Description Usage Arguments Details Value Note Author(s) Examples
Generates profile (binned) data in a given range from an indexed pair of vectors.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | profBin(x, y, num, xstart = min(x), xend = max(x), param = list())
profBinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE,
param = list())
profBinLin(x, y, num, xstart = min(x), xend = max(x), param = list())
profBinLinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE,
param = list())
profBinLinBase(x, y, num, xstart = min(x), xend = max(x), param = list())
profBinLinBaseM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE,
param = list())
profIntLin(x, y, num, xstart = min(x), xend = max(x), param = list())
profIntLinM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE,
param = list())
profMaxIdx(x, y, num, xstart = min(x), xend = max(x), param = list())
profMaxIdxM(x, y, zidx, num, xstart = min(x), xend = max(x), NAOK = FALSE,
param = list())
|
x |
numeric vector of value positions |
y |
numeric vector of values to bin |
zidx |
starting position of each new segment |
num |
number of equally spaced x bins |
xstart |
starting x value |
xend |
ending x value |
NAOK |
allow NA values (faster) |
param |
parameters for profile generation |
These functions take a vector of unequally spaced y
values
and transform them into either a vector or matrix, depending on
whether there is an index or not. Each point in the vector or
matrix represents the data for the point centered at its corresponding
x
value, plus or minus half the x
step size
(xend-xstart/(num-1)
).
The Bin
functions set each matrix or vector value to the
maximal point that gets binned into it.
The BinLin
functions do the same except that they linearly
interpolate values into which nothing was binned.
The BinLinBase
functions do the same except that they populate
empty parts of spectra with a base value. They take to two parameters:
1) baselevel
, the intensity level to fill in for empty parts
of the spectra. It defaluts to half of the minimum intensity. 2)
basespace
, the m/z length after which the signal will drop to
the base level. Linear interpolation will be used between consecuitive
data points falling within 2*basespace
of eachother. It defaluts
to 0.075.
The IntLin
functions set each matrix or vector value to
the integral of the linearly interpolated data from plus to minus
half the step size.
The MaxIdx
functions work similarly to the Bin
functions execpt that the return the integer index of which x,y
pair would be placed in a particular cell.
For prof*
, a numeric vector of length num
.
For prof*M
, a matrix with dimensions num
by
length(zidx)
.
For MaxIdx
, the data type is integer, for all others it
is double.
There are some issues with the profBinLin
method, see
https://github.com/sneumann/xcms/issues/46 and
https://github.com/sneumann/xcms/issues/49. Thus it is suggested
to use the functions binYonX
in combination with
imputeLinInterpol
instead.
Colin A. Smith, csmith@scripps.edu
1 2 3 4 5 6 7 8 9 10 11 12 | ## Not run:
library(faahKO)
cdfpath <- system.file("cdf", package = "faahKO")
cdffiles <- list.files(cdfpath, recursive = TRUE, full.names = TRUE)
xraw <- xcmsRaw(cdffiles[1])
image(xraw) ## not how with intLin the intensity's blur
profMethod(xraw) <- "bin"
image(xraw) ## now with 'bin' there is no blurring good for centroid data
##try binlinbase for profile data
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.