Hi Frank,<br><br>Thanks for the quick response, see my comments inline below:<br><br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
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1) I would be more comfortable if you didn't need to modify the behavior<br>
of the source layers. Why not have the aggregate layer have a list of<br>
the source layers, insteading of marking source layers with the<br>
target layer that will consume them?<br>
<br></blockquote><div><br>Technically I don't see too much difference between these 2 versions. However placing the reference at the source would make it easier to<br>override the vtable of the source to delegate the control when accessing the features from the source layer. We should make sure that the feaure<br>
preprocessing will take place in the first access of WhichShapes from any of these layers. (Considering that the feature query is happening in reverse layer order as the drawing operations)<br><br> </div><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
2) Are you planning to use the functions in maptree.c as a generic quad<br>
tree or are you hoping to take advantage of .qix files for shapefile<br>
sources?<br>
<br></blockquote><div><br>I intend to use that in memory to speed up the query based on a rectangle area of interest during the clustering operation.<br> </div><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
3) Are you planning to do clustering for dissimilar features from<br>
different sources? At the core I don't understand why the clustering<br>
needs to have multiple source layers. It seems like combining<br>
features from multiple layers and clustering features should be<br>
distinct operations.<br>
<br></blockquote><div><br>Negotiating features from multiple layers is a part of the recent specification we rely on. In fact expect to create a new layer to serve the combined features with different symbology as the source features, labeled based on different (aggregate) attributes. In this regard there's no meaningful difference whether to use one layer or multiple layers as feature data sources since a new layer is required in any case. According to our specification I intend to support the point layers only. <br>
I don't really understand why combining and clustering would be different in our term.<br><br>Best regards,<br><br>Tamas<br><br><br></div></div><div style="visibility: hidden; left: -5000px; position: absolute; z-index: 9999; padding: 0px; margin-left: 0px; margin-top: 0px; overflow: hidden; word-wrap: break-word; color: black; font-size: 10px; text-align: left; line-height: 130%;" id="avg_ls_inline_popup">
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