13,389 research outputs found

    A New Perspective on Clustered Planarity as a Combinatorial Embedding Problem

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    The clustered planarity problem (c-planarity) asks whether a hierarchically clustered graph admits a planar drawing such that the clusters can be nicely represented by regions. We introduce the cd-tree data structure and give a new characterization of c-planarity. It leads to efficient algorithms for c-planarity testing in the following cases. (i) Every cluster and every co-cluster (complement of a cluster) has at most two connected components. (ii) Every cluster has at most five outgoing edges. Moreover, the cd-tree reveals interesting connections between c-planarity and planarity with constraints on the order of edges around vertices. On one hand, this gives rise to a bunch of new open problems related to c-planarity, on the other hand it provides a new perspective on previous results.Comment: 17 pages, 2 figure

    Preservice teachers’ pictorial strategies for a multistep multiplicative fraction problem

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    Previous research has documented that preservice teachers (PSTs) struggle with under- standing fraction concepts and operations, and misconceptions often stem from their understanding of the referent whole. This study expands research on PSTs’ understanding of wholes by investigating pictorial strategies that 85 PSTs constructed for a multistep fraction task in a multiplicative context. The results show that many PSTs were able to construct valid pictorial strategies, and the strategies were widely diverse with respect to how they made sense of an unknown referent whole of a fraction in multiple steps, how they represented the wholes in their drawings, in which order they did multiple steps, and which type of model they used (area or set). Based on their wide range of pictorial strategies, we discuss potential benefits of PSTs’ construction of their own representations for a word problem in developing problem solving skills

    Grid Representations and the Chromatic Number

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    A grid drawing of a graph maps vertices to grid points and edges to line segments that avoid grid points representing other vertices. We show that there is a number of grid points that some line segment of an arbitrary grid drawing must intersect. This number is closely connected to the chromatic number. Second, we study how many columns we need to draw a graph in the grid, introducing some new \NP-complete problems. Finally, we show that any planar graph has a planar grid drawing where every line segment contains exactly two grid points. This result proves conjectures asked by David Flores-Pe\~naloza and Francisco Javier Zaragoza Martinez.Comment: 22 pages, 8 figure

    Edge Partitions of Optimal 22-plane and 33-plane Graphs

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    A topological graph is a graph drawn in the plane. A topological graph is kk-plane, k>0k>0, if each edge is crossed at most kk times. We study the problem of partitioning the edges of a kk-plane graph such that each partite set forms a graph with a simpler structure. While this problem has been studied for k=1k=1, we focus on optimal 22-plane and 33-plane graphs, which are 22-plane and 33-plane graphs with maximum density. We prove the following results. (i) It is not possible to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a forest, while (ii) an edge partition formed by a 11-plane graph and two plane forests always exists and can be computed in linear time. (iii) We describe efficient algorithms to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a plane graph with maximum vertex degree 1212, or with maximum vertex degree 88 if the optimal 22-plane graph is such that its crossing-free edges form a graph with no separating triangles. (iv) We exhibit an infinite family of simple optimal 22-plane graphs such that in any edge partition composed of a 11-plane graph and a plane graph, the plane graph has maximum vertex degree at least 66 and the 11-plane graph has maximum vertex degree at least 1212. (v) We show that every optimal 33-plane graph whose crossing-free edges form a biconnected graph can be decomposed, in linear time, into a 22-plane graph and two plane forests

    Partitioning Graph Drawings and Triangulated Simple Polygons into Greedily Routable Regions

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    A greedily routable region (GRR) is a closed subset of R2\mathbb R^2, in which each destination point can be reached from each starting point by choosing the direction with maximum reduction of the distance to the destination in each point of the path. Recently, Tan and Kermarrec proposed a geographic routing protocol for dense wireless sensor networks based on decomposing the network area into a small number of interior-disjoint GRRs. They showed that minimum decomposition is NP-hard for polygons with holes. We consider minimum GRR decomposition for plane straight-line drawings of graphs. Here, GRRs coincide with self-approaching drawings of trees, a drawing style which has become a popular research topic in graph drawing. We show that minimum decomposition is still NP-hard for graphs with cycles, but can be solved optimally for trees in polynomial time. Additionally, we give a 2-approximation for simple polygons, if a given triangulation has to be respected.Comment: full version of a paper appearing in ISAAC 201

    Experimental analysis of the accessibility of drawings with few segments

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    The visual complexity of a graph drawing is defined as the number of geometric objects needed to represent all its edges. In particular, one object may represent multiple edges, e.g., one needs only one line segment to draw two collinear incident edges. We study the question if drawings with few segments have a better aesthetic appeal and help the user to asses the underlying graph. We design an experiment that investigates two different graph types (trees and sparse graphs), three different layout algorithms for trees, and two different layout algorithms for sparse graphs. We asked the users to give an aesthetic ranking on the layouts and to perform a furthest-pair or shortest-path task on the drawings.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

    Relating Graph Thickness to Planar Layers and Bend Complexity

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    The thickness of a graph G=(V,E)G=(V,E) with nn vertices is the minimum number of planar subgraphs of GG whose union is GG. A polyline drawing of GG in R2\mathbb{R}^2 is a drawing Γ\Gamma of GG, where each vertex is mapped to a point and each edge is mapped to a polygonal chain. Bend and layer complexities are two important aesthetics of such a drawing. The bend complexity of Γ\Gamma is the maximum number of bends per edge in Γ\Gamma, and the layer complexity of Γ\Gamma is the minimum integer rr such that the set of polygonal chains in Γ\Gamma can be partitioned into rr disjoint sets, where each set corresponds to a planar polyline drawing. Let GG be a graph of thickness tt. By F\'{a}ry's theorem, if t=1t=1, then GG can be drawn on a single layer with bend complexity 00. A few extensions to higher thickness are known, e.g., if t=2t=2 (resp., t>2t>2), then GG can be drawn on tt layers with bend complexity 2 (resp., 3n+O(1)3n+O(1)). However, allowing a higher number of layers may reduce the bend complexity, e.g., complete graphs require Θ(n)\Theta(n) layers to be drawn using 0 bends per edge. In this paper we present an elegant extension of F\'{a}ry's theorem to draw graphs of thickness t>2t>2. We first prove that thickness-tt graphs can be drawn on tt layers with 2.25n+O(1)2.25n+O(1) bends per edge. We then develop another technique to draw thickness-tt graphs on tt layers with bend complexity, i.e., O(2t⋅n1−(1/β))O(\sqrt{2}^{t} \cdot n^{1-(1/\beta)}), where β=2⌈(t−2)/2⌉\beta = 2^{\lceil (t-2)/2 \rceil }. Previously, the bend complexity was not known to be sublinear for t>2t>2. Finally, we show that graphs with linear arboricity kk can be drawn on kk layers with bend complexity 3(k−1)n(4k−2)\frac{3(k-1)n}{(4k-2)}.Comment: A preliminary version appeared at the 43rd International Colloquium on Automata, Languages and Programming (ICALP 2016
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