library(tidyverse)
library(cmdstanr)
library(dplyr)

strategies <- c("put_fridge", "put_dishwasher", "read_book")
model_type <- "lstmlast_cross_entropy_bs_32_iter_2000_train_task_prob" 
rate <- "_0"
task_type <- "new_test_task" # new_test_task test_task
loss_type <- "ce"
set.seed(9746234)
if (task_type=="test_task"){
	user_num <- 92
	user <-c(0:(user_num-1))
	N <- 1
}
if (task_type=="new_test_task"){
	user_num <- 9
	user <-c(0:(user_num-1))
	N <- 1
}
total_user_act1 <- vector("list", length(user_num))
total_user_act2 <- vector("list", length(user_num))

sel <- vector("list", length(strategies))
act_series <- vector("list", user_num)
for (u in seq_along(user)){
	print('user')
	print(u)
	dat <- vector("list", length(strategies))
	for (i in seq_along(strategies)) {
		if (rate=="_0"){
			dat[[i]] <- read.csv(paste0("prediction/", task_type, "/user", user_num, "/", loss_type, "/", strategies[[i]], "/loss_weight_", model_type, "_prediction_", strategies[[i]], "_user", user[[u]], "_rate_", "90", ".csv"))
		} else if (rate=="_100"){
			dat[[i]] <- read.csv(paste0("prediction/", task_type, "/user", user_num, "/", loss_type, "/", strategies[[i]], "/loss_weight_", model_type, "_prediction_", strategies[[i]], "_user", user[[u]], ".csv"))
		}	else{
			dat[[i]] <- read.csv(paste0("prediction/", task_type, "/user", user_num, "/", loss_type, "/", strategies[[i]], "/loss_weight_", model_type, "_prediction_", strategies[[i]], "_user", user[[u]], "_rate", rate, ".csv")) 		
		}
		dat[[i]]$assumed_strategy <- strategies[[i]]
		dat[[i]]$index <- dat[[i]]$action_id # sample based on intention
		dat[[i]]$id <- dat[[i]][,1] # sample based on intention
	}
	
	N <- 1
	# select all action series and infer every one
	sel[[1]]<-dat[[1]] %>%
	group_by(task_name) %>%
	filter(task_name==1) 
	sel[[1]] <- data.frame(sel[[1]]) 
	unique_act_id_t1 <- unique(sel[[1]]$action_id)
	write.csv(unique_act_id_t1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "user_",u, "_put_dishwasher", ".csv"))
	total_user_act1[[u]] <- unique_act_id_t1
	
	sel[[1]]<-dat[[1]] %>%
	group_by(task_name) %>%
	filter(task_name==2) 
	sel[[1]] <- data.frame(sel[[1]]) 
	unique_act_id_t1 <- unique(sel[[1]]$action_id)
	write.csv(unique_act_id_t1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "user_",u, "_read_book", ".csv"))
	total_user_act2[[u]] <- unique_act_id_t1
}	
						
write.csv(total_user_act1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "_put_dishwasher_total", ".csv"))
write.csv(total_user_act2, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "read_book_total", ".csv"))