Title: | Calculate the Periodogram of a Time-Course |
---|---|
Description: | Provides a consistent interface to use various methods to calculate the periodogram and estimate the period of a rhythmic time-course. Methods include Lomb-Scargle, fast Fourier transform, and three versions of the chi-square periodogram. See Tackenberg and Hughey (2021) <doi:10.1371/journal.pcbi.1008567>. |
Authors: | Jake Hughey [aut, cre], Michael Tackenberg [aut], Josh Schoenbachler [ctb] |
Maintainer: | Jake Hughey <[email protected]> |
License: | GPL-2 |
Version: | 1.0.2 |
Built: | 2024-11-20 03:20:05 UTC |
Source: | https://github.com/hugheylab/spectr |
Calculate periodogram for a time-course using Lomb-Scargle, fast Fourier
transform, or selected version of chi-square. The spectr
function is a
wrapper for the various methods. lspgram
is in turn a wrapper for
lomb::lsp()
, and fftpgram
a wrapper for stats::spec.pgram()
. Among the
versions of chi-square, it is highly recommended to use greedy, which has
lower bias than standard and lower variance than conservative.
cspgram( x, deltat, periodRange = c(18, 32), method = c("greedy", "conservative", "standard"), na.action = stats::na.fail, dopar = FALSE ) fftpgram( x, deltat, periodRange = c(18, 32), pad = 50, na.action = stats::na.fail, ... ) lspgram(x, deltat, time, periodRange = c(18, 32), ofac = 50) spectr( x, deltat, time, periodRange = c(18, 32), method = c("greedy_chisq", "conservative_chisq", "standard_chisq", "lombscargle", "fft"), ofac = 50, pad = 50, na.action = stats::na.fail, dopar = FALSE, ... )
cspgram( x, deltat, periodRange = c(18, 32), method = c("greedy", "conservative", "standard"), na.action = stats::na.fail, dopar = FALSE ) fftpgram( x, deltat, periodRange = c(18, 32), pad = 50, na.action = stats::na.fail, ... ) lspgram(x, deltat, time, periodRange = c(18, 32), ofac = 50) spectr( x, deltat, time, periodRange = c(18, 32), method = c("greedy_chisq", "conservative_chisq", "standard_chisq", "lombscargle", "fft"), ofac = 50, pad = 50, na.action = stats::na.fail, dopar = FALSE, ... )
x |
Numeric vector of measurements. |
deltat |
Numeric value of the interval between time-points. |
periodRange |
Numeric vector of the minimum and maximum values of the
period to consider, in the same units as |
method |
Character indicating which method to use. Can be an unambiguous substring of the full name. |
na.action |
Function specifying how to handle |
dopar |
Logical indicating whether to run calculations in parallel if
a parallel backend is already set up, e.g., using
|
pad |
Numeric value of the proportion of the length of |
... |
Other arguments passed to |
time |
Numeric vector of time-points. Can be specified instead of
|
ofac |
Integer value of the oversampling factor. Must be >= 1. Only used for Lomb-Scargle. |
A data.table
with various columns depending on the method. For any
version of chi-square, columns will be period
, chisq
, df
, and
log_pval
. The log p-value is more reliable than the p-value, since R has
finite precision, so p-values less than about 5e-324 would be set to 0. For
Lomb-Scargle and FFT, columns will be period
and power
.
library('data.table') set.seed(1789) deltat = 0.1 tau = 25 tt = seq(0, 24 * 3, deltat) x = 3 * sin(tt / tau * 2 * pi) + rnorm(length(tt)) specCsp = spectr(x, deltat, method = 'greedy') peakCsp = specCsp[which.min(log_pval)] specLsp = spectr(x, deltat, method = 'lomb') peakLsp = specLsp[which.max(power)] specFft = spectr(x, deltat, method = 'fft') peakFft = specFft[which.max(power)]
library('data.table') set.seed(1789) deltat = 0.1 tau = 25 tt = seq(0, 24 * 3, deltat) x = 3 * sin(tt / tau * 2 * pi) + rnorm(length(tt)) specCsp = spectr(x, deltat, method = 'greedy') peakCsp = specCsp[which.min(log_pval)] specLsp = spectr(x, deltat, method = 'lomb') peakLsp = specLsp[which.max(power)] specFft = spectr(x, deltat, method = 'fft') peakFft = specFft[which.max(power)]