第 35 章 Graphviz - Graph Visualization Software

简介:

目录

35.1. Installation
35.1.1. Apt-get
35.1.2. Yum
35.2. The DOT Language
35.2.1. dot
35.2.1.1. 布局
35.2.2. twopi
35.2.3. gprof
35.3. Node, Edge and Graph Attributes
35.3.1. Color Names
35.3.2. Node Shapes
35.3.3. 箭头
35.4. Example
35.4.1. E-R
35.4.2. Network
35.4.3. workflow

http://www.graphviz.org/

35.1. Installation

35.1.1. Apt-get

to see all available graphviz packages.

$ apt-cache search graphviz |grep ^g
graphviz - rich set of graph drawing tools
graphviz-dev - transitional package for graphviz-dev rename
graphviz-doc - additional documentation for graphviz

$ apt-cache search graphviz |grep Graphviz
dot2tex - Graphviz to LaTeX converter
libgraph-easy-perl - Perl module to convert or render graphs (as ASCII, HTML, SVG or via Graphviz)
python-pydot - Python interface to Graphviz's dot
python-pygraphviz - Python interface to the Graphviz graph layout and visualization package
python-yapgvb - Python bindings for Graphviz, using Boost.Python
xdot - interactive viewer for Graphviz dot files
			

$ sudo apt install graphviz
			

Test, A "Hello World" example made by giving the command:

echo "digraph G {Hello->World}" | dot -Tpng >hello.png
			

35.1.2. Yum

# yum list 'graphviz*'
# yum install graphviz
			





原文出处:Netkiller 系列 手札
本文作者:陈景峯
转载请与作者联系,同时请务必标明文章原始出处和作者信息及本声明。

目录
相关文章
|
8月前
|
算法 Linux Shell
SGAT丨Single Gene Analysis Tool
SGAT丨Single Gene Analysis Tool
|
算法 Go 索引
Data Structure_Visualization
所以代码附上GitHub:https://github.com/GreenArrow2017/DataStructure_Java/tree/master/out/production/DataStructure_Java/ApplicationOfAlgorithm 排序可视化 SelectionSort 选择排序很简单,所有的排序算法在前面的博客都有讲解: https://www.jianshu.com/p/7fbf8671c742 选择排序很简单,遍历所有元素,查看一下他们的之后最小的元素和当前元素交换即可。
1509 0
Make Helix Shape in occQt
Make Helix Shape in occQtPCurve is a powerful modeling method, to make helix shapes in occQt to help you understand pcurve better, then you can also can model some intereting shape based on pcurve.
950 0
|
安全 关系型数据库 Unix
|
Python
feature visualization from ipython notebook
Feature visualization from ipython notebook Wang Xiao   1. install anaconda2 from: https://www.
806 0