In pratikunterwegs/process-pattern: What the Package Does (One Line, Title Case)

Plot SSF coefficients vs agent weights

library(data.table)
library(ggplot2)
library(colorspace)
library(patchwork)

# cut wt fun
source("R/fun_wt_vals.R")

Read data

paths = list.files("data/ssf_fits", full.names = T)
data = lapply(paths, fread)

data = rbindlist(data)
data = data[growth %in% c(0.01, 0.02, 0.03)]

Read agent weights

wt_data = fread("data/data_lt_wts_scaled.csv")

wt_data[, move_strategy := dplyr::case_when(
  wt_4 > 0.6 ~ "prey tracking",
  ((wt_4 > 0) & (wt_3 > 0) & (abs(wt_4 - wt_3) < 0.1))  ~ "prey and handler tracking",
  wt_3 > 0.5 ~ "handler tracking",
  wt_3 < -0.5 ~ "handler avoiding",
  wt_2 > 0.5 ~ "non-handler tracking",
  wt_2 < -0.5 ~ "non-handler avoiding",
  T ~ "mixed"
)]

wt_data[, move_strategy := factor(
  move_strategy, 
  levels = c(
    "prey tracking",
    "handler tracking",
    "prey and handler tracking",
    "non-handler avoiding",
    "handler avoiding",
    "mixed"
  )
)
]

Link coefficients and weights

# select only significant predictors
data = data[p.value <= 0.05, !(c("std.error", "statistic"))]
data = data[, !("p.value")]

data[, term := dplyr::case_when(
  term == "cell_r" ~ "ssf_R"
)]

data = dcast(data, id + growth + type + rep_ ~ term, value.var = "estimate")

data = merge(data, wt_data, 
             by.x = c("id", "growth", "rep_", "type"), 
             by.y = c("id", "growth", "rep_", "type"),
             all.x = T, all.y = F)

data = data[id < 100,]

data = split(data, by = "type")
data = data[c("exploit", "obligate")]

plot_ssf_hist = lapply(data, function(df) {
  ggplot(df)+
    geom_hline(
      yintercept = 0,
      lty = 2,
      col = 2
    )+
    ggdist::stat_histinterval(
      aes(
        factor(growth), ssf_R,
          fill = comp_strat
      ),
      col = "grey20",
      slab_colour = "black",
      slab_size = 0.2,
      # binwidth = 0.2,
      alpha = 0.7,
      position = position_nudge(x = 0.0),
      point_colour = NA
    )+
    scale_fill_manual(
      values = c(
        "forager" = "darkseagreen",
        "klept" = "brown"
      ),
      labels = c(
        "forager" = "Forager",
        "klept" = "Kleptoparasite"
      )
    )+
    scale_x_discrete(
      limits = rev(c("0.01", "0.02", "0.03"))
    )+
    scale_y_continuous(
      breaks = c(0, 1, 3, 5, 7, 9),
      limits = c(-2, 10)
    )+
    coord_flip(
      expand = F,
      xlim = c(0.8, NA)
    )+
    theme_test(
      base_size = 8
    )+
    theme(
      axis.title.x = ggtext::element_markdown(),
      axis.title.y = ggtext::element_markdown(),
      axis.text.y = element_text(
        angle = 90,
        hjust = 0.5
      ),
      axis.text.x = element_text(size = 6),
      legend.position = "top",
      legend.title = element_text(face = "bold"),
      legend.key.height = unit(2, "mm")
    )+
    labs(
      y = "Estimated relative selection for <i>r<i>",
      x = "Landscape productivity *r<sub>max</sub>*",
      fill = "Competitive strategy",
      colour = "Movement strategy"
    )+
    guides(
      fill = guide_legend(ncol = 2, title.position = "top"),
      colour = guide_legend(ncol = 2, title.position = "top", 
                            override.aes = list(size = 2))
    )
})

plot_ssf_hist =
  wrap_plots(
  plot_ssf_hist, guides = "collect"
)+
  plot_layout(
    tag_level = "new"
  )

# filter data for main strategies
data = rbindlist(data)
data_type_summary = data[
  , .N, 
  by = c("growth", "move_strategy", "rep_", 
         "comp_strat", "type")
]
data_type_summary = data_type_summary[N > 10,]
data = merge(data, data_type_summary)
data = split(data, by = "type")

# now plot
plot_ssf_box = lapply(data, function(df) {
  ggplot(df)+
    geom_hline(
      yintercept = 0,
      lty = 2,
      col = 2
    )+
    ggdist::stat_histinterval(
      aes(
        factor(growth), ssf_R,
          fill = move_strategy
      ),
      col = "grey20",
      slab_colour = "black",
      slab_size = 0.2,
      # binwidth = 0.2,
      alpha = 0.7,
      position = position_nudge(x = 0.0),
      point_colour = NA
    )+
    scale_fill_manual(
      values = c(
        "prey tracking" = "seagreen",
        "prey and handler tracking" = "royalblue",
        "non-handler avoiding" = "red",
        "handler avoiding" = "orange",
        "handler tracking" = "lightblue",
        "mixed" = "lightgrey",
        "NA" = "transparent"
      ),
      breaks = c(
        "prey tracking",
        "handler tracking",
        "prey and handler tracking",
        "non-handler avoiding",
        "handler avoiding",
        "mixed"
      )
    )+
    scale_y_continuous(
      breaks = c(0, 1, 3, 5, 7, 9),
      limits = c(-2, 10)
    )+
    scale_x_discrete(
      limits = rev(c("0.01", "0.02", "0.03"))
    )+
    coord_flip(
      expand = F,
      xlim = c(0.8, NA)
    )+
    theme_test(
      base_size = 8
    )+
    theme(
      axis.title.x = ggtext::element_markdown(),
      axis.title.y = ggtext::element_markdown(),
      axis.text.y = element_text(
        angle = 90,
        hjust = 0.5
      ),
      axis.text.x = element_text(size = 6),
      legend.position = "top",
      legend.title = element_text(face = "bold"),
      legend.key.height = unit(2, "mm")
    )+
    labs(
      y = "Estimated relative selection for <i>r<i>",
      x = "Landscape productivity *r<sub>max</sub>*",
      fill = "Movement strategy"
    )+
    guides(
      fill = guide_legend(ncol = 3, title.position = "top"),
      colour = guide_legend(ncol = 3, title.position = "top", 
                            override.aes = list(size = 2))
    )
})

plot_ssf_box = 
  wrap_plots(
  plot_ssf_box,
  guides = "collect"
)+
  plot_layout(
    tag_level = "new"
  ) &
  theme(
    legend.position = "top"
  )

plot_ssf =
  wrap_plots(
  plot_ssf_hist,
  plot_ssf_box,
  ncol = 1
)&
  plot_annotation(
    tag_levels = c("A", 1)
  )&
  theme(
    plot.tag = element_text(
      face = "bold",
      size = 8
    ),
    legend.position = "bottom"
  )

ggsave(
  plot_ssf,
  filename = "figures/fig_04.png",
  width = 120,
  height = 120, units = "mm"
)