def main(argv):
scenario_plotter = ScenarioPlotter()
elbow = Elbow()
elbow_controller = IntegralElbow()
observer_elbow = IntegralElbow()
# Test moving the elbow with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
initial_X = numpy.matrix([[0.707], [0.707]])
R = numpy.matrix([[1.0], [3.0], [1.0]])
scenario_plotter.run_test(elbow, goal=R, controller_elbow=elbow_controller,
observer_elbow=observer_elbow, iterations=2000)
scenario_plotter.Plot(elbow)
# Write the generated constants out to a file.
print(len(argv))
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the elbow and integral elbow.')
else:
namespaces = ['shit']
elbow = Elbow('Elbow')
loop_writer = control_loop.ControlLoopWriter(
'Elbow', [elbow], namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_elbow = IntegralElbow('IntegralElbow')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralElbow', [integral_elbow], namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def main(argv):
loaded_mass = 25
#loaded_mass = 0
elevator = Elevator(mass=13 + loaded_mass)
elevator_controller = Elevator(mass=13 + 15)
observer_elevator = Elevator(mass=13 + 15)
#observer_elevator = None
# Test moving the elevator with constant separation.
initial_X = numpy.matrix([[0.0], [0.0], [0.01], [0.0]])
#initial_X = numpy.matrix([[0.0], [0.0], [0.00], [0.0]])
R = numpy.matrix([[1.0], [0.0], [0.0], [0.0]])
run_test(elevator, initial_X, R, controller_elevator=elevator_controller,
observer_elevator=observer_elevator)
# Write the generated constants out to a file.
if len(argv) != 3:
glog.fatal('Expected .h file name and .cc file name for the elevator.')
else:
namespaces = ['y2015', 'control_loops', 'fridge']
elevator = Elevator("Elevator")
loop_writer = control_loop.ControlLoopWriter("Elevator", [elevator],
namespaces=namespaces)
if argv[1][-3:] == '.cc':
loop_writer.Write(argv[2], argv[1])
else:
loop_writer.Write(argv[1], argv[2])
def main(argv):
if FLAGS.plot:
loaded_mass = 25
#loaded_mass = 0
arm = Arm(mass=13 + loaded_mass)
#arm_controller = Arm(mass=13 + 15)
#observer_arm = Arm(mass=13 + 15)
#observer_arm = None
integral_arm = IntegralArm(mass=13 + loaded_mass)
integral_arm.X_hat[0, 0] += 0.02
integral_arm.X_hat[2, 0] += 0.02
integral_arm.X_hat[4] = 0
# Test moving the arm with constant separation.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
run_integral_test(arm, initial_X, R, integral_arm, disturbance=2)
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the arm and augmented arm.')
else:
namespaces = ['y2015', 'control_loops', 'fridge']
arm = Arm('Arm', mass=13)
loop_writer = control_loop.ControlLoopWriter('Arm', [arm],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_arm = IntegralArm('IntegralArm', mass=13)
loop_writer = control_loop.ControlLoopWriter('IntegralArm', [integral_arm],
namespaces=namespaces)
loop_writer.Write(argv[3], argv[4])
def main(argv):
argv = FLAGS(argv)
glog.init()
scenario_plotter = ScenarioPlotter()
intake = Intake()
intake_controller = IntegralIntake()
observer_intake = IntegralIntake()
# Test moving the intake with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[numpy.pi/2.0], [0.0], [0.0]])
scenario_plotter.run_test(intake, end_goal=R,
controller_intake=intake_controller,
observer_intake=observer_intake, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the intake and integral intake.')
else:
namespaces = ['y2016_bot3', 'control_loops', 'intake']
intake = Intake("Intake")
loop_writer = control_loop.ControlLoopWriter('Intake', [intake],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_intake = IntegralIntake("IntegralIntake")
integral_loop_writer = control_loop.ControlLoopWriter("IntegralIntake", [integral_intake],
namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def main(argv):
scenario_plotter = ScenarioPlotter()
intake = Intake()
intake_controller = IntegralIntake()
observer_intake = IntegralIntake()
# Test moving the intake with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[0.1], [0.0], [0.0]])
scenario_plotter.run_test(intake, end_goal=R,
controller_intake=intake_controller,
observer_intake=observer_intake, iterations=400)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the intake and integral intake.')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'intake']
intake = Intake('Intake')
loop_writer = control_loop.ControlLoopWriter('Intake', [intake],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant('kFreeSpeed', '%f',
intake.free_speed))
loop_writer.AddConstant(control_loop.Constant('kOutputRatio', '%f',
intake.G * intake.r))
loop_writer.Write(argv[1], argv[2])
integral_intake = IntegralIntake('IntegralIntake')
integral_loop_writer = control_loop.ControlLoopWriter('IntegralIntake', [integral_intake],
namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def main(argv):
argv = FLAGS(argv)
scenario_plotter = ScenarioPlotter()
shoulder = Shoulder()
shoulder_controller = IntegralShoulder()
observer_shoulder = IntegralShoulder()
# Test moving the shoulder with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[numpy.pi / 2.0], [0.0], [0.0]])
scenario_plotter.run_test(shoulder, goal=R, controller_shoulder=shoulder_controller,
observer_shoulder=observer_shoulder, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the shoulder and integral shoulder.')
else:
namespaces = ['y2016', 'control_loops', 'superstructure']
shoulder = Shoulder("Shoulder")
loop_writer = control_loop.ControlLoopWriter('Shoulder', [shoulder],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_shoulder = IntegralShoulder("IntegralShoulder")
integral_loop_writer = control_loop.ControlLoopWriter("IntegralShoulder", [integral_shoulder],
namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def load(dpath):
"""
Loads data from directory.
Arguments:
dpath -- directory
Returns:
train_set_x_orig -- train set features
train_set_y_orig -- train set labels
test_set_x_orig -- train set features
test_set_y_orig -- test set labels
classes -- list of classes
"""
if not os.path.exists(dpath):
log.fatal('{0} does not eixst'.format(dpath))
sys.exit(0)
train_dataset = h5py.File(os.path.join(dpath, 'train_catvnoncat.h5'), "r")
train_set_x_orig = np.array(train_dataset["train_set_x"][:])
train_set_y_orig = np.array(train_dataset["train_set_y"][:])
test_dataset = h5py.File(os.path.join(dpath, 'test_catvnoncat.h5'), "r")
test_set_x_orig = np.array(test_dataset["test_set_x"][:])
test_set_y_orig = np.array(test_dataset["test_set_y"][:])
classes = np.array(test_dataset["list_classes"][:])
train_set_y_orig = train_set_y_orig.reshape((1, train_set_y_orig.shape[0]))
test_set_y_orig = test_set_y_orig.reshape((1, test_set_y_orig.shape[0]))
return train_set_x_orig, train_set_y_orig, test_set_x_orig, test_set_y_orig, classes
def main(argv):
scenario_plotter = ScenarioPlotter()
wrist = Wrist()
wrist_controller = IntegralWrist()
observer_wrist = IntegralWrist()
# Test moving the wrist with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[1.0], [0.0], [0.0]])
scenario_plotter.run_test(wrist, goal=R, controller_wrist=wrist_controller,
observer_wrist=observer_wrist, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the wrist and integral wrist.')
else:
namespaces = ['y2016', 'control_loops', 'superstructure']
wrist = Wrist('Wrist')
loop_writer = control_loop.ControlLoopWriter(
'Wrist', [wrist], namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_wrist = IntegralWrist('IntegralWrist')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralWrist', [integral_wrist], namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def move_output_files(self, pipeline_type, dataset):
""" Moves all output files for a particular pipeline and dataset
from their temporary logging location during runtime to the evaluation location.
Args:
pipeline_type: a pipeline representing a set of parameters to use, as
defined in the experiments yaml file for the dataset in question.
dataset: a dataset to run as defined in the experiments yaml file.
"""
dataset_name = dataset["name"]
dataset_results_dir = os.path.join(self.results_dir, dataset_name)
dataset_pipeline_result_dir = os.path.join(dataset_results_dir,
pipeline_type)
log.debug(
"\033[1mMoving output dir:\033[0m \n %s \n \033[1m to destination:\033[0m \n %s"
% (self.pipeline_output_dir, dataset_pipeline_result_dir))
try:
evt.move_output_from_to(self.pipeline_output_dir,
dataset_pipeline_result_dir)
except:
log.fatal(
"\033[1mFailed copying output dir: \033[0m\n %s \n \033[1m to destination: %s \033[0m\n"
% (self.pipeline_output_dir, dataset_pipeline_result_dir))
def test_load(self):
dpath = os.environ['DATASETS_DIR']
if dpath == '':
log.fatal('Got empty DATASETS_DIR')
sys.exit(0)
log.info('running test_load...')
log.info('directory: {0}'.format(dpath))
train_x_orig, train_y, test_x_orig, test_y, classes = load(dpath)
log.info('train_x_orig.shape: {0}'.format(train_x_orig.shape))
log.info('train_y.shape: {0}'.format(train_y.shape))
log.info('test_x_orig.shape: {0}'.format(test_x_orig.shape))
log.info('test_y.shape: {0}'.format(test_y.shape))
log.info('classes.shape: {0}'.format(classes.shape))
self.assertEqual(train_x_orig.shape, (209, 64, 64, 3))
self.assertEqual(train_y.shape, (1, 209))
self.assertEqual(test_x_orig.shape, (50, 64, 64, 3))
self.assertEqual(test_y.shape, (1, 50))
self.assertEqual(classes.shape, (2, ))
index = 25
# plt.imshow(train_x_orig[index])
result = classes[train_y[0, index]].decode("utf-8")
log.info('cat or non-cat?: {0}'.format(result))
self.assertEqual(result, 'cat')
def main(argv):
scenario_plotter = ScenarioPlotter()
shooter = Shooter()
shooter_controller = IntegralShooter()
observer_shooter = IntegralShooter()
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[0.0], [100.0], [0.0]])
scenario_plotter.run_test(shooter, goal=R, controller_shooter=shooter_controller,
observer_shooter=observer_shooter, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
namespaces = ['y2016', 'control_loops', 'shooter']
shooter = Shooter('Shooter')
loop_writer = control_loop.ControlLoopWriter('Shooter', [shooter],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
integral_shooter = IntegralShooter('IntegralShooter')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralShooter', [integral_shooter], namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
def aggregate_all_results(results_dir, use_pgo=False):
""" Aggregate APE results and draw APE boxplot as well as write latex table
with results:
Args:
- result_dir: path to the directory with results ordered as follows:
\* dataset_name:
|___\* pipeline_type:
| |___results.yaml
|___\* pipeline_type:
| |___results.yaml
\* dataset_name:
|___\* pipeline_type:
| |___results.yaml
Basically all subfolders with a results.yaml will be examined.
- use_pgo: whether to aggregate all results for VIO or for PGO trajectory.
set to True for PGO and False (default) for VIO
Returns:
- stats: a nested dictionary with the statistics and results of all pipelines:
* First level ordered with dataset_name as keys:
* Second level ordered with pipeline_type as keys:
* Each stats[dataset_name][pipeline_type] value has:
* absolute_errors: an evo Result type with trajectory and APE stats.
* relative_errors: RPE stats.
"""
import fnmatch
# Load results.
log.info("Aggregate dataset results.")
# Aggregate all stats for each pipeline and dataset
yaml_filename = 'results_vio.yaml'
if use_pgo:
yaml_filename = 'results_pgo.yaml'
stats = dict()
for root, dirnames, filenames in os.walk(results_dir):
for results_filename in fnmatch.filter(filenames, yaml_filename):
results_filepath = os.path.join(root, results_filename)
# Get pipeline name
pipeline_name = os.path.basename(root)
# Get dataset name
dataset_name = os.path.basename(os.path.split(root)[0])
# Collect stats
if stats.get(dataset_name) is None:
stats[dataset_name] = dict()
try:
stats[dataset_name][pipeline_name] = yaml.load(
open(results_filepath, 'r'), Loader=yaml.Loader)
except yaml.YAMLError as e:
raise Exception("Error in results file: ", e)
except:
log.fatal("\033[1mFailed opening file: \033[0m\n %s" %
results_filepath)
log.debug("Check stats from: " + results_filepath)
try:
evt.check_stats(stats[dataset_name][pipeline_name])
except Exception as e:
log.warning(e)
return stats
def main(argv):
argv = FLAGS(argv)
claw = Claw()
if FLAGS.plot:
# Test moving the claw with constant separation.
initial_X = numpy.matrix([[-1.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[1.0], [0.0], [0.0], [0.0]])
run_test(claw, initial_X, R)
# Test just changing separation.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[0.0], [1.0], [0.0], [0.0]])
run_test(claw, initial_X, R)
# Test changing both separation and position at once.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[1.0], [1.0], [0.0], [0.0]])
run_test(claw, initial_X, R)
# Test a small separation error and a large position one.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[2.0], [0.05], [0.0], [0.0]])
run_test(claw, initial_X, R)
# Test a small separation error and a large position one.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[-0.5], [1.0], [0.0], [0.0]])
run_test(claw, initial_X, R)
# Test opening with the top claw at the limit.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[-1.5], [1.5], [0.0], [0.0]])
claw.hard_pos_limits = (-1.6, 0.1)
claw.pos_limits = (-1.5, 0.0)
run_test(claw, initial_X, R)
claw.pos_limits = None
# Test opening with the bottom claw at the limit.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[0], [1.5], [0.0], [0.0]])
claw.hard_pos_limits = (-0.1, 1.6)
claw.pos_limits = (0.0, 1.6)
run_test(claw, initial_X, R)
claw.pos_limits = None
# Write the generated constants out to a file.
if len(argv) != 3:
glog.fatal('Expected .h file name and .cc file name for the claw.')
else:
namespaces = ['y2014', 'control_loops', 'claw']
claw = Claw('Claw')
loop_writer = control_loop.ControlLoopWriter('Claw', [claw],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant('kClawMomentOfInertiaRatio',
'%f', claw.J_top / claw.J_bottom))
loop_writer.AddConstant(control_loop.Constant('kDt', '%f',
claw.dt))
loop_writer.Write(argv[1], argv[2])
def create_full_path_if_not_exists(filename):
if not os.path.exists(os.path.dirname(filename)):
try:
log.debug('Creating non-existent path: %s' % filename)
os.makedirs(os.path.dirname(filename))
except OSError as exc: # Guard against race condition
if exc.errno != errno.EEXIST:
log.fatal("Could not create inexistent filename: " + filename)
def main(argv):
if FLAGS.plot:
polydrivetrain.PlotPolyDrivetrainMotions(drivetrain.kDrivetrain)
elif len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
polydrivetrain.WritePolyDrivetrain(argv[1:3], argv[3:5], 'testbench',
drivetrain.kDrivetrain)
def test_backend(self):
exec_path = os.environ['SERVER_EXEC']
if exec_path == '':
log.fatal('Got empty backend-web-server path')
sys.exit(0)
if not os.path.exists(exec_path):
log.fatal('{0} does not eixst'.format(exec_path))
sys.exit(0)
log.info('Running {0}'.format(exec_path))
backend_proc = BACKEND(exec_path)
backend_proc.setDaemon(True)
backend_proc.start()
log.info('Sleeping...')
time.sleep(5)
endpoint = 'http://localhost:2200/cats-request/queue'
log.info('Posting client requests...')
# invalid item
item = {
'bucket': '/cats-request',
'key': '/cats-request',
'value': '',
'request_id': '',
}
itemresp1 = post_item(endpoint, item)
self.assertIsNot(itemresp1['error'], '')
# valid item
item['value'] = 'foo'
item['request_id'] = 'id'
itemresp2 = post_item(endpoint, item)
self.assertEqual(itemresp2['error'], u'unknown request ID \"id\"')
def cleanup():
log.info('Killing backend-web-server...')
backend_proc.kill()
backend_proc.join()
log.info('backend-web-server output: {0}'.format(
backend_proc.stderr))
self.addCleanup(cleanup)
time.sleep(3)
log.info('Fetching items...')
try:
fetch_item(endpoint, timeout=5)
except requests.exceptions.ReadTimeout:
log.info('Got expected timeout!')
log.info('Done!')
def main(argv):
argv = FLAGS(argv)
glog.init()
scenario_plotter = ScenarioPlotter()
J_accelerating = 18
J_decelerating = 7
arm = Arm(name='AcceleratingArm', J=J_accelerating)
arm_integral_controller = IntegralArm(
name='AcceleratingIntegralArm', J=J_accelerating)
arm_observer = IntegralArm()
# Test moving the shoulder with constant separation.
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[numpy.pi / 2.0],
[0.0],
[0.0], #[numpy.pi / 2.0],
[0.0],
[0.0],
[0.0]])
arm.X = initial_X[0:4, 0]
arm_observer.X = initial_X
scenario_plotter.run_test(arm=arm,
end_goal=R,
iterations=300,
controller=arm_integral_controller,
observer=arm_observer)
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the wrist and integral wrist.')
else:
namespaces = ['y2016', 'control_loops', 'superstructure']
decelerating_arm = Arm(name='DeceleratingArm', J=J_decelerating)
loop_writer = control_loop.ControlLoopWriter(
'Arm', [arm, decelerating_arm], namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
decelerating_integral_arm_controller = IntegralArm(
name='DeceleratingIntegralArm', J=J_decelerating)
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralArm',
[arm_integral_controller, decelerating_integral_arm_controller],
namespaces=namespaces)
integral_loop_writer.AddConstant(control_loop.Constant("kV_shoulder", "%f",
arm_integral_controller.shoulder_Kv))
integral_loop_writer.Write(argv[3], argv[4])
if FLAGS.plot:
scenario_plotter.Plot()
def open_db_ro(lmdb_file):
"""Open the lmdb in READ ONLY mode, if the db file not exist, return
None
"""
db = None
if os.path.exists(lmdb_file):
try:
db = lmdb.open(lmdb_file, readonly=True)
except:
log.fatal('\033[0;31mOpen lmdb %s error\033[0m' % lmdb_file)
return None
return db
def open_file(file_name, param_str):
try:
fp = open(file_name, param_str)
except IOError:
# May be the encoding of file name is not write
try:
fp = open(file_name.decode('utf8'), param_str)
except:
log.fatal('\033[01;31mERROR:\033[0m Can not open %s' % file_name)
sys.exit(2)
return fp
def main(argv):
if FLAGS.plot:
polydrivetrain.PlotPolyDrivetrainMotions(drivetrain.kDrivetrain)
elif len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
namespaces = [
'third_party', 'frc971', 'control_loops', 'drivetrain', 'y2016'
]
polydrivetrain.WritePolyDrivetrainFullName(argv[1:3], argv[3:5],
namespaces, namespaces,
drivetrain.kDrivetrain)
def main(argv):
scenario_plotter = ScenarioPlotter()
indexer = Indexer()
indexer_controller = IntegralIndexer()
observer_indexer = IntegralIndexer()
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[0.0], [20.0], [0.0]])
scenario_plotter.run_test(indexer, goal=R, controller_indexer=indexer_controller,
observer_indexer=observer_indexer, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
scenario_plotter = ScenarioPlotter()
indexer = Indexer()
indexer_controller = IntegralIndexer(voltage_error_noise=1.5)
observer_indexer = IntegralIndexer(voltage_error_noise=1.5)
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[0.0], [20.0], [0.0]])
scenario_plotter.run_test(indexer, goal=R, controller_indexer=indexer_controller,
observer_indexer=observer_indexer, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
if len(argv) != 7:
glog.fatal('Expected .h file name and .cc file names')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'indexer']
indexer = Indexer('Indexer')
loop_writer = control_loop.ControlLoopWriter('Indexer', [indexer],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant(
'kFreeSpeed', '%f', indexer.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kOutputRatio', '%f', indexer.G))
loop_writer.Write(argv[1], argv[2])
integral_indexer = IntegralIndexer('IntegralIndexer')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralIndexer', [integral_indexer], namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
stuck_integral_indexer = IntegralIndexer('StuckIntegralIndexer',
voltage_error_noise=1.5)
stuck_integral_loop_writer = control_loop.ControlLoopWriter(
'StuckIntegralIndexer', [stuck_integral_indexer], namespaces=namespaces)
stuck_integral_loop_writer.Write(argv[5], argv[6])
def _exec_bash_tool(tool_name):
"""Execute bash tool configured in config."""
tool = config.Config.get_tool(tool_name)
if tool is None:
msg = 'Cannot find config for tool {}'.format(tool_name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
# Construct the command string by joining all components.
tool.command[0] = config.Config.get_realpath(tool.command[0])
cmd_str = ' '.join(tool.command)
system_cmd.run_in_background(cmd_str, tool.stdout_file,
tool.stderr_file)
def _exec_bash_tool(tool_name):
"""Execute bash tool configured in config."""
tool = config.Config.get_tool(tool_name)
if tool is None:
msg = 'Cannot find config for tool {}'.format(tool_name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
# Construct the command string by joining all components.
tool.command[0] = config.Config.get_realpath(tool.command[0])
cmd_str = ' '.join(tool.command)
system_cmd.run_in_background(cmd_str, tool.stdout_file,
tool.stderr_file)
def main(argv):
src_file = None
dst_file = None
src_content = []
help_msg = 'dataset_shuffle_index.py -i <infile> -o <shuffledfile>'
try:
opts, args = getopt.getopt(argv, 'hi:o:')
except getopt.GetoptError:
print help_msg
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print help_msg
sys.exit()
elif opt == '-i':
src_file = arg
elif opt == '-o':
dst_file = arg
if src_file is None or dst_file is None:
print help_msg
sys.exit(2)
# Open the files
try:
src_fp = open(src_file, 'r')
except IOError:
log.fatal('Can not open %s' % src_file)
sys.exit(2)
try:
dst_fp = open(dst_file, 'w')
except IOError:
log.fatal('Can not open %s' % dst_file)
sys.exit(2)
# Load the src file
log.info('Loading %s ...' % src_file)
for line in src_fp.readlines():
src_content.append(line)
# shuffle the lines
log.info('Shuffling lines ...')
random.shuffle(src_content)
log.info('Writing %s ...' % dst_file)
# Write it the dst_file
for line in src_content:
dst_fp.writelines(line)
src_fp.close()
dst_fp.close()
log.info('Finished')
def _get_endpoint_error_loss(net,
loss_weights,
groundtruths,
weights=None,
loss_type=None):
"""
Returns endpoint error loss. Options are:
- L2
- Huber
- L2 weighted by uncertainty, like eqn 8 in:
https://arxiv.org/pdf/1703.04977.pdf
"""
losses = []
log.check_eq(len(groundtruths), len(loss_weights))
log.check_eq(len(net.estimator_net) + 1, len(loss_weights), \
("You do not have an appropriate number of loss weights. "
"Should have {}".format(1 + len(net.estimator_net))))
with tf.name_scope('endpoint_loss'):
for i, w in enumerate(loss_weights):
if i < len(loss_weights) - 1:
prediction = net.estimator_net[i].get_flow()
else:
if net.options.use_context_net is False:
log.warn(
'Context network is not set up, so there is no ' +
'need to penalize flow at the finest resolution.')
break
prediction = net.get_output_flow()
dim = prediction.shape.as_list()[1]
loss_name = '{}x{}'.format(dim, dim)
gt_at_scale = groundtruths[dim]
log.check_eq(gt_at_scale.shape.as_list()[1],
prediction.shape.as_list()[1])
log.check_eq(gt_at_scale.shape.as_list()[2],
prediction.shape.as_list()[2])
if loss_type == 'HUBER':
loss = tf_utils.endpoint_huber_loss_at_scale(
prediction, gt_at_scale, weights) * w
elif loss_type == 'L2':
loss = tf_utils.endpoint_loss_at_scale(
prediction, gt_at_scale, weights) * w
else:
log.fatal("Unrecognized loss type -- should specify "
"{'HUBER', 'L2' 'WEIGHTED'}.")
tf.summary.scalar(loss_name, loss)
losses.append(loss)
return losses
def main(argv):
scenario_plotter = ScenarioPlotter()
column = Column()
column_controller = IntegralColumn()
observer_column = IntegralColumn()
initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]])
R = numpy.matrix([[0.0], [10.0], [5.0], [0.0], [0.0], [0.0]])
scenario_plotter.run_test(column, end_goal=R, controller_column=column_controller,
observer_column=observer_column, iterations=400)
if FLAGS.plot:
scenario_plotter.Plot()
if len(argv) != 7:
glog.fatal('Expected .h file name and .cc file names')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'column']
column = Column('Column')
loop_writer = control_loop.ControlLoopWriter('Column', [column],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant(
'kIndexerFreeSpeed', '%f', column.indexer.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kIndexerOutputRatio', '%f', column.indexer.G))
loop_writer.AddConstant(control_loop.Constant(
'kTurretFreeSpeed', '%f', column.turret.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kTurretOutputRatio', '%f', column.turret.G))
loop_writer.Write(argv[1], argv[2])
# IntegralColumn controller 1 will disable the indexer.
integral_column = IntegralColumn('IntegralColumn')
disabled_integral_column = IntegralColumn('DisabledIntegralColumn',
disable_indexer=True)
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralColumn', [integral_column, disabled_integral_column],
namespaces=namespaces)
integral_loop_writer.Write(argv[3], argv[4])
stuck_integral_column = IntegralColumn('StuckIntegralColumn', voltage_error_noise=8.0)
stuck_integral_loop_writer = control_loop.ControlLoopWriter(
'StuckIntegralColumn', [stuck_integral_column], namespaces=namespaces)
stuck_integral_loop_writer.Write(argv[5], argv[6])
def move_output_from_to(from_dir, to_dir):
try:
if (os.path.exists(to_dir)):
rmtree(to_dir)
except:
log.info("Directory:" + to_dir + " does not exist, we can safely move output.")
try:
if (os.path.isdir(from_dir)):
move(from_dir, to_dir)
else:
log.info("There is no output directory...")
except:
print("Could not move output from: " + from_dir + " to: " + to_dir)
raise
try:
os.makedirs(from_dir)
except:
log.fatal("Could not mkdir: " + from_dir)
def execute_cmd(module_name, cmd_name):
""""""
# Run command on all modules if the module name is exactly 'all'.
if module_name == 'all':
for conf in config.Config.get_pb().modules:
ModuleApi._run_command(conf, cmd_name)
runtime_status.RuntimeStatus.broadcast_status_if_changed()
return 'OK', httplib.OK
# Or else, run command on the specified module.
conf = config.Config.get_module(module_name)
if conf is None:
msg = 'Cannot find config for module {}'.format(module_name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
result = ModuleApi._run_command(conf, cmd_name)
runtime_status.RuntimeStatus.broadcast_status_if_changed()
return result
def execute_cmd(module_name, cmd_name):
""""""
# Run command on all modules if the module name is exactly 'all'.
if module_name == 'all':
for conf in config.Config.get_pb().modules:
ModuleApi._run_command(conf, cmd_name)
runtime_status.RuntimeStatus.broadcast_status_if_changed()
return 'OK', httplib.OK
# Or else, run command on the specified module.
conf = config.Config.get_module(module_name)
if conf is None:
msg = 'Cannot find config for module {}'.format(module_name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
result = ModuleApi._run_command(conf, cmd_name)
runtime_status.RuntimeStatus.broadcast_status_if_changed()
return result
def main(argv):
argv = FLAGS(argv)
loaded_mass = 7+4.0
#loaded_mass = 0
#observer_elevator = None
# Test moving the Elevator
initial_X = numpy.matrix([[0.0], [0.0]])
up_R = numpy.matrix([[0.4572], [0.0], [0.0]])
down_R = numpy.matrix([[0.0], [0.0], [0.0]])
totemass = 3.54
scenario_plotter = ScenarioPlotter()
elevator_controller = IntegralElevator(mass=4*totemass + loaded_mass)
observer_elevator = IntegralElevator(mass=4*totemass + loaded_mass)
for i in xrange(0, 7):
elevator = Elevator(mass=i*totemass + loaded_mass)
glog.info('Actual poles are %s', str(numpy.linalg.eig(elevator.A - elevator.B * elevator_controller.K[0, 0:2])[0]))
elevator.X = initial_X
scenario_plotter.run_test(elevator, goal=up_R, controller_elevator=elevator_controller,
observer_elevator=observer_elevator, iterations=200)
scenario_plotter.run_test(elevator, goal=down_R, controller_elevator=elevator_controller,
observer_elevator=observer_elevator, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the Elevator and integral elevator.')
else:
design_mass = 4*totemass + loaded_mass
elevator = Elevator("Elevator", mass=design_mass)
loop_writer = control_loop.ControlLoopWriter("Elevator", [elevator],
namespaces=['y2015_bot3', 'control_loops', 'elevator'])
loop_writer.Write(argv[1], argv[2])
integral_elevator = IntegralElevator("IntegralElevator", mass=design_mass)
integral_loop_writer = control_loop.ControlLoopWriter("IntegralElevator", [integral_elevator],
namespaces=['y2015_bot3', 'control_loops', 'elevator'])
integral_loop_writer.Write(argv[3], argv[4])
def test_etcd(self):
"""etcd test function
"""
exec_path = os.environ['ETCD_EXEC']
if exec_path == '':
log.fatal('Got empty etcd path')
sys.exit(0)
if not os.path.exists(exec_path):
log.fatal('{0} does not eixst'.format(exec_path))
sys.exit(0)
log.info('Running {0}'.format(exec_path))
etcd_proc = ETCD(exec_path)
etcd_proc.setDaemon(True)
etcd_proc.start()
log.info('Sleeping...')
time.sleep(5)
log.info('Launching watch requests...')
watch_thread = threading.Thread(target=self.watch_routine)
watch_thread.setDaemon(True)
watch_thread.start()
time.sleep(3)
log.info('Launching client requests...')
log.info(put('http://localhost:2379', 'foo', 'bar'))
# Python 2
# self.assertEqual(get('http://localhost:2379', 'foo'), 'bar')
# Python 3
self.assertEqual(get('http://localhost:2379', 'foo'), b'bar')
log.info('Waing for watch...')
watch_thread.join()
log.info('Killing etcd...')
etcd_proc.kill()
etcd_proc.join()
log.info('etcd output: {0}'.format(etcd_proc.stderr))
log.info('Done!')
def read_one_orbdif_file(file_path):
glog.fatal("====> read : " + file_path)
if not os.path.exists(file_path):
glog.error("The file not exist : " + file_path)
return
PRN = ""
RMS = ""
LSQ = {}
ORI = {}
SAT = []
try:
with open(file_path) as file_object:
# get the sat list
lines = file_object.readlines()
for line in lines:
if "SAT" in line:
line = line[line.find("SAT") + 4:]
SAT = line.split()
for sat in SAT:
ORI[sat] = []
break
else:
continue
# get the ORI data
for line in lines:
line = line.rstrip()
if "GPST" in line:
continue
elif "SAT" in line:
break
else:
tmp = line.split()
ORI[tmp[1]].append(line)
except:
glog.error("The file not open : " + file_path)
sys.exit()
else:
glog.info("Os error : " + file_path)
result = {"ORI": ORI, "SAT": SAT}
return result
def __init__(self):
super(Classifier, self).__init__()
if cmd_args.gm == 'mean_field':
model = EmbedMeanField
elif cmd_args.gm == 'loopy_bp':
model = EmbedLoopyBP
elif cmd_args.gm == 'DGCNN':
model = DGCNN
else:
log.fatal('unknown gm %s' % cmd_args.gm)
sys.exit()
if cmd_args.gm == 'DGCNN':
self.s2v = model(latent_dim=cmd_args.latent_dim,
output_dim=cmd_args.out_dim,
num_node_feats=(cmd_args.feat_dim +
cmd_args.attr_dim),
num_edge_feats=0,
k=cmd_args.sortpooling_k)
else:
self.s2v = model(latent_dim=cmd_args.latent_dim,
output_dim=cmd_args.out_dim,
num_node_feats=cmd_args.feat_dim,
num_edge_feats=0,
max_lv=cmd_args.max_lv)
out_dim = cmd_args.out_dim
if out_dim == 0:
if cmd_args.gm == 'DGCNN':
out_dim = self.s2v.dense_dim
else:
out_dim = cmd_args.latent_dim
if False:
self.mlp = MLPClassifier(input_size=out_dim,
hidden_size=cmd_args.hidden,
num_class=cmd_args.num_class,
with_dropout=cmd_args.dropout)
self.mlp = MaxRecallAtPrecision(input_size=out_dim,
hidden_size=cmd_args.hidden,
alpha=0.6,
with_dropout=cmd_args.dropout)
def main(argv):
scenario_plotter = ScenarioPlotter()
if FLAGS.plot:
iterations = 200
initial_X = numpy.matrix([[0.0], [0.0], [0.0]])
R = numpy.matrix([[0.0], [100.0], [100.0], [0.0]])
scenario_plotter_int = ScenarioPlotter()
shooter = Shooter()
shooter_controller = IntegralShooter()
observer_shooter_hybrid = IntegralShooter()
scenario_plotter_int.run_test(shooter, goal=R, controller_shooter=shooter_controller,
observer_shooter=observer_shooter_hybrid, iterations=iterations,
hybrid_obs = True)
scenario_plotter_int.Plot()
pylab.show()
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'shooter']
shooter = Shooter('Shooter')
loop_writer = control_loop.ControlLoopWriter('Shooter', [shooter],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant(
'kFreeSpeed', '%f', shooter.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kOutputRatio', '%f', shooter.G))
loop_writer.Write(argv[1], argv[2])
integral_shooter = IntegralShooter('IntegralShooter')
integral_loop_writer = control_loop.ControlLoopWriter(
'IntegralShooter', [integral_shooter], namespaces=namespaces,
plant_type='StateFeedbackHybridPlant',
observer_type='HybridKalman')
integral_loop_writer.Write(argv[3], argv[4])
def test_cats(self):
dpath = os.environ['DATASETS_DIR']
if dpath == '':
log.fatal('Got empty DATASETS_DIR')
sys.exit(0)
param_path = os.environ['CATS_PARAM_PATH']
if param_path == '':
log.fatal('Got empty CATS_PARAM_PATH')
sys.exit(0)
log.info('running test_cats...')
log.info('directory path: {0}'.format(dpath))
log.info('parameters path: {0}'.format(param_path))
img_path = os.path.join(dpath, 'gray-cat.jpeg')
parameters = np.load(param_path).item()
img_result = classify(img_path, parameters)
log.info('img_result: {0}'.format(img_result))
self.assertEqual(img_result, 'cat')
def main(argv):
scenario_plotter = ScenarioPlotter()
hood = Hood()
hood_controller = IntegralHood()
observer_hood = IntegralHood()
# Test moving the hood with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[numpy.pi/4.0], [0.0], [0.0]])
scenario_plotter.run_test(hood, end_goal=R,
controller_hood=hood_controller,
observer_hood=observer_hood, iterations=200)
if FLAGS.plot:
scenario_plotter.Plot()
# Write the generated constants out to a file.
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name for the hood and integral hood.')
else:
namespaces = ['y2017', 'control_loops', 'superstructure', 'hood']
hood = Hood('Hood')
loop_writer = control_loop.ControlLoopWriter('Hood', [hood],
namespaces=namespaces)
loop_writer.AddConstant(control_loop.Constant(
'kFreeSpeed', '%f', hood.free_speed))
loop_writer.AddConstant(control_loop.Constant(
'kOutputRatio', '%f', hood.G))
loop_writer.Write(argv[1], argv[2])
integral_hood = IntegralHood('IntegralHood')
integral_loop_writer = control_loop.ControlLoopWriter('IntegralHood', [integral_hood],
namespaces=namespaces)
integral_loop_writer.AddConstant(control_loop.Constant('kLastReduction', '%f',
integral_hood.last_G))
integral_loop_writer.Write(argv[3], argv[4])
def _run_command(conf, cmd_name):
"""Implementation of running command on module."""
cmd = next((cmd for cmd in conf.supported_commands
if cmd.name == cmd_name), None)
if cmd is None:
msg = 'Cannot find command {} for module {}'.format(
cmd_name, conf.name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
# Construct the command string by joining all components.
cmd.command[0] = config.Config.get_realpath(cmd.command[0])
cmd_str = ' '.join(cmd.command)
system_cmd.run_in_background(cmd_str, cmd.stdout_file, cmd.stderr_file)
# Update module status.
module_status = runtime_status.RuntimeStatus.get_module(conf.name)
if cmd_name == 'start':
module_status.status = runtime_status_pb2.ModuleStatus.STARTED
elif cmd_name == 'stop':
module_status.status = runtime_status_pb2.ModuleStatus.STOPPED
return 'OK', httplib.OK
def main(argv):
loaded_mass = 0
#loaded_mass = 0
claw = Claw(mass=4 + loaded_mass)
claw_controller = Claw(mass=5 + 0)
observer_claw = Claw(mass=5 + 0)
#observer_claw = None
# Test moving the claw with constant separation.
initial_X = numpy.matrix([[0.0], [0.0]])
R = numpy.matrix([[1.0], [0.0]])
run_test(claw, initial_X, R, controller_claw=claw_controller,
observer_claw=observer_claw)
# Write the generated constants out to a file.
if len(argv) != 3:
glog.fatal('Expected .h and .cc filename for claw.')
else:
namespaces = ['y2015', 'control_loops', 'claw']
claw = Claw('Claw')
loop_writer = control_loop.ControlLoopWriter('Claw', [claw],
namespaces=namespaces)
loop_writer.Write(argv[1], argv[2])
def get_optimizer(self, loss):
""" Returns the optimizer. """
self.global_step = tf.Variable(0, trainable=False)
self.learning_rate = self._get_exponential_decay_learning_rate(
self.global_step)
if self._config['optimizer'] == 'SGD':
opt = tf.train.MomentumOptimizer(learning_rate=self.learning_rate,
momentum=self._config['momentum'],
use_nesterov=True)
elif self._config['optimizer'] == 'ADAM':
opt = tf.train.AdamOptimizer(learning_rate=self.learning_rate,
beta1=self._config['adam_beta1'],
beta2=self._config['adam_beta2'])
else:
log.fatal("UNRECOGNIZED OPTIMIZER TYPE")
gradients, variables = zip(*opt.compute_gradients(loss))
if 'max_gradient_norm' in self._config:
gradients, _ = tf.clip_by_global_norm(
gradients, self._config['max_gradient_norm'])
with tf.name_scope('gradients'):
variable_summary(tf.global_norm(gradients))
return opt.apply_gradients(zip(gradients, variables))
def _run_command(conf, cmd_name):
"""Implementation of running command on module."""
cmd = next(
(cmd for cmd in conf.supported_commands if cmd.name == cmd_name),
None)
if cmd is None:
msg = 'Cannot find command {} for module {}'.format(
cmd_name, conf.name)
glog.fatal(msg)
return msg, httplib.BAD_REQUEST
# Construct the command string by joining all components.
cmd.command[0] = config.Config.get_realpath(cmd.command[0])
cmd_str = ' '.join(cmd.command)
system_cmd.run_in_background(cmd_str, cmd.stdout_file, cmd.stderr_file)
# Update module status.
module_status = runtime_status.RuntimeStatus.get_module(conf.name)
if cmd_name == 'start':
module_status.status = runtime_status_pb2.ModuleStatus.STARTED
elif cmd_name == 'stop':
module_status.status = runtime_status_pb2.ModuleStatus.STOPPED
return 'OK', httplib.OK
return None
return item
except requests.exceptions.ConnectionError as err:
log.warning('Connection error: {0}'.format(err))
time.sleep(5)
except:
log.warning('Unexpected error: {0}'.format(sys.exc_info()[0]))
raise
if __name__ == "__main__":
if len(sys.argv) == 1:
log.fatal('Got empty endpoint: {0}'.format(sys.argv))
sys.exit(1)
EP = sys.argv[1]
if EP == '':
log.fatal('Got empty endpoint: {0}'.format(sys.argv))
sys.exit(1)
param_path = os.environ['CATS_PARAM_PATH']
if param_path == '':
log.fatal('Got empty CATS_PARAM_PATH')
sys.exit(1)
# 1. Initialize parameters / Define hyperparameters
# 2. Loop for num_iterations:
# a. Forward propagation
def try_log():
log.debug('2333happy deubgging....')
log.info('it works')
log.warn('something not ideal')
log.error('something went wrong')
log.fatal('AAAAAAAAAAA!')
doy_xml = ""
xml_dir = args.xml # xml file for each day, format is yyyydoy.xml
log_dir = args.dir
bin_dir = args.bin
grt_bin = "/project/jdhuang/GNSS_software/GREAT/great_pco_L3/build/Bin/"
scp_dir = "/workfs/jdhuang/great_projects/e_all/scripts/great" # scripts dir
mod_xml = "/workfs/jdhuang/great_projects/e_all/scripts/great/gnss_tb_ge_3_freq.xml" # model xml
python_version = "python3.7" # python version
year ='%04s' % args.year
idoy ='%03s' % args.idoy
yeardoy = "%04s%03s" % (year, idoy)
# create the xml file
glog.fatal("==========> beg trimcor.")
doy_xml = os.path.join(xml_dir, "gns_trimcor_%4s%03d.xml" % (args.year, int(args.idoy)))
create_xml_py = os.path.join(scp_dir, "gns_xml_create_xml.py")
tool.run_py_cmd(python_version=python_version, python_name=create_xml_py, log_dir=log_dir,log_name="create_xml.cmd_log", year=year, idoy=idoy, ilen=1, idst=mod_xml, odst=doy_xml)
print(grt_bin)
print(doy_xml)
print(log_dir)
print(bin_dir)
work_dir = os.path.join(log_dir,year,idoy)
os.system("mkdir -p " + work_dir)
os.chdir(work_dir)
tool.run_grt_cmd(app_dir=grt_bin, app_name="great_trimcor", xml_path=doy_xml, log_dir="./", log_name="great_tbedit.cmd_log", bin=bin_dir)
prj_dir = os.path.join(prj_dir, '%03s' % args.idoy)
prj_log = os.path.join(prj_log, '%03s' % args.idoy, "log_tb")
prj_log13 = os.path.join(prj_log13, '%03s' % args.idoy, "log_tb")
tool.check_path(prj_dir)
tool.check_path(xml_dir)
tool.check_path(prj_log)
tool.check_path(prj_log13)
os.chdir(prj_dir)
os.system("rm -r ./*")
os.system("mkdir ./log_tb")
os.system("cp -rf %s/*log ./log_tb" % prj_log) # 将统一存放的log文件粘贴到prj路径下
os.system("cp -rf %s/*log13 ./log_tb" % prj_log13)
tool.check_path(prd_dir)
tool.check_path(log_dir)
glog.fatal("crt dir is : " + os.getcwd())
# create the xml file
glog.fatal("=========> beg GNS POD IF.")
glog.fatal("==========> beg create the xml file.")
doy_xml = os.path.join(xml_dir,
"gns_pod_%4s%03d.xml" % (args.year, int(args.idoy)))
create_xml_py = os.path.join(scp_dir, "gns_xml_create_xml.py")
update_xml_py = os.path.join(scp_dir, "gns_xml_update_editres.py")
update_ambfix_xml_py = os.path.join(scp_dir, "gns_xml_update_ambfix.py")
os.system("chmod +x " + create_xml_py)
os.system("chmod +x " + update_xml_py)
os.system("chmod +x " + update_ambfix_xml_py)
glog.fatal("==========> creat xml.")
tool.run_py_cmd(python_version=python_version,
import glog as log
log.info("It works.")
log.warn("Something not ideal")
log.error("Something went wrong")
log.fatal("AAAAAAAAAAAAAAA!")
log.check(False)
doy_xml = ""
xml_dir = args.xml # xml file for each day, format is yyyydoy.xml
log_dir = args.dir
bin_dir = args.bin
grt_bin = "/project/jdhuang/GNSS_software/GREAT/great_pco_L3/build/Bin/"
scp_dir = "/workfs/jdhuang/great_projects/e_all/scripts/great" # scripts dir
mod_xml = "/workfs/jdhuang/great_projects/e_all/scripts/great/gnss_tb_ge_3_freq.xml" # model xml
python_version = "python3.7" # python version
year = '%04s' % args.year
idoy = '%03s' % args.idoy
yeardoy = "%04s%03s" % (year, idoy)
# create the xml file
glog.fatal("==========> beg tb.")
doy_xml = os.path.join(xml_dir,
"gns_tb_%4s%03d.xml" % (args.year, int(args.idoy)))
create_xml_py = os.path.join(scp_dir, "gns_xml_create_xml.py")
tool.run_py_cmd(python_version=python_version,
python_name=create_xml_py,
log_dir=log_dir,
log_name="create_xml.cmd_log",
year=year,
idoy=idoy,
ilen=1,
idst=mod_xml,
odst=doy_xml)
print(grt_bin)
print(doy_xml)
def main(argv):
db_file = None
skip_num = None
data_path = '../data'
overwrite = False
help_msg = 'download_image.py -i <lmdbfile> -o[optional] <datapath>\
--overwrite[optional] --skip <num>\n\
-i <lmdbfile> The input lmdb file contains the exif of photos\n\
-o <datapath> The path where to store the downloaded photos\n\
--overwrite If set, overwrite the exists photos, default not\n\
--skip <num> Skip the first XX photos'
try:
opts, args = getopt.getopt(argv, 'hi:o:', ['overwrite', 'skip='])
except getopt.GetoptError:
print help_msg
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print help_msg
sys.exit()
elif opt == '-i':
db_file = arg
elif opt == '-o':
data_path = arg
elif opt == '--overwrite':
overwrite = True
elif opt == '--skip':
skip_num = int(arg)
else:
print help_msg
sys.exit(2)
if db_file is None:
print help_msg
sys.exit(2)
# Try to open the database file
db = lt.open_db_ro(db_file)
if db is None:
log.fatal('\033[0;31mCan not open %s\033[0m' % db_file)
sys.exit(2)
# Get the entries from the database
entries = db.stat()['entries']
# Entries counter
counter = 0
# Check the data path
if not tb.check_path(data_path):
log.info('Create new dir %s' % data_path)
# Iter the data base
if skip_num is not None:
log.info('Skipping the first %d entries...' % skip_num)
with db.begin(write=False) as txn:
with txn.cursor() as cur:
for key, val in cur:
counter += 1
if skip_num is not None and counter < skip_num:
continue
# Parse the val into dict
val_dic = yaml.load(val)
# Get the avaliable url to download photo
photo = myxml.parse_xml_to_etree(val_dic['photo'])
url = tb.get_url(photo, val_dic['urls'], True)
# Download the url and save image
log.info('Download %s from %s [%d/%d]' %
(key, url, counter, entries))
try:
tb.download_url_and_save(url, key, overwrite, data_path)
except:
log.error('\033[0;31mFailed to download %s from %s\033[0m'
% (key, url))
continue
db.close()
'/apollo/monitor/system_status',
'/apollo/monitor/static_info',
]
@staticmethod
def ProcessBags(bags):
for bag_file in bags:
output_dir = os.path.join(os.path.dirname(bag_file), 'pnc_sample')
output_bag = os.path.join(output_dir, os.path.basename(bag_file))
if os.path.exists(output_bag):
glog.info('Skip {} which has been processed'.format(bag_file))
continue
glog.info('Processing bag {}'.format(bag_file))
if not os.path.exists(output_dir):
os.makedirs(output_dir)
with rosbag.Bag(bag_file, 'r') as bag_in:
with rosbag.Bag(output_bag, 'w') as bag_out:
for topic, msg, t in bag_in.read_messages(
topics=SamplePNC.TOPICS):
bag_out.write(topic, msg, t)
if __name__ == '__main__':
if len(sys.argv) == 1:
glog.fatal('Wrong arguments!')
sys.exit(1)
bags = sorted(sum([glob.glob(arg) for arg in sys.argv[1:]], []))
SamplePNC.ProcessBags(bags)
def main(argv):
vdrivetrain = VelocityDrivetrain()
if not FLAGS.plot:
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
namespaces = ['y2014_bot3', 'control_loops', 'drivetrain']
dog_loop_writer = control_loop.ControlLoopWriter(
"VelocityDrivetrain", [vdrivetrain.drivetrain_low_low,
vdrivetrain.drivetrain_low_high,
vdrivetrain.drivetrain_high_low,
vdrivetrain.drivetrain_high_high],
namespaces=namespaces)
dog_loop_writer.Write(argv[1], argv[2])
cim_writer = control_loop.ControlLoopWriter("CIM", [CIM()])
cim_writer.Write(argv[3], argv[4])
return
vl_plot = []
vr_plot = []
ul_plot = []
ur_plot = []
radius_plot = []
t_plot = []
left_gear_plot = []
right_gear_plot = []
vdrivetrain.left_shifter_position = 0.0
vdrivetrain.right_shifter_position = 0.0
vdrivetrain.left_gear = VelocityDrivetrain.LOW
vdrivetrain.right_gear = VelocityDrivetrain.LOW
glog.debug('K is %s', str(vdrivetrain.CurrentDrivetrain().K))
if vdrivetrain.left_gear is VelocityDrivetrain.HIGH:
glog.debug('Left is high')
else:
glog.debug('Left is low')
if vdrivetrain.right_gear is VelocityDrivetrain.HIGH:
glog.debug('Right is high')
else:
glog.debug('Right is low')
for t in numpy.arange(0, 1.7, vdrivetrain.dt):
if t < 0.5:
vdrivetrain.Update(throttle=0.00, steering=1.0)
elif t < 1.2:
vdrivetrain.Update(throttle=0.5, steering=1.0)
else:
vdrivetrain.Update(throttle=0.00, steering=1.0)
t_plot.append(t)
vl_plot.append(vdrivetrain.X[0, 0])
vr_plot.append(vdrivetrain.X[1, 0])
ul_plot.append(vdrivetrain.U[0, 0])
ur_plot.append(vdrivetrain.U[1, 0])
left_gear_plot.append((vdrivetrain.left_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
right_gear_plot.append((vdrivetrain.right_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
fwd_velocity = (vdrivetrain.X[1, 0] + vdrivetrain.X[0, 0]) / 2
turn_velocity = (vdrivetrain.X[1, 0] - vdrivetrain.X[0, 0])
if abs(fwd_velocity) < 0.0000001:
radius_plot.append(turn_velocity)
else:
radius_plot.append(turn_velocity / fwd_velocity)
# TODO(austin):
# Shifting compensation.
# Tighten the turn.
# Closed loop drive.
pylab.plot(t_plot, vl_plot, label='left velocity')
pylab.plot(t_plot, vr_plot, label='right velocity')
pylab.plot(t_plot, ul_plot, label='left voltage')
pylab.plot(t_plot, ur_plot, label='right voltage')
pylab.plot(t_plot, radius_plot, label='radius')
pylab.plot(t_plot, left_gear_plot, label='left gear high')
pylab.plot(t_plot, right_gear_plot, label='right gear high')
pylab.legend()
pylab.show()
return 0
def main(argv):
argv = FLAGS(argv)
vdrivetrain = VelocityDrivetrain()
if not FLAGS.plot:
if len(argv) != 5:
glog.fatal('Expected .h file name and .cc file name')
else:
namespaces = ['c2017', 'subsystems', 'drivetrain']
dog_loop_writer = control_loop.ControlLoopWriter(
"VelocityDrivetrain", [vdrivetrain.drivetrain_low_low,
vdrivetrain.drivetrain_low_high,
vdrivetrain.drivetrain_high_low,
vdrivetrain.drivetrain_high_high],
namespaces=namespaces)
dog_loop_writer.Write(argv[1], argv[2])
cim_writer = control_loop.ControlLoopWriter(
"CIM", [drivetrain.CIM()])
cim_writer.Write(argv[3], argv[4])
return
vl_plot = []
vr_plot = []
ul_plot = []
ur_plot = []
radius_plot = []
t_plot = []
left_gear_plot = []
right_gear_plot = []
vdrivetrain.left_shifter_position = 0.0
vdrivetrain.right_shifter_position = 0.0
vdrivetrain.left_gear = VelocityDrivetrain.LOW
vdrivetrain.right_gear = VelocityDrivetrain.LOW
glog.debug('K is %s', str(vdrivetrain.CurrentDrivetrain().K))
if vdrivetrain.left_gear is VelocityDrivetrain.HIGH:
glog.debug('Left is high')
else:
glog.debug('Left is low')
if vdrivetrain.right_gear is VelocityDrivetrain.HIGH:
glog.debug('Right is high')
else:
glog.debug('Right is low')
for t in numpy.arange(0, 1.7, vdrivetrain.dt):
if t < 0.5:
vdrivetrain.Update(throttle=0.00, steering=1.0)
elif t < 1.2:
vdrivetrain.Update(throttle=0.5, steering=1.0)
else:
vdrivetrain.Update(throttle=0.00, steering=1.0)
t_plot.append(t)
vl_plot.append(vdrivetrain.X[0, 0])
vr_plot.append(vdrivetrain.X[1, 0])
ul_plot.append(vdrivetrain.U[0, 0])
ur_plot.append(vdrivetrain.U[1, 0])
left_gear_plot.append((vdrivetrain.left_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
right_gear_plot.append((vdrivetrain.right_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
fwd_velocity = (vdrivetrain.X[1, 0] + vdrivetrain.X[0, 0]) / 2
turn_velocity = (vdrivetrain.X[1, 0] - vdrivetrain.X[0, 0])
if abs(fwd_velocity) < 0.0000001:
radius_plot.append(turn_velocity)
else:
radius_plot.append(turn_velocity / fwd_velocity)
# TODO(austin):
# Shifting compensation.
# Tighten the turn.
# Closed loop drive.
pylab.plot(t_plot, vl_plot, label='left velocity')
pylab.plot(t_plot, vr_plot, label='right velocity')
pylab.plot(t_plot, ul_plot, label='left voltage')
pylab.plot(t_plot, ur_plot, label='right voltage')
pylab.plot(t_plot, radius_plot, label='radius')
pylab.plot(t_plot, left_gear_plot, label='left gear high')
pylab.plot(t_plot, right_gear_plot, label='right gear high')
pylab.legend()
pylab.show()
return 0
def test_fatal(self):
log.fatal('test')
def main(argv):
db_file = None
list_file = None
img_path = None
ext = ".jpg"
if_check = False
help_msg = "dataset_create_imagelist.py -i <lmdb> -p <image path> -o <list>\
--check\n\
-i <lmdb> The input lmdb database file\n\
-o <list> The output image list file\n\
-p <image path> The path which store the downloaded images\n\
--check [optional] Force to check if the jpg image can be loaded.\n\
Which will slow down the process. Default False"
try:
opts, args = getopt.getopt(argv, "hi:p:o:", ["check"])
except getopt.GetoptError:
print help_msg
sys.exit(2)
for opt, arg in opts:
if opt == "-h":
print help_msg
sys.exit()
elif opt == "-i":
db_file = arg
elif opt == "-o":
list_file = arg
elif opt == "-p":
img_path = arg
elif opt == "--check":
if_check = True
else:
print help_msg
sys.exit(2)
# Check arguments
if db_file is None or list_file is None or img_path is None:
print help_msg
sys.exit(2)
# Check if the image path exists
log.info("Check image path %s" % img_path)
if os.path.exists(img_path) is False:
log.fatal("Can not locate the image path %s" % img_path)
sys.exit(2)
# Create the text list file
log.info("Open the image list file %s" % list_file)
try:
fp = open(list_file, "w")
except IOError:
log.fatal("Can not open %s for writing" % list_file)
sys.exit(2)
# open the lmdb file
log.info("Open db file %s" % db_file)
db = lt.open_db_ro(db_file)
db_stat = db.stat()
log.info("Total Entries: %d" % db_stat["entries"])
bar = eb.EasyProgressBar()
bar.set_end(db_stat["entries"])
bar.start()
counter = 0
err_counter = 0
# Iter the whole database
with db.begin(write=False) as txn:
with txn.cursor() as cur:
for key, val in cur:
counter += 1
# Get the avaliable url to download photo
try:
val_dic = yaml.load(val)
photo = myxml.parse_xml_to_etree(val_dic["photo"])
photo_id = photo.get("id")
focal_in35 = int(val_dic["focal_in35"])
except:
err_counter += 1
continue
# Filter our some error value
if focal_in35 < 5 or focal_in35 > 200:
continue
# Get the image full name
if img_path[-1] == r"/":
img_name = img_path + photo_id + ext
else:
img_name = img_path + r"/" + photo_id + ext
img_name = os.path.abspath(img_name)
# Check if the image exists
if if_check:
# Load the image
try:
Image.open(img_name)
except:
err_counter += 1
continue
else:
if os.path.exists(img_name) is False:
err_counter += 1
continue
# Write the info to list file
fp.writelines(img_name + " %d\n" % focal_in35)
bar.update(counter)
# Finish the loop
db.close()
fp.close()
bar.finish()
log.info("Finished. errors: %d" % err_counter)
def main(argv):
src_file = None
dst_file = None
config_file = None
result_dict = {}
help_msg = 'dataset_split_class.py -i <indexfile> -o <output> -c <config>\n\
-i <file> The input index text file\n\
-o <file> The output index text file\n\
-c <file> The configure xml file'
try:
opts, args = getopt.getopt(argv, 'hi:c:o:')
except getopt.GetoptError:
print help_msg
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print help_msg
sys.exit()
elif opt == '-i':
src_file = arg
elif opt == '-o':
dst_file = arg
elif opt == '-c':
config_file = arg
else:
print help_msg
sys.exit(2)
if src_file is None or dst_file is None or config_file is None:
print help_msg
sys.exit(2)
# Check the config file
log.info('Parsing configure file: %s' % config_file)
config = myxml.parse_classifier_xml(config_file)
result_dict = dict.fromkeys(config)
if config is None:
log.fatal('Parse configure file %s error' % config_file)
sys.exit(2)
# Check the src_file
log.info('Opening %s' % src_file)
try:
src_fp = open(src_file, 'r')
except IOError:
log.fatal('Can not open %s' % src_file)
sys.exit(2)
# Open the dst file
log.info('Opening %s' % dst_file)
try:
dst_fp = open(dst_file, 'w')
except IOError:
log.fatal('Can not open %s' % dst_file)
sys.exit(2)
# loop the src_file
for line in src_fp.readlines():
element = line.split(' ')
if len(element) != 2:
log.warn('\033[31mWARNING:\033[0m Extra space in %s' % line)
continue
focal_length = int(element[-1])
image_path = element[0]
# Get the label
label = get_class(config, focal_length)
if label is None:
log.warn('\033[32mSKIP:\033[0m %s' % line)
continue
if result_dict[label] is None:
result_dict[label] = 1
else:
result_dict[label] += 1
# Write the new file
dst_fp.writelines(image_path + ' %d\n' % label)
src_fp.close()
dst_fp.close()
log.info('Final result: %s' % str(result_dict))
log.info('Finished')
prj_log = os.path.join(prj_log, '%4s' % args.year)
tool.check_path(prj_dir)
tool.check_path(prj_log)
prj_dir = os.path.join(prj_dir, '%03s' % args.idoy)
prj_log = os.path.join(prj_log, '%03s' % args.idoy, "log_tb")
tool.check_path(prj_dir)
tool.check_path(xml_dir)
tool.check_path(prj_log)
os.chdir(prj_dir)
os.system("rm -r ./*") # 注意,会将工程目录清空
os.system("mkdir ./log_tb")
os.system("cp -rf %s/*log ./log_tb" % prj_log) # 将统一存放的log文件粘贴到prj路径下
tool.check_path(prd_dir)
tool.check_path(log_dir)
glog.fatal("crt dir is : " + os.getcwd())
# create the xml file
glog.fatal("==========> beg GNSS POD ALL MODE.")
glog.fatal("==========> beg create the xml file.")
doy_xml = os.path.join(xml_dir,
"gns_pod_%4s%03d.xml" % (args.year, int(args.idoy)))
create_xml_py = os.path.join(scp_dir, "gns_xml_create_xml.py")
update_xml_py = os.path.join(scp_dir, "gns_xml_update_editres.py")
update_ambfix_xml_py = os.path.join(scp_dir, "gns_xml_update_ambfix.py")
os.system("chmod +x " + create_xml_py)
os.system("chmod +x " + update_xml_py)
os.system("chmod +x " + update_ambfix_xml_py)
glog.fatal("==========> creat xml.")
