Visualize CLOSURE data in an ECDF plot — closure_plot

Call closure_plot_ecdf() to visualize CLOSURE results using the data's empirical cumulative distribution function (ECDF).

A diagonal reference line benchmarks the ECDF against a hypothetical linear relationship.

See closure_plot_bar() for more intuitive visuals.

Usage

closure_plot_ecdf(
  data,
  samples = c("mean", "all"),
  line_color = "#5D3FD3",
  text_size = 12,
  reference_line_alpha = 0.6,
  pad = TRUE
)

Arguments

data: List returned by closure_generate().
samples: String (length 1). How to aggregate the samples? Either draw a single ECDF line for the average sample ("mean", the default); or draw a separate line for each sample ("all"). Note: the latter option can be very slow if many values were found.
line_color: String (length 1). Color of the ECDF line. Default is "#5D3FD3", a purple color.
text_size: Numeric. Base font size in pt. Default is 12.
reference_line_alpha: Numeric (length 1). Opacity of the diagonal reference line. Default is 0.6.
pad: Logical (length 1). Should the ECDF line be padded on the x-axis so that it stretches beyond the data points? Default is TRUE.

Value

A ggplot object.

Details

The present function was inspired by rsprite2::plot_distributions(). However, plot_distributions() shows multiple lines because it is based on SPRITE, which draws random samples of possible datasets. CLOSURE is exhaustive, so closure_plot_ecdf() shows all possible datasets in a single line by default.

Examples

# Create CLOSURE data first:
data <- closure_generate(
  mean = "3.5",
  sd = "2",
  n = 52,
  scale_min = 1,
  scale_max = 5
)

# Visualize:
closure_plot_ecdf(data)