Chapter 6 Output

library(readxl)
library(tidyverse)
library(stringr)
library(zoo)
library(hrbrthemes)
library(ggthemes)
library(ggsci)

# ---------------
# N Cases
# ---------------
y <- usa.sf %>% 
  st_set_geometry(NULL) %>%
  inner_join(data, by="County.Code") %>%
  group_by(loc) %>%
  summarise(y = mean(synthetic_opioid_deaths, na.rm=T)) %>%
  mutate(Strata = str_sub(loc,1,1))

# ---------------
# PLOT
# ---------------

p <- read_excel("./_data/Spat_EMMERG_tables_v3.xlsx", sheet=2) %>%
  mutate(label = str_remove_all(model,pattern = "spatial"),
         label = str_remove_all(label,pattern = "spatio-temporal"),
         label = str_trim(label),
         Strata = na.locf(Strata)
         ) %>%
  inner_join(y, by="Strata") %>%
  mutate(NRMSE = RMSE/y,
         NMAE = MAE/y,
         NMSLE = MSLE/y)

start <- p %>% filter(Type=="baseline")
end <- p %>% filter(Type=="spatial")

p %>%
  ggplot(aes(y=Type, x=NRMSE, col=label)) +
  geom_segment(data=start, aes(x = NRMSE, y= Type, xend=end$NRMSE, yend=end$Type)) +
  geom_point(size = 5, alpha=.6) +
  geom_vline(xintercept = 0, linetype="dashed") +
  labs(y="") +
  scale_color_npg(breaks = c("Intercept only", "Healthcare", "Socioeconomics", "Drug market", "Susceptibility", "Full")) +
  theme_few() +
  #theme(legend.position = "top") +
  facet_wrap(.~Strata, ncol = 1)

p %>%
  filter(model!="Spatio-temporal only") %>%
  ggplot(aes(y=Type, x=NMAE, col=label)) +
  geom_segment(data=start, aes(x = NMAE, y= Type, xend=end$NMAE, yend=end$Type)) +
  geom_point(size = 5, alpha=.6) +
  geom_vline(xintercept = 0, linetype="dashed") +
  labs(y="", color = "Model") +
  scale_color_npg(breaks = c("Intercept only", "Healthcare", "Socioeconomics", "Drug market", "Susceptibility", "Full")) +
  theme_few() +
  #theme(legend.position = "top") +
  facet_wrap(.~Strata, ncol = 1)

#ggsave("./_out/f1.png", height = 7, width = 8, dpi = "retina")