README

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.

Installation

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

Example

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)