def __init__(self):
self.utils = Utilities()
self.validation = Validation()
self.entry = Entry()
self.menu = Menu()
self.results = list()
def __init__(self, config, hq): self.config = config self.ident = config.ident self.hq = hq self.state = 0 self.perm8_state = 0 self.stats = Stats(config, hq) self.utils = Utilities()
def main():
# Instantiate objects
config = Config()
fields = build_data()
utils = Utilities(fields, config)
agent = PPO(utils.total_fields, utils.total_fields, utils.field_indexes,
config)
# train on data
verify_network(agent, utils, config)
def main():
# Instantiate objects
agent_name = 'PPO'
config = Config(agent_name)
fields = build_data()
utils = Utilities(fields, config)
agent = PPO(utils.total_fields, utils.total_fields, utils.field_indexes,
config)
# train on data
train_network(agent, utils, config)
def feature_selection(data):
clf = LogisticRegression(max_iter=1000)
y = data["Outcome"].copy()
X = data.loc[:, ~data.columns.isin(['Outcome'])].copy()
num_attribs = [
"Age", "ContactsTotal", "DaysFromPrevAttempt", "PrevAttempts",
"CallDuration"
]
cat_attribs = [
"Job", "MaritalStatus", "EducationLevel", "ContactMeans",
"ContactMonth", "PrevOutcome"
]
ordinal_attribs = ["ContactDay"]
full_pipeline = ColumnTransformer([
("num", StandardScaler(), num_attribs),
("cat", OneHotEncoder(sparse=False), cat_attribs),
("ord", OrdinalEncoder(), ordinal_attribs)
])
X_p = full_pipeline.fit_transform(X)
rfecv = RFECV(estimator=clf, step=1, cv=StratifiedKFold(2), scoring='f1')
rfecv.fit(X_p, y)
# Plot number of features VS. cross-validation scores
plt.figure()
plt.xlabel("Number of features selected")
plt.ylabel("Cross validation score (nb of correct classifications)")
plt.plot(range(1, len(rfecv.grid_scores_) + 1), rfecv.grid_scores_)
plt.savefig("../plots/RFE.png")
plt.show()
print("Optimal number of features : %d" % rfecv.n_features_)
get_names = Utilities()
feature_names = get_names.get_column_names_from_ColumnTransformer(
full_pipeline)
res = list(compress(feature_names, rfecv.support_))
non_res = list(compress(feature_names, ~rfecv.support_))
print("The list with the optimal features is: ", str(res))
print("The list with non optimal features is: ", str(non_res))
indexes = [i for i, val in enumerate(rfecv.support_) if val]
with open("../models/optimal_features.txt", "wb") as fp:
pickle.dump(indexes, fp)
def run():
input_file_path = os.path.abspath(
os.path.join(os.path.dirname(__file__), 'input', 'inputPS4.txt'))
output_file_path = os.path.abspath(
os.path.join(os.path.dirname(__file__), 'output', 'outputPS4.txt'))
input_file = open(input_file_path, 'r')
output_file = open(output_file_path, 'w')
utils = Utilities(input_file)
input_data_list = utils.create_list_from_input_data()
for data in input_data_list:
if not data:
output_file.write("Empty or invalid row entered \n")
continue
if len(data) == 1:
output_file.write("Single element entered : " + str(data[0]) +
"\n")
continue
distribution_type = utils.get_distribution_type(data)
maxima_minima = utils.get_maxima_minima(distribution_type)
output_file.write(f"{distribution_type} {maxima_minima}\n")
def elevate(argv):
totalDomains = set([])
outputFileName = ''
targetDomain = ''
targetEmail = ''
partialOrgName = ''
checkEmails = False
verbose = False
try:
(opts, args) = getopt.getopt(argv, 'h:o:d:e:n:v')
except getopt.GetoptError:
print('elevate.py -o <outputfile> -d <domain name> -e <email address> -n <partial name> -v <verbose mode>')
sys.exit(2)
for (opt, arg) in opts:
if opt == '-h':
print('elevate.py -o <outputfile>')
sys.exit()
elif opt in '-o':
outputFileName = arg
elif opt in '-d':
targetDomain = arg
elif opt in '-e':
targetEmail = arg
elif opt in '-n':
partialOrgName = arg
elif opt in '-v':
verbose = True
if(outputFileName == ''):
raise Exception("Output file must be set with '-o' flag")
utils = Utilities()
if(targetDomain != ''):
totalDomains = totalDomains.union(whoisSearch(utils,targetDomain,verbose))
if(partialOrgName != ''):
totalDomains = totalDomains.union(asnSearch(utils,partialOrgName,verbose))
if(targetEmail != ''):
totalDomains = totalDomains.union(emailSearch(utils,targetEmail,verbose))
print(str(len(totalDomains)) + " unique domain names discovered.")
utils.writeToFile(list(totalDomains),outputFileName)
from test_data import build_data
sys.path.append('/Users/morgan/Code/RouteMuse/')
# sys.path.append('/home/kenpachi/Code/RouteMuse/')
from utils import Utilities
from config import Config
"""
Unit tests for all functions
seed the Utility class with the relevant data
"""
config = Config()
keys = config.keys
fields = build_data()
utils = Utilities(fields,keys)
class TestConversion(unittest.TestCase):
def test(self):
print('utils route_array',utils.route_array)
self.assertEqual(len(utils.field_indexes), 12)
class TestRandomRoutes(unittest.TestCase):
def test(self):
ran_routes = utils.gen_random_routes(5)
self.assertEqual(ran_routes.shape[0], 5)
class TestReadable(unittest.TestCase):
def test(self):
ran_routes = utils.gen_random_routes(5)
readable_routes = [utils.convert_route_to_readable(route) for route in ran_routes]
def test_return_correct_size_of_model(self):
utils = Utilities()
json_ob = utils.chunk_json_object(0, 2)
assertEqual(len(json_ob), 2)
def __init__(self):
super().__init__()
self.utils = Utilities()
self.validation = Validation()
def access_log(self):
'''Method containing the main loop to run the program.'''
menu = Menu()
entry = Entry()
utils = Utilities()
search = Search()
validation = Validation()
current_menu = constants.MAIN_MENU
if not os.path.exists(constants.FILENAME):
with open(constants.FILENAME, 'a') as file:
writer = csv.DictWriter(file, fieldnames=constants.FIELDNAMES)
writer.writeheader()
while True:
utils.clear_screen()
menu.display(current_menu)
choice = menu.get_user_choice()
if current_menu == constants.MAIN_MENU:
if not validation.is_valid_input(choice, menu='csq'):
continue
if choice == 'c':
utils.clear_screen()
entry.create_new_entry()
elif choice == 's':
current_menu = constants.SEARCH_MENU
elif choice == 'q':
break
elif current_menu == constants.SEARCH_MENU:
if not validation.is_valid_input(choice, menu='edtprm'):
continue
if choice == 'e':
search.search('Please enter a date to search: ', 'date')
elif choice == 'd':
search.search(
'Please enter two comma separated dates to search'
'\n(ex. 01/15/1982, 12/11/2017): ', 'date_range')
elif choice == 't':
search.search(
'Please enter a time to search: ', 'time_spent')
elif choice == 'p':
search.search(
'Please enter a word or phrase to search: ',
'exact_match')
elif choice == 'r':
search.search(
'Please enter a word or phrase to search: ', 'regex')
elif choice == 'm':
current_menu = constants.MAIN_MENU
