Simulates bivariate point process data

Simulates a spatial point pattern with three cell types: background, immune1, and immune2.

Usage

sim_pp_data_biv(
  lambda_n,
  abundance,
  markvar1 = "immune1",
  markvar2 = "immune2",
  markvar3 = "background",
  distribution = "hom",
  clust = FALSE
)

Arguments

lambda_n

Number of total cells in image

abundance

Percentage intensity for marker positive cells

markvar1

Marker positive cell type (default is "immune1")

markvar2

Marker positive cell type (default is "immune2")

markvar3

Marker negative cell type (default is "background")

distribution

Determines whether the image is homogeneous ("hom") or inhomogeneous ("inhom")

clust

Determines whether an image is simulated with or without clustering (TRUE/FALSE)

Value

A point pattern object of class "ppp" from the spatstat package where the three cell types are background, immune1, and immune2.

Details

Simulates bivariate point process data

Examples

if (requireNamespace("dplyr", quietly = TRUE) &&
   requireNamespace("ggplot2", quietly = TRUE) &&
   requireNamespace("tibble", quietly = TRUE) &&
   requireNamespace("magrittr", quietly = TRUE)) {
  pp_obj <- sim_pp_data_biv(lambda_n = 200, abundance = 0.3)
  magrittr::`%>%`(
  tibble::as_tibble(pp_obj),
  ggplot2::ggplot(ggplot2::aes(x, y, color = marks))
  ) +
  ggplot2::geom_point()
}