min_detect {WaverideR}R Documentation

Detect and filter out all minima in a signal

Description

The min_detect function is used to detect and filter out local minima in a sinusoidal signal

Usage

min_detect(data = NULL, pts = 3)

Arguments

data

Matrix or data frame with first column being depth or time and the second column being a proxy

pts

the pts parameter specifies how many points to the left/right up/down the peak detect algorithm goes in detecting a peak. The peak detecting algorithm works by comparing the values left/right up/down of it, if the values are both higher or lower then the value a peak. To deal with error produced by this algorithm the pts parameter can be changed which can aid in peak detection. Usually increasing the pts parameter means more peak certainty, however it also means that minor peaks might not be picked up by the algorithm Default=3

Value

#Returns a matrix with 2 columns first column is depth/time the second column are local minima values

Examples

#Example in which the ~210yr de Vries cycle is extracted from the Total Solar
#Irradiance data set of Steinhilber et al., (2012)
#after which all minima are extracted

TSI_wt <-
analyze_wavelet(
data = TSI,
dj = 1/200,
lowerPeriod = 16,
upperPeriod = 8192,
   verbose = FALSE,
   omega_nr = 6
 )

de_Vries_cycle <- extract_signal_stable(wavelet=TSI_wt,
cycle=210,
period_up =1.25,
period_down = 0.75,
add_mean=TRUE,
plot_residual=FALSE)


min_de_Vries_cycle <- min_detect(de_Vries_cycle)


[Package WaverideR version 0.3.2 Index]