Posts Tagged ‘tutorial


Have a merry x-mas… compiz style

One of the cooler, lesser-known plugins for Compiz, xglsnow, was sadly left in the dust with the inclusion of Compiz Fusion into Ubuntu 7.10. That doesn’t mean, however, you can’t still get it working in time for the holiday season! Check out the video below to see the plugin in action.

Here is a screenshot of what it looks like on my machine:

screenshot of xglsnow running on my desktop

Note: This tutorial assumes that you have Compiz or Compiz fusion setup already. If you don’t, however, try searching the forums– there is a huge number of guides floating around on getting Compiz running for different graphics cards.

Ready? Here goes…

I. Installing xglsnow

First, you need to install the necessary packages to build the plugin. Open up a console (alt+F2 -> “gnome-terminal”),
and type:

sudo apt-get install compiz-bcop compiz-dev build-essential libxcomposite-dev libpng12-dev libsm-dev libxrandr-dev libxdamage-dev libxinerama-dev libstartup-notification0-dev libgconf2-dev librsvg2-dev libdbus-1-dev libdbus-glib-1-dev libgnome-desktop-dev x11proto-scrnsaver-dev libxss-dev libxslt1-dev libtool

Create a directory in your home folder to install the plugin to:

mkdir -p ~/compiz/

Download xglsnow and extract it to the directory you just created:

Finally, navigate to the directory, compile and install:

cd ~/compiz/snow

make install

Now you just need to install some textures, configure xgl, and you’re done! :)

*The above steps are based off a tutorial by Scott at the Compiz Fusion forums. Thanks!

II. Adding textures

The above tarball doesn’t include any snow textures, so by default all you would see are some floating white blocks… not very pretty… The package from the xglsnow homepage, however, includes a texture which looks pretty nice. To set it up, go to the xglsnow project homepage and download xglsnow-0.2.0.tar.gz. Extract the files, and copy the file “snowflake2.png” to any location you would like, e.g. ~/.compiz/images or /usr/share/images:

tar -xf xglsnow-0.2.0.tar.gz

cd xglsnow-0.2.0/

mkdir ~/.compiz/images

mv snowflake2.png ~/.compiz/images

If you haven’t already, restart Compiz to load the new plugin (alt+F2 -> “compiz –replace”) and run the Compiz settings manager: alt+F2 -> “ccsm”. Find the “Snow” plugin and check the box to the left of it to enable it.

Compiz settings manager

Now click on the plugin’s name to modify its settings. Next go to “Textures” -> “add” -> “browse” (click the folder icon). Navigate to the location where you saved the texture from above and hit “okay.”

Compiz settings manager (snow configuration)

All done!

Press “Super + F3″ to start xgl snow. If you don’t see anything, check to make sure the the PNG plugin for compiz is enabled, and that the hotkey for xglsnow is in fact “super + F3.”

If you want to install some different snow textures, try the Snowflakes pack on Gnome-look.

III. Wallpapers

Finally, if you want to find some wintry wallpapers to go along with your new snow-covered desktop, take a look at Blue Christmas
from digital blasphemy (that is the one in the screenshot above). Gnome-art has a nice picture of a winter landscape in Alsace, France You can also find some winter wallpapers at Gnome-look and Kde-look.
Try searching for “winter” or “snow.”

That’s all!

Feel free to write any suggestions, or a link to a screenshot of your own holiday desktop :)


Intro Data Mining Webinar (December 13, 2007)

Salford Systems is hosting a free Introductory Data Mining Webinar on December 13, from 10-11am EST.

From the description of the seminar:

This one-hour webinar is a perfect place to start if you are new to data mining and have little-to-no background in statistics or machine learning.

In one hour, we will discuss:

**Data basics: what kind of data is required for data mining and predictive analytics; in what format must the data be; what steps are necessary to prepare data appropriately.

**What kinds of questions can we answer with data mining?

**How data mining models work: the inputs, the outputs, and the nature of the predictive mechanism.

**Evaluation criteria: how predictive models can be assessed and their value measured.

**Specific background knowledge to prepare you to begin a data mining project.

Data mining and the related field of machine learning deal with finding patterns in large sets of data. This is very useful for trying to understand and model complex natural phenomena, and bioinformaticians have not been shy to take advantage of these methods. Just look at any recent issue of BMC Bioinformatics or PLoS Computational Biology and you will see a number of articles involving SVMs, Neural Networks, and Bayesian networks.

This webinar is geared towards people with little or no understanding of data mining, so it should be a good introduction if you haven’t learned about machine learning or data mining. If you are interested in learning more, there are some good tutorials online at here, and here. and Peteris’s blog include a number of video lectures on the machine learning.

To sign up, go to the event description and click “enroll.”


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