Guided Tour of MPCluster: Adjusting the Display Settings
In most of these examples, MPCluster has been set to draw each cluster using a boundary outline and a central pushpin. The visual appearance of these clusters can be easily changed.
Controlling the boundary shape and central pin
The Display Options box in the upper right of the main MPCluster panel is used to control how MPCluster draws the clusters. Use the two check boxes to control whether MPCluster will mark each cluster's central location with a pushpin; and/or draw a boundary outline around the cluster. The central location is defined as the average (mean) location of all the cluster's component pushpins. The boundary is drawn as a convex hull around these component pushpins - the outer pushpins will form vertices of the boundary shape.
The boundary shape's color and outline thickness can be set by pressing the Boundary Shapes button.
Pressing the Boundary Shapes button will display the Boundary Shape Colors dialog box, illustrated on the right.
The Line Thickness option at the top is used to set the outline thickness for the boundary shapes.
MPCluster can draw outline shapes using either the current MapPoint shape settings, or using a specific set of colors defined in this dialog box. Use the radio buttons if you wish to override the default MapPoint colors with the colors on this dialog box.
The colors can be set for both the fill and the outline. One but not both of these can be set to be transparent (ie. no color). Typically the outline is set to an opaque color (red in this example) and the fill is set to transparent. This allows the component clusters to be visible. A color fill will often hide the component pushpins.
Here is an example using the above display settings. For maximum flexibility, MPCluster does not explicitly set the pushpin image used for the pushpin set it creates to store the central pushpins. This is easily changed by the user to one of the pushpins defined in the current instance of MapPoint. Here it has been changed to a green circle for clarity.
Next, we look at the MPCluster's Excel output.