discarded_plots.Rmd

---
title: "discarded plots"
output: html_notebook
---


```{r}

```


```{r}
source("functions/plot_fun_fig_2_box.R")
source("functions/plot_fun_fig_2_box_2.R")
source("functions/plot_fun_fig_2_violin.R")
```

```{r}
ggplot(zeta_cd) +
  geom_line(
    aes(
      x = value,
      y = cd,
      colour = decision
    )
  ) +
  facet_wrap(
    facets = ~ species,
    nrow = 2,
    scales = "free_x"
  )
```

Calculate the upper and lower bounds for plotting as for each species the highest of the 97.5th percentile decision score for each decision and lowest of the 2.5th percentile for each decision.
```{r}
zeta_estimates_limits <- zeta_estimates %>%
  group_by(species, decision) %>%
  summarise(
    p2.5 = quantile(
      x = zeta,
      probs = 0.05
    ),
    p97.5 = quantile(
      x = zeta,
      probs = 0.95
    )
  ) %>%
  group_by(species) %>%
  summarise(
    lower = min(p2.5),
    upper = max(p97.5)
  )

zeta_estimates_limits
```

```{r}
zeta_estimates_limits2 <- zeta_estimates %>%
  group_by(species, decision) %>%
  summarise(
    p2.5 = quantile(
      x = zeta,
      probs = 0.25
    ),
    p97.5 = quantile(
      x = zeta,
      probs = 0.75
    )
  ) %>%
  group_by(species) %>%
  summarise(
    lower = min(p2.5),
    upper = max(p97.5)
  )

zeta_estimates_limits2
```


Plot results for figure 2


Assemble boxplots
```{r figure_2}
fig2_list <- mapply(
  FUN = plot_fun_fig_2_box,
  species = unique(zeta_estimates$species),
   xlab = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    TRUE,
    FALSE
  ),
  ylab = c(
    TRUE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE
  ),
  xtext = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    TRUE,
    TRUE,
    TRUE
  ),
  MoreArgs = list(
    data = zeta_estimates,
    limits = zeta_estimates_limits,
    textsize = 9
  ),
  SIMPLIFY = FALSE
)


figure_2 <- fig2_list[[1]] +
  fig2_list[[2]] +
  fig2_list[[3]] +
  fig2_list[[4]] +
  fig2_list[[5]] +
  fig2_list[[6]] +
  fig2_list[[7]] +
  guide_area() +
  plot_layout(ncol = 4) +
  plot_layout(guides = "collect")

figure_2
```

```{r}
fig2_list2 <- mapply(
  FUN = plot_fun_fig_2_box_2,
  species = unique(zeta_estimates$species),
   xlab = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE
  ),
  ylab = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE
  ),
  xtext = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    TRUE,
    TRUE
  ),
  MoreArgs = list(
    data = zeta_estimates,
    limits = zeta_estimates_limits2,
    textsize = 10
  ),
  SIMPLIFY = FALSE
)

fig2_list2[[1]]
```

```{r}
f2legend <- get_legend(fig2_list2[[1]])

f2 <- plot_grid(
  NULL,
  NULL,
  fig2_list2[[1]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[2]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[3]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[4]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[5]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[6]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  fig2_list2[[7]] + scale_fill_manual(values = viridis(3)[3:1], guide = FALSE),
  #f2legend,
  ncol = 2,
  align = "hv",
  labels = c(
    "",
    "",
    "Alpine tree-frog",
    "Giant Ibis",
    "Red Handfish",
    "Smooth Newt",
    "Species1",
    "Tiger",
    "Wollemi Pine"#,
    #""
  ),
  #label_fontface = "plain",
  label_size = 12,
  vjust = -0.01,
  hjust = 0,
  rel_heights = c(0.1, 1, 1, 1, 1)
)

f2
```

```{r}
png(
  filename = "plots/f2.png",
  width = 20,
  height = 20,
  units = "cm",
  res = 300
)
f2
dev.off()
```

```{r}

figure_22 <- fig2_list2[[1]] +
  fig2_list2[[2]] +
  fig2_list2[[3]] +
  fig2_list2[[4]] +
  fig2_list2[[5]] +
  fig2_list2[[6]] +
  fig2_list2[[7]] +
  guide_area() +
  plot_layout(ncol = 4) +
  plot_layout(guides = "collect")

figure_22
```

```{r}
png(
  filename = "plots/figure_22.png",
  width = 30,
  height = 20,
  units = "cm",
  res = 300
)
figure_22
dev.off()
```


```{r figure_2 png}
png(
  filename = "plots/figure_2.png",
  width = 20,
  height = 15,
  units = "cm",
  res = 300
)
figure_2
dev.off()
```

```{r}
figs1_list <- mapply(
  FUN = plot_fun_fig_2_box,
  species = unique(zeta_estimates$species),
   xlab = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    TRUE,
    FALSE
  ),
  ylab = c(
    TRUE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    FALSE
  ),
  xtext = c(
    FALSE,
    FALSE,
    FALSE,
    FALSE,
    TRUE,
    TRUE,
    TRUE
  ),
  MoreArgs = list(
    data = zeta_estimates,
    textsize = 9
  ),
  SIMPLIFY = FALSE
)


figure_s1 <- figs1_list[[1]] +
  figs1_list[[2]] +
  figs1_list[[3]] +
  figs1_list[[4]] +
  figs1_list[[5]] +
  figs1_list[[6]] +
  figs1_list[[7]] +
  guide_area() +
  plot_layout(ncol = 4) +
  plot_layout(guides = "collect")


figure_s1
```


```{r figure_s1 png}
png(
  filename = "plots/figure_s1.png",
  width = 20,
  height = 15,
  units = "cm",
  res = 300
)
figure_s1
dev.off()
```



```{r}
ggplot(zeta_estimates %>% filter(species == "Alpine tree-frog")) +
  geom_density(
    aes(
      x = zeta,
      colour = decision,
      fill = decision
    ),
    alpha = 0.3
  ) +
  facet_zoom(
    xlim = c(zeta_estimates_limits$lower[1], zeta_estimates_limits$upper[1])
  )
  
```

```{r}
ggplot(zeta_estimates) +
  geom_density(
    aes(
      x = zeta,
      colour = decision,
      fill = decision
    ),
    alpha = 0.3
  ) +
  facet_wrap(
    facets = ~ species,
    scales = "free"
  )
```