Frequently Asked Questions¶
Where does the name “Chaco” come from?¶
It is named after Chaco Canyon, which had astronomical markings that served as an observatory for Native Americans. The original version of Chaco was built as part of a project for the Space Telescope Science Institute. This is also the origin of the name “Kiva” for our vector graphics layer that Chaco uses for rendering.
What are the pros and cons of Chaco vs. matplotlib?¶
This question comes up quite a bit. The bottom line is that the two projects initially set out to do different things, and although each project has grown a lot of overlapping features, the different original charters are reflected in the capabilities and feature sets of the two projects.
Here is an excerpt from a thread about this question on the enthought-dev mailing list.
Gael Varoquaux’s response:
On Fri, May 11, 2007 at 10:03:21PM +0900, Bill Baxter wrote: > Just curious. What are the pros and cons of chaco vs matplotlib? To me it seem the big pro of chaco is that it is much easier to use in a "programatic way" (I have no clue this means something in English). It is fully traited and rely quite a lot on inversion of control (sorry, I love this concept, so it has become my new buzz-word). You can make very nice object oriented interactive code. Another nice aspect is that it is much faster than MPL. The cons are that it is not as fully featured as MPL, that it does not has an as nice interactively useable functional interface (ie chaco.shell vs pylab) and that it is not as well documented and does not have the same huge community. I would say that the codebase of chaco is nicer, but than if you are not developping interactive application, it is MPL is currently an option that is lickely to get you where you want to go quicker. Not that I wouldn't like to see chaco building up a bit more and becoming **the** reference. Developers, if you want chaco to pick up momentum, give it a pylab-like interface (as close as you can to pylab) ! My 2 cents, Gael
Peter Wang’s response (excerpt):
On May 11, 2007, at 8:03 AM, Bill Baxter wrote: > Just curious. What are the pros and cons of chaco vs matplotlib? You had to go and ask, didn't you? :) There are many more folks here who have used MPL more extensively than myself, so I'll defer the comparisons to them. (Gael, as always, thanks for your comments and feedback!) I can comment, however, on the key goals of Chaco. Chaco is a plotting toolkit targeted towards developers for building interactive visualizations. You hook up pieces to build a plot that is then easy to inspect, interact with, add configuration UIs for (using Traits UI), etc. The layout of plot areas, the multiplicity and types of renderers within those windows, the appearance and locations of axes, etc. are all completely configurable since these are all first-class objects participating in a visual canvas. They can all receive mouse and keyboard events, and it's easy to subclass them (or attach tools to them) to achieve new kinds of behavior. We've tried to make all the plot renderers adhere to a standard interface, so that tools and interactors can easily inspect data and map between screen space and data space. Once these are all hooked up, you can swap out or update the data independently of the plots. One of the downsides we had a for a while was that this rich set of objects required the programmer to put several different classes together just to make a basic plot. To solve this problem, we've assembled some higher-level classes that have the most common behaviors built-in by default, but which can still be easily customized or extended. It's clear to me that this is a good general approach to preserving flexibility while reducing verbosity. At this point, Chaco is definitely capable of handling a large number of different plotting tasks, and a lot of them don't require too much typing or hacking skills. (Folks will probably require more documentation, however, but I'm working on that. :) I linked to the source for all of the screenshots in the gallery to demonstrate that you can do a lot of things with Chaco in a few dozen lines of code. (For instance, the audio spectrogram at the bottom of the gallery is just a little over 100 lines.) Fundamentally, I like the Chaco model of plots as compositions of interactive components. This really helps me think about visualization apps in a modular way, and it "fits my head". (Of course, the fact that I wrote much of it might have something to do with that as well. ;) The goal is to have data-related operations clearly happen in one set of objects, the view layout and configuration happen in another, and the interaction controls fit neatly into a third. IMHO a good toolkit should help me design/ architect my application better, and we definitely aspire to make Chaco meet that criterion. Finally, one major perk is that since Chaco is built completely on top of traits and its event-based component model, you can call edit_traits() on any visual component from within your app (or ipython) and get a live GUI that lets you tweak all of its various parameters in realtime. This applies to the axis, grid, renderers, etc. This seems so natural to me that I sometimes forget what an awesome feature it is. :)