def get_hanabi_partners(setting, partner_type): partners_dict = { "": { "ppo": { "train": [ "output/hanabi_n=4_run=1240_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1241_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1242_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1243_netsz=500_mreg=0.00", ], "test": [ "output/hanabi_n=4_run=1244_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1245_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1246_netsz=500_mreg=0.00", "output/hanabi_n=4_run=1247_netsz=500_mreg=0.00", ] } } } partners = partners_dict[setting][partner_type] if partner_type == "ppo": train_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["train"] ] test_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["test"] ] return train_partners, test_partners
def setUp(self): player1 = Player("bob") player2 = Player("sue") partner1 = Partner(player1,player2) player3 = Player("ralph") player4 = Player("greg") partner2 = Partner(player3,player4) self.table = Table("Awesome",partner1,partner2)
def getTable(self,table_name,name1,name2,name3,name4): player1 = Player(name1) player2 = Player(name2) player3 = Player(name3) player4 = Player(name4) partner1 = Partner(player1,player2) partner2 = Partner(player3,player4) return Table(table_name,partner1,partner2)
def __init__(self, machine_id, database, ui): Partner.__init__(self, ui) self.machine_id = machine_id self.database = database self.text_format = XMLFormat() self.server_info = {} self.con = None self.behind_proxy = None # Explicit variable for testability. self.proxy = None
def __init__(self, machine_id, host, port, ui): self.machine_id = machine_id WSGIServer.__init__(self, (host, port), WSGIRequestHandler) self.set_app(self.wsgi_app) Partner.__init__(self, ui) self.text_format = XMLFormat() self.stopped = False self.sessions = {} # {session_token: session} self.session_token_for_user = {} # {user_name: session_token}
def __init__(self, machine_id, port, ui): self.machine_id = machine_id # We only use 1 thread, such that subsequent requests don't run into # SQLite access problems. from cherrypy import wsgiserver self.wsgi_server = wsgiserver.CherryPyWSGIServer\ (("0.0.0.0", port), self.wsgi_app, server_name="localhost", numthreads=1, timeout=1000) Partner.__init__(self, ui) self.text_format = XMLFormat() self.sessions = {} # {session_token: session} self.session_token_for_user = {} # {user_name: session_token}
def create_Partner(iterate_dataset_name): """Instantiate partner object""" part = Partner(partner_id=0) dataset_name = iterate_dataset_name if dataset_name == "cifar10": (x_train, y_train), (x_test, y_test) = cifar10.load_data() part.y_train = data_cf.preprocess_dataset_labels(y_train) if dataset_name == "mnist": (x_train, y_train), (x_test, y_test) = mnist.load_data() part.y_train = data_mn.preprocess_dataset_labels(y_train) yield part
def create_partners_list(dataset_name, partners_count): partners_list = [] for i in range(partners_count): part = Partner(partner_id=i) if dataset_name == "cifar10": (x_train, y_train), (x_test, y_test) = cifar10.load_data() part.y_train = data_cf.preprocess_dataset_labels(y_train) if dataset_name == "mnist": (x_train, y_train), (x_test, y_test) = mnist.load_data() part.y_train = data_mn.preprocess_dataset_labels(y_train) partners_list.append(part) return partners_list
def instantiate_scenario_partners(self): """Create the partners_list - self.partners_list should be []""" if self.partners_list != []: raise Exception("self.partners_list should be []") self.partners_list = [Partner(i) for i in range(self.partners_count)]
def process_data(json_file): """ Processes the JSON file returned from the GET request, finds the minimum most consecutive dates for each country, and manipulates the data into a format ready for submission """ #dictionary with the keys set as countries and the values set as the "Results" class results_dic = {} #dictionary with keys set as countries and the values as partners from the respective country country_dic = defaultdict(list) for p in json_file['partners']: p = Partner(p) country_dic[p.country].append(p) for country in country_dic: available_dic = defaultdict(list) for partner in country_dic[country]: #finds consecutive dates of each individual partner and uses those dates as keys for a dictionary available_date = partner.get_consecutive() for dates in available_date: available_dic[dates].append(partner.email) #first sort maintains the minimum order of dates res = sorted(available_dic.items(), key=lambda item: item[0][0]) #second sort finds the maximum amount of attendees respective to minimum date res.sort(key=lambda item: len(item[1]), reverse=True) #adds result to "Results" class results_dic[country] = Results(res, country) return results_dic
def get_arms_human_partners(setting, partner_type): partners_dict = { "": { "fixed": { "train": [ [0, 2, 1], [0, 2, 1], [0, 2, 1], [0, 2, 1], [0, 3, 3], [0, 2, 1], [0, 2, 1], [0, 2, 1], [0, 2, 1], [0, 3, 3], [0, 2, 1], [0, 2, 1], ], "test": [ [0, 2, 1], [0, 3, 3], [0, 2, 1], [0, 3, 3], [0, 3, 1], [0, 2, 1], [0, 3, 3], [0, 2, 1], [0, 2, 1], [0, 3, 1], ], }, }, } partners = partners_dict[setting][partner_type] if partner_type == "fixed": train_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["train"] ] test_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["test"] ] if partner_type == "ppo": exit(1) return train_partners, test_partners
class TestPartner(unittest.TestCase): def setUp(self): player1 = Player("bob") player2 = Player("sue") self.partner = Partner(player1, player2) def testGetPlayers(self): players = self.partner.getPlayers() self.assertEqual(players[0].getName(), "bob") self.assertEqual(players[1].getName(), "sue") def testToString(self): strung = str(self.partner) self.assertEqual(strung, "Partners (bob,sue)")
def to_partner(partner): id = partner['id'] tradingName = partner['tradingName'] ownerName = partner['ownerName'] document = partner['document'] address = json.dumps(partner['address']) coverageArea = json.dumps(partner['coverageArea']) return Partner( id=id, tradingName=tradingName, ownerName=ownerName, document=document, address=address, coverageArea=coverageArea )
from partner import Partner from create_partner import CreatePartner p = CreatePartner() partner = Partner.from_dict({ 'owner_name': 'MnR', 'tranding_name': 'MnR', 'document': 0, 'address': [16, 16] }) print(' '.join([str(point) for point in partner.address])) result = p.set_data(partner) print(result)
def process_data(data): country_list = [] # this nested dictionary maintains a relationship of # countries -> dictionary of dates -> set of people available at those dates country_dates_attendees = dict() # put all the relationship from the data we got into our dictionary for p in data['partners']: person = Partner(p) if person.country not in country_dates_attendees: country_dates_attendees[person.country] = dict() for date in person.dates: if date not in country_dates_attendees[person.country]: country_dates_attendees[person.country][date] = set() country_dates_attendees[person.country][date].add(person) for country_name, dates_attendees in country_dates_attendees.items(): # the dates need to be in order to check for consecutive dates sorted_dates = sorted(dates_attendees.keys()) # variables to keep track of the dates where attendees are maximized most_attendees_count = float('-inf') most_attendees_day = None most_attendees = set() for index in xrange(len(sorted_dates[:-1])): # raw string dates raw_curr_date = sorted_dates[index] raw_next_date = sorted_dates[index + 1] # parsed into python datetime objects for easier comparison curr_date = parse(raw_curr_date) next_date = parse(raw_next_date) curr_attendees = dates_attendees[raw_curr_date] next_attendees = dates_attendees[raw_next_date] # check if next date is consecutive if not skip to next if next_date - curr_date != datetime.timedelta(1): continue # check the number of attendees that are in both dates using set intersection attendees = curr_attendees & next_attendees attendees_count = len(attendees) # update the most attendees count if the count is greater # OR if the count is the same and the current date is earlier if attendees_count > most_attendees_count or \ (attendees_count == most_attendees_count and raw_curr_date < most_attendees_day): most_attendees_count = attendees_count most_attendees_day = raw_curr_date most_attendees = attendees # create a new country result object and add it to the country list country = Country() country.name = country_name if most_attendees_count > 0: country.start_date = most_attendees_day for person in most_attendees: country.add_attendee(person) country_list.append(country) return country_list
def test_shuffle_labels_type(self): """shuffle_labels should be a numpy.ndarray""" with pytest.raises(TypeError): part = Partner(partner_id=0) part.shuffle_labels(part)
from flask import Flask, url_for, request from partner import Partner app = Flask(__name__) manager = Partner() @app.route('/') def index(): return 'Welcome, Starbucks! :) ' @app.route('/get_order', methods=['POST']) def get_order(): order_info = request.get_json() ordered_menu = manager.take_order(order_info) # return str(ordered_menu) return 'total_price: {}, total_time: {}'.format(ordered_menu['price'], ordered_menu['time'])
def setUp(self): player1 = Player("bob") player2 = Player("sue") self.partner = Partner(player1, player2)
def test_corrupt_labels_type(self): """partner.y_train should be a numpy.ndarray""" with pytest.raises(TypeError): part = Partner(partner_id=0) part.corrupt_labels()
def get_blocks_partners(setting, partner_type): partners_dict = { "": { "fixed": { "train": [ [1, 3, 0, 2], # clockwise [2, 0, 3, 1], # counter-clockwise [3, 2, 1, 0], # diagonal ], "test": [ [1, 0, 3, 2], [2, 3, 1, 0], [3, 2, 0, 1], [1, 2, 3, 0], [2, 3, 0, 1], [3, 0, 1, 2], ], "inverttrain": [ [1, 3, 0, 2], # clockwise [2, 0, 3, 1], # counter-clockwise [3, 2, 1, 0], # diagonal ], "inverttest": [ [1, 0, 3, 2], [2, 3, 1, 0], [3, 2, 0, 1], ], }, "ppo": { "train": [ "output/blocks_n=2_run=1230_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1231_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1232_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1233_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1234_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1235_vis1=1_vis2=3_onesided=0_mreg=0.00", ], "test": [ "output/blocks_n=2_run=1240_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1241_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1242_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1243_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1244_vis1=1_vis2=3_onesided=0_mreg=0.00", "output/blocks_n=2_run=1245_vis1=1_vis2=3_onesided=0_mreg=0.00", ] } } } partners = partners_dict[setting][partner_type] if partner_type == "fixed": train_partners = [ Partner(BlocksPermutationPartnerPolicy(perm=perm)) for perm in partners["train"] ] test_partners = [ Partner(BlocksPermutationPartnerPolicy(perm=perm)) for perm in partners["test"] ] inverttrain_partners = [ Partner(BlocksPermutationPartnerPolicy(perm=perm)) for perm in partners["inverttrain"] ] inverttest_partners = [ Partner(BlocksPermutationPartnerPolicy(perm=perm)) for perm in partners["inverttest"] ] if partner_type == "ppo": train_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["train"] ] test_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["test"] ] inverttrain_partners = None inverttest_partners = None return train_partners, test_partners, inverttrain_partners, inverttest_partners
beta_IR = 0.01 beta_SR = 0.01 beta_SV = 0.01 beta_PI = 0.01 beta_IV = 0.01 beta_RV = 0.01 beta_condom = 0.000001 beta_SI2 = beta beta_II2 = 0.0 beta_RI2 = beta_IR beta_VI2 = beta_IV phi_V = phi phi_T = 0.95 population = Person.make_population(N) partner_nwk = Partner(population) filename = '' # Default file name to export (.csv). Change when use prompt 'export' cmd. mode_master_list = [] # All objects should add into mode_master_list mode01 = mode.Mode01(population, partner_nwk) mode02 = mode.Mode02(population) mode04 = mode.Mode04(population, partner_nwk) mode05 = mode.Mode05(population, partner_nwk) mode06 = mode.Mode06(population, partner_nwk) mode21 = mode.Mode21(population, partner_nwk) mode31 = mode.Mode31(population) mode51 = mode.Mode51(population, partner_nwk) mode52 = mode.Mode52(population, partner_nwk) mode_master_list = [mode01, mode02, mode04, mode05, mode06, mode21, mode31]
import time from counter import Counter from partner import Partner if __name__ == "__main__": partner = Partner("partner@localhost", "password") partner_fut = partner.start() partner_fut.result() counter = Counter("counter@localhost", "password") counter_fut = counter.start() counter_fut.result() while not (counter.behaviour.is_killed() and partner.behaviour.is_killed()): try: time.sleep(1) except KeyboardInterrupt: break counter.stop() partner.stop()
def set_PPO_partners(self, partner_model_paths: List[str]): self.set_partners(partners=[ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partner_model_paths ])
def get_arms_partners(setting, partner_type): partners_dict = { "n4m0": { "fixed": { "train": [ [0, 1, 2, 3], [4, 1, 6, 7], [0, 5, 2, 7], [4, 5, 6, 3], ], "test": [ [0, 1, 2, 7], [4, 1, 6, 3], [0, 5, 2, 3], [4, 5, 6, 7], ], "inverttrain": [ [0, 1, 2, 7], [4, 1, 6, 3], [0, 5, 2, 3], [4, 5, 6, 7], ], "inverttest": [ [0, 1, 2, 7], [4, 1, 6, 3], [0, 5, 2, 3], [4, 5, 6, 7], ], }, "ppo": { "train": [ "output/arms_n=4_m=0_run=1240_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1241_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1242_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1243_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1244_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1245_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1246_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1247_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1248_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1249_netsz=030_mreg=0.00", ], "test": [ "output/arms_n=4_m=0_run=1230_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1231_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1232_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1233_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1234_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1235_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1236_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1237_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1238_netsz=030_mreg=0.00", "output/arms_n=4_m=0_run=1239_netsz=030_mreg=0.00", ] } }, "n4m1": { "fixed": { "train": [ [0, 1, 2, 3], [0, 1, 6, 7], [0, 5, 2, 7], [0, 5, 6, 3], ], "test": [ [0, 1, 2, 7], [0, 1, 6, 3], [0, 5, 2, 3], [0, 5, 6, 7], ], "inverttrain": [ [4, 1, 2, 3], [4, 1, 6, 7], [4, 5, 2, 7], [4, 5, 6, 3], ], "inverttest": [ [4, 1, 2, 7], [4, 1, 6, 3], [4, 5, 2, 3], [4, 5, 6, 7], ], }, "ppo": { "train": [ "output/arms_n=4_m=1_run=1240_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1241_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1242_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1243_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1244_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1245_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1246_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1247_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1248_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1249_netsz=030_mreg=0.00", ], "test": [ "output/arms_n=4_m=1_run=1230_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1231_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1232_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1233_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1234_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1235_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1236_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1237_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1238_netsz=030_mreg=0.00", "output/arms_n=4_m=1_run=1239_netsz=030_mreg=0.00", ] } }, "n4m2": { "fixed": { "train": [ [0, 1, 2, 3], [0, 1, 6, 7], [0, 1, 2, 7], [0, 1, 6, 3], ], "test": [ [0, 1, 2, 7], [0, 1, 6, 3], [0, 1, 2, 3], [0, 1, 6, 7], ], "inverttrain": [ [4, 5, 2, 3], [4, 5, 6, 7], [4, 5, 2, 7], [4, 5, 6, 3], ], "inverttest": [ [4, 5, 2, 7], [4, 5, 6, 3], [4, 5, 2, 3], [4, 5, 6, 7], ], }, "ppo": { "train": [ "output/arms_n=4_m=2_run=1240_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1241_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1242_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1243_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1244_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1245_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1246_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1247_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1248_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1249_netsz=030_mreg=0.00", ], "test": [ "output/arms_n=4_m=2_run=1230_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1231_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1232_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1233_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1234_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1235_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1236_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1237_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1238_netsz=030_mreg=0.00", "output/arms_n=4_m=2_run=1239_netsz=030_mreg=0.00", ] } }, "n4m3": { "fixed": { "train": [ [0, 1, 2, 3], [0, 1, 2, 7], [0, 1, 2, 7], [0, 1, 2, 3], ], "test": [ [0, 1, 2, 7], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 7], ], "inverttrain": [ [4, 5, 6, 3], [4, 5, 6, 7], [4, 5, 6, 7], [4, 5, 6, 3], ], "inverttest": [ [4, 5, 6, 7], [4, 5, 6, 3], [4, 5, 6, 3], [4, 5, 6, 7], ], }, "ppo": { "train": [ "output/arms_n=4_m=3_run=1240_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1241_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1242_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1243_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1244_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1245_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1246_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1247_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1248_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1249_netsz=030_mreg=0.00", ], "test": [ "output/arms_n=4_m=3_run=1230_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1231_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1232_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1233_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1234_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1235_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1236_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1237_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1238_netsz=030_mreg=0.00", "output/arms_n=4_m=3_run=1239_netsz=030_mreg=0.00", ] } }, "n4m4": { "fixed": { "train": [ [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], ], "test": [ [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], ], "inverttrain": [ [4, 5, 6, 7], [4, 5, 6, 7], [4, 5, 6, 7], [4, 5, 6, 7], ], "inverttest": [ [4, 5, 6, 7], [4, 5, 6, 7], [4, 5, 6, 7], [4, 5, 6, 7], ], }, "ppo": { "train": [ "output/arms_n=4_m=4_run=1240_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1241_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1242_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1243_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1244_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1245_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1246_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1247_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1248_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1249_netsz=030_mreg=0.00", ], "test": [ "output/arms_n=4_m=4_run=1230_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1231_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1232_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1233_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1234_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1235_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1236_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1237_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1238_netsz=030_mreg=0.00", "output/arms_n=4_m=4_run=1239_netsz=030_mreg=0.00", ] } }, } partners = partners_dict[setting][partner_type] if partner_type == "fixed": train_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["train"] ] test_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["test"] ] inverttrain_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["inverttrain"] ] inverttest_partners = [ Partner(ArmsPartnerPolicy(perm=perm)) for perm in partners["inverttest"] ] if partner_type == "ppo": train_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["train"] ] test_partners = [ Partner(PPOPartnerPolicy(pmpath)) for pmpath in partners["test"] ] inverttrain_partners = None inverttest_partners = None return train_partners, test_partners, inverttrain_partners, inverttest_partners
if up: flags += 'u' if down: flags += 'd' print(flags) pygame.init() screen = pygame.display.set_mode([SCREEN_WIDTH, SCREEN_HEIGHT]) pygame.display.set_caption('Player Test') all_sprites = pygame.sprite.Group() player = Player(100, 50) partner = Partner(50, 50, player) #add line about player.walls later all_sprites.add(player) all_sprites.add(partner) clock = pygame.time.Clock() done = False while not done: for event in pygame.event.get(): if event.type == pygame.QUIT: done = True elif event.type == pygame.KEYDOWN: if event.key == pygame.K_LEFT: if not right and not up and not down:
def __init__(self, machine_id, database, ui): Partner.__init__(self, ui) self.machine_id = machine_id self.database = database self.text_format = XMLFormat() self.server_info = {}