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Tasks
- Perform a clustering using the following workflow: https://github.com/SiLeBAT/BfROpenLab…
- Cluster all French primary producers based on their city.
- That means all stations from the same city should be put into one meta-station.
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- A window showing the delivery network opens.
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- Right click in the graph to open the context menu and select Set Selected Stations.
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- You should see this dialog now.
- Press the button in the red circle to change the Property value.
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- Now select “FR” as Value, since we want to cluster stations in France.
- Afterwards press Add to add another condition.
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- For the new condition select “type of business” as Property and “Primary Producer” as Value, since we want to cluster primary producers only.
- Now press OK.
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- All French primary producers are selected now, which is indicated by the blue color.
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- Right click in the graph to open the context menu and select Collapse by Property to cluster the selected stations.
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- Select Yes to only cluster selected stations.
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- We want to cluster on city level. That means all stations from the same city will be merged.
- Select City and press OK.
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- Just press OK, since we do not want to exclude any cities.
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- All French primary producers have been clustered to cities.
- Each selected station (blue circle) is a French city.
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- Select “Picking” as Editing Mode and click in the graph to deselect all stations.
- You can now see, that one of the stations is yellow. That means, that this station (French city) is connected to all outbreak spots (red circles).
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- Since the graph looks confusing now, we should reapply the layout algorithm.
- Right click in the graph and select Apply Layout > Fruchterman-Reingold in the context menu.
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- The stations should be arranged in better way now.
- The layout algorithm is not deterministic, therefore your result will look different from the screenshot.
- To see which city is connected to all outbreak spots double click on the yellow circle.
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- As you can see in the dialog the city is “Perpignan”.
- Press Switch to GIS to see the city and its relations on a map.
