More Data Smoothing fun and some Open GL
It's been an informative few weeks. While I feel like I've been using very thick unwaxed mental floss, I have been learning some new programming (and some data smoothing...) toys. A review of the OpenGL class at Big Nerd ranch is coming this weekend. I have my reasons for delaying this review. It was a great experience (don't worry Rocco); I just want to see if I can actually use what I've been learning in Atlanta to make something.
So! Below is an openGL rendering of the run data you saw in an earlier post. I'm getting closer to figuring out their smoothing tricks! What you are looking at is a moving average with a 14 point window. This gets us much closer to the Nike+ online graph, but we're not quite there yet. Next I try two things:
1. Throw out (or somehow attenuate) aberrant points.
2. Throw a best fit curve in there.
My goal is to be able to reproduce nike+apple's smoothing relatively reliably so that I can then present options (preferences...) to the user for data smoothing style in my cool new run logging application...
