app.title = 'GAP AND SPEED VISUALIZATION'
app.config['suppress_callback_exceptions'] = True
app.css.config.serve_locally = True
app.scripts.config.serve_locally = True
# Boostrap CSS file (local)
@app.server.route('/static/<path:path>')
def static_file(path):
static_folder = os.path.join(os.getcwd(), 'static')
return send_from_directory(static_folder, path)
# Global variables and initialization
# Open panda device (comma ai) and clear the buffer
panda_port = get_panda_id('ford_f150', 'send')
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/ford_f150_2017.dbc')
CAR_DBC = cantools.database.load_file(car)
LEDDAR_DBC = cantools.database.load_file(leddar)
CAN_VARIABLES = []
PROPS_VIS = visualization_props()
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)
# Create the app and assign excepctions
app = dash.Dash()
app.title = 'SPEED CONTROL AND VISUALIZATION'
app.config['suppress_callback_exceptions']=True
app.css.config.serve_locally = True
app.scripts.config.serve_locally = True
# Boostrap CSS file (local)
@app.server.route('/static/<path:path>')
def static_file(path):
static_folder = os.path.join(os.getcwd(), 'static')
return send_from_directory(static_folder, path)
# Global variables and initialization
# Open panda device (comma ai) and clear the buffer
panda_port = get_panda_id('mazda_cx9', 'send')
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')
# Print and plot results in the screen
plt.figure()
plt.subplot(2,1,1)
plt.plot(df['time_rel'], df['gap_m'])
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/mazda_cx9_2016.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('mazda_cx9', 'recv')
device = get_nidaqmx_dev_name()
can_logger(car_dbc = car_dbc, leddar_dbc = leddar_dbc, sample_time = 0.2,
port = panda_port, filename = 'mazda_cx9_preliminary_test', ni_device = device)
# Print and plot results in the screen
plt.figure()
plt.subplot(2,1,1)
plt.plot(df['time_rel'], df['gap_m'])
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_f150_2017.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_f150', 'recv')
device = get_nidaqmx_dev_name()
can_logger(car_dbc = car_dbc, leddar_dbc = leddar_dbc, sample_time = 0.2,
port = panda_port, filename = 'f150_preliminary_test', ni_device = device)
app.title = 'GAP AND SPEED CONTROL AND VISUALIZATION'
app.config['suppress_callback_exceptions'] = True
app.css.config.serve_locally = True
app.scripts.config.serve_locally = True
# Boostrap CSS file (local)
@app.server.route('/static/<path:path>')
def static_file(path):
static_folder = os.path.join(os.getcwd(), 'static')
return send_from_directory(static_folder, path)
# Global variables and initialization
# Open panda device (comma ai) and clear the buffer
panda_port = get_panda_id('ford_fusion', 'send')
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/ford_fusion_2011.dbc')
CAR_DBC = cantools.database.load_file(car)
LEDDAR_DBC = cantools.database.load_file(leddar)
CAN_VARIABLES = []
PEDAL_MODEL = PM('ford_fusion')
