Alternate Visualizations folder: Ethnocentrism - Alternative
Visualization, Flocking - Alternative Visualizations, Heat Diffusion - Alternative
visualization, Virus - Alternative Visualization, Virus - Circle Visualization
Promoted models: Honeycomb, Minority Game
Many other bugfixes and upgrades

Version 5.1.0 (July 2014)
bundle new network extension
File menu includes recently opened files
deprecate applets
support retina display on new MacBooks

Version 5.0.4 (March 2013)
upload models to the Modeling Commons

Version 5.0 (February 2012)
features:
open source (GPL license; source code online at
https://github.com/NetLogo/NetLogo)
new license for Sample Models and Curricular Models is Creative Commons
Attribution-NonCommercial-ShareAlike
international characters (Unicode) supported throughout application
GUI is localized in Spanish, Russian, and Chinese (volunteer translators wanted)
rich formatting and images in Info tabs using Markdown
plotting code goes inside plots instead of in code tab
authorable model speed (target frame rate setting)
buttons optionally disable until ticks start

translucent colors in 3D view and NetLogo 3D (for RGB colors only)
language changes:
“tasks” store code to be run later
aka first-class functions, closures, lambda
new primitives: task, is-command-task?, is-reporter-task?
these primitives accept tasks: run, runresult, foreach , map, reduce, filter, nvalues, sort-by
improved overall list performance (many operations take near-constant time
instead of linear time)
you must use reset-ticks to start the tick counter before usingtick or tickadvance

new primitives setup-plots and update-plots
new primitive sort-on lets you say e.g., sort-on [size] turtles
new primitive error causes a runtime error
random-normal rejects negative standard deviations
HubNet:
activities can run headless
new primitives hubnet-clients-list, hubnet-kick-client , hubnet-kick-allclients
hubnet-set-client-interface

no longer required
other fixes and changes:
tabs renamed to Interface/Info/Code
Command Center allows reporters, adds show command automatically
NetLogo 3D uses .nlogo3d suffix, not .nlogo
import-world is much faster
startup no longer runs headless or in background BehaviorSpace runs
fixed 3D rendering bug where small turtles were too bright
Mac app runs in 64 bit mode by default
upgraded Windows installer
GoGo extension getting-started experience now smoother on all platforms
models:
new Sample Models: Sandpile, Lightning, Osmotic Pressure, Robby the Robot,
Preferential Attachment 3D
new Curricular Models: Bug Hunt Consumers, Bug Hunt Predators and Invasive
Species, Plant Speciation, epiDEM Basic, epiDEM Travel and Control, Connected
Chemistry Atmosphere
new Code Examples: Info Tab Example, GoGoMonitorSimple

Version 4.1.3 (April 2011)
matrix extension
behaviorspace-run-number

Version 4.1 (December 2009)
parallel BehaviorSpace
controlling API allows embedding
automatic code indenter
searchable Models Library
translucent colors
mini-views in agent monitors
resize-world , set-patch-size
bitmap, QuickTime extensions
individualized HubNet client views
browser-based HubNet client

Version 4.0 (September 2007)
link agents
tick counter
view update modes (tick-based, continuous)
speed slider fast forwards
input boxes in interface tab
include multiple source files
RGB colors
slider bounds may be reporters
HubNet client editor
Mathematica-NetLogo link
array, table, profiler, GIS extensions
models run faster (partial compilation to JVM byte code)
logging

Version 3.1 (April 2006)
topologies (optional wrapping at world edges)
randomized agentset ordering

Version 3.0 (September 2005)
3D view (for 2D models)
formatted Info tabs
System Dynamics Modeler
follow, ride, watch
drawing layer
GoGo extension

Version 2.1 (December 2004)
“headless” mode for command line operation
“action keys” to trigger buttons by keypresses
makes QuickTime movies of models
let, carefully

Version 2.0.2 (August 2004)
extensions and controlling APIs
sound extension

Version 2.0 (December 2003)
fast, flicker-free, non-grid-based graphics

Version 1.3 (June 2003)
run, runresult, map, foreach , filter, reduce

Version 1.2 (March 2003)

computers as HubNet clients

Version 1.1 (July 2002)
Applets

Version 1.0 (April 2002)
first full release (after a series of betas)

System Requirements
NetLogo 6.0.4 User Manual

NetLogo runs on almost any current computer.
If you have any trouble with NetLogo not working, see Contacting Us.

Application Requirements
Windows
NetLogo runs on Windows 10, Windows 8, Windows 7 and Vista. NetLogo 5.2.1 was the last
version to support Windows XP and Windows 2000.
The NetLogo installer for Windows includes Java 8 for NetLogo’s private use only. Other
programs on your computer are not affected.

Mac OS X
Mac OS X 10.8.3 or newer is required. (NetLogo 5.1 was the last version to support 10.5 and
10.4; NetLogo 5.2.1 was the last version to support 10.6 and 10.7)
The NetLogo application contains a distribution of the Java 8 runtime for NetLogo’s private
use only. Other programs on your computer will not be affected.

Linux
NetLogo should work on standard Debian-based and Red Hat-based Linux distributions. The
NetLogo tarball includes a copy of the Java 8 runtime.
Start NetLogo by running the provided NetLogo executable.

3D Requirements
Occasionally an older, less powerful system is not able to use the 3D view or NetLogo 3D.
Try it and see.
Some systems can use 3D but can’t switch to full-screen mode. It depends on the graphics
card or controller. (For example, the ATI Radeon IGP 345 and Intel 82845 probably will not
work.)

32-bit or 64-bit?
For most users on Linux or Windows, the 32-bit version of NetLogo is the simplest way to a
working NetLogo installation. Advanced users will want to understand the advantages of 64bit NetLogo as well as how to determine whether their machine meets the requirements.
The primary advantage of the 64-bit version is the ability to add additional heap space by
changing the “-Xmx” JVM option. For more information, see How big can my model be. You
may also find it helpful to browse Oracle’s documentation on the performance characteristics
of the 64-bit JVM

To run 64-bit NetLogo, you must be running 64-bit Windows. To determine whether your
version of Windows is 64-bit, see Is my PC running the 32-bit or 64-bit version of Windowsif
you’re using Windows Vista, or Windows 7, or Which Windows operating system am I
running? if you are running any other version of Windows.
For Linux users, the easiest way to determine whether your operating system is 64-bit is
checking the output of
uname -m

If the output shows “x86_64” or “amd64”, you should be able to run the 64-bit version.

Contacting Us
NetLogo 6.0.4 User Manual

Feedback from users is essential to us in designing and improving NetLogo. We’d like to hear
from you.

Web site
Our web site at http://ccl.northwestern.edu/ includes our mailing address and phone number.
It also has information about our staff and our various research activities.

Feedback, questions, etc.
For help using NetLogo, try this group: http://groups.google.com/d/forum/netlogo-users.
If you have feedback, suggestions, or questions, you may write us at
feedback@ccl.northwestern.edu.

Reporting bugs
Our public bug tracker is on GitHub at https://github.com/NetLogo/NetLogo/issues. You can
look here to report a new bug, check if a bug has already been reported, and so on.
When submitting a bug report, please try to include as much of the following information as
possible:
A complete description of the problem and how it occurred.
The NetLogo model or code you are having trouble with. If possible, attach a complete
model. (It’s best if you can reduce the amount of code in the model to the minimum
necessary to demonstrate the bug.)
Your system information: NetLogo version, OS version, Java version, and so on. This
information is available from NetLogo’s “About NetLogo” menu item, then clicking the
System tab.
Any error messages that were displayed. Please copy and paste the entire error
message into your email, or make a screen capture if you are unable to copy and paste.
We also accept bug reports by email at bugs@ccl.northwestern.edu.

Open source
NetLogo is free, open source software. The source code is hosted at
https://github.com/NetLogo/NetLogo. Contributions from interested users are welcome.
For discussion of NetLogo API’s and the development of NetLogo itself, try
https://groups.google.com/group/netlogo-devel.

Sample Model: Party
NetLogo 6.0.4 User Manual

This activity gets you thinking about computer modeling and how you can use it. It also gives
you insight into NetLogo itself. We encourage beginning users to start here.

At a Party
Have you ever been at a party and noticed how people cluster in groups? You may have also
noticed that people don’t just stay in a group. As they circulate, the groups change. If you
watched these changes over time, you might notice patterns.
For example, in social settings, people may exhibit different behavior than at work or home.
Individuals who are confident within their work environment may become shy and timid at a
social gathering. And others who are reserved at work may be the “party starter” with friends.
These patterns can depend on the type of gathering. In some settings, people are trained to
organize themselves into mixed groups; for example, party games or school-like activities. But
in a non-structured atmosphere, people tend to group in a more random manner.
Is there any type of pattern to this kind of grouping?
Let’s take a closer look at this question by using the computer to model human behavior at a
party. NetLogo’s “Party” model looks specifically at the question of grouping by gender at
parties: why do groups tend to form that are mostly men, or mostly women?
Let’s use NetLogo to explore this question.
What to do:
1. Start NetLogo.
2. Choose “Models Library” from the File menu.

3.
4.
5.
6.

Open the “Social Science” folder.
Click on the model called “Party”.
Press the “open” button.
Press the “setup” button.

In the view of the model, you will see pink and blue groups with numbers:

These lines represent mingling groups at a party. Men are shown as blue, women pink. The
numbers are the sizes of the groups.
Do all the groups have about the same number of people?
Do all the groups have about the same number of each sex?
Let’s say you are having a party and invited 150 people. You are wondering how people will
gather together. Suppose 10 groups form at the party.
How do you think they will group?
Instead of asking 150 of your closest friends to gather and randomly group, let’s have the
computer simulate this situation for us.
What to do:
1.
2.
3.
4.

Press the “go” button. (Pressing “go” again will stop the model manually.)
Observe the movement of people until the model stops.
Watch the plots to see what’s happening in another way.
Use the speed slider if you need to slow the model down.

Now how many people are in each group?
Originally, you may have thought 150 people splitting into 10 groups, would result in about 15
people in each group. From the model, we see that people did not divide up evenly into the 10
groups. Instead, some groups became very small, whereas other groups became very large.
Also, the party changed over time from all mixed groups of men and women to all single-sex
groups.
What could explain this?
There are lots of possible answers to this question about what happens at real parties. The
designer of this simulation thought that groups at parties don’t just form randomly. The groups
are determined by how the individuals at the party behave. The designer chose to focus on a
particular variable, called “tolerance”:

Tolerance is defined here as the percentage of people of the opposite sex an individual is
“comfortable” with. If the individual is in a group that has a higher percentage of people of the
opposite sex than their tolerance allows, then they become “uncomfortable” and leave the
group to find another group.
For example, if the tolerance level is set at 25%, then males are only “comfortable” in groups
that are less than 25% female, and females are only “comfortable” in groups that are less

than 25% male.
As individuals become “uncomfortable” and leave groups, they move into new groups, which
may cause some people in that group to become “uncomfortable” in turn. This chain reaction
continues until everyone at the party is “comfortable” in their group.
Note that in the model, “tolerance” is not fixed. You, the user, can use the tolerance “slider” to
try different tolerance percentages and see what the outcome is when you start the model
over again.
How to start over:
1. If the “go” button is pressed (black), then the model is still running. Press the
button again to stop it.
2. Adjust the “tolerance” slider to a new value by dragging its red handle.
3. Press the “setup” button to reset the model.
4. Press the “go” button to start the model running again.

Challenge
As the host of the party, you would like to see both men and women mingling within the
groups. Adjust the tolerance slider on the side of the view to get all groups to be mixed as an
end result.
To make sure all groups of 10 have both sexes, at what level should we set the
tolerance?
Test your predictions on the model.
Can you see any other factors or variables that might affect the male to female
ratio within each group?
Make predictions and test your ideas within this model.
As you are testing your hypotheses, you will notice that patterns are emerging from the data.
For example, if you keep the number of people at the party constant but gradually increase
the tolerance level, more mixed groups appear.
How high does the tolerance value have to be before you get mixed groups?
What percent tolerance tends to produce what percentage of mixing?

Thinking with models
Using NetLogo to model a situation like a party allows you to experiment with a system in a
rapid and flexible way that would be difficult to do in the real world. Modeling also gives you
the opportunity to observe a situation or circumstance with less prejudice, as you can
examine the underlying dynamics of a situation. You may find that as you model more and
more, many of your preconceived ideas about various phenomena will be challenged. For
example, a surprising result of the Party model is that even if tolerance is relatively high, a
great deal of separation between the sexes occurs.
This is a classic example of an “emergent” phenomenon, where a group pattern results from

the interaction of many individuals. This idea of “emergent” phenomena can be applied to
almost any subject.
What other emergent phenomena can you think of?
To see more examples and gain a deeper understanding of this concept and how NetLogo
helps learners explore it, you may wish to explore NetLogo’s Models Library. It contains
models that demonstrate these ideas in systems of all kinds.
For a longer discussion of emergence and how NetLogo helps learners explore it, see
“Modeling Nature’s Emergent Patterns with Multi-agent Languages” (Wilensky, 2001).

What’s next?
The section of the User Manual called Tutorial #1: Running Models goes into more detail
about how to use the other models in the Models Library.
If you want to learn how to explore the models at a deeper level,Tutorial #2: Commands will
introduce you to the NetLogo modeling language.
Eventually, you’ll be ready for Tutorial #3: Procedures. There you can learn how to alter and
extend existing models to give them new behaviors, and you can start to build your own
models.

Tutorial #1: Models
NetLogo 6.0.4 User Manual

If you read the Sample Model: Party section, you got a brief introduction to what it’s like to
explore a NetLogo model. This section will go into more depth about the features that are
available while you’re exploring the models in the Models Library.
Throughout all of the tutorials, we’ll be asking you to make predictions about what the effects
of making changes to the models will be. Keep in mind that the effects are often surprising.
We think these surprises are exciting and provide excellent opportunities for learning.
You may want to print out the tutorials to make them easier to refer to while you’re using
NetLogo.

Sample Model: Wolf Sheep Predation
We’ll open one of the Sample Models and explore it in detail. Let’s try a biology model: Wolf
Sheep Predation, a predator-prey population model.

Open the Models Library from the File menu.

Choose “Wolf Sheep Predation” from the Biology section and press “Open”.

The Interface tab will fill up with lots of buttons, switches, sliders and monitors. These
interface elements allow you to interact with the model. Buttons are blue; they set up, start,
and stop the model. Sliders and switches are green; they alter model settings. Monitors and
plots are beige; they display data.
If you’d like to make the window larger so that everything is easier to see, you can use the
Zoom menu.
When you first open the model, you will notice that the “view” (the graphical display of the
agents in the model) is empty (all black). To begin the model, you will first need to set it up.

Press the “setup” button.
What do you see appear in the view?

Press the “go” button to start the simulation.
As the model is running, what is happening to the wolf and sheep
populations?
Press the “go” button to stop the model.

Controlling the Model: Buttons
When a button is pressed, the model responds with an action. A button can be a “once”
button, or a “forever” button. You can tell the difference between these two types of buttons
by a symbol on the face of the button. Forever buttons have two arrows in the bottom right
corners, like this:

Once buttons don’t have the arrows, like this:

Once buttons do one action and then stop. When the action is finished, the button pops back
up.
Forever buttons do an action over and over again. When you want the action to stop, press
the button again. It will finish the current action, then pop back up.
Most models, including Wolf Sheep Predation, have a once button called “setup” and a
forever button called “go”. Many models also have a once button called “go once” or “step
once” which is like “go” except that it advances the model by one tick (time step) instead of
over and over. Using a once button like this lets you watch the progress of the model more
closely.
Stopping a forever button is the normal way to pause or stop a model. After pausing you can
make it resume by pressing the button again. (You can also stop a model with the “Halt” item
on the Tools menu, but you should only do this if the model is stuck for some reason. Using
“Halt” may interrupt the model in the middle of an action, and as the result the model could
get confused.)

If you like, experiment with the “setup” and “go” buttons in the Wolf Sheep
Predation model.
Do you ever get different results if you run the model several times with
the same settings?

Controlling speed: Speed Slider
The speed slider allows you to control the speed of a model, that is, the speed at which turtles
move, patches change color, and so on.

When you move the slider to the left the model slows down so there are longer pauses
between each tick (time step). That makes it easier to see what is happening. You might even
slow the model down so far as to see exactly what a single turtle is doing.
When you move the speed slider to the right the model speeds up. NetLogo will start skipping
frames, that is, it won’t update the view at the end of every tick, only some ticks. Updating
takes time, so fewer view updates means the model progresses faster.
Note that if you push the speed slider well to the right, the view may update so infrequently
that the model appears to have slowed down. It hasn’t, as you can see by watching the tick
counter race ahead. Only the frequency of view updates has lessened.

Adjusting Settings: Sliders and Switches
A model’s settings let you explore different scenarios or hypotheses. Altering the settings and
then running the model to see how it reacts can give you a deeper understanding of the
phenomena being modeled.
Switches and sliders give you access to a model’s settings. Here are the switches and sliders
in Wolf Sheep Predation:

Let’s experiment with their effect on the behavior of the model.

Open Wolf Sheep Predation if it’s not open already.
Press “setup” and “go” and let the model run for about 100 ticks. (The tick
count is shown above the view.)
Stop the model by pressing the “go” button.
What happened to the sheep over time?
Let’s take a look and see what would happen to the sheep if we change a setting.
Turn the “grass?” switch on.
Press “setup” and “go” and let the model run for a similar amount of time as
before.

What did the switch do? Was the outcome the same as your previous run?

Turning the “grass?” switch on affected the outcome of the model. With the switch off, the
amount of grass available always stayed the same. This is not a realistic look at the predatorprey relationship; so by setting and turning on a grass regrowth rate, we were able to model
all three factors: sheep, wolf and grass populations.
Another type of setting is called a slider.
Besides switches, a model may also have sliders. While a switch has only two values, on and
off, a slider has a whole range of numeric values. For example, the “initial-number-sheep”
slider has a minimum value of 0 and a maximum value of 250. The model could run with 0
sheep or it could run with 250 sheep, or anywhere in between. Try this out and see what
happens. As you move the marker from the minimum to the maximum value, the number on
the right side of the slider changes; this is the number the slider is currently set to.
Let’s investigate Wolf Sheep Predation’s sliders.
Change from the Interface to the Info tab to learn what each of this models’
sliders represents.

The Info tab offers guidance and insight into the model. Within this tab you will find an
explanation of the model, suggestions on things to try, and other information. You may want
to read the Info tab before running a model, or you might want to just start experimenting,
then look at the Info tab later.

What would happen to the sheep population if there were more sheep and
less wolves initially?
Turn the “grass?” switch off.
Set the “initial-number-sheep” slider to 100.
Set the “initial-number-wolves” slider to 20.
Press “setup” and then “go”.
Let the model run for about 100 ticks.
Try running the model several times with these settings.
What happened to the sheep population?
Did this outcome surprise you? What other sliders or switches can be
adjusted to help out the sheep population?
Set “initial-number-sheep” to 80 and “initial-number-wolves” to 50. (This is
close to how they were when you first opened the model.)
Set “sheep-reproduce” to 10.0%.
Press “setup” and then “go”.
Let the model run for about 100 time ticks.
What happened to the wolves in this run?

When you open a model, all the sliders and switches are on a default setting. If you open a
new model or exit the program, your changed settings will not be saved, unless you choose
to save them.
(Note: in addition to sliders and switches, some models have choosers and input boxes. The
Wolf Sheep Predation doesn’t have any of these, though.)

Gathering Information: Plots and Monitors
The view lets you see what’s going on in a model. NetLogo also provides has other ways of
giving you information about model run, such as plots and monitors.

Plots
The plot in Wolf Sheep Predation contains three lines: sheep, wolves, and grass / 4. (The
grass count is divided by four so it doesn’t make the plot too tall.) The lines show what’s
happening in the model over time. The plot legend shows what each line indicates. In this
case, it’s the population counts.
When a plot gets close to becoming filled up, the horizontal axis is compressed and all of the
data from before gets squeezed into a smaller space. In this way, more room is made for the
plot to grow.
If you want to save the data from a plot to view or analyze it in another application, use the
“Export Plot” item on the File menu. It saves the plot data in a format that can by read back by
spreadsheet and database programs such as Excel. You can also export a plot by rightclicking it and choosing “Export…” from the popup menu.

Monitors
Monitors are another means of displaying information from a model. Here are the monitors in
Wolf Sheep Predation:

The monitors show us the population of sheep and wolves, and the amount of grass.
(Remember, the amount of grass is divided by four to keep the plot from getting too tall.)
The numbers displayed in the monitors change as the model runs, whereas the plots show
you data from the whole course of the model run.

Controlling the View
In the Interface tab, you’ll see a toolbar of controls. Some of these control aspects of the view.
Let’s experiment with the effect of these controls.
Press “setup” and then “go” to start the model running.
As the model runs, move the speed slider to the left.
What happens?

This slider is helpful if a model is running too fast for you to see what’s going on in
detail.
Move the speed slider to the middle.
Try moving the speed slider to the right.
Now try checking and unchecking the “view updates” checkbox.
What happens?

Fast forwarding the model and turning off view updates are useful if you’re impatient and want
a model to run faster. Fast forwarding (moving the speed slider to the right) drops view
updates so the model can run fast, since updating the view takes time that could be used for
running the model itself.
When view updates are off completely, the model continues to run in the background, and
plots and monitors still update. But if you want to see what’s happening, you need to turn view
updates back on by rechecking the box. Many models run much faster when view updates
are off. For others, it makes little difference.
The size of the view is determined by five separate settings: min-pxcor, max-pxcor, minpycor, max-pycor, and patch size. Let’s take a look at what happens when we change the
size of the view in the “Wolf Sheep Predation” model.
There are more model settings than there’s room for in the toolbar. The “Settings…” button
lets you get to the rest of the settings.

Press the “Settings…” button in the toolbar.
A dialog will open containing all the settings for the view:

What are the current settings for min-pxcor, max-pxcor, min-pycor, maxpycor, and patch size?
Press “cancel” to make this window go away without changing the settings.
Place your mouse pointer next to, but still outside of, the view.
You will notice that the pointer turns into a crosshair.
Hold down the mouse button and drag the crosshair over the view.
The view is now selected, which you know because it is now surrounded by a gray
border.
Drag one of the square black “handles”. The handles are found on the edges
and at the corners of the view.
Unselect the view by clicking anywhere in the white background of the
Interface tab.
Press the “Settings…” button again and look at the settings.
What numbers changed?
What numbers didn’t change?

The NetLogo world is a two dimensional grid of “patches”. Patches are the individual squares

in the grid. In Wolf Sheep Predation, when the “grass?” switch is on the individual patches are
easily seen, because some are green, others brown.
Think of the patches as being like square tiles in a room with a tile floor. By default, exactly in
the middle of the room is a tile labeled (0,0); meaning that if the room was divided in half one
way and then the other way, these two dividing lines would intersect on this tile. We now have
a coordinate system that will help us locate objects within the room:

How many tiles away is the (0,0) tile from the right side of the room?
How many tiles away is the (0,0) tile from the left side of the room?

In NetLogo, the number of tiles from right to left is called world-width. And the number of tiles
from top to bottom is world-height. These numbers are defined by top, bottom, left and right
boundaries.

In these diagrams, max-pxcor is 3 , min-pxcor is -3, max-pycor is 2 and min-pycor is -2.

When you change the patch size, the number of patches (tiles) doesn’t change, the patches
only get larger or smaller in the view.
Let’s look at the effect of changing the minimum and maximum coordinates in the world.

Using the Settings dialog that is still open, change max-pxcor to 30 and maxpycor value to 10. Notice that min-pxcor and min-pycor change too. That’s
because by default the origin (0,0) is in the center of the world.
What happened to the shape of the view?
Press the “setup” button.
Now you can see the new patches you have created.
Edit the view by pressing the “Settings…” button again.
Change the patch size to 20 and press “OK”.
What happened to the size of the view? Did its shape change?

Editing the view also lets you change other settings. Feel free to experiment with these.
Once you are done exploring the Wolf Sheep Predation model, you may want to take some
time just to explore some of the other models available in the Models Library.

Models Library
The library contains four sections: Sample Models, Curricular Models, Code Examples, and
HubNet Activities.

Sample Models
The Sample Models section is organized by subject area and currently contains more than
200 models. We are continuously working on adding new models to it, so come visit this
section at a later date to view the new additions to the library.
Some of the folders in Sample Models have folders inside them labeled “(unverified)”. These
models are complete and functional, but are still in the process of being reviewed for content,
accuracy, and quality of code.

Curricular Models
These are models designed to be used in schools in the context of curricula developed by the
CCL at Northwestern University. Some of these are models are also listed under Sample
Models; others are unique to this section. See the Info tabs of the models for more
information on the curricula they go with.

Code Examples
These are simple demonstrations of particular features of NetLogo. They’ll be useful to you

later when you’re extending existing models or building new ones. For example, if you wanted
to add a histogram to your model, you’d look at “Histogram Example” to find out how.

HubNet Activities
This section contains participatory simulations for use with groups. For more information
about HubNet, see the HubNet Guide.

What’s Next?
If you want to learn how to explore models at a deeper level,Tutorial #2: Commands will
introduce you to the NetLogo modeling language.
In Tutorial #3: Procedures you can learn how to alter and extend existing models and build
new ones.

Tutorial #2: Commands
NetLogo 6.0.4 User Manual

So far you’ve successfully navigated your way through opening and running models, pressing
buttons, changing sliders and switches, and gathering information from a model using plots
and monitors.
In this section, the focus will start to shift from observing models to manipulating models. You
will start to see the inner workings of the models and be able to change how they look.

Sample Model: Traffic Basic

Open the Models Library (from the File menu).
Open Traffic Basic, found in the “Social Science” section.
Run the model for a while to get a feel for it.
Consult the Info tab for any questions you may have.

In this model, you will notice one red car in a stream of blue cars. The stream of cars are all
moving in the same direction. Every so often they “pile up” and stop moving. This is modeling
how traffic jams can form without a specific cause like an accident.
You may alter the settings and observe a few runs to get a fuller understanding of the model.

As you are using the Traffic Basic model, have you noticed any additions
you would like to make to the model?

Looking at the Traffic Basic model, you may notice the environment is fairly simple; a black
background with a white street and number of blue cars and one red car. Changes that could
be made to the model include: changing the color and shape of the cars, adding a house or
street light, creating a stop light, or even creating another lane of traffic. Some of these
suggested changes are visual, to enhance the look of the model, while others are more
behavioral. We will be focusing more on the simpler or cosmetic changes throughout most of
this tutorial. (Tutorial #3 will go into greater detail about behavioral changes, which require
changing the Code tab.)
To make these simple changes we will be using the Command Center.

Command Center
The Command Center is found in the Interface tab. It allows you to enter commands or
directions to a model. Commands are instructions you can give to NetLogo’s agents: turtles,
patches, links, and the observer.
In Traffic Basic:
Press the “setup” button.
Locate the Command Center.

Click the mouse in the white box at the bottom of the Command Center.
Type the text shown here:

Press the return key.
What happened to the View?
You may have noticed the background of the View has turned all yellow and the
street has disappeared.
Why didn’t the cars turn yellow too?
Looking back at the command that was written, we asked only the patches to
change their color. In this model, the cars are represented by a different kind of
agent, called “turtles”. Therefore, the cars did not receive these instructions and thus
did not change.
What happened in the Command Center?
You may have noticed that the command you just typed is now displayed in the
Command Center as shown below:

Type in the bottom of the Command Center the text shown below:

Was the result what you expected?
The view should have a yellow background with a line of brown cars in the middle:

The NetLogo world is a two dimensional world that is made up of turtles, patches, links, and
an observer. The patches are the ground over which the turtles move. Links are connections
between turtles. And the observer is a being that oversees everything that is going on. (For
more specifics, refer to the NetLogo Programming Guide.)
In the Command Center you can give commands to any of these types of agents. You choose
which type to talk to by using the popup menu located in the bottom left corner. You can also
use the tab key on your keyboard to cycle through the different types.

In the Command Center, click on the “observer>” in the bottom left corner:

Choose “turtles” from the popup menu.
Type set color pink and press return.
Press the tab key until you see “patches>” in the bottom left corner.
Type set pcolor white and press return.
What does the View look like now?
Do you notice any differences between these two commands and the
observer commands from earlier?

The observer oversees the world and therefore can give a command to the patches or turtles
using ask. Like in the first example (observer>ask patches [set pcolor yellow] ), the
observer has to ask the patches to set their pcolor to yellow. But when a command is directly
given to a group of agents like in the second example (patches> set pcolor white), you only
have to give the command itself.

Press “setup”.
What happened?

Why did the View revert back to the old version, with the black background and white road?
Upon pressing the “setup” button, the model will reconfigure itself back to the settings outlined
in the Code tab. The Command Center doesn’t permanently change the model. It allows you
to manipulate the NetLogo world directly to further answer those “What if” questions that pop

up as you are investigating the models. (The Code tab is explained in the next tutorial, and in
the Programming Guide.)
Now that we have familiarized ourselves with the Command Center, let’s look at some more
details about how colors work in NetLogo.

Working with colors
You may have noticed in the previous section that we used two different words for changing
color: color and pcolor.

What is the difference between color and pcolor?
Choose “turtles” from the popup menu in the Command Center (or use the tab
key).
Type set color blue and press return.
What happened to the cars?
Think about what you did to make the cars turn blue, and try to make the patches
turn red.
If you try to ask the patches to set color red, an error message occurs:

Type set pcolor red instead and press return.

We call color and pcolor “variables”. Some commands and variables are specific to turtles
and some are specific to patches. For example, the color variable is a turtle variable, while
the pcolor variable is a patch variable.
Go ahead and practice altering the colors of the turtles and patches using theset command
and these two variables.
To be able to make more changes to the colors of turtles and patches, or shall we say cars
and backgrounds, we need to gain a little insight into how NetLogo deals with colors.
In NetLogo, colors have a numeric value. In all of the exercises we have been using the name
of the color. This is because NetLogo recognizes 16 different color names. This does not
mean that NetLogo only recognizes 16 colors. There are many shades in between these
colors that can be used too. Here’s a chart that shows the whole NetLogo color space:

To get an intermediate shade, you refer to it by a number instead, or by adding or subtracting
a number from a name. For example, when you type set color red, this does the same thing
as if you had typed set color 15 . And you can get a lighter or darker version of the same
color by using a number that is a little larger or a little smaller, as follows.

Choose “patches” from the popup menu in the Command Center (or use the
tab key).
Type set pcolor red - 2 (The spacing around the “-” is important.)
By subtracting from red, you make it darker.
Type set pcolor red + 2
By adding to red, you make it lighter.

You can use this technique on any of the colors listed in the chart.

Agent Monitors and Agent Commanders
In the previous activity, we used theset command to change the colors of all the cars. But if
you recall, the original model contained one red car amongst a group of blue cars. Let’s look
at how to change only one car’s color.

Press “setup” to get the red car to reappear.
Right-click on the red car.

If there is another turtle close to the red turtle you’ll see more than one turtle
listed at the bottom of the menu. Move your mouse over the turtle selections,
notice when your mouse highlights a turtle menu item that turtle is highlighted
in the view. Select “inspect turtle” from the sub-menu for the red turtle.
A turtle monitor for that car will appear:

The mini-view at the top of the agent monitor will always stay centered on this agent. You can
zoom the view in and out using the slider below the view and you can watch this turtle in the
main view by pressing the “watch-me” button.
Taking a closer look at this turtle monitor, we can see all of the variables that belong to the
red car. A variable is a location that holds a value.
Let’s take a closer look at the turtle monitor:

What is this turtle’s who number?

What color is this turtle?
What shape is this turtle?

This turtle monitor is showing a turtle who that has a who number of 0, a color of 15 (red –
see chart above), and the shape of a car.
There are two other ways to open a turtle monitor besides right-clicking. One way is to
choose “Turtle Monitor” from the Tools menu, then type the who number of the turtle you
want to inspect into the “who” field and press return. The other way is to type inspect turtle
0 (or other who number) into the Command Center.
You close a turtle monitor by clicking the close box in the upper left hand corner (Mac) or
upper right hand corner (other operating systems).
Now that we know more about Agent Monitors, we have three ways to change an individual
turtle’s color.
One way is to use the box called an Agent Commander found at the bottom of an Agent
Monitor. You type commands here, just like in the Command Center, but the commands you
type here are only done by this particular turtle.

In the Agent Commander of the Turtle Monitor for turtle 0, typeset color
pink.
What happens in the View?
Did anything change in the Turtle Monitor?

A second way to change one turtle’s color is to go directly to the color variable in the Turtle
Monitor and change the value.

Select the text to the right of “color” in the Turtle Monitor.
Type in a new color such as green + 2 .
What happened?

The third way to change an individual turtle’s or patch’s color is to use the observer. Since,
the observer oversees the NetLogo world, it can give commands that affect individual turtles,
as well as groups of turtles.

In the Command Center, select “observer” from the popup menu (or use the
tab key).
Type ask turtle 0 [set color blue] and press return.
What happens?

Just as there are Turtle Monitors, there are also Patch Monitors, which work very
similarly.
Can you make a patch monitor and use it to change the color of a single
patch?

If you try to have the observer ask patch 0 [set pcolor blue] , you’ll get an error message:

To ask an individual turtle to do something, we use its who number. But patches don’t have
who numbers, therefore we need to refer to them some other way.
Remember, patches are arranged on a coordinate system. Two numbers are needed to plot a
point on a graph: an x-axis value and a y-axis value. Patch locations are designated in the
same way as plotting a point.

Open a patch monitor for any patch.

The monitor shows that for the patch in the picture, itspxcor variable is -19 and its
pycor variable is 0. If we go back to the analogy of the coordinate plane and wanted
to plot this point, the point would be found on the x axis left of the origin, where x=-

19 and y=0.
To tell this particular patch to change color:
In the bottom of the patch monitor, enterset pcolor blue and press return.
Typing a command in a turtle or patch monitor addresses only that turtle or patch.
You can also talk to a single patch from the Command Center:
In the Command Center, enter ask patch -19 0 [set pcolor green] and
press return.

What’s Next?
At this point, you may want to take some time to try out the techniques you’ve learned on
some of the other models in the Models Library.
In Tutorial #3: Procedures you can learn how to alter and extend existing models and build
your own models.

Tutorial #3: Procedures
NetLogo 6.0.4 User Manual

This tutorial leads you through the process of building a complete model, built up in stages, with every step explained along the way.

Agents and procedures
In Tutorial #2, you learned how to use the command center and agent monitors to inspect and modify agents and make them do things.
Now you’re ready to learn about the real heart of a NetLogo model: the Code tab.
You’ve seen that agents in NetLogo are divided into patches, turtles, links, and the observer. Patches are stationary and arranged in a
grid. Turtles move over that grid. Links connect two turtles. The observer oversees everything that’s going on and does whatever the
turtles, patches and links can’t do for themselves.
All four types of agents can run NetLogo commands. All four can also run “procedures”. A procedure combines a series of NetLogo
commands into a single new command that you define.
You will now learn to write procedures that make turtles move, eat, reproduce, and die. You will also learn how to make monitors,
sliders, and plots. The model we’ll build is a simple ecosystem model not unlike Wolf Sheep Predation from Tutorial #1.

Making the setup button
To start a new model, select “New” from the File menu. Then begin by creating a setup button:

Click the “Add” icon in the toolbar at the top of the Interface tab.
On the menu next to Add, select Button (if it isn’t already selected).
Click wherever you want the button to appear in the empty white area of the Interface tab.
A dialog box for editing the button opens. Type setup in the box labeled “Commands”.
Press the OK button when you’re done; the dialog box closes.

Now you have a setup button. Pressing the button runs a procedure called “setup”. A procedure is a sequence of NetLogo commands
that we assign a new name. We’ll define that procedure soon, but we haven’t yet. The button refers to a procedure that doesn’t exist, so
the button turns red:

If you want to see the actual error message, click the button.
Now we’ll create the “setup” procedure, so the error message will go away:

Switch to the Code tab.
Type the following:
to setup
clear-all
create-turtles 100 [ setxy random-xcor random-ycor ]
reset-ticks
end

When you’re done, the Code tab looks like this:

Note that some lines are indented. Most people find it helpful to indent their code. It isn’t mandatory, but it makes the code easier to read
and change.
Your procedure begins with to and ends with end. Every procedure begins and ends with these words.
Let’s look at what you typed in and see what each line of your procedure does:
to setup begins defining a procedure named “setup”.
clear-all resets the world to an initial, empty state. All

the patches turn black and any turtles you might have created disappear.
Basically, it wipes the slate clean for a new model run.
create-turtles 100 creates 100 turtles. They start out standing at the origin, that is, the center of patch 0,0.
After create-turtles we can put commands for the new turtles to run, enclosed by square brackets.
setxy random-xcor random-ycor is a command using “reporters”. A reporter, as opposed to a command, reports a result. First each
turtle runs the reporter random-xcor which will report a random number from the allowable range of turtle coordinates along the X
axis. Then each turtle runs the reporter random-ycor, same for the Y axis. Finally each turtle runs thesetxy command with those
two numbers as inputs. That makes the turtle move to the point with those coordinates.
reset-ticks starts the tick counter, now that setup is otherwise complete.
end completes the definition of the “setup” procedure.
When you’re done typing, switch to the Interface tab and press the setup button you made before. You will see the turtles scattered
around the world:

Press setup a couple more times, and see how the arrangement of turtles is different each time. Note that some turtles may be right on
top of each other.
Think a bit about what you needed to do to make this happen. You needed to make a button in the interface and make a procedure that
the button uses. The button only worked once you completed both of these separate steps. In the remainder of this tutorial, you will
often have to complete two or more similar steps to add another feature to the model. If something doesn’t appear to work after you
completed what you thought is the final step for that new feature, continue to read ahead to see if there is still more to do. After reading
ahead for a couple of paragraphs, you should then go back over the directions to see if there is any step you might have missed.

Switching to tick-based view updates
Now that we’re using the tick counter (with reset-ticks), we should tell NetLogo that it only needs to update the view once per tick,
instead of continuously updating it.

Find the view updates menu. It’s above the view and by default says “continuous”.
Choose “on ticks” instead.

This makes your model run faster and ensures a consistent appearance (since the updates will happen at consistent times). See the
Programming Guide for a fuller discussion of view updates.

Making the go button
Now make a button called “go”. Follow the same steps you used to make the setup button, except:

For Commands enter go instead of setup.
Check the “Forever” checkbox in the edit dialog.
Check the “Disable until ticks start” checkbox too.

The “Forever” checkbox makes the button stay down once pressed, so its commands run over and over again, not just once.
The “Disable until ticks start” prevents you from pressing go before setup.

Then add a go procedure to the Code tab:
to go
move-turtles
tick
end

tick

is a primitive that advances the tick counter by one tick.

But what is move-turtles ? Is it a primitive (in other words, built-in to NetLogo)? No, it’s another procedure that you’re about to add. So
far, you have introduced two procedures that you added yourself: setup and go.

Add the move-turtles procedure after the goprocedure:
to go

move-turtles
tick
end
to move-turtles
ask turtles [
right random 360
forward 1
]
end

Note there are no spaces around the hyphen inmove-turtles . In Tutorial #2 we used red - 2 , with spaces, in order to subtract two
numbers, but here we want move-turtles , without spaces. The “-” combines “move” and “turtles” into a single name.
Here is what each command in the move-turtles procedure does:
ask turtles [ ... ] says that each turtle should run the commands in the brackets.
right random 360 is another command that uses a reporter. First, each turtle picks a random whole number between 0
(random doesn’t include the number you give it as a possible result.) Then the turtle turns right this number of degrees.
forward 1 makes the turtle move forward one step.

and 359.

Why couldn’t we have just written all of these commands ingo instead of in a separate procedure? We could have, but during the
course of building your project, it’s likely that you’ll add many other parts. We’d like to keep go as simple as possible, so that it is easy to
understand. Eventually, it will include many other things you want to have happen as the model runs, such as calculating something or
plotting the results. Each of these things to do will have its own procedure and each procedure will have its own unique name.
The ‘go’ button you made in the Interface tab is a forever button, meaning that it will continually run its commands until you shut it off (by
clicking on it again). After you have pressed ‘setup’ once, to create the turtles, press the ‘go’ button. Watch what happens. Turn it off,
and you’ll see that all the turtles stop in their tracks.
Note that if a turtle moves off the edge of the world, it “wraps”, that is, it appears on the other side. (This is the default behavior. It can be
changed; see the Topology section of the Programming Guide for more information.)

Experimenting with commands
We suggest you start experimenting with other turtle commands.
Type commands into the Command Center (like turtles> set color red), or add commands to setup, go, or move-turtles .
Note that when you enter commands in the Command Center, you must chooseturtles>, patches>, links>, or observer> in the popup
menu on the left, depending on which agents are going to run the commands. It’s just like using ask turtles or ask patches, but saves
typing. You can also use the tab key to switch agent types, which you might find more convenient than using the menu.
You might try typing turtles> pen-down into the Command Center and then pressing the go button.
Also, inside the move-turtles procedure you can try changing right random 360 to right random 45 .
Play around. It’s easy and the results are immediate and visible – one of NetLogo’s many strengths.
When you feel you’ve done enough experimenting for now, you’re ready to continue improving the model you are building.

Patches and variables
Now we’ve got 100 turtles aimlessly moving around, completely unaware of anything else around them. Let’s make things a little more
interesting by giving these turtles a nice background against which to move.

Go back to the setup procedure. We can rewrite it as follows:
to setup
clear-all
setup-patches
setup-turtles
reset-ticks
end

The new definition of setup refers to two new procedures. To define setup-patches , add this:
to setup-patches
ask patches [ set pcolor green ]
end

The setup-patches procedure sets the color of every patch to green to start with. (A turtle’s color variable iscolor; a
patch’s is pcolor.)
The only part remaining in our new ‘setup’ that is still undefined issetup-turtles .
Add this procedure too:
to setup-turtles
create-turtles 100
ask turtles [ setxy random-xcor random-ycor ]

end

Did you notice that the new setup-turtles procedure has most of the same commands as the oldsetup procedure?
Switch back to the Interface tab.
Press the setup button.

Voila! A lush NetLogo landscape complete with turtles and green patches appears:

After seeing the new setup procedure work a few times, you may find it helpful to read through the procedure definitions again.

Turtle variables
So we have some turtles running around on a landscape, but they aren’t doing anything with it. Let’s add some interaction between the
turtles and the patches.
We’ll make the turtles eat “grass” (the green patches), reproduce, and die. The grass will gradually grow back after it is eaten.
We’ll need a way of controlling when a turtle reproduces and dies. We’ll determine that by keeping track of how much “energy” each
turtle has. To do that we need to add a new turtle variable.
You’ve already seen built-in turtle variables like color. To make a new turtle variable, we add aturtles-own declaration at the top of the
Code tab, before all the procedures. Call it energy:
turtles-own [energy]
to go
move-turtles
eat-grass
tick
end

Let’s use this newly defined variable (energy) to allow the turtles to eat.

Switch to the Code tab.
Rewrite the go procedure as follows:
to go
move-turtles
eat-grass
tick
end

Add a new eat-grass procedure:
to eat-grass
ask turtles [
if pcolor = green [
set pcolor black
set energy energy + 10
]
]
end

We are using the if command for the first time. Look at the code carefully. Each turtle, when it runs these commands, compares the
value of the patch color it is on (pcolor) to the value for green. (A turtle has direct access to the variables of the patch it is standing on.) If
the patch color is green, the comparison reports true, and only then will the turtle run the commands inside the brackets (otherwise it
skips them). The commands make the turtle change the patch color to black and increase its own energy by 10. The patch turns black
to signify that the grass at that spot has been eaten. And the turtle is given more energy, from having just eaten.
Next, let’s make the movement of turtles use up some of the turtle’s energy.

Rewrite move-turtles as follows:
to move-turtles
ask turtles [
right random 360
forward 1
set energy energy - 1
]
end

As each turtle wanders, it will lose one unit of energy at each step.

Switch to the Interface tab now and press the setup button and the go button.
You’ll see the patches turn black as turtles travel over them.

Monitors
Next you will create two monitors in the Interface tab with the toolbar. (You make them just like buttons and sliders, using the Add icon
on the toolbar.) Let’s make the first monitor now.

Create a monitor by clicking the Add icon on the toolbar, selecting Monitor next to it, and clicking on an open spot in
the Interface.
A dialog box will appear.
In the dialog type: count turtles (see image below).
Press the OK button to close the dialog.

turtles

is an “agentset”, the set of all turtles.count tells us how many agents are in that set.

Let’s make the second monitor now:

Create a monitor by clicking the Add icon on the toolbar, selecting Monitor next to it, and clicking on an open spot in
the Interface.
A dialog box will appear.
In the Reporter section of the dialog box type: count patches with [pcolor = green] (see image below).
In the Display name section of the dialog box type:green patches
Press the OK button to close the dialog box.

Here we’re using count again to see how many agents are in an agentset.patches is the set of all the patches, but we don’t just want to
know how many patches there are total, we want to know how many of them are green. That’s what with does; it makes a smaller
agentset of just those agents for whom the condition in the brackets is true. The condition is pcolor = green , so that gives us just the
green patches.
Now we have two monitors that will report how many turtles and green patches we have, to help us track what’s going on in our model.
As the model runs, the numbers in the monitors will automatically change.

Use the setup and go buttons and watch the numbers in the monitors change.

Switches and labels
The turtles aren’t just turning the patches black. They’re also gaining and losing energy. As the model runs, try using a turtle monitor to
watch one turtle’s energy go up and down.
It would be nicer if we could see every turtle’s energy all the time. We will now do exactly that, and add a switch so we can turn the extra
visual information on and off.

Click on the Add icon on the toolbar (in the Interface tab).
Select Switch from the menu next to Add.
Click on an open spot in the interface.
A dialog will appear.

Into the Global variable field, type show-energy? Don’t forget to include the question mark in the name. (See image
below.)

Now go back to the ‘go’ procedure using the Code tab with the Toolbar.
Rewrite the eat-grass procedure as follows:
to eat-grass
ask turtles [
if pcolor = green [
set pcolor black
set energy energy + 10
]
ifelse show-energy?
[ set label energy ]
[ set label "" ]
]
end

The eat-grass procedure introduces the ifelse command. Look at the code carefully. Each turtle, when it runs these new commands,
checks the value of show-energy? (determined by the switch). If the switch is on, comparison is true and the turtle will run the commands
inside the first set of brackets. In this case, it assigns the value for the energy to the label of the turtle. If the comparison is false (the
switch is off) then the turtle runs the commands inside the second set of brackets. In this case, it removes the text labels (by setting the
label of the turtle to be nothing).
(In NetLogo, a piece of text is called a “string”, short for string of characters. A string is a sequence of letters or other characters, written
between double quotes. Here we have two double quotes right next to each other, with nothing in between them. That’s an empty string.
If a turtle’s label is an empty string, no text is attached to the turtle.)

Test this in the Interface tab, by running the model (using the setup and go buttons) switching theshow-energy?
switch back and forth.

When the switch is on, you’ll see the energy of each turtle go up each time it eats grass. You’ll also see its energy going down whenever
it moves.

More procedures
Now our turtles are eating. Let’s make them reproduce and die, too. And let’s make the grass grow back. We’ll add all three of these of
these behaviors now, by making three separate procedures, one for each behavior.

Go to the Code tab.
Rewrite the go procedure as follows:
to go
move-turtles
eat-grass
reproduce
check-death
regrow-grass
tick
end

Add the procedures for reproduce, check-death, and regrow-grass as shown below:
to reproduce
ask turtles [
if energy > 50 [
set energy energy - 50
hatch 1 [ set energy 50 ]
]
]
end
to check-death
ask turtles [
if energy <= 0 [ die ]
]
end
to regrow-grass
ask patches [
if random 100 < 3 [ set pcolor green ]
]
end

Each of these procedures uses the if command. Each turtle, when it runs check-death it will check to see if its energy is less or equal to
0. If this is true, then the turtle is told to die (die is a NetLogo primitive).
When each turtle runs reproduce, it checks the value of the turtle’senergy variable. If it is greater than 50, then the turtle runs the
commands inside the first set of brackets. In this case, it decreases the turtle’s energy by 50, then ‘hatches’ a new turtle with an energy
of 50. The hatch command is a NetLogo primitive which looks like this:hatch number [ commands ]. This turtle creates number new
turtles, each identical to its parent, and asks the new turtle(s) that have been hatched to run commands. You can use the commands to
give the new turtles different colors, headings, or whatever. In our case we run one command. We set the energy for the newly hatched
turtle to be 50.
When each patch runs regrow-grass it will check to see if a random integer from 0 to 99 is less than 3. If so, the patch color is set to
green. This will happen 3% of the time (on average) for each patch, since there are three numbers (0, 1, and 2) out of 100 possible that
are less than 3.

Switch to the Interface tab now and press the setup and go buttons.

You should see some interesting behavior in your model now. Some turtles die off, some new turtles are created (hatched), and some
grass grows back. This is exactly what we set out to do.
If you continue to watch your monitors in your model, you will see that thecount turtles and green patches monitors both fluctuate. Is
this pattern of fluctuation predictable? Is there a relationship between the variables?
It’d be nice if we had a easier way to track the changes in the model behavior over time. NetLogo allows us to plot data as we go along.
That will be our next step.

Plotting
To make plotting work, we’ll need to create a plot in the Interface tab and put some commands inside it.
The commands we put in the plots will run automatically when oursetup procedure calls reset-ticks and when our go procedure calls
tick.

Create a plot by clicking the Add icon on the toolbar, selecting Plot next to it, and clicking on an open spot in the
Interface.
Set its Name to “Totals” (see image below)
Set the X axis label to “time”
Set the Y axis label to “totals”
Change the name of the “default” pen to “turtles”.
Enter plot count turtles under Pen Update Commands.
Press the “Add Pen” button.
Change the name of the new pen to “grass”.
Enter plot count patches with [pcolor = green] under Pen Update Commands.

When you’re done, the dialog should look like this:

Press OK in the Plot dialog to finish editing.

Note that when you create the plot you can also set the minimum and maximum values on the X and Y axes. You’ll want to leave the
“Auto Scale” checkbox checked, so that if anything you plot exceeds the minimum and maximum values for the axes, the axes will
automatically grow so you can see all the data.
Note that we used the plot command to add the next point to a plot. This command moves the current plot pen to the point that has an
X coordinate equal to 1 greater than the previously plotted X coordinate and a Y coordinate equal to the value given in the plot
command (in the first case, the number of turtles, and in the second case, the number of green patches). As the pens move they each
draw a line.

Setup and run the model again.

You can now watch the plot being drawn as the model is running. Your plot should have the general shape of the one below, though
your plot might not look exactly the same.
Remember that we left “Auto Scale?” on. This allows the plot to readjust itself when it runs out of room.

If you forget which pen is which, you can edit the plot and check the “Show legend?” checkbox.
You might try running the model several times to see what aspects of the plot are the same and which are different from run to run.

Tick counter
To make comparisons between plots from one model run and another, it is often useful to do the comparison for the same length of
model run. Learning how to stop or start an action at a specific time can help make this happen by stopping the model at the same point
each model run. Keeping track of how many times the go procedure is run is a useful way to cue these actions. That’s what the tick
counter does.
You’re already using the tick counter in your model, with thereset-ticks and tick commands, which also trigger plotting.
You can also use the tick counter for other things, such as to set a limit on the total length of a run.

Change the go procedure:
to go
if ticks >= 500 [ stop ]
move-turtles
eat-grass
check-death
reproduce
regrow-grass
tick
end

Now setup and run the model.

The graph and model won’t keep running forever. They should stop automatically when the tick counter in the Interface tab’s toolbar
reaches 500.
The tick command advances the tick counter by 1.ticks is a reporter which reports the current value of the tick counter.reset-ticks, in
your setup procedure, takes care of restarting the tick counter at 0 when a new run is set up and ready to begin.

Some more details
First, instead of always using 100 turtles, you can have a varying number of turtles.

Create a slider named “number”: click the Add icon on the toolbar, select Slider next to it, and click on an open spot
in the interface.
Try changing the minimum and maximum values in the slider.
Then inside of setup-turtles , instead of create-turtles 100 you can type:
to setup-turtles
create-turtles number [ setxy random-xcor random-ycor ]
end

Test this change and compare how having more or fewer turtles initially affect the plots over time.
Second, wouldn’t it be nice to adjust the energy the turtles gain and lose as they eat grass and reproduce?

Make a slider called energy-from-grass .
Make another slider called birth-energy .
Then, inside of eat-grass, make this change:
to eat-grass
ask turtles [
if pcolor = green [
set pcolor black
set energy (energy + energy-from-grass)
]
ifelse show-energy?
[ set label energy ]
[ set label "" ]
]
end

And, inside of reproduce, make this change:
to reproduce
ask turtles [
if energy > birth-energy [
set energy energy - birth-energy
hatch 1 [ set energy birth-energy ]
]
]
end

Finally, what other slider could you add to vary how often grass grows back? Are there rules you can add to the movement of the turtles
or to the newly hatched turtles that happen only at certain times? Try writing them.

What’s next?
So now you have a simple model of an ecosystem. Patches grow grass. Turtles wander, eat the grass, reproduce, and die.
You have created an interface containing buttons, sliders, switches, monitors, and a plot. You’ve even written a series of procedures to
give the turtles something to do.

That’s where this tutorial leaves off.
If you’d like to look at some more documentation about NetLogo, theInterface Guide section of the manual walks you through every
element of the NetLogo interface in order and explains its function. For a detailed description and specifics about writing procedures,
refer to the Programming Guide. All of the primitives are listed and described in theNetLogo Dictionary.
Also, you can continue experimenting with and expanding this model if you’d like, experimenting with different variables and behaviors
for the agents.
Alternatively, you may want to revisit the first model in the tutorial, Wolf Sheep Predation. This is the model you used inTutorial #1. In
the Wolf Sheep Predation model, you saw sheep move around, consume resources that are replenished occasionally (grass),
reproduce under certain conditions, and die if they ran out of resources. But that model had another type of creature moving around –
wolves. The addition of wolves requires some additional procedures and some new primitives. Wolves and sheep are two different
“breeds” of turtle. To see how to use breeds, study Wolf Sheep Predation.
Alternatively, you can look at other models (including the many models in the Code Examples section of the Models Library) or even go
ahead and build your own model. You don’t even have to model anything. It can be interesting just to watch patches and turtles forming
patterns, to try to create a game to play, or whatever.
Hopefully you have learned some things, both in terms of the NetLogo language and about how to go about building a model. The entire
set of procedures that was created above is shown below.

Appendix: Complete code
The complete model is also available in NetLogo’s Models Library, in the Code Examples section. It’s called “Tutorial 3”.
Notice that this listing is full of “comments”, which begin with semicolons. Comments let you mix an explanation the code right in with the
code itself. You might use comments to help others understand your model, or you might use them as notes to yourself.
In the Code tab, comments are gray, so your eyes can pick them out easily.
turtles-own [energy] ;; for keeping track of when the turtle is ready
;; to reproduce and when it will die
to setup
clear-all
setup-patches
setup-turtles
reset-ticks
end
to setup-patches
ask patches [ set pcolor green ]
end
to setup-turtles
create-turtles number
;; uses the value of the number slider to create turtles
ask turtles [ setxy random-xcor random-ycor ]
end
to go
if ticks >= 500 [ stop ] ;; stop after 500 ticks
move-turtles
eat-grass
check-death
reproduce
regrow-grass
tick
;; increase the tick counter by 1 each time through
end
to move-turtles
ask turtles [
right random 360
forward 1
set energy energy - 1
]
end

;; when the turtle moves it looses one unit of energy

to eat-grass
ask turtles [
if pcolor = green [
set pcolor black
;; the value of energy-from-grass slider is added to energy
set energy energy + energy-from-grass
]
ifelse show-energy?
[ set label energy ] ;; the label is set to be the value of the energy
[ set label "" ]
;; the label is set to an empty text value
]
end
to reproduce
ask turtles [
if energy > birth-energy [
set energy energy - birth-energy ;; take away birth-energy to give birth
hatch 1 [ set energy birth-energy ] ;; give this birth-energy to the offspring
]
]
end
to check-death
ask turtles [
if energy <= 0 [ die ] ;; removes the turtle if it has no energy left
]
end
to regrow-grass
ask patches [ ;; 3 out of 100 times, the patch color is set to green
if random 100 < 3 [ set pcolor green ]
]
end

Interface Guide
NetLogo 6.0.4 User Manual

This section of the manual explains the function of each element in NetLogo’s user interface.
In NetLogo, you have the choice of viewing models found in the Models Library, adding to
existing models, or creating your own models. The NetLogo interface was designed to meet all
these needs.
The interface can be divided into two main parts: NetLogo menus, and the main NetLogo
window. The main window is divided into tabs.

Menus
On a Mac, if you are running the NetLogo application, the menu bar is located at the top of the
screen. On other platforms, the menu bar is found at the top of the NetLogo window.

The functions available from the menus in the menubar are listed in the following chart.

Chart: NetLogo menus

File
New

Starts a new model.

Open…

Opens any NetLogo model on your computer.

Models Library A collection of demonstration models.
Recent Files

Re-opens any previously model opened with "File -> Open"

Save

Save the current model, or the currently selected source file.

Save As…

Save the current model, or the currently selected source file, using a
different name.

Save All

Save the current model and all open source files. This option is only
available when one or more source files are open.

Upload to
Modeling
Commons

Uploads the model to Modeling Commons. See Modeling Commons

Save As
NetLogo
Web…

Saves a web page, in HTML format, containing NetLogo web running
your model.

Saves all variables, the current state of all turtles and patches, the
Export World… drawing , the plots, the output area and the random state information
to a file.
Export Plot…

Saves the data in a plot to a file.

Export All
Plots…

Saves the data in all the plots to a file.

Export View…

Save a picture of the current view (2D or 3D) to a file (in PNG
format).

Export
Interface…

Save a picture of the current Interface tab. ( in PNG format )

Export
Output…

Save the contents of the output area or the output section of the
command center to a file.

Export Code… Save the model's code to an HTML file, preserving colors.
Import World… Load a file that was saved by Export World.
Import Patch
Colors…

Load an image into the patches; see the import-pcolors command.

Import Patch
Colors RGB…

Load an image into the patches using RGB colors; see the importpcolors-rgb command.

Import
Drawing…

Load an image into the drawing, see the import-drawing command.

Import HubNet
Client
Load the interface from another model into the HubNet Client Editor.
Interface…
Print…

Sends the contents of the currently showing tab to your printer.

Quit

Exits NetLogo. On a Mac, this item is on the NetLogo menu instead.

Undo

Undo last text editing action you performed.

Redo

Redo last undo action you performed.

Cut

Cuts out or removes the selected text and temporarily saves it to the
clipboard.

Copy

Copies the selected text.

Paste

Places the clipboard text where cursor is currently located.

Edit

Delete

Deletes selected text.

Select All

Select all the text in the active window.

Find…

Finds a word or sequence of characters within the Info or Code tabs.

Find Next

Find the next occurrence of the word or sequence you last used Find
with.

Comment /
Uncomment

Used in the Code tab to add or remove semicolons from code
(semicolons are used in NetLogo code to indicate comments).

Shift Left / Shift
Used in the Code tab to change the indentation level of code.
Right
Format

Used in the Code tab to correct the indentation of the currently
selected code.

Snap to Grid

Available only in the Interface Tab. When enabled new widgets stay
on a 5 pixel grid so it is easier to line them up. (Note: this feature is
disabled when zoomed in or out.)

Convert from
5.3.1 to 6.0

Available only in an ".nls" code tab. Treats the code in this tab as
though it were written in 5.3.1 and converts it to run in NetLogo 6.
Note that this will not take into account code defined in the main
code tab. "Undo" doesn't take this operation into account, so you
won't want to save unless you're satisfied with the changes.

Tools
Opens the preferences dialog, where you can customize various
Preferences… NetLogo settings. On a Mac, this item is on the NetLogo menu
instead.

Halt

Stops all running code, including buttons and the command center.
(Warning: since the code is interrupted in the middle of whatever it
was doing, you may get unexpected results if you try to continue
running the model without first pressing "setup" to start the model
run over.)

Globals
Monitor

Displays the values of all global variables.

Turtle Monitor

Displays the values of all of the variables in a particular turtle. You
can can also edit the values of the turtle's variables and issue
commands to the turtle. (You can also open a turtle monitor via the
View; see the View section below.)

Patch Monitor

Displays the values of all of the variables in a particular patch. You
can can also edit the values of the patch's variables and issue
commands to the patch. (You can also open a patch monitor via the
View; see the View section below.)

Link Monitor

Displays the values of all of the variables in a particular link. You can
can also edit the values of the link's variables and issue commands
to the link. (You can also open a link monitor via the View; see the
View section below.)

Close All
Closes all open agent monitor windows.
Agent Monitors
Close Monitors
for Dead
Closes all open agent monitor windows targeting dead agents.
Agents
Hide/Show
Command
Center

Makes the command center visible or invisible. (Note that the
command center can also be shown or hidden, or resized, with the
mouse.) This option is only available when the Interface Tab is
active

3D View

Opens the 3D view. See the Views section of the Interface Tab
Guide for more information.

Color
Swatches

Opens the Color Swatches. See the Color Section of the
Programming Guide for details.

Turtle Shapes
Editor

Draw turtle shapes. See the Shapes Editor Guide for more
information.

Link Shapes
Editor

Draw link shapes. See the Shapes Editor Guide for more information.

BehaviorSpace

Runs the model over and over with different settings. See the
BehaviorSpace Guide for more information.

System
Dynamics
Modeler

Opens the System Dynamics Modeler. See the System Dynamics
Modeler Guide for more details.

Preview
Commands
Editor

Allows for easy editing of the commands sequence used to create
preview images for models. Gives a way to specify what code will be
used (or specify that the image is manually made) and preview the
resulting image.

HubNet Client
Editor

Opens the HubNet Client Editor. See the HubNet Authoring Guide
for more details.

HubNet
Disabled if no HubNet activity is open. See the HubNet Guide for
Control Center more information.
Zoom
Larger

Increase the overall screen size of the model. Useful on large
monitors or when using a projector in front of a group.

Normal Size

Reset the screen size of the model to the normal size.

Smaller

Decrease the overall screen size of the model.
This menu offers keyboard shortcuts for each of the tabs. On a Mac,
it's Command 1 through Command 3. On Windows, it's Control 1
through Control 3. Additional numbers are used for tabs containing
".nls" files.

Tabs

Help
Look Up In
Dictionary

Opens a browser with the dictionary entry for the selected command
or reporter. (You may also use the F1 key for this.)

NetLogo User
Manual

Opens this manual in a web browser.

NetLogo
Dictionary

Opens the NetLogo Dictionary in a web browser.

NetLogo Users
Opens the NetLogo Users Group site in a web browser.
Group
Introduction to
Agent-Based
Modeling

Opens the MIT Press page for "Introduction to Agent-Based
Modeling" (by Uri Wilensky and William Rand) in a web browser.

Donate

Opens the NetLogo donation page in a web browser.

About NetLogo Information on the current NetLogo version you are running. On a
6.0.4…
Mac, this menu item is on the NetLogo menu instead.

Tabs
At the top of NetLogo’s main window are three tabs labeled “Interface”, “Info” and “Code”. Only
one tab at a time can be visible, but you can switch between them by clicking on the tabs at the
top of the window.

Right below the row of tabs is a toolbar containing a row of controls. The controls available vary
from tab to tab.

International Usage
Character sets

NetLogo always saves and loads models in the UTF-8 character encoding, which includes a
wide range of international characters.
If you are in a locale other than U.S. English, let us know if you have any trouble using your local
character set.
The Transition Guide has advice on converting models containing international characters from
earlier NetLogo versions.

Languages
Most of NetLogo’s GUI, and some of its error messages, are now “internationalized”. This
means that it is now possible to display NetLogo in different languages.
We say “possible” here because the current release of NetLogo only supports English, Spanish,
Chinese, Russian, and Japanese.
The work on internationalization is not complete. We are asking for help from the user
community in helping us localize items such as the menus and error messages.

Default language
By default, NetLogo uses the same language your operating system is set to, if available. (If
unavailable, you get English.)
You can record a preference for a different language by changing the “User Interface Language”
option in the preferences dialog. Once a new language is chosen you will have to restart
NetLogo.

Support for translators
We hope NetLogo will become available in many different languages. If you would like to
translate NetLogo to your language, see this wiki page for instructions.

Interface Tab Guide
NetLogo 6.0.4 User Manual

The Interface tab is where you watch your model run. It also has tools you can use to inspect and alter
what’s going on inside the model.
When you first open NetLogo, the Interface tab is empty except for the view, where the turtles and
patches appear, and the Command Center, which allows you to issue NetLogo commands.

Working with interface elements
The toolbar on the Interface tab contains buttons that let you edit, delete, and create items in the
Interface tab and a menu that lets you select different interface items (such as buttons and sliders).

The buttons in the toolbar are described below.
Adding: To add an interface element, select the element from the drop down menu. Note that the Add
button stays down. Then click on the white area below the toolbar. (If the menu is already showing the
right type, you can just press the Add button instead of using the menu again.)
Selecting: To select an interface element, drag a rectangle around it with your mouse. A gray border
with black handles will appear around the element to show it is selected.
Selecting multiple items: You can select multiple interface elements at the same time by including
them in the rectangle you drag. If multiple elements are selected, one of them is the “key” item, which
means that if you use the “Edit” or “Delete” buttons on the Interface Toolbar, only the key item is
affected. The key item’s border is darker gray.
Unselecting: To unselect all interface elements, click the mouse on the white background of the
Interface tab. To unselect an individual element, right-click the element and choose “Unselect” from the
popup menu.
Editing: To change the characteristics of an interface element, select the element, then press the “Edit”
button on the Interface toolbar. You may also double click the element once it is selected. A third way to
edit an element is to right-click it and choose “Edit” from the popup menu. If you use this last method, it is
not necessary to select the element first.
Moving: Select the interface element, then drag it with your mouse to its new location. If you hold down
the shift key while dragging, the element will move only straight up and down or straight left and right.
Resizing: Select the interface element, then drag the black “handles” in the selection border.
Deleting: Select the element or elements you want to delete, then press the “Delete” button on the
Interface toolbar. You may also delete an element by right-clicking it and choosing “Delete” from the
popup menu. If you use this latter method, it is not necessary to select the element first.
To learn more about the different kinds of interface elements, refer to the chart below.

Chart: Interface Toolbar

Icon & Name

Description
A button is either once or forever. When you click on a once button, it executes its
instructions once. The forever button executes the instructions over and over, until
you click on the button again to stop the action. If you have assigned an action key
to the button, pressing the corresponding keyboard key will act just like a button
press when the button is in focus. Buttons with action keys have a letter in the
upper right corner of the button to show what the action key is. If the keyboard
focus is in another interface element such as the Command Center, pressing the
action key won't trigger the button. The letter in the upper right hand corner of the
button will be dimmed in this situation. To enable action keys, click in the white
background of the Interface tab.
Sliders are global variables, which are accessible by all agents. They are used in
models as a quick way to change a variable without having to recode the
procedure every time. Instead, the user moves the slider to a value and observes
what happens in the model.
Switches are a visual representation for a true/false global variable. You may set
the variable to either on (true) or off (false) by flipping the switch.
Choosers let you choose a value for a global variable from a list of choices,
presented in a drop down menu. The choices may be strings, numbers, booleans,
or lists.
Input Boxes are global variables that contain strings or numbers. The model author
chooses what types of values you can enter. Input boxes can be set to check the
syntax of a string for commands or reporters. Number input boxes read any type of
constant number reporter which allows a more open way to express numbers than
a slider. Color input boxes offer a NetLogo color chooser.
Monitors display the value of any reporter. The reporter could be a variable, a
complex reporter, or a call to a reporter procedure. Monitors automatically update
several times per second.
Plots show data the model is generating.
The output area is a scrolling area of text which can be used to create a log of
activity in the model. A model may only have one output area.
Notes lets you add informative text labels to the Interface tab. The contents of notes
do not change as the model runs.

The other controls in the Interface toolbar allow you to control the view updates and various other model
properties.

The slider lets you control how fast the model runs. Slower can be valuable since some models run
so fast they’re hard to follow. You can also fast-forward the model by moving the slider to the right,
reducing the frequency of view updates.
The view updates checkbox controls whether view updates happen at all.
The update mode menu allows you to switch between continuous and tick-based updates.
The “Settings…” button allows you to change model settings.
“Continuous” updates means that NetLogo updates (that is, redraws) the view many times a second,
regardless of what is going on in the model. “Tick-based” updates means that the view only updates
when the tick counter advances. (For a fuller discussion of view updates, see the Programming Guide.)

The 2D and 3D views

The large black square in the Interface tab is the 2D view. It’s a visual representation of the NetLogo
world of turtles and patches. Initially it’s all black because the patches are black and there are no turtles
yet. You can open the 3D View, an alternate visual representation of the world, by right clicking (ctrlclicking on Mac) on the View and choosing “Switch to 3D View” (this option is also available in the
“Tools” menu).

There are a number of settings for the View (accessible by editing the View, or by pressing the
“Settings…” button in the Interface Toolbar):

Notice that the settings are broken up into three groups. There are world, view, and ticks counter
settings. World settings affect the properties of the world that the turtles live in (changing them may
require resetting the world). View and tick counter settings only affect the appearance, changing them
will not affect the outcome of the model.
The world settings allow you to define the boundaries and topology of the world. At the top of the left
side of the world panel you can choose a location for the origin of the world either “Center”, “Corner”,
“Edge”, or “Custom”. By default the world has a center configuration where (0,0) is at the center of the
world and you define the number of patches from the center to the right and left boundaries and the
number of patches from the center to the top and bottom boundaries. For example: if you set Max-Pxcor

= 10, then Min-Pxcor will automatically be set to -10, thus there are 10 patches to the left of the origin
and 10 patches to the right of patch 0 0, for a total of 21 patches in each row.
A Corner configuration allows you to define the location of the origin as one of the corners of the world,
upper left, upper right, lower left, or lower right. Then you define the far boundary in the x and y
directions. For example if you choose to put the origin in the lower left corner of the world you define the
right and top (positive) boundaries.
Edge mode allows you to place the origin along one of the edges (x or y) then define the far boundary in
that direction and both boundaries in the other. For example if you select edge mode along the bottom of
the world, you must also define the top boundary, as well as the left and the right.
Finally, Custom mode allows you to place the origin at any location in the world, though patch 0 0 must
still exist in the world.
As you change the settings you will notice that the changes you make are reflected in the preview on the
right side of the panel which shows the origin and the boundaries. The width and height of the world are
displayed below the preview.
Also below the preview there are two checkboxes, the world wrap settings. These allow you to control
the topology of the world. Notice when you click the check boxes the preview indicates which directions
allow wrapping, and the name of the topology is displayed next to the world dimensions. See the
Topology section of the Programming Guide for more information.
The view settings allow you to customize the look of the view without changing the world. Changing view
settings will never force a world reset. To change the size of the 2D View adjust the “Patch Size” setting,
measured in pixels. This does not change the number of patches, only how large the patches appear in
the 2D View. (Note that the patch size does not affect the 3D View, as you can simply make the 3D
View larger by making the window larger.)
The font size setting lets you control the size of turtle, patch, and link labels.
The frame rate controls how often the view gets updated. This can have a dramatic effect on the default
speed at which a model runs. For more details, see the view updates section of the Programming Guide.
The “Smooth edges” checkbox controls the use of anti-aliasing in the 3D view only and only appears
when editing from the 3D view. Unchecking it makes lines appear more jagged but may speed up
rendering.
Tick counter settings control the appearance of the tick counter which is visible (or not) in the view
control strip.
Turtle, patch and link monitors are easily available through the View, just right-click on the turtle or patch
you want to inspect, and choose “inspect turtle …” or “inspect patch …” from the popup menu. You can
also watch, follow or ride a turtle by selecting the appropriate item in the turtle sub-menu. (Turtle, patch
and link monitors can also be opened from the Tools menu or by using the inspect command.)
Some NetLogo models let you interact with the turtles and patches with your mouse by clicking and
dragging in the View.

Manipulating the 3D View
At the bottom of the window there are buttons to move the observer, or change the perspective from
which you are looking at the world.

A blue cross appears at the current focus point as you adjust these settings. The little blue triangle will
always point along the y-axis in the positive direction, so you can orient yourself in case you get lost.

To look at the world from a different angle, press the “rotate” button, then click and drag the mouse. The
observer will continue to face the same point as before (where the blue cross is) but its position in the
relation to the xy-plane will change.
To move closer or farther away from the world or the agent you are watching, following or riding, press
the “zoom” button and drag up and down. Note when you are in follow or ride mode zooming will switch
you between ride and follow, since ride is just a special case of follow where the distance at which you
are following is 0.
To change the position of the observer without changing the direction it is facing select the “move”
button and drag the mouse inside the 3D View while holding down the mouse button.
To allow the mouse position and state to be passed to the model select the “interact” button and it will
function just as the mouse does in the 2D view.
To return the observer and focus point to their default positions press the “Reset Perspective” button (or
use the reset-perspective command).

Fullscreen Mode
To enter fullscreen mode, press the “Full Screen” button, to exit fullscreen mode, press the Esc key.
Note: Fullscreen mode doesn’t work on every computer. It depends on your graphics card. See the
System Requirements for details.

3D Shapes
Some shapes are automatically mapped to true 3D counterparts in the 3D view. For example, the 2D
circle shape becomes a sphere in the 3D view.
Shape name

3D shape

default

3D turtle shape

circle

sphere

dot

small sphere

square

cube

triangle

cone

line

3D line

cylinder

3D cylinder

line-half

3D line-half

car

3D car

All other shapes are based on their 2D forms. If a shape is a rotatable shape, it is assumed to be a top
view and it is extruded as if through a cookie cutter and oriented parallel to the xy-plane, as in Ants.

Or, if a shape is non-rotatable, it is assumed to be a side view, and it is drawn always facing the
observer, as in Wolf Sheep Predation.

Command Center
The Command Center allows you to issue commands directly, without adding them to the model’s
procedures. This is useful for inspecting and manipulating agents on the fly.
(Tutorial #2: Commands is an introduction to using commands in the Command Center.)
Let’s take a look at the design of the Command Center.

The smaller box, below the large box, is where you type a command. After typing it press the Return or
Enter key to run it.
To the left of where you type is a popup menu that initially says “observer>”. You can choose either
observer, turtles, or patches, to specify which agents run the command you type.
Tip: a quicker way to change agent types is to use the Tab key.

Reporters
If you enter a reporter into the Command Center, theshow command will be inserted before it
automatically.

Accessing previous commands
After you type a command, it appears in the large scrolling box above the command line. You can use
Copy on the Edit menu in this area to copy commands and then paste them elsewhere, such as the
Code tab.
You can also access previous commands using the history popup, which is the small downward pointing
triangle to the right of where you type commands. Click on the triangle and a menu of previously typed
commands appears, so you can pick one to use again.
Tip: a quicker way to access previous commands is with the up and down arrow keys on your keyboard.

Clearing
To clear the large scrolling area containing previous commands and output, click “clear” in the top right
corner.
To clear the history popup menu, choose “Clear History” on that menu.

Arranging
You can hide and show the command center using the Hide Command Center and Show Command
Center items on the Tools menu.
To resize the command center, drag the bar that separates it from the model interface. Or, click one of
the little arrows on the right end of the bar to make the command center either very big or hidden
altogether.
To switch between a vertical command center and a horizontal one, click the button with the doubleheaded arrow, just to the left of “Clear”.

Plots
When the mouse pointer is over the white area of a plot, the x and y coordinates of the mouse location
appear. (Note that the mouse location might not correspond exactly to any actual data points in the plot.
If you need to know the exact coordinates of plotted points, use the Export Plot menu item and inspect
the resulting file in another program.)
When you create a plot, as with all widgets, the edit dialog automatically appears.

Many of the fields are fairly self-explanatory, such as the name of the plot, labels for the x and y axes,
ranges for the axes, and the “Show legend?” checkbox.
If Auto Scale? is checked the x and y changes will automatically readjust as points are added to the plot
if they are outside the current range.
Under “Plot setup commands” and “Plot update commands” you can enter commands that will
automatically be run at appropriate times. Click the little triangle to open the text box for the commands.
Plot commands are explained in more detail in the Plotting section of the Programming Guide.

Plot Pens
In the plot pens section of the dialog, you can create and customize your plot’s pens. Each table row
represents a pen. By default there is one pen named “default”. (You may wish to change it to a name
that has meaning in your model.)
To edit the color of a pen click the colored rectangle to the left of the pen’s name. This will bring up a
dialog that allows you to set the color to one of the NetLogo base hues or a custom color using the color

swatches.
To edit the pen’s name, double click the name.
In the “Pen Update Commands” column you can enter commands that will be run whenreset-ticks,
tick, or update-plots commands are run. This is explained in more detail in the Plotting section of the
Programming Guide.
The last column has two buttons. Clicking the pencil icon will bring up an edit dialog with additional pen
settings. The trash can button deletes the pen.

Plot Pen Advanced Settings
Clicking a pen’s edit button will open this dialog:

Mode allows you to change the appearance of the plot pen: line, bar (for a bar chart), or point (a
scatter plot of individual points).
Interval is the amount by which x advances every time you use theplot command.
If the “Show in legend” checkbox is checked the selected pen will be a part of the legend in the
upper right hand corner of the plot.
In the “Setup commands” field you can enter commands that will be run whenreset-ticks or
setup-plots runs.
In the “Update commands” field you can enter commands that will be run whentick or updateplots runs. This field reappears in the advanced dialog to provide space for editing lengthier sets
of commands.
For more detailed information on how each of these features works you can see the Plotting Section of
the Programming Guide.

Sliders
A slider has an associated global variable. Moving the slider changes the variable’s value.
When you place a slider in the Interface tab the edit dialog automatically opens, as with all widgets. Most
of the fields will be familiar. However, it is important to notice the minimum, maximum and increment
fields will take any reporter, not just constants. So, for example, you could make the minimum min-pxcor
and the maximum max-pxcor and the slider bounds will automatically adjust when you change the size of
the world.

Agent Monitors
Agent monitors display both the values of all the variables for a particular agent and a mini-view that
shows the agent and a small area around it.
You can open agent monitors through the Tools menu or theinspect command.

You can zoom in or out using the slider beneath the view and you canwatch the agent in the main view
using the watch-me button.

Below the slider the current value of each agent variable is displayed. You can enter a new value. It will
be as if, for example, the code set pcolor ... had run.

Below the agent variable area there is a mini-command center. Rather than running code as the
observer, or talking to all of the turtles, patches, or links, the code entered in this command center is run
only by this agent.

You can close an agent monitor by clicking the box in the upper left corner, or by pressing the Esc key. If
you hold down shift while you click the box all open agent monitors will close or you can close all the
agent monitors using the “Close All Monitors” option in the Tools Menu.

Info Tab
NetLogo 6.0.4 User Manual

The Info tab provides an introduction to a model. It explains what system is being modeled, how
the model was created, and and how to use it. It may also suggest things to explore and ways to
extend the model, or call your attention to particular NetLogo features the model uses.

You may wish to read the Info tab before starting a model.

Editing
The normal, formatted view of the Info tab is not editable. To make edits, click the "Edit" button.
When done editing, click the "Edit" button again.

You edit the Info tab as unformatted plain text. When you're done editing, the plain text you
entered is displayed in a more attractive format.
To control how the formatted display looks, you use a "markup language" called Markdown. You
may have encountered Markdown elsewhere; it is used on a number of web sites. (There are
other markup languages in use on the web; for example, Wikipedia used a markup language
called MediaWiki. Markup languages differ in details.)
The remainder of this guide is a tour of Markdown.
Headings
Paragraphs
Italicized and bold text
Ordered lists
Unordered lists
Links
Images
Block quotations
Code
Code blocks
Superscripts and subscripts
Notes on usage
Other features

Headings
A heading begins with one or more hash marks (#). First level headings get one hash, second
level headings get two, and so on up to four levels.

Input
# First-level heading
## Second-level heading
### Third-level heading

#### Fourth-level heading

Paragraphs
Example
This is a paragraph. There are no spaces before the word 'This'.
This is another paragraph. The first line has two sentences.
The entire paragraph has two lines and three sentences.
Line breaks in the input,
Make line breaks in the output,
Like this.

Formatted
This is a paragraph. There are no spaces before the word ‘This’.
This is another paragraph. The first line has two sentences. The entire paragraph has two lines
and three sentences.
Line breaks in the input, Make line breaks in the output, Like this.

Italicized and bold text
Example
For italics, surround text with underscores:
_hello, world_.
For bold, surround text with two asterisks:
**hello, world**.
You can also combine them:
_**hello**_ and **_goodbye_**

Formatted
For italics, surround text with underscores: hello, world.
For bold, surround text with two asterisks: hello, world.
You can also combine them: hello and goodbye

Ordered lists
Example
We are about to start an ordered list.
1. Ordered lists are indented 2 spaces.
1. Subitems are indented 2 more spaces (4 in all).
2. The next item in the list starts with the next number.

3. And so on...

Formatted
We are about to start an ordered list.
1. Ordered lists are indented 2 spaces.
1. Subitems are indented 2 more spaces (4 in all for a second level item).
2. The next item in the list starts with the next number.
3. And so on…

Unordered lists
Example
We are about to start an unordered list.
* Like ordered lists, unordered lists are also indented 2 spaces.
* Unlike ordered lists, unordered lists use stars instead of numbers.
* Sub items are indented 2 more spaces.
* Here's another sub item.

Formatted
We are about to start an unordered list.
Like ordered lists, unordered lists are also indented 2 spaces.
Unlike ordered lists, unordered lists use stars instead of numbers.
Sub items are indented 2 more spaces.
Here’s another sub item.

Links
Automatic links
The simplest way to create a link is to just type it in:

Example
http://ccl.northwestern.edu/netlogo/

Formatted
http://ccl.northwestern.edu/netlogo/

Links with text
If you want to use your own text for the link, here’s how:

[link text here](link.address.here)

Example
[NetLogo](http://ccl.northwestern.edu/netlogo/)

Formatted
NetLogo

Local links
It is also possible to link to a page on your computer, instead of a page somewhere on the
Internet.
Local links have this form:
[alt text](file:path)

Any spaces in the path must be converted to %20. For example, this:
file:my page.html

must be written as:
file:my%20page.html

The path is relative to the directory that the model file is in.

Example
The easiest way to link to files on your computer is to put them into the same directory as your
model. Assuming you have a file named index.html in the same directory as your model, the link
would look like this:
[Home](file:index.html)

Example
Here is another example where the file lives in a directory called docs, and docs is in the same
directory as your model:
[Home](file:docs/index.html)

Images

Images are very similar to links, but have an exclamation point in front:
![alt text](http://location/of/image)

(The alternate text is the text that gets displayed if the image is not found.)

Example
![NetLogo](http://ccl.northwestern.edu/netlogo/images/netlogo-title-new.jpg)

Formatted

Local images
Also very similar to links, it is possible to display an image on your computer instead of an image
somewhere on the Internet. Assuming you have an image named image.jpg, local images look
like this:
![alt text](file:path)

The path is relative to the directory that the model file is in.
As with local links, any spaces in the name of the file or the path must be converted to %20.

Example
Like local links, the easiest way to display images on your computer is to put them into the same
directory as your model. This example displays the image “Perspective Example.png”, which
resides in the same directory as this model (Info Tab Example).
![Example](file:Perspective%20Example.png)

Formatted

Block quotations
Consecutive lines starting with > will become block quotations. You can put whatever text you like
inside of it and you can also style it.

Example
> Let me see: four times five is twelve, and four times six is thirteen,
> and four times seven is --- _oh dear!_
> I shall never get to twenty at that rate!

Formatted
Let me see: four times five is twelve, and four times six is thirteen, and four times seven
is — oh dear! I shall never get to twenty at that rate!

Code
To include a short piece of code in a sentence, surround it with backticks (`).

Example
You can create a single turtle with the `crt 1` command.

Formatted
You can create a single turtle with the crt 1 command.

Code blocks
It is also possible to have blocks of code. To create a code block, indent every line of the block by
4 spaces. Another way is to surround it with a three backticks line before and after the block. (If
you don’t want your code to be colored as NetLogo code, add text after the first three backticks.)

Example
About to start the code block.
Leave a blank line after this one, and then put the code block:
; a typical go procedure
to go
ask turtles
[ fd 1 ]
tick
end

or:
About to start the code block.
Leave a blank line after this one, and then put the code block:
```
; a typical go procedure
to go
ask turtles
[ fd 1 ]
tick
end
```

Formatted
About to start the code block. Leave a blank line after this one, and then put the code block:
; a typical go procedure
to go
ask turtles
[ fd 1 ]
tick
end

Superscripts and subscripts
Superscripts and subscripts are useful for writing formulas, equations, footnotes and more.
Subscripts appear half a character below the baseline, and are written using the HTML tag _{.
Superscripts appear half a character above the baseline, and are written using the HTML tag
^{.

Example

H₂O
2x⁴ + x²
WWW^[1]

Formatted
H 2O
2x4 + x2 + 42
WWW[1]

Notes on usage
Paragraphs, lists, code blocks and other features should be separated from each other with
a blank line. If you find that something isn’t formatted the way you expected, it might be
because you need to add a blank line before it.
To prevent a special character from being treated as markup, put a backslash (\) before it.
We use GitHub flavored newlines (https://github.github.com/github-flavored-markdown/)
instead of traditional Markdown handling of newlines. This means that newlines are treated
as real line breaks, instead of being combined with the previous line into a single paragraph.

Other features
Markdown has additional features that we have not shown here.
We have tested the features shown above on a variety of systems. If you use other Markdown
features, you may find that they work on your computer, or not. Even a feature that works on your
computer might work differently, or not work at all, for someone with a different operating system
or Java virtual machine.
If you want all NetLogo users to be able to read your Info tab, use only the features shown above.
More information about Markdown is at https://daringfireball.net/projects/markdown/. For
rendering Markdown, NetLogo uses the Flexmark-java library.

Code Tab Guide
NetLogo 6.0.4 User Manual

The Code tab is where the code for the model is stored. Commands you only want to use
immediately go in the Command Center; commands you want to save and use later, over and
over again, are found in the Code tab.

Checking for Errors
To determine if the code has any errors, you may press the “Check” button. If there are any
syntax errors, the Code tab will turn red, the code that contains the error will be highlighted,
and an error message will appear.

Switching tabs also causes the code to be checked, so if you just switch tabs, pressing the
Check button first isn’t necessary.

Find & Replace

To find a fragment of code in the procedures, click on the “Find” button in the Code toolbar
and the Find dialog will appear.

You may enter a word or phrase to find, and optionally also a new word or phrase to replace it
with. The “Ignore case” checkbox controls whether the capitalization must be the same to
indicate a match.
If the “Wrap around” checkbox is checked, the entire Code tab will be checked for the phrase,
starting at the cursor position. When it reaches the end it will return to the top, otherwise only
the area from the cursor position to the end of the Code tab will be searched. The “Next” and
“Previous” buttons will move down and up to find another occurrence of the search phrase.
“Replace” changes the currently selected phrase with the replace phrase and “Replace &
Find” changes the selected phrase and moves to the next occurrence. “Replace All” will
change all instances of the find phrase in the search area with the replace phrase.

Automatic Indentation
When the Indent Automatically checkbox is selected, NetLogo will automatically attempt to
align your code in a logically structured format. For example, when you open a set of square
brackets “[” (perhaps after an if statement), NetLogo will automatically add spaces so that
the following lines of code are two spaces further indented than the bracket. When you close
the square brackets the closing bracket will be lined up with the matching open bracket.

NetLogo will try to indent the code as you type, but you can also press the tab key anywhere
on any line to ask NetLogo to indent the line immediately. Or, you can select a whole region of
code and press the tab key to re-indent all of it.

More Editing Options
To find a particular procedure definition in your code, use the “Procedures” popup menu in the
Code tab. The menu lists all procedures in the order they appear in the file. To search for a
particular procedure, use the search field at the top of the popup. It will filter the list of
procedures using fuzzy matching as you type. Fuzzy match will include procedures whose

names contain the characters that you type in the order that they appear in the search field,
but the characters do not have to be right next to each other. For instance, “fnn” will
match"find-nearest-neighbors" and “wolf-down-neighbor” but not “nearest-wolf-neighbor”.
You may use the arrow keys or mouse to select a particular procedure and enter or click to
jump to it. This can be a very convenient way to navigate your file. To facilitate this, you can
use the shortcut ctrl-g (cmd+g on Mac OS) to access the procedures menu.
The “Shift Left”, “Shift Right”, “Comment”, and “Uncomment” items on the Edit menu are used
in the Code tab to change the indentation level of your code or add and remove semicolons,
which mark comments, from sections of code.
For more information about writing procedures, readTutorial #3: Procedures and the
Programming Guide.

Included Files Menu
Caution: The includes facility is new and experimental.
When you add the __includes keyword to a model a menu to the right of the procedures menu
appears. This is the “Included Files” menu which lists all the NetLogo source files (.nls)
included in this file. You can make this menu always visible using the Preferences dialog.

You can choose a file name from the menu to open a tab for that file, or you can open a new
or existing file using New Source File and Open Source File, respectively.

Once you’ve opened new tabs they become accessible from the Tabs menu, and you can use
the keyboard to move from tab to tab (Command + number on Mac, Control + number on
other operating systems).

Programming Guide
NetLogo 6.0.4 User Manual

This section describes the NetLogo programming language in detail.
The Code Example models mentioned throughout can be found in the Code Examples section of the
Models Library.

Agents
The NetLogo world is made up of agents. Agents are beings that can follow instructions.
In NetLogo, there are four types of agents:turtles, patches, links, and the observer.
Turtles are agents that move around in the world. The world is two dimensional and is divided up into a
grid of patches. Each patch is a square piece of “ground” over which turtles can move. Links are agents
that connect two turtles. The observer doesn’t have a location – you can imagine it as looking out over
the world of turtles and patches.
The observer doesn’t observe passively – it gives instructions to the other agents.
When NetLogo starts up, there are no turtles. The observer can make new turtles. Patches can make
new turtles too. (Patches can’t move, but otherwise they’re just as “alive” as turtles.)
Patches have coordinates. The patch at coordinates (0, 0) is called the origin and the coordinates of the
other patches are the horizontal and vertical distances from this one. We call the patch’s coordinates
pxcor and pycor. Just like in the standard mathematical coordinate plane,pxcor increases as you move
to the right and pycor increases as you move up.
The total number of patches is determined by the settingsmin-pxcor, max-pxcor, min-pycor and maxpycor. When NetLogo starts up, min-pxcor, max-pxcor, min-pycor and max-pycor are -16, 16, -16, and 16
respectively. This means that pxcor and pycor both range from -16 to 16, so there are 33 times 33, or
1089 patches total. (You can change the number of patches with the Settings button.)
Turtles have coordinates too: xcor and ycor. A patch’s coordinates are always integers, but a turtle’s
coordinates can have decimals. This means that a turtle can be positioned at any point within its patch; it
doesn’t have to be in the center of the patch.
Links do not have coordinates. Every link has two ends, and each end is a turtle. If either turtle dies, the
link dies too. A link is represented visually as a line connecting the two turtles.

Procedures
In NetLogo, commands and reporters tell agents what to do. A command is an action for an agent to
carry out, resulting in some effect. A reporter is instructions for computing a value, which the agent then
“reports” to whoever asked it.
Typically, a command name begins with a verb, such as “create”, “die”, “jump”, “inspect”, or “clear”. Most
reporter names are nouns or noun phrases.
Commands and reporters built into NetLogo are called primitives. The NetLogo Dictionary has a
complete list of built-in commands and reporters.
Commands and reporters you define yourself are called procedures. Each procedure has a name,
preceded by the keyword to or to-report, depending on whether it is a command procedure or a
reporter procedure. The keyword end marks the end of the commands in the procedure. Once you
define a procedure, you can use it elsewhere in your program.
Many commands and reporters take inputs – values that the command or reporter uses in carrying out
its actions or computing its result.
Here are two command procedures:

to setup
clear-all
create-turtles 10
reset-ticks
end
to go
ask turtles [
fd 1
rt random 10
lt random 10
]
tick
end

;; forward 1 step
;; turn right
;; turn left

Note the use of semicolons to add “comments” to the program. Comments can make your code easier
to read and understand, but they don’t affect its behavior.
In this program,
setup and go are user-defined commands.
clear-all, create-turtles , reset-ticks, ask, lt

(“left turn”), rt (“right turn”) and tick, are all
primitive commands.
random and turtles are primitive reporters. random takes a single number as an input and reports a
random integer that is less than the input (in this case, between 0 and 9). turtles reports the
agentset consisting of all the turtles. (We’ll explain about agentsets later.)
setup

and go can be called by other procedures, or by buttons, or from the Command Center.

Many NetLogo models have a once button that calls a procedure calledsetup and a forever button that
calls a procedure called go.
In NetLogo, you may specify which agents – turtles, patches, or links – are to run each command. If you
don’t specify, the code is run by the observer. In the code above, the observer uses ask to make the set
of all turtles run the commands between the square brackets.
and create-turtles can only be run by the observer. fd, on the other hand, can only be run
by turtles. Some other commands and reporters, such as set and ticks, can be run by different agent
types.
clear-all

Here are some more advanced features you can take advantage of when defining your own procedures.
Procedures with inputs
Procedures can take inputs, just like many primitives do. To create a procedure that accepts inputs, put
their names in square brackets after the procedure name. For example:
to draw-polygon [num-sides len]
pen-down
repeat num-sides [
fd len
rt 360 / num-sides
]
end

;; turtle procedure

Elsewhere in the program, you might use the procedure by asking the turtles to each draw an octagon
with a side length equal to its who number:
ask turtles [ draw-polygon 8 who ]

Reporter procedures
Just like you can define your own commands, you can define your own reporters. You must do two
special things. First, use to-report instead of to to begin your procedure. Then, in the body of the
procedure, use report to report the value you want to report.

to-report absolute-value [number]
ifelse number >= 0
[ report number ]
[ report (- number) ]
end

Variables
Agent variables
Agent variables are places to store values (such as numbers) in an agent. An agent variable can be a
global variable, a turtle variable, a patch variable, or a link variable.
If a variable is a global variable, there is only one value for the variable, and every agent can access it.
You can think of global variables as belonging to the observer.
Turtle, patch, and link variables are different. Each turtle has itsown value for every turtle variable. The
same goes for patches and links.
Some variables are built into NetLogo. For example, all turtles and links have acolor variable, and all
patches have a pcolor variable. (The patch variable begins with “p” so it doesn’t get confused with the
turtle variable, since turtles have direct access to patch variables.) If you set the variable, the turtle or
patch changes color. (See next section for details.)
Other built-in turtle variables including xcor, ycor, and heading . Other built-in patch variables include
pxcor and pycor. (There is a complete list here.)
You can also define your own variables. You can make a global variable by adding a switch, slider,
chooser, or input box to your model, or by using the globals keyword at the beginning of your code, like
this:
globals [score]

You can also define new turtle, patch and link variables using theturtles-own, patches-own and linksown keywords, like this:
turtles-own [energy speed]
patches-own [friction]
links-own [strength]

These variables can then be used freely in your model. Use theset command to set them. (Any variable
you don’t set has a starting value of zero.)
Global variables can be read and set at any time by any agent. As well, a turtle can read and set patch
variables of the patch it is standing on. For example, this code:
ask turtles [ set pcolor red ]

causes every turtle to make the patch it is standing on red. (Because patch variables are shared by
turtles in this way, you can’t have a turtle variable and a patch variable with the same name.)
In other situations where you want an agent to read a different agent’s variable, you can useof.
Example:
show [color] of turtle 5
;; prints current color of turtle with who number 5

You can also use of with a more complicated expression than just a variable name, for example:
show [xcor + ycor] of turtle 5

;; prints the sum of the x and y coordinates of
;; turtle with who number 5

Local variables
A local variable is defined and used only in the context of a particular procedure or part of a procedure.
To create a local variable, use the let command. If you use let at the top of a procedure, the variable
will exist throughout the procedure. If you use it inside a set of square brackets, for example inside an
“ask”, then it will exist only inside those brackets.
to swap-colors [turtle1 turtle2]
let temp [color] of turtle1
ask turtle1 [ set color [color] of turtle2 ]
ask turtle2 [ set color temp ]
end

Tick counter
In many NetLogo models, time passes in discrete steps, called “ticks”. NetLogo includes a built-in tick
counter so you can keep track of how many ticks have passed.
The current value of the tick counter is shown above the view. (You can use the Settings button to hide
the tick counter, or change the word “ticks” to something else.)
In code, to retrieve the current value of the tick counter, use theticks reporter. The tick command
advances the tick counter by 1. The clear-all command clears the tick counter along with everything
else.
When the tick counter is clear, it’s an error to try to read or modify it. Use thereset-ticks command
when your model is done setting up, to start the tick counter.
If your model is set to use tick-based updates, then thetick command will usually also update the view.
See the later section, View Updates.

When to tick
Use reset-ticks at the end of your setup procedure.
Use tick at the end of your go procedure.
to setup
clear-all
create-turtles 10
reset-ticks
end
to go
ask turtles [ fd 1 ]
tick
end

Fractional ticks
In most models, the tick counter starts at 0 and goes up 1 at a time, from integer to integer. But it’s also
possible for the tick counter to take on in-between floating point values.
To advance the tick counter by a fractional amount, use thetick-advance command. This command
takes a numeric input specifying how far to advance the tick counter.
A typical use of fractional ticks is to approximate continuous or curved motion. See, for example, the
GasLab models in the Models Library (under Chemistry & Physics). These models calculate the exact
time at which a future event is to occur, then advance the tick counter to exactly that time.

Colors
NetLogo represents colors in different ways. A color can be number in the range 0 to 140, with the
exception of 140 itself. Below is a chart showing the range of such colors you can use in NetLogo.

The chart shows that:
Some of the colors have names. (You can use these names in your code.)
Every named color except black and white has a number ending in 5.
On either side of each named color are darker and lighter shades of the color.
0 is pure black. 9.9 is pure white.
10, 20, and so on are all so dark they are very nearly black.
19.9, 29.9 and so on are all so light they are very nearly white.
Code Example: The color chart was made in NetLogo with the Color Chart Example model.
If you use a number outside the 0 to 140 range, NetLogo will repeatedly add or subtract 140 from the
number until it is in the 0 to 140 range. For example, 25 is orange, so 165, 305, 445, and so on are
orange too, and so are -115, -255, -395, etc. This calculation is done automatically whenever you set
the turtle variable color or the patch variable pcolor. Should you need to perform this calculation in
some other context, use the wrap-color primitive.
If you want a color that’s not on the chart, more exist between the integers. For example, 26.5 is a shade
of orange halfway between 26 and 27. This doesn’t mean you can make any color in NetLogo; the
NetLogo color space is only a subset of all possible colors. It contains only a fixed set of discrete hues
(one hue per row of the chart). Starting from one of those hues, you can either decrease its brightness
(darken it) or decrease its saturation (lighten it), but you cannot decrease both brightness and saturation.
Also, only the first digit after the decimal point is significant. Thus, color values are rounded down to the
next 0.1, so for example, there’s no visible difference between 26.5 and 26.52 or 26.58.
Color primitives
There are a few primitives that are helpful for working with colors.
We have already mentioned the wrap-color primitive.

The scale-color primitive is useful for converting numeric data into colors.
shade-of?
orange 27

will tell you if two colors are both “shades” of the same basic hue. For example,shade-of?
is true, because 27 is a lighter shade of orange.

Code Example: Scale-color Example demonstrates the scale-color reporter.
RGB and RGBA Colors
NetLogo also represents colors as RGB (red/green/blue) lists and RGBA (red/green/blue/alpha) lists.
When using RGB colors the full range of colors is available to you. RGBA colors allow all the colors that
RGB allows and you can also vary the transparency of a color. RGB and RGBA lists are made up of
three or four integers, respectively, between 0 and 255 if a number is outside that range 255 is
repeatedly subtracted until it is in the range. You can set any color variables in NetLogo (color for turtles
and links and pcolor for patches) to an RGB list and that agent will be rendered appropriately. So you
can set the color of patch 0 0 to pure red using the following code:
set pcolor [255 0 0]

Turtles, links, and labels can all contain RGBA lists as their color variables, however, patches cannot
have RGBA pcolors You can set the color of a turtle to be approximately half transparent pure red with
the following code:
set color [255 0 0 125]

You can convert from a NetLogo color to RGB or HSB (hue/saturation/brightness) usingextract-hsb
and extract-rgb. You can use rgb to generate rgb lists and hsb to convert from an HSB color to RGB.
Since many colors are missing from the NetLogo color space,approximate-hsb and approximate-rgb
often can’t give you the exact color you ask for, but they try to come as close as possible.
Example: you can change any turtle from it’s existing NetLogo color to a half transparent version of that
color using:
set color lput 125 extract-rgb color

Code Examples: HSB and RGB Example (lets you experiment with the HSB and RGB color
systems), Transparency Example
Color Swatches dialog
The Color Swatches dialog helps you experiment with and choose colors. Open it by choosing Color
Swatches on the Tools Menu.

When you click on a color swatch (or a color button), that color will be shown against other colors. In the
bottom left, the code for the currently selected color is displayed (for example, red + 2 ) so you can copy
and paste it into your code. On the bottom right there are three increment options, 1, 0.5, and 0.1.
These numbers indicate the difference between two adjacent swatches. When the increment is 1 there
are 10 different shades in each row; when the increment is 0.1 there are 100 different shades in each
row. 0.5 is an intermediate setting.

Ask
NetLogo uses the ask command to give commands to turtles, patches, and links. All code to be run by
turtles must be located in a turtle “context”. You can establish a turtle context in any of three ways:
In a button, by choosing “Turtles” from the popup menu. Any code you put in the button will be run
by all turtles.
In the Command Center, by choosing “Turtles” from the popup menu. Any commands you enter
will be run by all the turtles.
By using ask turtles, hatch, or other commands which establish a turtle context.
The same goes for patches, links, and the observer, except that you cannotask the observer. Any code
that is not inside any ask is by default observer code.
Here’s an example of the use ofask in a NetLogo procedure:
to setup
clear-all
create-turtles 100
;; create 100 turtles with random headings
ask turtles
[ set color red
;; turn them red
fd 50 ]
;; spread them around
ask patches
[ if pxcor > 0
;; patches on the right side
[ set pcolor green ] ] ;; of the view turn green
reset-ticks
end

The models in the Models Library are full of other examples. A good place to start looking is in the Code
Examples section.
Usually, the observer uses ask to ask all turtles, all patches or all links to run commands. You can also
use ask to have an individual turtle, patch or link run commands. The reportersturtle, patch, link and
patch-at are useful for this technique. For example:

to setup
clear-all
crt 3
;; make 3 turtles
ask turtle 0
;; tell the first one...
[ fd 1 ]
;; ...to go forward
ask turtle 1
;; tell the second one...
[ set color green ]
;; ...to become green
ask turtle 2
;; tell the third one...
[ rt 90 ]
;; ...to turn right
ask patch 2 -2
;; ask the patch at (2,-2)
[ set pcolor blue ]
;; ...to become blue
ask turtle 0
;; ask the first turtle
[ ask patch-at 1 0
;; ...to ask patch to the east
[ set pcolor red ] ]
;; ...to become red
ask turtle 0
;; tell the first turtle...
[ create-link-with turtle 1 ] ;; ...make a link with the second
ask link 0 1
;; tell the link between turtle 0 and 1
[ set color blue ]
;; ...to become blue
reset-ticks
end

Every turtle created has a who number. The first turtle created is number 0, the second turtle number 1,
and so forth.
The turtle primitive reporter takes a who number as an input, and reports the turtle with that who
number. The patch primitive reporter takes values for pxcor and pycor and reports the patch with those
coordinates. The link primitive takes two inputs, the who numbers of the two turtles it connects. And the
patch-at primitive reporter takes offsets: distances, in the x and y directions,from the first agent. In the
example above, the turtle with who number 0 is asked to get the patch east (and no patches north) of
itself.
You can also select a subset of turtles, or a subset of patches, or a subset of links and ask them to do
something. This involves using agentsets. The next section explains them in detail.
When you ask a set of agents to run more than one command, each agent must finish before the next
agent starts. One agent runs all of the commands, then the next agent runs all of them, and so on. For
example, if you write:
ask turtles
[ fd 1
set color red ]

first one turtle moves and turns red, then another turtle moves and turns red, and so on.
But if you write it this way:
ask turtles [ fd 1 ]
ask turtles [ set color red ]

first all the turtles move, then they all turn red.

Agentsets
An agentset is exactly what its name implies, a set of agents. An agentset can contain either turtles,
patches or links, but not more than one type at once.
An agentset is not in any particular order. In fact, it’s always in a random order. And every time you use
it, the agentset is in a different random order. This helps you keep your model from treating any
particular turtles, patches or links differently from any others (unless you want them to be). Since the
order is random every time, no one agent always gets to go first.
You’ve seen the turtles primitive, which reports the agentset of all turtles, thepatches primitive, which
reports the agentset of all patches and the links primitive which reports the agentset of all links.
But what’s powerful about the agentset concept is that you can construct agentsets that contain only
some turtles, some patches or some links. For example, all the red turtles, or the patches with pxcor

evenly divisible by five, or the turtles in the first quadrant that are on a green patch or the links
connected to turtle 0. These agentsets can then be used by ask or by various reporters that take
agentsets as inputs.
One way is to use turtles-here or turtles-at, to make an agentset containing only the turtles on my
patch, or only the turtles on some other patch at some x and y offsets. There’s also turtles-on so you
can get the set of turtles standing on a given patch or set of patches, or the set of turtles standing on
the same patch as a given turtle or set of turtles.
Here are some more examples of how to make agentsets:
;; all other turtles:
other turtles
;; all other turtles on this patch:
other turtles-here
;; all red turtles:
turtles with [color = red]
;; all red turtles on my patch
turtles-here with [color = red]
;; patches on right side of view
patches with [pxcor > 0]
;; all turtles less than 3 patches away
turtles in-radius 3
;; the four patches to the east, north, west, and south
patches at-points [[1 0] [0 1] [-1 0] [0 -1]]
;; shorthand for those four patches
neighbors4
;; turtles in the first quadrant that are on a green patch
turtles with [(xcor > 0) and (ycor > 0)
and (pcolor = green)]
;; turtles standing on my neighboring four patches
turtles-on neighbors4
;; all the links connected to turtle 0
[my-links] of turtle 0

Note the use of other to exclude this agent. This is common.
Once you have created an agentset, here are some simple things you can do:
Use ask to make the agents in the agentset do something
Use any? to see if the agentset is empty
Use all? to see if every agent in an agentset satisfies a condition.
Use count to find out exactly how many agents are in the set
And here are some more complex things you can do:
Pick a random agent from the set usingone-of. For example, we can make a randomly chosen
turtle turn green:
ask one-of turtles [ set color green ]

Or tell a randomly chosen patch to sprout a new turtle:
ask one-of patches [ sprout 1 ]

Use the max-one-of or min-one-of reporters to find out which agent is the most or least along some
scale. For example, to remove the richest turtle, you could say
ask max-one-of turtles [sum assets] [ die ]

Make a histogram of the agentset using thehistogram command (in combination with of).
Use of to make a list of values, one for each agent in the agentset. Then use one of NetLogo’s list
primitives to do something with the list. (See the “Lists” section below.) For example, to find out
how rich turtles are on the average, you could say

show mean [sum assets] of turtles

Use turtle-set, patch-set and link-set reporters to make new agentsets by gathering together
agents from a variety of possible sources.
Use no-turtles, no-patches and no-links reporters to make empty agentsets.
Check whether two agentsets are equal using = or !=.
Use member? to see whether a particular agent is a member of an agentset.
This only scratches the surface. See the Models Library for many more examples, and consult the
NetLogo Dictionary for more information about all of the agentset primitives.
More examples of using agentsets are provided in the individual entries for these primitives in the
NetLogo Dictionary.

Special agentsets
The agentsets turtles and links have special behavior because they always hold the sets ofall turtles
and all links. Therefore, these agentsets can grow.
The following interaction shows the special behavior. Assume the Code tab hasglobals [g]. Then:
observer>
observer>
observer>
observer>
5
observer>
observer>
10
observer>
observer>
10
observer>
observer>
10
observer>
15

clear-all
create-turtles 5
set g turtles
print count g
create-turtles 5
print count g
set g turtle-set turtles
print count g
create-turtles 5
print count g
print count turtles

The turtles agentset grows when new turtles are born, but other agentsets don’t grow. If I writeturtleset turtles, I get a new, normal agentset containing just the turtles thatcurrently exist. New turtles don’t
join when they’re born.
Breed agentsets are special in the same way asturtles and links. Breeds are introduced and
explained below.

Agentsets and lists
Earlier, we said that agentsets are always in random order, a different random order every time. If you
need your agents to do something in a fixed order, you need to make a list of the agents instead. See
the Lists section below.
Code Example: Ask Ordering Example

Breeds
NetLogo allows you to define different “breeds” of turtles and breeds of links. Once you have defined
breeds, you can go on and make the different breeds behave differently. For example, you could have
breeds called sheep and wolves, and have the wolves try to eat the sheep or you could have link breeds
called streets and sidewalks where foot traffic is routed on sidewalks and car traffic is routed on streets.

You define turtle breeds using the breed keyword, at the top of the Code tab, before any procedures:
breed [wolves wolf]
breed [sheep a-sheep]

You can refer to a member of the breed using the singular form, just like theturtle reporter. When
printed, members of the breed will be labeled with the singular name.
Some commands and reporters have the plural name of the breed in them, such ascreate-.
Others have the singular name of the breed in them, such as .
The order in which breeds are declared is also the order in which they are layered in the view. So
breeds defined later will appear on top of breeds defined earlier; in this example, sheep will be drawn
over wolves.
When you define a breed such as sheep, an agentset for that breed is automatically created, so that all of
the agentset capabilities described above are immediately available with the sheep agentset.
The following new primitives are also automatically available once you define a breed:create-sheep ,
hatch-sheep, sprout-sheep , sheep-here, sheep-at , sheep-on , and is-a-sheep?.
Also, you can use sheep-own to define new turtle variables that only turtles of the given breed have. (It’s
allowed for more than one breed to own the same variable.)
A turtle’s breed agentset is stored in thebreed turtle variable. So you can test a turtle’s breed, like this:
if breed = wolves [ ... ]

Note also that turtles can change breeds. A wolf doesn’t have to remain a wolf its whole life. Let’s
change a random wolf into a sheep:
ask one-of wolves [ set breed sheep ]

The set-default-shape primitive is useful for associating certain turtle shapes with certain breeds. See
the section on shapes below.
Who numbers are assigned irrespective of breeds. If you already have afrog 0, then the first mouse will
be mouse 1 , not mouse 0 , since the who number 0 is already taken.
Here is a quick example of using breeds:
breed [mice mouse]
breed [frogs frog]
mice-own [cheese]
to setup
clear-all
create-mice 50
[ set color white
set cheese random 10 ]
create-frogs 50
[ set color green ]
reset-ticks
end

Code Example: Breeds and Shapes Example

Link breeds
Link breeds are very similar to turtle breeds, however, there are a few differences.

When you declare a link breed you must declare whether it is a breed of directed or undirected links by
using the directed-link-breed and undirected-link-breed keywords.
directed-link-breed [streets street]
undirected-link-breed [friendships friendship]

Once you have created a breeded link you cannot create unbreeded links and vice versa. (You can,
however, have directed and undirected links in the same world, just not in the same breed)
Unlike with turtle breeds the singular breed name is required for link breeds, as many of the link
commands and reports use the singular name, such as -neighbor? .
The following primitives are also automatically available once you define a directed link breed:createstreet-from create-streets-from create-street-to create-streets-to in-street-neighbor? instreet-neighbors in-street-from my-in-streets my-out-streets out-street-neighbor? out-streetneighbors out-street-to

And the following are automatically available when you define an undirected link breed:createfriendship-with create-friendships-with friendship-neighbor? friendship-neighbors friendshipwith my-friendships

Multiple link breeds may declare the same -own variable, but a variable may not be shared between a
turtle breed and a link breed.
Just as with turtle breeds the order in which link breeds are declared defines the order in which the links
are drawn, so the friendships will always be on top of streets (if for some reason these breeds were in
the same model). You can also use -own to declare variables of each link breed
separately.
You can change the breed of a link withset breed. (However, you cannot change a breeded link to an
unbreeded one, to prevent having breeded and unbreeded links in the same world.)
ask one-of friendships [ set breed streets ]
ask one-of friendships [ set breed links ] ;; produces a runtime error

set-default-shape

may also be used with link breeds to associate it with a particular link shape.

Code Example: Link Breeds Example

Buttons
Buttons in the interface tab provide an easy way to control the model. Typically a model will have at
least a “setup” button, to set up the initial state of the world, and a “go” button to make the model run
continuously. Some models will have additional buttons that perform other actions.
A button contains some NetLogo code. That code is run when you press the button.
A button may be either a “once button”, or a “forever button”. You can control this by editing the button
and checking or unchecking the “Forever” checkbox. Once buttons run their code once, then stop and
pop back up. Forever buttons keep running their code over and over again.
A forever button stops if the user presses the button again to stop it. The button waits until the current
iteration has finished, then pops up.
A forever button can also be stopped from code. If the forever button directly calls a procedure, then
when that procedure stops, the button stops. (In a turtle or patch forever button, the button won’t stop
until every turtle or patch stops – a single turtle or patch doesn’t have the power to stop the whole
button.)
Normally, a button is labeled with the code that it runs. For example, a button that says “go” on it usually

contains the code “go”, which means “run the go procedure”. (Procedures are defined in the Code tab;
see below.) But you can also edit a button and enter a “display name” for the button, which is a text that
appears on the button instead of the code. You might use this feature if you think the actual code would
be confusing to your users.
When you put code in a button, you must also specify which agents you want to run that code. You can
choose to have the observer run the code, or all turtles, or all patches, or all links. (If you want the code
to be run by only some turtles or some patches, you could make an observer button, and then have the
observer use the ask command to ask only some of the turtles or patches to do something.)
When you edit a button, you have the option to assign an “action key”. This makes that key on the
keyboard behave just like a button press. If the button is a forever button, it will stay down until the key is
pressed again (or the button is clicked). Action keys are particularly useful for games or any model
where rapid triggering of buttons is needed.
Buttons take turns
More than one button can be pressed at a time. If this happens, the buttons “take turns”, which means
that only one button runs at a time. Each button runs its code all the way through once while the other
buttons wait, then the next button gets its turn.
In the following examples, “setup” is a once button and “go” is a forever button.
Example #1: The user presses “setup”, then presses “go” immediately, before the “setup” has popped
back up. Result: “setup” finishes before “go” starts.
Example #2: While the “go” button is down, the user presses “setup”. Result: the “go” button finishes its
current iteration. Then the “setup” button runs. Then “go” starts running again.
Example #3: The user has two forever buttons down at the same time. Result: first one button runs its
code all the way through, then the other runs its code all the way through, and so on, alternating.
Note that if one button gets stuck in an infinite loop, then no other buttons will run.
Turtle, patch, and link forever buttons
There is a subtle difference between putting commands in a turtle, patch or link forever button, and
putting the same commands in an observer button that does ask turtles, ask patches or ask links. An
“ask” doesn’t complete until all of the agents have finished running all of the commands in the “ask”. So
the agents, as they all run the commands concurrently, can be out of sync with each other, but they all
sync up again at the end of the ask. The same isn’t true of turtle, patch and link forever buttons. Since
ask was not used, each turtle or patch runs the given code over and over again, so they can become
(and remain) out of sync with each other.
At present, this capability is very rarely used in the models in our Models Library. A model that does use
the capability is the Termites model, in the Biology section of Sample Models. The “go” button is a turtle
forever button, so each termite proceeds independently of every other termite, and the observer is not
involved at all. This means that if, for example, you wanted to add ticks and/or a plot to the model, you
would need to add a second forever button (an observer forever button), and run both forever buttons at
the same time. Note also that a model like this cannot be used with BehaviorSpace.
Code Example: State Machine Example shows how Termites can be recoded in a tick-based
way, without using a turtle forever button.
At present, NetLogo has no way for one forever button to start another. Buttons are only started when
you press them.

Lists
In the simplest models, each variable holds only one piece of information, usually a number or a string.
Lists let you store multiple pieces of information in a single value by collecting that information in a list.
Each value in the list can be any type of value: a number, or a string, an agent or agentset, or even

another list.
Lists allow for the convenient packaging of information in NetLogo. If your agents carry out a repetitive
calculation on multiple variables, it might be easier to have a list variable, instead of multiple number
variables. Several primitives simplify the process of performing the same computation on each value in
a list.
The NetLogo Dictionary has a section that lists all of the list-related primitives.
Constant lists
You can make a list by simply putting the values you want in the list between brackets, like this:set
mylist [2 4 6 8]. Note that the individual values are separated by spaces. You can make lists that
contain numbers and strings this way, as well as lists within lists, for example [[2 4] [3 5]] .
The empty list is written by putting nothing between the brackets, like this:[].
Building lists on the fly
If you want to make a list in which the values are determined by reporters, as opposed to being a series
of constants, use the list reporter. The list reporter accepts two other reporters, runs them, and
reports the results as a list.
If I wanted a list to contain two random values, I might use the following code:
set random-list list (random 10) (random 20)

This will set random-list to a new list of two random integers each time it runs.
To make longer or shorter lists, you can use thelist reporter with fewer or more than two inputs, but in
order to do so, you must enclose the entire call in parentheses, e.g.:
(list random 10)
(list random 10 random 20 random 30)

For more information, see Varying number of inputs.
Some kinds of lists are most easily built using then-values reporter, which allows you to construct a list
of a specific length by repeatedly running a given reporter. You can make a list of the same value
repeated, or all the numbers in a range, or a lot of random numbers, or many other possibilities. See
dictionary entry for details and examples.
The of primitive lets you construct a list from an agentset. It reports a list containing each agent’s value
for the given reporter. (The reporter could be a simple variable name, or a more complex expression –
even a call to a procedure defined using to-report.) A common idiom is
max [...] of turtles
sum [...] of turtles

and so on.
You can combine two or more lists using thesentence reporter, which concatenates lists by combining
their contents into a single, larger list. Like list, sentence normally takes two inputs, but can accept any
number of inputs if the call is surrounded by parentheses.
Changing list items
Technically, lists can’t be modified, but you can construct new lists based on old lists. If you want the
new list to replace the old list, use set. For example:
set mylist [2 7 5 Bob [3 0 -2]]
; mylist is now [2 7 5 Bob [3 0 -2]]

set mylist replace-item 2 mylist 10
; mylist is now [2 7 10 Bob [3 0 -2]]

The replace-item reporter takes three inputs. The first input specifies which item in the list is to be
changed. 0 means the first item, 1 means the second item, and so forth.
To add an item, say 42, to the end of a list, use thelput reporter. (fput adds an item to the beginning of
a list.)
set mylist lput 42 mylist
; mylist is now [2 7 10 Bob [3 0 -2] 42]

But what if you changed your mind? The but-last (bl for short) reporter reports all the list items but the
last.
set mylist but-last mylist
; mylist is now [2 7 10 Bob [3 0 -2]]

Suppose you want to get rid of item 0, the 2 at the beginning of the list.
set mylist but-first mylist
; mylist is now [7 10 Bob [3 0 -2]]

Suppose you wanted to change the third item that’s nested inside item 3 from -2 to 9? The key is to
realize that the name that can be used to call the nested list [3 0 -2] is item 3 mylist . Then the replaceitem reporter can be nested to change the list-within-a-list. The parentheses are added for clarity.
set mylist (replace-item 3 mylist
(replace-item 2 (item 3 mylist) 9))
; mylist is now [7 10 Bob [3 0 9]]

Iterating over lists
If you want to do some operation on each item in a list in turn, theforeach command and the map
reporter may be helpful.
is used to run a command or commands on each item in a list. It takes an input list and a
command name or block of commands, like this:
foreach

foreach [1 2 3] show
=> 1
=> 2
=> 3
foreach [2 4 6]
[ n -> crt n
show (word "created " n " turtles") ]
=> created 2 turtles
=> created 4 turtles
=> created 6 turtles

In the block, the variable n holds the current value from the input list.
Here are some more examples of foreach :
foreach [1 2 3] [ steps -> ask turtles [ fd steps ] ]
;; turtles move forward 6 patches
foreach [true false true true] [ should-move? -> ask turtles [ if should-move? [ fd 1 ] ] ]
;; turtles move forward 3 patches

is similar to foreach , but it is a reporter. It takes an input list and a reporter name or reporter block.
Note that unlike foreach , the reporter comes first, like this:
map

show map round [1.2 2.2 2.7]
;; prints [1 2 3]

reports a list containing the results of applying the reporter to each item in the input list. Again, use
the variable named in the anonymous procedure (x in the examples below) to refer to the current item in
the list.
map

Here are a couple more examples ofmap:
show map [ x -> x < 0 ] [1 -1 3 4 -2 -10]
;; prints [false true false false true true]
show map [ x -> x * x ] [1 2 3]
;; prints [1 4 9]

Besides map and foreach , other primitives for processing whole lists in a configurable way include
filter, reduce, and sort-by .
These primitives aren’t always the solution for every situation in which you want to operate on an entire
list. In some situations, you may need to use some other technique such as a loop using repeat or
while, or a recursive procedure.
The blocks of code we’re giving to map and foreach in these examples are actually anonymous
procedures. Anonymous procedures are explained in more detail inAnonymous procedures, below.
Varying number of inputs
Some commands and reporters involving lists and strings may take a varying number of inputs. In these
cases, in order to pass them a number of inputs other than their default, the primitive and its inputs must
be surrounded by parentheses. Here are some examples:
show list 1 2
=> [1 2]
show (list 1 2 3 4)
=> [1 2 3 4]
show (list)
=> []

Note that each of these special primitives has a default number of inputs for which no parentheses are
required. The primitives which have this capability are list, word, sentence, map, foreach , run, and
runresult.
Lists of agents
Earlier, we said that agentsets are always in random order, a different random order every time. If you
need your agents to do something in a fixed order, you need to make a list of the agents instead.
There are two primitives that help you do this, sort and sort-by .
Both sort and sort-by can take an agentset as input. The result is always a new list, containing the
same agents as the agentset did, but in a particular order.
If you use sort on an agentset of turtles, the result is a list of turtles sorted in ascending order bywho
number.
If you use sort on an agentset of patches, the result is a list of patches sorted left-to-right, top-to-bottom.
If you use sort on an agentset of links, the result is a list of links, sorted in ascending order first byend1
then by end2 any remaining ties are resolved by breed in the order they are declared in the Code tab.
If you need descending order instead, you can combine reverse with sort, for example reverse sort
turtles .
If you want your agents to be ordered by some other criterion than the standard onessort uses, you’ll
need to use sort-by instead.

Here’s an example:
sort-by [ [a b] -> [size] of a < [size] of b ] turtles

This returns a list of turtles sorted in ascending order by their turtle variablesize.
There’s a common pattern to get a list of agents in a random order, using a combination ofof and self,
in the rare case that you cannot just use ask:
[self] of my-agentset

Asking a list of agents
Once you have a list of agents, you might want to ask them each to do something. To do this, use the
foreach and ask commands in combination, like this:
foreach sort turtles [ the-turtle ->
ask the-turtle [
...
]
]

This will ask each turtle in ascending order by who number. Substitute “patches” for “turtles” to ask
patches in left-to-right, top-to-bottom order.
Note that you can’t use ask directly on a list of turtles. ask only works with agentsets and single agents.
Performance of lists
The data structure underlying NetLogo’s lists is a sophisticated tree-based data structure on which most
operations run in near-constant time. That includes fput, lput, butfirst, butlast , length, item, and
replace-item.
One exception to the fast-performance rule is that concatenating two lists withsentence requires
traversing and copying the whole second list. (This may be fixed in a future version.)
Technically, “near-constant time” is actually logarithmic time, proportional to the depth of the underlying
tree, but these trees have large nodes and a high branching factor, so they are never more than a few
levels deep. This means that changes can be made in at most a few steps. The trees are immutable, but
they share structure with each other, so the whole tree doesn’t need to be copied to make a changed
version.
The actual data structure used is the immutable Vector class from the Scala collections library. These
are 32-wide hash array mapped tries, as implemented by Tiark Rompf, based in part on work by Phil
Bagwell and Rich Hickey.

Math
All numbers in NetLogo are stored internally as double precision floating point numbers, as defined in
the IEEE 754 standard. They are 64 bit numbers consisting of one sign bit, an 11-bit exponent, and a
52-bit mantissa. See the IEEE 754 standard for details.
An “integer” in NetLogo is simply a number that happens to have no fractional part. No distinction is
made between 3 and 3.0; they are the same number. (This is the same as how most people use
numbers in everyday contexts, but different from some programming languages. Some languages treat
integers and floating point numbers as distinct types.)
Integers are always printed by NetLogo without the trailing “.0”:
show 1.5 + 1.5
observer: 3

If a number with a fractional part is supplied in a context where an integer is expected, the fractional part
is simply discarded. So for example, crt 3.5 creates three turtles; the extra 0.5 is ignored.
The range of integers is +/-9007199254740992 (2^53, about 9 quadrillion). Calculations that exceed this
range will not cause runtime errors, but precision will be lost when the least significant (binary) digits are
rounded off in order fit the number into 64 bits. With very large numbers, this rounding can result in
imprecise answers which may be surprising:
show 2 ^ 60 + 1 = 2 ^ 60
=> true

Calculations with smaller numbers can also produce surprising results if they involve fractional
quantities, since not all fractions can be precisely represented and roundoff may occur. For example:
show 1 / 6 + 1 / 6 + 1 / 6 + 1 / 6 + 1 / 6 + 1 / 6
=> 0.9999999999999999
show 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9 + 1 / 9
=> 1.0000000000000002

Any operation which produces the special quantities “infinity” or “not a number” will cause a runtime
error.
Scientific notation
Very large or very small floating point numbers are displayed by NetLogo using “scientific notation”.
Examples:
show 0.000000000001
=> 1.0E-12
show 50000000000000000000
=> 5.0E19

Numbers in scientific notation are distinguished by the presence of the letter E (for “exponent”). It means
“times ten to the power of”, so for example, 1.0E-12 means 1.0 times 10 to the -12 power:
show 1.0 * 10 ^ -12
=> 1.0E-12

You can also use scientific notation yourself in NetLogo code:
show 3.0E6
=> 3000000
show 8.123456789E6
=> 8123456.789
show 8.123456789E7
=> 8.123456789E7
show 3.0E16
=> 3.0E16
show 8.0E-3
=> 0.0080
show 8.0E-4
=> 8.0E-4

These examples show that numbers with fractional parts are displayed using scientific notation if the
exponent is less than -3 or greater than 6. Numbers outside of NetLogo’s integer range of 9007199254740992 to 9007199254740992 (+/-2^53) are also always shown in scientific notation:
show 2 ^ 60
=> 1.15292150460684698E18

When entering a number, the letter E may be either upper or lowercase. When printing a number,
NetLogo always uses an uppercase E:

show 4.5e20
=> 4.5E20

Floating point accuracy
Because numbers in NetLogo are subject to the limitations of how floating point numbers are
represented in binary, you may get answers that are slightly inaccurate. For example:
show 0.1 + 0.1 + 0.1
=> 0.30000000000000004
show cos 90
=> 6.123233995736766E-17

This is an inherent issue with floating point arithmetic; it occurs in all programming languages that use
floating point numbers.
If you are dealing with fixed precision quantities, for example dollars and cents, a common technique is
to use only integers (cents) internally, then divide by 100 to get a result in dollars for display.
If you must use floating point numbers, then in some situations you may need to replace a
straightforward equality test such as if x = 1 [ ... ] with a test that tolerates slight imprecision, for
example if abs (x - 1) < 0.0001 [ ... ] .
Also, the precision primitive is handy for rounding off numbers for display purposes. NetLogo monitors
round the numbers they display to a configurable number of decimal places, too.

Random numbers
The random numbers used by NetLogo are what is called “pseudo-random”. (This is typical in computer
programming.) That means they appear random, but are in fact generated by a deterministic process.
“Deterministic” means that you get the same results every time, if you start with the same random
“seed”. We’ll explain in a minute what we mean by “seed”.
In the context of scientific modeling, pseudo-random numbers are actually desirable. That’s because it’s
important that a scientific experiment be reproducible – so anyone can try it themselves and get the
same result that you got. Since NetLogo uses pseudo-random numbers, the “experiments” that you do
with it can be reproduced by others.
Here’s how it works. NetLogo’s random number generator can be started with a certain seed value,
which must be an integer in the range -2147483648 to 2147483647. Once the generator has been
“seeded” with the random-seed command, it always generates the same sequence of random numbers
from then on. For example, if you run these commands:
random-seed
show random
show random
show random

137
100
100
100

You will always get the numbers 79, 89, and 61 in that order.
Note, however, that you’re only guaranteed to get those same numbers if you’re using the same version
of NetLogo. Sometimes when we make a new version of NetLogo the random number generator
changes. (Presently, we use a generator known as the Mersenne Twister.)
To create a number suitable for seeding the random number generator, use thenew-seed reporter. newseed creates a seed, evenly distributed over the space of possible seeds, based on the current date and
time. It never reports the same seed twice in a row.
Code Example: Random Seed Example

If you don’t set the random seed yourself, NetLogo sets it to a value based on the current date and time.
There is no way to find out what random seed it chose, so if you want your model run to be reproducible,
you must set the random seed yourself ahead of time.
The NetLogo primitives with “random” in their names (random, random-float, and so on) aren’t the only
ones that use pseudo-random numbers. Many other operations also make random choices. For
example, agentsets are always in random order, one-of and n-of choose agents randomly, the sprout
command creates turtles with random colors and headings, and the downhill reporter chooses a
random patch when there’s a tie. All of these random choices are governed by the random seed as well,
so model runs can be reproducible.
In addition to the uniformly distributed random integers and floating point numbers generated byrandom
and random-float , NetLogo also offers several other random distributions. See the dictionary entries for
random-normal , random-poisson , random-exponential , and random-gamma .

Auxiliary generator
Code run by buttons or from the command center uses the main random number generator.
Code in monitors uses an auxiliary random generator, so even if a monitor does a calculation that uses
random numbers, the outcome of the model is not affected. The same is true of code in sliders.

Local randomness
You may want to explicitly specify that a section of code does not affect the state of the main random
generator, so the outcome of the model is not affected. The with-local-randomness command is
provided for this purpose. See its entry in the NetLogo Dictionary for more information.

Turtle shapes
In NetLogo, turtle shapes are vector shapes. They are built up from basic geometric shapes; squares,
circles, and lines, rather than a grid of pixels. Vector shapes are fully scalable and rotatable. NetLogo
caches bitmap images of vector shapes size 1, 1.5, and 2 in order to speed up execution.
A turtle’s shape is stored in its shape variable and can be set using the set command.
New turtles have a shape of “default”. The set-default-shape primitive is useful for changing the default
turtle shape to a different shape, or having a different default turtle shape for each breed of turtle.
The shapes primitive reports a list of currently available turtle shapes in the model. This is useful if, for
example, you want to assign a random shape to a turtle:
ask turtles [ set shape one-of shapes ]

Use the Turtle Shapes Editor to create your own turtle shapes, or to add shapes to your model from our
shapes library, or to transfer shapes between models. For more information, see the Shapes Editor
section of this manual.
The thickness of the lines used to draw the vector shapes can be controlled by the__set-linethickness primitive.
Code Examples: Breeds and Shapes Example, Shape Animation Example

Link shapes
Link Shapes are similar to turtle shapes, only you use the Link Shape Editor to create and edit them.
Link shapes consist of between 0 and 3 lines which can have different patterns and a direction indicator

that is composed of the same elements as turtle shapes. Links also have a shape variable that can be
set to any link shape that is in the model. By default links have the “default” shape, though you can
change that using set-default-shape. The link-shapes reporter reports all the link shapes included in
the current model.
The thickness of the lines in the link shape is controlled by thethickness link variable.

View updates
The “view” in NetLogo lets you see the agents in your model on your computer’s screen. As your agents
move and change, you see them moving and changing in the view.
Of course, you can’t really see your agents directly. The view is a picture that NetLogo paints, showing
you how your agents look at a particular instant. Once that instant passes and your agents move and
change some more, that picture needs to be repainted to reflect the new state of the world. Repainting
the picture is called “updating” the view.
When does the view get updated? This section discusses how NetLogo decides when to update the
view, and how you can influence when it gets updated.
NetLogo offers two updates modes, “continuous” updates and “tick-based” updates. You can switch
between NetLogo’s two view update modes using a popup menu at the top of the Interface tab.
Continuous updates are the default when you start up NetLogo or start a new model. Nearly every
model in our Models Library, however, uses tick-based updates.
Continuous updates are simplest, but tick-based updates give you more control over when and how
often updates happen.
It’s important exactly when an update happens, because when updates happen determines what you
see on the screen. If an update comes at an unexpected time, you may see something unexpected –
perhaps something confusing or misleading.
It’s also important how often updates happen, because updates take time. The more time NetLogo
spends updating the view, the slower your model will run. With fewer updates, your model runs faster.

Continuous updates
Continuous updates are very simple. With continuous updates, NetLogo updates the view a certain
number of times per second – by default, 30 times a second when the speed slider is in the default,
middle setting.
If you move the speed slider to a slower setting, NetLogo will update more than 30 times a second,
effectively slowing down the model. On a faster setting, NetLogo will update less than 30 times a
second. On the fastest setting, updates will be separated by several seconds.
At extremely slow settings, NetLogo will be updating so often that you will see your agents moving (or
changing color, etc.) one at a time.
If you need to temporarily shut off continuous updates, use theno-display command. The display
command turns updates back on, and also forces an immediate update (unless the user is fastforwarding the model using the speed slider).

Tick-based updates
As discussed above in the Tick Counter section, in many NetLogo models, time passes in discrete
steps, called “ticks”. Typically, you want the view to update once per tick, between ticks. That’s the
default behavior with tick-based updates.
If you want additional view updates, you can force an update using thedisplay command. (The update
may be skipped if the user is fast-forwarding the model using the speed slider.)

You don’t have to use the tick counter to use tick-based updates. If the tick counter never advances, the
view will update only when you use the display command.
If you move the speed slider to a fast enough setting, eventually NetLogo will skip some of the updates
that would ordinarily have happened. Moving the speed slider to a slower setting doesn’t cause
additional updates; rather, it makes NetLogo pause after each update. The slower the setting, the longer
the pause.
Even under tick-based updates, the view also updates whenever a button in the interface pops up (both
once and forever buttons) and when a command entered in the Command Center finishes. So it’s not
necessary to add the display command to once buttons that don’t advance the tick counter. Many
forever buttons that don’t advance the tick counter do need to use the display command. An example in
the Models Library is the Life model (under Computer Science -> Cellular Automata). The forever
buttons that let the user draw in the view use the display command so the user can see what they are
drawing, even though the tick counter is not advancing.

Choosing a mode
Advantages of tick-based updates over continuous updates include:
1. Consistent, predictable view update behavior which does not vary from computer to computer or
from run to run.
2. Continuous updates can confuse the user of your model by letting them see model states they
aren’t supposed to see, which may be misleading.
3. Since setup buttons don’t advance the tick counter, they are unaffected by the speed slider; this is
normally the desired behavior.
Nearly every model in our Models Library uses tick-based updates.
Continuous updates are occasionally useful for those rare models in which execution is not divided into
short, discrete phases. An example in the Models Library is Termites. (See also, however, the State
Machine Example model, which shows how to re-code Termites using ticks.)
Even for models that would normally be set to tick-based updates, it may be useful to switch to
continuous updates temporarily for debugging purposes. Seeing what’s going on within a tick, instead of
only seeing the end result of a tick, could help with troubleshooting. After switching to continuous
updates, you may want to use the speed slider to slow the model down until you see your agents
moving one at a time. Don’t forget to change back to tick-based updates when you are done, as the
choice of update mode is saved with the model.
Changing the update mode also affects model speed. Updating the view takes time; often enforcing a
single update per tick (by using tick-based updates) will make your model faster. On the other hand,
continuous updates will be faster when running a single tick is faster than drawing a frame of the model.
Most models run faster under tick-based updates, but for an example of a model which is faster with
continuous updates see the “Heroes and Cowards” library model.

Frame rate
One of the model settings in NetLogo’s “Settings…” dialog is “Frame rate” which defaults to 30 frames
per second.
The frame rate setting affects both continuous updates and tick-based updates.
With continuous updates, the setting directly determines the frequency of updates.
With tick-based updates, the setting is a ceiling on how many updates per second you get. If the frame
rate is 30, then NetLogo will ensure that the model never runs faster than that when the speed slider is
in the default position. If any frame takes less than 1/30 of a second to compute and display, NetLogo
will pause and wait until the full 1/30 of a second has passed before continuing.
The frame rate settings lets you set what you consider to be a normal speed for your model. Then you,
or the user of your model, can use the speed slider to temporarily get a faster or slower speed.

Plotting
NetLogo’s plotting features let you create plots to help you understand what’s going on in your model.
Before you can plot, you need to create one or more plots in the Interface tab. For more information on
using and editing plots in the Interface tab, see the Interface Guide.

Plotting points
The two basic commands for actually plotting things are plot and plotxy.
With plot you need only specify the y value you want plotted. The x value will automatically be 0 for the
first point you plot, 1 for the second, and so on. (That’s if the plot pen’s “interval” is the default value of 1;
you can change the interval.)
The plot command is especially handy when you want your model to plot a new point at every time
step. Example:
plot count turtles

If you need to specify both the x and y values of the point you want plotted, then useplotxy instead.
This example assumes that a global variable called time exists:
plotxy time count-turtles

Plot commands
Each plot and its pens have setup and update code fields that may contain commands (usually
containing plot or plotxy). These commands are run automatically triggered by other commands in
NetLogo.
Plot setup commands and pen setup commands are run when the eitherreset-ticks or setup-plots
commands are run. If the stop command is run in the body of the plot setup commands then the pen
setup commands will not run.
Plot update commands and pen update commands are run when the eitherreset-ticks, tick or
update-plots commands are run. If the stop command is run in the body of the plot update commands
then the pen update commands will not run.
Here are the four commands that trigger plotting explained in more detail.
executes commands for one plot at a time. For each plot, the plot’s setup commands
are executed. If the stop command is not encountered while running those commands, then each
of the plot’s pens will have their setup code executed.
update-plots is very similar to setup-plots. For each plot, the plot’s update commands are
executed. If the stop command is not encountered while running those commands, then each of
the plot’s pens will have their update code executed.
tick is exactly the same as update-plots except that the tick counter is incremented before the
plot commands are executed.
reset-ticks first resets the tick counter to 0, and then does the equivalent ofsetup-plots followed
by update-plots .
setup-plots

A typical model will use reset-ticks and tick like so:
to setup
clear-all
...
reset-ticks
end

to go
...
tick
end

Note that in this example we plot from both thesetup and go procedures (because reset-ticks runs plot
setup and plot update commands). We do this because we want our plot to include the initial state of the
system at the end of setup. We plot at the end of thego procedure, not the beginning, because we want
the plot always to be up to date after the go button stops.
Models that don’t use ticks but still want to do plotting will instead use setup-plots and update-plots . In
the previous code, replace reset-ticks with setup-plots update-plots and replace tick with updateplots.
Code Example: Plotting Example

Other kinds of plots
By default, NetLogo plot pens plot in line mode, so that the points you plot are connected by a line.
If you want to move the pen without plotting, you can use theplot-pen-up command. After this
command is issued, the plot and plotxy commands move the pen but do not actually draw anything.
Once the pen is where you want it, use plot-pen-down to put the pen back down.
If you want to plot individual points instead of lines, or you want to draw bars instead of lines or points,
you need to change the plot pen’s “mode”. Three modes are available: line, bar, and point. Line is the
default mode.
Normally, you change a pen’s mode by editing the plot. This changes the pen’s default mode. It’s also
possible to change the pen’s mode temporarily using the set-plot-pen-mode command. That command
takes a number as input: 0 for line, 1 for bar, 2 for point.

Histograms
A histogram is a special kind of plot that measures how frequently certain values, or values in certain
ranges, occur in a collection of numbers that arise in your model.
For example, suppose the turtles in your model have an age variable. You could create a histogram of
the distribution of ages among your turtles with the histogram command, like this:
histogram [age] of turtles

The numbers you want to histogram don’t have to come from an agentset; they could be any list of
numbers.
Note that using the histogram command doesn’t automatically switch the current plot pen to bar mode. If
you want bars, you have to set the plot pen to bar mode yourself. (As we said before, you can change a
pen’s default mode by editing the plot in the Interface tab.)
Like other types of plots, histograms can be set to auto scale. However, auto scaled histograms do not
automatically resize themselves horizontally like other plot types do. To set the range programmatically,
you can use the set-plot-x-range primitive.
The width of the bars in a histogram is controlled by the plot pen’s interval. You can set a plot pen’s
default interval by editing the plot in the Interface tab. You can also change the interval temporarily with
the set-plot-pen-interval command or the set-histogram-num-bars. If you use the latter command,
NetLogo will set the interval appropriately so as to fit the specified number of bars within the plot’s
current x range.

Code Example: Histogram Example

Clearing and resetting
You can clear the current plot with the clear-plot command, or clear every plot in your model with
clear-all-plots. The clear-all command also clears all plots, in addition to clearing everything else in
your model.
If you want to remove only the points that a particular pen has drawn, useplot-pen-reset.
When a whole plot is cleared, or when a pen is reset, that doesn’t just remove the data that has been
plotted. It also restores the plot or pen to its default settings, as they were specified in the Interface tab
when the plot was created or last edited. Therefore, the effects of such commands as set-plotbackground-color, set-plot-x-range and set-plot-pen-color are only temporary.

Ranges and auto scaling
The default x and y ranges for a plot are fixed numbers, but they can be changed at setup time or as the
model runs.
To change the ranges at any time, use set-plot-x-range and set-plot-y-range. Or, you can let the
ranges grow automatically. Either way, when the plot is cleared the ranges will return to their default
values.
By default, all NetLogo plots have the auto scaling feature enabled. This means that if the model tries to
plot a point which is outside the current displayed range, the range of the plot will grow along one or
both axes so that the new point is visible. Histogram plots, however, do not auto scale horizontally.
In the hope that the ranges won’t have to change every time a new point is added, when the ranges
grow they leave some extra room: 25% if growing horizontally, 10% if growing vertically.
If you want to turn off this feature, edit the plot and uncheck the “Auto Scale?” checkbox. At present, it is
not possible to enable or disable this feature only on one axis; it always applies to both axes.

Using a Legend
You can show the legend of a plot by checking the “Show legend” checkbox in the edit dialog. If you
don’t want a particular pen to show up in the legend you can uncheck the “Show in Legend” checkbox
for that pen also in the advanced plot pen settings (the advanced plot pen settings can be opened by
clicking the pencil button for that pen in the plot pens table in the plot edit dialog).

Temporary plot pens
Most plots can get along with a fixed number of pens. But some plots have more complex needs; they
may need to have the number of pens vary depending on conditions. In such cases, you can make
“temporary” plot pens from code and then plot with them. These pens are called “temporary” because
they vanish when the plot is cleared (by the clear-plot, clear-all-plots, or clear-all commands).
To create a temporary plot pen, use the create-temporary-plot-pen command. Typically, this would be
done in the Code tab, but it is also possible to use this command from plot setup or plot update code (in
the edit dialog). By default, the new pen is down, is black in color, has an interval of 1, and plots in line
mode. Commands are available to change all of these settings; see the Plotting section of the NetLogo
Dictionary.
Before you can use the pen, you’ll have to use the use theset-current-plot and set-current-plot-pen
commands. These are explained in the next section.

set-current-plot and set-current-plot-pen

Before NetLogo 5, it was not possible to put plot commands in the plot itself. All of the plot code was
written in the Code tab with the rest of the code. For backwards compatibility, and for temporary plot
pens, this is still supported. Models in previous versions of NetLogo (and those using temporary plot
pens) have to explicitly state which plot is the current plot with the set-current-plot command and
which pen is the current pen with the set-current-plot-pen command.
To set the current plot use the set-current-plot command with the name of the plot enclosed in double
quotes, like this:
set-current-plot "Distance vs. Time"

The name of the plot must be exactly as you typed it when you created the plot. Note that later if you
change the name of the plot, you’ll also have to update the set-current-plot calls in your model to use
the new name. (Copy and paste can be helpful here.)
For a plot with multiple pens, you can manually specify which pen you want to plot with. If you don’t
specify a pen, plotting will take place with the first pen in the plot. To plot with a different pen, the setcurrent-plot-pen command was used with the name of the pen enclosed in double quotes, like this:
set-current-plot-pen "distance"

Once the current pen is set, then commands like plot count turtles can be executed for that pen.
Older models with plots usually had their own do-plotting procedure that looked something like this:
to do-plotting
set-current-plot "populations"
set-current-plot-pen "sheep"
plot count sheep
set-current-plot-pen "wolves"
plot count wolves
set-current-plot "next plot"
...
end

Once again, this is no longer necessary in NetLogo 5, unless you are using temporary plot pens.

Conclusion
Not every aspect of NetLogo’s plotting system has been explained here. See the Plotting section of the
NetLogo Dictionary for information on additional commands and reporters related to plotting.
Many of the Sample Models in the Models Library illustrate various advanced plotting techniques. Also
check out the following code examples:
Code Examples: Plot Axis Example, Plot Smoothing Example, Rolling Plot Example

Strings
Strings may contain any Unicode characters.
To input a constant string in NetLogo, surround it with double quotes.
The empty string is written by putting nothing between the quotes, like this:"".
Most of the list primitives work on strings as well:
but-first "string" => "tring"

but-last "string" => "strin"
empty? "" => true
empty? "string" => false
first "string" => "s"
item 2 "string" => "r"
last "string" => "g"
length "string" => 6
member? "s" "string" => true
member? "rin" "string" => true
member? "ron" "string" => false
position "s" "string" => 0
position "rin" "string" => 2
position "ron" "string" => false
remove "r" "string" => "sting"
remove "s" "strings" => "tring"
replace-item 3 "string" "o" => "strong"
reverse "string" => "gnirts"

A few primitives are specific to strings, such as is-string?, substring, and word:
is-string? "string" => true
is-string? 37 => false
substring "string" 2 5 => "rin"
word "tur" "tle" => "turtle"

Strings can be compared using the =, !=, <, >, <=, and >= operators.
If you need to embed a special character in a string, use the following escape sequences:
\n
\t
\"
\\

= newline
= tab
= double quote
= backslash

Output
This section is about output to the screen. Output to the screen can also be later saved to a file using
the export-output command. If you need a more flexible method of writing data to external files, see the
next section, File I/O.
The basic commands for generating output to the screen in NetLogo areprint, show, type, and write.
These commands send their output to the Command Center.
For full details on these four commands, see their entries in the NetLogo Dictionary. Here is how they
are typically used:
print is useful in most situations.
show lets you see which agent is printing what.
type lets you print several things on the same line.
write lets you print values in a format which can be

read back in usingfile-read.

A NetLogo model may optionally have an “output area” in its Interface tab, separate from the Command
Center. To send output there instead of the Command Center, use the output-print , output-show,
output-type, and output-write commands.
The output area can be cleared with theclear-output command and saved to a file withexport-output .
The contents of the output area will be saved by the export-world command. The import-world
command will clear the output area and set its contents to the value in imported world file. It should be
noted that large amounts of data being sent to the output area can increase the size of your exported
worlds.
If you use output-print , output-show, output-type, output-write , clear-output , or export-output in a
model which does not have a separate output area, then the commands apply to the output portion of
the Command Center.

How Output Primitives Differ

This information is a quick reference for more advanced users.
The print, show, type, and write primitives differ on the following facets:
What types of values does the primitive accept?
Does the primitive output a newline at the end?
Are strings output with quotes surrounding them?
Does the primitive output the agent which printed it?
The following table summarizes the behavior of each primitive.
Primitive

Acceptable values

Adds
newline?

Strings
quoted?

Outputs
self?

any NetLogo value

yes

show

any NetLogo value

yes

type

any NetLogo value

write

boolean, number, string, lists containing only
these types

yes

File I/O
In NetLogo, there is a set of primitives that give you the power to interact with outside files. They all
begin with the prefix file-.
There are two main modes when dealing with files: reading and writing. The difference is the direction of
the flow of data. When you are reading in information from a file, data that is stored in the file flows into
your model. On the other hand, writing allows data to flow out of your model and into a file.
When working with files, always begin by using the primitivefile-open. This specifies which file you will
be interacting with. None of the other primitives work unless you open a file first.
The next file- primitive you use dictates which mode the file will be in until the file is closed, reading or
writing. To switch modes, close and then reopen the file.
The reading primitives include file-read, file-read-line, file-read-characters, and file-at-end?.
Note that the file must exist already before you can open it for reading.
Code Examples: File Input Example
The primitives for writing are similar to the primitives that print things in the Command Center, except
that the output gets saved to a file. They include file-print, file-show, file-type, and file-write. Note
that you can never “overwrite” data. In other words, if you attempt to write to a file with existing data, all
new data will be appended to the end of the file. (If you want to overwrite a file, use file-delete to
delete it, then open it for writing.)
Code Examples: File Output Example
When you are finished using a file, you can use the commandfile-close to end your session with the
file. If you wish to remove the file afterwards, use the primitive file-delete to delete it. To close multiple
opened files, one needs to first select the file by using file-open before closing it.
;; Open 3
file-open
file-open
file-open

files
"myfile1.txt"
"myfile2.txt"
"myfile3.txt"

;; Now close the 3 files

file-close
file-open "myfile2.txt"
file-close
file-open "myfile1.txt"
file-close

Or, if you know you just want to close every file, you can usefile-close-all.
Two primitives worth noting are file-write and file-read . These primitives are designed to easily save
and retrieve NetLogo constants such as numbers, lists, booleans, and strings. file-write will always
output the variable in such a manner that file-read will be able to interpret it correctly.
file-open "myfile.txt" ;; Opening file for writing
ask turtles
[ file-write xcor file-write ycor ]
file-close
file-open "myfile.txt" ;; Opening file for reading
ask turtles
[ setxy file-read file-read ]
file-close

Code Examples: File Input Example and File Output Example
Letting the user choose
The user-directory, user-file, and user-new-file primitives are useful when you want the user to
choose a file or directory for your code to operate on.

Movies
This section describes how to capture an “.mp4” movie of a NetLogo model.
First, use the vid:start-recorder command to start the video recorder.
To add a frame to your movie, use either vid:record-view or vid:record-interface, depending on
whether you want the movie to show just the current view, or the entire Interface tab. In a single movie,
the resolution will be one of the following:
The resolution specified in the call to vid:start-recorder width height if you specified the
resolution. These are optional parameters.
The resolution of the view if you did not specify a resolution in the call tovid:start-recorder and
call vid:record-view before calling vid:record-interface
The resolution of the interface if you did not specify a resolution in the call tovid:start-recorder
and call vid:record-interface before calling vid:record-view
Note that if the resolution of a recorded image doesn’t match the resolution of the recording it will be
scaled to fit which can result in images which look blurry or out-of-focus.
When you’re done adding frames, use vid:save-recording. The filename you provide should end with
.mp4, the extension for MP4-encoded movies (playable in QuickTime and other programs).
;; export a 30 frame movie of the view
extensions [vid]
;...
setup
vid:start-recorder
vid:record-view ;; show the initial state
repeat 30
[ go
vid:record-view ]
vid:save-recording "out.mp4"

A movie will play back at 25 frames per second. To make the movie playback faster or slower, consider
using a video postprocessing tool.
To check whether or not you are recording, call vid:recorder-status, which reports a string that
describes the state of the current recorder.
To throw away the movie currently being recorded, call vid:reset-recorder.
Code Example: Movie Example
Movies generated when running headless, or by background runs in a parallel BehaviorSpace
experiment may use only vid:record-view primitive. Movies generated in NetLogo GUI may also use
vid:record-interface and vid:record-source .
NetLogo movies are exported as H.264-encoded MP4 files. To play an MP4 movie, you can usethe VLC
Player, a free download from the VideoLAN organization.
Movies can take up a lot of disk space. You will probably want to compress your movies with third-party
software. The software may give you a choice of different kinds of compression. Some kinds of
compression are lossless, while others are lossy. “Lossy” means that in order to make the files smaller,
some of the detail in the movie is lost. Depending on the nature of your model, you may want to avoid
using lossy compression, for example if the view contains fine pixel-level detail.

Perspective
The 2D and the 3D view show the world from the perspective of the observer. By default the observer is
looking down on the world from the positive z-axis at the origin. You can change the perspective of the
observer by using the follow, ride and watch observer commands and follow-me , ride-me and watch-me
turtle commands. When in follow or ride mode the observer moves with the subject agent around the
world. The difference between follow and ride is only visible in the 3D view. In the 3D view the user can
change the distance behind the agent using the mouse. When the observer is following at zero distance
from the agent it is actually riding the agent. When the observer is in watch mode it tracks the
movements of one turtle without moving. In both views you will see a spotlight appear on the subject and
in the 3D view the observer will turn to face the subject. To determine which agent is the focus you can
use the subject reporter.
Code Example: Perspective Example

Drawing
The drawing is a layer where turtles can make visible marks.
In the view, the drawing appears on top of the patches but underneath the turtles. Initially, the drawing is
empty and transparent.
You can see the drawing, but the turtles (and patches) can’t. They can’t sense the drawing or react to it.
The drawing is just for people to look at.
Turtles can draw and erase lines in the drawing using thepen-down and pen-erase commands. When a
turtle’s pen is down (or erasing), the turtle draws (or erases) a line behind it whenever it moves. The
lines are the same color as the turtle. To stop drawing (or erasing), use pen-up.
Lines drawn by turtles are normally one pixel thick. If you want a different thickness, set thepen-size
turtle variable to a different number before drawing (or erasing). In new turtles, the variable is set to 1.
Lines made when a turtle moves in a way that doesn’t fix a direction, such as withsetxy or move-to , the
shortest path line that obeys the topology will be drawn.
Here’s some turtles which have made a drawing over a grid of randomly shaded patches. Notice how

the turtles cover the lines and the lines cover the patch colors. The pen-size used here was 2:

The stamp command lets a turtle leave an image of itself behind in the drawing andstamp-erase lets it
remove the pixels below it in the drawing.
To erase the whole drawing, use the observer commmand clear-drawing . (You can also use clear-all,
which clears everything else too.)
Importing an image
The observer command import-drawing command allows you to import an image file from disk into the
drawing.
is useful only for providing a backdrop for people to look at. If you want turtles and
patches to react to the image, you should use import-pcolors or import-pcolors-rgb instead.
import-drawing

Comparison to other Logos
Drawing works somewhat differently in NetLogo than some other Logos.
Notable differences include:
New turtles’ pens are up, not down.
Instead of using a fence command to confine the turtle inside boundaries, in NetLogo you edit the
world and turn wrapping off.
There is no screen-color , bgcolor , or setbg. You can make a solid background by coloring the
patches, e.g. ask patches [ set pcolor blue ] .
Drawing features not supported by NetLogo:
There is no window command. This is used in some other Logos to let the turtle roam over an
infinite plane.
There is no flood or fill command to fill an enclosed area with color.

Topology
The way the world of patches is connected can change. By default the world is a torus which means it
isn’t bounded, but “wraps” – so when a turtle moves past the edge of the world, it disappears and
reappears on the opposite edge and every patch has the same number of “neighbor” patches. If you’re
a patch on the edge of the world, some of your “neighbors” are on the opposite edge.
However, you can change the wrap settings with the Settings button. If wrapping is not allowed in a
given direction then in that direction (x or y) the world is bounded. Patches along that boundary will have
fewer than 8 neighbors and turtles will not move beyond the edge of the world.
The topology of the NetLogo world has four potential values, torus, box, vertical cylinder, or horizontal
cylinder. The topology is controlled by enabling or disabling wrapping in the x or y directions. The default
world is a torus.

A torus wraps in both directions, meaning that the top and bottom edges of the world are connected and
the left and right edges are connected. So if a turtle moves beyond the right edge of the world it appears
again on the left and the same for the top and bottom.
A box does not wrap in either direction. The world is bounded so turtles that try to move off the edge of
the world cannot. Note that the patches around edge of the world have fewer than eight neighbors; the
corners have three and the rest have five.
Horizontal and vertical cylinders wrap in one direction but not the other. A horizontal cylinder wraps
vertically, so the top of the world is connected to the bottom. but the left and right edges are bounded. A
vertical cylinder is the opposite; it wraps horizontally so the left and right edges are connected, but the
top and bottom edges are bounded.
Code Example: Neighbors Example
When coordinates wrap, turtles and links wrap visually in the view, too. If a turtle shape or link extends
past an edge, part of it will appear at the other edge. (Turtles themselves are points that take up no
space, so they cannot be on both sides of the world at once, but in the view, they appear to take up
space because they have a shape.)
Wrapping also affects how the view looks when you are following a turtle. On a torus, wherever the turtle
goes, you will always see the whole world around it:

Whereas in a box or cylinder the world has edges, so the areas past those edges show up in the view
as gray:

Code Example: Termites Perspective Demo (torus), Ants Perspective Demo (box)
The topology settings also control the behavior of the distance(xy), in-radius, in-cone, face(xy), and
towards(xy) primitives. The topology controls whether the primitives wrap or not. They always use the
shortest path allowed by the topology. For example, the distance from the center of the patches in the
bottom right corner (min-pxcor, min-pycor) and the upper left corner (max-pxcor, max-pycor) will be as
follows for each topology given that the min and max pxcor and pycor are +/-2:
Torus - sqrt(2) ~ 1.414 (this will be the same for all world sizes since the patches are directly
diagonal to each other in a torus.)
Box - sqrt(world-width^2 + world-height^2) ~ 7.07
Vertical Cylinder - sqrt(world-height^2 + 1) ~ 5.099
Horizontal Cylinder - sqrt(world-width^2 + 1) ~ 5.099
All the other primitives will act similarly to distance. If you formerly used-nowrap primitives in your model
we recommend removing them and changing the topology of the world instead.
If your model has turtles that move around you’ll need to think about what happens to them when they
reach the edge of the world, if the topology you’re using has some non-wrapping edges. There are a few
common options: the turtle is reflected back into the world (either systematically or randomly), the turtle
exits the system (dies), or the turtle is hidden. It is no longer necessary to check the bounds using turtle
coordinates, instead we can just ask NetLogo if a turtle is at the edge of the world. There are a couple
ways of doing this, the simplest is to use the can-move? primitive.
if not can-move? distance [ rt 180 ]

can-move? merely returns true if the position distance in front of the turtle is inside the NetLogo world,
false otherwise. In this case, if the turtle is at the edge of the world it simple goes back the way it came.
You can also use patch-ahead 1 != nobody in place of can-move?. If you need to do something smarter
that simply turning around it may be useful to use patch-at with dx and dy.
if patch-at dx 0 = nobody [
set heading (- heading)
]
if patch-at 0 dy = nobody [
set heading (180 - heading)
]

This tests whether the turtle is hitting a horizontal or vertical wall and bounces off that wall.
In some models if a turtle can’t move forward it simply dies (exits the system, like in Conductor or
Mousetraps).
if not can-move? distance[ die ]

If you are moving turtles using setxy rather than forward you should test to make sure the patch you are
about to move to exists since setxy throws a runtime error if it is given coordinates outside the world.
This is a common situation when the model is simulating an infinite plane and turtles outside the view
should simply be hidden.
let new-x new-value-of-xcor
let new-y new-value-of-ycor
ifelse patch-at
[ hide-turtle
[ setxy new-x
show-turtle

(new-x - xcor) (new-y - ycor) = nobody
]
new-y
]

Several models in the Models Library use this technique, Gravitation, N-Bodies, and Electrostatics are
good examples.

The diffuse and diffuse4 commands behave correctly in all topologies. Each patch diffuses and equal
amount of the diffuse variable to each of its neighbors, if it has fewer than 8 neighbors (or 4 if you are
using diffuse4), the remainder stays on the diffusing patch. This means that the overall sum of patchvariable across the world remains constant. However, if you want the diffuse matter to still fall off the
edges of the world as it would on an infinite plane you still need to clear the edges each step as in the
Diffuse Off Edges Example.

Links
A link is an agent that connects two turtles. These turtles are sometimes also called nodes.
The link is always drawn as a line between the two turtles. Links do not have a location as turtles do,
they are not considered to be on any patch and you cannot find the distance from a link to another point.
There are two link designations: undirected and directed. A directed link is out of, or from, one node and
into, or to, another node. The relationship of a parent to a child could be modeled as a directed link. An
undirected link appears the same to both nodes, each node has a link with another node. The
relationship between spouses, or siblings, could be modeled as an undirected link.
There is a global agentset of all links, just as with turtles and patches. You can create undirected links
using the create-link-with and create-links-with commands; and directed links using the createlink-to , create-links-to , create-link-from, and create-links-from commands. Once the first link has
been created directed or undirected, all unbreeded links must match (links also support breeds, much
like turtles, which will be discussed shortly); it’s impossible to have two unbreeded links where one is
directed and the other is undirected. A runtime error occurs if you try to do it. (If all unbreeded links die,
then you can create links of that breed that are different in designation from the previous links.)
In general, link primitive names indicate what kind of links they deal with:
Primitives that have “out” in their name utilize outgoing and undirected links. You can think of these
as “the links I can use to get from the current node to other nodes.” In general, these are probably
the primitives you want to use.
Primitives that have “in” in their name utilize incoming and undirected links. You can think of these
as “the links I can use to get to the current node from other nodes.”
Primtives that do not specify “in” or “out”, or have “with” in their name utilizeall links, both
undirected and directed, incoming and outgoing.
A link’s end1 and end2 variables contain the two turtles the link connects. If the link is directed, it goes
from end1 to end2. If the link is undirected, end1 is always the older of the two turtles, that is, the turtle
with the smaller who number.
Link breeds, like turtle breeds, allow you to define different types of links in your model. Link breeds
must either be directed or undirected, unlike unbreeded links this is defined at compile time rather than
run time. You declare link breeds using the keywords undirected-link-breed and directed-link-breed.
Breeded links can be created using the commands create--with and create--with for
undirected breeds and the commands create--to , create--to , create--from,
and create--from for directed links.
There cannot be more than one undirected link of the same breed (or more than one unbreeded
undirected link) between a pair of agents, nor more than one directed link of the same breed in the
same direction between a pair of agents. You can have two directed links of the same breed (or two
unbreeded directed links) between a pair if they are in opposite directions.
Layouts
As part of our network support we have also added several different primitives that will help you to
visualize the networks. The simplest is layout-circle which evenly spaces the agents around the center
of the world given a radius.

is a good layout if you have something like a tree structure, though even if there are some
cycles in the tree it will still work, though as there are more and more cycles it will probably not look as
good. layout-radial takes a root agent to be the central node places it at (0,0) and arranges the nodes
connected to it in a concentric pattern. Nodes one degree away from the root will be arranged in a
circular pattern around the central node and the next level around those nodes and so on. layoutradial will attempt to account for asymmetrical graphs and give more space to branches that are wider.
layout-radial also takes a breed as an input so you use one breed of links to layout the network and
not another.
layout-radial

Given a set of anchor nodes layout-tutte places all the other nodes at the center of mass of the nodes
it is linked to. The anchor set is automatically arranged in a circle layout with a user defined radius and
the other nodes will converge into place (this of course means that you may have to run it several times
before the layout is stable.)

is useful for many kinds of networks. The drawback is that is relatively slow since it takes
many iterations to converge. In this layout the links act as springs that pull the nodes they connect
toward each other and the nodes repel each other. The strength of the forces is controlled by inputs to
the primitives. These inputs will always have a value between 0 and 1; keep in mind that very small
changes can still affect the appearance of the network. The springs also have a length (in patch units),
layout-spring

however, because of all the forces involved the nodes will not end up exactly that distance from each
other.
**Code Examples:**Network Example, Network Import Example, Giant Component, Small
Worlds, Preferential Attachment

Anonymous procedures
Anonymous procedures let you store code to be run later. Just like regular NetLogo procedures, an
anonymous procedures can be either a command (anonymous command) or a reporter (anonymous
reporter).
Anonymous procedures are values, which means they may be passed as input, reported as a result, or
stored in a variable.
An anonymous procedure might be run once, multiple times, or not at all.
In other programming languages anonymous procedures are known as first-class functions, closures, or
lambda.

Anonymous procedure primitives
Primitives specific to anonymous procedures are ->, is-anonymous-command?, and is-anonymousreporter?.
The -> creates an anonymous procedure. The anonymous procedure it reports might be a command or
a reporter, depending on what kind of block you pass it. For example [ -> fd 1 ] reports an
anonymous command, because fd is a command, while [ -> count turtles ] reports an anonymous
reporter, because count is a reporter.
These primitives require anonymous procedures as input: foreach , map, reduce, filter, n-values , sortby . When calling these primitives, using an -> is optional if your anonymous procedure contains a single
primitive which has requires no more inputs than are are provided by the primitive. For example one
may write simply foreach mylist print instead of foreach mylist [ [x] -> print x ] , though the
latter is also accepted. Depending on the anonymous procedure, various parts of the anonymous
procedure syntax can be omitted. For a summary of optional syntax, see the table below.
The run command accepts anonymous commands as well as strings.
The runresult reporter accepts anonymous reporters as well as strings.
and runresult allow passing inputs to an anonymous procedure. As with all primitives accepting
varying number of inputs, the whole call must be surrounded with parentheses, so for example (run myanonymous-command 5) or (runresult my-anonymous-reporter "foo" 2). When not passing input, no
parentheses are required.
run

Anonymous procedure inputs
An anonymous procedure may take zero or more inputs. The inputs are referenced the variables
declared before the arrow. For instance, in the anonymous reporter [ [a b] -> a + b ] , a and b are
inputs.

Anonymous procedures and strings
Creating and running anonymous procedures is fast. To use run or runresult on a new string for the first
time is about 100x slower than running an anonymous procedure. Modelers should normally use
anonymous procedures instead of running strings, except when running strings entered by the user.

Concise syntax
Simple uses of foreach , map, reduce, filter, n-values , and sort-by can be written with an especially
concise syntax. You can write:
map abs [1 -2 3 -4]
;; => [1 2 3 4]
reduce + [1 2 3 4]
;; => 10
filter is-number? [1 "x" 3]
;; => [1 3]
foreach [1 2 3 4] print
;; prints 1 through 4

In older NetLogo versions (4 and earlier), these had to be written:
map [abs ?] [1 -2 3 -4]
;; => [1 2 3 4]
reduce [?1 + ?2] [1 2 3 4]
;; => 10
filter [is-number? ?] [1 "x" 3]
;; => [1 3]
foreach [1 2 3 4] [ print ? ]
;; prints 1 through 4

Anonymous procedures as closures
Anonymous procedures are “closures”; that means they capture or “close over” the bindings (not just the
current values) of local variables and procedure inputs. They do not capture agent variables and do not
capture the identity (or even the agent type) of the current agent.

Nonlocal exits
The stop and report commands exit from the dynamically enclosing procedure, not the enclosing
anonymous procedure. (This is backward-compatible with older NetLogo versions.)

Anonymous procedures and extensions
The extensions API supports writing primitives that accept anonymous procedures as input. Write us for
sample code.

Limitations
We hope to address at least some of the following limitations in future NetLogo versions:
does not support anonymous procedures.
Anonymous procedures can’t be variadic (accept a varying number of inputs).
Anonymous reporters can’t contain commands, only a single reporter expression. So for example
you must use ifelse-value not if, and you don’t use report at all. If your code is too complex to
be written as one reporter, you’ll need to move the code to a separate reporter procedure, and
then call that procedure from your anonymous reporter, passing it any needed inputs.
Anonymous procedures are not interchangeable with command blocks and reporter blocks. Only
the primitives listed above accept anonymous procedures as input. Control primitives such as
ifelse and while and agent primitives such as of and with don’t accept anonymous procedures.
So for example if I have an anonymous reporter let r [ -> if random 2 == 0 ] and two
anonymous commands let c1 [ -> tick ] and let c2 [ -> stop ] , I can’t write ifelse r c1 c2 ,
I must write ifelse runresult r [ run c1 ] [ run c2 ] .
The concise syntax where -> may be omitted is only available to primitives and extension
primitives, not ordinary procedures. So for example if I have a procedure p that accepts an
anonymous procedure as input, it must be called as e.g. p [ -> ... ] not p [ ... ] .
import-world

What is Optional?
There are several different ways of writing anonymous procedures which allow users to omit part or all
of the anonymous procedure syntax. These are summarized in the table below.
What is the anonymous
procedure like?

What can be left
out?

Examples

The anonymous procedure
is a single primitive

input names
arrow
block
brackets

foreach mylist stamp ; no inputs
foreach mylist print ; single input
(foreach xs ys setxy) ; multiple
inputs
map round [1.3 2.4 3.5] ; reporter,
single input
(map + [1 2 3] [4 5 6]) ; reporter,
multiple inputs

The anonymous procedure
takes no inputs

input names
arrow

foreach mylist [ print "abc" ]
map [ 4 ] mylist

brackets
around input
names

foreach mylist [ -> stamp ] ; no
inputs
foreach mylist [ x -> print x ] ;
single input
foreach mylist [ x -> rt x fd x ] ;
multiple primitives, single input
map [ -> world-width ] mylist ;
reporter, no inputs
map [ x -> x ^ 2 ] mylist ; reporter,
single input

nothing

(foreach xs ys [ [ x y ] -> setx x +
y ])
(map [ [ x y ] -> x mod round y ] xs
ys)

The anonymous procedure
has zero or one input(s)

Anonymous procedure takes
more than one input

Note: brackets around input names were always required in NetLogo 6.0.0. If you copy and paste code
into NetLogo 6.0.0 using anonymous procedures with unbracketed input names, the code will not
compile until you add the brackets.

Code example
Code Example: State Machine Example

Ask-Concurrent
NOTE: The following information is included only for backwards compatibility. We don’t recommend
using the ask-concurrent primitive at all in new models.
In very old versions of NetLogo, ask had simulated concurrent behavior by default. Since NetLogo 4.0
(2007), ask is serial, that is, the agents run the commands inside the ask one at a time.
The following information describes the behavior of theask-concurrent command, which behaves the

way the old ask behaved.
produces simulated concurrency via a mechanism of turn-taking. The first agent takes a
turn, then the second agent takes a turn, and so on until every agent in the asked agentset has had a
turn. Then we go back to the first agent. This continues until all of the agents have finished running all of
the commands.
ask-concurrent

An agent’s “turn” ends when it performs an action that affects the state of the world, such as moving, or
creating a turtle, or changing the value of a global, turtle, patch, or link variable. (Setting a local variable
doesn’t count.)
The forward (fd) and back (bk) commands are treated specially. When used inside ask-concurrent,
these commands can take multiple turns to execute. During its turn, the turtle can only move by one
step. Thus, for example, fd 20 is equivalent to repeat 20 [ fd 1 ] , where the turtle’s turn ends after
each run of fd. If the distance specified isn’t an integer, the last fraction of step takes a full turn. So for
example fd 20.3 is equivalent to repeat 20 [ fd 1 ] fd 0.3 .
The jump command always takes exactly one turn, regardless of distance.
To understand the difference between ask and ask-concurrent, consider the following two commands:
ask turtles [ fd 5 ]
ask-concurrent turtles [ fd 5 ]

With ask, the first turtle takes five steps forward, then the second turtle takes five steps forward, and so
on.
With ask-concurrent, all of the turtles take one step forward. Then they all take a second step, and so
on. Thus, the latter command is equivalent to:
repeat 5 [ ask turtles [ fd 1 ] ]

Code Example: Ask-Concurrent Example shows the difference betweenask and askconcurrent.
The behavior of ask-concurrent cannot always be so simply reproduced using ask, as in this example.
Consider this command:
ask-concurrent turtles [ fd random 10 ]

In order to get the same behavior usingask, we would have to write:
turtles-own [steps]
ask turtles [ set steps random 10 ]
while [any? turtles with [steps > 0]] [
ask turtles with [steps > 0] [
fd 1
set steps steps - 1
]
]

To prolong an agent’s “turn”, use the without-interruption command. (The command blocks inside
some commands, such as create-turtles and hatch, have an implied without-interruption around
them.)
Note that the behavior of ask-concurrent is completely deterministic. Given the same code and the
same initial conditions, the same thing will always happen (if you are using the same version of NetLogo
and begin your model run with the same random seed).
In general, we suggest you not use ask-concurrent at all. If you do, we suggest you write your model so

that it does not depend on the exact details of how ask-concurrent works. We make no guarantees that
its semantics will remain the same in future versions of NetLogo, or that it will continue to be supported
at all.

User Interaction Primitives
NetLogo features several primitives which allow a model to interact with the user. These primitives
include user-directory, user-file, user-new-file, user-input, user-message, user-one-of, and user-yes-orno?.
These primitives differ in precisely what interaction they take with the user.user-directory, user-file,
and user-new-file are all reporters which prompt the user to select an item from the file system and
report the path of the selected item to NetLogo. user-yes-or-no?, user-one-of, and user-input all
prompt the user to provide input in the form of text or a selection. user-message simply presents a
message to the user.
Note that all active forever buttons will pause when one of these primitives is used and will resume only
when the user completes the interaction with the button.

What does “Halt” mean?
The primitives which prompt the user for input, as well as user-message all provide a “Halt” button. The
effect of this button is the same for all of these primitives - it halts the model. When the model is halted
all running code is stopped, including buttons and the command center. Since halting stops code in the
middle of whatever it happened to be doing at the time it was halted, you may see strange results if you
continue to run the model after a halt without setting it up again.

Tie
Tie connects two turtles so that the movement of one turtles affects the location and heading of another.
Tie is a property of links so there must be a link between two turtles to create a tie relationship.
When a link’s tie-mode is set to “fixed” or “free”end1 and end2 are tied together. If the link is directed
end1 is the “root agent” and end2 is the “leaf agent”. That is when end1 moves (using fd , jump, setxy, etc.)
end2 also moves the same distance and direction. However whenend2 moves it does not affect end1.
If the link is undirected it is a reciprocal tie relationship, meaning, if either turtle moves the other turtle
will also move. So depending on which turtle is moving either turtle can be considered the root or the
leaf. The root turtle is always the turtle that initiates the movement.
When the root turtle turns right or left, the leaf turtle rotates around the root turtle the same amount as if
a stiff were attaching the turtles. When tie-mode is set to “fixed” the heading of the leaf turtle changes by
the same amount. If the tie-mode is set to “free” the heading of the leaf turtle is unchanged.
The tie-mode of a link can be set to “fixed” using thetie command and set to “none” (meaning the
turtles are no longer tied) using untie to set the mode to “free” you need to:set tie-mode "free".
Code Example: Tie System Example

Multiple source files
The __includes keyword allows you to use multiple source files in a single NetLogo model.
The keyword begins with two underscores to indicate that the feature is experimental and may change
in future NetLogo releases.
When you open a model that uses the __includes keyword, or if you add it to the top of a model and hit
the Check button, the includes menu will appear in the toolbar. From the includes menu you can select
from the files included in this model.

When you open included files they appear in additional tabs. See theInterface Guide for more details.
You can have anything in external source files (.nls) that you would normally put in the Code tab:
globals , breed, turtles-own, patches-own, breeds-own, procedure definitions, etc. Note though that these
declarations all share the same namespace. That is, if you declare a global my-global in the Code tab
you cannot declare a global (or anything else) with the name my-global in any file that is included in the
model. my-global will be accessible from all the included files. The same would be true ifmy-global were
declared in one of the included files.

Syntax
Colors
In the Code tab and elsewhere in the NetLogo user interface, program code is color-coded by the
following scheme:
Keywords are green
Constants are orange
Comments are gray
Primitive commands are blue
Primitive reporters are purple
Everything else is black

Notice
The remainder of this section contains technical terminology which will be unfamiliar to some readers.

Keywords
The only keywords in the language are globals , breed, turtles-own, patches-own, to, to-report, and end,
plus extensions and the experimental __includes keyword. (Built-in primitive names may not be
shadowed or redefined, so they are effectively a kind of keyword as well.)

Identifiers
All primitives, global and agent variable names, and procedure names share a single global caseinsensitive namespace; local names (let variables and the names of procedure inputs) may not shadow
global names or each other. Identifiers may contain any Unicode letter or digit and the following ASCII
characters:
.?=*!<>:#+/%$_^'&-

Some primitive names begin with two underscores to indicate that they are experimental and are
especially likely to change or be removed in future NetLogo releases.

Scope
NetLogo is lexically scoped. Local variables (including inputs to procedures) are accessible within the
block of commands in which they are declared, but not accessible by procedures called by those
commands.

Comments
The semicolon character introduces a comment, which lasts until the end of the line. There is no multiline comment syntax.

Structure
A program consists of optional declarations (globals , breed, turtles-own, patches-own, -own,
extensions) in any order, followed by zero or more procedure definitions. Multiple breeds may be
declared with separate breed declarations; the other declarations may appear once only.
Every procedure definition begins with to or to-report, the procedure name, and an optional bracketed
list of input names. Every procedure definition ends with end. In between are zero or more commands.

Commands and reporters
Commands take zero or more inputs; the inputs are reporters, which may also take zero or more inputs.
No punctuation separates or terminates commands; no punctuation separates inputs. Identifiers must be
separated by whitespace or by parentheses or square brackets. (So for example, a+b is a single
identifier, but a(b[c]d)e contains five identifiers.)
All commands are prefix. All user-defined reporters are prefix. Most primitive reporters are prefix, but
some (arithmetic operators, boolean operators, and some agentset operators like with and in-points) are
infix.
All commands and reporters, both primitive and user-defined, take a fixed number of inputs by default.
(That’s why the language can be parsed though there is no punctuation to separate or terminate
commands and/or inputs.) Some primitives are variadic, that is, may optionally take a different number
of inputs than the default; parentheses are used to indicate this, e.g. (list 1 2 3) (since the list
primitive only takes two inputs by default). Parentheses are also used to override the default operator
precedence, e.g. (1 + 2) * 3 , as in other programming languages.
Sometimes an input to a primitive is a command block (zero or more commands inside square brackets)
or a reporter block (a single reporter expression inside square brackets). User-defined procedures may
not take a command or reporter block as input.
Operator precedences are as follows, high to low:
with, at-points, in-radius, in-cone

(all other primitives and user-defined procedures)
^
*, /, mod
+, <, >, <= , >=
=, !=
and, or , xor

Compared to other Logos
There is no agreed-upon standard definition of Logo; it is a loose family of languages. We believe that
NetLogo has enough in common with other Logos to earn the Logo name. Still, NetLogo differs in some
respects from most other Logos. The most important differences are as follows.

Surface differences
The precedence of mathematical operators is different. Infix math operators (like +, *, etc.) have
lower precedence than reporters with names. For example, in many Logos, if you write sin x + 1 ,
it will be interpreted as sin (x + 1) . NetLogo, on the other hand, interprets it the way most other
programming languages would, and the way the same expression would be interpreted in
standard mathematical notation, namely as (sin x) + 1 .
The and and or reporters are special forms, not ordinary functions, and they “short circuit”, that is,
they only evaluate their second input if necessary.
Procedures can only be defined in the Code tab, not interactively in the Command Center.
Reporter procedures, that is, procedures that “report” (return) a value, must be defined withtoreport instead of to . The command to report a value from a reporter procedure isreport, not

output.

When defining a procedure, the inputs to the procedure must be enclosed in square brackets, e.g.
to square [x] .
Variable names are always used without any punctuation: always foo, never :foo or "foo. (To
make this work, instead of a make command taking a quoted argument we supply a set special
form which does not evaluate its first input.) As a result, procedures and variables occupy a single
shared namespace.
The last three differences are illustrated in the following procedure definitions:
most Logos
to square :x
output :x * :x
end

NetLogo
to-report square [x]
report x * x
end

Deeper differences
NetLogo’s local variables and inputs to procedures are lexically scoped, not dynamically scoped.
NetLogo has no “word” data type (what Lisp calls “symbols”). Eventually, we may add one, but
since it is seldom requested, it may be that the need doesn’t arise much in agent-based modeling.
We do have strings. In most situations where traditional Logo would use words, we simply use
strings instead. For example in Logo you could write [see spot run] (a list of words), but in
NetLogo you must write "see spot run" (a string) or ["see" "spot" "run"] (a list of strings)
instead.
NetLogo’s run command works on anonymous procedures and strings, not lists (since we have no
“word” data type), and does not permit the definition or redefinition of procedures.
Control structures such as if and while are special forms, not ordinary functions. You can’t define
your own special forms, so you can’t define your own control structures. (You can do something
similar using anonymous procedures, but you must use the ->, run, and runresult primitives for
that, you cannot make them implicit.)
Anonymous procedures (aka function values or lambda) are true lexically-scoped closures. This
feature is available in NetLogo and in modern Lisps, but not in standard Logo.
Of course, the NetLogo language also contains other features not found in most Logos, most importantly
agents and agentsets.

Transition Guide
NetLogo 6.0.4 User Manual

Many models created in earlier versions of NetLogo also work in NetLogo 5.0. However,
some models will need changes. If an old model isn’t working, this section of the User Manual
may be able to help you.
What issues may arise depends on what version of NetLogo the model was created with.
This guide only covers changes most likely to cause issues for users. See therelease notes
for more complete details on differences between versions.

Changes for NetLogo 6.0.3
Arduino Extension Changes
The arduino extension has substantially changed the way it receives values from Arduino
boards. Please consult the arduino example sketch (included within the “models” folder under
Chapter 8 of the IABM textbook) for an updated sketch compatible with the Arduino example
model. If you have an existing arduino sketch, you will need to adjust the format used to send
values to NetLogo. Old sketches will have code which sends back messages like “;A,2.5;”. For
the new version of the arduino extension to receive the same message, sketches should
send “;A,D,2.5;” instead. The added ‘D,’ informs Netlogo that the value being sent is a
number and not a string.

CF Extension Changes
All primitives have been removed from the cf extension and replaced by the cf:ifelse and
cf:ifelse-value multi-branch primitives. We encourage existing cf users to adjust their code
to use these new primitives. Over time, we hope to use these primitives as an example on
which to remodel NetLogo’s existing ifelse and ifelse-value primitives. Because this would
be a relatively large language change, we would love to hear any feedback address you may
have from using these cf extension primitives.

Changes for NetLogo 6.0
Tasks replaced by Anonymous Procedures
In NetLogo 6.0, tasks have been replaced by anonymous procedures. This means thattask is
no longer a primitive, it’s been replaced by the new arrow syntax for creating anonymous
procedures. Similarly, question mark variables like ?, ?1, and ?2 are now just ordinary names
in NetLogo and can be used to name procedure variables, let variables, or anonymous
procedure variables. Finally, is-reporter-task? and is-command-task? have been replaced by
is-anonymous-reporter? and is-anonymous-command?.
To make this transition easier, we’ve added an automatic conversion step which should allow
most models saved in NetLogo 5 to be converted to use the new syntax automatically. The
autoconverter has been a substantial piece of effort and we’ve tested it on all the models in
the models library. To use it, ensure the model compiles and run properly in NetLogo 5 or
later, then save it from NetLogo 5 or later. Then, simply open the model in NetLogo 6. If all
goes well, you’ll see the converter has changed code like task [?1 + ?2] to [ [?1 ?2] -> ?1

+ ?2 ].

The question marks are meant to serve as temporary placeholders for conversion.
They enable your model to run, but you can (and should) replace these variables with
meaningful names. If you open a model with tasks and it has not been converted, the
autoconverter wasn’t able to convert your model. Rather than attempt to autoconvert your
model and break something, the model will open, you will be shown the appropriate errors
and given a chance to edit your model.
While we have tested the autoconverter thoroughly, we expect there to be some cases it
doesn’t cover.
If you make use of extensions that aren’t yet compiled for NetLogo 6, the autoconverter
will not work until those extensions have been updated.
If your code uses run or runresult to evaluate strings containing tasks, the
autoconverter will not change those strings to be anonymous procedures. To make run
and runresult work as expected, look at strings in your model and change any which
rely on task or ?-variables to instead rely on anonymous procedures
If your model doesn’t fall into the above categories and doesn’t convert or converts
incorrectly, please email our feedback address and we’ll be happy to offer whatever
assistance we can.

Link reporters overhauled to be more consistent and flexible
In previous versions of NetLogo, link reporters have had a number of inconsistencies
regarding directed and undirected links. For example, my-links would report all links
connected to a turtle, whereas link-neighbors would only report neighbors connected by
undirected links. Furthermore, it was quite difficult to work with models where the links could
either be directed or undirected.
To alleviate these issues, the link primitives have been overhauled in 6.0. These changes
only affect existing models that use both directed and undirected links while also using the
unbreeded link primitives.
The changes are as follows:
Link reporters that contain the word “out” now utilize both directed, outgoing links and
undirected links. That is, they now specify links that can be used to get from the current
node to other nodes. For example, out-link-neighbor? will report true if the current
turtle is connected to the given turtle by either an outgoing directed link or an undirected
link. If you only want directed, outgoing links, you can use a breed-specific reporter or
my-out-links with [ is-directed? self ]. Generally, when working with models that
have both directed and undirected links, you will probably want to use the “out”
primitives for most things now.
Link reporters that contain the word “in” now utilize both directed, incoming links and
undirected links. That is, they now specify links that can be used to get to the current
node from other nodes. For example, in-link-neighbor? will report true if the current
turtle is connected to the given turtle by either an incoming directed link or an undirected
link. If you only want directed, incoming links, you can use a breed-specific reporter or
my-in-links with [ is-directed? self ].
Link reporters that do not specify “out” or “in” utilizeall links.
Furthermore, there are no longer restrictions regarding which reporters can be used with
which breeds. For unbreeded links, this makes it possible to use the same primitives
regardless of whether your network ends up being directed or undirected.
The new behavior (including all changed primitives) is summarized by the following table,

where “un” refers to undirected links, “out” refers to directed, outgoing links, and “in” refers to
directed, incoming links.
New link reporter behavior

Old link reporter behavior

Removal of Applets

Oracle, the company behind Java, has announced that Java applets are deprecated (seethis
blog post for more information). This comes as the major browsers have removed support for
plug-ins (like java applets) or announced that they plan to do so.
Instead of using applets to distribute your model, NetLogo offers the option to export to
NetLogo Web. While NetLogo Web doesn’t yet offer the full functionality of desktop NetLogo
(in particular, extensions aren’t supported), it is now capable of running most of the models in
the NetLogo models library and we hope that most model distributors will find that it meets
their needs. To export to NetLogo Web, choose the “Save As NetLogo Web” option from the
“File” menu.

Changes to the NetLogo User Interface
Users will notice several tweaks to the NetLogo User interface when opening NetLogo 6 for
the first time. We’ve removed the bar border above the view. To open the 3D View in 6.0, you
can right click on the view and choose “Switch to 3D View”, or choose the same option from
the “Tools” menu. Ticks are now displayed in the interface tab toolbar beneath the speed
slider. To adjust the label used for “ticks” and other view properties, you can choose the
“Settings” button at the far right of the interface tab toolbar or right-click on the view and
choose “Edit…” from the context menu that appears.

Nobody Not Permitted as a Chooser Value
In NetLogo 6.0, nobody is no longer a valid chooser value. Just as you can’t putturtle 0 or
turtles , nobody refers to a non-literal value which isn’t supported in choosers. As part of this
transition, choosers containing nobody (or nobody within a nested list) will have all uses of
nobody changed to "nobody" when opened in NetLogo 6.0.

Breeds must have singular and plural names
In NetLogo 6.0, you must specify both plural and singular breed names. In prior versions,
declarations like breed [mice] were legal, but this support has been removed in 6.0. If you
have models which use only plural breed names, it is recommended that you convert them to
specify both names before opening in 6.0 since doing so will permit the NetLogo converter to
work most effectively on any other code in your model which needs conversion.

Removal of “Movie” Prims
The NetLogo movie prims hadn’t been updated in quite some time and generated invalid
quicktime movie files. They have been replaced by prims in the new vid extension. The full
documentation for the vid extension is available in the Vid Extension section of the manual.
As with all extensions, users will need to include vid in the extensions section of their
NetLogo model.
Many of the movie primitives have direct parallels in thevid extension which can be found in
the following table:
movie prim

vid prim

movie-cancel

vid:reset-recorder

movie-close

vid:save-recording *file-name*

movie-grab-view

vid:record-view

movie-grab-interface

vid:record-interface

movie prim

vid prim

movie-start *file-name* vid:start-recorder *optional-width* *optional-height*
movie-status

vid:recorder-status

When you first open a file in NetLogo 6.0, your file will be automatically converted to use the
new primitives. This will include adding a new global variable - _recording-save-file-name to
track the name of the active recording, as well as adding the vid extension to the model. You
should verify that the conversion took place correctly. There is no replacement for movie-setframe-rate. The vid extension records frames at 25 per second, slightly more than the default
15 frames-per-second of the movie prims. If your recording is sensitive to framerate, consider
recording each existing frame twice (2/25 is fairly close to 1/15) or consider using a
postprocessing tool (like gstreamer or ffmpeg) to adjust the video playback speed.

Improved Name Collision Detection
In NetLogo 6.0, expanded error-checking in the NetLogo compiler causes models which
define undirected-link-breed [ undirected-links undirected-link ] and/or directedlink-breed [ directed-links directed-link ] to error for redefining a primitive reporter
(either is-directed-link? or is-undirected-link?). If your model doesn’t use is-directedlink? or is-undirected-link? at all, simply changing the breed names should resolve the
error.
If you used either of the is--link? prim, there are several ways you might
modify your model to account for this change. If your model has no other breeded links,
consider removing the link breed and using the built-in link primitives. If your model has other
breeded links, but only of different directedness, simply changing the breed name (and all
related primitive names) should resolve the problem. Note that in this case is-directed-link?
and/or is-undirected-link? continue to behave the same as before. If your model has other
breeded links of the same directedness, the change will vary depending on your model. The
breed name(s) must be changed, but you must decide whether you used is-directed-link? /
is-undirected-link? to check link directedness or to check that link breed membership. If you
used it to check link directedness leaving it as-is should keep the current behavior of the
model. Otherwise, it can simply be replaced by is-?.

Removal of

hubnet-set-client-interface

The hubnet-set-client-interface primitive was rendered obsolete by the introduction of the
HubNet client editor and end of support for calculator HubNet. We have found it used in very
few models and have decided to remove it from the language. On opening an existing model
in 6.0, the autoconverter should remove all uses of hubnet-set-client-interface from your
code.

Improved & Updated Extensions API
One of our goals in NetLogo 6.0 has been to make it easier to develop extensions and easy
to develop more powerful extensions. To that end, we’ve bumped the extension API from 5.0
to 6.0. Existing extensions will need to recompile changing the “NetLogo-Extension-APIVersion” in their jar’s MANIFEST.MF from 5.0 to 6.0.
Some of the changes we’ve made to the extensions API include:

now allows access to the current world and workspace objects
without requiring a cast to an org.nlogo.nvm.ExtensionContext.
org.nlogo.api.Workspace has been introduced as a stable API for extensions to depend
on.
A NetLogo jar is now available from BinTray.
org.nlogo.api.Context

For a full list of changes between 5.0 and 6.0, please visit ourExtension Transition Guide on
GitHub.
In service of making it easier to build extensions, we’ve expanded and improved theNetLogo
Extension Plugin for sbt, the Scala Build Tool. Sbt is a powerful tool for building JVM projects
and can be used in projects that use Scala, Java, or a combination of the two. We’re now
using the Extension Plugin to build all of the bundled extensions and we strongly recommend
extension authors take advantage of the plugin as it makes configuring a NetLogo extension
build extremely straightforward. The plugin handles fetching the NetLogo jar which extensions
compile against as well as generation of a jar for the extension containing the appropriate
metadata.

Add

range

primitive

A new range primitive was added in NetLogo 6. As “range” may appear in existing models as
a procedure or variable name, we have added an autoconversion step which will ensure that
these models continue to operate immediately upon opening in NetLogo 6. Existing uses of
range in models authored before NetLogo 6 will be converted to_range upon first opening in
NetLogo 6. Once the model opens, you can rename _range to suit your model.

Changes for NetLogo 5.2
hsb primitives
In 5.2, the hsb primitives have been changed to work with the standard scale values of 360
for hue, and 100 for saturation and brightness. This affects the primitives hsb, extract-hsb
and approximate-hsb.
The old primitives, scaled to 255, are automatically transitioned to and have been renamed
__hsb-old, __extract-hsb-old and __approximate-hsb-old.

GoGo extension
The GoGo extension has been upgraded to use newer GoGo boards with the HID interface.
Many of the older primitives no longer work, and will alert you to upgrading your GoGo
board’s firmware.
If you need to continue to use a serial interface, you can use the bundled gogo-serial
extension. Change your model to use gogo-serial as opposed to gogo. More details here.
If you cannot upgrade to use the new HID extension nor the new serial extension, the original
extension can be found at https://github.com/NetLogo/GoGo-RXTX-Extension

Changes for NetLogo 5.0
Plotting

In 5.0, you don’t have to put your plotting code in the Code tab anymore. Instead, you can put
it inside the plots themselves, in the Interface tab.
Nonetheless, the old style and all of the existing plotting primitives are still supported. We
recommend changing your model to use the new style, but if you don’t, it should still work.
The following example shows how to change a model to use the new style. Suppose you
have a typical NetLogo 4.1 model with one plot called “populations” and two pens called
“robots” and “humans”. The old code might look like:
to setup
clear-all
...
do-plotting
end
to go
...
tick
do-plotting
end
to do-plotting
set-current-plot "populations"
set-current-plot-pen "robots"
plot count robots
set-current-plot-pen "humans"
plot count humans
end

Here are the steps to make the transition:
Copy the plot count robots command and paste it into the Update Commands field for
the robots pen in the plot edit dialog. Remove it from the do-plotting procedure.
The plot count humans command can be moved in the same way for the humans pen.
After those lines are removed from the do-plotting procedure, it doesn’t actually do
anything anymore! Remove it.
The final step is to replace the do-plotting procedure calls in setup and go. In setup, the
do-plotting call should be changed to reset-ticks. In go , the do-plotting call should be
changed to tick. reset-ticks and tick will both cause plotting to happen automatically.
The resulting (much simpler) code looks like this:
to setup
clear-all
...
reset-ticks
end
to go
...
tick
end

For more details on how plotting works in NetLogo 5.0, see the Plotting Sections of the
Programming Guide and the Interface Guide. For details on how plotting interacts with the tick
counter, read on.

Tick counter
The way the tick counter works has changed in 5.0. Instead of being initially set to 0, the tick

counter is initially blank.
reset-ticks

You must use reset-ticks to start the tick counter at 0 before usingticks, tick or tickadvance for the first time.
should go at the end of your setup procedure. Putting it there will allow your
model to work with 5.0’s new plotting features.
reset-ticks

reset-ticks

and plotting

In 5.0, you don’t have to put your plotting code in the Code tab anymore. Instead, you can put
it inside the plots themselves, in the Interface tab. Code inside plots is triggered by resetticks and tick. Resetting the tick counter runs plot setup code, and then it also runs plot
update code to plot the initial state of the model. The initial state of the model won’t be in
place until the end of setup, so that’s why reset-ticks should go at the end.
__clear-all-and-reset-ticks

In order for models from previous NetLogo versions to work in 5.0 without changes, when an
old model is opened in 5.0, any occurrences of clear-all (or ca) are automatically changed to
__clear-all-and-reset-ticks, which combines the effects of clear-all and reset-ticks. The
two underscores on the name indicate that this is not a normal primitive, but exists only for
backwards compatibility.
You should remove __clear-all-and-reset-ticks from your code, replace it withclear-all,
and put reset-ticks at the end of your setup procedure. (This doesn’t happen automatically
because the structure of NetLogo models is too free-form for an automatic converter to
reliably make the change for you.)

Unicode characters
NetLogo 5.0 fully supports international characters cross-platform, using the Unicode
character set. NetLogo 5.0 model files always represent Unicode characters using the UTF-8
encoding.
Previous versions of NetLogo allowed Unicode characters to be used in some contexts.
However, model files were saved in the platform’s default encoding, which on most systems
was something other than UTF-8. Characters were handled correctly on the same platform
(e.g. two Windows machines), but could be altered if the model was moved between
platforms (e.g. from Windows to Mac or vice versa).
When opening an existing model in NetLogo 5.0, if the model contains international or other
non-ASCII characters, the characters may be interpreted incorrectly, because they were
originally written in a platform-specific encoding, but then read back in in UTF-8.
If only a few characters are affected, you might find it easiest just to fix them manually.
But if you expect a large number of characters to be affected, and you want them translated
automatically, you can use a third party utility to re-encode your .nlogo file from its original
encoding into UTF-8. After conversion, open the model in NetLogo 5.0 and all characters
should be correct.

Info tabs
NetLogo 5.0 uses the Markdown markup language to allow you to format your Info tab,
including headers, bold and italics, images, and so forth.
Earlier versions of NetLogo used a custom markup language with much more limited
capabilities.
When opening a model from an older version, NetLogo 5.0 translates your old markup into
Markdown. Most of the time this produces good results, but you may want to check the
results yourself and make sure that your Info tab still looks good.

Model speed
In NetLogo 5.0 every model has a “target frame rate” which affects the default speed at which
the model runs, when the speed slider is in the middle, on the “normal speed” setting.
The default target frame rate for new models, and for models that were created in earlier
versions of NetLogo, is 30 frames per second. If you are using tick-based updates, as we
recommend for most models, then that translates to 30 ticks per second.
If your model runs slower in 5.0 than it ran in 4.1, it’s probably just because its speed is being
limited by this rate. If you want, you can press the Settings button in the Interface tab and
change the frame rate to a higher number.
Some old models used the every command to set a default speed. In most case this can be
now removed from the code, and the target frame rate setting used instead.

List performance
The underlying data structure for NetLogo lists has changed.
In NetLogo 4.1, a NetLogo list was represented internally as a singly linked list. Some
operations on singly linked lists are fast (such as first and butfirst) but others are slow
because they could require traversing the whole list (such as item and last).
In NetLogo 5.0, lists are now actually trees internally. As a result, some operations are a little
slower, but other operations are drastically faster on long lists. See the Lists section of the
Programming Guide for details.
Some models may run a little slower with the new data structure, especially if you make
heavy use of short lists. But other models will run faster – perhaps dramatically faster.
Some special ways of writing list-processing code that were useful in NetLogo 4.1 are no
longer needed in 5.0. For example, since in 4.1 fput was fast and lput was slow, modelers
sometimes built up lists in reverse order using fput, perhaps calling reverse later to restore
the intended order. In NetLogo 5.0, you don’t need to code that way anymore. fput and lput
are the same speed.

Extensions API
If you are the author of an extension, you will need to recompile it against the 5.0 NetLogo.jar
and lib directory for it to work with 5.0.

You may also need to be aware of the following changes:

Syntax constants
The code for specifying the syntax of a primitive has changed slightly, for example
Syntax.TYPE_STRING is now Syntax.StringType(). (From Java, the pair of parentheses at the
end is required. In Scala, you can omit them.)

LogoList construction
One significant change is that org.nlogo.api.LogoList no longer has a public constructor.
Instead, there are two new ways to construct a LogoList.
If you have a java.lang.Iterable, you can copy the contents into a fresh LogoList by passing
it to the static method LogoList.fromJava(). See the array extension source code for a
sample usage.
Or, to build up a new list one item a time, useorg.nlogo.api.LogoListBuilder. The
Extensions Guide has sample code showing the use of LogoListBuilder.

Primitive classes
In prior NetLogo versions, the extensions API required that each extension primitive have its
own separate top-level class with a no-argument constructor. These limitations have now
been lifted. Also, api.Primitive objects are now made only once, when the extension is
loaded, instead of every time the Code tab was recompiled.

Changes for NetLogo 4.1
Combining set and

The following syntax is no longer supported:
set [] of

Commands of this form must be rewritten using ask:
ask [ set ]

Or, if the new value must be computed by the asking agent and not by the agent whose
variable is being set:
;; OPTION #1 (using let):
let new-value
ask [ set new-value ]
;; OPTION #2 (using myself):
ask [ set [value] of myself ]

So for example, this:

set [color] of turtle 0 red

Can be rewritten as:
ask turtle 0 [ set color red ]

It is not necessary to use let or myself since red is red from the point of view of both agents.
However, this:
set [color] of turtle 0 color

Must be rewritten as:
let new-color color
ask turtle 0 [ set color new-color ]

or
ask turtle 0 [ set color [color] of myself ]

in order not to change the meaning, since the two agents may have different starting values
for color. The form using myself is briefer, but the former using let may be considered
clearer, depending on context and individual preference.

Changes for NetLogo 4.0
Who numbering
Prior to NetLogo 4.0, a dead turtle’s who number (stored in thewho turtle variable) could be
reassigned to a later newborn turtle. In NetLogo 4.0, who numbers are never reused until who
numbering is reset to 0 by the clear-all or clear-turtles command. This change in behavior
may break a few old models.

Turtle creation: randomized vs. “ordered”
NetLogo 4.0 provides two different observer commands for creating turtles,create-turtles
(crt) and create-ordered-turtles (cro).
gives the new turtles random colors and random integer headings.cro assigns colors
sequentially and gives the turtles sequential equally spaced headings, with the first turtle
facing north (heading of 0).
crt

Prior to NetLogo 4.0, the crt command behaved the way cro does now. If your old model
depends on the “ordered” behavior, you will need to change your code to use cro instead of
crt.
It is common for old models that used crt to contain extra commands to randomize the new
turtles’ headings, for example rt random 360 or set heading random 360 . These commands
are no longer necessary when used inside crt.

Adding strings and lists
Prior to NetLogo 4.0, the + (addition) operator could be used to concatenate strings and join
lists. In current NetLogo, + only works on numbers. To concatenate strings, use the word
primitive; to join lists together, use the sentence primitive. This language change was made to
increase the speed of code that uses +.
Old code:
print "There are " + count turtles + " turtles."

New code:
print (word "There are " count turtles " turtles.")

Likewise, if you need to concatenate lists, use SENTENCE.
This change is not handled automatically when converting old models; users will need to
change their code by hand.
We know this change will be awkward for users who are used to the old syntax. We have
made this change for efficiency and consistency. We can implement an addition operator that
only adds numbers much more efficiently than one that handles several different data types.
Because addition is such a common operation, NetLogo’s overall speed is affected.

The

-at

primitives

The observer may no longer use patch-at , turtles-at, and BREEDS-at . Use patch, turtles-on
patch, and BREEDS-on patch instead. Note that patch now rounds its inputs (before it only
accepted integer inputs).

Links
NetLogo 3.1 had supports for using links to connect turtles to make networks, graphs, and
geometric figures. The links were themselves turtles.
In NetLogo 4.0, instead of links being turtles, links are now an independent fourth agent type,
right alongside observer, turtles, patches. The primitives involving links are no longer
considered experimental; they are now fully part of the language.
Models that use the old, experimental turtle-based link primitives will need to be updated to
use link agents. The differences are not huge, but hand updating is required.
Links are documented in the Links section of the Programming Guide, and in the NetLogo
Dictionary entries for the link primitives. See the Networks section of the Models Library for
example models that use links. There are also some link-based Code Examples.
First you will need to remove any breeds called “links” if you are only using one type of links
then you will not have to use breeds at all. If you are using multiple types of links see
undirected-link-breed and directed-link-breed. Commands and reporters that contain the
word “links” (like __create-links-with, etc.) will automatically be converted to the new form
without underscores (create-links-with ). However, primitives that use a different breed
name (such as “edges”) will not be converted. You will need to remove the underscores by

hand and unless you are declaring a link breed with that name you will need to change the
breed designation to “links”.
The commands remove-link(s)-with/from/to no longer exist. Instead you should ask the
links in question to die.
For example:
ask turtle 0 [ __remove-links-with link-neighbors ]

becomes
ask turtle 0 [ ask my-links [ die ] ]

Several of the layout commands have slightly different inputs, the first two inputs are
generally a turtle agentset and a link agentset to perform the layout on. See the dictionary
entries for details. layout-spring , layout-radial and layout-tutte
You may also need to rearrange the declaration of turtles-own variables, since links were
once actually turtles. Any variables that apply to links should be moved into a links-own block.
Since links are no longer turtles they no longer have the built-in turtle variables (though some
of the link variables are the same such as color and label. If you formerly used the location of
link turtles you will now need to calculate the midpoint of the link. This is fairly simple in a
non-wrapping world.
to-report link-xcor
report mean [xcor] of both-ends
end
to-report link-ycor
report mean [ycor] of both-ends
end

it is a little bit trickier in a wrapping world but still fairly straightforward.
to-report link-xcor
let other-guy end2
let x 0
ask end1
[
hatch 1
[
face other-guy
fd [distance other-guy] of myself / 2
set x xcor
die
]
]
report x
end

and similarly for ycor.
If you used either the size or heading of the link turtles you can use the reporterslink-length
and link-heading instead.

New “of” syntax

We have replaced three different language constructs, -of (with hyphen), value-from, and
values-from with a single of construct (no hyphen).
old

new

`color-of turtle 0`

`[color] of turtle 0`

`value-from turtle 0 [size * size]`

`[size * size] of turtle
0`

`mean values-from turtles [size]` `mean [size] of turtles`
When of is used with a single agent, it reports a single value. When used with an agentset, it
reports a list of values (in random order, since agentsets are always in random order).
Note that when opening old models in the new version,-of , value-from, and values-from will
automatically be converted to use “of” instead, but some nested uses of these constructs are
too complex for the converter and must be converted by hand.

Serial ask
The ask command is now serial rather than concurrent. In other words, the asked agents will
run one at a time. Not until one agent completely finishes the entire body of the ask does the
next agent start.
Note that even the old ask was never truly concurrent; we simulated concurrent execution by
interleaving execution among the agents using a turn-taking mechanism described in the
NetLogo FAQ.
We have made this change because in our experience, users often wrote models that
behaved in unexpected ways due to the simulated concurrency, but rarely wrote models that
benefited from the simulated concurrency. Models exhibiting unexpected behavior could
usually be fixed by adding the without-interruption command in the right places, but it was
difficult for users to know whether that command was needed and if so, where.
In NetLogo 4.0, without-interruption is no longer necessary unless your model uses askconcurrent (or a turtle or patch forever button containing code that depends on simulated
concurrency). In most models, all uses of without-interruption can be removed.
The simulated concurrency formerly employed by “ask” is still accessible in three ways:
You may use the ask-concurrent primitive instead of ask to get the old simulated
concurrency. (We don’t recommend this, though.)
Commands issued in the Command Center directly to turtles, patches, or links have an
implied ask-concurrent.
Turtle, patch, and link forever buttons have an implied ask-concurrent as well.
Note that ask itself is always serial regardless of the context in which it is used, however.
In our own Models Library, models that make use of this concurrency are rare. A prominent
example, though, is Termites, which uses a concurrent turtle forever button.

Tick counter
NetLogo now has a built-in tick counter for representing the passage of simulated time.

You advance the counter by one using thetick command. If you need to read its value,
there’s a reporter called ticks. The clear-all command resets the tick counter; so does
reset-ticks.
In most models the tick counter will be integer-valued, but if you want to use smaller
increments of time, you can use the tick-advance command to advance the tick counter by
any positive amount, including fractional amounts. Some Models Library models that use
tick-advance are Vector Fields and the GasLab models.
The value of the tick counter is displayed in the toolbar at the top of the Interface tab. (You
can use the Settings… button in the toolbar to hide the tick counter, or change the word
“ticks” to something else.)

View update modes
In the past, NetLogo always tried to update the view about 20 times a second. We’re now
calling that “continuous” view updates. The biggest problem with it was that you usually want
updates to happen between model ticks, not in the middle of a tick, so we had a checkbox on
buttons that (by default) forced a display update after every button iteration. That made sure
updates happened between ticks, but it didn’t get rid of the intermediate updates. You had to
use no-display and display to lock them out.
We still support continuous updates. They are the default when you start up NetLogo. But
most Models Library models now use tick-based updates. With tick-based updates, updates
happen only when the tick counter advances. (The display command can be used to force
additional updates; see below.)
The advantages of tick-based updates as we see them are as follows:
1. Consistent, predictable view update behavior which does not vary from computer to
computer or from run to run.
2. Intermediate updates can confuse the user of your model by letting them see things
they aren’t supposed to see, which may be misleading.
3. Increased speed. Updating the view takes time, so if one update per tick is enough, then
enforcing than there is only one update per tick will make your model faster.
4. Instead of having a “force view update” checkbox in every button like in NetLogo 3.1, we
only need one choice which applies to the entire model.
5. Using the speed slider to slow down a model now just inserts pauses between ticks. So
with tick-based updates, setup buttons are no longer affected by the speed slider. This
was a real annoyance with the old speed slider. (The annoyance persists for models
that use continuous updates, though.)
As mentioned above, most models in our Models Library now use tick-based updates.
Even for models that would normally be set to tick-based updates, it may be useful to switch
to continuous updates temporarily for debugging purposes. Seeing what’s going on within a
tick, instead of only seeing the end result of a tick, could help with troubleshooting.
If you switch your model to use tick-based updates, you’ll also need to add thetick
command to your code, otherwise the view won’t update. (Note that the view still always
updates when a button pops up or a command entered in the command center finishes,
though. So it’s not like the view will just stay frozen indefinitely.)

How to make a model use ticks and tick-based updates

Here are the steps to follow to convert your model to use ticks and tick-based updates in
NetLogo 4.0:
1. In the Interface tab toolbar, on the right hand side where it says “update view:”, change
the setting from “continuously” to “on ticks”.
2. Add the tick command to your go procedure, at or near the end. In Models Library
models we always put tick after the agents move but before any plotting commands.
That’s because the plotting commands might contain something like plotxy ticks ...
and we want the new value of the tick counter used, not the old one. Most models don’t
refer to the tick counter in their plotting commands, but nonetheless, for consistency and
to avoid mistakes we suggest always putting tick before the plotting commands.
Some models will require some additional changes:
1. If your model already has a global “ticks” or “clock” or “time” variable, get rid of it. Use
the tick command and ticks reporter instead. (If your model uses fractional increments
of time, use tick-advance instead of tick.) If you had a monitor for that variable, you can
get rid of it; there’s now a tick counter in the toolbar.
2. clear-all resets the tick counter to zero. If you don’t use clear-all in your setup
procedure, then you may need to add reset-ticks to reset the counter to zero.
3. If you used no-display and display to prevent view updates from happening in the
middle of go, you can get rid of them.
4. If your model needs to update the view without advancing the tick counter (examples:
Party, Dice Stalagmite, network models with animated layout, models with mouse
interaction buttons), use the display command to force additional view updates so the
user can see what is going on.

Speed slider
Previous versions of NetLogo had a speed slider that could be used to make models run
slower, so you can see what’s going on.
In NetLogo 4.0, the slider can be used to speed up models as well. It does this by updating
the view less frequently. Updating the view takes time, so the fewer updates, the faster the
model runs.
The default position of the slider is in the center. When you’re at the center, the slider says
“normal speed”.
As you move the slider away from the center position, the model will gradually run faster or
slower.
At very high speeds, view updates become very infrequent and may be separated by several
seconds. It may feel like the model is actually running slower, since the updates are so
infrequent. But watch the tick counter, or other indicators such as plots, and you’ll see that
yes, the model really is running faster. If the infrequent updates are disconcerting, don’t push
the slider so far over.
When using tick-based updates, slowing the model down does not cause additional view
updates. Rather, NetLogo simply pauses after each tick.
When using continuous updates, slowing the model down means view updates become more
closely spaced. If you push the speed slider more than halfway to the left, the model will be
running so slowly that you can watch turtles moving one at a time! This is new in NetLogo 4.0;
in previous NetLogo versions, no matter how slowly you ran a model, you would never see the
agents in an ask moving one at a time; all the agents in anask always appeared to move

together.

Numbers
NetLogo no longer maintains an internal distinction between integers and floating point
numbers. So for example:
Old:
observer>
3
observer>
3.0
observer>
3
observer>
3.0
observer>
true

print 3
print 3.0
print 1 + 2
print 1.5 + 1.5
print 3 = 3.0

(The last line shows that although the distinction between integer 3 and floating point 3.0 was
maintained, the two numbers were still considered equal.)
New:
observer>
3
observer>
3
observer>
3
observer>
3
observer>
true

print 3
print 3.0
print 1 + 2
print 1.5 + 1.5
print 3 = 3.0

We expect that only rare models will be negatively impacted by this change.
A benefit of this change is that NetLogo now supports a much larger range of integers. The
old range was -2,147,483,648 to 2,147,483,647 (around +/- 2 billion); the new range is +/9,007,199,254,740,992 (around +/- 9 quadrillion).

Agentset building
NetLogo 3.1 (and some earlier versions) included primitives called turtles-from and patchesfrom that were occasionally useful for building agentsets. In NetLogo 4.0, these primitives
have been replaced with new primitives called turtle-set and patch-set that are much more
flexible and powerful. (link-set exists as well.) See the entries for these primitives in the
NetLogo Dictionary. Models that use the old turtles-from and patches-from will need to be
altered by hand to use the new primitives.

RGB Colors
In NetLogo 3.1 RGB and HSB colors could be approximated as NetLogo colors using thergb
and hsb primitives. These have been renamed to approximate-rgb and approximate-hsb and
now expect inputs in the range 0-255, not 0-1.

The full RGB spectrum is now available in NetLogo so it may no longer be necessary to use
these primitives at all. You can set any color variable to a three-item RGB list, with values in
the 0-255 range, and get that exact color. See the Color section of the Programming Guide
for details.

Tie
In previous versions __tie was provided as an experimental feature. As of NetLogo 4.0 links
have a tie-mode variable which can be set to "none", "free", or "fixed" . In 4.0 tie is now a
link-only primitive. This means that to tie turtle 1 to turtle 0 you write:
ask turtle 0 [ create-link-to turtle 1 [ tie ] ]

See the Tie section of the programming guide for details.

Changes for NetLogo 3.1
Agentsets
If your model is behaving strangely or incorrectly, it may be because since NetLogo 3.1,
agentsets are now always in random order. In prior versions of NetLogo, agentsets were
always in a fixed order. If your code depended on that fixed order, then it won’t work anymore.
How to fix your model to work with randomized agentsets depends on the details of what your
code is doing. In some situations, it is helpful to use the sort or sort-by primitives to convert
an agentset (random order) into a list of agents (fixed order). See “Lists of agents” in the Lists
section of the Programming Guide.

Wrapping
If you are seeing pieces of turtle shapes wrapping around the view edges, it’s because
NetLogo 3.0 allowed you to turn off such wrapping in the view without affecting the behavior
of the model. Since NetLogo 3.1, if you don’t want the view to wrap you must make it so the
world doesn’t wrap, using the new topology feature. Making this change may require other
changes to your model, though. See the Topology section of the Programming Guide for a
thorough discussion of how to convert your model to take advantage of this new feature.

Random turtle coordinates
Many models made in NetLogo 3.0 or earlier usesetxy random world-width random worldheight to scatter turtles randomly, using either random or random-float . It only works if world
wrapping is on.
(Why? Because when wrapping is on, you can set coordinates of turtles to numbers beyond
the edge of the world and NetLogo will wrap the turtle to the other side. But in worlds that
don’t wrap setting the x or y coordinates of a turtle to a point outside the bounds of the world
causes a runtime error. The world wrap settings were added in NetLogo 3.1. See the
Topology section of the Programming Guide for more information.)
To fix your model so that it works regardless of the wrapping settings, use one of these two
commands instead:

setxy random-xcor random-ycor
setxy random-pxcor random-pycor

The two commands are a bit different. The first command puts the turtle on a random point in
the world. The second command puts the turtle on the center of a random patch. An even
more concise way to put a turtle on the center of a random patch is:
move-to one-of patches

Shapes Editor Guide
NetLogo 6.0.4 User Manual

The Turtle and Link Shape Editors allows you to create and save turtle and link designs.
NetLogo uses fully scalable and rotatable vector shapes, which means you can create
designs by combining basic geometric elements, which can appear on-screen in any size or
orientation.

Getting started
To begin making shapes, choose Turtle Shapes Editor or Link Shapes Editor in the Tools
menu. A new window will open listing all the shapes currently in the model, beginning with
default, the default shape. The Shapes Editor allows you to edit shapes, create new shapes,
and borrow from another model. You can also import turtle shapes from a library of preexisting shapes.

Importing shapes
Every new model in NetLogo starts off containing a small core set of frequently used shapes.
Many more turtle shapes are available by using the Import from library… button. This brings
up a dialog where you can select one or more shapes and bring them into your model. Select
the shapes, then press the Import button.
Similarly, you can use the Import from model… button to borrow shapes from another
model.
Default shapes
Here are the turtle shapes that are included by default in every new NetLogo model:

First row: default, airplane, arrow, box, bug, butterfly, car
Second row: circle, circle 2, cow, cylinder, dot, face happy, face neutral

Third row: face sad, fish, flag, flower, house, leaf, line
Fourth row: line half, pentagon, person, plant, sheep, square, square 2
Fifth row: star, target, tree, triangle, triangle 2, truck, turtle
Sixth row: wheel, x
Shapes library
And here are the shapes in the shapes library (including all of the default shapes, too):

By default there is only one Link shape in a model, that is “default”. This shape is simply a
single straight line with a simple arrowhead (if the link happens to be directed).

Creating and editing turtle shapes
Pressing the New button will make a new shape. Or, you may select an existing shape and
press Edit.

Tools
In the upper left corner of the editing window is a group of drawing tools. The arrow is the
selection tool, which selects an already drawn element.
To draw a new element, use one of the other seven tools:
The line tool draws line segments.
The circle, square, and polygon tools come in two versions, solid and outline.
When using the polygon tool, click the mouse to add a new segment to the polygon. When
you’re done adding segments, double click.
After you draw a new element, it is selected, so you can move, delete, or reshape it if you
want:
To move it, drag it with the mouse
To delete it, press the Delete button.
To reshape it, drag the small “handles” that appear on the element only when it is
selected.
To change its color, click on the new color.

Previews
As you draw your shape, you will also see it in five smaller sizes in the five preview areas
found near the bottom of the editing window. The previews show your shape as it might
appear in your model, including how it looks as it rotates. The number below each preview is
the size of the preview in pixels. When you edit the view, patch size is also measured in
pixels. So for example, the preview with “20” below it shows you how your shape would look
on a turtle (of size 1) on patches of size 20 pixels.

The rotatable feature can be turned off if you want a shape that always faces the same way,
regardless of the turtle’s heading.

Overlapping shapes
New elements go on top of previous elements. You can change the layering order by
selecting an element and then using the Bring to front and Send to back buttons.

Undo
At any point you can use the Undo button to undo the edit you just performed.

Colors
Elements whose color matches the Color that changes (selected from a drop-down menu –
the default is gray) will change color according to the value of each turtle’s color variable in
your model. Elements of other colors don’t change. For example, you could create cars that
always have yellow headlights and black wheels, but different body colors.

Other buttons
The “Rotate Left” and “Rotate Right” buttons rotate elements by 90 degrees. The “Flip
Horizontal” and “Flip Vertical” buttons reflect elements across the axes.
These four buttons will rotate or flip the entire shape, unless an element is selected, in which
case only that element is affected.
These buttons are especially handy in conjunction with the “Duplicate” button if you want to
make shapes that are symmetrical. For example, if you were making a butterfly, you could
draw the butterfly’s left wing with the polygon tool, then duplicate the wing with the “Duplicate”
button, then turn the copy into a right wing with the “Flip Horizontal” button.

Shape design
It’s tempting to draw complicated, interesting shapes, but remember that in most models, the
patch size is so small that you won’t be able to see very much detail. Simple, bold, iconic
shapes are usually best.

Keeping a shape
When the shape is done, give it a name and press theDone button at the bottom of the
editing window. The shape and its name will now be included in the list of shapes along with
the “default” shape.

Creating and editing link shapes
Managing link shapes is very similar to managing turtle shapes. So, you can create a new
shape by pressing the New button or you can edit existing shapes. When you are done
editing a shape press Done if you want to keep it.

Changing link shape properties
There are several different properties for each link shape that you are allowed to change:
Name - link shapes can have the same name as turtle shapes but must be unique
among link shapes.
Direction Indicator - the direction indicator (the little arrow on directed links) is just like
the turtle vector shapes, you can edit it using the same editor by pressing the Edit
button.
Curviness - this is the amount of bend in a link expressed in patches (this is particularly
useful if you have directed links going in both directions so you can discern both links)
Number of lines: You can have 1, 2, or 3 lines in each link shape, you control this by
selecting line patterns in the “left line”, “middle line”, and “right line” selection boxes.
Dash pattern of lines: There are several dashed line patterns available in the selection
boxes so not all lines need be solid.
Here are some link shapes with various properties:

Using shapes in a model
In the model’s code or in the command center, you can use any of the shapes that are in the
model (though only turtles can have turtle shapes and only links can have link shapes). For
example, suppose you want to create 50 turtles with the shape “rabbit”. Provided there is
some turtle shape called rabbit in this model, give this command to the observer in the
command center:
observer> crt 50

And then give these commands to the turtles to spread them out, then change their shape:
turtles> fd random 15
turtles> set shape "rabbit"

Voila! Rabbits! Note the use of double quotes around the shape name. Shape names are
strings.
Similarly, you can set the shape variable of links. Assuming there is a link shape called “road”
in this model:
observer> crt 5 [ create-links-with other turtles ]
turtles> fd 5
links> set shape "road"

The set-default-shape command is also useful for assigning shapes to turtles and links.

BehaviorSpace Guide
NetLogo 6.0.4 User Manual

This guide has three parts:
What is BehaviorSpace?: A general description of the tool, including the ideas and
principles behind it.
How It Works: Walks you through how to use the tool and highlights its most commonly
used features.
Advanced Usage: How to use BehaviorSpace from the command line, or from your
own Java code.

What is BehaviorSpace?
BehaviorSpace is a software tool integrated with NetLogo that allows you to perform
experiments with models.
BehaviorSpace runs a model many times, systematically varying the model’s settings and
recording the results of each model run. This process is sometimes called “parameter
sweeping”. It lets you explore the model’s “space” of possible behaviors and determine which
combinations of settings cause the behaviors of interest.
If your computer has multiple processor cores, then by default, model runs will happen in
parallel, one per core.

Why BehaviorSpace?
The need for this type of experiment is revealed by the following observations. Models often
have many settings, each of which can take a range of values. Together they form what in
mathematics is called a parameter space for the model, whose dimensions are the number of
settings, and in which every point is a particular combination of values. Running a model with
different settings (and sometimes even the same ones) can lead to drastically different
behavior in the system being modeled. So, how are you to know which particular
configuration of values, or types of configurations, will yield the kind of behavior you are
interested in? This amounts to the question of where in its huge, multi-dimension parameter
space does your model perform best?
For example, suppose you want speedy synchronization from the agents in the Fireflies
model. The model has four sliders – number, cycle-length, flash-length and number-flashes –
that have approximately 2000, 100, 10 and 3 possible values, respectively. That means there
are 2000 * 100 * 10 * 3 = 600,000 possible combinations of slider values! Trying combinations
one at a time is hardly an efficient way to learn which one will evoke the speediest
synchronization.
BehaviorSpace offers you a much better way to solve this problem. If you specify a subset of
values from the ranges of each slider, it will run the model with each possible combination of
those values and, during each model run, record the results. In doing so, it samples the
model’s parameter space – not exhaustively, but enough so that you will be able to see
relationships form between different sliders and the behavior of the system. After all the runs
are over, a dataset is generated which you can open in a different tool, such as a
spreadsheet, database, or scientific visualization application, and explore.
By enabling you to explore the entire “space” of behaviors a model can exhibit,
BehaviorSpace can be a powerful assistant to the modeler.

How It Works
To begin using BehaviorSpace, open your model, then choose the BehaviorSpace item on
NetLogo’s Tools menu.

Managing experiment setups
The dialog that opens lets you create, edit, duplicate, delete, and run experiment setups.
Experiments are listed by name and how by model runs the experiment will consist of.
Experiment setups are considered part of a NetLogo model and are saved as part of the
model.
To create a new experiment setup, press the “New” button.

Creating an experiment setup
In the new dialog that appears, you can specify the following information. Note that you don’t
always need to specify everything; some parts can be left blank, or left with their default
values, depending on your needs.
Experiment name: If you have multiple experiments, giving them different names will help
you keep them straight.
Vary variables as follows: This is where you specify which settings you want varied, and
what values you want them to take. Variables can include sliders, switches, choosers, and
any global variables in your model.
Variables can also include max-pxcor, min-pxcor, max-pycor and min-pycor, world-width,
world-height and random-seed. These are not, strictly speaking, variables, but BehaviorSpace
lets you vary them as if they were. Varying the world dimensions lets you explore the effect of
world size upon your model. Since setting world-width and world-height does not necessarily
define the bounds of the world how they are varied depends on the location of the origin. If
the origin is centered, BehaviorSpace will keep it centered so the values world-width or
world-height must be odd. If one of the bounds is at zero that bound will be kept at zero and
the other bound will move, for example if you start with a world with min-pxcor = 0 max-pxcor
= 10 and you vary world-width like this:
["world-width" [11 1 14]]

will stay at zero and max-pxcor will set to 11, 12, and 13 for each of the runs. If
neither of these conditions are true, the origin is not centered, nor at the edge of the world
you cannot vary world-height or world-width directly but you should vary max-pxcor, maxpycor, min-pxcor and min-pycor instead.
min-pxcor

Varying random-seed lets you repeat runs by using a known seed for the NetLogo random
number generator. Note that you’re also free to use the random-seed command in your
experiment’s setup commands. For more information on random seeds, see the Random
Numbers section of the Programming Guide.
You may specify values either by listing the values you want used, or by specifying that you
want to try every value within a given range. For example, to give a slider named number
every value from 100 to 1000 in increments of 50, you would enter:

["number" [100 50 1000]]

Or, to give it only the values of 100, 200, 400, and 800, you would enter:
["number" 100 200 400 800]

Be careful with the brackets here. Note that there are fewer square brackets in the second
example. Including or not including this extra set of brackets is how you tell BehaviorSpace
whether you are listing individual values, or specifying a range.
Also note that the double quotes around the variable names are required.
You can vary as many settings as you want, including just one, or none at all. Any settings
that you do not vary will retain their current values. Not varying any settings is useful if you
just want to do many runs with the current settings.
What order you list the variables in determines what order the runs will be done in. All values
for a later variable will be tried before moving to the next value for an earlier variable. So for
example if you vary both x and y from 1 to 3, and x is listed first, then the order of model runs
will be: x=1 y=1, x=1 y=2, x=1 y=3, x=2 y=1, and so on.
Repetitions: Sometimes the behavior of a model can vary a lot from run to run even if the
settings don’t change, if the model uses random numbers. If you want to run the model more
than once at each combination of settings, enter a higher number.
Measure runs using these reporters: This is where you specify what data you want to
collect from each run. For example, if you wanted to record how the population of turtles rose
and fell during each run, you would enter:
count turtles

You can enter one reporter, or several, or none at all. If you enter several, each reporter must
be on a line by itself, for example:
count frogs
count mice
count birds

If you don’t enter any reporters, the runs will still take place. This is useful if you want to
record the results yourself your own way, such as with the export-world command.
Measure runs at every step: Normally NetLogo will measure model runs at every step,
using the reporters you entered in the previous box. If you’re doing very long model runs, you
might not want all that data. Uncheck this box if you only want to measure each run after it
ends.
Setup commands: These commands will be used to begin each model run. Typically, you
will enter the name of a procedure that sets up the model, typically setup. But it is also
possible to include other commands as well.

Go commands: These commands will be run over and over again to advance to the model
to the next “step”. Typically, this will be the name of a procedure, such as go, but you may
include any commands you like.
Stop condition: This lets you do model runs of varying length, ending each run when a
certain condition becomes true. For example, suppose you wanted each run to last until there
were no more turtles. Then you would enter:
not any? turtles

If you want the length of runs to all be of a fixed length, just leave this blank.
The run may also stop because the go commands use thestop command, in the same way
that stop can be used to stop a forever button. The stop command may be used directly in the
go commands, or in a procedure called directly by the go commands. (The intent is that the
same go procedure should work both in a button and in a BehaviorSpace experiment.) Note
that the step in which stop is used is considered to have been aborted, so no results will be
recorded for that step. Therefore, the stopping test should be at the beginning of the go
commands or procedure, not at the end.
Final commands: These are any extra commands that you want run once, when the run
ends. Usually this is left blank, but you might use it to call the export-world command or
record the results of the run in some other way.
Time limit: This lets you set a fixed maximum length for each run. If you don’t want to set any
maximum, but want the length of the runs to be controlled by the stop condition instead, enter
0.

Special primitives for BehaviorSpace experiments
Currently there are only two, behaviorspace-run-number and behaviorspace-experiment-name.
The run number reported by the former primitive matches the run number used in the results
files generated by BehaviorSpace. The experiment name reported by the latter matches the
name with which the experiment was set up.

Running an experiment
When you’re done setting up your experiment, press the “OK” button, followed by the “Run”
button. A dialog titled “Run options” will appear.

Run options: formats
The run options dialog lets you select the formats you would like the data from your
experiment saved in. Data is collected for each run or step, according to the setting of
Measure runs at every step option. In either case, the initial state of the system is recorded,
after the setup commands run but before the go commands run for the first time.
Table format lists each interval in a row, with each metric in a separate column. Table data is
written to the output file as each run completes. Table format is suitable for automated
processing of the data, such as importing into a database or a statistics package.
Spreadsheet format calculates the min, mean, max, and final values for each metric, and then
lists each interval in a row, with each metric in a separate column. Spreadsheet data is more

human-readable than Table data, especially if imported into a spreadsheet application.
(Note however that spreadsheet data is not written to the results file until the experiment
finishes. Since spreadsheet data is stored in memory until the experiment is done, very large
experiments could run out of memory. So you should disable spreadsheet output unless you
really want it. If you do want spreadsheet output, note that if anything interrupts the
experiment, such as a runtime error, running out of memory, or a crash or power outage, no
spreadsheet results will be written. For long experiments, you may want to also enable table
format as a precaution so that if something happens and you get no spreadsheet output you’ll
at least get partial table output.)
After selecting your output formats, BehaviorSpace will prompt you for the name of a file to
save the results to. The default name ends in “.csv”. You can change it to any name you want,
but don’t leave off the “.csv” part; that indicates the file is a Comma Separated Values (CSV)
file. This is a plain-text data format that is readable by any text editor as well as by most
popular spreadsheet and database programs.

Run options: parallel runs
The run options dialog also lets you select whether you want multiple model runs to happen in
parallel, and if so, how many are allowed to be simultaneously active. This number will default
to the number of processor cores in your computer.
There are a few cautions associated with parallel runs.
First, if multiple runs are active, only one of them will be in the “foreground” and cause the
view and plots to update. The other runs will happen invisibly in the background.
Second, invisible background runs can’t use primitives that only work in the GUI. For
example, a background run can’t make a movie.
Third, since parallel runs progress independently of each other, table format output may
contain interleaved, out-of-order results. When you analyze your table data, you may wish to
sort it by run number first. (Spreadsheet format output is not affected by this issue, since it is
not written until the experiment completes or is aborted.)
Fourth, using all available processor cores may make your computer slow to use for other
tasks while the experiment is running.
Fifth, doing runs in parallel will multiply the experiment’s memory requirements accordingly.
You may need to increase NetLogo’s memory ceiling (see this FAQ entry).

Observing runs
After you complete the run options dialog, another dialog will appear, titled “Running
Experiment”. In this dialog, you’ll see a progress report of how many runs have been
completed so far and how much time has passed. If you entered any reporters for measuring
the runs, and if you left the “Measure runs at every step” box checked, then you’ll see a plot of
how they vary over the course of each run.
You can also watch the runs in the main NetLogo window. (If the “Running Experiment” dialog
is in the way, just move it to a different place on the screen.) The view and plots will update as
the model runs. If you don’t need to see them update, then use the checkboxes in the
“Running Experiment” dialog to turn the updating off. This will make the experiment go faster.
If you want to stop your experiment before it’s finished, press the “Abort” button. Any results

generated so far will still be saved.
When all the runs have finished, the experiment is complete.

Advanced Usage
Running from the command line
It is possible to run BehaviorSpace experiments “headless”, that is, from the command line,
without any graphical user interface (GUI). This is useful for automating runs on a single
machine or a cluster of machines.
No Java programming is required. Experiment setups can be created in the GUI and then run
later from the command line, or, if you prefer, you can create or edit experiment setups
directly using XML.

How to use it
Run NetLogo using the included command line script. This is found in the root directory of
your NetLogo installation and is named netlogo-headless.sh on Mac and Linux and netlogoheadless.bat on Windows. The netlogo-headless script supports the following arguments:
--model : pathname of model to open (required)
--setup-file : read experiment setups from this file instead of the model file
--experiment : name of experiment to run
--table : pathname to send table output to (or - for standard output)
--spreadsheet : pathname to send table output to (or - for standard output)
--threads : use this many threads to do model runs in parallel, or 1 to disable

parallel runs. defaults to one thread per processor.
--min-pxcor : override world size setting in model file
--max-pxcor : override world size setting in model file
--min-pycor : override world size setting in model file
--max-pycor : override world size setting in model file
is required. If you don’t specify --experiment , you must specify --setup-file . By
default no results are generated, so you’ll usually want to specify either --table or -spreadsheet, or both. If you specify any of the world dimensions, you must specify all four.
--model

Note: The remainder of this guide uses netlogo-headless.sh to refer to the NetLogo
Headless launch script. If you are using Windows, please substitute netlogo-headless.bat for
netlogo-headless.sh in each example.

Examples
It is easiest if you create your experiment setup ahead of time in the GUI, so it is saved as
part of the model. To run an experiment setup saved in a model, here is an example
command line:
netlogo-headless.sh \
--model Fire.nlogo \
--experiment experiment1 \
--table -

For this to work, Java (version 1.8 or later) must be available. You can make Java available to
headless in either of two ways
1. Set the JAVA_HOME environment variable to the path to the Java installation. This is the
directory of the Java installation which contains a “bin” directory.
2. Add the directory containing the Java executable to thePATH environment variable
If JAVA_HOME is defined, netlogo-headless will run NetLogo using the Java that it points to,
ignoring the version of Java available on the path.
After the named experiment has run, the results are sent to standard output in table format,
as CSV. (“-” is how you specify standard output instead of output to a file.)
When running netlogo headless, it forces the system property java.awt.headless to be true.
This tells Java to run in headless mode, allowing NetLogo to run on machines when a
graphical display is not available.
The required --model argument is used to specify the model file you want to open.
The --experiment argument is used to specify the name of the experiment you want to run.
(At the time you create an experiment setup in the GUI, you assign it a name.)
Here’s another example that shows some additional, optional arguments:
netlogo-headless.sh \
--model Fire.nlogo \
--experiment experiment2 \
--max-pxcor 100 \
--min-pxcor -100 \
--max-pycor 100 \
--min-pycor -100

Note the use of the optional --max-pxcor, --max-pycor, etc. arguments to specify a different
world size than that saved in the model. (It’s also possible for the experiment setup to specify
values for the world dimensions; if they are specified by the experiment setup, then there is
no need to specify them on the command line.)
Since neither --table nor --spreadsheet is specified, no results will be generated. This is
useful if the experiment setup generates all the output you need by some other means, such
as exporting world files or writing to a text file.
Yet another example:
netlogo-headless.sh \
--model Fire.nlogo \
--experiment experiment2 \
--table table-output.csv \
--spreadsheet spreadsheet-output.csv

The optional --table argument specifies that output should be generated in a
table format and written to the given file as CSV data. If - is specified as the filename, than
the output is sent to the standard system output stream. Table data is written as it is
generated, with each complete run.
The optional --spreadsheet argument specified that spreadsheet output should
be generated and written to the given file as CSV data. If - is specified as the filename, than
the output is sent to the standard system output stream. Spreadsheet data is not written out
until all runs in the experiment are finished.

Note that it is legal to specify both --table and --spreadsheet , and if you do, both kinds of
output file will be generated.
Here is one final example that shows how to run an experiment setup which is stored in a
separate XML file, instead of in the model file:
netlogo-headless.sh \
--model Fire.nlogo \
--setup-file fire-setups.xml \
--experiment experiment3

If the XML file contains more than one experiment setup, it is necessary to use the-experiment argument to specify the name of the setup to use.
In order to run a NetLogo 3D experiment, run headless with the--3D argument, for example:
netlogo-headless.sh \
--3D \
--model "Mousetraps 3D.nlogo3d" \
--experiment experiment1 \
--table -

Note that you should supply a 3D model and there are also 3D arguments--max-pzcor
and --min-pzcor .
The next section has information on how to create standalone experiment setup files using
XML.

Setting up experiments in XML
We don’t yet have detailed documentation on authoring experiment setups in XML, but if you
already have some familiarity with XML, then the following pointers may be enough to get you
started.
The structure of BehaviorSpace experiment setups in XML is determined by a Document
Type Definition (DTD) file. The DTD is stored in NetLogo.jar, as system/behaviorspace.dtd.
(JAR files are also zip files, so you can extract the DTD from the JAR using Java’s “jar” utility
or with any program that understands zip format.)
The easiest way to learn what setups look like in XML, though, is to author a few of them in
BehaviorSpace’s GUI, save the model, and then examine the resulting .nlogo file in a text
editor. The experiment setups are stored towards the end of the .nlogo file, in a section that
begins and ends with a experiments tag. Example:

setup
go
not any? fires
burned-trees

In this example, only one experiment setup is given, but you can put as many as you want
between the beginning and ending experiments tags.
Between looking at the DTD, and looking at examples you create in the GUI, it will hopefully
be apparent how to use the tags to specify different kind of experiments. The DTD specifies
which tags are required and which are optional, which may be repeated and which may not,
and so forth.
When XML for experiment setups is included in a model file, it does not begin with any XML
headers, because not the whole file is XML, only part of it. If you keep experiment setups in
their own file, separate from the model file, then the extension on the file should be .xml not
.nlogo, and you’ll need to begin the file with proper XML headers, as follows:

The second line must be included exactly as shown. In the first line, you may specify a
different encoding than UTF-8, such as ISO-8859-1.

Adjusting JVM Parameters
Opening the NetLogo Headless launcher script will show the options used to launch java
when running NetLogo Headless. You can adjust various JVM parameters in this script. You
may also pass in Java properties starting with -D to the launcher.
Note the use of -Xmx to specify a maximum heap size of one gigabyte. If you don’t specify a
maximum heap size, you will get your VM’s default size, which may be unusably small. (One
gigabyte is an arbitrary size which should be more than large enough for most models; you
can specify a different limit if you want.)
Note the use of -Dfile.encoding=UTF-8. This forces all file I/O to use UTF-8 encoding. Doing
so ensures that NetLogo can load all models consistently, and that file-* primitives work
consistently on all platforms, including models containing Unicode characters.

Controlling API
If BehaviorSpace is not sufficient for your needs, a possible alternative is to use our
Controlling API, which lets you write Java code that controls NetLogo. The API lets you run
BehaviorSpace experiments from Java code, or, you can write custom code that controls
NetLogo more directly to do BehaviorSpace-like things. See the Controlling section of the
User Manual for further details on both possibilities.

System Dynamics Guide
NetLogo 6.0.4 User Manual

This guide has three parts:
What is the System Dynamics Modeler?: A general description of the tool, including the ideas and
principles behind it.
How It Works: Describes the interface and how you use it.
Tutorial: Wolf-Sheep Predation (aggregate): Walks you through creating a model with the System
Dynamics Modeler.

What is the NetLogo System Dynamics Modeler?
System Dynamics is a type of modeling where you try to understand how things relate to one another. It is a little
different from the agent-based approach we normally use in NetLogo models.
With the agent-based approach we usually use in NetLogo, you program the behavior of individual agents and
watch what emerges from their interaction. In a model of Wolf-Sheep Predation, for example, you provide rules
for how wolves, sheep and grass interact with each other. When you run the simulation, you watch the emergent
aggregate-level behavior: for example, how the populations of wolves and sheep change over time.
With the System Dynamics Modeler, you don’t program the behavior of individual agents. Instead, you program
how populations of agents behave as a whole. For example, using System Dynamics to model Wolf-Sheep
Predation, you specify how the total number of sheep would change as the total number of wolves goes up or
down, and vice versa. You then run the simulation to see how both populations change over time.
The System Dynamics Modeler allows you to draw a diagram that defines these populations, or “stocks”, and
how they affect each other. The Modeler reads your diagram and generates the appropriate NetLogo code –
global variables, procedures and reporters – to run your System Dynamics model inside of NetLogo.

Basic Concepts
A System Dynamics diagram is made of four kinds of elements: Stocks, Variables, Flows and Links.
A Stock is a collection of stuff, an aggregate. For example, a Stock can represent a population of sheep, the
water in a lake, or the number of widgets in a factory.
A Flow brings things into, or out of a Stock. Flows look like pipes with a faucet because the faucet controls how
much stuff passes through the pipe.
A Variable is a value used in the diagram. It can be an equation that depends on other Variables, or it can be a
constant.
A Link makes a value from one part of the diagram available to another. A link transmits a number from a
Variable or a Stock into a Stock or a Flow.
The System Dynamics Modeler figures out how the value of your Stocks change over time by estimating them
over and over. The estimation isn’t always perfect, but you can affect its accuracy by changing the value of dt. As
dt decreases, you estimate the model more frequently, so it gets more accurate. However, decreasing dt also
makes the model slower.

Sample Models
There are four basic models in the Sample Models section of the NetLogo Models Library that demonstrate the
use of the System Dynamics Modeler. All four basic models explore population growth (and, in models with
predation, population decline).
Exponential Growth and Logistic Growth are simple examples of growth in one stock.
Wolf Sheep Predation (System Dynamics) is an example of a system with multiple stocks influencing one
another. It models a predator-prey ecosystem using the System Dynamics Modeler.
Wolf Sheep Predation (Docked Hybrid) is an example of a model that runs both the a System Dynamics model
and an agent-based model side-by-side. It runs the System Dynamics implementation of Wolf-Sheep Predation
next to the agent-based Wolf Sheep Predation model from the Biology section of Sample Models.

How it Works
To open the System Dynamics Modeler, choose the System Dynamics Modeler item in the Tools menu. The
System Dynamics Modeler window will appear.

Diagram Tab
The Diagram tab is where you draw your System Dynamics diagram.
The toolbar contains buttons to edit, delete and create items in your diagram.

Creating Diagram Elements

A System Dynamics diagram is made up of four kinds of components: Stocks, Variables, Flows and Links.
Stock
To create a Stock, press the Stock button in the toolbar and click in the diagram area below. A new Stock
appears. Each Stock requires a unique name, which becomes a global variable. Stocks also require an
**Initial value**. It can be a number, a variable, a complex NetLogo expression, or a call to a NetLogo
reporter.
Variable
To create a Variable, press the Variable button and click on the diagram. Each Variable in the System
Dynamics Model requires a unique name, which becomes the name of a procedure, or a global variable.
Variables also require an **Expression**. This expression can be a number, a variable, a complex NetLogo
expression, or a call to a NetLogo reporter.
Flow
To create a Flow, press the Flow button. Click and hold where you want the Flow to begin -- either on a
Stock or in an empty area -- and drag the mouse to where you want the Flow to end -- on a Stock or in an
empty area. Each Flow requires a unique name, which becomes a NetLogo reporter. Flows require an
**Expression**, which is the rate of flow from the input to the output. This expression can be a number, a
variable, a complex NetLogo expression, or a call to a NetLogo reporter. If the value is negative, the flow is
in the opposite direction.
When more than one Flow is connected to a Stock, it is important to consider how they should interact with
one another. NetLogo will not enforce that the Flows out of a stock occur in any particular order. Also,
NetLogo will not ensure that the sum of Flows out of a Stock are less than or equal to the value of the
Stock. These behaviors can be implemented explicitly when creating the Expression for a Flow.

For example, if the Flow is defined as a constant value, 10, you can ensure it never draws more than the
value of the Stock by using the min primitive: min (list stock 10). If I want Flow A to deplete a Stock
before Flow B is calculated, I can link Flow A to Flow B and modify Flow B to subtract Flow A’s value from
the stock: min (list (max (list 0 (stock - flow-a))) 10) .
Link
To create a Link, click and hold on the starting point for the link -- a Variable, Stock or Flow -- and drag the
mouse to the destination Variable or Flow.

Working with Diagram Elements
When you create a Stock, Variable, or Flow, you see a red question-mark on the element. The question-mark
indicates that the element doesn’t have a name yet. The red color indicates that the Stock is incomplete: it’s
missing one or more values required to generate a System Dynamics model. When a diagram element is
complete, the name turns black.
Selecting: To select a diagram element, click on it. To select multiple elements, hold the shift key. You can also
select one or more elements by dragging a selection box.
Editing: To edit a diagram element, select the element and press the “Edit” button on the toolbar. Or just doubleclick the element. (You can edit Stocks, Flows and Variables, but you can’t edit Links).
Moving: To move a diagram element, select it and drag the mouse to a new location.

Editing dt

On the right side of the toolbar is the default dt, the interval used to approximate the results of your System
Dynamics model. To change the value of the default dt for your aggregate model, press the Edit button next to
the dt display and enter a new value.

Errors
When you click the “check” button or when you edit a stock, flow, or variable the modeler will automatically
generate the NetLogo code the corresponds to your diagram and try to compile that code. If there is an error the
Code tab will turn red and a message will appear, and the portion of the generated code that is causing the
trouble will be highlighted.

This should give you a better idea which element in the diagram is causing the problem.

Code Tab
The System Dynamics Modeler generates NetLogo variables and procedures based on the contents of your
diagram. These procedures are what make the diagram actually perform calculations. The Code tab in the
System Dynamics Modeler window displays the NetLogo procedures generated from your diagram.
You can’t edit the contents of the Code tab. To modify your System Dynamics mode, edit the diagram.
Let’s take a closer look at how the generated code relates to the diagram:
Stocks correspond to a global variable that is initialized to the value or expression you provided in the
Initial value field. Each Stock will be updated every step based on the Flows in and out.
Flows correspond to a procedure that contains the expression you provided in theExpression field.
Variables can either be global variables or procedures. If the Expression you provided is a constant it will
be a global variable and initialized to that value. If you used a more complicated Expression to define the
Variable it will create a procedure like a Flow.
The variables and procedures defined in this tab are accessible in the main NetLogo window, just like the
variables and procedures you define yourself in the main NetLogo Code tab. You can call the procedures from
the main Code tab, from the Command Center, or from buttons in the Interface tab. You can refer to the global
variables anywhere, including in the main Code tab and in monitors.
There are three important procedures to notice: system-dynamics-setup, system-dynamics-go , and systemdynamics-do-plot.
initializes the aggregate model. It sets the value ofdt, calls reset-ticks, and initializes
your stocks and your converters. Converters with a constant value are initialized first, followed by the stocks with
constant values. The remaining stocks are initialized in alphabetical order.
system-dynamics-setup

runs the aggregate model for dt time units. It computes the values of Flows and Variables
and updates the value of Stocks. It also calls tick-advance with the value of dt. Converters and Flows with nonconstant Expressions will be calculated only once when this procedure is called, however, their order of
evaluation is undefined
system-dynamics-go

plots the values of Stocks in the aggregate model. To use this, first create a plot in the
main NetLogo window. You then need to define a plot pen for each Stock you want to be plotted. This procedure
will use the current plot, which you can change using the set-current-plot command.
system-dynamics-do-plot

The System Dynamics Modeler and NetLogo
The diagram you create with the System Dynamics Modeler, and the procedures generated from your diagram,
are part of your NetLogo model. When you a save the NetLogo model, your diagram is saved with it, in the same
file.

Tutorial: Wolf-Sheep Predation
Let’s create a model of Wolf-Sheep Predation with the System Dynamics Modeler.

Step 1: Sheep Reproduction

Open a new model in NetLogo.

Launch the System Dynamics Modeler in the Tools menu.

Our model will have a population of wolves and a population of sheep. Let’s start with the sheep. First, create a
Stock that holds a population of Sheep.

Press the Stock button in the toolbar.

Click in the diagram area.

You see a Stock with a red question-mark in the middle.

Double-click the Stock to edit.
Name the stock sheep
Set the initial value to 100.
Deselect the Allow Negative Values checkbox. It doesn’t make sense to have negative sheep!

Our sheep population can increase if new sheep are born. To add this to our diagram, we create a Flow into the
stock of sheep.

Click on the Flow button in the toolbar and press the mouse button in an empty area to the left
of the sheep Stock. Drag the Flow to the right until it connects to the sheep Stock and let go.
Edit the Flow and name it sheep-births .
For now, enter a constant, such as 1, into the Expression field.

The number of sheep born during a period of time depends on the number of sheep that are alive: more sheep
means more reproduction.

Draw a Link from the sheep Stock to the sheep-births Flow.

The rate of sheep births also depends on some constant factors that are beyond the scope of this model: the
rate of reproduction, etc.

Create a Variable and name it sheep-birth-rate. Set its value to 0.04.
Draw a Link from the sheep-birth-rate Variable to the sheep-births .

Your diagram should look something like this:

Our diagram has the correct structure but we aren’t yet finished because it the amount of sheep flowing into the
stock doesn’t depend upon the number of sheep and sheep birth rate.

Edit the sheep-births Flow and set the expression to sheep-birth-rate * sheep .

We now have a complete diagram. To see the NetLogo code generated by our diagram, you can click on the
Code tab of the System Dynamics Modeler window. It looks like this:

Step 2: NetLogo Integration
Once you create an aggregate model with the System Dynamics Modeler, you can interact with the model
through the main NetLogo interface window. Let’s build our NetLogo model to run the code generated by our
diagram. We’ll need a setup and go buttons which call the system-dynamics-setup and system-dynamics-go
procedures created by the System Dynamics Modeler. And we’ll want a monitor and a plot to watch the changes
in sheep population.

Select the main NetLogo window
In the Code tab, write:
to setup
ca
system-dynamics-setup
end
to go
system-dynamics-go
system-dynamics-do-plot
end

Move to the Interface tab
Create a setup button
Create a go button (don’t forget to make it forever)
Create a sheep monitor.
Create a plot called “populations” with a pen named “sheep”.

Now we’re ready to run our model.

Press the setup button.
Don’t press the “go” button yet. Instead, typego four or five times into the Command Center.

Notice what happens. The sheep population increases exponentially. After four or five iterations, we have an
enormous number of sheep. That’s because we have sheep reproduction, but our sheep never die.

To fix that, let’s finish our diagram by introducing a population of wolves which eat sheep.

Step 3: Wolf Predation

Move back to the System Dynamics window
Add a stock of wolves
Add Flows, Variables and Links to make your diagram look like this:

Add one more Flow from the wolves Stock to the Flow that goes out of the Sheep stock.
Fill in the names of the diagram elements so it looks like this:

where
initial-value of wolves is 30,
wolf-deaths is wolves * wolf-death-rate ,
wolf-death-rate is 0.15,
predator-efficiency is .8 ,
wolf-births is wolves * predator-efficiency * predation-rate * sheep ,
predation-rate is 3.0E-4,
and sheep-deaths is sheep * predation-rate * wolves .
Adjust the dt of the system dynamics model by selecting “Edit” next todt in the toolbar of the
system dynamics modeler. In the dialog that appears, enter 0.01.

Now we’re really done.

Go back to the main NetLogo window
Add a plot pen named “wolves” to the population plot
Press setup and go to see your System Dynamics Modeler diagram in action.

You see a plot of the populations that looks like this:

HubNet Guide
NetLogo 6.0.4 User Manual

This section of the User Manual introduces the HubNet system and includes instructions to
set up and run a HubNet activity.
HubNet is a technology that lets you use NetLogo to runparticipatory simulations in the
classroom. In a participatory simulation, a whole class takes part in enacting the behavior of a
system as each student controls a part of the system by using an individual device, such as a
networked computer.
For example, in the Gridlock simulation, each student controls a traffic light in a simulated city.
The class as a whole tries to make traffic flow efficiently through the city. As the simulation
runs, data is collected which can afterwards be analyzed on a computer.
For more information on participatory simulations and their learning potential, please visit the
Participatory Simulations Project web site.

Understanding HubNet
NetLogo
NetLogo is a programmable modeling environment. It comes with a large library of existing
simulations, both participatory and traditional, that you can use and modify. Content areas
include social science and economics, biology and medicine, physics and chemistry, and
mathematics and computer science. You and your students can also use it to build your own
simulations.
In traditional NetLogo simulations, the simulation runs according to rules that the simulation
author specifies. HubNet adds a new dimension to NetLogo by letting simulations run not just
according to rules, but by direct human participation.
Since HubNet builds upon NetLogo, we recommend that before trying HubNet for the first
time, you become familiar with the basics of NetLogo. To get started using NetLogo models,
see Tutorial #1: Running Models in the NetLogo Users Manual.

HubNet Architecture
HubNet simulations are based on a client/server architecture. The activity leader uses the
NetLogo application to run a HubNet activity. When NetLogo is running a HubNet activity, we
refer to it as a HubNet server. Participants use a client application to log in and interact with
the HubNet server.
While HubNet is only supported via the Java Desktop clients at the moment, we hope to add
support for other types of clients such as tablets and phones in the future.

Computer HubNet
Activities
The following activities are available in the Models Library, in the HubNet Activities folder.
Information on how to run the models and activities can be found in the Info tab of each

model. Additional discussion of educational goals and ways to incorporate many of the
activities into your classroom in the Participatory Simulations Guide on the Participatory
Simulations Project web site.
Bug Hunters Camouflage - students hunt bugs and camouflaging emerges.
Dice Stalagmite HubNet - students roll dice and explore the space of dependent and
independent events.
Disease - A disease spreads through the simulated population of students.
Disease Doctors - A slight modification to the Disease activity where some students can
recover from the disease.
Gridlock - Students use traffic lights to control the flow of traffic through a city.
Polling - Ask students questions and plot their answers.
Root Beer Game - An adaptation of a popular game created at MIT in the early 1960s
that shows how small delays in a distribution system can create big problems.
Sampler - Students engage in statistical analysis as individuals and as a classroom.
Through these activities, students discover the meaning and use of basic concepts in
statistics.
Tragedy of the Commons - Students work as farmers sharing a common resource.

Clients
To use the client application you simply need to launch the HubNet client application that is
bundled with NetLogo.

Requirements
To use Computer HubNet, you need a networked computer with NetLogo installed for the
server. When using the client application you will also need a networked computer with
NetLogo installed for each participant. When using in classroom settings we also suggest an
attached projector for the leader to project the entire simulation to the participants.

Starting an activity
You’ll find the HubNet activities in NetLogo’s Models Library, in the HubNet Activities folder.
We suggest doing a few practice runs of an activity before trying it in front of a class.

Open a Computer HubNet model. NetLogo will prompt you to enter the name of your new
HubNet session. This is the name that participants will use to identify this activity. You may
also see a broadcast network selection dropdown for which more extensive documentation is
available in the FAQ. For now, just enter a name and press Start.

NetLogo will open the HubNet Control Center, which lets you interact with the HubNet server.
You, as the leader, should then notify everyone that they may join. To join the activity,
participants launch the HubNet Client application and enter their name. They should see your
activity listed and can join your activity by selecting it and pressing Enter. If the activity you
started is not listed the student can enter the server address manually which can be found in
the HubNet Control Center.

HubNet Control Center

The HubNet Control Center lets you interact with the HubNet server. It displays the name,
activity, address and port number of your server. The “Mirror 2D View on clients” checkbox
controls whether the HubNet participants can see the view on their clients, assuming there is
a view in the client setup. The “Mirror plots on clients” checkbox controls whether participants
will receive plot information.
The client list on the right displays the names of clients that are currently connected to you
activity. To remove a participant from the activity, select their name in the list and press the
Kick button. To launch your own HubNet client press the Local button, this is particularly
useful when you are debugging an activity. The “Reset” button kicks out all currently logged in
clients and reloads the client interface.
The lower part of the Control Center displays messages when a participant joins or leaves the
activity. To broadcast a message to all the participants, click on the field at the bottom, type
your message and press Broadcast Message.

Troubleshooting
I started a HubNet activity, but when participants open a HubNet Client, my
activity isn’t listed.

On some networks, the HubNet Client cannot automatically detect a HubNet server. Tell your
participants to manually enter the server address and port of your HubNet server, which
appear in the HubNet Control Center.
Note: The technical details on this are as follows. In order for the client to detect the server,
multicast routing must be available between them. Not all networks support multicast routing.
In particular, networks that use the IPsec protocol typically do not support multicast. The
IPsec protocol is used on many Virtual Private Networks (VPNs).

When a participant tries to connect to an activity, nothing happens (the client
appears to hang or gives an error saying that no server was found).
If your computer or network has a firewall, it may be impeding the HubNet server from
communicating. Make sure that your computer and network are not blocking ports used by
the HubNet server (ports 9173-9180).

The view on the HubNet client is gray.
Verify that the “Mirror 2D view on clients” checkbox in the HubNet Control Center is
selected.
Make sure that the display switch in the model is on.
If you have made changes to the size of the view on the server you may need to press
the “Reset” button in the Control Center to ensure the clients get the new size.

There is no view on the HubNet client.
Some activities don’t have a view on the client. If you want to add a view simply select
“HubNet Client Editor” from the Tools Menu and add a view like any other widget. Make sure
to press the “Reset” button before having clients log in.

I can’t quit a HubNet client.
You will have to force the client to quit. On OS X, force quit the application by selecting Force
Quit… in the Apple menu. On Windows, press Ctrl-Alt-Delete to open the Task Manager,
select HubNet Client and press End Task.

My computer went to sleep while running a HubNet activity. When I woke the
computer up, I got an error and HubNet wouldn’t work anymore.
The HubNet server may stop working if the computer goes to sleep. If this happens, quit the
NetLogo application and start over. Change the settings on your computer so it won’t sleep
again.

My problem is not addressed on this page.
See Contacting Us.

Known Limitations
If HubNet malfunctions, see the bug reporting information atContacting Us.

Please note that:
HubNet has not yet been extensively tested with large numbers of clients (i.e. more
than about 25). Unexpected results may occur with more clients.
Out-of-memory conditions are not handled gracefully
Sending large amounts of plotting messages to the clients can take a long time.
NetLogo does not handle malicious clients in a robust manner (in other words, it is likely
vulnerable to denial-of-service type attacks).
Performance does not degrade gracefully over slow or unreliable network connections.
If you are on a wireless network or sub-LAN, the IP address in the HubNet Control
Center is not always the entire IP address of the server.
Computer HubNet has only been tested on LANs, and not on dial-up connections or
WANs.

Teacher workshops
For information on upcoming workshops and NetLogo and HubNet use in the classroom,
please contact us.

HubNet Authoring Guide
To learn about authoring or modifying HubNet activities, see the HubNet Authoring Guide.

Running HubNet in headless mode
To learn about running HubNet activities from the command line, with no GUI on the server,
see the HubNet section in the Controlling Guide.

Getting help
If you have any questions about HubNet or need help getting started,contact us.

HubNet Authoring Guide
NetLogo 6.0.4 User Manual

This guide shows how to understand and modify the code of existing HubNet activities and
write your own new ones. It assumes you are familiar with running HubNet activities, basic
NetLogo code and NetLogo interface elements. For more general information about HubNet
see the HubNet Guide.

Coding HubNet activities
Many HubNet activities will share bits of the same code. That is the code that it used to setup
the network and the code that is used to receive information from and send information to the
clients. If you understand this code you should be able to easily make modifications to
existing activities and you should have a good start on writing your own activities. To get you
started we have provided a Template model (in HubNet Activities -> Code Examples) that
contains the most basic components that will be in the majority of HubNet activities. You
should be able to use this activity as a starting point for most projects.
Code Example: Template

Setup
To make a NetLogo model into a HubNet activity you must first initialize the network. In most
HubNet activities you will use the startup procedure to initialize the network. startup is a
special procedure that NetLogo runs automatically when you open any model. That makes it a
good place to put code that you want to run once and only once (no matter how many times
the user runs the model). For HubNet we put the command that initializes the network in
startup because once the network is setup we don’t need to do so again. We initialize the
system using hubnet-reset , which will ask the user for a session name and open up the
HubNet Control Center. Here is the startup procedure in the template model:
to startup
hubnet-reset
end

Now that the network is all setup you don’t need to worry about callinghubnet-reset again.
Take a look at the setup procedure in the template model:
to setup
cp
cd
clear-output
ask turtles
[
set step-size 1
hubnet-send user-id "step-size" step-size
]
end

For the most part it looks like most other setup procedures, however, you should notice that it
does not call clear-all. In this model, and in the great majority of HubNet activities in the
Models Library, we have a breed of turtles that represent the currently logged in clients. In this
case we’ve called this breed students. Whenever a client logs in we create a student and

record any information we might need later about that client in a turtle variable. Since we don’t
want to require users to log out and log back in every time we setup the activity we don’t want
to kill all the turtles, instead, we want to set all the variables back to initial values and notify
the clients of any changes we make (more on that later).

Receiving messages from clients
During the activity you will be transferring data between the HubNet clients and the server.
Most HubNet activities will call a procedure in the go loop that checks for new messages from
clients in this case it’s called listen clients:
to listen-clients
while [ hubnet-message-waiting? ]
[
hubnet-fetch-message
ifelse hubnet-enter-message?
[ create-new-student ]
[
ifelse hubnet-exit-message?
[ remove-student ]
[ execute-command hubnet-message-tag ]
]
]
end

As long as there are messages in the queue this loop fetches each message one at a time.
hubnet-fetch-message makes the next message in the queue the current message and sets
the reporters hubnet-message-source, hubnet-message-tag and hubnet-message to the
appropriate values. The clients send messages when the users login and logout any time the
user manipulates one of the interface elements, that is, pushes a button, moves a slider,
clicks in the view, etc. We step through each message and decide what action to take
depending on the type of message (enter, exit, or other), the hubnet-message-tag (the name
of the interface element), and the hubnet-message-source of the message (the name of the
client the message came from).
On an enter message we create a turtle with auser-id that matches the hubnet-messagesource which is the name that each user enters upon entering the activity, it is guaranteed to
be unique.
to create-new-student
create-students 1
[
set user-id hubnet-message-source
set label user-id
set step-size 1
send-info-to-clients
]
end

At this point we set any other client variables to default values and send them to the clients if
appropriate. We declared a students-own variable for every interface element on the client
that holds state, that is, anything that would be a global variable on the server, sliders,
choosers, switches and input boxes. It is important to make sure that these variables stay
synchronized with the values visible on the client.
When the clients logout they send an exit message to the server which gives you a chance to
clean up any information you have been storing about the client, in this case we merely have
to ask the appropriate turtle to die.

to remove-student
ask students with [user-id = hubnet-message-source]
[ die ]
end

All other messages are interface elements identified by thehubnet-message-tag which is the
name that appears in the client interface. Every time an interface element changes a
message is sent to the server. Unless you store the state of the values currently displayed in
the client interface will not be accessible in other parts of the model. That’s why we’ve
declared a students-own variable for every interface element that has a state (sliders,
switches, etc). When we receive the message from the client we set the turtle variable to the
content of the message:
if hubnet-message-tag = "step-size"
[
ask students with [user-id = hubnet-message-source]
[ set step-size hubnet-message ]
]

Since buttons don’t have any associated data there is generally no associated turtle variable,
instead they indicate an action taken by the client, just as with a regular button there is often
procedure associated with each button that you call whenever you receive a message
indicating the button has been pressed. Though it is certainly not required, the procedure is
often a turtle procedure, that is, something that the student turtle associated with the message
source can execute:
if command = "move left"
[ set heading 270
fd 1 ]

Sending messages to clients
As mentioned earlier you can also send values to any interface elements that display
information: monitors, sliders, switches, choosers, and input boxes (note that plots and the
view are special cases that have their own sections).
There are two primitives that allow you to send information hubnet-send and hubnetbroadcast. Broadcast sends the information to all the clients; send sends to one client, or a
selected group.
As suggested earlier, nothing on the client updates automatically. If a value changes on the
server, it is your responsibility as the activity author to update monitors on the client.
For example, say you have a slider on the client called step-size and a monitor called Step
Size (note that the names must be different) you might write updating code like this:
if hubnet-message-tag = "step-size"
[
ask student with [ user-id = hubnet-message-source ]
[
set step-size hubnet-message
hubnet-send user-id "Step Size" step-size
]
]

You can send any type of data you want, numbers, strings, lists, lists of lists, lists of strings,

however, if the data is not appropriate for the receiving interface element (say, if you were to
send a string to a slider) the message will be ignored. Here are a few code examples for
different types of data:
data
type

hubnet-broadcast

number

hubnet-broadcast "A" 3.14

hubnet-send "jimmy" "A" 3.14

string

hubnet-broadcast "STR1" "HI THERE"

hubnet-send ["12" "15"] "STR1" "HI
THERE"

example

hubnet-send

example

list of
hubnet-broadcast "L2" [1 2 3]
numbers

hubnet-send hubnet-message-source
"L2" [1 2 3]

matrix of hubnet-broadcast "[A]" [[1 2] [3
numbers 4]]

hubnet-send "susie" "[A]" [[1 2] [3
4]]

list of
strings

hubnet-broadcast "user-names"
[["jimmy" "susie"] ["bob"
"george"]]

hubnet-send "teacher" "user-names"
[["jimmy" "susie"] ["bob" "george"]]

Examples
Study the models in the “HubNet Activities” section of the Models Library to see how these
primitives are used in practice in the Code tab. Disease is a good one to start with.

How to make a client interface
Open the HubNet Client Editor, found in the Tools Menu. Add any buttons, sliders, switches,
monitors, plots, choosers, or notes that you want just as you would in the interface tab. You’ll
notice that the information you enter for each of the widgets is slightly different than in the
Interface panel. Widgets on the client don’t interact with the model in the same way. Instead
of a direct link to commands and reporters the widgets send messages back to the server and
the model then determines how those messages affect the model. All widgets on the client
have a tag which is a name that uniquely identifies the widget. When the server receives a
message from that widget the tag is found in hubnet-message-tag.
For example, if you have a button called “move left”, a slider called “step-size”, a switch called
“all-in-one-step?”, and a monitor called “Location:”, the tags for these interface elements will
be as follows:
interface
element

tag

move left

step-size

all-in-one-step?

Location:

Note that you can only have one interface element with a specific name. Having more than
one interface element with the same tag in the client interface will result in unpredictable

behavior since it is not clear which element you intended to send the information to.

View updates on the clients
View mirroring lets views of the world be displayed in clients as well on the server. View
mirroring is enabled using a checkbox in the HubNet Control Center.
When mirroring is enabled, client views update whenever the view on the server does. To
avoid excessive network traffic, the view should not update more often than necessary.
Therefore we strongly recommend using tick-based updates, rather than continuous updates.
See the View Updates section of the Programming Guide for an explanation of the two types
of updates.
With tick-based updates, updates happen when a tick or display command runs. We
recommend using these commands only inside an every block, to limit the frequency of view
updates and thus also limit network traffic. For example:
every 0.1
[
display
]

If there is no View in the clients or if the Mirror 2D View on Clients checkbox in the HubNet
Control Center is not checked, then no view updates are sent to the clients.

Clicking in the view on clients
If the View is included in the client, two messages are sent to the server every time the user
clicks in the view. The first message, when the user presses the mouse button, has the tag
“View”. The second message, sent when the user releases the mouse button, has the tag
“Mouse Up”. Both messages consist of a two item list of the x and y coordinates. For example,
to turn any patch that was clicked on by the client red, you would use the following NetLogo
code:
if hubnet-message-tag = "View"
[
ask patches with [ pxcor = (round item 0 hubnet-message) and
pycor = (round item 1 hubnet-message) ]
[ set pcolor red ]
]

Customizing the client’s view
When view mirroring is enabled, by default clients see the same view the activity leader sees
on the server. But you can change this so that each client sees something different, not just a
literal “mirror”.
You can change what a client sees in two distinct ways. We call them “client perspectives”
and “client overrides”.
Changing a client’s perspective means making it “watch” or “follow” a particular agent, much
like the watch and follow commands that work with ordinary NetLogo models. See the
dictionary entries for hubnet-send-watch , hubnet-send-follow , and hubnet-reset-perspective .

Code Example: Client Perspective Example
Client overrides let you change the appearance of patches, turtles, and links in the client
views. You can override any of the variables affecting an agent’s appearance, including the
hidden? variable causing a turtle or link to be visible or invisible. See the dictionary entries for
hubnet-send-override, hubnet-clear-override, and hubnet-clear-overrides .
Code Example: Client Overrides Example

Plot updates on the clients
If plot mirroring is enabled (in the HubNet Control Center) and a plot in the NetLogo model
changes and a plot with the exact same name exists on the clients, a message with that
change is sent to the clients causing the client’s plot to make the same change. For example,
let’s pretend there is a HubNet model that has a plot called Milk Supply in NetLogo and the
clients. Milk Supply is the current plot in NetLogo and in the Command Center you type:
plot 5

This will cause a message to be sent to all the clients telling them that they need to plot a
point with a y value of 5 in the next position of the plot. Notice, if you are doing a lot of plotting
all at once, this can generate a lot of plotting messages to be sent to the clients.

Modeling Commons Guide
NetLogo 6.0.4 User Manual

Introduction

The Modeling Commons (http://modelingcommons.org/) is a Web-based collaboration system for
NetLogo modelers. Users of the Modeling Commons can share, download, modify, create variations
of, comment on, and run NetLogo models – both those that are a part of the NetLogo models
library, and also those that have been uploaded by other NetLogo users.
By uploading your NetLogo models to the Modeling Commons, you make it easy for others to see,
review, and comment on your work. You can optionally keep the model private, either to yourself or
to a group of your choice, if you aren’t comfortable with letting everyone see the model. You can
always change the permissions associated with a model, if you change your mind later on.
NetLogo now makes it possible to save models to the Modeling Commons, just as you can save
them to .nlogo files on your own computer. You can access this functionality by selecting “Upload to
Modeling Commons” from the “File” menu.
Use of the Modeling Commons is free of charge. You may use it for your own personal work, for
your research group or company, or for a class in which you are a student or teacher. The Modeling
Commons is sponsored by the CCL, the same group that develops and distributes NetLogo.

Modeling Commons Accounts

In order to upload models to the Modeling Commons, you must first be a registered user.
Unregistered users can view and download models, but cannot upload, edit, or comment on them.
The first time that you invoke “Save to Modeling Commons” in NetLogo, you will be prompted to
enter your e-mail address and password. If you already have an account, then you can enter this
information and click on the “Login” button.
If you don’t yet have an account with the Modeling Commons, then you will need to create one.
Click on the “Create Account” button, and enter the requested information. Once you have done so,
click on the “Create Account” button. If there are no errors, then you will be prompted to upload a
NetLogo model. Alternatively, you may go to the Modeling Commons itself and register with your
Web browser.

Uploading Models

There are three ways to upload a model to the Modeling Commons: Uploading, updating, and
creating a child (“forking”). The following sections describe these in detail.

Upload A New Model
A new model will be created in the Modeling Commons, with its own page, description, and forum.
You should use this function the first time that you save a model to the Modeling Commons.

You must give your model a name. Model names are not required to be unique; you could have 2 or
more models with the same name, though we recommend that you not do this.
By default, anyone can view, fork, and update your model. You can restrict the ability to view and
fork your model by changing the visibility permission. You can restrict the ability to update your
model by changing the changeability permission. In order to set permissions for multiple people,
assign your model to a group, and then restrict visibility or changeability to members of that group.
Groups can be created from the Modeling Commons. Once you have uploaded your model, you can
edit the permissions from the model’s Modeling Commons page.
You can optionally upload a preview image to your model. The preview image will be displayed
alongside your model whenever it is shown on the Modeling Commons. While uploading a preview
image is optional, we highly recommend that you do so, in one of the following three ways:
The “Use current image” option tells NetLogo to use the current view as your preview. We
recommend that you first run the model, such that it shows off the key visual features.
The “Auto-generate image” feature auto-generates a preview image by running random-seed 0

setup repeat 75 [ go ] .

This option will only be enabled if you have definedsetup and go
procedures for NetLogo to run.
The “Image from file” feature allows you to upload any PNG image. Preview images work best
when they are square.

Upload A Child Of An Existing Model (“forking”)
Saving a model in this way, sometimes known as “forking,” does not change or overwrite the
original model. Rather, it creates a new model on the Modeling Commons, much as a plain “save”
would do, simultaneously creating a parent-child relationship between the old model and the new
one. This relationship can be seen on the “family” tab for a given model. You may fork any model for
which you have “view” permissions, including one that you cannot change. You may wish, for
example, to create a variation on a model in the NetLogo models library.

To fork a model, you must give your new child a name, as well as select an existing model to fork.
To indicate the existing model, start typing the name of the model that you would like to fork. Select
its name from among the search results.
Finally, you must enter a description about what you are changing in your child model, and how it
relates to its parent.

Updating An Existing Model
Use this option if you have improved a model that already exists in the Modeling Commons. Existing

attachments, discussions, and social tags will be preserved, but the model that users can display,
run, and download will be updated. You may only update a model for which you have “write”
permissions.
All versions of a model are saved in the Modeling Commons, so you should feel free to experiment
with new ideas. If something goes wrong, you can always refer to an old version from the “history”
tab on a model’s page.
To indicate which model should be updated, start typing the name of the model. Select the name
that pops up with the search results. Finally, enter a description about what you are changing in
your new version.

Logging
NetLogo 6.0.4 User Manual

NetLogo’s logging facility allows researchers to record student actions for later analysis.
Logging in NetLogo, once initiated, is invisible to the student. The researcher can choose the
type of events logged through a configuration file.
NetLogo uses the log4j package for logging. If you have previous experience with this package
you’ll find logging in NetLogo familiar.
Logging is supported only by the special NetLogo Logging application.

Starting logging
This depends on what operating system you are using.

Mac OS X or Windows
There is a special logging launcher in the NetLogo directory called NetLogo Logging. Double
click on the icon.
On Windows, the NetLogo directory can be found atC:\Program Files, unless you chose a
different location when you installed NetLogo.

Linux and others
To enable logging, invoke the netlogo.sh script as follows:
netlogo.sh --logging netlogo_logging.xml

You could also modify the script to include these flags, or copy the script and modify the copy.
You can replace netlogo_logging.xml with any valid log4j XML configuration file, which will be
discussed in more detail later.

Using logging
When NetLogo starts up it will ask for a user name. This name will appear in all the logs
generated during this session.

Where logs are stored
Logs are stored in the OS-specific temp directory. On most Unix-like systems that is/tmp. On
Windows Vista the logs can be found in c:\Users\\AppData\Local\Temp, where is
the logged in user. On Mac OS X, the temp directory varies for each user. You can determine
your temp directory by opening the Terminal application and typing echo $TMPDIR > at the
prompt.
There are two convenience commands that will help you manage the logs.__zip-log-files
filename will gather all the logs in the temp directory and put them in one zip file, at the

location specified. After doing __zip-log-files the existing logs are not deleted, you can do
so explicitly by using __delete-log-files.
The following is a chart describing the name of the loggers available, the type of events each
logs, at what level, and provides a sample output using the XMLLayout. All the loggers are
found in org.nlogo.log.Logger. When referring to the loggers in the configuration file you
should use the fully qualified name. So, for example, the logger GLOBALS would actually be
org.nlogo.log.Logger.GLOBALS

Logger

Events

Level

Example

a global variable info,
changes
debug

FOO
51.0

GREENS

sliders,
switches,
choosers, input
boxes are
changed
through the
interface

info

changed
foo
51.0

0.0
100.0
1.0

CODE

code is
compiled,
including:
command
center, Code
tab, slider
bounds, and
buttons

info

compiled
crt 1
O
success

info

added

GLOBALS

a widget is
added or
WIDGETS
removed from
the interface

a button is
BUTTONS pressed or

info

show 1

Logger released
Events

SPEED

TURTLES

LINKS

the speed slider
changes

turtles die or
are born

links die or are
born

Level

released
Example
once

info

0.0

info

turtle 1
born
TURTLES

info

link 2 7
born
LINKS

How to configure the logging output
The default logging configuration (netlogo_logging.xml) looks something like this:
NetLogo defines 8 loggers, all descend directly from the root logger, which means unless you
explicitly set the properties (appender, layout, and output level) in the configuration they will
inherit them from the root. In the default configuration the root is set to level INFO, the
appender is org.nlogo.log.XMLFileAppender and layout is org.nlogo.log.XMLLayout. Together
these generate a nicely formatted XML file as defined in the netlogo_logging.dtd which is
based on the log4j dtd. If the appender is a FileAppender (including the XMLFileAppender) a
new file is start each time the user opens a model.

This configuration, first defines an appender named “A1” of type XMLFileAppender with an
XMLLayout. The appender defines where the logging data goes, in this case the data goes
into a file. In fact, if NetLogo is given a FileAppender it will automatically start a new file every
time the user opens a new model. The XMLFileAppender also does some formatting and
writes the appropriate headers to the file. The layout defines how to write each individual
message. Unless you are an advanced user there is no need change (or worry about) the
appender or the layout.
At the end of the configuration notice the definition of the root logger. All of the other loggers
descend from the root logger and, thus, inherit the properties of the root unless explicitly set.
This case is fairly simple, having set up the appender A1 we make that the default appender
for the root (and all other loggers) and make the default priority “INFO”. Messages that are
logged at the INFO level or higher will be written, messages logged at lower levels will not.
Note that with only one exception NetLogo always logs at level INFO. Sets to globals that don’t
change the value of the global are logged at level DEBUG. Which means that these messages
are disabled by default, since debug is lower level than info. The rest of the body of the
configuration file overrides properties of the root logger in a few specific loggers (or categories
as they are known in the configuration file, the terms can be assumed to be synonymous for
the proposes of this document). That is it turns off the WIDGET, TURTLES, and LINKS
loggers, by default. To re-enable them you can changes the priority from off to info, like this:

or you can simply remove the entire reference to the category from the configuration file, as it
is not serving any other purpose.

Advanced Configuration
This is only a basic introduction to configuration files for logging in NetLogo. There are many
more configuration options available through the log4j framework. See the log4j
documentation.

Controlling Guide
NetLogo 6.0.4 User Manual

NetLogo can be invoked and controlled by another program running on the Java Virtual
Machine. For example, you might want to call NetLogo from a small program that does
something simple like automate a series of model runs. Or, you might want to embed
NetLogo models in a larger application.
For more information, go here.

Mathematica Link
NetLogo 6.0.4 User Manual

The NetLogo-Mathematica link provides modelers with an easy to use, real-time link between
NetLogo and Mathematica. Together, these tools can provide users with a highly interactive,
self-documenting work flow that neither can provide alone.
Mathematica includes many of the tools that agent-based modelers rely on throughout the
research process: advanced import capabilities, statistical functions, data visualization, and
document creation. With the NetLogo-Mathematica link, you can run all of these tools side-byside with NetLogo.
Because all Mathematica documents, or notebooks, contain comments, code, images,
annotations, and interactive objects, the integration of NetLogo and Mathematica provides a
more complete solution for complex model exploration for students and researchers alike.
The basic functionality of the link is much like the NetLogo Controlling API: you can load
models, execute commands, and report back data from NetLogo. Unlike the Controlling API,
which is based on Java, all interactions with the link are interpreted, making it ideal not only
for rapidly designing custom BehaviorSpace-like experiments, but also as a companion to
NetLogo in debugging your model.
For more information about Mathematica, please visit the Wolfram Research web site.

What can I do with it?
Here are a few examples of what you can do with the Mathematica-NetLogo link.
Analyze your model in real-time with seamless two-way data conversion
Develop high quality, custom visualizations of model data
Collect detailed simulation data across large multi-dimensional parameter spaces
Rapidly develop interactive interfaces for exploring model behavior
Have direct access to patches and network data with built-in functions

Installation
The NetLogo-Mathematica link supports Mathematica 10 or greater. To install the NetLogoMathematica link:
1.
2.
3.
4.
5.
6.
7.
8.

Go to the menu bar in Mathematica
Click on File and select Install…
In the Install Mathematica Item dialog
Select Package for Type of item to install
Click Source, and select From file…
In the file browser, go to the location of your NetLogo installation,
click on the Mathematica Link subfolder, and select NetLogo.m.
For Install Name, enter NetLogo.

You can either install the NetLogo link in your user base directory or in the system-wide
directory. If the NetLogo link is installed in the user base directory, other users on the system
must also go through the NetLogo-Mathematica link installation process to use it. This option
might be preferable if you do not have permission to modify files outside of your home
directory. Otherwise, you can install NetLogo-Mathematica link in the system-wide
Mathematica base directory.

Usage
This section will very briefly introduce how to use the NetLogo-Mathematica Link. It will show
you how to load the NetLogo-Mathematica Link package, start NetLogo, execute commands,
and retrieve data from NetLogo.
Loading the package: Once the NetLogo-Mathematica link is installed, you can load the
package by entering the following into your Mathematica notebook:
<-at
turtles-at dx dy dz
-at dx dy dz

Since 4.1

3D versions of turtles-at and breeds-at.
Reports an agentset containing the turtles on the patch (dx, dy, dz) from the caller
(including the caller itself if it's a turtle).
;; suppose I have 40 turtles at the origin
show [count turtles-at 0 0 0] of turtle 0
=> 40

world-depth

Since 4.1

world-depth
Reports the total depth of the NetLogo world.
The depth of the world is the same as max-pzcor - min-pzcor + 1.
See also max-pzcor, min-pzcor, world-width, and world-height

zcor
zcor

This is a built-in turtle variable. It holds the current z coordinate of the turtle. This is a
floating point number, not an integer. You can set this variable to change the turtle's
location.
This variable is always greater than or equal to (- screen-edge-z) and strictly less than
screen-edge-z.
See also setxy, xcor, ycor, pxcor, pycor, pzcor

zoom

Since 4.1

zoom number

Move the observer toward the point it is facing, number steps. The observer will never
move beyond the point it is facing so if number is greater than the distance to that point it
will only move as far as the point it is facing.

Extensions Guide
NetLogo 6.0.4 User Manual

NetLogo allows users to write new commands and reporters in Java and other languages and
use them in their models. This section of the User Manual introduces this facility and shows
how to use an extension in your model once you have obtained or made one.
Extensions created by members of the NetLogo community are available from
https://github.com/NetLogo/NetLogo/wiki/Extensions.
For information on creating your own extensions, go here.

Using Extensions
To use an extension in a model, add the extensions keyword at the beginning of the Code
tab, before declaring any breeds or variables.
After extensions comes a list of extension names in square brackets. For example:
extensions [sound speech]

Using extensions tells NetLogo to find and open the specified extension and makes the
custom commands and reporters found in the extension available to the current model. You
can use these commands and reporters just as if they were built-in NetLogo primitives.

Where extensions are located
NetLogo will look for extensions in several places:
1. In the folder of the current model.
2. The extensions folder located with the NetLogo installation. For typical NetLogo
installations:
On Mac OS X: /Applications/NetLogo 6.0.4/extensions
On 64-bit Windows with 64-bit NetLogo or 32-bit Windows with 32-bit NetLogo:
C:\Program Files\NetLogo 6.0.4\app\extensions
On 64-bit Windows with 32-bit NetLogo: C:\Program Files (x86)\NetLogo
6.0.4\app\extensions
On Linux: the app/extensions subdirectory of the NetLogo directory extracted
the installation .tgz

from

Each NetLogo extension consists of a folder with the same name as the extension, entirely in
lower case. This folder must contain a JAR file with the same name as the folder. For
example, the sound extension is stored in a folder called sound with a file inside called
sound.jar.
To install a NetLogo extension for use by any model, put the extension’s folder in the NetLogo
extensions directory. Or, you can just keep the extension’s folder in the same folder as the
model that uses it.
Some extensions depend on additional files. These files will be in the extension’s folder along
with the JAR file. The folder may also contain other files such as documentation and example
models.

NetLogo Arduino Extension
Using
For a first use without compiling code, do the following:
1.

Acquire the NetLogo software. The Arduino extension comes pre-installed with
NetLogo 5.2.1 and later.

Acquire an Arduino board and install the arduino IDE

Use the Arduino IDE to edit the Sketch (if desired) and send to the board. (See
elaborate comments in the sketch for recommendations about what to comment
out/leave in depending on your setup & circuit on the board.)

Once the Arduino has the sketch loaded on it, it will run that sketch whenever it is
powered on.

Open the test “Arduino Example” model in the NetLogo Models library (it’s in the
“IABM Textbook” > “Chapter 8” folder)

Connect the Arduino to a USB port on the computer if it is not still connected from
step 3.

Press OPEN to choose the port to communicate with and establish the connection.

Use the buttons to send byte commands; use the interface to inspect variable
value(s) that your sketch is sending.

Note that by typing arduino:primitives you can get a list of the available commands
in the extension.

Notes
A NetLogo model using this extension must work in conjunction with an Arduino Sketch.
These two endpoints communicate by way of an application protocol that they define. For
example, if the NetLogo model sends a byte ‘1’ over the wire this may mean something to
the Arduino Sketch, which will respond accordingly. The Arduino Sketch for its own part
may send name-value pairs over the serial port, which then can be looked up
asynchronously by the NetLogo model.
The modeler is free to build as simple or as complex an application protocol on top of this
raw communication mechanism.
The asynchronous nature of the board-to-computer communications has one notable
limitation. If you choose to try to simulate a synchronous, BLOCKING READ
communications pattern, (e.g., by sending a byte-based signal to the board, which triggers
a response in a known name-value pair), then you are likely to be ‘off by one’ response.
That is, if you do the following in NetLogo code:
arduino:write-byte b
show arduino:get "varname"

You are likely to get the value ofvarname from the PRIOR command represented by

writing the byte b. This is because the second line of NetLogo code will execute while the
Arduino is off generating a new value for varname .
There are ways of getting around this (simulating a blocking interface by polling on a value
to indicate fresh “news” on varname ). But this extension works best in settings where the
Arduino Sketch is “chatty” and the NetLogo model samples this stream when it needs
data.

Compatibility
This code has been tested on Windows 7 and 10 with 32-bit NetLogo and on Mac OS X.
You are likely to encounter issues when running this with 64-bit NetLogo in Windows 8 or
Windows 10, so if you have Windows 8 or 10, please download the 32-Bit version of
NetLogo if you plan on using the Arduino extension. We strive for cross-platform
compatibility across Mac, Win, and Linux. So if you have troubles, please let us know.

Questions
If you run into problems or have questions about the extension, please emailccl-feedback
or cbrady@inquirelearning.com.

Primitives
arduino:primitives arduino:ports arduino:open arduino:close arduino:get arduino:writestring arduino:write-int arduino:write-byte arduino:is-open? arduino:debug-to-arduino
arduino:debug-from-arduino

arduino:primitives
arduino:primitives
Reports a list of primitives available in the extension, with basic hints about their syntax.

arduino:ports
arduino:ports
Reports a list of port names

arduino:open
arduino:open port-name
Opens the port named port-name.

arduino:close
arduino:close
Closes the currently open port.

arduino:get
arduino:get var-name
Reads and reports the value associated with var-name on the Arduino board. If there is no
value associated with var-name, returns false. Note: var-name is case insensitive.

arduino:write-string
arduino:write-string string-message
Writes a string message to the currently open port.

arduino:write-int
arduino:write-int int-message
Writes a integer message to the currently open port.

arduino:write-byte
arduino:write-byte byte-message
Writes a byte message to the currently open port.

arduino:is-open?
arduino:is-open?
Reports a boolean value (true or false) indicating if a port is open.

arduino:debug-to-arduino
arduino:debug-to-arduino
Reports a list of the last messages sent from NetLogo to the Arduino, up to a maximum of
5 messages. Each entry in this list is a string beginning with “s:” if the message sent was a
string, “i:” if the message sent was an int, and “b:” if the message sent was a byte.

arduino:debug-from-arduino
arduino:debug-from-arduino
Reports a list of lists containing any errant messages sent from NetLogo to the Arduino, up
to a maximum of 10 errant messages. Each sublist contains the raw message as its first
element and a message describing the error as the second element.

NetLogo Array Extension
Using
The array extension is pre-installed in NetLogo.
To use the array extension in your model, add a line to the top of your Code tab:
extensions [array]

If your model already uses other extensions, then it already has anextensions line in it, so
just add array to the list.
For more information on using NetLogo extensions, see theExtensions Guide

When to Use
In general, anything you can do with an array in NetLogo, you could also just use a list for.
But you may want to consider using an array instead for speed reasons. Lists and arrays
have different performance characteristics, so you may be able to make your model run
faster by selecting the appropriate data structure.
Arrays are useful when you need a collection of values whose size is fixed. You can
quickly access or alter any item in an array if you know its position.
Unlike NetLogo’s lists and strings, arrays are “mutable”. That means that you can actually
modify them directly, rather than constructing an altered copy as with lists. If the array is
used in more than one place in your code, any changes you make will show up
everywhere. It’s tricky to write code involving mutable structures and it’s easy to make
subtle errors or get surprising results, so we suggest sticking with lists and strings unless
you’re certain you want and need mutability.

Example use of Array Extension
let a array:from-list n-values 5 [0]
print a
=> {{array: 0 0 0 0 0}}
print array:length a
=> 5
foreach n-values 5 [ i -> i ] [ i -> array:set a i i * i ]
print a
=> {{array: 0 1 4 9 16}}
print array:item a 0
=> 0
print array:item a 3
=> 9
array:set a 3 50
print a
=> {{array: 0 1 4 50 16}}

Primitives
array:from-list array:item array:set array:length array:to-list

array:from-list

array:from-list
array:from-list list
Reports a new array containing the same items in the same order as the input list.

array:item
array:item array index
Reports the item in the given array with the given index (ranging from zero to the length of
the array minus one).

array:set
array:set array index value
Sets the item in the given array with the given index (ranging from zero to the length of
the array minus one) to the given value.
Note that unlike the replace-item primitive for lists, a new array is not created. The given
array is actually modified.

array:length
array:length array
Reports the length of the given array, that is, the number of items in the array.

array:to-list
array:to-list array
Reports a new list containing the same items in the same order as the given array.

NetLogo Bitmap Extension
Using
The bitmap extension is pre-installed in NetLogo. For instructions on using it, or for more
information about NetLogo extensions, see the NetLogo User Manual.

What does the Bitmap Extension do?
The Bitmap Extension allows you to manipulate and import images into the drawing and
patches. It offers features not provided by the NetLogo core primitives, such as: scaling,
manipulation of different color channels, and width and height reporters.

Getting started
To import and manipulate images you will need to include the bitmap extension in your
NetLogo model.
extensions[ bitmap ]

The image file formats supported are determined by your Java virtual machine’s imageio
library. Typically this is PNG, JPG, GIF, and BMP. PNG is a good, standard choice that is
likely to work everywhere.
If the image format supports transparency (alpha), that information will be imported as
well.

Primitives
bitmap:average-color bitmap:channel bitmap:copy-to-drawing bitmap:copy-to-pcolors
bitmap:difference-rgb bitmap:export bitmap:from-view bitmap:to-grayscale bitmap:height
bitmap:import bitmap:scaled bitmap:width

bitmap:average-color
bitmap:average-color image
Reports a 3-element list describing the amount of R, G, and B inimage, by summing
across all pixels, and normalizing each component by the number of pixels in the image,
so each component ranges from 0 to 255.

bitmap:channel
bitmap:channel image channel
Extracts either the alpha, red, green, or blue channel from an image. The inputchannel
should be an integer 0-3 indicating the channel to remove (alpha=0, red=1, green=2,
blue=3). The resulting image is a grayscale image representing specified channel.

bitmap:copy-to-drawing
bitmap:copy-to-drawing image x y
Imports the given image into the drawing without scaling the image at the given pixel
coordinates.

bitmap:copy-to-pcolors
bitmap:copy-to-pcolors image boolean
Imports the given image into the pcolors, scaled to fit the world. The second input
indicates whether the colors should be interpreted as NetLogo colors or left as RGB
colors. false means RGB colors.

bitmap:difference-rgb
bitmap:difference-rgb image1 image2
Reports an image that is the absolute value of the pixel-wise RGB difference between two
images. Note that image1 and image2 MUST be the same width and height as each other,
or errors will ensue.

bitmap:export
bitmap:export image filename
Writes image to filename.

bitmap:from-view
bitmap:from-view
Reports an image of the current view.

bitmap:to-grayscale
bitmap:to-grayscale image
Converts the given image to grayscale.

bitmap:height
bitmap:height image
Reports the height of given image

bitmap:import

bitmap:import filename
Reports a LogoBitmap containing the image at filename.

bitmap:scaled
bitmap:scaled image width height
Reports a new image that is image scaled to the given width and height

bitmap:width
bitmap:width image
Reports the width of the given image

NetLogo Cf Extension
Primitives
cf:ifelse cf:ifelse-value

cf:ifelse
cf:ifelse condition consequent conditions/consequents optional-else
Runs the first command block following a true condition:
let x 3
(cf:ifelse
x < 2 [ print
x < 4 [ print
x < 6 [ print
[ print

"x
"x
"x
"x

is
is
is
is

less than 2!" ]
less than 4!" ]
less than 6!" ]
greater than or equal to 6!" ])

The above code will print out x is less than 4! since that’s the first case with a true
condition.
A final command block without a matching condition may be provided, in which case it will
run if no other command blocks do. If no such command block is provided and no
conditions are true, nothing will happen.
The default number of arguments is 3, so that if you only have one condition, a
consequent, and an else block (like a regular NetLogo ifelse), you do not need
parentheses:
cf:ifelse 0 < 1 [ print "hi" ] [ print "bye" ]

cf:ifelse-value
cf:ifelse-value condition consequent conditions/consequents else-reporter
Runs the first reporter following a true condition and reports its value:
(cf:ifelse-value
x < 2 [ "x is less than 2!" ]
x < 4 [ "x is less than 4!" ]
x < 6 [ "x is less than 6!" ]
[ "x is greater than or equal to 6!" ])

The above code will report x is less than 4! since that’s the first case with a true
condition.
Unlike cf:ifelse, the else-block is required in cf:ifelse-value. If no condition is true, the
result of the else block will be reported.
Note that cf:ifelse-value has somewhat different associativity than NetLogo’s ifelse,
making it so that you don’t need to put parentheses around the conditions, as in the above

example.
The default number of arguments is 3, so that if you only have one condition, a
consequent, and an else block (like a regular NetLogo ifelse-value ), you do not need
parentheses:
cf:ifelse-value 0 < 1 [ "hi" ] [ "bye" ]

NetLogo Csv Extension
Common use cases and examples
Read a file all at once
Just use csv:from-file "/path/to/myfile.csv"! See from-file for more information.

Read a file one line at a time
For really big files, you may not want to store the entire file in memory, but rather just process it a line at a
time. For instance, if you want to sum each of the columns of a numeric CSV file, you can do:
to-report sum-columns [ file ]
file-open file
set result csv:from-row file-read-line
while [ not file-at-end? ] [
let row csv:from-row file-read-line
set result (map [?1 + ?2] result row)
]
file-close
report result
end

You can also use this technique to…

Read a file one line per tick
Here’s an example model that reads in a file one line per tick:
globals [ data ]
to setup
clear-all
file-close-all % Close any files open from last run
file-open "data.csv"
% other setup goes here
reset-ticks
end
to go
if file-at-end? [ stop ]
set data csv:from-row file-read-line
% model update goes here
tick
end

Write a file
Just use csv:to-file "/path/to/myfile.csv" my-data! See to-file for more information.

Primitives
Formatting NetLogo data as CSV
csv:to-row csv:to-string csv:to-file

Parsing CSV input to NetLogo data
csv:from-row csv:from-string csv:from-file

csv:from-row
csv:from-row string
csv:from-row string delimiter

Parses the given string as though it were a row from a CSV file and returns it as a list of values. For example:
observer> show csv:from-row "one,two,three"
observer: ["one" "two" "three"]

Quotes can be used when items contain commas:
observer> show csv:from-row "there's,a,comma,\"in,here\""
observer: ["there's" "a" "comma" "in,here"]

You can put two quotes in a row to put an actual quote in an entry. If the entry is not quoted, you can just use
one quote:
observer> foreach (csv:from-row "he said \"hi there\",\"afterwards, she said \"\"hello\"\"\"") print
he said "hi there"
afterwards, she said "hello"

Number-like-entries will be parsed as numbers:
observer> show csv:from-row "1,-2.5,1e3"
observer: [1 -2.5 1000]

true

and false with any capitalization will be parsed as booleans:

observer> show csv:from-row "true,TRUE,False,falsE"
observer: [true true false false]

To use a different delimiter, you can specify a second, optional argument. Only single character delimiters are
supported:
observer> show (csv:from-row "1;2;3" ";")
observer: [1 2 3]

Different types of values can be mixed freely:
observer> show csv:from-row "one,2,true"
observer: ["one" 2 true]

csv:from-string
csv:from-string string
csv:from-string string delimiter
Parses a string representation of one or more CSV rows and returns it as a list of lists of values. For example:
observer> show csv:from-string "1,two,3\nfour,5,true"
observer: [[1 "two" 3] ["four" 5 true]]

csv:from-file
csv:from-file csv-file
csv:from-file csv-file delimiter
Parses an entire CSV file to a list of lists of values. For example, if we have a fileexample.csv that contains:
1,2,3
4,5,6
7,8,9
10,11,12

Then, we get:

observer> show csv:from-file "example.csv"
observer: [[1 2 3] [4 5 6] [7 8 9] [10 11 12]]

The parser doesn’t care if the rows have different numbers of items on them. The number of items in the rows
list will always be + 1 , though blank lines are skipped. This makes handling files with
headers quite easy. For instance, if we have header.csv that contains:
My Data
2/1/2015
Parameters:
start,stop,resolution,population,birth?
0,4,1,100,true
Data:
time,x,y
0,0,0
1,1,1
2,4,8
3,9,27

This gives:
observer>
observer:
observer:
observer:
observer:
observer:
observer:
observer:
observer:
observer:
observer:
observer:

foreach csv:from-file "header.csv" show
["My Data"]
["2/1/2015"]
["Parameters:"]
["start" "stop" "resolution" "population" "birth?"]
[0 4 1 100 true]
["Data:"]
["time" "x" "y"]
[0 0 0]
[1 1 1]
[2 4 8]
[3 9 27]

csv:to-row
csv:to-row list
csv:to-row list delimiter
Reports the given list as a CSV row. For example:
observer> show csv:to-row ["one" 2 true]
observer: "one,2,true"

csv:to-string
csv:to-string list
csv:to-string list delimiter
Reports the given list of lists as a CSV string. For example:
observer> show csv:to-string [[1 "two" 3] [4 5]]
observer: "1,two,3\n4,5"

csv:to-file
csv:to-file csv-file list
csv:to-file csv-file list delimiter
Writes the given list of lists to a new CSV file. For example:
observer> csv:to-file "myfile.csv" [[1 "two" 3] [4 5]]

will result in a file myfile.csv containing:

1,two,3
4,5

NetLogo Gis Extension
Using
This extension adds GIS (Geographic Information Systems) support to NetLogo. It
provides the ability to load vector GIS data (points, lines, and polygons), and raster GIS
data (grids) into your model.
The extension supports vector data in the form of ESRI shapefiles. The shapefile (.shp)
format is the most common format for storing and exchanging vector GIS data. The
extension supports raster data in the form of ESRI ASCII Grid files. The ASCII grid file
(.asc or .grd) is not as common as the shapefile, but is supported as an interchange
format by most GIS platforms.

How to use
In general, you first define a transformation between GIS data space and NetLogo space,
then load datasets and perform various operations on them. The easiest way to define a
transformation between GIS space and NetLogo space is to take the union of the
“envelopes” or bounding rectangles of all of your datasets in GIS space and map that
directly to the bounds of the NetLogo world. See GIS General Examples for an example of
this technique.
You may also optionally define a projection for the GIS space, in which case datasets will
be re-projected to match that projection as they are loaded, as long as each of your data
files has an associated .prj file that describes the projection or geographic coordinate
system of the data. If no associated .prj file is found, the extension will assume that the
dataset already uses the current projection, regardless of what that projection is.
Once the coordinate system is defined, you can load datasets usinggis:load-dataset. This
primitive reports either a VectorDataset or a RasterDataset, depending on what type of file
you pass it.
A VectorDataset consists of a collection of VectorFeatures, each one of which is a point,
line, or polygon, along with a set of property values. A single VectorDataset may contain
only one of the three possible types of features.
There are several things you can do with a VectorDataset: ask it for the names of the
properties of its features, ask it for its “envelope” (bounding rectangle), ask for a list of all
VectorFeatures in the dataset, search for a single VectorFeature or list of VectorFeatures
whose value for a particular property is less than or greater than a particular value, or lies
within a given range, or matches a given string using wildcard matching (“*”, which
matches any number of occurrences of any characters). If the VectorFeatures are
polygons, you can also apply the values of a particular property of the dataset’s features to
a given patch variable.
There are also several things you can do with a VectorFeature from a VectorDataset: ask
it for a list of vertex lists, ask it for a property value by name, ask it for its centroid (center of
gravity), and ask for a subset of a given agentset whose agents intersect the given
VectorFeature. For point data, each vertex list will be a one-element list. For line data,
each vertex list will represent the vertices of a line that makes up that feature. For polygon
data, each vertex list will represent one “ring” of the polygon, and the first and last vertex
of the list will be the same. The vertex lists are made up of values of type Vertex, and the
centroid will be a value of type Vertex as well.

There are a number of operations defined for RasterDatasets as well. Mostly these involve
sampling the values in the dataset, or re-sampling a raster to a different resolution. You
can also apply a raster to a given patch variable, and convolve a raster using an arbitrary
convolution matrix.
Code Example: GIS General Examples has general examples of how to use the
extension
Code Example: GIS Gradient Example is a more advanced example of raster
dataset analysis.

Known Issues
Values of type RasterDataset, VectorDataset, VectorFeature, and Vertex are not handled
properly by export-world and import-world . To save datasets, you must use the
gis:store-dataset primitive.
There is currently no way to distinguish positive-area “shell” polygons from negative-area
“hole” polygons, or to determine which holes are associated with which shells.

Credits
The primary developer of the GIS extension was Eric Russell.
The GIS extension makes use of several open-source software libraries. For copyright and
license information on those, see the copyright section of the manual. The extension also
contains elements borrowed from My World GIS.
This documentation and the example NetLogo models are in the public domain. The GIS
extension itself is free and open source software. See the README.md file in the
extension/gis directory for details.
We would love to hear your suggestions on how to improve the GIS extension, or just
about what you’re using it for. Post questions and comments at the NetLogo Users Group,
or write directly to Eric Russell and the NetLogo team at ccl-gis@ccl.northwestern.edu

Primitives
RasterDataset Primitives
gis:width-of gis:height-of gis:raster-value gis:set-raster-value gis:minimum-of
gis:maximum-of gis:sampling-method-of gis:set-sampling-method gis:raster-sample
gis:raster-world-envelope gis:create-raster gis:resample gis:convolve gis:apply-raster

Dataset Primitives
gis:load-dataset gis:store-dataset gis:type-of gis:patch-dataset gis:turtle-dataset
gis:link-dataset

VectorDataset Primitives

gis:shape-type-of gis:property-names gis:feature-list-of gis:vertex-lists-of
gis:centroid-of gis:location-of gis:property-value gis:find-features gis:find-onefeature gis:find-less-than gis:find-greater-than gis:find-range gis:property-minimum
gis:property-maximum gis:apply-coverage gis:coverage-minimum-threshold gis:setcoverage-minimum-threshold gis:coverage-maximum-threshold gis:set-coverage-maximumthreshold gis:intersects? gis:contains? gis:contained-by? gis:have-relationship?
gis:relationship-of gis:intersecting

Coordinate System Primitives
gis:set-transformation gis:set-transformation-ds gis:set-world-envelope gis:set-worldenvelope-ds gis:world-envelope gis:envelope-of gis:envelope-union-of gis:loadcoordinate-system gis:set-coordinate-system

Drawing Primitives
gis:drawing-color gis:set-drawing-color gis:draw gis:fill gis:paint gis:import-wmsdrawing

gis:set-transformation
gis:set-transformation gis-envelope netlogo-envelope
Defines a mapping between GIS coordinates and NetLogo coordinates. Thegis-envelope
and netlogo-envelope parameters must each be four-element lists consisting of:
[minimum-x maximum-x minimum-y maximum-y]

The scale of the transformation will be equal to the minimum of the scale necessary to
make the mapping between the ranges of x values and the scale necessary to make the
mapping between the ranges of y values. The GIS space will be centered in NetLogo
space.
For example, the following two lists would map all of geographic (latitude and longitude)
space in degrees to NetLogo world space, regardless of the current dimensions of the
NetLogo world:
(list -180 180 -90 90)
(list min-pxcor max-pxcor min-pycor max-pycor)

However, if you’re setting the envelope of the NetLogo world, you should probably be
using set-world-envelope.

gis:set-transformation-ds
gis:set-transformation-ds gis-envelope netlogo-envelope
Does the same thing as set-transformation above, except that it allows the scale for
mapping the range of x values to be different than the scale for y values. The “-ds” on the
end stands for “different scales”. Using different scales will cause distortion of the shape
of GIS features, and so it is generally not recommended, but it may be useful for some
models.

Here is an example of the difference betweenset-transformation and set-transformationds:

Using [set-transformation]
(#gisset-transformation), the
scale along the x and y axis is
the same, preserving the round
shape of the Earth in this
Orthographic projection.

Using [set-transformation-ds](#gissettransformation-ds), the scale along
the x axis is stretched so that the
earth covers the entire NetLogo View,
which in this case distorts the shape
of the Earth.

gis:set-world-envelope
gis:set-world-envelope gis-envelope
A shorthand for setting the transformation by mapping the envelope of the NetLogo world
to the given envelope in GIS space, while keeping the scales along the x and y axis the
same. It is equivalent to:
set-transformation gis-envelope (list min-pxcor max-pxcor min-pycor max-pycor)

This primitive is supplied because most of the time you’ll want to set the envelope of the
entire NetLogo world, rather than just a part of it.

gis:set-world-envelope-ds
gis:set-world-envelope-ds gis-envelope
A shorthand for setting the transformation by mapping the envelope of the NetLogo world
to the given envelope in GIS space, using different scales along the x and y axis if
necessary. It is equivalent to:
set-transformation-ds gis-envelope (list min-pxcor max-pxcor min-pycor max-pycor)

See the pictures above for the difference between using equal scales for x and y
coordinates and using different scales.

gis:world-envelope
gis:world-envelope
Reports the envelope (bounding rectangle) of the NetLogo world, transformed into GIS
space. An envelope consists of a four-element list of the form:

[minimum-x maximum-x minimum-y maximum-y]

gis:envelope-of
gis:envelope-of thing
Reports the envelope (bounding rectangle) of thing in GIS coordinates. The thing may be
an Agent, an AgentSet, a RasterDataset, a VectorDataset, or a VectorFeature. An
envelope consists of a four-element list of the form:
[minimum-x maximum-x minimum-y maximum-y]

gis:envelope-union-of
gis:envelope-union-of envelope1 envelope2
gis:envelope-union-of envelope1 ...
Reports an envelope (bounding rectangle) that entirely contains the given envelopes. An
envelope consists of a four-element list of the form
[minimum-x maximum-x minimum-y maximum-y]

No assumption is made about the coordinate system of the arguments, though if they are
not in the same coordinate system, results will be unpredictable.

gis:load-coordinate-system
gis:load-coordinate-system file
Loads a new global projection used for projecting or re- projecting GIS data as it is loaded
from a file. The file must contain a valid Well-Known Text (WKT) projection description.
WKT projection files are frequently distributed alongside GIS data files, and usually have a
“.prj” filename extension.
Relative paths are resolved relative to the location of the current model, or the user’s
home directory if the current model hasn’t been saved yet.
The GIS extension does not support all WKT coordinate systems and projections. Only
geographic ("GEOGCS") and projected ("PROJCS") coordinate systems are supported. For
projected coordinate systems, only the following projections are supported:
Albers_Conic_Equal_Area
Lambert_Conformal_Conic_2SP
Polyconic
Lambert_Azimuthal_Equal_Area
Mercator_1SP
Robinson
Azimuthal_Equidistant
Miller
Stereographic

Cylindrical_Equal_Area
Oblique_Mercator
Transverse_Mercator
Equidistant_Conic
hotine_oblique_mercator
Gnomonic
Orthographic
See remotesensing.org for a complete list of WKT projections and their parameters.

gis:set-coordinate-system
gis:set-coordinate-system system
Sets the global projection used for projecting or re- projecting GIS data as it is loaded. The
system must be either a string in Well-Known Text (WKT) format, or a NetLogo list that
consists of WKT converted to a list by moving each keyword inside its associated brackets
and putting quotes around it. The latter is preferred because it makes the code much more
readable.
The same limitations on WKT support apply as described above in the documentation for
load-coordinate-system

gis:load-dataset
gis:load-dataset file
Loads the given data file, re-projecting the data as necessary if a global projection is
defined and if the data file itself has an associated .prj file, then reports the resulting
dataset.
If no “.prj” file is present, then load-dataset assumes that the projection of the data being
loaded is the same as the current global coordinate system.
Relative paths are resolved relative to the location of the current model, or the user’s
home directory if the current model hasn’t been saved yet.
Currently, two types of data file are supported:
“.shp” (ESRI shapefile): contains vector data, consisting of points, lines, or polygons.
When the target file is a shapefile, load-dataset reports a VectorDataset.
“.asc” or “.grd” (ESRI ASCII grid): contains raster data, consisting of a grid of values.
When the target file is an ASCII grid file, load-dataset reports a RasterDataset.

gis:store-dataset
gis:store-dataset dataset file
Saves the given dataset to the given file. If the name of the file does not have the proper
file extension, the extension will be automatically appended to the name. Relative paths
are resolved relative to the location of the current model, or the user’s home directory if
the current model hasn’t been saved yet.
Currently, this primitive only works for RasterDatasets, and it can only save those datasets

as ESRI ASCII grid files.

gis:type-of
gis:type-of dataset
Reports the type of the given GIS dataset: either “VECTOR” or “RASTER”

gis:patch-dataset
gis:patch-dataset patch-variable
Reports a new raster whose cells correspond directly to NetLogo patches, and whose cell
values consist of the values of the given patch variable. This primitive is basically the
inverse of apply-raster; apply-raster copies values from a raster dataset to a patch
variable, while this primitive copies values from a patch variable to a raster dataset.

gis:turtle-dataset
gis:turtle-dataset turtle-set
Reports a new, point VectorDataset built from the turtles in the given agentset. The points
are located at locations of the turtles, translated from NetLogo space into GIS space using
the current coordinate transformation. And the dataset’s properties consist of all of the
turtle variables common to every turtle in the agentset.

gis:link-dataset
gis:link-dataset link-set
Reports a new, line VectorDataset built from the links in the given agentset. The endpoints
of each line are at the location of the turtles connected by each link, translated from
NetLogo space into GIS space using the current coordinate transformation. And the
dataset’s properties consist of all of the link variables common to every link in the
agentset.

gis:shape-type-of
gis:shape-type-of VectorDataset
Reports the shape type of the given dataset. The possible output values are “POINT”,
“LINE”, and “POLYGON”.

gis:property-names
gis:property-names VectorDataset
Reports a list of strings where each string is the name of a property possessed by each
VectorFeature in the given VectorDataset, suitable for use in gis:property-value.

gis:feature-list-of
gis:feature-list-of VectorDataset
Reports a list of all VectorFeatures in the given dataset.

gis:vertex-lists-of
gis:vertex-lists-of VectorFeature
Reports a list of lists of Vertex values. For point datasets, each vertex list will contain
exactly one vertex: the location of a point. For line datasets, each vertex list will contain at
least two points, and will represent a “polyline”, connecting each adjacent pair of vertices
in the list. For polygon datasets, each vertex list will contain at least three points,
representing a polygon connecting each vertex, and the first and last vertices in the list will
be the same.

gis:centroid-of
gis:centroid-of VectorFeature
Reports a single Vertex representing the centroid (center of gravity) of the given feature.
For point datasets, the centroid is defined as the average location of all points in the
feature. For line datasets, the centroid is defined as the average of the locations of the
midpoints of all line segments in the feature, weighted by segment length. For polygon
datasets, the centroid is defined as the weighted sum of the centroids of a decomposition
of the area into (possibly overlapping) triangles. See this FAQ for more details on the
polygon centroid algorithm.

gis:location-of
gis:location-of Vertex
Reports a two-element list containing the x and y values (in that order) of the given vertex
translated into NetLogo world space using the current transformation, or an empty list if
the given vertex lies outside the NetLogo world.

gis:property-value
gis:property-value VectorFeature property-name
Reports the value of the property with the given name for the given VectorDataset. The
reported value may be a number, a string, or a boolean value, depending on the type of
the field in the underlying data file.
For shapefiles, values from dBase CHARACTER and DATE fields are returned as strings,
values from NUMBER and FLOAT fields are returned as numbers, and values from LOGICAL
fields are returned as boolean values. MEMO fields are not supported. DATE values are
converted to strings using ISO 8601 format (YYYY-MM-DD).

gis:find-features

gis:find-features VectorDataset property-name specified-value
Reports a list of all VectorFeatures in the given dataset whose value for the property
property-name matches specified-value (a string). Value comparison is not case sensitive,
and the wildcard character “*” will match any number of occurrences (including zero) of
any character.

gis:find-one-feature
gis:find-one-feature VectorDataset property-name specified-value
Reports the first VectorFeature in the dataset whose value for the propertyproperty-name
matches the given string. Value comparison is not case sensitive, and the wildcard
character “*” will match any number of occurrences (including zero) of any character.
Features are searched in the order that they appear in the data file that was the source of
the dataset, and searching stops as soon as a match is found. Reports nobody if no
matching VectorFeature is found.

gis:find-less-than
gis:find-less-than VectorDataset property-name value
Reports a list of all VectorFeatures in the given dataset whose value for the property
property-name is less than the given value. String values are compared using casesensitive lexicographic order as defined in the Java Documentation. Using a string value
for a numeric property or a numeric value for a string property will cause an error.

gis:find-greater-than
gis:find-greater-than VectorDataset property-name value
Reports a list of all VectorFeatures in the given dataset whose value for the property
property-name is greater than the given value. String values are compared using casesensitive lexicographic order as defined in the Java Documentation. Using a string value
for a numeric property or a numeric value for a string property will cause an error.

gis:find-range
gis:find-range VectorDataset property-name minimum-value maximum-value
Reports a list of all VectorFeatures in the given dataset whose value for the property
property-name is strictly greater than minimum-value and strictly less than maximumvalue. String values are compared using case-sensitive lexicographic order as defined in
the Java Documentation. Using a string value for a numeric property or a numeric value for
a string property will cause an error.

gis:property-minimum
gis:property-minimum VectorDataset property-name
Reports the smallest value for the given property over all of the VectorFeatures in the

given dataset. String values are compared using case-sensitive lexicographic order as
defined in the Java Documentation.

gis:property-maximum
gis:property-maximum VectorDataset property-name
Reports the largest value for the given property over all of the VectorFeatures in the given
dataset. String values are compared using case-sensitive lexicographic order as defined
in the Java Documentation.

gis:apply-coverage
gis:apply-coverage VectorDataset property-name patch-variable
Copies values from the given property of the VectorDataset’s features to the given patch
variable. The dataset must be a polygon dataset; points and lines are not supported.
For each patch, it finds all VectorFeatures that intersect that patch. Then, if the property is
a string property, it computes the majority value by computing the total area of the patch
covered by VectorFeatures having each possible value of the property, then returning the
value which represents the largest proportion of the patch area. If the property is a
numeric property, it computes a weighted average of property values from all
VectorFeatures which intersect the patch, weighted by the proportion of the patch area
they cover.
There are two exceptions to this default behavior:
If a percentage of a patches’ area greater than the coverage-maximum-threshold is
covered by a single VectorFeature, then the property value from that VectorFeature
is copied directly. If more than one VectorFeature covers a percentage of area
greater than the threshold, only the first will be used.
If the total percentage of a patches’ area covered by VectorFeatures is less than the
coverage-minimum-threshold, the target patch variable is set to Not A Number.
By default, the minimum threshold is 10% and the maximum threshold is 33%. These
values may be modified using the four primitives that follow.

gis:coverage-minimum-threshold
gis:coverage-minimum-threshold
Reports the current coverage minimum threshold used by gis:apply-coverage.

gis:set-coverage-minimum-threshold
gis:set-coverage-minimum-threshold new-threshold
Sets the current coverage minimum threshold to be used by gis:apply-coverage.

gis:coverage-maximum-threshold

gis:coverage-maximum-threshold
Reports the current coverage maximum threshold used by gis:apply-coverage.

gis:set-coverage-maximum-threshold
gis:set-coverage-maximum-threshold new-threshold
Sets the current coverage maximum threshold to be used by gis:apply-coverage.

gis:intersects?
gis:intersects? x y
Reports true if the given objects’ spatial representations share at least one point in
common, and false otherwise. The objects x and y may be any one of:
a VectorDataset, in which case the object’s spatial representation is the union of all the
points, lines, or polygons the dataset contains.
a VectorFeature, in which case the object’s spatial representation is defined by the
point, line, or polygon the feature contains.
A turtle, in which case the spatial representation is a point.
A link, whose spatial representation is a line segment connecting the two points
represented by the turtles the link is connecting.
A patch, whose spatial representation is a rectangular polygon.
An agentset, whose spatial representation is the union of the representations of all of
the agents it contains.
A list containing of any of the items listed here, including another list. The spatial
representation of such a list is the union of the spatial representations of its contents.

gis:contains?
gis:contains? x y
Reports true if every point of y’s spatial representation is also a part of x’s spatial
representation. Note that this means that polygons do contain their boundaries. The
objects x and y may be any one of
a VectorDataset, in which case the object’s spatial representation is the union of all the
points, lines, or polygons the dataset contains.
a VectorFeature, in which case the object’s spatial representation is defined by the
point, line, or polygon the feature contains.
A turtle, in which case the spatial representation is a point.
A link, whose spatial representation is a line segment connecting the two points
represented by the turtles the link is connecting.
A patch, whose spatial representation is a rectangular polygon.
An agentset, whose spatial representation is the union of the representations of all of
the agents it contains.
A list containing of any of the items listed here, including another list. The spatial
representation of such a list is the union of the spatial representations of its contents.

gis:contained-by?

gis:contained-by? x y
Reports true if every point of x’s spatial representation is also a part of y’s spatial
representation. The objects x and y may be any one of:
a VectorDataset, in which case the object’s spatial representation is the union of all the
points, lines, or polygons the dataset contains.
a VectorFeature, in which case the object’s spatial representation is defined by the
point, line, or polygon the feature contains.
A turtle, in which case the spatial representation is a point.
A link, whose spatial representation is a line segment connecting the two points
represented by the turtles the link is connecting.
A patch, whose spatial representation is a rectangular polygon.
An agentset, whose spatial representation is the union of the representations of all of
the agents it contains.
A list containing of any of the items listed here, including another list. The spatial
representation of such a list is the union of the spatial representations of its contents.

gis:have-relationship?
gis:have-relationship? x y
Reports true if the spatial representations of the two objects have the given spatial
relationship, and false otherwise. The spatial relationship is specified using a
Dimensionally Extended Nine- Intersection Model (DE-9IM) matrix. The matrix consists
of 9 elements, each of which specifies the required relationship between the two objects’
interior space, boundary space, or exterior space. The elements must have one of six
possible values:
“T”, meaning the spaces must intersect in some way
“F”, meaning the spaces must not intersect in any way
“0”, meaning the dimension of the spaces’ intersection must be zero (i.e., it must be a
point or non-empty set of points).
“1”, meaning the dimension of the spaces’ intersection must be one (i.e., it must be a
line or non-empty set of line segments).
“2”, meaning the dimension of the spaces’ intersection must be two (i.e., it must be a
polygon or set of polygons whose area is greater than zero).
“*”, meaning that the two spaces may have any relationship.
For example, this matrix:
x

Interior
y Boundary
Exterior

Interior

Boundary

Exterior

would return true if and only if some part of object x’s interior lies inside object y’s interior,
and no part of object x’s interior or boundary intersects object y’s exterior. This is
essentially a more restrictive form of the contains? primitive; one in which polygons are
not considered to contain their boundaries.

The matrix is given to the have-relationship? primitive as a string, whose elements are
given in the following order:
1

So to use the example matrix above, you would write:
gis:have-relationship? x y "T*****FF*"

A much more detailed and formal description of the DE-9IM matrix and the associated
point-set theory can be found in the OpenGIS Simple Features Specification for SQL.
The objects x and y may be any one of:
a VectorDataset, in which case the object’s spatial representation is the union of all the
points, lines, or polygons the dataset contains.
a VectorFeature, in which case the object’s spatial representation is defined by the
point, line, or polygon the feature contains.
A turtle, in which case the spatial representation is a point.
A link, whose spatial representation is a line segment connecting the two points
represented by the turtles the link is connecting.
A patch, whose spatial representation is a rectangular polygon.
An agentset, whose spatial representation is the union of the representations of all of
the agents it contains.
A list containing of any of the items listed here, including another list. The spatial
representation of such a list is the union of the spatial representations of its contents.

gis:relationship-of
gis:relationship-of x y
Reports the Dimensionally Extended Nine-Intersection Model (DE-9IM) matrix that
describes the spatial relationship of the two objects. The matrix consists of 9 elements,
each of which describes the relationship between the two objects’ interior space, boundary
space, or exterior space. Each element will describe the dimension of the intersection of
two spaces, meaning that it may have one of four possible values:
“-1”, meaning the spaces do not intersect
“0”, meaning the dimension of the spaces’ intersection is zero (i.e., they intersect at a
point or set of points).
“1”, meaning the dimension of the spaces’ intersection is one (i.e., they intersect along
one or more lines).
“2”, meaning the dimension of the spaces’ intersection is two (i.e., their intersection is a
non-empty polygon).
For example, the two polygons x and y shown here:

have the following DE-9IM matrix:
x

Interior
y Boundary
Exterior

Interior

Boundary

Exterior

Which would be reported by the relationship-of primitive as the string “212101212”.
A much more detailed and formal description of the DE-9IM matrix and the associated
point-set theory can be found in the OpenGIS Simple Features Specification for SQL.
The objects x and y may be any one of:
a VectorDataset, in which case the object’s spatial representation is the union of all the
points, lines, or polygons the dataset contains.
a VectorFeature, in which case the object’s spatial representation is defined by the
point, line, or polygon the feature contains.
A turtle, in which case the spatial representation is a point.
A link, whose spatial representation is a line segment connecting the two points
represented by the turtles the link is connecting.
A patch, whose spatial representation is a rectangular polygon.
An agentset, whose spatial representation is the union of the representations of all of
the agents it contains.
A list containing of any of the items listed here, including another list. The spatial
representation of such a list is the union of the spatial representations of its contents.

gis:intersecting
patch-set gis:intersecting data
Reports a new agent set containing only those members of the given agent set which
intersect given GIS data, which may be any one of: a VectorDataset, a VectorFeature, an
Agent, an Agent Set, or a list containing any of the above.

gis:width-of
gis:width-of RasterDataset
Reports the number of columns in the dataset. Note that this is the number of cells from

left to right, not the width of the dataset in GIS space.

gis:height-of
gis:height-of RasterDataset
Reports the number of rows in the dataset. Note that this is the number of cells from top to
bottom, not the height of the dataset in GIS space.

gis:raster-value
gis:raster-value RasterDataset x y
Reports the value of the given raster dataset in the given cell. Cell coordinates are
numbered from left to right, and from top to bottom, beginning with zero. So the upper left
cell is (0, 0), and the bottom right cell is (gis:width-of dataset - 1, gis:height-of dataset
- 1).

gis:set-raster-value
gis:set-raster-value RasterDataset x y value
Sets the value of the given raster dataset at the given cell to a new value. Cell coordinates
are numbered from left to right, and from top to bottom, beginning with zero. So the upper
left cell is (0, 0), and the bottom right cell is (gis:width-of dataset - 1, gis:height-of
dataset - 1).

gis:minimum-of
gis:minimum-of RasterDataset
Reports the highest value in the given raster dataset.

gis:maximum-of
gis:maximum-of RasterDataset
Reports the lowest value in the given raster dataset.

gis:sampling-method-of
gis:sampling-method-of RasterDataset
Reports the sampling method used to compute the value of the given raster dataset at a
single point, or over an area smaller than a single raster cell. Sampling is performed by the
GIS extension primitives raster-sample, resample, convolve, and apply-raster. The
sampling method will be one of the following:
"NEAREST_NEIGHBOR": the value of the cell nearest the sampling location is used.
"BILINEAR": the value of the four nearest cells are sampled by linear weighting,

according to their proximity to the sampling site.
"BICUBIC": the value of the sixteen nearest cells are sampled, and their values are
combined by weight according to a piecewise cubic polynomial recommended by
Rifman (see Digital Image Warping, George Wolberg, 1990, pp 129-131, IEEE
Computer Society Press).
"BICUBIC_2": the value is sampled using the same procedure and the same polynomial
as with BICUBIC above, but using a different coefficient. This method may produce
somewhat sharper results than BICUBIC , but that result is data dependent.
For more information on these sampling methods and on raster sampling in general, see
this wikipedia article.

gis:set-sampling-method
gis:set-sampling-method RasterDataset sampling-method
Sets the sampling method used by the given raster dataset at a single point, or over an
area smaller than a single raster cell. Sampling is performed by the GIS extension
primitives raster-sample, resample, convolve, and apply-raster. The sampling method must
be one of the following:
"NEAREST_NEIGHBOR"
"BILINEAR"
"BICUBIC"
"BICUBIC_2"

See sampling-method-of above for a more specific description of each sampling method.

gis:raster-sample
gis:raster-sample RasterDataset sample-location
Reports the value of the given raster over the given location. The location may be any of
the following:
A list of length 2, which is taken to represent a point in netlogo space [( xcor ycor]) of
the sort reported by location-of Vertex. The raster dataset is sampled at the point of that
location.
A list of length 4, which is taken to represent an envelope in GIS space, of the sort
reported by envelope-of. The raster dataset is sampled over the area of that envelope.
A patch, in which case the raster dataset is sampled over the area of the patch.
A turtle, in which case the raster dataset is sampled at the location of that turtle.
A Vertex, in which case the raster dataset is sampled at the location of that Vertex.
If the requested location is outside the area covered by the raster dataset, this primitive
reports the special value representing “not a number”, which is printed by NetLogo as
“NaN”. Using the special “not a number” value as an argument to primitives that expect a
number may cause an error, but you can test the value reported by this primitive to filter
out “not a number” values. A value that is not a number will be neither less than nor
greater than a number value, so you can detect “not a number” values using the following:
let value gis:raster-sample dataset turtle 0
; set color to blue if value is a number, red if value is "not a number"
ifelse (value <= 0) or (value >= 0)
[ set color blue ]
[ set color red ]

If the requested location is a point, the sample is always computed using the method set
by set-sampling-method. If the requested location is an area (i.e., an envelope or patch),
the sample is computed by taking the average of all raster cells covered by the requested
area.

gis:raster-world-envelope
gis:raster-world-envelope RasterDataset x y
Reports the GIS envelope needed to match the boundaries of NetLogo patches with the
boundaries of cells in the given raster dataset. This envelope could then be used as an
argument to set-transformation-ds.
There may be more cells in the dataset than there are patches in the NetLogo world. In
that case, you will need to select a subset of cells in the dataset by specifying which cell in
the dataset you want to match with the upper-left corner of the NetLogo world. Cells are
numbered from left to right, and from top to bottom, beginning with zero. So the upper left
cell is (0, 0), and the bottom right cell is (gis:width-of dataset - 1, gis:height-of dataset
- 1).

gis:create-raster
gis:create-raster width height envelope
Creates and reports a new, empty raster dataset with the given number of columns and
rows, covering the given envelope.

gis:resample
gis:resample RasterDataset envelope width height
Reports a new dataset that consists of the given RasterDataset resampled to cover the
given envelope and to contain the given number of columns and rows. If the new raster’s
cells are smaller than the existing raster’s cells, they will be resampled using the method
set by set-sampling-method. If the new cells are larger than the original cells, they will be
sampled using the "NEAREST_NEIGHBOR" method.

gis:convolve
gis:convolve RasterDataset kernel-rows kernel-columns kernel key-column key-row
Reports a new raster whose data consists of the given raster convolved with the given
kernel.
A convolution is a mathematical operation that computes each output cell by multiplying
elements of a kernel with the cell values surrounding a particular source cell. A kernel is a
matrix of values, with one particular value defined as the “key element”, the value that is
centered over the source cell corresponding to the destination cell whose value is being
computed.
The values of the kernel matrix are given as a list, which enumerates the elements of the

matrix from left to right, top to bottom. So the elements of a 3-by-3 matrix would be listed
in the following order:
1

The key element is specified by column and row within the matrix. Columns are numbered
from left to right, beginning with zero. Rows are numbered from top to bottom, also
beginning with zero. So, for example, the kernel for the horizontal Sobel operator, which
looks like this:
1
2
1

0
0
(key)

-1
-2
-1

would be specified as follows:
let horizontal-gradient gis:convolve dataset 3 3 [1 0 -1 2 0 -2 1 0 -1] 1 1

gis:apply-raster
gis:apply-raster RasterDataset patch-variable
Copies values from the given raster dataset to the given patch variable, resampling the
raster as necessary so that its cell boundaries match up with NetLogo patch boundaries.
This resampling is done as if using resample rather than raster-sample, for the sake of
efficiency. However, patches not covered by the raster are assigned values of “not a
number” in the same way that raster-sample reports values for locations outside the
raster.

gis:drawing-color
gis:drawing-color
Reports the color used by the GIS extension to draw vector features into the NetLogo
drawing layer. Color can be represented either as a NetLogo color (a single number
between zero and 140) or an RGB color (a list of 3 numbers). See details in the Colors
section of the Programming Guide.

gis:set-drawing-color
gis:set-drawing-color color
Sets the color used by the GIS extension to draw vector features into the NetLogo drawing
layer. Color can be represented either as a NetLogo color (a single number between zero

and 140) or an RGB color (a list of 3 numbers). See details in the Colors section of the
Programming Guide.

gis:draw
gis:draw vector-data line-thickness
Draws the given vector data to the NetLogo drawing layer, using the current GIS drawing
color, with the given line thickness. The data may consist either of an entire
VectorDataset, or a single VectorFeature. This primitive draws only the boundary of
polygon data, and for point data, it fills a circle with a radius equal to the line thickness.

gis:fill
gis:fill vector-data line-thickness
Fills the given vector data in the NetLogo drawing layer using the current GIS drawing
color, using the given line thickness around the edges. The data may consist either of an
entire VectorDataset, or a single VectorFeature. For point data, it fills a circle with a radius
equal to the line thickness.

gis:paint
gis:paint RasterDataset transparency
Paints the given raster data to the NetLogo drawing layer. The highest value in the
dataset is painted white, the lowest is painted in black, and the other values are painted in
shades of gray scaled linearly between white and black.
The transparency input determines how transparent the new image in the drawing will be.
Valid inputs range from 0 (completely opaque) to 255 (completely transparent).

gis:import-wms-drawing
gis:import-wms-drawing server-url spatial-reference layers transparency
Imports an image into the NetLogo drawing layer using theWeb Mapping Service
protocol, as defined by the Open Geospatial Consortium.
The spatial reference and layers inputs should be given as strings. The spatial reference
input corresponds to the SRS parameter to the GetMap request as defined in section
7.2.3.5 of version 1.1.1 of the WMS standard. The layers input corresponds to the
LAYERS parameter to the as defined in 7.2.3.3 of version 1.1.1 of the WMS standard.
You can find the list of valid spatial reference codes and layer names by examining the
response to a GetCapabilities request to the WMS server. Consult the relevant standard
for instructions on how to issue a GetCapabilities request to the server and how to
interpret the results.
The transparency input determines how transparent the new image in the drawing will be.
Valid inputs range from 0 (completely opaque) to 255 (completely transparent).

NetLogo Gogo Extension
Usage
The GoGo Extension comes preinstalled when you download and install NetLogo. To use
the extension in your model, add this line to the top of your Code tab:
extensions [ gogo ]

If your model already uses other extensions, then it already has an extensions line in it, so
just add gogo to the list.
After loading the extension, you can see whether one or more HID-based gogos are on
and attached to the computer by typing the following into the command center:
gogo:howmany-gogos

Changes
Compared to previous versions of the GoGo extension, this version offers:
Improved robustness. With prior versions of the GoGo extension, crashes were fairly
common due to problems in the USB-Serial stack across platforms. The switch to HID
improved robustness, and the new extension also uses a “daemon” architecture which
shields NetLogo from any problems that may occur in direct communication with the
GoGo board. The result is a substantial reduction in the number of crashes of NetLogo.
No Installation of Drivers. Because the new GoGo firmware presents the board as an
HID device, the extension could be written so as not to require installing drivers. This
means there is no need for the user to have administrator rights on the computer.
Directionality for Motors. The board now has polarity-ensuring output connectors, so
that “counterclockwise” or “clockwise” can now be specified in code.

Primitives
Other Outputs
gogo:led gogo:beep

Utilities
gogo:read-all

General
gogo:primitives gogo:howmany-gogos

Sensors
gogo:read-sensors gogo:read-sensor

Outputs and Servos
gogo:talk-to-output-ports gogo:set-output-port-power gogo:output-port-on gogo:outputport-off gogo:output-port-clockwise gogo:output-port-counterclockwise gogo:set-servo

gogo:primitives
gogo:primitives
Returns a list of the primitives of this extension.

gogo:howmany-gogos
gogo:howmany-gogos
Reports the number of USB HID devices visible to the computer and having the correct
vendor and product ID to be a GoGo board. A board will only be detected if it is both
connected and powered on. Using this primitive is one way to determine quickly whether a
GoGo board has the HID firmware loaded. (A USB-Serial version of the board will not be
detected.).

gogo:talk-to-output-ports
gogo:talk-to-output-ports list-of-portnames
Establishes a list of output ports that will be controlled with subsequent output-port
commands. See below…

gogo:set-output-port-power
gogo:set-output-port-power power-level
is a number between 0 and 100, reflecting the percentage of maximum
power. Sets the amount of power that will be fed to the output ports indicated in talk-tooutput-ports . This will not affect the on-off state of the output ports. So, for example, if a
motor is already connected to an output port and running, changing its power will change
its speed. If the motor is not running, changing the power level will not turn it on; instead, it
will affect the speed at which the motor starts when it is turned on with output-port-on .
power-level

gogo:output-port-on
gogo:output-port-on
Turns on the output ports which have been indicated with talk-to-output-ports. If none have
been set with talk-to-output-ports, no ports will be turned on.

gogo:output-port-off
gogo:output-port-off

Turns off the output ports which have been indicated with talk-to-output-ports. If none have
been set with talk-to-output-ports, no ports will be turned off.

gogo:output-port-clockwise
gogo:output-port-clockwise
Sets the polarity of the output port(s) that have been specified with talk-to-output-ports, so
that a motor attached to one of these ports would turn clockwise.

gogo:output-port-counterclockwise
gogo:output-port-counterclockwise
Sets the polarity of the output port(s) that have been specified withtalk-to-output-ports,
so that a motor attached to one of these ports would turn counterclockwise.

gogo:set-servo
gogo:set-servo number
Sets the Pulse-Width Modulation (PWM) proportion of the output port(s) that have been
specified with talk-to-output-ports. Note that the servo connectors are the male pins next
to the standard motor connectors. Different servos respond to different PWM ranges, but
all servos read PWM proportions and set the position of their main gear accordingly.

gogo:led
gogo:led on-or-off
Turns the user-LED on or off, depending on the argument. gogo:led 1 turns the LED on;
gogo:led 0 turns it off.

gogo:beep
gogo:beep
Causes the GoGo board to beep.

gogo:read-sensors
gogo:read-sensors
Reports a list containing the current readings of all eight sensors ports of the GoGo.

gogo:read-sensor
gogo:read-sensor which-sensor

Reports the value of sensor number which-sensor, where which-sensor is a number
between 0-7.

gogo:read-all
gogo:read-all
Reports all data available from the board, in a raw-list form useful for debugging.

gogo:send-bytes
gogo:send-bytes list
Sends a list of bytes to the GoGo board. Useful for debugging or for testing any new or
future functionality that is added to the GoGo board with new firmware updates.

NetLogo Ls Extension
LevelSpace fundamentals
LevelSpace must be loaded in a model using extensions [ls] at the top of your model.
Once this is done, a model will be able to load up other models using the LevelSpace
primitives, run commands and reporters in them, and close them down when they are no
longer needed.
Asking and reporting in LevelSpace is conceptually pretty straight forward: You pass blocks
of code to child models, and the child models respond as if you had typed that code into
their Command Center. LevelSpace allows you to report strings, numbers, and lists from a
child to its parent. It is not possible to directly report turtles, patches, links, or any of their
respective sets. Further, it is not possible to push data from a child to its parent - parents
must ask their children to report. This mimicks the way in which turtles cannot “push” data
to the observer, but rely on the observer to ask them for it.
In general, the LevelSpace syntax has been designed to align with existing NetLogo
primitives whenever possible.

Headless and Interactive Models
LevelSpace has two different child model types; headless models and interactive models.
They each have their strengths and weaknesses:
Interactive models * are full-fledged models that give full access to their interface and
widgets, * run a bit slower, and use more memory * are visible by default
Headless Models * only give you access to their view and command center * are faster and
use less memory than interactive models. * are hidden by default
Typically you will want to use headless models when you are running a large number of
models, or if you simply want to run them faster. Interactive models are good if you run a
small amount of models, if you are writing a LevelSpace model and need to be able to
debug, or if you need access to widgets during runtime.

Keeping Track of Models
Child models are kept track of in the extension with an id number, starting with 0, and all
communication from parent to child is done by referencing this number, henceforth referred
to as model-id .
The easiest way to work with multiple models is to store theirmodel-id in a list, and use
NetLogo’s list primitives to sort, filter, etc. them during runtime.
Keeping track of models is important: Most LevelSpace primitives will fail and cause a
runtime interruption if provided a model-id to a non-existing model. You can use ls:modelexists? model-id to check if model-id refers to an existing model.

A general use case: Asking and Reporting
This use case is based on the Model Visualizer and Plotter Example-model from the
NetLogo Models Library.

A simple thing we can do is to open up some models, run them concurrently, and calculate
the average of some reporter. Let’s say that we are interested in finding the mean number
of sheep in a bunch of Wolf Sheep Predation models. First we would open up some of
these models, and set them up:
to setup
ls:reset
ca
ls:create-models 30 "Wolf Sheep Predation.nlogo"
ls:ask ls:models [ set grass? true setup ]
reset-ticks
end

We then want to run all our child models, and then find out what the mean number of
sheep is:
to go
ls:ask ls:models [ go ]
show mean [ count sheep ] ls:of ls:models
end

A general use case: Inter-Model Interactions
This use case is based on the Model Interactions Example-model from the NetLogo Models
Library.
Let’s imagine that we have two models: a Wolf Sheep Predation-model called WSP, and a
Climate Change model called CC. Now let’s imagine that we want the regrowth time in the
wSP model to depend on the temperature in the CC model. Using LevelSpace’s primitives,
we could do something like this:
; save new regrowth time in a temporary LevelSpace let-variable
ls:let new-regrowth-time 25 + ( abs [ temperature - 55 ] ls:of CC ) / 2
; remove decimals, pass it to the wolf sheep predation model and change the time
ls:ask WSP [
set grass-regrowth-time round new-regrowth-time
]
; finally ask both models to go
ls:ask ls:models [ go ]

A general Usecase: Tidying up “Dead” Child Models
As previously mentioned, it is important to keep track of “living” and “dead” models when
you dynamically create and dispose of models. Let us imagine we have some lists of
models of different kinds, and we want to make sure that we only keep the models that are
alive. After running code that kills child models we can use the ls:model-exists? primitive
to clean up our list of models like this:
to-report remove-dead-models [list-of-models]
report filter [ [ model-id ] -> ls:model-exists model-id] list-of-models
end

We then reassign each list of models with this, e.g.

set a-list-of-models remove-dead-models a-list-of-models
set another-list-of-models remove-dead-models a-list-of-models

Citing LevelSpace in Research
If you use LevelSpace in research, we ask that you cite us,
Hjorth, A. Head, B. & Wilensky, U. (2015). “LevelSpace NetLogo extension”.
http://ccl.northwestern.edu/rp/levelspace/index.shtml Evanston, IL: Center for Connected
Learning and Computer Based Modeling, Northwestern University.

Primitives
Commanding and Reporting
ls:ask ls:of ls:report ls:with ls:let ls:assign

Logic and Control
ls:models ls:show ls:show-all ls:hide ls:hide-all ls:path-of ls:name-of ls:model-exists?

Opening and Closing Models
ls:create-models ls:create-interactive-models ls:close ls:reset

ls:create-models
ls:create-models number path
ls:create-models number path anonymous command
Create the specified number of instances of the given .nlogo model. The path can be
absolute, or relative to the main model. Compared with ls:create-interactive-models , this
primitive creates lightweight models that are hidden by default. You should use this
primitive if you plan on having many instances of the given model. The models may be
shown using ls:show ; when visible, they will have a view and command center, but no
other widgets, e.g. plots or monitors.
If given a command, LevelSpace will call the command after loading each instance of the
model with the model-id as the argument. This allows you to easily store model ids in a
variable or list when loading models, or do other initialization. For example, to store a
model id in a variable, you can do:
let model-id 0
(ls:create-models "My-Model.nlogo" [ [id] -> set model-id id ])

Child model RNGs are seeded from the parent models RNG when they are created. Thus,
if you seed the parent’s model RNG before child model before child models are created,
the simulation as a whole will be reproducible. Use the ls:random-seed primitive to seed the
model system’s RNGs after child models have been created.

ls:create-interactive-models

ls:create-interactive-models number path
ls:create-interactive-models number path anonymous command
Like ls:create-models, creates the specified number of instances of the given .nlogo
model. Unlike ls:create-models, ls:create-interactive-models creates models that are
visible by default, and have all widgets. You should use this primitive if you plan on having
only a handful of instances of the given model, and would like to be able to interact with the
instances through their interfaces during runtime.
Child model RNGs are seeded from the parent models RNG when they are created. Thus,
if you seed the parent’s model RNG before child model before child models are created,
the simulation as a whole will be reproducible. Use the ls:random-seed primitive to seed the
model system’s RNGs after child models have been created.

ls:close
ls:close model-or-list-of-models
Close the model or models with the given model-id .

ls:reset
ls:reset
Close down all child models (and, recursively, their child models). You’ll often want to call
this in your setup procedure.
Note that clear-all does not close LevelSpace models.

ls:ask
ls:ask model-or-list-of-models command argument
Ask the given child model or list of child models to run the given command. This is the
primary of doing things with child models. For example:
ls:ask model-id [ create-turtles 5 ]

You can also ask a list of models to all do the same thing:
ls:ask ls:models [ create-turtles 5 ]

You may supply the command with arguments, just like you would with anonymous
commands:
let turtle-id 0
let speed 5
(ls:ask model-id [ [t s] -> ask turtle t [ fd s ] ] turtle-id speed)

Note that the commands cannot access variables in the parent model directly. You must
either pass information in through arguments or using ls:let.

ls:of
reporter ls:of model-or-list-of-models
Run the given reporter in the given model and report the result.
is designed to work like NetLogo’s inbuilt of: If you send ls:of a model-id , it will
report the value of the reporter from that model. If you send it a list of model-ids, it will
report a list of values of the reporter string from all models. You cannot pass arguments to
ls:of, but you can use ls:let.
ls:of

[ count turtles ] ls:of model-id

ls:report
ls:report model-or-list-of-models reporter argument
Run the given reporter in the given model and report the result. This form exists to allow
you to pass arguments to the reporter.
let turtle-id 0
(ls:report model-id [ [a-turtle] -> [ color ] of turtle a-turtle ] turtle-id)

ls:with
list-of-models ls:with reporter
Reports a new list of models containing only those models that reporttrue when they run
the reporter block.
ls:models ls:with [ count turtles > 100 ]

ls:let
ls:let variable-name value
Creates a variable containing the given data that can be accessed by the child models.
ask turtles [
ls:let my-color color
ls:ask my-model [
ask turtles [ set color my-color ]
]
]

ls:let

works quite similar to let in that the variable is only locally accessible:

ask turtles [
ls:let my-color color
]
;; my-color is innaccessible here

ls:let

is very similar to let, except in a few cases.

ls:let

will overwrite previous values in the variable

If you do
ls:let my-var 5
ls:let my-var 6
my-var will
ls:let

be set equal to 6. There is no ls:set.

supports variable shadowing

If you do
ls:let my-var 5
ask turtles [
ls:let my-var 6
ls:ask child-model [ show my-var ]
]
ls:ask child-model [ show my-var ]

child-model

will show 6 and then 5. This is known as variable shadowing.

The parent model cannot directly read the value of an ls variable
For example, this does not work.
ls:let my-var 5
show my-var

This is intentional. ls variables are meant to be used for sharing data with child models. The
parent model already has access to the data.
Furthermore, changing the value of an ls let variable in a child model will not affect it in any
other model. For example:
ls:let my-var 0
ls:ask ls:models [
set my-var my-var + 1
show my-var
]

All models will print 1.

ls:assign
ls:assign model-or-list-of-models global-variable value
Sets the given global variable in child model to given value. For instance
ls:assign ls:models glob1 count turtles

sets the global variable glob1 in all models to the parent’s model count turtles .

ls:models
ls:models
Report a list of model-ids for all existing models.

ls:show
ls:show model-or-list-of-models
Makes all of the given models visible.

ls:show-all
ls:show-all model-or-list-of-models
Makes all of the given models and their descendents visible.

ls:hide
ls:hide model-or-list-of-models
Hide all of the given models. Hiding models is a good way of making your simulation run
faster.

ls:hide-all
ls:hide-all model-or-list-of-models
Hide all of the given models and their descendents. Hiding models is a good way of making
your simulation run faster.

ls:path-of
ls:path-of model-or-list-of-models
Report the full path, including the .nlogo file name, of the model. If a list of models is given,
a list of paths is reported.

ls:name-of
ls:name-of model-or-list-of-models
Reports the name of the .nlogo file of the model. This is the name of the window in which
the model appears when visible. If a list of models is given, a list of names is reported.

ls:model-exists?

ls:model-exists? model-or-list-of-models
Report a boolean value for whether there is a model with that model-id. This is often useful
when you are dynamically generating models, and want to ensure that you are not asking
models that no longer exist to do stuff.

ls:random-seed
ls:random-seed seed
Behaves exactly like NetLogo’s built-in primitive random-seed, except that child models have
their RNGs seeded based on the given seed as well (as well their child models, and their
child models’ child models, and so forth). This primitive should almost always be used
instead of NetLogo’s built-in one for seeding RNG when using LevelSpace.

NetLogo Matrix Extension
Using
The matrix extension adds a new matrix data structure to NetLogo. A matrix is a mutable 2-dimensional array containing
only numbers.

When to Use
Although matrices store numbers, much like a list of lists, or an array of arrays, the primary reason to use the matrix data
type is to take advantage of special mathematical operations associated with matrices. For instance, matrix multiplication
is a convenient way to perform geometric transformations, and the repeated application of matrix multiplication can also
be used to simulate other dynamic processes (for instance, processes on graph/network structures).
If you’d like to know more about matrices and how they can be used, you might consider a course on linear algebra, or
search the web for tutorials. The matrix extension also allows you to solve linear algebraic equations (specified in a
matrix format), and even to identify trends in your data and perform linear (ordinary least squares) regressions on data
sets with multiple explanatory variables.

How to Use
The matrix extension comes preinstalled.
To use the matrix extension in your model, add a line to the top of your Code tab:
extensions [matrix]

If your model already uses other extensions, then it already has anextensions line in it, so just add matrix to the list.

Example
let m matrix:from-row-list [[1 2 3] [4 5 6]]
print m
=> {{matrix: [ [ 1 2 3 ][ 4 5 6 ] ]}}
print matrix:pretty-print-text m
=>
[[ 1 2 3 ]
[ 4 5 6 ]]
print matrix:dimensions m
=> [2 3]
;;(NOTE: row & column indexing starts at 0, not 1)
print matrix:get m 1 2 ;; what number is in row 1, column 2?
=> 6
matrix:set m 1 2 10 ;; change the 6 to a 10
print m
=> {{matrix: [ [ 1 2 3 ][ 4 5 10 ] ]}}
let m2 matrix:make-identity 3
print m2
=> {{matrix: [ [ 1 0 0 ][ 0 1 0 ][ 0 0 1 ] ]}}
print matrix:times m m2 ;; multiplying by the identity changes nothing
=> {{matrix: [ [ 1 2 3 ][ 4 5 10 ] ]}}
;; make a new matrix with the middle 1 changed to -1
let m3 (matrix:set-and-report m2 1 1 -1)
print m3
=> {{matrix: [ [ 1 0 0 ][ 0 -1 0 ][ 0 0 1 ] ]}}
print matrix:times m m3
=> {{matrix: [ [ 1 -2 3 ][ 4 -5 10 ] ]}}
print matrix:to-row-list (matrix:plus m2 m3)
=> [[2 0 0] [0 0 0] [0 0 2]]

Primitives
Matrix creation and conversion to/from lists
matrix:make-constant matrix:make-identity matrix:from-row-list matrix:from-column-list matrix:to-row-list
matrix:to-column-list matrix:copy matrix:pretty-print-text

Advanced features
matrix:solve matrix:forecast-linear-growth matrix:forecast-compound-growth matrix:forecast-continuous-growth
matrix:regress

Matrix data retrieval and manipulation
matrix:get matrix:get-row matrix:get-column matrix:set matrix:set-row matrix:set-column matrix:swap-rows
matrix:swap-columns matrix:set-and-report matrix:dimensions matrix:submatrix matrix:map

Math operations
matrix:times-scalar matrix:times matrix:* matrix:times-element-wise matrix:plus-scalar matrix:plus matrix:+
matrix:minus matrix:- matrix:inverse matrix:transpose matrix:real-eigenvalues matrix:imaginary-eigenvalues
matrix:eigenvectors matrix:det matrix:rank matrix:trace

matrix:make-constant
matrix:make-constant n-rows n-cols initialValue
Reports a new n-rows by n-cols matrix object, with all entries in the matrix containing the same value (number).

matrix:make-identity
matrix:make-identity size
Reports a new square matrix object (with dimensions n-size x n-size), consisting of the identity matrix (1s along the main
diagonal, 0s elsewhere).

matrix:from-row-list
matrix:from-row-list nested-list
Reports a new matrix object, created from a NetLogo list, where each item in that list is another list (corresponding to
each of the rows of the matrix.)
print matrix:from-row-list [[1 2] [3 4]]
=> {{matrix: [ [ 1 2 ][ 3 4 ] ]}}
;; Corresponds to this matrix:
;; 1 2
;; 3 4

matrix:from-column-list
matrix:from-column-list nested-list
Reports a new matrix object, created from a NetLogo list containing each of thecolumns of the matrix.

matrix:to-row-list
matrix:to-row-list matrix
Reports a list of lists, containing each row of the matrix.

matrix:to-column-list
matrix:to-column-list matrix
Reports a list of lists, containing each column of the matrix.

matrix:copy
matrix:copy matrix
Reports a new matrix that is an exact copy of the given matrix. This primitive is important because the matrix type is
mutable (changeable). Here’s a code example:
let m1 matrix:from-column-list [[1 4 7][2
print m1
=> {{matrix: [ [ 1 2 3 ][ 4 5 6 ][ 7 8 9
let m2 m1 ;; m2 refers to the same matrix
let m3 matrix:copy m1 ;; m3 is a new copy

5 8][3 6 9]] ; a 3x3 matrix
] ]}}
object as m1
containing m1's data

matrix:set m1 0 0 100 ;; now m1 is changed
print m1
=> {{matrix:

[ [ 100 2 3 ][ 4 5 6 ][ 7 8 9 ] ]}}

print m2
=> {{matrix: [ [ 100 2 3 ][ 4 5 6 ][ 7 8 9 ] ]}}
;;Notice that m2 was also changed, when m1 was changed!
print m3
=> {{matrix:

[ [ 1 2 3 ][ 4 5 6 ][ 7 8 9 ] ]}}

matrix:pretty-print-text
matrix:pretty-print-text matrix
Reports a string that is a textual representation of the matrix, in a format that is reasonably human-readable when
displayed.

matrix:get
matrix:get matrix row-i col-j
Reports the (numeric) value at location row-i (second argument), col-j (third argument), in the given matrix given in the
first argument

matrix:get-row
matrix:get-row matrix row-i
Reports a simple (not nested) NetLogo list containing the elements ofrow-i (second argument) of the matrix supplied in
the first argument.

matrix:get-column
matrix:get-column matrix col-j
Reports a simple (not nested) NetLogo list containing the elements ofcol-j of the matrix supplied in the first argument.

matrix:set
matrix:set matrix row-i col-j new-value
Changes the given matrix by setting the value at location row-i, col-j to new-value

matrix:set-row
matrix:set-row matrix row-i simple-list
Changes the given matrix matrix by replacing the row at row-i with the contents of the simple (not nested) NetLogo list
simple-list. The simple-list must have a length equal to the number of columns in the matrix, i.e., the matrix row length.

matrix:set-column
matrix:set-column matrix col-j simple-list
Changes the given matrix matrix by replacing the column at col-j with the contents of the simple (not nested) NetLogo list
simple-list. The simple-list must have a length equal to the number of rows in the matrix, i.e., the matrix column length
length.

matrix:swap-rows
matrix:swap-rows matrix row1 row2
Changes the given matrix matrix by swapping the rows at row1 and row2 with each other.

matrix:swap-columns

matrix:swap-columns matrix col1 col2
Changes the given matrix matrix by swapping the columns at col1 and col2 with each other.

matrix:set-and-report
matrix:set-and-report matrix row-i col-j new-value
Reports a new matrix, which is a copy of the given matrix except that the value atrow-i,col-j has been changed to newvalue. A NetLogo statement such as set mat matrix:set-and-report mat 2 3 10 will result in mat pointing to this new
matrix, a copy of the old version of mat with the element at row 2, column 3 being set to 10. The old version of mat will be
“lost”.

matrix:dimensions
matrix:dimensions matrix
Reports a 2-element list ([num-rows,num-cols]), containing the number of rows and number of columns in the given
matrix

matrix:submatrix
matrix:submatrix matrix r1 c1 r2 c2
Reports a new matrix object, consisting of a rectangular subsection of the given matrix. The rectangular region is from
row r1 up to (but not including) row r2, and from column c1 up to (but not including) column c2.
Here is an example:
let m matrix:from-row-list [[1 2 3][4 5 6][7 8 9]]
print matrix:submatrix m 0 1 2 3 ; matrix, row-start, col-start, row-end, col-end
; rows from 0 (inclusive) to 2 (exclusive),
; columns from 1 (inclusive) to 3 (exclusive)
=> {{matrix: [ [ 2 3 ][ 5 6 ] ]}}

matrix:map
matrix:map anonymous reporter matrix
matrix:map anonymous reporter matrix anything
Reports a new matrix which results from applying reporter (an anonymous reporter or the name of a reporter) to each of
the elements of the given matrix. For example,
matrix:map sqrt matrix

would take the square root of each element of matrix. If more than one matrix argument is provided, the reporter is given
the elements of each matrix as arguments. Thus,
(matrix:map + matrix1 matrix2)

would add matrix1 and matrix2.
This reporter is meant to be the same asmap, but for matrices instead of lists.

matrix:times-scalar
matrix:times-scalar matrix factor
As of NetLogo 5.1, matrix:times can multiply matrices by scalars making this function obsolete. Usematrix:times
instead.
Reports a new matrix, which is the result of multiplying every entry in the originalmatrix by the given scaling factor.

matrix:times
matrix:times m1 m2
matrix:times m1 m2 ...

Reports a matrix, which is the result of multiplying the given matrices and scalars (using standard matrix multiplication –
make sure your matrix dimensions match up.) Without parentheses, it takes two arguments. With parentheses it takes
two or more. The arguments may either be numbers or matrices, but at least one must be a matrix.

matrix:*
m1 matrix:* m2
Reports a matrix, which is the result of multiplying the given matrices and/or scalars (using standard matrix multiplication
– make sure your matrix dimensions match up.) This is exactly the same as matrix:times m1 m2
Takes precedence over matrix:+ and matrix:-, same as normal multiplication.

matrix:times-element-wise
matrix:times-element-wise m1 m2
Reports a matrix, which is the result of multiplying the given matrices together, element-wise. All elements are multiplied
by scalar arguments as well. Note that all matrix arguments must have the same dimensions. Without parentheses, it
takes two arguments. With parentheses it takes two or more. The arguments may either be numbers or matrices, but at
least one must be a matrix.

matrix:plus-scalar
matrix:plus-scalar matrix number
As of NetLogo 5.1, matrix:plus can add matrices and scalars making this function obsolete. Use matrix:plus instead.
Reports a matrix, which is the result of adding the constantnumber to each element of the given matrix.

matrix:plus
matrix:plus m1 m2
matrix:plus m1 m2 ...
Reports a matrix, which is the result of adding the given matrices and scalars. Scalars are added to each element.
Without parentheses, it takes two arguments. With parentheses it takes two or more. The arguments may either be
numbers or matrices, but at least one must be a matrix.

matrix:+
m1 matrix:+ m2
Reports a matrix, which is the result of adding the given matrices and/or scalars. This is exactly the same asmatrix:plus
m1 m2

Takes precedence after matrix:*, same as normal addition.

matrix:minus
matrix:minus m1 m2
matrix:minus m1 m2 ...
Reports a matrix, which is the result of subtracting all arguments besidesm1 from m1. Scalar arguments are treated as
matrices of the same size as the matrix arguments with every element equal to that scalar. Without parentheses, it takes
two arguments. With parentheses it takes two or more. The arguments may either be numbers or matrices, but at least
one must be a matrix.

matrix:m1 matrix:- m2
Reports a matrix, which is the result of subtracting the given matrices and/or scalars. This is exactly the same as
matrix:minus m1 m2

Takes precedence after matrix:*, same as normal subtraction.

matrix:inverse
matrix:inverse matrix
Reports the inverse of the given matrix, or results in an error if the matrix is not invertible.

matrix:transpose
matrix:transpose matrix
Reports the transpose of the given matrix.

matrix:real-eigenvalues
matrix:real-eigenvalues matrix
Reports a list containing the real eigenvalues of the givenmatrix.

matrix:imaginary-eigenvalues
matrix:imaginary-eigenvalues matrix
Reports a list containing the imaginary eigenvalues of the givenmatrix.

matrix:eigenvectors
matrix:eigenvectors matrix
Reports a matrix that contains the eigenvectors of the given matrix. (Each eigenvector as a column of the resulting
matrix.)

matrix:det
matrix:det matrix
Reports a the determinant of the matrix.

matrix:rank
matrix:rank matrix
Reports the effective numerical rank of the matrix,obtained from SVD (Singular Value Decomposition).

matrix:trace
matrix:trace matrix
Reports the trace of the matrix, which is simply the sum of the main diagonal elements.

matrix:solve
matrix:solve A C
Reports the solution to a linear system of equations, specified by theA and C matrices. In general, solving a set of linear
equations is akin to matrix division. That is, the goal is to find a matrix B such that A * B = C. (For simple linear systems,
C and B can both be 1-dimensional matrices – i.e. vectors). If A is not a square matrix, then a “least squares” solution is
returned.
;; To solve the set of equations x + 3y = 10 and 7x - 4y = 20
;; We make our A matrix [[1 3][7 -4]], and our C matrix [[10][20]]
let A matrix:from-row-list [[1 3][7 -4]]
let C matrix:from-row-list [[10][20]]
print matrix:solve A C
=> {{matrix: [ [ 4 ][ 2.0000000000000004 ] ]}}
;; NOTE: as you can see, the results may be only approximate
;; (In this case, the true solution should be x=4 and y=2.)

matrix:forecast-linear-growth
matrix:forecast-linear-growth data-list
Reports a four-element list of the form:
[ forecast constant slope R 2 ]

The forecast is the predicted next value that would follow in the sequence given by thedata-list input, based on a linear
trend-line. Normally data-list will contain observations on some variable, Y, from time t = 0 to time t = (n-1) where n is the
number of observations. The forecast is the predicted value of Y at t = n. Theconstant and slope are the parameters of
the trend-line
Y = *constant* + *slope* * t.
2 = 1 being a perfect fit and an R2 of 0
The R 2 value measures the goodness of fit of the trend-line to the data, with an R
indicating no discernible trend. Linear growth assumes that the variable Y grows by a constant absolute amount each
period.
;; a linear extrapolation of the next item in the list.
print matrix:forecast-linear-growth [20 25 28 32 35 39]
=> [42.733333333333334 20.619047619047638 3.6857142857142824 0.9953743395474031]
;; These results tell us:
;; * the next predicted value is roughly 42.7333
;; * the linear trend line is given by Y = 20.6190 + 3.6857 * t
;; * Y grows by approximately 3.6857 units each period
;; * the R^2 value is roughly 0.9954 (a good fit)

matrix:forecast-compound-growth
matrix:forecast-compound-growth data-list
Reports a four-element list of the form:
[ forecast constant growth-proportion R 2 ]

Whereas matrix:forecast-linear-growth assumes growth by a constant absolute amount each period,matrix:forecastcompound-growth assumes that Y grows by a constant proportion each period. The constant and growth-proportion are
the parameters of the trend-line
Y = constant * growth-proportion t .

Note that the growth proportion is typically interpreted as growth-proportion = (1.0 + growth-rate). Therefore, if
matrix:forecast-compound-growth returns a growth-proportion of 1.10, that implies that Y grows by (1.10 - 1.0) = 10%
each period. Note that if growth is negative, matrix:forecast-compound-growth will return a growth-proportion of less than
one. E.g., a growth-proportion of 0.90 implies a growth rate of -10%.
NOTE: The compound growth forecast is achieved by taking the ln of Y. (Seematrix:regress, below.) Because it is
impossible to take the natural log of zero or a negative number, matrix:forecast-compound-growth will result in an error if
it finds a zero or negative number in data-list.
;; a compound growth extrapolation of the next item in the list.
print matrix:forecast-compound-growth [20 25 28 32 35 39]
=> [45.60964465307147 21.15254147944863 1.136621034423892 0.9760867518334806]
;; These results tell us:
;; * the next predicted value is approximately 45.610
;; * the compound growth trend line is given by Y = 21.1525 * 1.1366 ^ t
;; * Y grows by approximately 13.66% each period
;; * the R^2 value is roughly 0.9761 (a good fit)

matrix:forecast-continuous-growth
matrix:forecast-continuous-growth data-list
Reports a four-element list of the form:
growth-rate R2 ] . Whereas matrix:forecast-compound-growth assumes discrete time with Y
growing by a given proportion each finite period of time (e.g., a month or a year), matrix:forecast-continuous-growth
assumes that Y is compounded continuously (e.g., each second or fraction of a second). Theconstant and growth-rate
are the parameters of the trend-line
[ forecast constant

Y = constant * e (growth-rate * t)

matrix:forecast-continuous-growth is the “calculus” analog of matrix:forecast-compound-growth. The two will normally
yield similar (but not identical) results, as shown in the example below. growth-rate may, of course, be negative.
NOTE: The continuous growth forecast is achieved by taking the ln of Y. (Seematrix:regress, below.)
Because it is impossible to take the natural log of zero or a negative number, matrix:forecast-continuous-growth
will result in an error if it finds a zero or negative number in data-list.

;; a continuous growth extrapolation of the next item in the list.
print matrix:forecast-continuous-growth [20 25 28 32 35 39]
=> [45.60964465307146 21.15254147944863 0.12805985615332668 0.9760867518334806]
;; These results tell us:
;; * the next predicted value is approximately 45.610
;; * the compound growth trend line is given by Y = 21.1525 * e ^ (0.1281 * t)
;; * Y grows by approximately 12.81% each period if compounding takes place continuously
;; * the R^2 value is roughly 0.9761 (a good fit)

matrix:regress
matrix:regress data-matrix
All three of the forecast primitives above are just special cases of performing an OLS (ordinary-least-squares) linear
regression – the matrix:regress primitive provides a flexible/general-purpose approach. The input is a matrix data-matrix,
with the first column being the observations on the dependent variable and each subsequent column being the
observations on the (1 or more) independent variables. Thus each row consists of an observation of the dependent
variable followed by the corresponding observations for each independent variable.
The output is a Logo nested list composed of two elements. The first element is a list containing the regression constant
followed by the coefficients on each of the independent variables. The second element is a 3-element list containing the
R 2 statistic, the total sum of squares, and the residual sum of squares. The following code example shows how the
matrix:regress primitive can be used to perform the same function as the code examples shown in the matrix:forecast-*growth primitives above. (However, keep in mind that the matrix:regress primitive is more powerful than this, and can
have many more independent variables in the regression, as indicated in the fourth example below.)
;; this is equivalent to what the matrix:forecast-linear-growth does
let data-list [20 25 28 32 35 39]
let indep-var (n-values length data-list [ x -> x ]) ; 0,1,2...,5
let lin-output matrix:regress matrix:from-column-list (list data-list indep-var)
let lincnst item 0 (item 0 lin-output)
let linslpe item 1 (item 0 lin-output)
let linR2
item 0 (item 1 lin-output)
;;Note the "6" here is because we want to forecast the value at time t=6.
print (list (lincnst + linslpe * 6) (lincnst) (linslpe) (linR2))
;; this is equivalent to what the matrix:forecast-compound-growth does
let com-log-data-list (map ln [20 25 28 32 35 39])
let com-indep-var2 (n-values length com-log-data-list [ x -> x ]) ; 0,1,2...,5
let com-output matrix:regress matrix:from-column-list (list com-log-data-list com-indep-var2)
let comcnst exp item 0 (item 0 com-output)
let comprop exp item 1 (item 0 com-output)
let comR2
item 0 (item 1 com-output)
;;Note the "6" here is because we want to forecast the value at time t=6.
print (list (comcnst * comprop ^ 6) (comcnst) (comprop) (comR2))
;; this is equivalent to what the matrix:forecast-continuous-growth does
let con-log-data-list (map ln [20 25 28 32 35 39])
let con-indep-var2 (n-values length con-log-data-list [ x -> x ]) ; 0,1,2...,5
let con-output matrix:regress matrix:from-column-list (list con-log-data-list con-indep-var2)
let concnst exp item 0 (item 0 con-output)
let conrate
item 1 (item 0 con-output)
let conR2
item 0 (item 1 con-output)
print (list (concnst * exp (conrate * 6)) (concnst) (conrate) (conR2))
;; example of a regression with two independent variables:
;; Pretend we have a dataset, and we want to know how well happiness
;; is correlated to snack-food consumption and accomplishing goals.
let happiness [2 4 5 8 10]
let snack-food-consumed [3 4 3 7 8]
let goals-accomplished [2 3 5 8 9]
print matrix:regress matrix:from-column-list (list happiness snack-food-consumed goals-accomplished)
=> [[-0.14606741573033788 0.3033707865168543 0.8202247191011234] [0.9801718440185063 40.8 0.8089887640449439]]
;; linear regression: happiness = -0.146 + 0.303*snack-food-consumed + 0.820*goals-accomplished
;; (Since the 0.820 coefficient is higher than the 0.303 coefficient, it appears that each goal
;; accomplished yields more happiness than does each snack consumed, although both are positively
;; correlated with happiness.)
;; Also, we see that R^2 = 0.98, so the two factors together provide a good fit.

NetLogo Nw Extension
Usage
The first thing that one needs to understand in order to work with the network extension is how to tell the extension
which network to work with. Consider the following example situation:
breed [ bankers banker ]
breed [ clients client ]
undirected-link-breed [ friendships friendship ]
directed-link-breed [ accounts account ]

Basically, you have bankers and clients. Clients can have accounts with bankers. Bankers can probably have
account with other bankers, and anyone can be friends with anyone.
Now we might want to consider this whole thing as one big network. If that is the case, there is nothing special to do:
by default, the NW extension primitives consider all turtles and all links to be part of the current network.
We could also, however, be only interested in a subset of the network. Maybe we want to consider only friendship
relations. Furthermore, maybe we want to consider only the friendships between bankers. After all, having a very
high centrality in a network of banker friendships is very different from having a high centrality in a network of client
friendships.
To specify such networks, we need to tell the extensionboth which turtles and which links we are interested in. All
the turtles from the specified set of turtles will be included in the network, and only the links from the specified set of
links that are between turtles of the specified set will be included. For example, if you ask for bankers and
friendships, even the lonely bankers with no friends will be included, but friendship links between bankers and
clients will not be included. The way to tell the extension about this is with thenw:set-context primitive, which you
must call prior to doing any operations on a network.
Some examples:
nw:set-context turtles links

will give you everything: bankers and clients, friendships and accounts, as one big

network.
nw:set-context turtles friendships

will give you all the bankers and clients and friendships between any of

them.
nw:set-context bankers friendships will give you
nw:set-context bankers links will give you all the

all the bankers, and only friendships between bankers.
bankers, and any links between them, whether these links are

friendships or accounts.
will give you all the clients, and accounts between each other, but since in our
fictional example clients can only have accounts with bankers, this will be a completely disconnected network.
nw:set-context clients accounts

Special agentsets vs normal agentsets
It must be noted that NetLogo has two types of agentsets that behave slightly differently, and that this has an impact
on the way nw:set-context works. We will say a few words about these concepts here but, for a thorough
understanding, it is highly recommended that you read the section on agentsets in the NetLogo programming guide.
The “special” agentsets in NetLogo are turtles , links and the different “breed” agentsets. What is special about
them is that they can grow: if you create a new turtle, it will be added to the turtles agentset. If you have a bankers
breed and you create a new banker, it will be added to the bankers agentset and to the turtles agentset. Same goes
for links. Other agentsets, such as those created with the with primitive (e.g., turtles with [ color = red ] ) or the
turtle-set and link-set primitives) are never added to. The content of normal agentsets will only change if the
agents that they contain die.
To show how different types of agentsets interact withnw:set-context , let’s create a very simple network:
clear-all
create-turtles 3 [ create-links-with other turtles ]

Let’s set the context to turtles and links (which is the default anyway) and use nw:get-context to see what we
have:
nw:set-context turtles links
show map sort nw:get-context

We get all three turtles and all three links:

[[(turtle 0) (turtle 1) (turtle 2)] [(link 0 1) (link 0 2) (link 1 2)]]

Now let’s kill one turtle:
ask one-of turtles [ die ]
show map sort nw:get-context

As expected, the context is updated to reflect the death of the turtle and of the two links that died with it:
[[(turtle 0) (turtle 1)] [(link 0 1)]]

What if we now create a new turtle?
create-turtles 1
show map sort nw:get-context

Since our context is using the special turtles agentset, the new turtle is automatically added:
[[(turtle 0) (turtle 1) (turtle 3)] [(link 0 1)]]

Now let’s demonstrate how it works with normal agentsets. We start over with a new network of red turtles:
clear-all
create-turtles 3 [
create-links-with other turtles
set color red
]

And we set the context to turtles with [ color = red ]) and links
nw:set-context (turtles with [ color = red ]) links
show map sort nw:get-context

Since all turtles are red, we get everything in our context:
[[(turtle 0) (turtle 1) (turtle 2)] [(link 0 1) (link 0 2) (link 1 2)]]

But what if we ask one of them to turn blue?
ask one-of turtles [ set color blue ]
show map sort nw:get-context

No change. The agentset used in our context remains unaffected:
[[(turtle 0) (turtle 1) (turtle 2)] [(link 0 1) (link 0 2) (link 1 2)]]

If we kill one of them, however…
ask one-of turtles [ die ]
show map sort nw:get-context

It gets removed from the set:
[[(turtle 0) (turtle 2)] [(link 0 2)]]

What if we add a new red turtle?
create-turtles 1 [ set color red ]
show map sort nw:get-context

Nope:
[[(turtle 0) (turtle 2)] [(link 0 2)]]

A note regarding floating point calculations
Neither JGraphT nor Jung, the two network libraries that we use internally, usestrictfp floating point calculations.
This does mean that exact reproducibility of results involving floating point calculations between different hardware
architectures is not fully guaranteed. (NetLogo itself always uses strict math so this only applies to some primitives of
the NW extension.)

Performance
In order to be fast in as many circumstances as possible, the NW extension tries hard to never calculate things
twice. It remembers all paths, distances, and centralities that it calculates. So, while the first time you ask for the
distance between turtle 0 and turtle 3782 may take some time, after that, it should be almost instantaneous.
Furthermore, it keeps track of values it just happened to calculate along the way. For example, if turtle 297 is closer
to turtle 0 than turtle 3782 is, it may just happen to figure out the distance betweenturtle 0 and turtle 297 while
it figures out the distance between turtle 0 and turtle 3782. It will remember this value, so that if you ask it for the
distance between turtle 0 and turtle 297, it doesn’t have to do all that work again.
There are a few circumstances where the NW extension has to forget things. If the network changes at all (you add
turtles or links, or remove turtles or links), it has to forget everything. For weighted primitives, if the value of the
weight variable changes for any of the links in the network, it will forget the values associated with that weight
variable.
If you’re working on a network that can change regularly, try to do all your network calculations at once, then all your
network changes at once. The more your interweave network calculations and network changes, the more the NW
extension will have to recalculate things. For example, if you have a traffic model, and cars need to figure out the
shortest path to their destination based on the traffic each tick, have all the cars find their shortest paths, then
change the network weights to account for how traffic has changed.
There may be rare occasions in which you don’t want the NW extension to remember values. For example, if you’re
working on an extremely large network, remembering all those values may take more memory than you have. In that
case, you can just call nw:set-context (first nw:get-context) (last nw:get-context) to force the NW extension to
immediately forget everything.

Primitives
Generators
nw:generate-preferential-attachment nw:generate-random nw:generate-watts-strogatz nw:generate-small-world
nw:generate-lattice-2d nw:generate-ring nw:generate-star nw:generate-wheel

Path and Distance
nw:turtles-in-radius nw:turtles-in-reverse-radius nw:distance-to nw:weighted-distance-to nw:path-to nw:turtleson-path-to nw:weighted-path-to nw:turtles-on-weighted-path-to nw:mean-path-length nw:mean-weighted-path-length

Clusterer/Community Detection
nw:bicomponent-clusters nw:weak-component-clusters nw:louvain-communities nw:maximal-cliques nw:biggestmaximal-cliques

Context Management
nw:set-context nw:get-context nw:with-context

Import and Export
nw:save-matrix nw:load-matrix nw:save-graphml nw:load-graphml nw:load nw:save

Centrality Measures
nw:betweenness-centrality nw:eigenvector-centrality nw:page-rank nw:closeness-centrality nw:weighted-closenesscentrality

Clustering Measures

nw:clustering-coefficient nw:modularity

nw:set-context
nw:set-context turtleset linkset
Specifies the set of turtles and the set of links that the extension will consider to be the current graph. All the turtles
from turtleset and all the links from linkset that connect two turtles from turtleset will be included.
This context is used by all other primitives (unless specified otherwise) until a new context is specified. (At the
moment, only the generator primitives and the file input primitives are exceptions to this rule.)
See the usage section for a much more detailed explanation of nw:set-context .

nw:get-context
nw:get-context
Reports the content of the current graph context as a list containing two agentsets: the agentset of turtles that are
part of the context and the agentset of links that are part of the context.
Let’s say we start with a blank slate and the default context consisting ofturtles and links, nw:get-context will
report a list the special turtles and links breed agentsets:
observer> clear-all
observer> show nw:get-context
observer: [turtles links]

If we add some turtles and links to our context, we’ll still see the same thing, even thoughturtles and links have
internally grown:
observer> crt 2 [ create-links-with other turtles ]
observer> show nw:get-context
observer: [turtles links]

If you had set your context to normal agentsets instead (built withturtle-set, link-set or with) here is what you
would see:
observer>
observer>
observer>
observer:

clear-all
nw:set-context turtle-set turtles link-set links
show nw:get-context
[(agentset, 0 turtles) (agentset, 0 links)]

If you then create new turtles and links, they are not added to the context because normal agentsets don’t grow (see
Special agentsets vs normal agentsets):
observer> crt 2 [ create-links-with other turtles ]
observer> show nw:get-context
observer: [(agentset, 0 turtles) (agentset, 0 links)]

But if you construct new agentsets and set the context to them, your new agents will be there:
observer> nw:set-context turtle-set turtles link-set links
observer> show nw:get-context
observer: [(agentset, 2 turtles) (agentset, 1 link)]

If you want to see the actual content of your context, it is easy to turn your agentsets into lists that can be nicely
displayed. Just use a combination of map and sort:
observer> show map sort nw:get-context
observer: [[(turtle 0) (turtle 1)] [(link 0 1)]]

Finally, you can use nw:get-context to store a context that you eventually want to restore:
extensions [ nw ]
to store-and-restore-context
clear-all
crt 2 [
set color red

create-links-with other turtles with [ color = red ] [
set color yellow
]
]
crt 2 [
set color blue
create-links-with other turtles with [ color = blue ] [
set color green
]
]
nw:set-context turtles with [ color = red ] links with [ color = yellow ]
show map sort nw:get-context
let old-turtles item 0 nw:get-context
let old-links item 1 nw:get-context
nw:set-context turtles with [ color = blue ] links with [ color = green ]
show map sort nw:get-context
nw:set-context old-turtles old-links
show map sort nw:get-context
end

Here is the result:
observer>
observer:
observer:
observer:

store-and-restore-context
[[(turtle 0) (turtle 1)] [(link 0 1)]]
[[(turtle 2) (turtle 3)] [(link 2 3)]]
[[(turtle 0) (turtle 1)] [(link 0 1)]]

nw:with-context
nw:with-context turtleset linkset command-block
Executes the command-block with the context temporarily set to turtleset and linkset. After command-block finishes
running, the previous context will be restored.
For example:
observer>
observer>
observer:
observer>
observer:

create-turtles 3 [ create-links-with other turtles ]
nw:with-context (turtle-set turtle 0 turtle 1) (link-set link 0 1) [ show nw:get-context ]
[(agentset, 2 turtles) (agentset, 1 link)
show nw:get-context
[turtles links]

If you have NW extension code running in two forever buttons orloop blocks that each need to use different
contexts, you should use nw:with-context in each to make sure they are operating in the correct context.

nw:turtles-in-radius
nw:turtles-in-radius radius
Returns the set of turtles within the given distance (number of links followed) of the calling turtle in the current
context, including the calling turtle.
nw:turtles-in-radius form will follow both undirected
radius as “turtles who I can get to in radius steps”.

links and directed out links. You can think of turtles-in-

If you want the primitive to follow only undirected links or only directed links, you can do it by setting the context
appropriately. For example: nw:set-context turtles undir-links (assuming undir-links is an undirected link
breed) or nw:set-context turtles dir-links (assuming dir-links is a directed link breed).
Example:
clear-all
create-turtles 5
ask turtle 0 [ create-link-with turtle
ask turtle 0 [ create-link-with turtle
ask turtle 1 [ create-link-with turtle
ask turtle 2 [ create-link-with turtle
ask turtle 0 [
show sort nw:turtles-in-radius 1
]

1
2
3
4

]
]
]
]

Will output:
(turtle 0): [(turtle 0) (turtle 1) (turtle 2)]

As you may have noticed, the result includes the calling turtle. This mimics the behavior of the regular NetLogoinradius primitive.

nw:turtles-in-reverse-radius
nw:turtles-in-reverse-radius radius
Like nw:turtles-in-radius, but follows in-links instead of out-links. Also follow undirected links. You can think of
turtles-in-reverse-radius as “turtles who can get to me in radius steps”.

nw:distance-to
nw:distance-to target-turtle
Finds the shortest path to the target turtle and reports the total distance for this path, or false if no path exists in the
current context. Each link counts for a distance of one.
Example:
to go
clear-all
create-turtles
ask turtle 0 [
ask turtle 1 [
ask turtle 0 [
ask turtle 3 [
ask turtle 4 [
ask turtle 0 [
end

5
create-link-with turtle 1 ]
create-link-with turtle 2 ]
create-link-with turtle 3 ]
create-link-with turtle 4 ]
create-link-with turtle 2 ]
show nw:distance-to turtle 2 ]

Will output:
(turtle 0): 2

nw:weighted-distance-to
nw:weighted-distance-to target-turtle weight-variable
Like nw:distance-to, but takes link weight into account. The weights cannot be negative numbers.
Example:
links-own [ weight ]
to go
clear-all
create-turtles 5
ask turtle 0 [ create-link-with turtle 1 [ set weight 2.0 ]
ask turtle 1 [ create-link-with turtle 2 [ set weight 2.0 ]
ask turtle 0 [ create-link-with turtle 3 [ set weight 0.5 ]
ask turtle 3 [ create-link-with turtle 4 [ set weight 0.5 ]
ask turtle 4 [ create-link-with turtle 2 [ set weight 0.5 ]
ask turtle 0 [ show nw:weighted-distance-to turtle 2 weight
end

]
]
]
]
]
]

Will output:
(turtle 0): 1.5

nw:path-to
nw:path-to target-turtle
Finds the shortest path to the target turtle and reports the actual path between the source and the target turtle. The
path is reported as the list of links that constitute the path.
If no path exist between the source and the target turtles,false will be reported instead.
Note that the NW-Extension remembers paths that its calculated previously unless the network changes. Thus, you
don’t need to store paths to efficiently move across the network; you can just keep re-calling one of the path
primitives. If the network changes, however, the stored answers are forgotten. Example:

links-own [ weight ]
to go
clear-all
create-turtles 5
ask turtle 0 [ create-link-with turtle 1 ]
ask turtle 1 [ create-link-with turtle 2 ]
ask turtle 0 [ create-link-with turtle 3 ]
ask turtle 3 [ create-link-with turtle 4 ]
ask turtle 4 [ create-link-with turtle 2 ]
ask turtle 0 [ show nw:path-to turtle 2 ]
end

Will output:
(turtle 0): [(link 0 1) (link 1 2)]

nw:turtles-on-path-to
nw:turtles-on-path-to target-turtle
Like nw:path-to, but the turtles on the path are reported, instead of the links, including the source turtle and target
turtle.
Example:
to go
clear-all
create-turtles
ask turtle 0 [
ask turtle 1 [
ask turtle 0 [
ask turtle 3 [
ask turtle 4 [
ask turtle 0 [
end

5
create-link-with turtle 1 ]
create-link-with turtle 2 ]
create-link-with turtle 3 ]
create-link-with turtle 4 ]
create-link-with turtle 2 ]
show nw:turtles-on-path-to turtle 2 ]

Will output:
(turtle 0): [(turtle 0) (turtle 1) (turtle 2)]

nw:weighted-path-to
nw:weighted-path-to target-turtle weight-variable
Like nw:path-to, but takes link weight into account.
Example:
links-own [ weight ]
to go
clear-all
create-turtles 5
ask turtle 0 [ create-link-with turtle 1 [ set
ask turtle 1 [ create-link-with turtle 2 [ set
ask turtle 0 [ create-link-with turtle 3 [ set
ask turtle 3 [ create-link-with turtle 4 [ set
ask turtle 4 [ create-link-with turtle 2 [ set
ask turtle 0 [ show nw:weighted-path-to turtle
end

weight 2.0
weight 2.0
weight 0.5
weight 0.5
weight 0.5
2 weight ]

Will output:
(turtle 0): [(link 0 3) (link 3 4) (link 2 4)]

nw:turtles-on-weighted-path-to
nw:turtles-on-weighted-path-to target-turtle weight-variable
Like nw:turtles-on-path-to, but takes link weight into account.

]
]
]
]
]

Example:
links-own [ weight ]
to go
clear-all
create-turtles 5
ask turtle 0 [ create-link-with turtle 1 [ set
ask turtle 1 [ create-link-with turtle 2 [ set
ask turtle 0 [ create-link-with turtle 3 [ set
ask turtle 3 [ create-link-with turtle 4 [ set
ask turtle 4 [ create-link-with turtle 2 [ set
ask turtle 0 [ show nw:weighted-path-to turtle
end

weight 2.0
weight 2.0
weight 0.5
weight 0.5
weight 0.5
2 weight ]

]
]
]
]
]

Will output:
(turtle 0): [(turtle 0) (turtle 3) (turtle 4) (turtle 2)]

nw:mean-path-length
nw:mean-path-length
Reports the average shortest-path length between all distinct pairs of nodes in the current context.
Reports false unless paths exist between all pairs.
Example:
links-own [ weight ]
to go
clear-all
create-turtles 3
ask turtle 0 [ create-link-with turtle 1 [ set weight 2.0 ] ]
ask turtle 1 [ create-link-with turtle 2 [ set weight 2.0 ] ]
show nw:mean-path-length
create-turtles 1 ; create a new, disconnected turtle
show nw:mean-path-length
end

Will ouput:
observer: 1.3333333333333333
observer: false

nw:mean-weighted-path-length
nw:mean-weighted-path-length weight-variable
Like nw:mean-path-length, but takes into account link weights.
Example:
links-own [ weight ]
to go
clear-all
create-turtles 3
ask turtle 0 [ create-link-with turtle 1 [ set weight 2.0 ] ]
ask turtle 1 [ create-link-with turtle 2 [ set weight 2.0 ] ]
show nw:mean-path-length
show nw:mean-weighted-path-length weight
create-turtles 1 ; create a new, disconnected turtle
show nw:mean-path-length
show nw:mean-weighted-path-length weight
end

Will ouput:
observer: 2.6666666666666665
observer: false

nw:betweenness-centrality

nw:betweenness-centrality
To calculate the betweenness centrality of a turtle, you take every other possible pairs of turtles and, for each pair,
you calculate the proportion of shortest paths between members of the pair that passes through the current turtle.
The betweenness centrality of a turtle is the sum of these.
As of now, link weights are not taken into account.

nw:eigenvector-centrality
nw:eigenvector-centrality
The Eigenvector centrality of a node can be thought of as the amount of influence a node has on a network. In
practice, turtles that are connected to a lot of other turtles that are themselves well-connected (and so on) get a
higher Eigenvector centrality score.
In this implementation, the eigenvector centrality is normalized such that the highest eigenvector centrality a node
can have is 1. This implementation is designed to agree with Gephi’s implementation out to at least 3 decimal
places. If you discover that it disagrees with Gephi on a particular network, please report it.
The primitive respects link direction, even in mixed-directed networks. This is the one place where it should disagree
with Gephi; Gephi refuses to treat directed links as directed in mixed-networks.
As of now, link weights are not taken into account.

nw:page-rank
nw:page-rank
The page rank of a node can be thought of as the proportion of time that an agent walking forever at random on the
network would spend at this node. The agent has an equal chance of taking any of a nodes edges, and will jump
around the network completely randomly 15% of the time. In practice, like with eigenvector centrality, turtles that are
connected to a lot of other turtles that are themselves well-connected (and so on) get a higher page rank.
Page rank is one of the several algorithms that search engines use to determine the importance of a website.
The sum of all page rank values should be approximately one. Unlike eigenvector centrality, page rank is defined for
all networks, no matter the connectivity. Currently, it treats all links as undirected links.
As of now, link weights are not taken into account.

nw:closeness-centrality
nw:closeness-centrality
The closeness centrality of a turtle is defined as the inverse of the average of it’s distances to all other turtles. (Some
people use the sum of distances instead of the average, but the extension uses the average.)
Note that this primitive reports the intra-component closeness of a turtle, that is, it takes into account only the
distances to the turtles that are part of the same component as the current turtle, since distance to turtles in other
components is undefined. The closeness centrality of an isolated turtle is defined to be zero.

nw:weighted-closeness-centrality
nw:weighted-closeness-centrality link-weight-variable
This is identical to nw:closeness-centrality, except that weights provided by the given variable are treated as the
distances of links.

nw:clustering-coefficient
nw:clustering-coefficient
Reports the local clustering coefficient of the turtle. The clustering coefficient of a node measures how connected its
neighbors are. It is defined as the number of links between the node’s neighbors divided by the total number of
possible links between its neighbors.

takes the directedness of links into account. A directed link counts as a single link
whereas an undirected link counts as two links (one going one-way, one going the other).
nw:clustering-coefficient

The global clustering coefficient measures how much nodes tend to cluster together in the network in general. It is
defined based on the types of triplets in the network. A triplet consists of a central node and two of its neighbors. If its
neighbors are also connected, it’s a closed triplet. If its neighbors are not connected, it’s an open triplet. The global
clustering coefficient is simply the number of closed triplets in a network divided by the total number of triplets. It can
be calculated from the local clustering coefficient quite easily with the following code
to-report global-clustering-coefficient
let closed-triplets sum [ nw:clustering-coefficient * count my-links * (count my-links - 1) ] of turtles
let triplets sum [ count my-links * (count my-links - 1) ] of turtles
report closed-triplets / triplets
end

Note that the above will only work with the default context, and may need to tweaked if you’ve set the turtles or links
in the network to something other than turtles and links.
The average local clustering coefficient is another popular method for measuring the amount of clustering in the
network as a whole. It may be calculated with
mean [ nw:clustering-coefficient ] of turtles

nw:modularity
nw:modularity
Modularity is a measurement of community structure in the network. It is defined based on the number of incommunity links versus the number of between-community links. This primitive takes as input a list of agentsets,
where each of the agentsets is one the communities that you’re separating the network into.
This measurement works on undirected, directed, and mixed-directedness networks. In the case of mixeddirectedness, undirected links are treated essentially the same as two opposing directed links. It does not take
weight into account.
Example:
nw:modularity (list (turtles with [ color = blue ]) (turtles with [ color = red ]))

nw:bicomponent-clusters
nw:bicomponent-clusters
Reports the list of bicomponent clusters in the current network context. A bicomponent (also known as a maximal
biconnected subgraph) is a part of a network that cannot be disconnected by removing only one node (i.e. you need
to remove at least two to disconnect it). The result is reported as a list of agentsets, in random order. Note that one
turtle can be a member of more than one bicomponent at once.

nw:weak-component-clusters
nw:weak-component-clusters
Reports the list of “weakly” connected components in the current network context. A weakly connected component is
simply a group of nodes where there is a path from each node to every other node. A “strongly” connected
component would be one where there is a directed path from each node to every other. The extension does not
support the identification of strongly connected components at the moment.
The result is reported as a list of agentsets, in random order. Note that one turtlecannot be a member of more than
one weakly connected component at once.

nw:louvain-communities
nw:louvain-communities
Detects community structure present in the network. It does this by maximizingmodularity using the Louvain method.
The communities are reported as a list of turtle-sets.

Often you’ll want to tell turtles about the community that they are in. You can do this like so:
turtles-own [ community ]
...
foreach nw:louvain-communities [ [comm] ->
ask comm [ set community comm ]
]

You can give each community its own color with something like this:
let communities nw:louvain-communities
let colors sublist 0 (length communities) base-colors
(foreach communities colors [ [community col] ->
ask community [ set color col ]
])

nw:maximal-cliques
nw:maximal-cliques
A clique is a subset of a network in which every node has a direct link to every other node. A maximal clique is a
clique that is not, itself, contained in a bigger clique.
The result is reported as a list of agentsets, in random order. Note that one turtle can be a member of more than one
maximal clique at once.
The primitive uses the Bron–Kerbosch algorithm and only works with undirected links.

nw:biggest-maximal-cliques
nw:biggest-maximal-cliques
The biggest maximal cliques are, as the name implies, the biggest cliques in the current context. Often, more than
one clique are tied for the title of biggest clique, so the result is reported as a list of agentsets, in random order. If you
want only one clique, use one-of nw:biggest-maximal-cliques .
The primitive uses the Bron–Kerbosch algorithm and only works with undirected links.

nw:generate-preferential-attachment
nw:generate-preferential-attachment turtle-breed link-breed num-nodes min-degree optional-commandblock
Generates a new network using a version of the Barabási–Albert algorithm. This network will have the property of
being “scale free”: the distribution of degrees (i.e. the number of links for each turtle) should follow a power law.
Generation works as follows turtles are added, one by one, each formingmin-degree links to a previously added
turtles, until num-nodes is reached. The more links a turtle already has, the greater the probability that new turtles
form links with it when they are added.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-preferential-attachment turtles links 100 1 [ set color red ]

nw:generate-random
nw:generate-random turtle-breed link-breed num-nodes connection-probability optional-command-block
Generates a new random network of num-nodes turtles in which each one has a connection-probability (between 0
and 1) of being connected to each other turtles. The algorithm uses the G(n, p) variant of the Erdős–Rényi model.
The algorithm is O(n²) for directed networks and O(n²/2) for undirected networks, so generating more than a couple
thousand nodes will likely take a very long time.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:

nw:generate-random turtles links 100 0.5 [ set color red ]

nw:generate-watts-strogatz
nw:generate-watts-strogatz turtle-breed link-breed num-nodes neighborhood-size rewire-probability
optional-command-block
Generates a new Watts-Strogatz small-world network.
The algorithm begins by creating a ring of nodes, where each node is connected toneighborhood-size nodes on
either side. Then, each link is rewired with probability rewire-prob.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. Furthermore,
the turtles are generated in the order they appear as in create-ordered-turtles . So, in order to lay the ring out as a
ring, you can do something like:
nw:generate-watts-strogatz turtles links 50 2 0.1 [ fd 10 ]

nw:generate-small-world
nw:generate-small-world turtle-breed link-breed row-count column-count clustering-exponent is-toroidal
optional-command-block
Generates a new small-world network using the Kleinberg Model. Note that nw:generate-watts-strogatz generates a
more traditional small-world network.
The algorithm proceeds by generating a lattice of the given number of rows and columns (the lattice will wrap around
itself if is-toroidal is true). The “small world effect” is created by adding additional links between the nodes in the
lattice. The higher the clustering-exponent, the more the algorithm will favor already close-by nodes when adding
new links. A clustering exponent of 2.0 is typically used.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-small-world turtles links 10 10 2.0 false [ set color red ]

The turtles are generated in the order that they appear in the lattice. So, for instance, to generate a kleinberg lattice
accross the entire world, and lay it out accordingly, try the following:
nw:generate-small-world turtles links world-width world-height 2.0 false
(foreach (sort turtles) (sort patches) [ [t p] -> ask t [ move-to p ] ])

nw:generate-lattice-2d
nw:generate-lattice-2d turtle-breed link-breed row-count column-count is-toroidal optional-command-block
Generates a new 2D lattice network (basically, a grid) of row-count rows and column-count columns. The grid will
wrap around itself if is-toroidal is true.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-lattice-2d turtles links 10 10 false [ set color red ]

The turtles are generated in the order that they appear in the lattice. So, for instance, to generate a lattice accross
the entire world, and lay it out accordingly, try the following:
nw:generate-lattice-2d turtles links world-width world-height false
(foreach (sort turtles) (sort patches) [ [t p] -> ask t [ move-to p ] ])

nw:generate-ring
nw:generate-ring turtle-breed link-breed num-nodes optional-command-block
Generates a ring network of num-nodes turtles, in which each turtle is connected to exactly two other turtles.

The number of nodes must be at least three.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-ring turtles links 100 [ set color red ]

nw:generate-star
nw:generate-star turtle-breed link-breed num-nodes optional-command-block
Generates a star network in which there is one central turtle and every other turtle is connected only to this central
node. The number of turtles can be as low as one, but it won’t look much like a star.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-star turtles links 100 [ set color red ]

nw:generate-wheel
nw:generate-wheel turtle-breed link-breed num-nodes optional-command-block
Variants:
nw:generate-wheel-inward
nw:generate-wheel-outward

Generates a wheel network, which is basically a ring network with an additional “central” turtle that is connected to
every other turtle.
The number of nodes must be at least four.
The nw:generate-wheel only works with undirected link breeds. The nw:generate-wheel-inward and nw:generatewheel-outward versions only work with directed link-breed. The inward and outward part of the primitive names refer
to the direction that the “spokes” of the wheel point to relative to the central turtle.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:generate-wheel turtles links 100 [ set color red ]

nw:save-matrix
nw:save-matrix file-name
Saves the current network, as defined bynw:set-context , to file-name, as a text file, in the form of a simple
connection matrix.
Here is, for example, a undirected ring network with four nodes:
0.00
1.00
0.00
1.00

1.00
0.00
1.00
0.00

0.00
1.00
0.00
1.00

1.00
0.00
1.00
0.00

And here is the directed version:
0.00
0.00
0.00
1.00

1.00
0.00
0.00
0.00

0.00
1.00
0.00
0.00

0.00
0.00
1.00
0.00

At the moment, nw:save-matrix does not support link weights. Every link is represented as a “1.00” in the connection
matrix. This will change in a future version of the extension.

nw:load-matrix
nw:load-matrix file-name optional-command-block

Generates a new network according to the connection matrix saved infile-name, using turtle-breed and link-breed to
create the new turtles and links.
At the moment, nw:load-matrix does not support link weights.
Please be aware that the breeds that use use to load the matrix may be different from those that you used when you
saved it.
For example:
extensions [ nw ]
directed-link-breed [ dirlinks dirlink ]
to go
clear-all
crt 5 [ create-dirlinks-to other turtles ]
nw:set-context turtles dirlinks
nw:save-matrix "matrix.txt"
clear-all
nw:load-matrix "matrix.txt" turtles links
layout-circle turtles 10
end

…will give you back undirected links, even if you saved directed links into the matrix.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:load-matrix "matrix.txt" turtles links [ set color red ]

nw:save-graphml
nw:save-graphml file-name
You can save the current graph to GraphML. The following NetLogo code:
extensions [ nw ]
breed [ bankers banker ]
bankers-own [ bank-name ]
breed [ clients client ]
clients-own [ hometown ]
undirected-link-breed [ friendships friendship ]
directed-link-breed [ accounts account ]
accounts-own [ amount ]
to go
clear-all
create-bankers 1 [
set bank-name "The Bank"
]
create-clients 1 [
set hometown "Turtle City"
create-friendship-with banker 0
create-account-to banker 0 [
set amount 9999.99
]
]
nw:set-context turtles links
nw:save-graphml "example.graphml"
end

Will produce the following GraphML file:

up
0
1

default
clients
1
false
9.9
356
Turtle City
115
0
1

up
0
1

default
bankers
0
false
9.9
32
The Bank
85
0
1

(client 1)
none
(banker 0)
9.9
0

default
accounts
5
9999.99
false

(banker 0)
none
(client 1)
9.9
0

default
friendships
5
false

A few things to notice:
The breed is stored as data field, both for nodes and edges.
The data includes both NetLogo’s internal variables and the variables that were defined as eitherbreeds-own,
turtles-own, linkbreeds-own or links-own.
Each key gets an attr.type based on the actual types of the values contained in the agent variables. The three
possible types are "string", "double" and "boolean". To determine the attribute type of a particular agent variable,
the extension will look at the first agent in the graph. To see which agent is first, you can look at the result of
nw:get-context . Note that variables containing other types of values, such as turtles, patches, lists, etc., will be
stored as strings.
This example only has a directed link, and you will notice the element. If we had
only undirected links, we would have . What if we try to mix both kinds of link?
At the moment, the extension will save such a “mixed” graph as if it were an undirected graph (see this issue for
more details). The order of the source and target will be respected, however, so if you know which breeds
represent directed links, you can figure it out a posteriori.

nw:load-graphml

nw:load-graphml file-name optional-command-block
Loading a GraphML file into NetLogo with the network extension should be as simple as callingnw:load-graphml
"example.graphml" , but there is a bit of preparation involved.
The key idea is that nw:load-graphml will try to assign the attribute values defined in the GraphML file to NetLogo
agent variables of the same names (this is not case sensitive). The first one it tries to set is breed if it is there, so the
turtle or link will get the right breed and, hence, the right breed variables.
One special case is the who number, which is ignored by the importer if it is present as a GraphML attribute: NetLogo
does not allow you to modify this number once a turtle is created and, besides, there could already be an existing
turtle with that number.
The simplest case to handle is when the original GraphML file has been saved from NetLogo by usingnw:savegraphml . In this case, all you should have to do is to make sure that you have the same breed and variables
definition as when you saved the file and you should get back your original graph. For example, if you want to load
the file from the nw:save-graphml example above, you should have the following definitions:
breed [ bankers banker ]
bankers-own [ bank-name ]
breed [ clients client ]
clients-own [ hometown ]
undirected-link-breed [ friendships friendship ]
directed-link-breed [ accounts account ]
accounts-own [ amount ]

Loading a graph that was saved from a different program than NetLogo is quite possible as well, but it may take a bit
of tinkering to get all the attribute-variable match up right. If you encounter major problems, please do not hesitate to
open an issue.
The extension will try to assign the type defined byattr.type to each variable that it loads. If it’s unable to convert it
to that type, it will load it as a string. If attr.type is not defined, or is set to an unknown value, the extension will first
try to load the value as a double, then try it as a boolean, and finally fall back on a string.
If you specify an optional-command-block, it is executed for each turtle in the newly created network. For example:
nw:load-graphml "example.graphml" [ set color red ]

Note that this command block can be used to build a list or an agentset containing the newly created nodes:
let node-list []
nw:load-graphml "example.graphml" [
set node-list lput self node-list
]
let node-set turtle-set node-list

nw:load
nw:load file-name default-turtle-breed default-link-breed optional-command-block
Filetype specific variants:
nw:load
nw:load-dl
nw:load-gdf
nw:load-gexf
nw:load-gml
nw:load-vna

Import the given file into NetLogo. Likenw:load-graphml, the importer will do its best to match node and edge
attributes in the file with turtle and link variables in NetLogo. If breed is specified for nodes and edges in the file and
exists in NetLogo, it will be used. Otherwise, the default turtle and link breeds are used.
Limitations:
Multigraphs are not supported in importing. Even if the file format supports it (and many don’t), only the first link
will be used on import. This is due to a limitation in the parsing libraries NW uses. nw:load-graphml does support
multigraphs with the normal NetLogo limitation that two turtles can share more than one link only if all the links are
of different breeds.

determines the file-type of given file based on the extension and calls the correspondingload-* primitive on
it. Note that GraphML must be imported with nw:load-graphml.
nw:load

nw:save
nw:save file-name
Filetype specific variants:
nw:save-dl
nw:save-gdf
nw:save-gexf
nw:save-gml
nw:save-vna

Export the network context in the given format to the given file. Turtle and link attributes will be exported to formats
that support node and edge properties.
Limitations:
and y (not xcor and ycor) can only be numbers. x and y are commonly used in formats pertaining to position and
behind the scenes NW uses Gephi’s libraries for exporting. Furthermore, x and y will be added even if they didn’t
exist in the model. Again, this is because NW uses Gephi’s libraries which assume that nodes have positions
stored in x and y. If you wish to export to Gephi specifically, we recommend creatingx and y turtles variables and
setting them to xcor and ycor before export.
Color will be exported in a standard RGB format. This should hopefully increase compatibility with other programs.
Turtle and link variables that contain values of different types will be stored as strings. Unfortunately, most network
formats require that node and attributes have a single type.
Many programs use label to store the id of nodes. Thus, if you’re having trouble importing data exported from
NetLogo into another program, you might try setting turtles’ labels to their who number.
Multigraphs are not supported. Thus, two turtles can share at most one link.nw:save-graphml does support
multigraphs, so use that if turtles can have more than one type of link connecting them.
x

determines the file-type of the given file based on the extension and calls the correspondingsave-* primitive
on it. Note that GraphML must be exported with nw:save-graphml.
nw:save

NetLogo Palette Extension
Using the Palette Extension
The NetLogo palette extension allows to map values to colors. The colors go beyond NetLogo colors, including
ColorBrewer color schemes or arbitrary RGB colors. Additionally, it provides a primitive to map to color gradients and a
primitive to launch a ColorBrewer dialog for easy scheme selection.

Getting Started
To get started with palettes add to the top of your Code tab:
extensions [palette]

you can then call any of the primitives by adding palette: before the primitive:
palette:scale-gradient
palette:scale-scheme
palette:scheme-color
palette:scheme-dialog

The palette extension primitives return a list containing RGB colors [[r g b][r g b]...[r g b]] , except for
palette:scheme-dialog which opens a dialog.

What colors should I use ?
ColorBrewer has many colors where to start. ColorBrewer has three schemes Sequential, Divergent and Qualitative. The
use of ColorBrewer for maps is discussed at length in this paper (Harrower, Brewer 2003). Choosing the right colors is a
design problem, thus, there are many acceptable solution. However, these guidelines might be useful for choosing colors
in Agent Based Models:
Sequential colors are best for continuous natural phenomena models such as as heat diffusion in physics or fire in
earth sciences.
Divergent colors are useful for highlighting a middle value in a model. It can be also applied to the heat diffusion model
if the goal is to highlight the middle temperature.
Qualitative colors are best for choosing colors in models where color denotes category and not value.
For agents that cover large areas avoid strong colors and try to use pastel colors. However, for a low number of small
isolated agents try to use strong colors such as such a accent.
The main goal is to avoid having a large area covered with agents with a bright color and or having small areas having
a muted pastel color.
If you are coloring both turtles and patches, make sure they have different ranges of hue, saturation and value. E.g.
Use different hues of pastel for patches and accent for turtles

Should I use a continuous color gradient or just a discrete color set ?
The answer depends on the task that your will be asking from your user.
For example, gradients are more aesthetic thus are more memorable than discrete colors. Consequently, a gradient can
be a better choice for presentations where the main goal of the image is to be attractive and memorable. However,
binning values in a discrete set of colors simplifies tasks such as estimation and counting by removing unnecessary
detail to display the big picture. Thus, discrete colors can be a better choice for a paper where the user will have the time
and interest to study the visualization.
In order to see the difference you can turn on and off the gradient in the Heat Diffusion model. You can observe that
turning gradient on makes the model more aesthetic, but it becomes harder to estimate the value of a patch at a given
position.

Example Models
There is an example of using the palette primitives in the Code Examples section of the models library:
Palette Example
And one Sample Model that uses the extension:
Heat Diffusion - Alternative Gradient

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