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LaTeX version control todonotes http …

LaTeX version control

you can try this out todonotes

http://midtiby.blogspot.com/2008/07/todonotes-version-2008-07-28.html

Todo notes
Todo notes

Good for leaving comments.
Image placeholder.

24 year old guy dating 30 year old woman trackchanges

http://trackchanges.sourceforge.net/index.html

track changes
Track changes footnote
Track changes inline
track changes margins
Track changes margins

Margin, footnote, inline options to display the changes.
GUI to accept changes. Python installation is required.

see here now changes

http://www.ctan.org/tex-archive/macros/latex/contrib/changes

changes
Changes inline
changes options
Changes draft options

Draft and final options. Easy to make final output without running another utility or scripts.

blog latexdiff

http://www.pppl.gov/~hammett/comp/tex/latexdiff.html

latex diff
LaTeX Diff output

Edit the LaTeX source file without extra tags so the source remains clean.
This Perl script generates another LaTeX file for review.
Perl installation is required.

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Using rsync to sync files rsync avh source…

Using rsync to sync files.

rsync -avh source_folder/ target_folder/
  • -a: archive mode
  • -v: verbose
  • -h: human readable

Additional options

  • -u: update only (preserve newer files)
  • -H: preserve the hard link
  • –progress: shows progress
  • -n: dry run (without actual copying)

By the way, “/home/user/dir/” and “/home/usr/dir” are not the same thing to rsync. Without the final slash, rsync will copy the directory in its entirety. With the trailing slash, it will copy the contents of the directory but won’t recreate the directory.

For more explanations, check this nice post.

http://www.linux.com/news/enterprise/storage/8200-back-up-like-an-expert-with-rsync

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R graph by examples http://rgraphics.li …

R graph by examples
http://rgraphics.limnology.wisc.edu/index.php

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functions depending on the data types in …

functions depending on the data types in R
[table id=1 /]

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Differences in single argument subscript …

Differences in single argument subscripting in matrix and data frame.
Even though the two variables look similar, the results are different depending on the data type.
The single argument scripting of data frame returns a column, while matrix returns an element according to its position as matrix is a vector.

> class(my2)
[1] "data.frame"
> my2
  a1  b  c a1.1
1 10 20 30   35
2 10 20 30   35
> my2[1]
  a1
1 10
2 10
> class(my2.matrix)
[1] "matrix"
> my2.matrix
  a1  b  c a1.1
1 10 20 30   35
1 10 20 30   35
> my2.matrix[1]
[1] 10 
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Prevent drop dimension attribute by drop …

Prevent drop dimension attribute by drop = FALSE.

test.matrix <- matrix(1:15, nc=5)
> test.matrix[1, ]
[1]  1  4  7 10 13
> test.matrix[1, , drop=FALSE]
     [,1] [,2] [,3] [,4] [,5]
[1,]    1    4    7   10   13
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Subscripting in R * [ gives the same …

Subscripting in R

[ gives the same data type as the data it is applied to.
[[ and $ extract the element and the data type is not necessarily the same as that of the data it is applied to.

$ does partial matching.
[ and [[ don’t.

$ does not evaluate.
[ and [[ evaluate their arguments.

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declare a list and adding an element in …

declare a list and adding an element in R

test.list <- list()
test.list[['key']] <- value  # adding an element
test.list[['key']]  # retrieve the element