Given a time series vector, create a PSD and find the dominant frequency

The range to look for a dominant frequency (frequency corresponding to max PSD value) should be specified for this function. This function uses the MakePowerSpectralDensity() function and the IdentifyMaxOnXY() function together. If multiple equal maxima are found, then IdentifyMaxOnXY() will display a message.

PSDIdentifyDominantFrequency(
  sampling_frequency,
  data_vector,
  x_start = 0,
  x_end,
  x_increment
)

Arguments

sampling_frequency	Numeric value specifying sampling frequency in hertz. If data is sampled once every second, then sampling frequency is 1 Hz. If data is sampled once every 2 seconds, then sampling frequency is 0.5 Hz.
data_vector	Vector of numeric values. Timeseries vector of data.
x_start	Numeric value specifying start of x value to look at.
x_end	Numeric value specifying end of x value to look at.
x_increment	Numeric value specifying the increment of the x-values to use.

Value

A vector with two elements, The first element is the x value (frequency) where the max y value (PSD value) is found. The second element is the max y value.

Examples

#Create a vector of time that represent times where data are sampled.
Fs = 100; #sampling frequency in Hz
T = 1/Fs; #sampling period
L = 1000; #length of time vector
t = (0:(L-1))*T; #time vector

#First signal
#1. 1 Hz with amplitude of 2
S1 <- 2*sin(2*pi*1*t)
level1.vals <- rep("a", length(S1))
level2.vals <- rep("1", length(S1))
S1.data.frame <- as.data.frame(cbind(t, S1, level1.vals, level2.vals))
colnames(S1.data.frame) <- c("Time", "Signal", "level1.ID", "level2.ID")
S1.data.frame[,"Signal"] <- as.numeric(S1.data.frame[,"Signal"])


results <- PSDIdentifyDominantFrequency(Fs, S1.data.frame[,"Signal"], 0, 10, 0.01)