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

Plot variation within and between scenarios

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

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

Figure functional variation

# read scaled weights
data_sc_wt = fread("data/data_lt_wts_scaled.csv")
data_sc_wt = data_sc_wt[growth %in% c(0.01) & rep_ == 2]
data_sc_wt = data_sc_wt[type %in% c("exploit", "obligate")]

# assign strategy
data_sc_wt[, 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"
)]

data_sc_wt = split(data_sc_wt, by = "type")

Figure movement strategies

plot_move_types = function(df) {
  ggplot(df)+
    geom_hline(
      yintercept = 0, # size = 0.2,
      col = "grey"
    )+
    geom_vline(
      xintercept = 0, # size = 0.2,
      col = "grey"
    )+
    geom_abline(
      slope = c(-1, 1),
      intercept = c(1, -1),
      col = "grey",
      lty = 2,
      size = 0.5
    )+
    geom_jitter(
      aes(wt_4, wt_3, fill = move_strategy),
      shape = 21, col = alpha("grey30", 0.1),
      size = 3,
      show.legend = T,
      alpha = 0.05
    )+
    geom_text(
      data = data.table(
        x = c(1, 0.1, 0.1),
        y = c(0, 1, -1),
        strat = c("Prey tracking", "Handler tracking",  "Handler avoiding"),
        angle = c(90, 0, 0)
      ),
      aes(x, y, label = strat, angle = angle),      
      size = 3,
      col = "grey30",
      hjust = "inward",
      fontface = "italic"
    )+
    scale_fill_manual(
      values = c(
        "prey tracking" = "seagreen",
        "prey and handler tracking" = "royalblue",
        "non-handler avoiding" = "red",
        "handler avoiding" = "orange",
        "handler tracking" = "lightblue",
        "mixed" = "grey90",
        "NA" = "grey90"
      ),
      breaks = c(
        "prey tracking",
        "handler tracking",
        "prey and handler tracking",
        "non-handler avoiding",
        "handler avoiding",
        "mixed"
      ),
      na.value = "grey90"
    )+
    facet_grid(
      ~ comp_strat, 
      # ncol = 2, 
      labeller = labeller(
        .multi_line = F,
        growth = label_both,
        comp_strat = c(
          "forager" = "Foragers",
          "klept" = "Kleptoparasites"
        )
      )
    )+
    coord_cartesian(
      expand = T,
      xlim = c(-0, 1),
      ylim = c(-1, 1)
    )+
    theme_test(
      base_size = 8
    )+
    theme(
      strip.background = element_blank(),
      strip.text = element_text(
        face = "italic"
      ),
      legend.position = "top",
      legend.key.width = unit(5, units = "mm"),
      legend.key.height = unit(1, "mm")
    )+
    labs(
      x = "sP",
      y = "sH",
      fill = NULL
    )+
    guides(
      fill = guide_legend(override.aes = list(alpha = 1))
    )
}

plots_move_types = lapply(data_sc_wt, plot_move_types) |>
  wrap_plots(
    guides = "collect",
    design = "ABB"
  ) +
  plot_layout(tag_level = "new") &
  theme(
    legend.position = "top"
  )

Figure movement distance distribution

# get path summaries
paths = list.files(path = "data/lt_tracks", full.names = T)
# read files
data_stats = lapply(paths, fread)
# bind data
data_stats = rbindlist(data_stats)[growth == 0.01 & 
                                     type %in% c("exploit", "obligate")]
# bind datascwt
data_sc_wt = rbindlist(data_sc_wt)

# link to data_stats
data_stats = merge(data_stats[, !(c("wt_2", "wt_3", "wt_4"))], data_sc_wt, 
                   by = c("id", "growth", "type", "rep_", "intake", "gen"))

# subset data for interesting strats
# data_stats = data_stats[
#   (type == "exploit" & (move_strategy %in% c(
#     "prey tracking", "prey and handler tracking", "non-handler avoiding",
#     "handler tracking"))) |
#     (type == "obligate" & (move_strategy %in% c(
#       "non-handler avoiding", "handler avoiding", "handler tracking")))
# ]

# split data
data_stats = split(data_stats, by = "type")

Make plot

plot_dist_hist =
  lapply(data_stats, function(df) {
    ggplot(df)+
      geom_histogram(
        aes(
          x = distance,
          fill = move_strategy
        ),
        binwidth = 5,
        alpha = 0.7,
        position = "identity"
      )+
      scale_fill_manual(
        values = c(
          "prey tracking" = "seagreen",
          "prey and handler tracking" = "royalblue",
          "non-handler avoiding" = "red",
          "handler avoiding" = "orange",
          "handler tracking" = "lightblue",
          "mixed" = "grey90",
          "NA" = "grey90"
        ),
        breaks = c(
          "prey tracking",
          "handler tracking",
          "prey and handler tracking",
          "non-handler avoiding",
          "handler avoiding",
          "mixed"
        ),
        na.value = "grey90"
      )+
      scale_y_continuous(
        labels = scales::comma
      )+
      facet_grid(
        ~ comp_strat,
        labeller = labeller(
          .multi_line = F,
          comp_strat = c(
            "forager" = "Foragers",
            "klept" = "Kleptoparasites"
          )
        )
      )+
      theme_test(base_size = 8)+
      theme(
        axis.text.y = element_text(angle = 90, hjust = 0.5),
        legend.key.height = unit(2, "mm"),
        strip.background = element_blank(),
        strip.text = element_text(
          face = "italic"
        )
      )+
      coord_cartesian(
        expand = T
      )+
      guides(
        colour = guide_legend(override.aes = list(
          size = 2)
        )
      )+
      labs(
        fill = NULL,
        y = "# Tracks",
        x = "Distance"
      )
  })

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

Wrap all plots

fig_id_var =
  wrap_plots(
    plots_move_types,
    plot_dist_hist,
    guides = "collect",
    ncol = 1
  ) +
  plot_annotation(tag_levels = c("A", 1)) &
  theme(
    legend.position = "bottom",
    plot.tag = element_text(face = "bold", size = 8)
  )

ggsave(
  plot = fig_id_var,
  filename = "figures/fig_02.png",
  width = 155,
  height = 150,
  units = "mm"
)