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. -