from get_csv_data import HandleData
data = HandleData(total_data=880,data_per_angle=110,num_angles=8)
antenna_data,label_data = data.get_synthatic_data(test_data=False)
data_test = HandleData(total_data=80, data_per_angle=10, num_angles=8)
antenna_data_test, label_data_test = data_test.get_synthatic_data(test_data=True)
data_test_noise = HandleData(total_data=120, data_per_angle=120, num_angles=8)
antenna_data_test_noise, label_data_test_noise = data_test_noise.get_synthatic_data(test_data=-1)
# DAE_out = getDAE([antenna_data,antenna_data_test,antenna_data_test_noise])
DAE_out = [genfromtxt('TrainDOA_Data.csv', delimiter=','),genfromtxt('TestDOA_Data.csv', delimiter=','),genfromtxt('TestDOA_Noise_Data.csv', delimiter=',')]
data.data_set = DAE_out[0]
antenna_data = DAE_out[0]
antenna_data_test = DAE_out[1]
data_test.data_set = DAE_out[1]
antenna_data_test_noise = DAE_out[2]
data_test_noise.data_set = DAE_out[2]
# np.savetxt("TrainDOA_Data.csv", DAE_out[0], delimiter=",")
# np.savetxt("TestDOA_Data.csv", DAE_out[1], delimiter=",")
# np.savetxt("TestDOA_Noise_Data.csv", DAE_out[2], delimiter=",")
#
# antenna_data = genfromtxt('TrainDOA_Data.csv', delimiter=',')
# data.data_set = antenna_data
#
return out_layer
if __name__ == "__main__":
data = HandleData(total_data=880, data_per_angle=110, num_angles=8)
antenna_data, label_data = data.get_synthatic_data(test_data=False)
data_test = HandleData(total_data=80, data_per_angle=10, num_angles=8)
antenna_data_test, label_data_test = data_test.get_synthatic_data(
test_data=True)
DAE_out = getDAE([
antenna_data, antenna_data_test
]) # get denoising autoencoder outputs for the train and test data
data.data_set = DAE_out[0]
antenna_data = DAE_out[0]
antenna_data_test = DAE_out[1]
data_test.data_set = DAE_out[1]
TRAIN = False
# Parameters
learning_rate = 0.0001
training_epochs = 2000
batch_size = 5
display_step = 1
# Network Parameters
n_hidden_1 = 12 # 1st layer number of features
n_hidden_2 = 12 # 2nd layer number of features