This post is one of my white whales – the problem that has eluded me for far too long and drove me to the edge of insanity. I’m talking about writing binary. Now, let me be clear when I say that I am far from a computer scientist: I don’t think in base 16, I don’t dream in assembly code, I don’t limit my outcomes to zeros and ones. I do, however, digest material before writing about it, seek creative and efficient solutions to problems, and do my best to share this information with others (that’s where you come in).
First, let’s create a fake dataset with help from Nick Cox’s egenmore ssc command: set obs 300 forvalues i = 1/200 { gen x`i' = round(runiform()*50*_n) } gen id = _n reshape long x, i(id) j(vars) egen count = xtile(x), nq(30) keep id vars count Today we will be making a bitmap of a map for Fitbit activities by writing bits of binned colors in a binary file. Alliteration aside, this post pulls from various sources and is intended to cover a great deal of topics that might be foreign to the average Stata user – in other words, hold on tight! It’s going to be a bumpy bitmap ride as we cover three major topics: (1) Color Theory, (2) Bitmap Structures, and (3) Writing Binary Files using Stata. Color Theory
In creating gradients, it was recommended to me to use a Hue, Saturation, Value (HSV) linear interpolation rather than the Red, Green, Blue (RGB) interpolation because it looks more “natural.” I will not argue this point, as I know nothing about it. For me, I know that if I play with the sliders in Photoshop, it automatically changes the numbers and I never have to think about what it’s actually doing in the conversion. In order to convert from RGB to HSV and vice versa, I used the equations provided here – to learn about what’s going on, Wikipedia has a great article on the HSV cones!
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bitmap.do | |
File Size: | 4 kb |
File Type: | do |
Will Matsuoka is the creator of W=M/Stata - he likes creativity and simplicity, taking pictures of food, competition, and anything that can be analyzed.
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