{
xname = "lai"; xlab = "Leaf area index (LAI)"; lims = c(-4.5, 4.5)
# xname = "AI" ; xlab = "Aridity index (PET/P)"; lims = c(0, 10)
# res = step_quantile(df_sm2, xname, lims, 0.01)
res = step_quantile(df_sm, xname, lims, 0.01)
# d$variable %>% levels
formula <- glue("{xname} + variable + alpha ~ val_type")
d = melt(res, c(xname, "prob")) %>%
merge(d_prob[,.(alpha, val_type = variable, prob)]) %>%
dcast(formula, value.var = "value")
levs <- unique(d$alpha) # %>% rev()
nlev <- length(levs)
ind = 1:(nlev - 1)
d$alpha %<>% factor(levs[ind], paste0((1 - levs[ind])*100, "% interval"))
cols = hue_pal()(nlev-1) # %>% rev()
labs = c(
expression("(a) GPP (g C" ~ m ^ -2 * y^-1 * ")"),
expression("(b) Ec ("*mm~y^-1*")"),
expression("(c) Es ("*mm~y^-1*")"),
expression("(d) Ei ("*mm~y^-1*")")
)
# labs = c(
# expression("(a) " * d[GPP]/d[LAI]),
# expression("(b) " * d[Ec]/d[LAI]),
# expression("(c) " * d[Es]/d[LAI]),
# expression("(d) " * d[Ei]/d[LAI])
# )
d$variable %<>% factor(c("GPP", "Ec", "Es", "Ei"), as.character(labs))
{
# p <-
p <- ggplot(d[is.na(alpha)], aes_string(xname, "mid")) +
geom_ribbon(data = d[!is.na(alpha), ],
aes(ymax = max, ymin = min, fill = alpha, y = NULL), alpha = 0.9) +
geom_line(color = "white") +
facet_wrap(~variable, scale = "free", labeller = label_parsed) +
scale_fill_manual(values = cols) +
# geom_smooth() +
# geom_abline(slope = 1) +
labs(x = xlab, y = NULL) +
# geom_vline(xintercept = 0.76, col = "red", lty = 2) +
# geom_vline(xintercept = 1.35, col = "blue", lty = 2) +
theme(
legend.position = "bottom", #c(0, 1), "none"
# legend.justification = c(0, 1),
legend.title = element_blank(),
legend.margin = margin(l = 5, t = -1, r = 5),
strip.text = element_text(face = 2, size = 9, lineheight=0.5))
# scale_y_continuous(limits = symmetric_range)
# p
write_fig(p, "Figure(abandoned)4_dx~dLAI.pdf", 9, 6)
}
# tag_facet(p, x = Inf, hjust = 1.4, size = 5, fontface = 1, tag_pool = labs, parse = TRUE) %>%
}
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