Detect and filter out all minima in a signal

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

Signal in which the local extremes are detected: a two-column matrix or data frame with depth or time in column 1 (in increasing order) and the proxy value in column 2. Required (Default=NULL).

pts

Number of points to each side that a point is compared with (integer, >= 2): a point is a local minimum when it is above (maximum) or below (minimum) the value pts points further on and the value pts - 1 points back. Of consecutive extremes of the same type only the most extreme one is kept. Larger values give more robust extremes but may miss minor ones. 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 <-
analyse_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)