plot_ages | R Documentation |
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,
french = FALSE,
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
)
dat |
Input data frame. Should be from |
max_size |
Maximum dot size (passed to |
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 |
french |
Logical for French or English. |
line_col |
A named character vector of colors for male and females. |
survey_cols |
If not |
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
|
count_label_size |
The size of the total count labels along the top.
Passed to |
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).
## Not run:
pop_samples %>%
tidy_ages_raw(survey = "SYN QCS") %>%
plot_ages()
# main age/length data:
rs_comm_samples <- gfdata::get_commercial_samples("redstripe rockfish")
rs_survey_samples <- gfdata::get_survey_samples("redstripe rockfish")
#
# for weighting:
rs_catch <- gfdata::get_catch("redstripe rockfish")
rs_survey_sets <- gfdata::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()
## End(Not run)
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