def get_processed_data(filepath):
dog = AstroDog()
print('Preprocessing: ', filepath)
obs_data = RINEXFile(filepath)
rinex_meas_grouped = raw.read_rinex_obs(obs_data)
del obs_data
rinex_processed_grouped = []
for meas in tqdm(rinex_meas_grouped):
proc = raw.process_measurements(meas, dog=dog)
rinex_processed_grouped.append(proc)
print('Data is IN!')
del rinex_meas_grouped
return rinex_processed_grouped
def test_station_position(self):
print(
'WARNING THIS TAKE CAN TAKE A VERY LONG TIME THE FIRST RUN TO DOWNLOAD'
)
dog = AstroDog()
# Building this cache takes forever just copy it from repo
cache_directory = '/tmp/gnss/cors_coord/'
try:
os.mkdir('/tmp/gnss/')
except OSError:
pass
try:
os.mkdir(cache_directory)
except OSError:
pass
examples_directory = os.path.join(
os.path.dirname(os.path.abspath(__file__)), '../examples')
copyfile(os.path.join(examples_directory, 'cors_station_positions'),
os.path.join(cache_directory, 'cors_station_positions'))
station_name = 'sc01'
time = GPSTime.from_datetime(datetime(2020, 1, 11))
slac_rinex_obs_file = download_cors_station(time, station_name,
dog.cache_dir)
obs_data = RINEXFile(slac_rinex_obs_file)
sc01_exact_position = get_station_position('sc01')
rinex_meas_grouped = raw.read_rinex_obs(obs_data)
rinex_corr_grouped = []
for meas in tqdm(rinex_meas_grouped):
proc = raw.process_measurements(meas, dog=dog)
corr = raw.correct_measurements(meas, sc01_exact_position, dog=dog)
rinex_corr_grouped.append(corr)
# Using laika's WLS solver we can now calculate position
# fixes for every epoch (every 30s) over 24h.
ests = []
for corr in tqdm(rinex_corr_grouped[:]):
fix, _ = raw.calc_pos_fix(corr)
ests.append(fix)
ests = np.array(ests)
mean_fix = np.mean(ests[:, :3], axis=0)
np.testing.assert_allclose(mean_fix,
sc01_exact_position,
rtol=0,
atol=1)
def data_for_station(dog, station_name, date=None):
"""
Get data from a particular station and time.
Station names are CORS names (eg: 'slac')
Dates are datetimes (eg: datetime(2020,1,7))
"""
if date is None:
date = datetime(2020,1,7)
time = GPSTime.from_datetime(date)
rinex_obs_file = download_cors_station(time, station_name, dog.cache_dir)
obs_data = RINEXFile(rinex_obs_file)
station_pos = get_station_position(station_name)
return station_pos, raw.read_rinex_obs(obs_data)
def run_station_position(self, length):
dog = AstroDog()
# Building this cache takes forever just copy it from repo
cache_directory = '/tmp/gnss/cors_coord/'
os.makedirs('/tmp/gnss/', exist_ok=True)
os.makedirs(cache_directory, exist_ok=True)
examples_directory = os.path.join(
os.path.dirname(os.path.abspath(__file__)), '../examples')
copyfile(os.path.join(examples_directory, 'cors_station_positions'),
os.path.join(cache_directory, 'cors_station_positions'))
station_name = 'sc01'
time = GPSTime.from_datetime(datetime(2020, 1, 11))
slac_rinex_obs_file = download_cors_station(time, station_name,
dog.cache_dir)
obs_data = RINEXFile(slac_rinex_obs_file)
sc01_exact_position = get_station_position('sc01')
rinex_meas_grouped = raw.read_rinex_obs(obs_data)
# Select small sample out of ~2800 to reduce computation time
rinex_meas_grouped = rinex_meas_grouped[:length]
rinex_corr_grouped = []
for meas in tqdm(rinex_meas_grouped):
proc = raw.process_measurements(meas, dog=dog)
corr = raw.correct_measurements(proc, sc01_exact_position, dog=dog)
rinex_corr_grouped.append(corr)
# Using laika's WLS solver we can now calculate position
# fixes for every epoch (every 30s) over 24h.
ests = []
for corr in tqdm(rinex_corr_grouped):
ret = raw.calc_pos_fix(corr)
if len(ret) > 0:
fix, _ = ret
ests.append(fix)
ests = np.array(ests)
mean_fix = np.mean(ests[:, :3], axis=0)
np.testing.assert_allclose(mean_fix,
sc01_exact_position,
rtol=0,
atol=1)
def data_for_station(dog, station_name, date):
"""
Get data from a particular station and time. Wraps a number of laika function calls.
Station names are CORS names (eg: 'slac')
Dates are datetimes (eg: datetime(2020,1,7))
"""
time = GPSTime.from_datetime(date)
rinex_obs_file = None
# handlers for specific networks
handlers = {'Korea': download_korean_station}
network = station_network_info.get(station_name, None)
# no special network, so try using whatever
if network is None:
try:
station_pos = get_station_position(station_name,
cache_dir=dog.cache_dir)
rinex_obs_file = download_cors_station(time,
station_name,
cache_dir=dog.cache_dir)
except (KeyError, DownloadError):
pass
if not rinex_obs_file:
# station position not in CORS map, try another thing
if station_name in extra_station_info:
station_pos = numpy.array(extra_station_info[station_name])
rinex_obs_file = download_misc_igs_station(
time, station_name, cache_dir=dog.cache_dir)
else:
raise DownloadError
else:
station_pos = numpy.array(extra_station_info[station_name])
rinex_obs_file = handlers[network](time,
station_name,
cache_dir=dog.cache_dir)
obs_data = RINEXFile(rinex_obs_file, rate=30)
return station_pos, raw.read_rinex_obs(obs_data)
def get_processed_data(filepath):
dog = AstroDog()
print('step 1')
obs_data = RINEXFile(filepath)
print('obs_data size: ', sys.getsizeof(obs_data))
print('step 2')
rinex_meas_grouped = raw.read_rinex_obs(obs_data)
del obs_data
print('step 3')
print('rinex_meas_grouped size: ', sys.getsizeof(rinex_meas_grouped))
rinex_processed_grouped = []
step = 1
for meas in tqdm(rinex_meas_grouped):
print(step + 1)
proc = raw.process_measurements(meas, dog=dog)
rinex_processed_grouped.append(proc)
print('Data is IN!')
del rinex_meas_grouped
print('rinex_processed_grouped size: ', sys.getsizeof(rinex_processed_grouped))
return rinex_processed_grouped
