graph-visualization

问题 I've been looking around for solutions to my question, but nothing does exactly what I want. What I want to do is save a whole JUNG graph (with custom vertex and edge rendering) to an image (PNG or JPEG). When I save the VisualizationViewer to a BufferedImage, it only takes the visible part. I want to save the whole graph, so that's not an option. Does anyone have an idea on how to render my whole graph to an image? Thanks in advance! 回答1: I finally found the solution to my problem, using a

问题 I want to draw a decision tree chart using graphviz. The graph I want to draw looks like this: I am using the following dot language: graph a { A [shape=box; label="A"] B [shape=box; label="B"] al [shape=none; label="0"] bl [shape=none; label="1"] br [shape=none; label="0"] A -- al [label="0"]; A -- B [label="1"]; B -- bl [label="0"]; B -- br [label="1"]; } However my resulting graph looks like this: How can I force the left to right order of the nodes generated by graphviz? Furthermore, as

问题 I need to draw large dataset on image, I used graphvis command lines with all available tools (dot, neato, twopi .. etc) but the result is not readable and contains overlapping. What I need is display the nodes with labels on the edges, with minimum overlapping so the graph can be readable and also printed on A4 or A3 paper. I used the options overlap=false, splines=true in neato and same overlapping result. Here is the dataset: graph { graph [ bgcolor=ivory2, overlap=false, splines=true,

问题 I'm using VivaGraphJS to create my graph which is dynamic and keeps on updating as he data comes in. The problem is that VivaGraph doesn't have the circular layout by default which I need. I came across the circular layout in cytoscape.js which I'd like to port to VivaGraph. I'm not able to completely understand what changes to make so as to have a port to VivaGraph. It'll be really appreciated if you could help me and guide me through it. Thanks :) Also, here's an algorithm that I need since

问题 I've been able to build a Force Directed Graph using a Force Layout. Most features work great but the one big issue I'm having is that, on starting the layout, it bounces all over the page (in and out of the canvas boundary) before settling to its location on the canvas. I've tried using alpha to control it but it doesn't seem to work: // Create a force layout and bind Nodes and Links var force = d3.layout.force() .charge(-1000) .nodes(nodeSet) .links(linkSet) .size([width/8, height/10])

问题 Can you help me visualise an undirected graph? I have about 500 strings that look like this: ;javascript;java;tapestry;d;design;jquery;css;html;com;air;testing;events;crm;soa;documentation;.a;email;iso;dynamic;mobile;this;project;resolution;s;automation;web;like;e-commerce;profile;commerce;out;jobs;inventory;operators;environment;system;include;integration;relationship;field;implementation;key;.profile;planning;knockout.js;sun;packaging;collaboration;report;public;virtual;communication;send

问题 I tried searching over the internet but could not find the right tool for the purpose,so if anyone could provide me a link to the tool which could parse and display a graph for RDF and OWL ontologies 回答1: SemWebGraphicalNotation — W3C-maintained list of graphical notations and software applications (outdated); RDF Visualization at Ontotext Research Space; VOWL: Visual Notation for OWL Ontologies — almost standard graphical notation for OWL visualization, the page contains links to

问题 Expanding on a prior question: Changing colors for decision tree plot created using export graphviz How would I color the nodes of the tree bases on the dominant class (species of iris), instead of a binary distinction? This should require a combination of the iris.target_names, the string describing the class, and iris.target, the class. import pydotplus from sklearn.datasets import load_iris from sklearn import tree import collections clf = tree.DecisionTreeClassifier(random_state=42) iris

问题 Trying to find communities in tweet data. The cosine similarity between different words forms the adjacency matrix. Then, I created graph out of that adjacency matrix. Visualization of the graph is the task here: # Document Term Matrix dtm = DocumentTermMatrix(tweets) ### adjust threshold here dtms = removeSparseTerms(dtm, 0.998) dim(dtms) # cosine similarity matrix t = as.matrix(dtms) # comparing two word feature vectors #cosine(t[,"yesterday"], t[,"yet"]) numWords = dim(t)[2] # cosine

问题 I have a .csv file with only two columns in it, date and time: 04-02-15,11:15 04-03-15,09:35 04-04-15,09:10 04-05-15,18:05 04-06-15,10:30 04-07-15,09:20 I need this data to be plotted (preferably in an area graph, haven't gotten that far yet) using matplotlib. I need the y-axis to be time, and the x-axis to be date. I'm having trouble wrapping my head around some of the usage for time/date, and was hoping someone could take a look at my code and offer some guidance: import numpy as np from