Extended clustering example

+ Shows the usage of custom classes for a fine grained control about + the clustering behaviour. +

+ The vectorlayer in this example contains random data with an + attribute "clazz" that can take the values 1, 2, 3 and 4. The + features with clazz = 4 are considered more important than the + others. +

+ The radiobuttons on the right of the map control the + cluster strategy to be applied to the features. +

+ No strategy + means that all features are + rendered, no clustering shall be applied +
+ Simple cluster-strategy + applies the cluster + strategy with default options to the layer. You should notice + that many of the important features with clazz = 4 are getting + lost, since clustering happens regardless of feature attributes +
+ Attributive cluster-strategy + uses a + customized cluster strategy. This strategy is configured to + cluster features of the same clazz only. You should be able to see all + red points (clazz = 4) even though the data is clustered. A + cluster now contains only features of the same clazz. +
+ Rulebased cluster-strategy + uses another + customized cluster strategy. This strategy is configured to + cluster features that follow a certain rule only. In this case only + features with a clazz different from 4 are considered as + candidates for clustering. That means that usually you have fewer + clusters on the map, yet all with clazz = 4 are easily + distinguishable +

+ Hover over the features to get a short infomation about the + feature or cluster of features. +