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_id	ecaade2016_119
id	ecaade2016_119
authors	Koenig, Reinhard and Varoudis, Tasos
year	2016
title	Spatial Optimisations - Merging depthmapX, spatial graph networks and evolutionary design in Grasshopper
doi	https://doi.org/10.52842/conf.ecaade.2016.2.249
source	Herneoja, Aulikki; Toni Österlund and Piia Markkanen (eds.), Complexity & Simplicity - Proceedings of the 34th eCAADe Conference - Volume 2, University of Oulu, Oulu, Finland, 22-26 August 2016, pp. 249-254
summary	In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (Varoudis, 2016) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper.
wos	WOS:000402064400024
keywords	Space Syntax; Evolutionary Algorithm; Grasshopper; Python; DepthmapX; Optimization
series	eCAADe
email
last changed	2022/06/07 07:51

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