akt_setting.py

import argparse

import config

from lib.util.FileManager import FileManager
from lib.util.parse import parse_data_type
from lib.util.data import read_preprocessed_file
from lib.data_processor.util import process4Akt_assist2009
from lib.dataset.split_seq import dataset_truncate2multi_seq
from lib.dataset.split_dataset import n_fold_split2


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--dataset_name", type=str, default="assist2009",
                        choices=("assist2009", "assist2017", "assist2015", "statics2011"))
    args = parser.parse_args()
    params = vars(args)

    params["setting_name"] = "akt_setting"
    if params["dataset_name"] == "assist2015":
        params["data_type"] = "only_question"
    elif params["dataset_name"] in ["assist2017", "statics2011"]:
        params["data_type"] = "single_concept"
    else:
        params["data_type"] = "multi_concept"
    params["max_seq_len"] = 200
    params["min_seq_len"] = 3
    params["n_fold"] = 5
    params["valid_radio"] = 0.25

    objects = {"file_manager": FileManager(config.FILE_MANAGER_ROOT)}
    params["lab_setting"] = {
        "name": params["setting_name"],
        "max_seq_len": params["max_seq_len"],
        "min_seq_len": params["min_seq_len"],
        "n_fold": params["n_fold"],
        "valid_radio": params["valid_radio"]
    }

    objects["file_manager"].add_new_setting(params["lab_setting"]["name"], params["lab_setting"])
    parse_data_type(params["dataset_name"], params["data_type"])
    data_uniformed_path = objects["file_manager"].get_preprocessed_path(params["dataset_name"], params["data_type"])
    data_uniformed = read_preprocessed_file(data_uniformed_path)

    if params["dataset_name"] == "assist2009":
        concept_id2name = objects["file_manager"].get_concept_id2name("assist2009")
        concept_id_map = objects["file_manager"].get_concept_id_map("assist2009", "multi_concept")
        data_uniformed = process4Akt_assist2009(data_uniformed, concept_id2name, concept_id_map)

    dataset_truncated = dataset_truncate2multi_seq(data_uniformed,
                                                   params["min_seq_len"],
                                                   params["max_seq_len"],
                                                   single_concept=params["data_type"] != "multi_concept")
    n_fold_split2(dataset_truncated, params, objects)