Summarize the distribution of number of offspring and number of mates

More later

summarize_offspring_and_mate_numbers(
  census_postkill,
  pedigree,
  deaths,
  lifetime_hexbin_width = c(1, 1),
  contrib_bin_width = 0.01
)

Arguments

census_postkill

a tibble with the postkill numbers of individuals. This is here so we know the total number of individuals that could have reproduced in a given year.

pedigree

a tibble with columns of year, kid, pa, and ma. The IDs of the' individuals must by like MX_Y where M means male, X is the birth year, and Y is the unique ID number.

deaths

a tibble with columns of ID, year, and age, giving the years and ages at which different individuals died.

lifetime_hexbin_width

a vector of length two. The first element is the width in the age direction of each hexbin and the second is the width in the lifetime number of offspring direction for the plot_lifetime_output_vs_age_at_death output plot.

contrib_bin_width

width of bins of histogram of contribution of parents of each age and sex to the offspring.

Value

A list with three components, each of them a ggplot object:

• plot_age_specific_number_of_offspring: a ggplot object that plots boxplots and jittered points. The x-axis are the ages of the individuals; the y-axis shows the number of offspring. Summarized over the entire spip simulation. This is faceted by sex.

• plot_lifetime_output_vs_age_at_death: a ggplot object. This is a hexbin plot. The x-axis are age-at-death bins, the y axis are bins of total number of offspring produced in a lifetime. The fill color of each bin gives the number of individuals with that age at death and number of offspring encountered over the whole simulation. Plot is faceted by sex.

• plot_fraction_of_offspring_from_each_age_class: a ggplot object. This shows the distribution over all years of the simulation, of the fraction of offspring produced each year that were produced by males or females of a given age (the plots are facet-wrapped by both age and sex). The blue vertical line gives the mean.

Examples

# get stored slurped output for an example
X <- species_1_slurped_results
g <- summarize_offspring_and_mate_numbers(
  X$census_postkill,
  X$pedigree,
  X$deaths
)

# Now g is a list holding three plots, accessible like this:

# g$plot_age_specific_number_of_offspring

# g$plot_lifetime_output_vs_age_at_death

# g$plot_fraction_of_offspring_from_each_age_class