A recent article in The Atlantic titled, “How the Professor Who Fooled Wikipedia Got Caught By Reddit” describes how GMU’s Prof. T. Mills Kelly has had students fake history online, and how their most recent effort unraveled. There’s lots to think about here regarding what scientists should know about using the web, trusting it, and making it their own…
We are pleased to announce that we will be running two boot camps in Ontario in July: one at the University of Waterloo on July 12-13, and another at the University of Toronto (Scarborough) on July 19-20. If you’d like to take part, please sign up, and please let friends and colleagues know about them as well.
Last week’s homework was to convert a two-level bullet-point list like this:
* A * B * 1 * 2 * C * 3
into an HTML list like this:
<ul>
<li>A</li>
<li>B
<ul>
<li>1</li>
<li>2</li>
</ul>
</li>
<li>C
<ul>
<li>3</li>
</ul>
</li>
</ul>
so it would display like this:
My solution is shown in the video below; the code follows.
import sys
def do_inner(lines, current):
need_to_start = True
need_to_close = False
while (current < len(lines)) and \
lines[current].startswith(' * '):
if need_to_start:
print ' <ul>'
need_to_start = False
text = lines[current].lstrip(' * ').rstrip()
print ' <li>' + text + '</li>'
need_to_close = True
current += 1
if need_to_close:
print ' </ul>'
return current
def do_outer(lines):
print '<ul>'
current = 0
while current < len(lines):
assert lines[current].startswith('* ')
text = lines[current].lstrip('* ').rstrip()
print '<li>' + text
current = do_inner(lines, current+1)
print '</li>'
print '</ul>'
lines = sys.stdin.readlines()
do_outer(lines)
Our workshop at Michigan State University this week was three days long instead of two, and included two topics (Git and the IPython notebook) that we haven’t tried before. Feedback was generally positive, but we’ve got lots to work on for next time as well.
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RunMyCode is a web site and service intended to support reproducible research (initially in computational economics). Authors create companion web sites for papers that include the software they used; other people can then re-run their models, and (crucially) play with parameters, using cloud-based instances of those environments. They only support MATLAB, R, and SAS right now, but are hoping to add more tools soon. It’s a cool idea, and we’d welcome your impressions.
The May/June 2012 issue of Washington Monthly has an article by Alison Fairbrother titled “A Fish Story“. Near the top, it says, “In 2009, a routine methodological upgrade at NOAA—and the subsequent discovery of a few lines of faulty computer code—forced the start of a profound shift in the ASMFC’s estimates of menhaden stocks.” A few pages later, we get more details:
In 2009, the Menhaden Technical Committee updated its methodology for estimating the menhaden population—something it does every five years—and then ran the menhaden catch data through a new computer model. The results weren’t much different: although the numbers of menhaden were declining, the estimated number of eggs produced by spawning female menhaden was at the target level, so according to the reference point, menhaden weren’t being overfished.
Shortly thereafter, a colleague of Jim Uphoff’s, a biologist named Alexei Sharov, got hold of the computer model that had been updated by NOAA scientists. Going through the code line by line, Sharov, one of Maryland’s representatives on the Technical Committee, found a fundamental miscalculation buried inside the model. Uphoff, meanwhile, studied the methodology of the code and discovered that NOAA had both underestimated the amount of fish killed by the industry and overestimated the spawning potential. Sharov brought these two mistakes to his peers on the committee, and it was agreed that corrections needed to be made.
Several months later, after the model had finished running a second time, the science finally caught up with what Jim Price and the anglers had been saying for decades: even using the lax reference points developed by the ASMFC, menhaden had been subject to overfishing in thirty-two of the past fifty-four years. When the assessment was then peer reviewed by a group of international scientists, the reviewers deemed that the reference point currently in use for menhaden—8 percent of maximum spawning potential—was not sufficiently safe or precautionary.
Furthermore, the number of menhaden swimming in the Atlantic had declined by 88 percent since 1983—to a level so low that it caused George Lapointe, former commissioner of Maine’s Department of Marine Resources, to have what he called an “oh shit moment.”
If anyone knows more about the “fundamental miscalculation”, I’d be grateful for a summary.
We are pleased to announce that we will be running a boot camp on July 9 and 10 in Boston—please see its page for details (some of which we’re still working out). We have room for 40 participants, so please register early. (And if you can, register with friends: we are finding that people get a lot more out of this training if they’re learning with their labmates and other collaborators.)
We are very pleased to announce that The Architecture of Open Source Applications: Volume 2 is now available from Lulu. A PDF version will go on sale in the next few days, and e-book will become available as soon as we can produce it. Many thanks to everyone who contributed, and to the indefatigable Amy Brown for pulling it all together. As always, all royalties will go directly to Amnesty International, so if you buy a copy, you’ll be helping to make the world a better place.
Let’s say you have a text file called workout.csv that contains information about your workouts for the month of March:
# date, kind of workout, distance (miles), time (min) "2012, Mar-01", run, 2, 25 "2012, Mar-03", bike, 10, 55 "2012, Mar-06", bike, 5, 20 "2012, Mar-09", run, 3, 42 "2012, Mar-10", skateboarding, 2, 10 # Broke my leg"2012, Mar-11", Wii, 0, 60 "2012, Mar-12", Wii, 0, 60 "2012, Mar-13", Wii, 0, 60 "2012, Mar-14", Wii, 0, 60
It’s a common-separated value (CSV) file, but contains comments and blank lines. The first line (a comment) describes the fields in this file, which are (from left to right) the date of your workout, the kind of workout, how many miles you traveled, and how many minutes you spent.
Our goal will be to read this data into Python and plot a graph with the day of the month on the x-axis and the time worked out on the y-axis. Let’s get started.
For the boot camp at UCL, we tried using Mercurial (with EasyMercurial) instead of Subversion in the version control segment.
You can see the plan for the segment on this EasyMercurial project page. Briefly, we opened with a few plain slides about the purpose of version control, followed by a hands-on example in three parts (working by yourself, working by yourself with an online remote repository, and working with others). We started at the beginning and got as far as “hg bisect”, but did not cover branching.
I was presenting the segment, so I’m not well placed to judge how effective it was as a learning experience. But I did make some notes.