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How to use set_data method in tempest

Best Python code snippet using tempest_python

RunController.py

Source:RunController.py

1# Author: Thomas C.F. Goolsby - tgoolsby@mit.edu2# This file was created in support of the CNCPT Thesis3# Fall 2020 - EM.THE45import cProfile6import datetime7import io8import os9import pickle10import pstats11import random12from pstats import SortKey1314import numpy as np1516from ArchitectureGeneration.Architecture import Architecture17from Simulation.Communication.Network import auto_network_architectures18from Simulation.DataManagement.PostProcessing import post_process19from Simulation.SimulationManager import SimulationManager20from Simulation.Utility.Constants import intialize_constants212223class RunController:24    """ 2526    """2728    def __init__(self, output_path=None, profile=False):29        """3031        :param output_path:32        :return:33        """34        if output_path is None:35            path = os.path.join(os.path.dirname(__file__), "..", 'Output')36            self.output_path = os.path.abspath(path)37        else:38            self.output_path = os.path.abspath(output_path)39        self.timestamp_format = "%Y-%m-%d-%H%M%S"40        self.seedstamp_format = "%d"41        self.SimulationManager = SimulationManager42        self.profile = profile4344        try:45            os.mkdir(self.output_path)46        except FileExistsError:47            pass4849    def run_set_CnCPT(self, CONOPCon, CompCon, LeadershipPriority, FixedArchGenerator, VariableArchInstance, controls,50                      seeds=[0], name=None,51                      constants=None):52        """5354        :param all_units:55        :param controls:56        :param seeds:57        :param name:58        :param constants:59        :return:60        """61        set_data = {}6263        if constants is None:64            constants = intialize_constants()6566        # Generate Top level directory67        if name is not None:68            output_path = os.path.join(self.output_path, name)69            try:70                os.mkdir(output_path)71            except FileExistsError:72                pass73        else:74            output_path = self.output_path7576        # Generate Timestamp level directory77        datestring = datetime.datetime.now().strftime(self.timestamp_format)78        output_path = os.path.join(output_path, datestring)79        try:80            os.mkdir(output_path)81        except FileExistsError:82            pass8384        # Run Seeds85        for seed in seeds:86            FixedArchUnits = FixedArchGenerator()87            VariableArch = Architecture.create_from_code(VariableArchInstance.ArchCode, CONOPCon, CompCon,88                                                         LeadershipPriority, VariableArchInstance.side,89                                                         VariableArchInstance.name)90            all_units = VariableArch.units + FixedArchUnits91            seed_data = self.run_seed(all_units, controls, constants, seed, output_path)92            set_data[seed] = seed_data93        data = {"score_mean": np.mean([set_data[seed]["score"] for seed in set_data]),94                "score_var": np.var([set_data[seed]["score"] for seed in set_data]),95                "vsm_ships_mean": np.mean([set_data[seed]["vsm_ships"] for seed in set_data]),96                "vsm_ships_var": np.var([set_data[seed]["vsm_ships"] for seed in set_data]),97                "vsm_aircraft_mean": np.mean([set_data[seed]["vsm_aircraft"] for seed in set_data]),98                "vsm_aircraft_var": np.var([set_data[seed]["vsm_aircraft"] for seed in set_data]),99                "vscm_ships_mean": np.mean([set_data[seed]["vscm_ships"] for seed in set_data]),100                "vscm_ships_var": np.var([set_data[seed]["vscm_ships"] for seed in set_data]),101                "vscm_aircraft_mean": np.mean([set_data[seed]["vscm_aircraft"] for seed in set_data]),102                "vscm_aircraft_var": np.var([set_data[seed]["vscm_aircraft"] for seed in set_data]),103                "vscm_blue_mean": np.mean([set_data[seed]["vscm_blue"] for seed in set_data]),104                "vscm_blue_var": np.var([set_data[seed]["vscm_blue"] for seed in set_data]),105                "fam_ships_mean": np.mean([set_data[seed]["fam_ships"] for seed in set_data]),106                "fam_ships_var": np.var([set_data[seed]["fam_ships"] for seed in set_data]),107                "fam_aircraft_mean": np.mean([set_data[seed]["fam_aircraft"] for seed in set_data]),108                "fam_aircraft_var": np.var([set_data[seed]["fam_aircraft"] for seed in set_data]),109                "facm_ships_mean": np.mean([set_data[seed]["facm_ships"] for seed in set_data]),110                "facm_ships_var": np.var([set_data[seed]["facm_ships"] for seed in set_data]),111                "facm_aircraft_mean": np.mean([set_data[seed]["facm_aircraft"] for seed in set_data]),112                "facm_aircraft_var": np.var([set_data[seed]["facm_aircraft"] for seed in set_data]),113                "facm_red_mean": np.mean([set_data[seed]["facm_red"] for seed in set_data]),114                "facm_red_var": np.var([set_data[seed]["facm_red"] for seed in set_data]),115                "individual_seed_data_mean": set_data}116        data["score_mean_variance"] = data["score_mean"] - ((2 * ((data["score_var"]) ** 2)) / 2.0)117        return data, output_path118119    def run_set(self, FixedArchGenerator, VariableArchGenerator, controls,120                seeds=[0], name=None,121                constants=None):122        """123        :param controls:124        :param seeds:125        :param name:126        :param constants:127        :return:128        """129        set_data = {}130131        if constants is None:132            constants = intialize_constants()133134        # Generate Top level directory135        if name is not None:136            output_path = os.path.join(self.output_path, name)137            try:138                os.mkdir(output_path)139            except FileExistsError:140                pass141        else:142            output_path = self.output_path143144        # Generate Timestamp level directory145        datestring = datetime.datetime.now().strftime(self.timestamp_format)146        output_path = os.path.join(output_path, datestring)147        try:148            os.mkdir(output_path)149        except FileExistsError:150            pass151152        # Run Seeds153        for seed in seeds:154            FixedArchUnits = FixedArchGenerator()155            VariableArchUnits = VariableArchGenerator()156            all_units = VariableArchUnits + FixedArchUnits157            seed_data = self.run_seed(all_units, controls, constants, seed, output_path)158            set_data[seed] = seed_data159160        data = {"score_mean": np.mean([set_data[seed]["score"] for seed in set_data]),161                "score_var": np.var([set_data[seed]["score"] for seed in set_data]),162                "vsm_ships_mean": np.mean([set_data[seed]["vsm_ships"] for seed in set_data]),163                "vsm_ships_var": np.var([set_data[seed]["vsm_ships"] for seed in set_data]),164                "vsm_aircraft_mean": np.mean([set_data[seed]["vsm_aircraft"] for seed in set_data]),165                "vsm_aircraft_var": np.var([set_data[seed]["vsm_aircraft"] for seed in set_data]),166                "vscm_ships_mean": np.mean([set_data[seed]["vscm_ships"] for seed in set_data]),167                "vscm_ships_var": np.var([set_data[seed]["vscm_ships"] for seed in set_data]),168                "vscm_aircraft_mean": np.mean([set_data[seed]["vscm_aircraft"] for seed in set_data]),169                "vscm_aircraft_var": np.var([set_data[seed]["vscm_aircraft"] for seed in set_data]),170                "vscm_blue_mean": np.mean([set_data[seed]["vscm_blue"] for seed in set_data]),171                "vscm_blue_var": np.var([set_data[seed]["vscm_blue"] for seed in set_data]),172                "fam_ships_mean": np.mean([set_data[seed]["fam_ships"] for seed in set_data]),173                "fam_ships_var": np.var([set_data[seed]["fam_ships"] for seed in set_data]),174                "fam_aircraft_mean": np.mean([set_data[seed]["fam_aircraft"] for seed in set_data]),175                "fam_aircraft_var": np.var([set_data[seed]["fam_aircraft"] for seed in set_data]),176                "facm_ships_mean": np.mean([set_data[seed]["facm_ships"] for seed in set_data]),177                "facm_ships_var": np.var([set_data[seed]["facm_ships"] for seed in set_data]),178                "facm_aircraft_mean": np.mean([set_data[seed]["facm_aircraft"] for seed in set_data]),179                "facm_aircraft_var": np.var([set_data[seed]["facm_aircraft"] for seed in set_data]),180                "facm_red_mean": np.mean([set_data[seed]["facm_red"] for seed in set_data]),181                "facm_red_var": np.var([set_data[seed]["facm_red"] for seed in set_data]),182                "individual_seed_data_mean": set_data}183        data["score_mean_variance"] = data["score_mean"] - ((2 * ((data["score_var"]) ** 2)) / 2.0)184        return data, output_path185186    def run_seed(self, all_units, controls, constants, seed, output_path):187        """188189        :param all_units:190        :param controls:191        :param constants:192        :param seed:193        :param output_path:194        :return:195        """196197        seed_string = self.seedstamp_format % seed198        output_path = os.path.join(output_path, seed_string)199        success = False200        while not success:201            try:202                os.mkdir(output_path)203            except FileExistsError:204                print('This Output Path is not Empty: {0}'.format(output_path))205            else:206                success = True207208        open(os.path.join(output_path, 'meta_data.txt'), "w").write(output_path)209210        networks = auto_network_architectures(all_units)211        SimulationManager = self.SimulationManager(all_units, networks, constants, output_path,212                                                   start_time=controls['start_time'],213                                                   end_time=controls['end_time'],214                                                   full_data_logging=controls["full_data_logging"])215216        # Seed217        random.seed(seed)218219        for unit in all_units:220            unit.register(SimulationManager, constants)221222        self.run(SimulationManager, controls)223224        seed_data = post_process(SimulationManager)225        if controls["full_data_logging"]:226            log_data = {"kill_log": SimulationManager.kill_log,227                        "isr_log": SimulationManager.isr_log,228                        "weapon_log": SimulationManager.weapon_log,229                        "drawdown_log": SimulationManager.drawdown_log}230            with open(os.path.join(SimulationManager.output_path, "Simulation_Logs.pkl"), 'wb') as f:231                pickle.dump(log_data, f)232        SimulationManager.data_logger.close_data_logger(SimulationManager)233        return seed_data234235    def run(self, simulation_manager, controls):236        """237238        :param simulation_manager:239        :param controls:240        :return:241        """242        if self.profile:243            pr = cProfile.Profile()244            pr.enable()245            simulation_manager.run(until=controls['end_time'])246            pr.disable()247            s = io.StringIO()248            sortby = SortKey.CUMULATIVE249            ps = pstats.Stats(pr, stream=s).sort_stats(sortby)250            ps.print_stats()251            print(s.getvalue())252        else:
...

diana_pad_gen.py

Source:diana_pad_gen.py

1import copy2string_set = ['0', '1', '2', '3', '4', '1', '0', '3', '2', None, '2', '3', '0', '1', None, '3', '2', '1', '0', None, '4', None, None, None, '0']3pair_set=['00', '01', '02', '03', '04', '10', '11', '12', '13', '14', '20', '21', '22', '23', '24', '30', '31', '32', '33', '34', '40', '41', '42', '43', '44']4init_set=[None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]5total_set=[init_set]6def printAllKLength(char_set, k):7    n = len(char_set)8    printAllKLengthRec(char_set, "", n, k)9def fill(x,y,ch,set_data):10  ch_int=int(ch)11  x_int=int(pair_set[5*x+y][0])12  y_int=int(pair_set[5*x+y][1])13  if set_data[5*x+y] or set_data[5*y+x] or set_data[5*x_int+ch_int] or set_data[5*ch_int+x_int] or set_data[5*y_int+ch_int] or set_data[5*ch_int+y_int] is not None:14    return False15  else:16    set_data[5*x_int+ch_int]=pair_set[5*x+y][1]17    set_data[5*ch_int+x_int]=pair_set[5*x+y][1]18    set_data[5*y_int+ch_int]=pair_set[5*x+y][0]19    set_data[5*ch_int+y_int]=pair_set[5*x+y][0]20    set_data[5*y+x]=ch21    set_data[5*x+y]=ch22    return True23def revert_fill(x,y,ch,set_data):24  ch_int=int(ch)25  x_int=int(pair_set[5*x+y][0])26  y_int=int(pair_set[5*x+y][1])27  set_data[5*x_int+ch_int]=None28  set_data[5*ch_int+x_int]=None29  set_data[5*y_int+ch_int]=None30  set_data[5*ch_int+y_int]=None31  set_data[5*y+x]=None32  set_data[5*x+y]=None33def find_empty(set_data):34  for i in range(25):35    if set_data[i] is None:36      x=i//537      y=i-5*x38      return (x,y)39  return None40def mapping(ch):41  if ch == "0":42    return "A"43  if ch == "1":44    return "B"45  if ch == "2":46    return "C"47  if ch == "3":48    return "D"49  if ch == "4":50    return "E"51  if ch is None:52    return "-"53def print_table(set_data):54  print(" ")55  for i in range(8):56    print("-",end="-")57  print("-")58  for i in ["|","  |","A","B","C","D","E"]:59    print(i,end=" ")60  print("|")61  for i in range(8):62    print("-",end="-")63  print("-")64  for i in range(5):65    print("|",end=" ")66    print(mapping(str(i)),"|",end=" ")67    for j in range(5):68      print(mapping(set_data[5*i+j]),end=" ")69    print("|")70    for j in range(8):71      print("-",end="-")72    print("-")73def solver():74  total_set=[[None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]]75  flagGlob=True76  while flagGlob:77    t_set=copy.deepcopy(total_set)78    for i in total_set:79      iter=copy.deepcopy(i)80      ans=find_empty(iter)81      if ans is None:82        flagGlob=False83        pass84      else:85        x,y=ans[0],ans[1]86        test=copy.deepcopy(iter)87        flag=True88        for j in ["0","1","2","3","4"]:89          dat=fill(x,y,j,iter)90          if dat:91            flag=False92            t_set.append(iter)93            iter=copy.deepcopy(test)94        t_set.remove(test)95    total_set=copy.deepcopy(t_set)      96  for i in total_set:97    print_table(i)98  print(len(total_set))99# The main recursive method100# to print all possible101# strings of length k102def printAllKLengthRec(char_set, prefix, n, k):103    global string_set104    # Base case: k is 0,105    # print prefix106    if k == 0:107        string_set.append(prefix)108        return109    # One by one add all characters110    # from set and recursively111    # call for k equals to k-1112    for i in range(n):113        # Next character of input added114        newPrefix = prefix + char_set[i]115        # k is decreased, because116        # we have added a new character117        printAllKLengthRec(char_set, newPrefix, n, k - 1)118for i in range(0,25):119  string_set.append(None)120#printAllKLength(["0","1","2","3","4"],2)121solver()122#iter=init_set123#dat=fill(0,0,"0",iter)124#print(iter)125#iter=string_set...

sweep_lm_data.py

Source:sweep_lm_data.py

1#!/usr/bin/env python32def set_data_based_on_shortname(args):3    def set_data(fmt, num_shards):4        if num_shards == 0:5            args.data = fmt.format(0)6        else:7            args.data = ":".join([fmt.format(i) for i in range(num_shards)])8    # mmap datasets9    if args.data == "CC-NEWS-en.v7.1":10        set_data("/private/home/myleott/data/data-bin/CC-NEWS-en.v7.1/shard{}", 10)11    elif args.data == "fb_posts":12        set_data("/data/tmp/fb_posts.en.2018-2019.bpe.mmap-bin/shard{}", 100)13    elif args.data == "fb_posts_gfs":14        set_data(15            "/mnt/vol/gfsai-flash2-east/ai-group/users/myleott/fb_posts/fb_posts.en.2018-2019.bpe.mmap-bin/shard{}",16            100,17        )18    elif args.data == "bookwiki_aml-mmap-bin":19        set_data("/data/tmp/bookwiki_aml-mmap-bin/shard{}", 5)20    elif args.data == "bookwiki_aml_CC-NEWS-en.v7.1":21        set_data("/data/tmp/bookwiki_aml_CC-NEWS-en.v7.1/shard{}", 5)22    # old datasets23    elif args.data == "CC-NEWS-en.v6":24        set_data("/private/home/myleott/data/data-bin/CC-NEWS-en.v6", 0)25    elif args.data == "CC-NEWS-en.v9":26        set_data(27            "/private/home/namangoyal/fairseq-py/data-bin/CC-NEWS-en.v9/shard{}", 10028        )29    elif args.data == "bookwiki":30        set_data("/private/home/myleott/data/data-bin/bookwiki.10shards/shard{}", 10)31    elif args.data == "bookwiki_full":32        set_data("/private/home/myleott/data/data-bin/bookwiki-bin", 0)33    elif args.data == "fb_posts_old":34        set_data("/data/tmp/mono.english.public.2018-2019.shard{}.sents.bpe-bin", 100)35    elif args.data == "fb_posts_gfs":36        set_data(37            "/mnt/vol/gfsai-flash2-east/ai-group/users/myleott/fb_posts/en/mono.english.public.2018-2019.shard{}.sents.bpe-bin",38            100,39        )40    elif args.data == "wmt19_en_news_docs":41        set_data(42            "/private/home/myleott/data/data-bin/wmt19_en_news_docs/wmt19_en_news_docs.bpe.shard{}",43            100,44        )45    else:46        set_data(args.data, 0)...

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