I am trying to do a disease simulation, where I want the infected node(is_infected>0) to be red and the un-infected(is_infected=0) node color to be cyan.
results <- results %>% mutate(
S = infected == 0,
E = 0 < infected & infected < 6,
I = infected >= 6 & infected <= 11,
R = infected > 11,
is_infected = infected > 0
)
net.layout.by.time <-
split(results, f = results$t%in% c(5, 7, 16, 40, 80)) %>%
lapply(FUN = right_join,
y = net.layout,
by = "id") %>%
bind_rows
net.layout.by.time <- split(results, f = results$t) %>%
lapply(FUN = right_join, y = net.layout, by = "id") %>%
bind_rows
net.layout.by.time %>%
filter(t %in% c(5, 6, 7, 20, 40)) %>%
ggplot(aes(xend = xend, yend = yend, x = x, y = y)) +
geom_edges(color = "lightgray") +
geom_nodes(aes(color = is_infected)) +
facet_wrap(~ t) +
theme_blank()
This can be useful but not tested in lack of shared data:
library(ggplot2)
#Code
net.layout.by.time %>%
filter(t %in% c(5, 6, 7, 20, 40)) %>%
ggplot(aes(xend = xend, yend = yend, x = x, y = y)) +
geom_edges(color = "lightgray") +
geom_nodes(aes(color = is_infected)) +
facet_wrap(~ t) +
theme_blank()+scale_color_manual(values=c("blue","red"))