A hilarious economics post

This post:
https://medium.com/@yichuanw/a-dynamic-theory-of-romantic-choice-6e275270da93

is about explaining why "all the single people are crazy" and "all the good ones are taken".  It is hilarious and mathematical.

It would be awesome to fit that model with data from OK Cupid...

Electric imp temperature sensors

After experiencing many burst pipes (in our baseboard heaters) I decided to build some temperature sensors.  My friend Phil recommended using the electric imp microcontroller and quickly found a tutorial on how to use it to make a temperature sensor:   https://plot.ly/electric-imp/tmp36-temperature-tutorial/

In the above the general concept & required components are spot on, but some of the specifics / details are off.  Here's what I did, which is the same in outline but differs in some specifics (which I hope are accurate).

Parts:

• Electric imp
• developer kit quick start guide:  https://electricimp.com/docs/gettingstarted/quickstartguide/
• electric imp breakout board
• spec sheet:  https://cdn.sparkfun.com/datasheets/Wireless/WiFi/electric-imp-breakout-v12.pdf
• analog devices tmp36 temperature sensor
• spec sheet:  http://dlnmh9ip6v2uc.cloudfront.net/datasheets/Sensors/Temp/TMP35_36_37.pdf
• AC to USB adapter (vivitar, rated to ~1 A)
• USB to mini USB cord
• important:  this is mini, not micro.  the electric imp breakout board from sparkfun takes mini, not micro.
• bread board
• wire jumpers
• wire
• solder
• soldering iron
• code to run in electric imp IDE:  https://github.com/dllahr/home_control/tree/eimp_blog_posts/electric_imp/temperature_sensing

Clustering vs. Linear Regression - which to use?

I've got some data and I'm trying to make an informed decision whether it is better described by a linear regression or a set of clusters.

My goal here is to compare linear regression and clustering for some cases that are obviously better for one of these or the other, using 2-dimensional data that is easy to visualize.  By comparing these two workhorse methods under these conditions I'm hoping to gain better understanding of each and of how to decide when to use one or the other.

The 3 data sets I used were:

1. "obviously" better described by linear regression
2. "obviously" better described by clustering
3. in between the above 2 extremes

I used R.  The scripts I used are present in this repository:
https://github.com/dllahr/cluster_vs_linear_regression

I got the code for clustering from:
http://www.statmethods.net/advstats/cluster.html

Before we get started:  my friend Phil Montgomery who kindly reviewed this post made a good suggestion that in general, when you have 2 models and you are trying to decide which one to use, you want to compare the statistical likelihood of each.  Usually this is done by comparing different values of parameters for a mathematical model, but it is worth investigating if it has been done for comparison of these two systems.

Raspberry Pi RAID array

I largely followed these very helpful instructions:
http://www.davidhunt.ie/raid-pi-raspberry-pi-as-a-raid-file-server/

also useful:
http://ubuntuforums.org/showthread.php?t=408461
http://en.wikipedia.org/wiki/RAID
http://en.wikipedia.org/wiki/Mdadm

ingredients

• 2 1-TB western digital drives
• USB hub with power supply for these
• Edit: make sure it has enough power to power the drives! My initial one (pictured below) did not and I suspect it was drawing power from the pi causing it to crash
• raspberry pi
• USB power supply for this (separate from above)
• 8 GB sandisk microSD card
• for use in raspberry pi
• microSD card reader
• cables to connect all

Matlab solar system trajectory simulation

I wrote some code to simulate the trajectory of an object through a grossly simplified version of the solar system.  It uses the ordinary differential equation solver that comes with Matlab, some Newtonian physics, only has the Sun, Earth and Moon, and only uses idealized, circular orbits for those.  The code is here in this github repository:
https://github.com/dllahr/Matlab_solar_trajectory_sim

It's kind of fun to play with and someday I'd like to make an interactive web browser version of it, using perhaps this javascript library for numerical calculations:
http://numericjs.com/

Update - important note:  I have subsequently learned about the problem of energy drift which is when using basic differential equation solvers on even simple Newtonian systems, the result will have the system's energy increasing over time - sometimes even exponentially!  There are another class of differential equation solvers (Verlet Integration, Sympletic Integrator) that address this problem, the solar system trajectory code above should be updated to use these instead.

Priceless description of thesis research

http://www.cs.virginia.edu/~evans/cs655/manifests/rabbit.html

This applies more generally, unfortunately

Peanut butter porter - the bottling

I bottled the peanut butter porter today, I used ~5/8 cup of dry malt extract for the sugar, boiled in water ~5 minutes, added to the beer as I was transferring from the carboy to the bottling bucket.  The material left over in the carboy was an oily mess, and based on that and what I tasted, I'm hopeful that most / all of the oil was left behind and the beer in the bottles is not oily.  However, I tasted it and it didn't really taste like peanut butter!