Computer Science ›› 2019, Vol. 46 ›› Issue (1): 107-111.doi: 10.11896/j.issn.1002-137X.2019.01.016

• CCDM2018 • Previous Articles     Next Articles

Edge Bundling Method of Spiral Graph Based on Interval Classification

ZHU Li-xia, LI Tian-rui, TENG Fei, PENG Bo   

  1. (School of Information Science and Technology,Southwest Jiaotong University,Chengdu 611756,China)
  • Received:2018-05-11 Online:2019-01-15 Published:2019-02-25

Abstract: Spiral graph is a common visualization method in visualizing time series data.It can not only simultaneous display the multiple-stages data in one plane space,but also demonstrate the data with different time length in a limited space.In order to solve the problem of visual clutter caused by the intersection of helical lines in the present spiral image visualization methods,a method of edge bundling is of great significance.First,the data points on the state circle are classified.Then the virtual bundling circles are set between the adjacent state circles,and the data points on the state ring are mapped to the corresponding virtual bundling circle by the function of edge bundling.Finally,in order to achieve the effect of curve bundling,the Bézier curve is drawn between the state circle and its corresponding virtual bundling circle,and the spiral curve is drawn between the virtual bundling circle and the virtual bundling circle.Experimental results show that the edge-bundling algorithm is effective for large-scale data visualization and can effectively alleviate the problem of visual clutter.

Key words: Edge bundling, Spiral graph, Time series, Visualization

CLC Number: 

  • TP311.11
[1]WEBER M,ALEXA M,MÜLLER W.Visualizing Time-Series on Spirals[C]//Proceedings of IEEE Symposium on Information Visualization.IEEE,2001:7-13.<br /> [2]TOMINSKI C,ABELLO J,SCHUMANN H.Axes-based visualizations with radial layouts[C]//Proceedings of ACM Sympo-sium on Applied Computing.ACM,2004:1242-1247.<br /> [3]LEI H,XIA J,GUO F,et al.Visual exploration of latent ranking evolutions in time series[J].Journal of Visualization,2016,19(4):1-13.<br /> [4]JIANG T T,XIAO W D,ZHANG C,et al.Text visualization method for time series based on Sankey diagram[J].Application Research of Computers,2016,33(9):2683-2687.(in Chinese)姜婷婷,肖卫东,张翀,等.基于桑基图的时间序列文本可视化方法[J].计算机应用研究,2016,33(9):2683-2687.<br /> [5]BOUALI F,DEVAUX S,BASTIEN,et al.Visual mining of time series using a tubular visualization[J].Visual Computer,2016,32(1):15-30.<br /> [6]YANG H H,LI T R,CHEN X D.Visualization of time series data based on spiral graph[J].Journal of Computer Applications,2017,37(9):2443-2448.(in Chinese)<br /> 杨欢欢,李天瑞,陈馨菂.基于螺旋图的时间序列数据可视化[J].计算机应用,2017,37(9):2443-2448.<br /> [7]ZHOU H,XU P,YUAN X,et al.Edge Bundling in Information Visualization[J].Tsinghua Science and Technology,2013,18(2):145-156.<br /> [8]GANSNER E,HU Y,NORTH S,et al.Multilevel agglomerative edge bundling for visualizing large graphs[C]//Proceedings of IEEE Pacific Visualization Symposium.IEEE,2011:187-194.<br /> [9]MCDONNELL K T,MUELLER K.Illustrative parallel coordinates[J].Computer Graphics Form,2008,27(3):1031-1038.<br /> [10]ZHOU H,YUAN X R,QU H M,et al.Visual clustering in parallel coordinates[J].Computer Graphics Forum,2008,27(3):1047-1054.<br /> [11]HEINRICH J,LUO Y,KIRKPATRICK A E,et al.Evaluation of a bundling technique for parallel coordinates[J].Energy Conversion & Management,2011,88(5):259-266.<br /> [12]PALMAS G,BACHYNSKYI M,OULASVIRTA A,et al.An edge-bundling layout for interactive parallel coordinates[C]//Proceedings of IEEE Pacific Visualization Symposium.IEEE,2014:57-64.<br /> [13]SPURR B D.Density estimation for statistics and data analysis[J].Journal of the Royal Statistical Society,1987,150(4):403-404.<br /> [14]QIN H X,WEI X S.A Study on Edge Bundling Technology in Parallel Coordinates[J].Journal of Computer-Aided Design & Computer Graphics,2017,29(7):1235-1244.(in Chinese)<br /> 秦红星,卫学仕.平行坐标中的边捆绑算法[J].计算机辅助设计与图形学学报,2017,29(7):1235-1244.<br /> [15]KANUNGO T,MOUNT D M,NETANYAHU N S,et al.An efficient k-means clustering algorithm:analysis and implementation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(7):881-892.<br /> [16]HOLTEN D,VAN WIJK J J.Evaluation of Cluster Identification Performance for Different PCP Variants[J].Computer Graphics Forum,2010,29(3):793-802.
[1] GAO Zhen-zhuo, WANG Zhi-hai, LIU Hai-yang. Random Shapelet Forest Algorithm Embedded with Canonical Time Series Features [J]. Computer Science, 2022, 49(7): 40-49.
[2] YANG Xiao, WANG Xiang-kun, HU Hao, ZHU Min. Survey on Visualization Technology for Equipment Condition Monitoring [J]. Computer Science, 2022, 49(7): 89-99.
[3] CHEN Hui-pin, WANG Kun, YANG Heng, ZHENG Zhi-jie. Visual Analysis of Multiple Probability Features of Bluetongue Virus Genome Sequence [J]. Computer Science, 2022, 49(6A): 27-31.
[4] LIU Bao-bao, YANG Jing-jing, TAO Lu, WANG He-ying. Study on Prediction of Educational Statistical Data Based on DE-LSTM Model [J]. Computer Science, 2022, 49(6A): 261-266.
[5] CAI Xin-yu, FENG Xiang, YU Hui-qun. Adaptive Weight Based Broad Learning Algorithm for Cascaded Enhanced Nodes [J]. Computer Science, 2022, 49(6): 134-141.
[6] ZHU Min, LIANG Zhao-hui, YAO Lin, WANG Xiang-kun, CAO Meng-qi. Survey of Visualization Methods on Academic Citation Information [J]. Computer Science, 2022, 49(4): 88-99.
[7] SHEN Shao-peng, MA Hong-jiang, ZHANG Zhi-heng, ZHOU Xiang-bing, ZHU Chun-man, WEN Zuo-cheng. Three-way Drift Detection for State Transition Pattern on Multivariate Time Series [J]. Computer Science, 2022, 49(4): 144-151.
[8] GAO Yan-lu, XU Yuan, ZHU Qun-xiong. Predicting Electric Energy Consumption Using Sandwich Structure of Attention in Double -LSTM [J]. Computer Science, 2022, 49(3): 269-275.
[9] LI Jia-zhen, JI Qing-ge, ZHU Yong-lin. Ray Tracing Checkerboard Rendering in Molecular Visualization [J]. Computer Science, 2022, 49(2): 134-141.
[10] LI Jia-zhen, JI Qing-ge. Dynamic Low-sampling Ambient Occlusion Real-time Ray Tracing for Molecular Rendering [J]. Computer Science, 2022, 49(1): 175-180.
[11] LUO Jing-jing, TANG Wei-zhen, DING Ji-ting. Research of ATC Simulator Training Values Independence Based on Pearson Correlation Coefficient and Study of Data Visualization Based on Factor Analysis [J]. Computer Science, 2021, 48(6A): 623-628.
[12] HUANG Ming, SUN Lin-fu, REN Chun-hua , WU Qi-shi. Improved KNN Time Series Analysis Method [J]. Computer Science, 2021, 48(6): 71-78.
[13] ZHANG Zheng-wan, WU Di, ZHANG Chun-jiong. Study of Cellular Traffic Prediction Based on Multi-channel Sparse LSTM [J]. Computer Science, 2021, 48(6): 296-300.
[14] SU Qing, LI Zhi-zhou, LIU Tian-tian, WU Wei-min, HUANG Jian-feng, LI Xiao-mei. Tree Structure Evaluation Visualization Model for Program Debugging [J]. Computer Science, 2021, 48(5): 68-74.
[15] E Hai-hong, ZHANG Tian-yu, SONG Mei-na. Web-based Data Visualization Chart Rendering Optimization Method [J]. Computer Science, 2021, 48(3): 119-123.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!