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Basic

Clustering


Display

Filter


Manipulation

Spectral


Tools

SpiderWeb

ADDON. Version 4.2. Released on 2015-Jul-20. Provides 31 components. Created by Richard Schaffranek. Features 0 video tutorials.

SpiderWeb provides functionality for preforming calculations on graphs. The library is created with a special focuse on the integration of graphs and graph related theroies (e.g. SpaceSyntax) in parametric design envoirnments.

Basic

	Data Tree To Graph (DTG) parse a DataTree
	Dual Graph (dualG) Dual Graph
	graph From Cells (gFC) Create a Graph From a Set of Ajoining Cells
	graph From Lines (gFL) create a graph from a set of connected lines
	graph From Mesh (gFM) Create a directed Graph From a Mesh
	graph From Points (gFP) Create a Graph From a Set of Points and a Connection Distance
	graph Matrix (gM) Creates a graphMatrix from a graph
	Graph To Data Tree (GDT) convert a Graph to a DataTree
	visual Graph Grid (vGG) Create a visualGraphGrid from obstacles and a boundary area

Tools

	Eulerian Path (EulerianPath) Checks if the Given Graph Has an Eulerian Path and Eeturns All Possible Starting Points
	Breadth-first Search (BFS) Breadth-first Search
	Min ST (MinST) Mininmal Spanning Tree
	Shortest Path Between Points (SPBP) Callculates the shortest path between points
	randomized Sequential Graph Coloring (rndSGC) Randomized Sequential Graph Coloring
	recursive Shadow Casting (RSC) preformes recursive shadow casting on a visualGraph
	Single Source Shortest Path (SSSP) Solves the Single Source Shortest Path Problem

Display

	Display Graph (DG) Display Graph
	Display graph Edge (DE) Display graphEdge
	Display graph Vertex (DV) Display graphVertex
	Display visual Graph (dVG) Display visualGraph
	Graph Style (gS) Greate New Style for Displaying a Graph

Manipulation

	find Edges (fE) get the index of a graphEdge within a Graph
	manipulate Edges (mE) Merge, Delete, Insert Edges
	manipulate Vertices (mV) Merge, Delete Insert Vertices
	Split (S) Split a graph at a given Distance

Clustering

	agglomerative Clustering (aC) Preforms a bottom up distance clustering.
	distance Clustering (dC) Preforms a top down distance clustering.

Spectral

	Eigensystem (ESYS) Computes the Eigensystem of graphMatrix
	Spectral Matching (SM) computes n-dimensional vectors for spectralGraphMatching

Filter

	Image-Graph Filter (IGF) Iamge based Filters on Graphs
	Points of Interest (POI) Points of Interest