def main(argv):
goal, mode = '', ''
nn_name, rf_name = [], []
number = 10
try:
opts, args = getopt.getopt(
argv, "s:r:n:m:e:",
["size=", "randomforest=", "neuralnetwork=", "mode=", "elements="])
except getopt.GetoptError:
print(
'Error. Command line structure: Main.py -s <size> -r <random forest model> -n <neural network model>'
'-m <[Learn, Compare]>, -e <number of elements to compare>]')
sys.exit(2)
for opt, arg in opts:
if opt in ('-s', '-size'):
goal = generate_goal(int(arg))
elif opt == '-r':
rf_name = arg.split(',')
elif opt == '-n':
nn_name = arg.split(',')
elif opt in ('-m', '--mode'):
mode = arg.lower()
elif opt in ('-e', '-elements'):
number = int(arg)
if goal == '':
goal = generate_goal(4)
if not rf_name and not nn_name:
print(
"Error. Please give the name for random forest model (rf <name>) or neural network model (nn <name>)"
)
sys.exit(0)
if mode in ('l', 'learn'):
learn(nn_name, rf_name, goal)
elif mode in ('c', 'compare'):
compare(number, nn_name, rf_name, goal)
else:
print("Error. Mode can be L (Learn), or C (Compare)")
sys.exit(0)
def test_generate_goal_6(self):
test_goal = generate_goal(6)
self.assertEqual(test_goal, self.goal_6)
def test_generate_goal_4(self):
test_goal = generate_goal(4)
self.assertEqual(test_goal, self.goal_4)
def test_generate_goal_5(self):
test_goal = generate_goal(5)
self.assertEqual(test_goal, self.goal_5)
def test_generate_goal_3(self):
test_goal = generate_goal(3)
self.assertEqual(test_goal, self.goal_3)