BY diploid with the same mating factors (in progress)

Kaeberlein and Kennedy has a RLS paper using BY diploid with the same mating factor. Which paper is that?

ifelse logical mistake

The following codes has a logical mistake, and will not assign color by categories. The ifelse should be nested.

# tbomegaH2C1S1$color[i] = ifelse( tbomegaH2C1S1$CoatLocation[i]=="OuterCoat", 'red', tbomegaH2C1S1$color[i] )
# tbomegaH2C1S1$color[i] = ifelse( tbomegaH2C1S1$CoatLocation[i]=="InnerCoat", 'blue', tbomegaH2C1S1$color[i] )
   tbomegaH2C1S1$color[i] = ifelse( tbomegaH2C1S1$coatflag[i]=="coat", 'red', tbomegaH2C1S1$color[i] )
   tbomegaH2C1S1$color[i] = ifelse( tbomegaH2C1S1$essenflag[i]=="essential", 'black', tbomegaH2C1S1$color[i] )

Survival probability of computer viruses is exponential

Romualdo Pastor-Satorras, Alessandro Vespianai, Physical Review Letters, 2001, Epidemic spreading in scale-free networks.

GDP per capital by country, case study

Countries with small populations will have large sample variances, whereas countries with large population will have much smaller sample variances. There is a Ted talk on this, but I had not found the original video. I only remember it is from a population geneticist.

SEM = sigma / sqrt(sample_size)

R code for demo

world = rnorm(7.1E3)  #world population 7.1 billion
china = sample(world, 1.1E3)  #china 1.1 billion
c1 = sample(world, 20) #20 million pop for country c1

itr = 100
list.china = numeric(itr)
list.c1 = numeric(itr) 
for( i in 1:itr){
 list.china[i] = mean( sample(world, 1.1E3) )
 list.c1[i] = mean(sample(world, 20)  )
}


Reference: 

http://ablog.typepad.com/keytrendsinglobalisation/2013/05/only-30-of-the-world-now-has-a-higher-gdp-per-capita-than-china.html

Ted video on GDP per capital by country.

behind the scene of Gibhub

output of 'ps -ef | grep git'

  502  3074 86237   0  4:15PM ??         0:00.00 git pull --rebase --progress --prune --recurse-submodules=on-demand origin
  502  3075  3074   0  4:15PM ??         0:00.01 /bin/sh /Applications/GitHub.app/Contents/Resources/git/libexec/git-core/git-pull --rebase --progress --prune --recurse-submodules=on-demand origin
  502  3166  3075   0  4:16PM ??         0:00.10 git fetch --progress --update-head-ok --prune --recurse-submodules=on-demand origin
  502  3174  3166   0  4:16PM ??         0:00.00 git gc --auto
  502  3177  3174   0  4:16PM ??         0:00.00 git repack -d -l
  502  3178  3177   0  4:16PM ??         0:00.01 /bin/sh /Applications/GitHub.app/Contents/Resources/git/libexec/git-core/git-repack -d -l
  502  3191  3178   0  4:16PM ??         0:00.00 /bin/sh /Applications/GitHub.app/Contents/Resources/git/libexec/git-core/git-repack -d -l
  502  3192  3191   0  4:16PM ??         0:19.38 git pack-objects --keep-true-parents --honor-pack-keep --non-empty --all --reflog --unpacked --incremental --local --delta-base-offset /Users/hqin/github/BacillusSporeCoat/.git/objects/pack/.tmp-3178-pack

Greek letters and Latex formula in R (to be continuted)

I tried to add $\omega_s$ as axis label. It seems some extra work need to be done.

plot(1:3, ylab = expression("Diameter of apeture (" * mu ~ "m)"),
  , xlab = expression("Force spaces with ~" ~ mu ~ pi * sigma ~ pi)
  , main = expression("This is another Greek character with space" ~ sigma))

http://stackoverflow.com/questions/6044800/adding-greek-character-to-axis-title

http://stackoverflow.com/questions/1395105/getting-latex-into-r-plots

Konigsberg bridge problem is taught at the 4th grade in primary school in China

The Konigsberg 7 bridge problem is discussed in a 4-th grade math textbook in primary schools in China. This textbook is the training materials for Olympic Math competition, and has been used in mass.

Yi Jiang's note, 20130918

Yi Jiang's note:

I find out that these two methods are what we need to parse those huge XML files: cElementTree.iterparse() and ElementTree.iterparse().
(1) http://effbot.org/zone/celementtree.htm
(2) http://effbot.org/zone/element-iterparse.htm

Both can load a small piece of the XML file into the memory and then parse it, which prevents occupying too much memory resources. And the iterparse() method in cElementTree library is faster than that in ElementTree library.

There are two questions I need to figure out:
1. How to remove items.
once an item is parsed, it needs to be removed to release the memory. Things to be released not only include the content within the item, but also include the item itself. Also, we also need to remove those items that we are not interested in.

2. namespace
Some documents discussed on how to solve problems related to the namespace. I will try to figure out whether it will be a problem in our project.