DENVclimate:

devtools::load_all()

library(ggplot2)


# define parameters -----------------------------------------------------------


n <- 10000

seq_n <- seq(0, 10, length.out = n)


# run -------------------------------------------------------------------------


df_c_a <- data.frame(x = seq_n,
                     y = dgamma(seq_n, shape = 1, rate = 10),
                     trait_par = "c_a")

x_T0_a <- runif(n, min = 0, max = 24)
df_T0_a <- data.frame(x = x_T0_a,
                      y = dunif(x_T0_a, min = 0, max = 24),
                      trait_par = "T0_a")

x_Tm_a <- runif(n, min = 25, max = 45)
df_Tm_a <- data.frame(x = x_Tm_a,
                      y = dunif(x_Tm_a, min = 25, max = 45),
                      trait_par = "Tm_a")

df_c_b <- data.frame(x = seq_n,
                     y = dgamma(seq_n, shape = 1, rate = 10),
                     trait_par = "c_b")

x_T0_b <- runif(n, min = 0, max = 24)
df_T0_b <- data.frame(x = x_T0_b,
                      y = dunif(x_T0_b, min = 0, max = 24),
                      trait_par = "T0_b")

x_Tm_b <- runif(n, min = 25, max = 45)
df_Tm_b <- data.frame(x = x_Tm_b,
                      y = dunif(x_Tm_b, min = 25, max = 45),
                      trait_par = "Tm_b")

df_c_c <- data.frame(x = seq_n,
                     y = dgamma(seq_n, shape = 1, rate = 10),
                     trait_par = "c_c")

x_T0_c <- runif(n, min = 0, max = 24)
df_T0_c <- data.frame(x = x_T0_c,
                      y = dunif(x_T0_c, min = 0, max = 24),
                      trait_par = "T0_c")

x_Tm_c <- runif(n, min = 25, max = 45)
df_Tm_c <- data.frame(x = x_Tm_c,
                      y = dunif(x_Tm_c, min = 25, max = 45),
                      trait_par = "Tm_c")

df_c_lf <- data.frame(x = seq_n,
                      y = dgamma(seq_n, shape = 1, rate = 1),
                      trait_par = "c_lf")

x_T0_lf <- runif(n, min = 0, max = 24)
df_T0_lf <- data.frame(x = x_T0_lf,
                       y = dunif(x_T0_lf, min = 0, max = 24),
                       trait_par = "T0_lf")

x_Tm_lf <- runif(n, min = 25, max = 45)
df_Tm_lf <- data.frame(x = x_Tm_lf,
                       y = dunif(x_Tm_lf, min = 25, max = 45),
                       trait_par = "Tm_lf")

df_c_PDR <- data.frame(x = seq_n,
                       y = dgamma(seq_n, shape = 1, rate = 10),
                       trait_par = "c_PDR")

x_T0_PDR <- runif(n, min = 0, max = 24)
df_T0_PDR <- data.frame(x = x_T0_PDR,
                        y = dunif(x_T0_PDR, min = 0, max = 24),
                        trait_par = "T0_PDR")

x_Tm_PDR <- runif(n, min = 25, max = 45)
df_Tm_PDR <- data.frame(x = x_Tm_PDR,
                        y = dunif(x_Tm_PDR, min = 25, max = 45),
                        trait_par = "Tm_PDR")

all_df <- rbind(df_c_a, df_T0_a, df_Tm_a, df_c_b, df_T0_b, df_Tm_b,
                df_c_c, df_T0_c, df_Tm_c, df_c_lf, df_T0_lf, df_Tm_lf,
                df_c_PDR, df_T0_PDR, df_Tm_PDR)


# plot ------------------------------------------------------------------------


p <- ggplot(data = all_df, mapping = aes(x = x, y = y)) +
  geom_line() +
  facet_wrap(~ trait_par, scales = "free") +
  scale_x_continuous("Trait value", labels = function(x) format(x, scientific = FALSE)) +
  scale_y_continuous("PDF") +
  ggtitle("Vague priors") +
  theme_bw() +
  theme(axis.text = element_text(size = 6))

save_plot(p, "figures", "vague_priors", wdt = 20, hgt = 18)