20 research outputs found
Research on Visualization of Port Transportation Network based on Force Directed Model
Visualization technology has been extensive used in various fields which makes the information presented in a visual way. Visualization directly improves the cognitive efficiency of information, greatly reduces the complexity of data understanding, and breaks through the limitation of the traditional statistical analysis method. The automatic placement of nodes and edges in the network graph has been an important part of visualization research, and the automatic layout algorithm based on force directed graph is a kind of method in this kind of research. An abstract data model of the port transport network is built and the force directed model is improved and applied to port transportation network in this paper
A Parallel Solver for Graph Laplacians
Problems from graph drawing, spectral clustering, network flow and graph
partitioning can all be expressed in terms of graph Laplacian matrices. There
are a variety of practical approaches to solving these problems in serial.
However, as problem sizes increase and single core speeds stagnate, parallelism
is essential to solve such problems quickly. We present an unsmoothed
aggregation multigrid method for solving graph Laplacians in a distributed
memory setting. We introduce new parallel aggregation and low degree
elimination algorithms targeted specifically at irregular degree graphs. These
algorithms are expressed in terms of sparse matrix-vector products using
generalized sum and product operations. This formulation is amenable to linear
algebra using arbitrary distributions and allows us to operate on a 2D sparse
matrix distribution, which is necessary for parallel scalability. Our solver
outperforms the natural parallel extension of the current state of the art in
an algorithmic comparison. We demonstrate scalability to 576 processes and
graphs with up to 1.7 billion edges.Comment: PASC '18, Code: https://github.com/ligmg/ligm
A Sparse Stress Model
Force-directed layout methods constitute the most common approach to draw
general graphs. Among them, stress minimization produces layouts of
comparatively high quality but also imposes comparatively high computational
demands. We propose a speed-up method based on the aggregation of terms in the
objective function. It is akin to aggregate repulsion from far-away nodes
during spring embedding but transfers the idea from the layout space into a
preprocessing phase. An initial experimental study informs a method to select
representatives, and subsequent more extensive experiments indicate that our
method yields better approximations of minimum-stress layouts in less time than
related methods.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
New Algorithm for Drawings of 3-Planar Graphs
Graphs arise in a natural way in many applications, together with the need to be drawn. Except for very small instances, drawing a graph by hand becomes a very complex task, which must be performed by automatic tools. The field of graph drawing is concerned with finding algorithms to draw graph in an aesthetically pleasant way, based upon a certain number of aesthetic criteria that define what a good drawing, (synonyms: diagrams, pictures, layouts), of a graph should be. This problem can be found in many such as in the computer networks, data networks, class inter-relationship diagrams in object oriented databases and object oriented programs, visual programming interfaces, database design systems, software engineering…etc. Given a plane graph G, we wish to find a drawing of G in the plane such that the vertices of G are represented as grid points, and the edges are represented as straight-line segments between their endpoints without any edge-intersection. Such drawings are called planar straight-line drawings of G. An additional objective is to minimize the area of the rectangular grid in which G is drawn. In this paper we introduce a new algorithms that finds an embedding of 3-planar graph. Keywords: 3- Planar Graph; Graph Drawing; drawing on grid
Balancing between the Local and Global Structures (LGS) in Graph Embedding
We present a method for balancing between the Local and Global Structures
(LGS) in graph embedding, via a tunable parameter. Some embedding methods aim
to capture global structures, while others attempt to preserve local
neighborhoods. Few methods attempt to do both, and it is not always possible to
capture well both local and global information in two dimensions, which is
where most graph drawing live. The choice of using a local or a global
embedding for visualization depends not only on the task but also on the
structure of the underlying data, which may not be known in advance. For a
given graph, LGS aims to find a good balance between the local and global
structure to preserve. We evaluate the performance of LGS with synthetic and
real-world datasets and our results indicate that it is competitive with the
state-of-the-art methods, using established quality metrics such as stress and
neighborhood preservation. We introduce a novel quality metric, cluster
distance preservation, to assess intermediate structure capture. All
source-code, datasets, experiments and analysis are available online.Comment: Appears in the Proceedings of the 31st International Symposium on
Graph Drawing and Network Visualization (GD 2023