`sample_from_binormal_circle()` samples outside uncertainty circle

[wlangera]

p_norm argument does not work properly.

# Load packages
library(gcube)     # simulate biodiversity data cubes
library(sf)        # work with spatial objects
library(tidyverse) # data wrangling and visualisation

# Lets create a random point with 25 meter coordinate uncertainty.
# We sample 1000 times using normal randomisation
point_df <- tibble(
  x = 200,
  y = 500,
  time_point = 1,
  coordinateUncertaintyInMeters = 25) %>%
  st_as_sf(coords = c("x", "y"))

n_sim <- 1000

# Take 1000 samples with normal randomisation
list_samples_normal <- vector("list", length = n_sim)
for (i in seq_len(n_sim)) {
  sampled_point_normal <- sample_from_binormal_circle(point_df, p_norm = 0.95)
  sampled_point_normal$sim <- i
  list_samples_normal[[i]] <- sampled_point_normal
}
samples_normal_df <- do.call(rbind.data.frame, list_samples_normal)

# Visualise the samples
coordinates_normal_df <- data.frame(st_coordinates(samples_normal_df))
coordinates_point_df <- data.frame(st_coordinates(point_df))

ggplot() +
  geom_point(data = coordinates_normal_df,
             aes(x = X, y = Y),
             colour = "cornflowerblue") +
  geom_segment(data = coordinates_point_df,
               aes(x = X, xend = X + 25,
                   y = Y, yend = Y),
               linewidth = 1.5, colour = "darkgreen") +
  geom_label(aes(y = 503, x = 212.5, label = "25 m"), colour = "black",
             size = 5) +
  stat_ellipse(data = coordinates_normal_df,
               aes(x = X, y = Y), level = 0.975, linewidth = 1.5, color = "firebrick") +
  geom_point(data = coordinates_point_df,
             aes(x = X, y = Y),
             color = "firebrick", size = 2) +
  coord_fixed() +
  theme_minimal()

[wlangera]

or only adjust documentation?