Bank a Plot's Own Data at Every Scale

A convenience wrapper around bank_slopes_multiscale that extracts y directly from an already-specified ggplot and returns one copy of the plot per scale of interest, each with the appropriate coord_fixed applied. The result is the small-multiples display used throughout Heer and Agrawala (2006): the same data, banked to reveal trends at different frequencies.

Usage

bank_plot_multiscale(
  plot,
  method = c("ms", "as", "ao", "was"),
  cull = TRUE,
  layer = 1,
  ...
)

Arguments

plot: A ggplot object.
method, cull, ...: Passed to bank_slopes_multiscale.
layer: Integer. Which layer of plot to extract y from. Defaults to the first layer.

Value

A named list of ggplot objects, one per retained scale, in ascending order of frequency and named by frequency index.

Details

Multi-scale banking is defined on the frequency domain of a single series sampled on a regular grid, so unlike bank_plot this function requires the chosen layer to hold exactly one series with evenly spaced x values.

References

Heer, Jeffrey and Maneesh Agrawala, 2006. "Multi-Scale Banking to 45." IEEE Transactions On Visualization And Computer Graphics 12(5).

Examples

library("ggplot2")

y <- as.numeric(sunspot.year)
p <- ggplot(data.frame(x = seq_along(y), y = y), aes(x = x, y = y)) +
  geom_line()

# One plot per scale of interest, named by frequency index.
plots <- bank_plot_multiscale(p)
names(plots)
#> [1] "7"  "31"

## Low-frequency trend across sunspot cycles
plots[[1]]


## The individual 11-year cycles
plots[[2]]