Plot age frequency data

Functions for plotting age frequency data.

plot_ages(dat, max_size = 5, sex_gap = 0.2, year_increment = 2,
  ylab = "Age (years)", year_range = NULL, line_col = c(M =
  "#666666", F = "#f44256"), survey_cols = NULL, alpha = 0.2,
  grid_col = "grey95", diagonal_lines = seq(-2100, -1850, 10),
  count_label_size = 2.25)

Arguments

dat	Input data frame. Should be from tidy_ages_raw() or tidy_ages_weighted() or be formatted similarly. See details.
max_size	Maximum dot size (passed to ggplot2::scale_size_area()).
sex_gap	Horizontal gap between male and female bubbles.
year_increment	Increment between year labels on x axis.
ylab	Y axis label.
year_range	If not NULL, a the range of years to plot. Defaults to all years included in original data.
line_col	A named character vector of colors for male and females.
survey_cols	If not NULL, a named character vector for different colors for the various surveys.
alpha	Transparency for the fill color.
grid_col	Colour for the gridlines.
diagonal_lines	A numeric a vector of years to start diagonal lines at to help trace cohorts. Note that these are passed to ggplot2::geom_abline() as intercepts.
count_label_size	The size of the total count labels along the top. Passed to ggplot2::geom_text().

Details

• tidy_ages_raw() or tidy_ages_weighted() prepare PBS data for plot_ages(). These work across one or multiple species.

• plot_ages() Plots age frequencies for each year for selected surveys for a single species. Input data frame should come from tidy_ages_raw() or tidy_ages_weighted() or follow the following format: The input data frame must have the columns (in any order): survey, year, sex (coded as "M" and "F"), age, proportion, total (for the total sample number label).

Examples

# NOT RUN {
pop_samples %>%
  tidy_ages_raw(survey = "SYN QCS") %>%
  plot_ages()

# main age/length data:
rs_comm_samples <- get_commercial_samples("redstripe rockfish")
rs_survey_samples <- get_survey_samples("redstripe rockfish")
#
# for weighting:
rs_catch <- get_catch("redstripe rockfish")
rs_survey_sets <- get_survey_sets("redstripe rockfish")

# survey raw age frequencies:
tidy_ages_raw(rs_survey_samples,
  sample_type = "survey") %>%
  plot_ages()

# survey weighted age frequencies:
tidy_ages_weighted(rs_survey_samples,
  sample_type = "survey",
  dat_survey_sets = rs_survey_sets) %>%
  plot_ages()

# commercial raw age frequencies:
tidy_ages_raw(rs_comm_samples,
  sample_type = "commercial") %>%
  plot_ages()
# }