SearcharxivSearch

arXiv subjects

Marcel Radermacher

Publications and source records attributed to Marcel Radermacher.

7 recordsLinked to original sources

Towards a characterization of stretchable aligned graphs

We consider the problem of stretching pseudolines in a planar straight-line drawing to straight lines while preserving the straightness and the combinatorial embedding of the drawing. We answer open questions by Mchedlidze et al. by showing that not all instances with two pseudolines are stretchable. On the positive side, for $k\geq 2$ pseudolines intersecting in a single point, we prove that in case that some edge-pseudoline intersection-patterns are forbidden, all instances are stretchable. For intersection-free pseudoline arrangements we show that every aligned graph has an aligned drawing. This considerably reduces the gap between stretchable and non-stretchable instances.

cs.CG

Geometric Crossing-Minimization -- A Scalable Randomized Approach

We consider the minimization of edge-crossings in geometric drawings of graphs $G=(V, E)$, i.e., in drawings where each edge is depicted as a line segment. The respective decision problem is NP-hard [Bienstock, '91]. In contrast to theory and the topological setting, the geometric setting did not receive a lot of attention in practice. Prior work [Radermacher et al., ALENEX'18] is limited to the crossing-minimization in geometric graphs with less than $200$ edges. The described heuristics base on the primitive operation of moving a single vertex $v$ to its crossing-minimal position, i.e., the position in $\mathbb{R}^2$ that minimizes the number of crossings on edges incident to $v$. In this paper, we introduce a technique to speed-up the computation by a factor of $20$. This is necessary but not sufficient to cope with graphs with a few thousand edges. In order to handle larger graphs, we drop the condition that each vertex $v$ has to be moved to its crossing-minimal position and compute a position that is only optimal with respect to a small random subset of the edges. In our theoretical contribution, we consider drawings that contain for each edge $uv \in E$ and each position $p \in \mathbb{R}^2$ for $v$ $o(|E|)$ crossings. In this case, we prove that with a random subset of the edges of size $Θ(k \log k)$ the co-crossing number of a degree-$k$ vertex $v$, i.e., the number of edge pairs $uv \in E, e \in E$ that do not cross, can be approximated by an arbitrary but fixed factor $δ$ with high probability. In our experimental evaluation, we show that the randomized approach reduces the number of crossings in graphs with up to $13\,000$ edges considerably. The evaluation suggests that depending on the degree-distribution different strategies result in the fewest number of crossings.

cs.CG

Drawing Clustered Graphs on Disk Arrangements

Let $G=(V, E)$ be a planar graph and let $\mathcal{C}$ be a partition of $V$. We refer to the graphs induced by the vertex sets in $\mathcal{C}$ as Clusters. Let $D_{\mathcal C}$ be an arrangement of disks with a bijection between the disks and the clusters. Akitaya et al. give an algorithm to test whether $(G, \mathcal{C})$ can be embedded onto $D_{\mathcal C}$ with the additional constraint that edges are routed through a set of pipes between the disks. Based on such an embedding, we prove that every clustered graph and every disk arrangement without pipe-disk intersections has a planar straight-line drawing where every vertex is embedded in the disk corresponding to its cluster. This result can be seen as an extension of the result by Alam et al. who solely consider biconnected clusters. Moreover, we prove that it is NP-hard to decide whether a clustered graph has such a straight-line drawing, if we permit pipe-disk intersections.

cs.CG

Multilevel Planarity

In this paper, we introduce and study the multilevel-planarity testing problem, which is a generalization of upward planarity and level planarity. Let $G = (V, E)$ be a directed graph and let $\ell: V \to \mathcal P(\mathbb Z)$ be a function that assigns a finite set of integers to each vertex. A multilevel-planar drawing of $G$ is a planar drawing of $G$ such that the $y$-coordinate of each vertex $v \in V$ is $y(v) \in \ell(v)$, and each edge is drawn as a strictly $y$-monotone curve. We present linear-time algorithms for testing multilevel planarity of embedded graphs with a single source and of oriented cycles. Complementing these algorithmic results, we show that multilevel-planarity testing is NP-complete even in very restricted cases.

cs.DS

Aligned Drawings of Planar Graphs

Let $G$ be a graph that is topologically embedded in the plane and let $\mathcal{A}$ be an arrangement of pseudolines intersecting the drawing of $G$. An aligned drawing of $G$ and $\mathcal{A}$ is a planar polyline drawing $Γ$ of $G$ with an arrangement $A$ of lines so that $Γ$ and $A$ are homeomorphic to $G$ and $\mathcal{A}$. We show that if $\mathcal{A}$ is stretchable and every edge $e$ either entirely lies on a pseudoline or it has at most one intersection with $\mathcal{A}$, then $G$ and $\mathcal{A}$ have a straight-line aligned drawing. In order to prove this result, we strengthen a result of Da Lozzo et al., and prove that a planar graph $G$ and a single pseudoline $\mathcal{L}$ have an aligned drawing with a prescribed convex drawing of the outer face. We also study the less restrictive version of the alignment problem with respect to one line, where only a set of vertices is given and we need to determine whether they can be collinear. We show that the problem is NP-complete but fixed-parameter tractable.

cs.DS

A Greedy Heuristic for Crossing-Angle Maximization

The crossing angle of a straight-line drawing $Γ$ of a graph $G=(V, E)$ is the smallest angle between two crossing edges in $Γ$. Deciding whether a graph $G$ has a straight-line drawing with a crossing angle of $90^\circ$ is $\mathcal NP$-hard. We propose a simple heuristic to compute a drawing with a large crossing angle. The heuristic greedily selects the best position for a single vertex in a random set of points. The algorithm is accompanied by a speed-up technique to compute the crossing angle of a straight-line drawing. We show the effectiveness of the heuristic in an extensive empirical evaluation. Our heuristic was clearly the winning algorithm (CoffeeVM) in the Graph Drawing Challenge 2017.

cs.CG

Inserting an Edge into a Geometric Embedding

The algorithm of Gutwenger et al. to insert an edge $e$ in linear time into a planar graph $G$ with a minimal number of crossings on $e$, is a helpful tool for designing heuristics that minimize edge crossings in drawings of general graphs. Unfortunately, some graphs do not have a geometric embedding $Γ$ such that $Γ+e$ has the same number of crossings as the embedding $G+e$. This motivates the study of the computational complexity of the following problem: Given a combinatorially embedded graph $G$, compute a geometric embedding $Γ$ that has the same combinatorial embedding as $G$ and that minimizes the crossings of $Γ+e$. We give polynomial-time algorithms for special cases and prove that the general problem is fixed-parameter tractable in the number of crossings. Moreover, we show how to approximate the number of crossings by a factor $(Δ-2)$, where $Δ$ is the maximum vertex degree of $G$.

cs.DS