Perform Fourier Analysis to a Time Series in R

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情书的邮戳
情书的邮戳 2021-02-01 11:47

I would like to perform fourier transform to a time series using R. I would like to:

  1. Get the sum of the 5th to 18th harmonics
  2. plot each wave
  3. and
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  • 2021-02-01 12:03

    A much easier solution is to use the Fast Fourier Transform (fft)

    dat   <- read.csv("Baguio.csv", header=FALSE)
    y     <- dat$V1
    t     <- 1:73
    rg    <- diff(range(y))
    
    nff = function(x = NULL, n = NULL, up = 10L, plot = TRUE, add = FALSE, main = NULL, ...){
      #The direct transformation
      #The first frequency is DC, the rest are duplicated
      dff = fft(x)
      #The time
      t = seq(from = 1, to = length(x))
      #Upsampled time
      nt = seq(from = 1, to = length(x)+1-1/up, by = 1/up)
      #New spectrum
      ndff = array(data = 0, dim = c(length(nt), 1L))
      ndff[1] = dff[1] #Always, it's the DC component
      if(n != 0){
        ndff[2:(n+1)] = dff[2:(n+1)] #The positive frequencies always come first
        #The negative ones are trickier
        ndff[length(ndff):(length(ndff) - n + 1)] = dff[length(x):(length(x) - n + 1)]
      }
      #The inverses
      indff = fft(ndff/73, inverse = TRUE)
      idff = fft(dff/73, inverse = TRUE)
      if(plot){
        if(!add){
          plot(x = t, y = x, pch = 16L, xlab = "Time", ylab = "Measurement",
            main = ifelse(is.null(main), paste(n, "harmonics"), main))
          lines(y = Mod(idff), x = t, col = adjustcolor(1L, alpha = 0.5))
        }
        lines(y = Mod(indff), x = nt, ...)
      }
      ret = data.frame(time = nt, y = Mod(indff))
      return(ret)
    }
    

    Then we need to call res, passing the timeseries as x, the number of harmonics as n and the upsampling (so we plot points in time beside the original ones) as up.

    png("res_18.png")
    res = nff(x = y, n = 18L, up = 100L, col = 2L)
    dev.off()
    


    To get the sum of the 5th to the 18th harmonics it's simply a difference between series

    sum5to18 = nff(x = y, n = 18L, up = 10L, plot = FALSE)
    sum5to18$y = sum5to18$y - nff(x = y, n = 4L, up = 10L, plot = FALSE)$y
    png("sum5to18.png")
    plot(sum5to18, pch = 16L, xlab = "Time", ylab = "Measurement", main = "5th to 18th harmonics sum", type = "l", col = 2)
    dev.off()
    


    Adding the arguments add and col allow us to plot multiple waves as well, with specific colors

    colors = rainbow(36L, alpha = 0.3)
    nff(x = y, n = 36L, up = 100L, col = colors[1])
    png("all_waves.png")
    for(i in 1:18){
      ad = ifelse(i == 1, FALSE, TRUE)
      nff(x = y, n = i, up = 100L, col = colors[i], add = ad, main = "All waves up to 18th harmonic")
    }
    dev.off()
    


    Is there a way so extract the data of each series then save as a csv file. So in this example, I should have 18 csv files for the 18 waves.

    I edited the code to allow a 0 harmonic (basically a mean), so now you extract the separate waves as:

    sep = array(data = NA_real_, dim = c(7300L, 2 + 18), dimnames = list(NULL, c("t", paste0("H", 0:18))))
    sep[,1:2] = as.matrix(nff(x = y, n = 0, up = 100L, plot = FALSE))
    
    for(i in 1:18L){
      sep[,i+2] = nff(x = y, n = i, up = 100L, plot = FALSE)$y - nff(x = y, n = i-1, up = 100L, plot = FALSE)$y
    } 
    

    Then you can use write.table to write a csv file.

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