Background
This control is inspired by the free web-based word cloud generator called Wordle. In fact, the control is a screw-out product of my project at http://sourcecodecloud.codeplex.com.
I really loved the visualizations produced by Wordle, but my goal was to write a non web based local solution to process large amounts of sensible data. There were a number of components I found on the web, but most of them had either very pure performance when processing text and the visualization or the layout was not what I expected.
Architecture and usage
There are four phases when visualizing the word cloud:
Processing data like text, HTML, or source code, and extracting the relevant words while ignoring others. As an example, I have implemented three of them. TextExtractor extracts all words from some text string ignoring spaces and all non-letter characters. FileExtractor is able to process large text files line by line. Another one UriExtractor fetches a URL content and tries to clean away HTML tags and JavaScript (to be honest, I just implemented it as a showcase and its filtering capabilities are very pure).
To tap your own data source, just implement the IEnumerable<string> interface or derive from BaseExtractor.
Counting words and ignoring ones from blacklist.
The result is an enumeration with pairs of terms (words) and integers representing the number of occurrences of this word in a text. In the first implementation, I was using KeyValuePair<string, int> to represent them. In this version, I switched to the IWord interface.
public interface IWord : IComparable<IWord>
{
string Text { get; }
int Occurrences { get; }
string GetCaption();
}
I have also moved to LINQ and gave up my own classes for word counting, grouping, and sorting. I loved them very much, but using LINQ increased readability, reduced complexity, and shortened code. All these at the price of an ignorable insignificant performance drawback was really a good deal.
IBlacklist blacklist = new CommonWords();
IProgressIndicator progress = new ProgressBarWrapper(progressBar);
IEnumerable<string> terms = new StringExtractor(textBox.Text, progress);
cloudControl.WeightedWords =
terms
.Filter(blacklist)
.CountOccurences()
.SortByOccurences();
Layout – I use a QuadTree data structure to create a non overlapping map of words on controls graphics. The same data structure is also used to query control which words are under a certain rectangular area or point. This query is used to redraw only a particular area when needed or perform some action when a control is clicked. Thereby it is very useful to know which word was clicked to perform a word related action, let’s say show statistics or navigate to some URL.
private void cloudControl_Click(object sender, EventArgs e)
{
LayoutItem itemUderMouse;
Point mousePositionRelativeToControl =
cloudControl.PointToClient(new Point(MousePosition.X, MousePosition.Y));
if (!cloudControl.TryGetItemAtLocation(
mousePositionRelativeToControl, out itemUderMouse))
{
return;
}
MessageBox.Show(itemUderMouse.Word);
}
Configuring the Word Cloud Control
There are several things you may vary on this control:
You can change the font type and size.
cloudControl.MinFontSize = 6;
cloudControl.MaxFontSize = 60;
cloudControl.Font = new Font(new FontFamily("Verdana"), 8, FontStyle.Regular);
Use different colours:
cloudControl.Palette = new Brush[] {Brushes.DarkRed, Brushes.Red, Brushes.LightPink};
Use a different layout. Currently, there are two layouts implemented. You can implement your own by deriving from BaseLayout or just by implementing the ILayout interface on your own.
cloudControl.LayoutType = LayoutType.Typewriter;
The logic of lay out and drawing graphics is strictly separated by the IGraphicEngine interface. So I think it would not be a big deal to port it to WPF or Silverlight in the future.
For experts
By digging in the code, you will discover the following extra features:
- Creating your own blacklist -
IBlacklist interface or the CommonBlacklist base class. - Loading blacklist from file -
CommonBlacklist.CreateFromFile(...) method. - Grouping words having common stem like - departed, depart, departing.
- You are even able to see statistics on it.
Credits
