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GOA_gear_performance.qmd
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---
format: docx
editor: visual
---
```{r setup}
#| include: false
library(trawlmetrics)
library(flextable)
trawlmetrics_data <- get_trawlmetrics(survey = c("GOA"),
year = 2023,
select_haul_types = c(3, 13, 20),
save_rds = FALSE)
```
```{r}
#| include: false
png(file = here::here("plots", "trawl_height_width.png"), width = 7, height = 9, res = 600, units = "in")
print(
cowplot::plot_grid(
ggplot() +
geom_segment(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
yend = NET_NUMBER,
x = MIN_NET_HEIGHT,
xend = MAX_NET_HEIGHT,
color = MEAN_NET_HEIGHT > H25 & MEAN_NET_HEIGHT < H75)) +
geom_segment(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
yend = NET_NUMBER,
x = Q25_NET_HEIGHT,
xend = Q75_NET_HEIGHT,
color = MEAN_NET_HEIGHT > H25 & MEAN_NET_HEIGHT < H75),
size = 3) +
geom_point(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
x = MEAN_NET_HEIGHT,
color = MEAN_NET_HEIGHT > H25 & MEAN_NET_HEIGHT < H75),
size = 4,
shape = 21,
fill = "white") +
geom_label(data = trawlmetrics_data[['plot_data']],
aes(y = NET_NUMBER,
x = 0.8,
color = MEAN_NET_HEIGHT > H25 & MEAN_NET_HEIGHT < H75,
label = N_HAULS)) +
scale_y_discrete(name = "Net Number") +
scale_x_continuous(name = "Net Height (m)", expand = c(0.05, 0.1)) +
scale_color_manual(name = "Mean within 25-75% range?",
values = c("red", "darkgreen"),
labels = c("No", "Yes")) +
trawlmetrics::theme_pngs() +
theme(legend.position = "none"),
ggplot() +
geom_segment(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
yend = NET_NUMBER,
x = MIN_NET_WIDTH,
xend = MAX_NET_WIDTH,
color = MEAN_NET_WIDTH > W25 & MEAN_NET_WIDTH < W75)) +
geom_segment(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
yend = NET_NUMBER,
x = Q25_NET_WIDTH,
xend = Q75_NET_WIDTH,
color = MEAN_NET_WIDTH > W25 & MEAN_NET_WIDTH < W75),
size = 3) +
geom_point(data = trawlmetrics_data[['plot_data']],
mapping = aes(y = NET_NUMBER,
x = MEAN_NET_WIDTH,
color = MEAN_NET_WIDTH > W25 & MEAN_NET_WIDTH < W75),
size = 4,
shape = 21,
fill = "white") +
geom_label(data = trawlmetrics_data[['plot_data']],
aes(y = NET_NUMBER,
x = 10,
color = MEAN_NET_WIDTH > W25 & MEAN_NET_WIDTH < W75,
label = N_HAULS)) +
scale_y_discrete(name = "Net Number") +
scale_x_continuous(name = "Net Width (m)", expand = c(0.05, 0.1)) +
scale_color_manual(name = "Mean within 25-75% range?",
values = c("red", "darkgreen"),
labels = c("No", "Yes")) +
trawlmetrics::theme_pngs() +
theme(legend.position = "none"),
nrow = 2)
)
dev.off()
```
[](%60r%20paste0(%22Trawl%20height%20and%20width%20from%20the%20%22,%20year,%20%22%20%22,%20paste(survey,%20sep%20=%20%22%20and%20%22),%20%22survey(s).%22)%20%60)
```{r setup_tables}
#| include: false
cat("{{< pagebreak >}}")
unique_trawls <- trawlmetrics_data[['trawlmetrics_survey']] |>
dplyr::select(YEAR, VESSEL, NET_NUMBER) |>
dplyr::arrange(NET_NUMBER)
tab_net_metrics <- list()
tab_haul_history <- list()
for(ii in 1:nrow(unique_trawls)) {
sel_net <- dplyr::filter(trawlmetrics_data[['trawl_data']],
YEAR == unique_trawls$YEAR[ii],
VESSEL == unique_trawls$VESSEL[ii],
NET_NUMBER == unique_trawls$NET_NUMBER[ii])
sel_net_summary <- dplyr::filter(sel_net, NET_MEASURED == "Y")[1,] |>
dplyr::inner_join(trawlmetrics_data[['trawlmetrics_survey']])
tab_net_metrics[[ii]] <- data.frame(Field = c("Gear", "Net number", "Year", "Survey", "Vessel", "Good hauls", "Bad hauls", "Avg. Height", "Avg. Spread", "Out of range"),
Value = c(sel_net_summary$SHORT_NAME,
sel_net_summary$NET_NUMBER,
sel_net_summary$YEAR,
paste(trawlmetrics_data[['survey']], collapse =", "),
sel_net_summary$VESSEL,
sel_net_summary$N_GOOD,
sel_net_summary$N_BAD,
paste0(round(sel_net_summary$MEAN_NET_HEIGHT, 1), " m"),
paste0(round(sel_net_summary$MEAN_NET_WIDTH, 1), " m"),
NA)) |>
flextable::flextable(cwidth = c(2, 2)) |>
flextable::set_caption(caption = paste0("Net deployment summary for net number ", unique_trawls$NET_NUMBER[ii], " during ", trawlmetrics_data[['year']], " survey."))
tab_haul_history[[ii]] <- sel_net |>
dplyr::select(START_TIME, VESSEL, CRUISE, HAUL, PERFORMANCE_DESCRIPTION) |>
dplyr::arrange(CRUISE, HAUL) |>
dplyr::mutate(START_TIME = as.Date(START_TIME),
CRUISE = as.character(CRUISE)) |>
dplyr::rename(Date = START_TIME,
Vessel = VESSEL,
Cruise = CRUISE,
Haul = HAUL,
Performance = PERFORMANCE_DESCRIPTION) |>
flextable::flextable(cwidth = c(1.1, 0.7, 0.7, 0.7, 3.3)) |>
flextable::align(align = "left", j = c(1, 5), part = "all") |>
flextable::align(align = "center", j = c(2,3,4), part = "all") |>
flextable::set_caption(caption = paste0("Trawl performance by haul for net number ", unique_trawls$NET_NUMBER[ii], " during ", trawlmetrics_data[['year']], " survey."))
}
```
```{r}
#| results: asis
#| echo: false
#| ft.align: left
for(ii in 1:nrow(unique_trawls)) {
cat(paste0(" \n## Net number: ", unique_trawls$NET_NUMBER[ii]))
cat(" \n")
cat("#####\n")
cat(" \n")
flextable::flextable_to_rmd(tab_net_metrics[[ii]])
cat(" \n")
cat("#####\n")
cat(" \n")
flextable::flextable_to_rmd(tab_haul_history[[ii]])
cat("{{< pagebreak >}}")
}
```