fftab

The goal of fftab is to make working with fft’s in R easier and more consistent. It follows the tidy philosophy by working with tabular data rather than lists, vectors, and so on. Typical signal processing operations can thus often be accomplished in a single dplyr::mutate call or by a call to similar functions. Some examples are shown here.

Related work

• The fftpipe package takes a approach similar to that of fftab.
• The healthyR.ts package includes a tidy_fft function.

Installation

You can install the development version of fftab from GitHub with:

# install.packages("pak")
pak::pak("thk686/fftab")

Example

Using fftab with ggplot.

fftab(sunspot.month, norm = TRUE) |>
  to_rect(.keep = "all") |>
  to_polr(.keep = "all") |>
  print(n = 5) ->
ssm.fft
#> # A tibble: 3,177 × 6
#>    .dim_1 fx              re     im   mod    arg
#>     <dbl> <cpl>        <dbl>  <dbl> <dbl>  <dbl>
#> 1 0       51.96+0.00i 52.0    0     52.0   0    
#> 2 0.00378  4.37+4.99i  4.37   4.99   6.63  0.852
#> 3 0.00755 -0.86+5.08i -0.860  5.08   5.15  1.74 
#> 4 0.0113  -2.65-5.70i -2.65  -5.70   6.29 -2.01 
#> 5 0.0151  -4.64-0.59i -4.64  -0.586  4.68 -3.02 
#> # ℹ 3,172 more rows

ggplot(fortify(sunspot.month)) +
  geom_line(aes(x = Index, y = Data)) +
  ylab("Sunspot count") +
  xlab("Year") +
  theme_bw() ->
p1

xlocs <- c(1, 0.1, 0.01)
xlabs <- c("1", "10", "100")

ssm.fft |>
  dplyr::filter(.dim_1 > 0) |>
  ggplot() +
  geom_point(aes(x = .dim_1, y = mod)) +
  geom_smooth(aes(x = .dim_1, y = mod)) +
  scale_y_continuous(trans = "log", labels = function(y) signif(y, 1)) +
  scale_x_continuous(trans = "log", breaks = xlocs, labels = xlabs) +
  xlab("Cycle duration (years)") +
  ylab("Mean amplitude") +
  theme_bw() ->
p2

print(p1 / p2)