数据与计算发展前沿 ›› 2021, Vol. 3 ›› Issue (4): 44-53.doi: 10.11871/jfdc.issn.2096-742X.2021.04.004

• 可视化与可视分析专题 • 上一篇    下一篇

基于矢量完全信息熵的流线并行分布方法

申丽铭1(),郭雨蒙2(),王文珂1,*()   

  1. 1.国防科技大学,气象海洋学院,湖南 长沙 410003
    2.军事科学院军队政治工作研究院,北京 100091
  • 收稿日期:2021-06-10 出版日期:2021-08-20 发布日期:2021-08-30
  • 通讯作者: 王文珂
  • 作者简介:申丽铭,国防科技大学,硕士研究生,研究方向为科学可视化与信息可视化等,已发表SCI论文2篇。
    本文中负责数据处理、模型构建、实验、论文撰写。
    SHEN Liming is a master's student of National University of Defense Technology. Her research int-erests include scientific visualization and information visuali-zation. She has published 2 academic papers.
    In this paper, she is responsible for data processing, model con-struction, experiments, and paper writing.
    E-mail: slmwow@nudt.edu.cn|郭雨蒙,现工作于军事科学院军队政治工作研究院,博士,研究方向为虚拟现实与可视化。
    本文主要承担工作为实验与协助模型构建。
    GUO Yumeng, Ph.D., currently works at the Academy of Military Political Work of the Academy of Military Sciences. His research interets include virtual reality and visualization.
    In this paper, he is responsible for conducting experiments and assisting model construction.
    E-mail: guoyumeng@nudt.edu.cn|王文珂,国防科技大学气象海洋学院可视化团队负责人,博士,副研究员,主要研究方向为科学计算可视化,主持和参与了国家重大专项、973、863、自然科学基金等多项课题,获军队科技进步二等奖1项,发表学术论文50余篇,撰写学术专著1部,授权国家发明专利5项。
    本文主要承担工作为流线分布算法研究框架设计。
    WANG Wenke, Ph.D., associate professor, is currently the Director of Visualization Teaching and Research Section of College of Meteorology and Oceanography, National University of Defense Technology. His main research interests include Scientific Computing Visualization. He has presided over and participated in a number of national major projects, including 973, 863, Natural Science Foundation and other projects. He has won Second Prize of Military Science and Technology Progress, published more than 50 academic papers, written 1 academic monograph, and granted 5 national invention patents.
    In this paper, he is responsible for the design of streamline distribution algorithm research framework.
    E-mail: wangwenke@nudt.edu.cn
  • 基金资助:
    国家自然科学基金“非结构网格线性矢量场高效拓扑可视化关键技术研究”(61972411);国家自然科学基金“高精度海洋声场模型的可扩展并行算法与千亿网格应用”(61972406)

Streamline Parallel Distribution Method Based on Vector Complete Information Entropy

SHEN Liming1(),GUO Yumeng2(),WANG Wenke1,*()   

  1. 1. College of Meteorology and Oceanography, National University of Defense Technology, Changsha, Hunan 410003, China
    2. Academy of Military Political Work, Academy of Military Sciences, Beijing 100091, China
  • Received:2021-06-10 Online:2021-08-20 Published:2021-08-30
  • Contact: WANG Wenke

摘要:

【目的】流线可视化效果依赖于流线分布方法,其对矢量场数据的理解有着重要作用。现有的流线分布方法只考虑了矢量场的方向分量,忽略了另一重要的矢量长度信息。此外,为了提高计算效率,本文提出了一种基于矢量完全信息熵的并行流线分布方法。【方法】该方法考虑了矢量方向和长度分量,分块并行计算熵场并以此指导流线的放置。在放置过程中,采用了一种改进的精简剪枝方法来提高算法的效率。【结果】本文选取了三组实验数据,产生不同数量的流线与已有方法进行对比实验。实验结果表明,该方法能够高效生成可反映矢量场方向和长度变化信息的流线。【结论】本文提出的并行流线分布方法,能够高效揭示更多的矢量场信息,且不遗漏矢量场的显著特征。

关键词: 流线可视化, 流线分布, 完全信息熵

Abstract:

[Objective] Streamline visualization depends on the streamline distribution method, which plays an important role in understanding flow field data. The existing streamline distribution methods only consider the directional component of the vector field and ignore magnitude information. In addition, considering that the flow field data are steadily on the increase, a parallel streamline distribution method based on complete vector information entropy is proposed in this paper. [Methods] The proposed method considers both direction and magnitude components of the vector and calculates the entropy field in parallel in blocks to guide the placement of streamlines. An improved pruning method is applied to improve the efficiency of the algorithm. [Results] In this paper, different numbers of streamlines are generated to conduct comparative experiments with existing methods on three flow field datasets. The experimental results show that the proposed method can generate streamlines that reflect the information of both direction and magnitude of the flow field efficiently. [Conclusions] The parallel streamline distribution method proposed in this paper can effectively reveal more flow field information without missing the significant characteristics of the flow field.

Key words: streamline visualization, streamline distribution, complete vector information entropy