def __init__(self):
##CONST CODE AREA
self.CLIPS_FILE_LOAD_FAILED_CODE = 404
self.CLIPS_FILE_LOAD_SUCCESS_CODE = 200
self.codetype = sys.getfilesystemencoding()
##GLOBAL_AREA
self.file_pointers = 1 # sim.data file read position
self.m_nCount = 0
self.data_file_name = TEMP_FILE_PREFIX + 'test_flight_facts.dat'
self.clips_dribble_filename = TEMP_FILE_PREFIX + 'record.dat'
self.clips_env = clips.Environment()
self.engine = clips
self.filemodel = FileModel()
self.fact_filename = ''
## fact dataframe
self.data = np.array([])
self.data_header = np.array([])
# self.dataframe = pd.DataFrame
## mapper
self.mapper_list = [] # Template and slot mapping pair list
self.record_name = '' # Reasoning result record file name
print "\t\t\t\t-----------------------------------------------"
print "\t\t\t\t PID Tuning with Artificial Intelegence method"
print "\t\t\t\t Tower Copter Control"
print "\t\t\t\t M.Imam Muttaqin"
print "\t\t\t\t-----------------------------------------------"
print "\t\t\t\t Select Mode > 1.Automatic (use default-conf)"
print "\t\t\t\t > 2.Genetic Algorithm (Hard Tune)"
print "\t\t\t\t > 3.Neural Network (Soft Tune)"
print "\t\t\t\t > 4.TensorFlow (Soft Tune)"
print "\t\t\t\t > 5.NN Predict"
print "\t\t\t\t > 99.Exit"
i_mode = input("\t\t\t\t : ")
name_model = raw_input("Enter name of models: ")
file_model = FileModel(name_model)
if i_mode == 1:
ga(True)
nn()
elif i_mode == 2:
ga()
elif i_mode == 3:
nn()
elif i_mode == 4:
keras()
elif i_mode == 5:
nn_predict()
else:
sys.exit()