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\name{caTools-package}
\alias{caTools-package}
\alias{caTools}
\docType{package}
\title{
Tools: moving window statistics, GIF, Base64, ROC AUC, etc.
}
\description{
Contains several basic utility functions including: moving
(rolling, running) window statistic functions, read/write for
GIF and ENVI binary files, fast calculation of AUC, LogitBoost
classifier, base64 encoder/decoder, round-off error free sum
and cumsum, etc.
}
\details{
\tabular{ll}{
Package: \tab caTools\cr
Version: \tab 1.6\cr
Date: \tab Apr 11 2006\cr
Depends: \tab R (>= 2.2.0), bitops\cr
Suggests: \tab MASS, rpart\cr
License: \tab The caMassClass Software License, Version 1.0 (See COPYING
file or \url{http://ncicb.nci.nih.gov/download/camassclasslicense.jsp})\cr
URL: \tab http://ncicb.nci.nih.gov/download/index.jsp\cr
Built: \tab R 2.2.1; i386-pc-mingw32; 2006-04-14 10:45:20; windows\cr
}
Index:
\preformatted{
LogitBoost LogitBoost Classification Algorithm
predict.LogitBoost Prediction Based on LogitBoost Algorithm
base64encode Convert R vectors to/from the Base64 format
colAUC Column-wise Area Under ROC Curve (AUC)
combs All Combinations of k Elements from Vector v
read.ENVI Read and Write Binary Data in ENVI Format
read.gif Read and Write Images in GIF format
runmean Mean of a Moving Window
runmin Minimum and Maximum of Moving Windows
runquantile Quantile of Moving Window
runmad Median Absolute Deviation of Moving Windows
runsd Standard Deviation of Moving Windows
sample.split Split Data into Test and Train Set
sum.exact Basic Sum Operations without Round-off Errors
trapz Trapezoid Rule Numerical Integration
}
}
\author{Jarek Tuszynski <jaroslaw.w.tuszynski@saic.com>}
\keyword{ package }
\examples{
# GIF image read & write
write.gif( volcano, "volcano.gif", col=terrain.colors, flip=TRUE,
scale="always", comment="Maunga Whau Volcano")
y = read.gif("volcano.gif", verbose=TRUE, flip=TRUE)
image(y$image, col=y$col, main=y$comment, asp=1)
# test runmin, runmax and runmed
k=25; n=200;
x = rnorm(n,sd=30) + abs(seq(n)-n/4)
col = c("black", "red", "green", "brown", "blue", "magenta", "cyan")
plot(x, col=col[1], main = "Moving Window Analysis Functions (window size=25)")
lines(runmin (x,k), col=col[2])
lines(runmed (x,k), col=col[3])
lines(runmean(x,k), col=col[4])
lines(runmax (x,k), col=col[5])
legend(0,.9*n, c("data", "runmin", "runmed", "runmean", "runmax"), col=col, lty=1 )
# sum vs. sum.exact
x = c(1, 1e20, 1e40, -1e40, -1e20, -1)
a = sum(x); print(a)
b = sum.exact(x); print(b)
}
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