plt.ylabel('gap (m)')
plt.subplot(2, 1, 2)
plt.plot(df['time_rel'], df['axle_torque_ch_0_V'])
plt.plot(df['time_rel'], df['axle_torque_ch_1_V'])
plt.ylabel('torque voltages')
plt.xlabel('time (sec)')
plt.legend()
plt.show()
if __name__ == "__main__":
# Read dbc files and loaded into the can_logger_function
base_path = dirname(abspath(__file__))
leddar = join(base_path, 'dbc_files/leddar_vu_8_segments.dbc')
car = join(base_path, 'dbc_files/ford_fusion_2011.dbc')
leddar_dbc = cantools.database.load_file(leddar)
car_dbc = cantools.database.load_file(car)
# Get the panda port that is used to recv data: it must have GPS
panda_port = get_panda_id('ford_fusion', 'recv')
device = get_nidaqmx_dev_name()
can_logger(car_dbc=car_dbc,
leddar_dbc=leddar_dbc,
sample_time=0.2,
port=panda_port,
filename='fusion_preliminary_test',
ni_device=device)
PANDA = Panda(panda_port)
PANDA.can_clear(0xFFFF)
PANDA.set_safety_mode(Panda.SAFETY_ALLOUTPUT)
# Send request to broadcast leddar messages
dat = '0301000000000000'
PANDA.can_send(0x740, dat.decode('hex'), 1)
# DBC files: car and leddar
base_path = dirname(abspath(__file__))
leddar = join(base_path,'dbc_files/leddar_vu_8_segments.dbc')
car = join(base_path,'dbc_files/mazda_cx9_2016.dbc')
CAR_DBC = cantools.database.load_file(car)
LEDDAR_DBC = cantools.database.load_file(leddar)
SPEED = 0
PEDAL_MODEL = PM('mazda_cx9')
DEV = get_nidaqmx_dev_name()
PROPS_VIS = visualization_props()
X = []
Y0 = []; Y1 = []
TRACES0 = []; TRACES1 = []
# Layout of the app
app.layout = app_layouts.layout_control_cruise_control(PROPS_VIS)
@app.callback(
Output('live_update_graph', 'figure'),
[Input('refresh', 'n_intervals'),
Input('speed_input', 'value'),
Input('prop_gain', 'value'),
Input('max_accel', 'value'),
Input('min_accel', 'value')])