Monthly Archives: January 2012

Max Miscellanea #1

Just a couple of silly things that I tried after watching some videos by the creators of Max, Cycling ’74. These were posted on YouTube under their “Did You Know” series, although I’m linking them in to my YouTube account as I watch each one. The first is a little bon bon for us nice and orderly types and the second is frivolous, although it does have some more useful application, which may come up later.

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MMJ4M 02: Generating Music

“Random Atonal Trash,” or RAT, is the term that VJ Manzo uses for the Max patches in Chapter 2 of his book Max/MSP/Jitter for Music. What that means is that tones are generated using random numbers. There are several variations on the patch, including a few with sliders for duration and tone. The next few patches seem to require an actual keyboard, which I don’t have, so we’ll see what happens.

And, happily, I just came across another blog that is working through VJ Manzo’s Max book: mikecrane.wordpress.com. I’ll link his stuff as often as I can.

Completed:

  • Max/MSP/Jitter for Music, Ch. 2: Generating Music (first part) (6 exercises)
  • Patches can be downloaded from http://db.tt/GBYLb0vY (Dead Link)
  • UPDATED LINK: Patches can now be downloaded from http://j.mp/1iy19Xl
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Film School Advice for Data Analysts

 

I just finished reading Neil Landau and Matthew Frederick’s delightful little book, 101 Things I Learned in Film School. (It’s part of an entire series of books that started with Frederick’s own 101 Things I Learned in Architecture School, of which more will be said at a later date. The other titles address fashion school, culinary school, and business school. I will address these, too, at later dates.) What’s most interesting about this book is not that plan on going to film school or working with film as such but that I can see at least some connection between many of the ideas in the book and my own goal of data analysis (believe it or not). The idea is this: when you analyze data, you are telling a story, and stories can be told in ways that are more or less interesting, informative, or effective. Inasmuch as cinema also tells stories, some of the principle carry over. For example:

  • 10: Make Psychology Visual. That is, by changing camera angles and distance, different meanings can be ascribed to a scene. The same is true for designing visualizations (I imagine).
  • 14: Beginning, Middle, End. That is, there is a comfortable narrative structure to a film, and that structure can be repeated at smaller scales. Although visualizations are typically presented as static images, they can still present a form of narrative. This is especially true for those gigantic, long infographics you’ll see. And it is certainly true for any video-based visualization (and maybe there should be more of those).
  • 22: Plot is physical events; story is emotional events. Data analysis is more than just presenting bits of information (i.e., the physical events). It is an exercise in meaning-making through the interpretation and application of insights derived from analysis (akin to the “emotional” component of the story).
  • 64: Dig Deeper. “Do fewer things, but do them better.” In analysis, rather than presenting as many factoids as possible, it is better to understand the distinctive characteristics of the nature, such as why there are outliers on a particular variable, why a scatterplot is curved instead of straight, and why the wording of two similar questions gives different answers.
  • 93: “Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.” — Antoine de Saint-Exupéry. It’s very easy and very tempting to add more charts, more variables, more tables, more stuff to an analysis. But people have a limited attention span and the analysis is often understood in a heuristic fashion anyhow, so it’s much better to limit oneself to the minimum amount of analysis that will give a valid and useful conclusion.

So, it may be a bit of a stretch, but that’s actually what I had in mind when I was reading this fine book and the other ones in the series. Inspiration is everywhere.

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Bouncing off the Walls

In the second group of exercises from Daniel Shiffman’s book Learning Processing, the topics covered include basic rollovers, toggles, movement from edge to edge, and simulated gravity. I have to admit that it took me about two hours to work through a bizarre little kink in the synthetic gravity part, where the objects would fall down and sometimes just quiver on the floor. Not what I was looking for. I think I solved it. Maybe. I think that the most interesting effects, though, are the ones involving semi-transparent circles leaving traces on the screen. Ooooooohhhh, wow… In any case, here are a few more screenshots and videos.

Completed:

  • Learning Processing, Ch. 05: Conditionals (6 exercises)
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Elmore Leonard on Preemptive Editing

Writer Elmore Leonard was interviewed on NPR today. He was introduced with this pearl:

“I try to leave out the parts the readers skip.”

Amen.

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Fiona Apple on Truth in Art

“The way I feel about music is that there is no right and wrong. Only true and false.”

— Fiona Apple (as quoted in Daniel Shiffman’s book Learning Processing)

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Back to the Basics with "Learning Processing"

I decided that before I got too much further in Ben Fry‘s rather-advanced book Visualizing Data I would do well to go back through Daniel Shiffman’s introductory-intermediate-advanced book Learning Processing. So, in a sense I’m starting from square one again, as I’m doing every coding exercise in the book from  the beginning. But it’s always nice to have a firm foundation, isn’t it?

So, here’s the first batch of sketches. In the book, Shiffman recommends that one create a basic shape to elaborate upon as one learns new material. He made a simple alien that he calls Zoog. I decided to make a stick-figure dancer. (In Getting Started with Processing by Casey Reas and Ben Fry, they use P5, the Processing Robot as the running example.) I have still images in the gallery above. The first two are inherently static, the second two are screenshots from a dynamic sketch. Videos of the sketches in action are below.

Completed:

  • Learning Processing, Ch. 00: Preface (0 exercises)
  • Learning Processing, Ch. 01: Pixels (1 exercise)
  • Learning Processing, Ch. 02: Processing (1 exercise)
  • Learning Processing, Ch. 03: Interaction (2 exercises)
  • Learning Processing, Ch. 04: Variables (1 exercise)
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Getting It All on Video

I’m planning on creating a whole bunch of things on my computer that can’t be adequately represented with screenshots. (I will, however, still include those as often as possible.) As such, I thought it would be nice to upload some small videos so my professors could see what I’m up to. I already have a YouTube channel at youtube.com/bartonpoulson but that functions primarily for my statistics tutorials (which are doing very nicely, thank you) and I didn’t want to mix these up with those.

At first I thought I’d try posting my artsy videos on the extra artsy Vimeo service. But then everything got very, very complicated. Vimeo wanted money, they wanted me to wait 30 minutes to see my 30 second clip, and so on. Then I thought I would try WordPress’ own service, VideoPress. But that, too, looked like it would be expensive and cumbersome.

Then I found out that I could simply embed the URLs from YouTube. Quick, easy, and free. As Yul Brenner, as Pharoah, was wont to say: “So let it be written, so let it be done.”

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More Than a Straight Line This Time

When I last posted on my work with Ben Fry’s excellent book Visualizing Data, I posted all of two drawings, both of which were made with straight lines. Well, Chapter 3, “Mapping,” does a heck of a lot more than that. It took me two days to get through this chapter (as opposed to 1:48 — I timed it — for Chapter 2). It was working on an interactive map of the US. Anyhow, the gallery above contains the many version of the sketches I did while following along with the examples. The still photos do not demonstrate the interactive, changing nature of several of these sketches, I’ve embedded a YouTube video below:

In the meantime, I think I need to go back to Daniel Shiffman’s fabulous book Learning Processing to get up to speed on some of the intermediate stuff first.

Completed:

  • Visualizing Data, Ch. 3: Mapping (17 exercises)
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Finally Launchpad Makes Sense

So when Steve Jobs gave a preview of Lion (AKA Mac OS X 10.7) he talked all about how they were bringing features from the iPhone “back to the Mac.” One of these was the icon screen, which on the Mac is called Launchpad. All I can remember is that when I first installed Lion and looked at Launchpad, it was an irretrievable mess, so I tried to forget that it existed.

Then, I decided to do a total wipe of my hard drive and start all over. (This was motivated by the fact that sometimes my computer would get stuck and just hang on processes that shouldn’t have been a problem.) But this time I installed my apps very selectively and in order. I then cleaned up Launchpad as things came in. And now, it’s so lovely and wonderful that I just can’t stand it!

Also, I had to deal with my desire to categorize everything. In this case, I tried organizing the games (which I basically never play) in several ways, until finally I decided that they didn’t have to get categorized at all but could just have their own pages and be in alphabetical order. Ahhhhh….

Anyhow, I’m so happy with it I thought I’d post a few pictures.

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