77 lines
2.7 KiB
R
77 lines
2.7 KiB
R
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library(tidyverse)
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library(cmdstanr)
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library(dplyr)
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strategies <- c("put_fridge", "put_dishwasher", "read_book")
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model_type <- "lstmlast_cross_entropy_bs_32_iter_2000_train_task_prob"
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rate <- "_0"
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task_type <- "new_test_task" # new_test_task test_task
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loss_type <- "ce"
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set.seed(9746234)
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if (task_type=="test_task"){
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user_num <- 92
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user <-c(0:(user_num-1))
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N <- 1
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}
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if (task_type=="new_test_task"){
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user_num <- 9
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user <-c(0:(user_num-1))
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N <- 1
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}
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total_user_act1 <- vector("list", length(user_num))
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total_user_act2 <- vector("list", length(user_num))
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sel <- vector("list", length(strategies))
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act_series <- vector("list", user_num)
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for (u in seq_along(user)){
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print('user')
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print(u)
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dat <- vector("list", length(strategies))
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for (i in seq_along(strategies)) {
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if (rate=="_0"){
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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"))
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} else if (rate=="_100"){
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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"))
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} else{
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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"))
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}
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dat[[i]]$assumed_strategy <- strategies[[i]]
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dat[[i]]$index <- dat[[i]]$action_id # sample based on intention
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dat[[i]]$id <- dat[[i]][,1] # sample based on intention
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}
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N <- 1
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# select all action series and infer every one
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sel[[1]]<-dat[[1]] %>%
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group_by(task_name) %>%
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filter(task_name==1)
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sel[[1]] <- data.frame(sel[[1]])
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unique_act_id_t1 <- unique(sel[[1]]$action_id)
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write.csv(unique_act_id_t1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "user_",u, "_put_dishwasher", ".csv"))
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total_user_act1[[u]] <- unique_act_id_t1
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sel[[1]]<-dat[[1]] %>%
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group_by(task_name) %>%
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filter(task_name==2)
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sel[[1]] <- data.frame(sel[[1]])
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unique_act_id_t1 <- unique(sel[[1]]$action_id)
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write.csv(unique_act_id_t1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "user_",u, "_read_book", ".csv"))
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total_user_act2[[u]] <- unique_act_id_t1
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}
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write.csv(total_user_act1, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "_put_dishwasher_total", ".csv"))
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write.csv(total_user_act2, paste0("result/", task_type, "/user", user_num, "/", loss_type, "/act", "/", "action_series_", "read_book_total", ".csv"))
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