Convert factors to numbers

If you have a vector of factors it is easy to get the factor level; however, I always forget how to extract the factor value. I ran into the answer here.

> x<-factor(c(round(rnorm(10),2),"A","B",NA))
> x
 [1] 1.61  1.12  1.26  0.09  -0.13 0.16  -0.03 -0.1  0.09  -0.47 
 [11] A     B    
Levels: -0.03 0.09 -0.1 -0.13 0.16 -0.47 1.12 1.26 1.61 A B
> as.numeric(x)
 [1]  9  7  8  2  4  5  1  3  2  6 10 11 NA
> as.numeric(levels(x)[x])
 [1]  1.61  1.12  1.26  0.09 -0.13  0.16 -0.03 -0.10  0.09 -0.47    
 [11]   NA    NA   NA
Warning message:
NAs introduced by coercion 

**UPDATE**
And another method mentioned in the comments (that I like better):

> as.numeric(as.character(x))

Preparing plots for publication

The plotting capabilities of R are excellent; however, when I am preparing a figure for publication, I often need to combine multiple plots or add objects (e.g., arrows or text) to an existing plot. While this can be accomplished in R, my patience for tweaking layout parameters tends to run out quickly. I searched around and found a nice solution using open source software (an example with Matlab plots is described here).

1) Create the desired figure in R and export as an eps file:

library(ggplot2)
postscript("myfig.eps",horizontal=FALSE, paper="special",height=10,width=10)
qplot(x,y,data=mydat)
dev.off()

2) Install the necessary software on your computer, and then convert the image file to one more easily edited.

#install software
sudo aptitude install pstoedit tgif

#clean up the eps file so it is more easily read
eps2eps myfig.eps myfig2.eps

#convert the eps file to a tgif object
pstoedit -f tgif myfig2.eps myfig2.obj

3) Edit the new file myfig2.obj in tgif.

Approximate sunrise and sunset times

This function is not perfect, but it does a reasonable job estimating sunrise and sunset times for my field site. If more accurate data are required, try here. Note, the command to calculate day of year is: strptime(x, "%m/%d/%Y")$yday+1

suncalc<-function(d,Lat=48.1442,Long=-122.7551){
  ## d is the day of year
  ## Lat is latitude in decimal degrees
  ## Long is longitude in decimal degrees (negative == West)
  
  ##This method is copied from:
  ##Teets, D.A. 2003. Predicting sunrise and sunset times.
  ##  The College Mathematics Journal 34(4):317-321.
 
  ## At the default location the estimates of sunrise and sunset are within
  ## seven minutes of the correct times (http://aa.usno.navy.mil/data/docs/RS_OneYear.php)
  ## with a mean of 2.4 minutes error.

  ## Function to convert degrees to radians
  rad<-function(x)pi*x/180
  
  ##Radius of the earth (km)
  R=6378
  
  ##Radians between the xy-plane and the ecliptic plane
  epsilon=rad(23.45)

  ##Convert observer's latitude to radians
  L=rad(Lat)

  ## Calculate offset of sunrise based on longitude (min)
  ## If Long is negative, then the mod represents degrees West of
  ## a standard time meridian, so timing of sunrise and sunset should
  ## be made later.
  timezone = -4*(abs(Long)%%15)*sign(Long)

  ## The earth's mean distance from the sun (km)
  r = 149598000

  theta = 2*pi/365.25*(d-80)

  z.s = r*sin(theta)*sin(epsilon)
  r.p = sqrt(r^2-z.s^2)

  t0 = 1440/(2*pi)*acos((R-z.s*sin(L))/(r.p*cos(L)))
  
  ##a kludge adjustment for the radius of the sun
  that = t0+5 

  ## Adjust "noon" for the fact that the earth's orbit is not circular:
  n = 720-10*sin(4*pi*(d-80)/365.25)+8*sin(2*pi*d/365.25)

  ## now sunrise and sunset are:
  sunrise = (n-that+timezone)/60
  sunset = (n+that+timezone)/60

  return(list("sunrise" = sunrise,"sunset" = sunset))
}

Convert polar coordinates to Cartesian

When I want to calculate the coordinates of a location (e.g., a nest or burrow) based on distance and bearing from a grid point, this function helps me avoid writing down SOH-CAH-TOA every time. Just note that the bearing in this case is from the grid point (known location) to the unknown location.

polar2cart<-function(x,y,dist,bearing,as.deg=FALSE){
  ## Translate Polar coordinates into Cartesian coordinates
  ## based on starting location, distance, and bearing
  ## as.deg indicates if the bearing is in degrees (T) or radians (F)
  
  if(as.deg){
    ##if bearing is in degrees, convert to radians
    bearing=bearing*pi/180
  }
  
  newx<-x+dist*sin(bearing)  ##X
  newy<-y+dist*cos(bearing)  ##Y
  return(list("x"=newx,"y"=newy))
}


##Example

oldloc=c(0,5) 
bearing=200 #degrees
dist=5

newloc<-polar2cart(oldloc[1],oldloc[2],dist,bearing,TRUE)
plot(oldloc[1],oldloc[2],xlim=c(-10,10),ylim=c(-10,10))
points(newloc$x,newloc$y,col="red")

Reorder factor levels

Very often, especially when plotting data, I need to reorder the levels of a factor because the default order is alphabetical. There must be many ways of reordering the levels; however, I always forget which package to look in. A direct way of reordering, using standard syntax is as follows:

## generate data
x = factor(sample(letters[1:5],100, replace=TRUE))

print(levels(x))  ## This will show the levels of x are "Levels: a b c d e"

## To reorder the levels:
## note, if x is not a factor use levels(factor(x))
x = factor(x,levels(x)[c(4,5,1:3)])

print(levels(x))  ## Now "Levels: d e a b c"

In this case, the level order could be set in the first line; however, if there are many levels (and you don't want to type out all of the levels explicitly), the above method is preferred. Again, if there is a better way to do this, please let me know in the comments.

Extract objects from a list

When using Rmpi to send processes to many nodes, it is convenient to create a list of tasks that are assigned to nodes as they become available. In my case, I was working through a large factorial set of simulations and needed to use a unique set of variable values for each task. Rather than assign these variables individually within the slave function, I decided to extract the variables directly from the list using a variation of the following code:

mylist=(list(a=1,b=2,c="string1",d=list("r"=2,"z"="string2")))

for(i in 1:length(mylist)){
  ##first extract the object value
  tempobj=mylist[[i]]
  ##now create a new variable with the original name of the list item
  eval(parse(text=paste(names(mylist)[[i]],"= tempobj")))
}

> print(a)
[1] 1
> print(b)
[1] 2
> print(c)
[1] "string1"
> print(d)
$r
[1] 2

$z
[1] "string2"

If there is a more elegant way to do this, please let me know in the comments.

Parallel computing in R

Lately I have been running R in parallel on a Beowulf cluster using the Rmpi package. Instrumental in my ability to do this were two excellent tutorials:

The Division of Biostatistics at UCSF provides some of the background required to get things running on the Linux side of things. (Note: sometimes the url for this site comes up with an extra "biostat" in the address -- just delete that and the page should load.

The Acadia Centre for Mathematical Modelling and Computation has a variety of sample scripts to point you in the right direction. Once you read through the code, it becomes very easy to set up a template you can re-use in the future.