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1. #NETLOGO FOREACH INSTALL#
2. #NETLOGO FOREACH MANUAL#
3. #NETLOGO FOREACH PATCH#
4. #NETLOGO FOREACH FULL#
5. #NETLOGO FOREACH CODE#

#NETLOGO FOREACH MANUAL#

Variant 1 (requires NetLogo 6.1.0 or higher): Manual Installation via NetLogo Extension Manager For more details about the installation via Extension Manager, see Variant 1. You can manage the installed extension in the Extension Manager.

#NETLOGO FOREACH CODE#

NetLogo will then prompt you to confirm the installation of the extension and you can immediately use the clustering features in your code (Note: Sometimes a restart of NetLogo seems necessary to activate newly installed extensions). To trigger the installation, simply add extensions at the top of your model code and click on the Check button in the editor (or switch tabs). Variant 0 (requires NetLogo 6.1.0 or higher): Auto-Installation Alternatively, for all supported versions of NetLogo you can build the extension from source (Variant 3). For older versions of NetLogo (i.e., 6.0 or lower) you can download the corresponding jar files directly (Variant 2).

#NETLOGO FOREACH INSTALL#

Alternatively, you can install the extension using the Extension Manager provided from NetLogo 6.1 onwards (see Variant 1). Since NetLogo 6.1 the preferred deployment variant is the use of the auto-installation feature (see Variant 0). There are various deployment approaches available, ranging from simple auto-installation to building the extension from source. (Note: the NetLogo 5 demo model does not include an example for clustering patches in addition to agents this feature is only available for NetLogo 6 onwards.)įor NetLogo 6 (and higher), use demo/ogo.Ĭlustering agents by location using any of the demo models should produce the following output (in this example the cluster centroid is shown as a coloured patch).įor a screenshot of the entire demo GUI including control elements and further cluster-related information have a look here. Demoįor more comprehensive examples for the feature set, try out the demo that corresponds to your NetLogo version.įor NetLogo 5, use demo/ogo. The clusters can then be used as shown in the section Clustering individuals by variable. Let clusters dbscan:cluster-by-location agents 3 3 Cluster agents by location, with at least 3 members to constitute a cluster, and a maximum distance of 3 The reporter returns a nested list of clustered patches. minimum-members: a minimum number of patches to constitute a cluster, and.

#NETLOGO FOREACH PATCH#

Syntax: cluster-by-variable patches-to-be-clustered cluster-variable minimum-members maximum-distanceĬlusters a given set of patches patches-to-be-clustered by patch variable cluster-variable, along with two hyperparameters required for the operation of DBSCAN:

Just to clarify, you can still install the latest version of the extension in NetLogo 5, but you won't be able to cluster patches. However, this feature is only supported for NetLogo 6 or higher. Since version 0.3, this extension also supports the clustering of patches by variable. Output-print (word "Cluster " ctr ": " aset) Set label (word "ID: " who ", Cluster: " ctr ", Wealth: " wealth) ] (foreach clusters (n-of (length clusters) base-colors) The reporter returns a nested list of clustered agents.

#NETLOGO FOREACH FULL#

The feature set of the extension varies depending on the NetLogo version, with full feature support from NetLogo 6 onwards (see details below).Īuthor: Christopher Frantz (cf at christopherfrantz dot org) Usage This extension supports all versions of NetLogo from 5 onwards, including the latest version 6.2.

The main advantage over supervised algorithms such as K-Means is that it is not necessary to specify the number of resulting clusters in advance. The extension allows you to perform unsupervised density-based clustering of turtles/agents and patches based on specified variables or by proximity. NetLogo extension for DBSCAN clustering algorithm