readSpectra: Read in Power Spectra and Auxiliary Information

In gslcca: Generalized Semi-Linear Canonical Correlation Analysis

Description

Read in a tab-delimited text file containing power spectra and auxiliary information, i.e. subject, treatment and time variables.

Usage

readSpectra(file, info = 1:3, 
    treatment = c("Control", "Low Dose", "Middle Dose", "High Dose"), 
    resolution = 1, end = 42900, nfreq = 36, ...)

Arguments

file	The name of the file.
info	Numeric indices of columns containing auxiliary information - the remaining columns are assumed to contain the power spectra.
treatment	A vector of levels for the treatment variable, assumed to be named "treatment" (case insensitive) - ignored if no such variable is found.
resolution	The desired resolution of frequencies, in Hz. Data read in at a higher resolution is aggregated.
end	The last time point to be included in the result - observations at further time points are dropped from the data.
nfreq	The number of frequencies to be included in the result (after any aggregation specified by resolution), i.e. the number of columns in the returned matrix of spectra.
...	Further arguments passed to read.delim

Details

Information variables that are read as character vectors are converted to factors, using the levels passed to the treatment argument for the treatment variable (if found). Note these levels must match the original values of the treatment variable, this argument simply specifies the ordering of the levels.

Value

A data frame containing the information variables with their original names and the matrix of spectra, named "spectra".

Author(s)

Heather Turner

See Also

gslcca, bandSpectra

Examples

## Not run: 
## Read data in from tab-delimited text file
DATA <- readSpectra("Compound1.txt", info = 1:3, 
    treatment = c("Control", "Low Dose", "Middle Dose", "High Dose"),
    resolution = 1, end = 42900, nfreq = 36)

## Use result directly in call to gslcca
result <- gslcca(spectra,  "Double Exponential",
                 time=Time, subject = Rat, 
                 treatment = Treatment, data = DATA,
                 separate = FALSE, global = FALSE,
                 subject.smooth = TRUE, pct.explained = 0.96)

## End(Not run)

gslcca documentation built on May 2, 2019, 5:46 p.m.