filter_highfreq_noise: Filter high frequency noise by Gaussian filter

In fluxfixer: Advanced Framework for Sap Flow Data Post-Process

Filter high frequency noise by Gaussian filter

Description

'filter_highfreq_noise()' filters a time series with a specific period by convolving it with a Gaussian window, removing high-frequency noise.

Usage

filter_highfreq_noise(
  vctr_time,
  vctr_target,
  vctr_time_noise,
  wndw_size_noise = 13,
  inv_sigma_noise = 0.01,
  label_err = -9999
)

Arguments

vctr_time	A timestamp vector of class POSIXct or POSIXlt. The timestamps must be equally spaced and arranged chronologically.
vctr_target	A vector of a targeted time series to be checked. The length of the time series must be the same as that of 'vctr_time'.
vctr_time_noise	A timestamp vector of class POSIXct or POSIXlt, indicating when high-frequency noise exists in the targeted time series.
wndw_size_noise	A positive integer indicating the number of data points included in a moving Gaussian window for the high-frequency noise filtering. The default is 13, meaning that the window size is 6.5 hours if the time interval of the input timestamp is 30 minutes.
inv_sigma_noise	A positive value defining a Gaussian window width for the high-frequency noise filtering. The width of the Gaussian window is inversely proportional to this parameter. Default is 0.01.
label_err	A numeric value representing a missing value in the input vector(s). Default is -9999.

Value

A vector of the noise-filtered time series. The length of the time series is the same as the input time series.

Author(s)

Yoshiaki Hata

Examples

## Create data
time <- seq(as.POSIXct("2026/01/01"), length.out = 360, by = "1 day")
x <- seq(1, 360)
target <- sin(x / 180 * pi) + stats::rnorm(length(x), sd = 0.2)
time_noise <-
  seq(as.POSIXct("2026/01/01"), as.POSIXct("2026/09/01"), by = "1 day")

## Filter noise
result <-
  filter_highfreq_noise(vctr_time = time, vctr_target = target,
                        vctr_time_noise = time_noise)

fluxfixer documentation built on April 11, 2026, 5:06 p.m.