dwinter

entrez_search <- function(dbase, term, retmax=6,...){
    base_url <- "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=%s&term=%s&retmax=%i"
    search <- sprintf(base_url, dbase, term, retmax)
    raw_result <- getURL(search)
    ids <- unlist(getNodeSet(xmlParse(raw_result), "//Id", fun=xmlValue))
    return(as.integer(ids))
}

entrez_fetch <- function(dbase, ids, format, ...){

dwinter

"""
Summarise a variable in a BEAST logfile

arguments:
  -h, --help              show this help message and exit
  -f or --file string     whats the name of the BEAST file
  -v or --variable string value you want to summarise                          
  -b or --burnin int      number of states to ignore
  -g                      export graphs to summarise the sample?
  -l                      export a logfile for just this variable

dwinter

#
# Code to parse the interesting bits of a PAML results file that contains
# statistics for several trees. Note, this approach contains some hacks that
# are probably specific to multiple-tree CODEML files, Biopython has a module
# for handling other PAML outputs, and it probably a better starting point for
# 'normal' (single tree) input files.
#
# TODO - should clean up handlng of resifues - use @property decorator and
# ._functions to simplify writing/reading.
#

dwinter

#calculate Cummings et al (2008) _gsi_ - a meaure of the exlusivity of a 
#predefiend group of leaves in a phylogenetic tree


#example
#
# tr <- rtree(10)
# grp <- paste("t", 1:5, sep="")
# gsi(tr, grp)

dwinter

library(ggplot2)

df0 <- data.frame(x=rnorm(100), y=rnorm(100), grp=factor(rep(letters[1:2], each=50)))
p <- ggplot(df0, aes(x,y, colour=grp, alpha=y))
p + geom_point() 



library(RColorBrewer)

dwinter

chars <- c("ABC", NA, "DEF")
(urls <- paste("web-api&id=", chars, sep=""))
## [1] "my-fav-web-api/id=ABC" "my-fav-web-api/id=NA"  "my-fav-web-api/id=DEF"

dwinter

df1 <- data.frame(x=sample(letters, 20), y=rnorm(20))
df2 <- data.frame(x=sample(letters, 20), z=rnorm(20))
new_df <- merge(df1, df2, all.x=TRUE)

matched <- merged[complete.cases(merged),]
unmatched <- merged[!complete.cases(merged),]

dwinter

model_diagnostics <- function(modlist, plot=TRUE){

  get_param_ranges <- function(x) {
		res <- apply((sapply(x, posterior.mode)),1,range)
		rownames(res) <- c("min", "max")
		return(res)
	}
	
	n <- length(modlist)
	on.exit(devAskNewPage(devAskNewPage())) #ie send it back the way it was

dwinter

f <- function(x,y) sin(x)/cos(y)
x <- seq(-5,5,0.1)
y <- seq(-5,5,0.1)

df <- expand.grid(x,y) #all possible combinations of x and y
df$value <- apply(df, 1, function(x) f(x[1], x[2]))

p <- ggplot(df, aes(Var1,Var2,fill=res>0))
p + geom_raster()

dwinter

import random

def shotgun(iterable, size=12):
    """ """
    start = random.choice(range(0, len(iterable)-size))
    return(start, iterable[start:start+size])

def paired_end(iterable, read_size=10, gap_size=15):
    """ """
    start = random.choice(range(0, len(iterable)-(read_size+gap_size)))