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,