Interactive Angular Accumulation Plot (plotly hover tooltips)

Builds the same turtle-graphics bouquet as make_plot_bouquet() and converts it to an interactive plotly figure. Hovering over any point on a path shows the series name, date/time, step number, and value.

Usage

make_plot_bouquet_interactive(
  data,
  time_col = 1,
  series_col = 2,
  value_col = 3,
  stem_colors = "#3a7d2c",
  flower_colors = "#f472b6",
  ceiling_pct = 0.8,
  launch_deg = 90,
  dark_mode = FALSE,
  title = NULL,
  from = NULL,
  to = NULL,
  normalise = FALSE,
  verbose = FALSE
)

Arguments

data

A long-format data frame – same format as make_plot_bouquet().

time_col

<tidy-select> Time column. Default: first column.

series_col

<tidy-select> Series identifier column. Default: second column.

value_col

<tidy-select> Numeric value column. Default: third column.

stem_colors

Single hex string or a named character vector (one hex per series name). Default "#3a7d2c".

flower_colors

Single hex string or a named character vector for the end-of-series markers. Default "#f472b6".

ceiling_pct

Fraction of maximum angle. Default 0.80.

launch_deg

Launch heading in degrees. Default 90.

dark_mode

Logical. Default FALSE.

title

Plot title string. Default NULL.

from

Optional time lower bound for filtering. Default NULL.

to

Optional time upper bound for filtering. Default NULL.

normalise

Logical. Per-series angle normalisation. Default FALSE.

verbose

Logical. Print angle diagnostics. Default FALSE.

Value

A plotly htmlwidget object.

Details

This function requires the plotly package.

See also

make_plot_bouquet() for the static ggplot2 version with full styling options. save_bouquet() to export the static version to a file. cluster_bouquet() to colour-code series by directional cluster before plotting.

Examples

# \donttest{
if (requireNamespace("plotly", quietly = TRUE)) {
set.seed(42)
n   <- 52L
gw  <- tibble::tibble(
  week    = rep(seq(as.Date("2023-01-01"), by = "week", length.out = n), 3L),
  station = rep(c("A", "B", "C"), each = n),
  level   = c(cumsum(rnorm(n)), cumsum(rnorm(n)), cumsum(rnorm(n)))
)
make_plot_bouquet_interactive(gw, "week", "station", "level")
}

# }