Skiing/rom_evaluate.py

import sys
import operator
from os import listdir, system
import subprocess
import re
from collections import defaultdict

from random import randrange
from ale_py import ALEInterface, SDL_SUPPORT, Action
from PIL import Image
from matplotlib import pyplot as plt
import cv2
import pickle
import queue
from dataclasses import dataclass, field

from sklearn.cluster import KMeans, DBSCAN

from enum import Enum

from copy import deepcopy

import numpy as np

import logging
logger = logging.getLogger(__name__)

#import readchar

from sample_factory.algo.utils.tensor_dict import TensorDict
from query_sample_factory_checkpoint import SampleFactoryNNQueryWrapper

import time

tempest_binary = "/home/spranger/projects/tempest-devel/ranking_release/bin/storm"
rom_file = "/home/spranger/research/Skiing/env/lib/python3.10/site-packages/AutoROM/roms/skiing.bin"

def tic():
    import time
    global startTime_for_tictoc
    startTime_for_tictoc = time.time()

def toc():
    import time
    if 'startTime_for_tictoc' in globals():
        return time.time() - startTime_for_tictoc

class Verdict(Enum):
    INCONCLUSIVE = 1
    GOOD = 2
    BAD = 3

verdict_to_color_map = {Verdict.BAD: "200,0,0", Verdict.INCONCLUSIVE: "40,40,200", Verdict.GOOD: "00,200,100"}

def convert(tuples):
    return dict(tuples)

@dataclass(frozen=True)
class State:
    x: int
    y: int
    ski_position: int
    velocity: int
def default_value():
    return {'action' : None, 'choiceValue' : None}

@dataclass(frozen=True)
class StateValue:
    ranking: float
    choices: dict = field(default_factory=default_value)

def exec(command,verbose=True):
    if verbose: print(f"Executing {command}")
    system(f"echo {command} >> list_of_exec")
    return system(command)

num_tests_per_cluster = 50
factor_tests_per_cluster = 0.2
num_ski_positions = 8
num_velocities = 8

def input_to_action(char):
    if char == "0":
        return Action.NOOP
    if char == "1":
        return Action.RIGHT
    if char == "2":
        return Action.LEFT
    if char == "3":
        return "reset"
    if char == "4":
        return "set_x"
    if char == "5":
        return "set_vel"
    if char in ["w", "a", "s", "d"]:
        return char

def saveObservations(observations, verdict, testDir):
    testDir = f"images/testing_{experiment_id}/{verdict.name}_{testDir}_{len(observations)}"
    if len(observations) < 20:
        logger.warn(f"Potentially spurious test case for {testDir}")
        testDir = f"{testDir}_pot_spurious"
    exec(f"mkdir {testDir}", verbose=False)
    for i, obs in enumerate(observations):
        img = Image.fromarray(obs)
        img.save(f"{testDir}/{i:003}.png")

ski_position_counter = {1: (Action.LEFT, 40), 2: (Action.LEFT, 35), 3: (Action.LEFT, 30), 4: (Action.LEFT, 10), 5: (Action.NOOP, 1), 6: (Action.RIGHT, 10), 7: (Action.RIGHT, 30), 8: (Action.RIGHT, 40) }

def run_single_test(ale, nn_wrapper, x,y,ski_position, velocity, duration=50):
#def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=50):
    #print(f"Running Test from x: {x:04}, y: {y:04}, ski_position: {ski_position}", end="")
    testDir = f"{x}_{y}_{ski_position}_{velocity}"
    #testDir = f"{x}_{y}_{ski_position}"
    for i, r in enumerate(ramDICT[y]):
        ale.setRAM(i,r)
    ski_position_setting = ski_position_counter[ski_position]
    for i in range(0,ski_position_setting[1]):
        ale.act(ski_position_setting[0])
        ale.setRAM(14,0)
        ale.setRAM(25,x)
    ale.setRAM(14,180) # TODO

    all_obs = list()
    speed_list = list()
    resized_obs = cv2.resize(ale.getScreenGrayscale(), (84,84), interpolation=cv2.INTER_AREA)
    for i in range(0,4):
        all_obs.append(resized_obs)
    for i in range(0,duration-4):
        resized_obs = cv2.resize(ale.getScreenGrayscale(), (84,84), interpolation=cv2.INTER_AREA)
        all_obs.append(resized_obs)
        if i % 4 == 0:
            stack_tensor = TensorDict({"obs": np.array(all_obs[-4:])})
            action = nn_wrapper.query(stack_tensor)
            ale.act(input_to_action(str(action)))
        else:
            ale.act(input_to_action(str(action)))
        speed_list.append(ale.getRAM()[14])
        if len(speed_list) > 15 and sum(speed_list[-6:-1]) == 0:
            saveObservations(all_obs, Verdict.BAD, testDir)
            return Verdict.BAD
    saveObservations(all_obs, Verdict.GOOD, testDir)
    return Verdict.GOOD

def computeStateRanking(mdp_file, iteration):
    logger.info("Computing state ranking")
    tic()
    try:
        command = f"{tempest_binary} --prism {mdp_file} --buildchoicelab --buildstateval --build-all-labels --prop 'Rmax=? [C <= 1000]'"
        result = subprocess.run(command, shell=True, check=True)
        print(result)
    except Exception as e:
        print(e)
        sys.exit(-1)
    exec(f"mv action_ranking action_ranking_{iteration:03}")
    logger.info(f"Computing state ranking - DONE: took {toc()} seconds")

def fillStateRanking(file_name, match=""):
    logger.info(f"Parsing state ranking, {file_name}")
    tic()
    state_ranking = dict()
    try:
        with open(file_name, "r") as f:
            file_content = f.readlines()
        for line in file_content:
            if not "move=0" in line: continue
            ranking_value = float(re.search(r"Value:([+-]?(\d*\.\d+)|\d+)", line)[0].replace("Value:",""))
            if ranking_value <= 0.1:
                continue
            stateMapping = convert(re.findall(r"([a-zA-Z_]*[a-zA-Z])=(\d+)?", line))
            #print("stateMapping", stateMapping)
            choices = convert(re.findall(r"[a-zA-Z_]*(left|right|noop)[a-zA-Z_]*:(-?\d+\.?\d*)", line))
            choices = {key:float(value) for (key,value) in choices.items()}
            #print("choices", choices)
            #print("ranking_value", ranking_value)
            state = State(int(stateMapping["x"]), int(stateMapping["y"]), int(stateMapping["ski_position"]), int(stateMapping["velocity"])//2)
            #state = State(int(stateMapping["x"]), int(stateMapping["y"]), int(stateMapping["ski_position"]))
            value = StateValue(ranking_value, choices)
            state_ranking[state] = value
        logger.info(f"Parsing state ranking - DONE: took {toc()} seconds")
        return state_ranking
    except EnvironmentError:
        print("Ranking file not available. Exiting.")
        toc()
        sys.exit(-1)
    except:
        toc()

def createDisjunction(formulas):
    return " | ".join(formulas)

def clusterFormula(cluster):
    if len(cluster) == 0: return
    formulas = list()
    for state in cluster:
        formulas.append(f"(x={state[0].x} & y={state[0].y} & velocity={state[0].velocity} & ski_position={state[0].ski_position})")

    while len(formulas) > 1:
        formulas_tmp = [f"({formulas[i]} | {formulas[i+1]})" for i in range(0,len(formulas)//2)]
        if len(formulas) % 2 == 1:
            formulas_tmp.append(formulas[-1])
        formulas = formulas_tmp

    return "(" + formulas[0] + ")"

def clusterFormulaTrimmed(cluster):
    formula = ""
    states = [(s[0].x,s[0].y, s[0].ski_position, s[0].velocity) for s in cluster]
    #states = [(s[0].x,s[0].y, s[0].ski_position) for s in cluster]
    skiPositionGroup = defaultdict(list)
    for item in states:
        skiPositionGroup[item[2]].append(item)

    #todo add velocity here
    firstVelocity = True
    for skiPosition, skiPos_group in skiPositionGroup.items():
        formula += f"ski_position={skiPosition} & "
        velocityGroup = defaultdict(list)
        for item in skiPos_group:
            velocityGroup[item[3]].append(item)
        for velocity, velocity_group in velocityGroup.items():
            if firstVelocity:
                firstVelocity = False
            else:
                formula += " | "
            formula += f" (velocity={velocity} & "
            firstY = True
            yPosGroup = defaultdict(list)
            for item in velocity_group:
                yPosGroup[item[1]].append(item)
            for y, y_group in yPosGroup.items():
                if firstY:
                    firstY = False
                else:
                    formula += " | "
                sorted_y_group = sorted(y_group, key=lambda s: s[0])
                formula += f"( y={y} & ("
                current_x_min = sorted_y_group[0][0]
                current_x = sorted_y_group[0][0]
                x_ranges = list()
                for state in sorted_y_group[1:-1]:
                    if state[0] - current_x == 1:
                        current_x = state[0]
                    else:
                        x_ranges.append(f" ({current_x_min}<= x & x<={current_x})")
                        current_x_min = state[0]
                        current_x = state[0]
                x_ranges.append(f" ({current_x_min}<= x & x<={sorted_y_group[-1][0]})")
                formula += " | ".join(x_ranges)
                formula += ") )"
            formula += ")"
        return formula



def createBalancedDisjunction(indices, name):
    #logger.info(f"Creating balanced disjunction for {len(indices)} ({indices}) formulas")
    if len(indices) == 0:
        return f"formula {name} = false;\n"
    else:
        while len(indices) > 1:
            indices_tmp = [f"({indices[i]} | {indices[i+1]})" for i in range(0,len(indices)//2)]
            if len(indices) % 2 == 1:
                indices_tmp.append(indices[-1])
            indices = indices_tmp
        disjunction = f"formula {name} = " + " ".join(indices) + ";\n"
    return disjunction

def createUnsafeFormula(clusters):
    label = "label \"Unsafe\" = Unsafe;\n"
    formulas = ""
    indices = list()
    for i, cluster in enumerate(clusters):
        formulas += f"formula Unsafe_{i} = {clusterFormulaTrimmed(cluster)};\n"
        indices.append(f"Unsafe_{i}")
    return formulas + "\n" + createBalancedDisjunction(indices, "Unsafe")# + label

def createSafeFormula(clusters):
    label = "label \"Safe\" = Safe;\n"
    formulas = ""
    indices = list()
    for i, cluster in enumerate(clusters):
        formulas += f"formula Safe_{i} = {clusterFormula(cluster)};\n"
        indices.append(f"Safe_{i}")

    return formulas + "\n" + createBalancedDisjunction(indices, "Safe")# + label

def updatePrismFile(newFile, iteration, safeStates, unsafeStates):
    logger.info("Creating next prism file")
    tic()
    initFile = f"{newFile}_no_formulas.prism"
    newFile = f"{newFile}_{iteration:03}.prism"
    exec(f"cp {initFile} {newFile}", verbose=False)
    with open(newFile, "a") as prism:
        prism.write(createSafeFormula(safeStates))
        prism.write(createUnsafeFormula(unsafeStates))

    logger.info(f"Creating next prism file - DONE: took {toc()} seconds")


ale = ALEInterface()


#if SDL_SUPPORT:
#    ale.setBool("sound", True)
#    ale.setBool("display_screen", True)

# Load the ROM file
ale.loadROM(rom_file)

with open('all_positions_v2.pickle', 'rb') as handle:
    ramDICT = pickle.load(handle)
y_ram_setting = 60
x = 70


nn_wrapper = SampleFactoryNNQueryWrapper()

experiment_id = int(time.time())
init_mdp = "velocity_safety"
exec(f"mkdir -p images/testing_{experiment_id}", verbose=False)

markerSize = 1

imagesDir = f"images/testing_{experiment_id}"

def drawOntoSkiPosImage(states, color, target_prefix="cluster_", alpha_factor=1.0):
    #markerList = {ski_position:list() for ski_position in range(1,num_ski_positions + 1)}
    markerList = {(ski_position, velocity):list() for velocity in range(0, num_velocities + 1) for ski_position in range(1,num_ski_positions + 1)}
    for state in states:
        s = state[0]
        #marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
        marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'point {s.x},{s.y} '"
        markerList[(s.ski_position, s.velocity)].append(marker)
    for (pos, vel), marker in markerList.items():
        command = f"convert {imagesDir}/{target_prefix}_{pos:02}_{vel:02}_individual.png {' '.join(marker)} {imagesDir}/{target_prefix}_{pos:02}_{vel:02}_individual.png"
        exec(command, verbose=False)


def concatImages(prefix, iteration):
    images = [f"{imagesDir}/{prefix}_{pos:02}_{vel:02}_individual.png" for vel in range(0,num_velocities+1) for pos in range(1,num_ski_positions+1) ]
    for vel in range(0, num_velocities + 1):
        for pos in range(1, num_ski_positions + 1):
            command =  f"convert {imagesDir}/{prefix}_{pos:02}_{vel:02}_individual.png "
            command += f"-pointsize 10 -gravity NorthEast -annotate +8+0 'p{pos:02}v{vel:02}' "
            command += f"{imagesDir}/{prefix}_{pos:02}_{vel:02}_individual.png"
            exec(command, verbose=False)
    exec(f"montage {' '.join(images)} -geometry +0+0 -tile 8x9 {imagesDir}/{prefix}_{iteration}.png", verbose=False)
    #exec(f"sxiv {imagesDir}/{prefix}_{iteration}.png&", verbose=False)

def drawStatesOntoTiledImage(states, color, target, source="images/1_full_scaled_down.png", alpha_factor=1.0):
    """
    Useful to draw a set of states, e.g. a single cluster
    markerList = {1: list(), 2:list(), 3:list(), 4:list(), 5:list(), 6:list(), 7:list(), 8:list()}
    logger.info(f"Drawing {len(states)} states onto {target}")
    tic()
    for state in states:
        s = state[0]
        marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
        markerList[s.ski_position].append(marker)
    for pos, marker in markerList.items():
        command = f"convert {source} {' '.join(marker)} {imagesDir}/{target}_{pos:02}_individual.png"
        exec(command, verbose=False)
    exec(f"montage {imagesDir}/{target}_*_individual.png -geometry +0+0 -tile x1 {imagesDir}/{target}.png", verbose=False)
    logger.info(f"Drawing {len(states)} states onto {target} - Done: took {toc()} seconds")
    """

def drawClusters(clusterDict, target, iteration, alpha_factor=1.0):
    logger.info(f"Drawing clusters")
    tic()
    for velocity in range(0, num_velocities + 1):
        for ski_position in range(1, num_ski_positions + 1):
            source = "images/1_full_scaled_down.png"
            exec(f"cp {source} {imagesDir}/{target}_{ski_position:02}_{velocity:02}_individual.png", verbose=False)
    for _, clusterStates in clusterDict.items():
        color = f"{np.random.choice(range(256))}, {np.random.choice(range(256))}, {np.random.choice(range(256))}"
        drawOntoSkiPosImage(clusterStates, color, target, alpha_factor=alpha_factor)
    concatImages(target, iteration)
    logger.info(f"Drawing clusters - DONE: took {toc()} seconds")

def drawResult(clusterDict, target, iteration):
    logger.info(f"Drawing clusters")
    for velocity in range(0,num_velocities+1):
        for ski_position in range(1, num_ski_positions + 1):
            source = "images/1_full_scaled_down.png"
            exec(f"cp {source} {imagesDir}/{target}_{ski_position:02}_{velocity:02}_individual.png", verbose=False)
    for _, (clusterStates, result) in clusterDict.items():
        color = "100,100,100"
        if result == Verdict.GOOD:
            color = "0,200,0"
        elif result == Verdict.BAD:
            color = "200,0,0"
        drawOntoSkiPosImage(clusterStates, color, target, alpha_factor=0.7)
    concatImages(target, iteration)
    logger.info(f"Drawing clusters - DONE: took {toc()} seconds")

def _init_logger():
    logger = logging.getLogger('main')
    logger.setLevel(logging.INFO)
    handler = logging.StreamHandler(sys.stdout)
    formatter = logging.Formatter(       '[%(levelname)s] %(module)s - %(message)s')
    handler.setFormatter(formatter)
    logger.addHandler(handler)

def clusterImportantStates(ranking, iteration):
    logger.info(f"Starting to cluster {len(ranking)} states into clusters")
    tic()
    states = [[s[0].x,s[0].y, s[0].ski_position * 20, s[0].velocity * 20, s[1].ranking] for s in ranking]
    #states = [[s[0].x,s[0].y, s[0].ski_position * 30, s[1].ranking] for s in ranking]
    #kmeans = KMeans(n_clusters, random_state=0, n_init="auto").fit(states)
    dbscan = DBSCAN(eps=15).fit(states)
    labels = dbscan.labels_
    n_clusters = len(set(labels)) - (1 if -1 in labels else 0)
    logger.info(f"Starting to cluster {len(ranking)} states into clusters - DONE: took {toc()} seconds with {n_clusters} cluster")
    clusterDict = {i : list() for i in range(0,n_clusters)}
    for i, state in enumerate(ranking):
        if labels[i] == -1: continue
        clusterDict[labels[i]].append(state)
    drawClusters(clusterDict, f"clusters", iteration)
    return clusterDict

if __name__ == '__main__':
    _init_logger()
    logger = logging.getLogger('main')
    logger.info("Starting")
    n_clusters = 40
    testAll = False

    safeStates = list()
    unsafeStates = list()
    iteration = 0
    while True:
        updatePrismFile(init_mdp, iteration, safeStates, unsafeStates)
        computeStateRanking(f"{init_mdp}_{iteration:03}.prism", iteration)
        ranking = fillStateRanking(f"action_ranking_{iteration:03}")
        sorted_ranking = sorted( (x for x in ranking.items() if x[1].ranking > 0.1), key=lambda x: x[1].ranking)
        clusters = clusterImportantStates(sorted_ranking, iteration)

        if testAll: failingPerCluster = {i: list() for i in range(0, n_clusters)}
        clusterResult = dict()
        for id, cluster in clusters.items():
            num_tests = int(factor_tests_per_cluster * len(cluster))
            num_tests = 1
            #logger.info(f"Testing {num_tests} states (from {len(cluster)} states) from cluster {id}")
            randomStates = np.random.choice(len(cluster), num_tests, replace=False)
            randomStates = [cluster[i] for i in randomStates]

            verdictGood = True
            for state in randomStates:
                x = state[0].x
                y = state[0].y
                ski_pos = state[0].ski_position
                velocity = state[0].velocity
                #result = run_single_test(ale,nn_wrapper,x,y,ski_pos, duration=50)
                result = run_single_test(ale,nn_wrapper,x,y,ski_pos, velocity, duration=50)
                result = Verdict.BAD # TODO REMOVE ME!!!!!!!!!!!!!!
                if result == Verdict.BAD:
                    if testAll:
                        failingPerCluster[id].append(state)
                    else:
                        clusterResult[id] = (cluster, Verdict.BAD)
                        verdictGood = False
                        unsafeStates.append(cluster)
                        break
            if verdictGood:
                clusterResult[id] = (cluster, Verdict.GOOD)
                safeStates.append(cluster)
        logger.info(f"Iteration: {iteration:03} -\tSafe Results : {sum([len(c) for c in safeStates])} -\tUnsafe Results:{sum([len(c) for c in unsafeStates])}")
        if testAll: drawClusters(failingPerCluster, f"failing", iteration)

        #drawResult(clusterResult, "result", iteration)
        iteration += 1