def get_id_prediction(arb_index):
file = "temp_file.txt" # read frames collected by frame fetcher which collects frames from a file in the datasets
Arb_id = temp_frame_extractor.prepare_dataset(file, arbitration_id=all_ids[
arb_index]) # returns two consecutive packets of the same arbitration IDs
bit_0, bit_1, bit_2, bit_3, bit_4, bit_5, bit_6, bit_7, bit_8, bit_9, bit_10, bit_11, bit_12, bit_13, bit_14, bit_15, bit_16, bit_17, bit_18, \
bit_19, bit_20, bit_21, bit_22, bit_23, bit_24, bit_25, bit_26, bit_27, bit_28, bit_29, bit_30, bit_31, bit_32, bit_33, bit_34, bit_35, bit_36, \
bit_37, bit_38, bit_39, bit_40, bit_41, bit_42, bit_43, bit_44, bit_45, bit_46, bit_47, bit_48, bit_49, bit_50, bit_51, bit_52, bit_53, bit_54, \
bit_55, bit_56, bit_57, bit_58, bit_59, bit_60, bit_61, bit_62, bit_63 = bits_extractor.extract_all_bits(Arb_id)
arb_id = predictor.ready_for_testing(bit_0, bit_1, bit_2, bit_3, bit_4, bit_5, bit_6, bit_7,
bit_8, bit_9, bit_10, bit_11, bit_12, bit_13, bit_14,
bit_15, bit_16, bit_17, bit_18, bit_19, bit_20, bit_21,
bit_22, bit_23, bit_24, bit_25, bit_26, bit_27, bit_28,
bit_29, bit_30, bit_31, bit_32, bit_33, bit_34, bit_35,
bit_36, bit_37, bit_38, bit_39, bit_40, bit_41, bit_42,
bit_43, bit_44, bit_45, bit_46, bit_47, bit_48, bit_49,
bit_50, bit_51, bit_52, bit_53, bit_54, bit_55, bit_56,
bit_57, bit_58, bit_59, bit_60, bit_61, bit_62, bit_63,
batch_size=batch_size,
model_dir='../../trained_models/' + str(
arb_index) + '/training_checkpoints') # this folder is not available unless all arbitration IDs are trained first
return arb_id[0]
file = open("minatobus-candump-2019-05-08_030759.log")
_, train_data = frame_reader_from_file.prepare_dataset(
file,
min_index=train_min_index,
max_index=train_max_index,
arbitration_id=all_ids[0])
val_data = train_data[int(len(train_data) * 0.8):]
train_data = train_data[:int(len(train_data) * 0.8)]
# bits extraction from packets for training
bit_0, bit_1, bit_2, bit_3, bit_4, bit_5, bit_6, bit_7, bit_8, bit_9, bit_10, bit_11, bit_12, bit_13, bit_14, bit_15, bit_16, bit_17, bit_18, \
bit_19, bit_20, bit_21, bit_22, bit_23, bit_24, bit_25, bit_26, bit_27, bit_28, bit_29, bit_30, bit_31, bit_32, bit_33, bit_34, bit_35, bit_36, \
bit_37, bit_38, bit_39, bit_40, bit_41, bit_42, bit_43, bit_44, bit_45, bit_46, bit_47, bit_48, bit_49, bit_50, bit_51, bit_52, bit_53, bit_54, \
bit_55, bit_56, bit_57, bit_58, bit_59, bit_60, bit_61, bit_62, bit_63 = bits_extractor.extract_all_bits(
np.array(train_data))
# bits extraction from packets for validation
val_bit_0, val_bit_1, val_bit_2, val_bit_3, val_bit_4, val_bit_5, val_bit_6, val_bit_7, val_bit_8, val_bit_9, val_bit_10, \
val_bit_11, val_bit_12, val_bit_13, val_bit_14, val_bit_15, val_bit_16, val_bit_17, val_bit_18, val_bit_19, val_bit_20, \
val_bit_21, val_bit_22, val_bit_23, val_bit_24, val_bit_25, val_bit_26, val_bit_27, val_bit_28, val_bit_29, val_bit_30, \
val_bit_31, val_bit_32, val_bit_33, val_bit_34, val_bit_35, val_bit_36, val_bit_37, val_bit_38, val_bit_39, val_bit_40, \
val_bit_41, val_bit_42, val_bit_43, val_bit_44, val_bit_45, val_bit_46, val_bit_47, val_bit_48, val_bit_49, val_bit_50, \
val_bit_51, val_bit_52, val_bit_53, val_bit_54, val_bit_55, val_bit_56, val_bit_57, val_bit_58, val_bit_59, val_bit_60, \
val_bit_61, val_bit_62, val_bit_63 = bits_extractor.extract_all_bits(np.array(val_data))
for bs_siz in range(len(par_bs_size)):
for duratio in range(len(par_duration)):
train_data = dataset_creator_new.ready_for_training(
bit_0,
bit_1,
freq = list(all_ids_length.values())
duration = 1 # detection duration
frames_fetcher.fetch(
duration
) # fetch packets from the terminal that is playing the can dataset
batch_size = 1 # we need to change the batch size to 1 inorder to make predictions
#===================================================
file = open("temp_file.txt", "r") #read frames collected by frame fetcher
Arb_id_0 = read_temp_frame.prepare_dataset(
file, arbitration_id=all_ids[0]) # total, sequencelength, 64 # 700,68,64
file.close()
bit_0, bit_1, bit_2, bit_3, bit_4, bit_5, bit_6, bit_7, bit_8, bit_9, bit_10, bit_11, bit_12, bit_13, bit_14, bit_15, bit_16, bit_17, bit_18, \
bit_19, bit_20, bit_21, bit_22, bit_23, bit_24, bit_25, bit_26, bit_27, bit_28, bit_29, bit_30, bit_31, bit_32, bit_33, bit_34, bit_35, bit_36, \
bit_37, bit_38, bit_39, bit_40, bit_41, bit_42, bit_43, bit_44, bit_45, bit_46, bit_47, bit_48, bit_49, bit_50, bit_51, bit_52, bit_53, bit_54, \
bit_55, bit_56, bit_57, bit_58, bit_59, bit_60, bit_61, bit_62, bit_63 = bits_extractor.extract_all_bits(Arb_id_0)
arb_id_0 = testing_dataset_creator_with_time.ready_for_testing(
bit_0,
bit_1,
bit_2,
bit_3,
bit_4,
bit_5,
bit_6,
bit_7,
bit_8,
bit_9,
bit_10,
bit_11,
bit_12,