main_script.py

data = {
    "time": {"vbl": [], "flip": [], "miss": [], "fps": [], "cost": [], "JSCheckCost": [], "datasavingCost": [],
             "rewardCost": [], "drawCost": [], "flipCost": [], "ghostUpCost": [], "pacManUpCost": [], "ifi": float},
    "gameMap": {"currentTiles": [], "totalDots": [], "version": 'GenerateRandomMap_V13([0 0 1 1 1 1 1 1])'},
    "pacMan": {"frames": [], "tile_x": [], "tile_y": [], "pixel_x": [], "pixel_y": [], "dir_x": [], "dir_y": [],
               "dirEnum": [], "nextDirEnum": [], "distToMid_x": [], "distToMid_y": [], },
    "ghosts": {"tile_x": [], "tile_y": [], "pixel_x": [], "pixel_y": [], "dir_x": [], "dir_y": [], "dirEnum": [],
               "distToMid_x": [],
               "distToMid_y": [], "targetTile_x": [], "targetTile_y": [], "cornerTile_x": [], "cornerTile_y": [],
               "frames": [],
               "mode": [], "targeting": [], "scared": [], "sigReverse": [], "sigLeaveHome": [],
               "faceDirEnum": [], },
    "energizer": {"pointsDuration": [], "duration": [], "flashes": [], "flashInterval": [], "count": [],
                  "active": [], "points": [], "pointsFramesLeft": [], },
    "direction": {"up": [], "down": [], "left": [], "right": [], "bug": [], },
    "Voltage": {"up": [], "down": [], "left": [], "right": [], },
    "rewd": {"reward": [], "rewardWin": [], "rewardX": [], "magdot": [], "magghoast": [], "mageneg": [], },
}
num = 0
for key in data.keys():
    num += len(list(data[key].keys()))

import pandas as pd
import numpy as np
from BasicStrategy.DataPreProcessHuman import human_data_preprocess
from BasicStrategy.GetUtilityHuman import get_human_utility
from BasicStrategy.CorrectUtilityHuman import correct_human_utility
from BasicStrategy.FittingWeightHuman import get_human_weight
from BasicStrategy.reviseWeight.reviseHuman import correct_human_weight
from BasicStrategy.GetUtilityMonkey import get_monkey_utility
from BasicStrategy.CorrectUtilityMonkey import correct_monkey_utility
from BasicStrategy.FittingWeightMonkey import get_monkey_weight
from BasicStrategy.reviseWeight.reviseMonkey import correct_monkey_weight

from FeatureExtractor.ExtractFeaturesHuman import extract_human_feature
from FeatureExtractor.ExtractFeaturesMonkey import extract_monkey_feature

from GrammarInduction.DataFormedHuman import form_date_human
from GrammarInduction.DataFormedMonkey import form_date_monkey

from GrammarInduction.LearnStateHuman import learm_state_graph_human
from GrammarInduction.LearnStateMonkey import learm_state_graph_monkey

from GrammarInduction.GrammarInductionHuman import grammar_induction_human
from GrammarInduction.GrammarInductionMonkey import grammar_induction_monkey

from GrammarInduction.GenerateGramDepthHuman import LoPS_complexity_human
from GrammarInduction.GenerateGramDepthMonkey import LoPSC_omplexity_monkey

from GrammarInduction.GrammarProcess import DividePerson, GrammarAlign

from FeatureExtractor.PerformanceHuman import reaction_time_human, reward_human
from FeatureExtractor.PerformanceMonkey import reaction_time_monkey, reward_monkey
from DrawImg.generate_data.GenerateData import *
from DrawImg.generate_data.grammarTransition import *

from DrawImg.plot_code.plot_main import *


def generate_data():
    dates = ["session1", "session2"]
    for date in dates:
        # human data preprocess
        human_data_preprocess(date)
        # get utility of every strategy
        get_human_utility(date)
        correct_human_utility(date)
        # get weight of every strategy
        get_human_weight(date)
        correct_human_weight(date)
        # extract feature
        extract_human_feature(date)
        # form data
        form_date_human(date)
        # learn state
        learm_state_graph_human(date)
        # grammar induction
        grammar_induction_human(date)
        DividePerson(date)
        GrammarAlign("human", date)
        # LoPS Complexity
        LoPS_complexity_human(date)

        # Performance
        reaction_time_human(date)
        reward_human(date)

    dates = ["Year1", "Year2", "Year3"]
    for date in dates:
        # get utility of every strategy
        get_monkey_utility(date)
        correct_monkey_utility(date)
        # get weight of every strategy
        get_monkey_weight(date)
        correct_monkey_weight(date)
        # extract feature
        extract_monkey_feature(date)

        # form data
        form_date_monkey(date)
        # learn state
        learm_state_graph_monkey("Omega", date)
        learm_state_graph_monkey("Patamon", date)
        # grammar induction
        grammar_induction_monkey("Omega", date)
        grammar_induction_monkey("Patamon", date)
        GrammarAlign("Monkey", date)
        # LoPS Complexity
        LoPSC_omplexity_monkey("Omega", date)
        LoPSC_omplexity_monkey("Patamon", date)

        # Performance
        reaction_time_monkey("Omega", date)
        reaction_time_monkey("Patamon", date)
        reward_monkey("Omega", date)
        reward_monkey("Patamon", date)


def generate_img_data():
    Fig2b()
    Fig2c()
    Fig3a()
    Fig3b()
    Fig4a2_4b2()
    Fig4a3_4b3()

    Fig5a()
    Fig5b()

    subj_types = ["expert", "novice", "monkey"]
    for subj in subj_types:
        generate_transition_data_human(subj)
    transition_filter(0.7, False)
    toCsvMain()



def draw_img():
    plot_2b()
    plot_2c()
    plot_3a()
    plot_3b()
    plot_4a2_4b2()
    plot_4a3_4b3()

    plot_5a()
    plot_5b()

    plot_6()
    plot_7()
    plot_sup1()
    plot_sup3a()
    plot_sup3b()
    plot_s2()

    grammar_contribute_performance()
    static_RD_GD()
    static_LROfS_CNT()


if __name__ == '__main__':

    generate_data()
    generate_img_data()
    draw_img()