library(tidyverse)
library(fixest)
ISFSI <- read_csv("./Data/Raw_Data/Cost_Tables/Table_C-9_Number_of_ISFSIs_by_Project_Plan.csv")
ONE <- ISFSI[1:3] 
colnames(ONE) <- c("Year","Active","Decom")
ONE <- ONE %>% mutate(Phase="Partial",Cost_Assumption="Low")

TWO <- ISFSI[,c(1,4:5)] 
colnames(TWO) <- c("Year","Active","Decom")
TWO <- TWO%>% mutate(Phase="Full",Cost_Assumption="Low")

THREE <- ISFSI[,c(1,6:7)] 
colnames(THREE) <- c("Year","Active","Decom")
THREE <- THREE %>% mutate(Phase="Partial",Cost_Assumption="High")

FOUR <- ISFSI[,c(1,8:9)] 
colnames(FOUR) <- c("Year","Active","Decom")
FOUR <- FOUR %>% mutate(Phase="Full",Cost_Assumption="High")
ISFSI_NUM <- rbind(ONE,TWO,THREE,FOUR)
SAVE_DIR <- "./Data/Cleaned_Data/"
dir.create(SAVE_DIR,showWarnings=FALSE,recursive=TRUE)
saveRDS(ISFSI_NUM,paste0(SAVE_DIR,"ISFSI_Data.Rds"))
rm(ONE,TWO,THREE,FOUR)
######CIFS costs
CIFS <- rbind( read_csv("./Data/Raw_Data/Cost_Tables/Table_C-3_Undiscounted_Cost_Estimates_Phase_1_Low.csv") %>% mutate(Phase='Partial',Cost_Assumption="Low"),read_csv("./Data/Raw_Data/Cost_Tables/Table_C-4_Undiscounted_Cost_Estimates_Phase_1_High.csv") %>% mutate(Phase='Partial',Cost_Assumption="High"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-5_Undiscounted_Cost_Estimates_Full_Low.csv") %>% mutate(Phase='Full',Cost_Assumption="Low"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-6_Undiscounted_Cost_Estimates_Full_High.csv") %>% mutate(Phase='Full',Cost_Assumption="High"))
saveRDS(CIFS,"Data/Cleaned_Data/Texas_CIFS_Costs.Rds")

######Onsite costs
ONSITE <- rbind( read_csv("./Data/Raw_Data/Cost_Tables/Table_C-10_Undiscounted_No_Action_Phase_1_Low.csv") %>% mutate(Phase='Partial',Cost_Assumption="Low"),read_csv("./Data/Raw_Data/Cost_Tables/Table_C-11_Undiscounted_No_Action_Phase_1_High.csv") %>% mutate(Phase='Partial',Cost_Assumption="High"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-12_Undiscounted_No_Action_Full_Low.csv") %>% mutate(Phase='Full',Cost_Assumption="Low"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-13_Undiscounted_No_Action_Full_High.csv") %>% mutate(Phase='Full',Cost_Assumption="High"))
ISFSI_NUM %>% filter(Year>=30,Phase=='Full') %>% print(n=100)
#######
SUMMARY <- ONSITE %>% inner_join(ISFSI_NUM) %>% group_by(Year,Cost_Assumption) %>% summarize(Decom_num=Decom,OP=Operations_Active/ifelse(Active==0,1,Active),Decom=Operations_Decom/ifelse(Decom==0,1,Decom))
OP <- SUMMARY %>% filter(OP!=0) %>% pull(OP) %>% mean
TEST <-SUMMARY %>% filter(Cost_Assumption=='High')  %>% unique
hist(TEST$Decom)

TEST <-SUMMARY   %>% unique
hist(TEST$Decom)
TEST %>% filter(OP!=0,Year>28) %>% print(n=100)
SUMMARY <- SUMMARY %>% mutate(CLOSING=ifelse(Year>=31,1,0))
SUMMARY
(10*77964491)/36
(2*125682289)/9
TEST
77964491/108647430
feols(Decom~Decom_num+CLOSING*Year,SUMMARY %>% filter(OP!=0))
hist(SUMMARY$Decom)
#####
M <- (779644907-251364578)/(40000-5000)
C <- 779644907-M*40000
(M*150000+C)/10^6