cost = readRDS("cost.RDS")
drone = readRDS("drone.RDS")

df = data.frame(n = numeric(), y = numeric(), g = numeric(),
                stringsAsFactors = F)
df[1,] = 1:3
for(i in 1:4){
  costvec = numeric()
  dronevec = numeric()
  for(j in 1:20){
    costvec  = c(costvec,  cost[[j+(i-1)*20]])
    dronevec = c(dronevec, drone[[j+(i-1)*20]])          
  }
  n = length(costvec)
  e = nrow(df)
  df[(e+1):(n+e),] = cbind(dronevec, costvec, i)
}

df = df[-1,]
library(dplyr)
library(ggplot2)
library(tidyr)
df %>% group_by(g,n) %>% summarise(md = min(y)) %>% 
  ggplot(aes(x = n, y = md, group = g)) + 
  geom_line() + geom_point(aes(shape = factor(g))) + facet_wrap(~g)

df2 = df %>% group_by(g,n) %>% filter(g==3) %>% summarise(min = min(y),
                                                          avg = mean(y),
                                                          ndt = n())
# df3 = df2 %>% ungroup() %>% as.data.frame()
# xlsx::write.xlsx(df3, "dronecost.xlsx",
#                  row.names = F, showNA = F, sheetName = "data")
df2 %>%  
  gather(key, value, min, avg) %>% 
  ggplot(aes(x = n, y = value, shape = key)) + 
  geom_line() + geom_point()
