I just tried my first mulled beer: BFM La Dragonne. While the weather is not quite appropriate yet, it is just beginning to get cool here in Atlanta. I heated it to about 55 degrees C and enjoyed it in a wine glass, though perhaps a tumbler would have been better. Also while the beer is labeled at 7%, someone scratched it out and wrote 4% by hand. Not sure what that’s about. I’m going to save a bottle for Thanksgiving and enjoy it again with family, when the weather is more appropriate. Christmas might be a better choice, but I don’t have that kind of patience.
This week I came across two very appealing technologies from completely unexpected sources. Granted, these aren’t new, but I think they pose interesting challenges to the reigning awesome sauce (Mac OSX, iOS, Android).
Actual innovation in the operating system space from Microsoft? Windows 8 looks like it could be a real challenger.
And the Nokia N9. Just when I had written Nokia off for good, they produce a phone that looks like it’s actually worth looking twice at.
Tags: code, math, random number generation, ruby, rubygems, statistics
gem install simple-random
The gem allows you to sample from the following distributions:
- Chi Square
- Inverse Gamma
- Laplace (double exponential)
- Student t
r = SimpleRandom.new
r.uniform # => 0.127064087195322
r.normal(5, 1) # => 5.71972152940515
Tags: attention scarcity, daniel tunkelang, tunkrank
Tags: fluiddb, tickery, tunkrank, twitter
Tickery is a rather awesome application of FluidDB that lets you explore Twitter in a number of ways. I mentioned previously in post on recent TunkRank improvements that TunkRank scores would soon be integrated with Tickery, and thanks to Terry Jones and his crew, the time is now!
Full disclosure: I’m a fan of FluidDB. I think it’s an awesomely useful technology and concept and I’m happy that TunkRank scores can be a part of it. One cool thing is that FluidDB’s permission system is designed so that even though Tickery is using TunkRank’s data, TunkRank still owns it. It can be revoked at any time if there was a reason to do so (not that I can imagine such a thing will ever be the case). Also, the data in FluidDB for Tickery and TunkRank are completely independent. Anyone else can come along and add a new set of data for mash-ups that would then use all three, without TunkRank or Tickery having to do a thing.
Playing around with Tickery
Now when you use the advanced search on Tickery, you can filter your results by TunkRank score, letting you do some interesting combinations on the data. For example, if I want to see who I’m following TunkRank scores greater than 50:
has twitter.com/friends/ealdent and tunkrank.com/score > 50
There’s lots to play around with there, especially when you start comparing the friends of various users. For example, if you wanted to know who Daniel Tunkelang (@dtunkelang) and I both follow who have TunkRank scores less than 20:
has twitter.com/friends/ealdent and
has twitter.com/friends/dtunkelang and
tunkrank.com/score < 20
Those people have something clearly in common, and it tells you something about the interests that Daniel and I share. I hope you check it out and let me know what you think.
Tags: api, dictionaries, erin mckean, ruby, rubygems, wordnik
They released an API a few months ago and I quickly threw together a gem wrapping it, based on HTTParty. Tonight I updated the gem for version 3 of the API and simplified it to just a single class with the bare essentials. You can perform pretty much all of the API calls and get a hash of the results. It’s nothing major, but will give you a chance to play around with the Wordnik API with almost no work on your part (aside from getting yourself a key). This change breaks backwards compatibility completely, sorry.
w = Wordnik.new("YOUR_API_KEY")
w.define('gem') # => big hash with all the definitions
w.examples('gem') # => example sentences using "gem"