def add(config_key, dset):
delta_pos = list()
for _ in dset.for_each_suffix("station"):
if position.is_position(dset.site_pos):
sta_delta = position.PositionDelta(np.zeros((dset.num_obs, 3)),
system="gcrs",
ref_pos=dset.site_pos)
elif position.is_posvel(dset.site_pos):
sta_delta = position.PosVelDelta(np.zeros((dset.num_obs, 6)),
system="gcrs",
ref_pos=dset.site_pos)
if config_key not in dset.fields:
return list(sta_delta)
pos_fields = [
f for f in dset[config_key]._fields
if f.endswith(dset.default_field_suffix)
]
for field in pos_fields:
sta_delta += dset[config_key][field]
delta_pos.append(sta_delta)
return delta_pos
def ocean_pole_tides_station(dset, opt):
"""Calculate the ocean pole tide corrections for a station
Ocean pole tide corrections are returned in meters in the Geocentric Celestial Reference System for each
observation.
Args:
dset: A Dataset containing model data.
version: Version number of conventional mean pole model
opt: Apriori ocean pole tide coefficients
Returns:
Numpy array with ocean tide corrections in meters.
"""
eop = apriori.get("eop", time=dset.time)
# Constants in IERS Conventions equation 7.29
H_p = np.sqrt(8 * np.pi / 15) * constant.omega ** 2 * constant.a ** 4 / constant.GM
K = 4 * np.pi * constant.G * constant.a * constant.rho_w * H_p / (3 * constant.g_E)
# @todo make these global? related to love numbers somehow
gamma_2_R = 0.6870
gamma_2_I = 0.0036
# Equation (7.24) IERS Conventions 2010
m_1 = (eop.x - eop.x_pole) * Unit.arcsec2rad
m_2 = (eop.y_pole - eop.y) * Unit.arcsec2rad
lat, lon, _ = dset.site_pos.pos.llh.T
u_enu_R = np.array(
[opt["u_e_R"](lon, lat, grid=False), opt["u_n_R"](lon, lat, grid=False), opt["u_r_R"](lon, lat, grid=False)]
)
u_enu_I = np.array(
[opt["u_e_I"](lon, lat, grid=False), opt["u_n_I"](lon, lat, grid=False), opt["u_r_I"](lon, lat, grid=False)]
)
# Equation (7.29) IERS Conventions 2010
denu = (K * ((m_1 * gamma_2_R + m_2 * gamma_2_I) * u_enu_R + (m_1 * gamma_2_R - m_2 * gamma_2_I) * u_enu_I)).T
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(denu, system="enu", ref_pos=dset.site_pos, time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
denu = np.concatenate((denu, np.zeros(denu.shape)), axis=1)
pos_correction = position.PosVelDelta(denu, system="enu", ref_pos=dset.site_pos, time=dset.time)
else:
log.fatal(f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray.")
return pos_correction.gcrs
def solid_pole_tides_station(dset):
"""Calculate the solid pole tide corrections for a station
Solid pole tide corrections are returned in meters in the Geocentric Celestial Reference System for each
observation.
Args:
dset: A Dataset containing model data.
version: Version number of conventional mean pole model
Returns:
Numpy array with ocean tide corrections in meters.
"""
eop = apriori.get("eop", time=dset.time)
# Equation (7.24) IERS Conventions 2010
m_1 = eop.x - eop.x_pole
m_2 = eop.y_pole - eop.y
lat, lon, _ = dset.site_pos.pos.llh.T
theta = np.pi / 2 - lat
coslon, sinlon = np.cos(lon), np.sin(lon)
# Equation (7.26) IERS Conventions 2010
dup = -33 * np.sin(2 * theta) * (m_1 * coslon + m_2 * sinlon) * Unit.mm2m
dsouth = -9 * np.cos(2 * theta) * (m_1 * coslon + m_2 * sinlon) * Unit.mm2m
deast = 9 * np.cos(theta) * (m_1 * sinlon + m_2 * coslon) * Unit.mm2m
# Correction in topocentric (east, north, up) coordinates
denu = np.vstack((deast, -dsouth, dup)).T
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
denu = np.concatenate((denu, np.zeros(denu.shape)), axis=1)
pos_correction = position.PosVelDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
else:
log.fatal(
f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray."
)
return pos_correction.gcrs
def solid_tides_station(dset, correction_cache):
"""Calculate the solid tide corrections for a station
Solid tide corrections are returned in meters in the Geocentric Celestial Reference System for each observation.
Args:
dset: A Dataset containing model data.
Returns:
Numpy array with solid tide corrections in meters.
"""
eph = apriori.get("ephemerides", time=dset.time)
dxyz = np.zeros((dset.num_obs, 3))
obs_dt = dset.time.utc.datetime
hour_of_day = dset.time.utc.jd_frac * 24
sun_itrs = eph.pos_itrs("sun")
moon_itrs = eph.pos_itrs("moon")
# Calculate correction
for obs in range(dset.num_obs):
cache_key = (dset.station[obs], obs_dt[obs])
if cache_key in correction_cache:
dxyz[obs] = correction_cache[cache_key]
else:
dxyz[obs] = iers.dehanttideinel(
dset.site_pos.pos[obs],
obs_dt[obs].year,
obs_dt[obs].month,
obs_dt[obs].day,
hour_of_day[obs],
sun_itrs[obs],
moon_itrs[obs],
)
correction_cache[cache_key] = dxyz[obs]
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(dxyz, system="trs", ref_pos=dset.site_pos, time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
dxyz = np.concatenate((dxyz, np.zeros(dxyz.shape)), axis=1)
pos_correction = position.PosVelDelta(dxyz, system="trs", ref_pos=dset.site_pos, time=dset.time)
else:
log.fatal(f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray.")
return pos_correction.gcrs
def non_tidal_atmospheric_loading_station(ntapl, dset):
"""Apply non tidal atmospheric loading displacements for a station field.
Corrections are returned in meters in the Geocentric
Celestial Reference System for each observation.
Args:
dset: A Dataset containing model data
Returns:
Numpy array: GCRS corrections in meters.
"""
lat, lon, _ = dset.site_pos.pos.llh.T
try:
dup = ntapl["up"](dset.time, lon, lat)
deast = ntapl["east"](dset.time, lon, lat)
dnorth = ntapl["north"](dset.time, lon, lat)
except KeyError:
log.warn(
f"No non-tidal atmospheric loading available for {dset.rundate}")
dup = np.zeros(len(dset.time))
deast = np.zeros(len(dset.time))
dnorth = np.zeros(len(dset.time))
denu = np.stack((deast, dnorth, dup), axis=1)
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
denu = np.concatenate((denu, np.zeros(denu.shape)), axis=1)
pos_correction = position.PosVelDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
else:
log.fatal(
f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray."
)
return pos_correction.gcrs
def atmospheric_tides_station(dset):
"""Calculate the atmospheric tides corrections for a station
Atmospheric tides corrections are returned in meters in the Geocentric Celestial Reference System for each
observation.
Args:
dset: A Dataset containing model data
Returns:
Numpy array with atmospheric tide corrections in meters.
"""
coeff = apriori.get("atmospheric_tides")
use_cmc = config.tech.atmospheric_tides_cmc.bool
# S1 has a period of 1 cycle/day, S2 has a period of 2 cycle/day
omega_1 = 2 * np.pi
omega_2 = 4 * np.pi
# Time argument is fraction of UT1 day, see [2].
t = dset.time.ut1.jd_frac
lat, lon, _ = dset.site_pos.pos.llh.T
# Equation 7.19a and 7.19b from IERS Conventions 2010
de = (
coeff["A_d1_e"](lon, lat, grid=False) * np.cos(omega_1 * t)
+ coeff["B_d1_e"](lon, lat, grid=False) * np.sin(omega_1 * t)
+ coeff["A_d2_e"](lon, lat, grid=False) * np.cos(omega_2 * t)
+ coeff["B_d2_e"](lon, lat, grid=False) * np.sin(omega_2 * t)
)
dn = (
coeff["A_d1_n"](lon, lat, grid=False) * np.cos(omega_1 * t)
+ coeff["B_d1_n"](lon, lat, grid=False) * np.sin(omega_1 * t)
+ coeff["A_d2_n"](lon, lat, grid=False) * np.cos(omega_2 * t)
+ coeff["B_d2_n"](lon, lat, grid=False) * np.sin(omega_2 * t)
)
du = (
coeff["A_d1_u"](lon, lat, grid=False) * np.cos(omega_1 * t)
+ coeff["B_d1_u"](lon, lat, grid=False) * np.sin(omega_1 * t)
+ coeff["A_d2_u"](lon, lat, grid=False) * np.cos(omega_2 * t)
+ coeff["B_d2_u"](lon, lat, grid=False) * np.sin(omega_2 * t)
)
denu = np.vstack([de, dn, du]).T * Unit.mm2m
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(denu, system="enu", ref_pos=dset.site_pos, time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
denu = np.concatenate((denu, np.zeros(denu.shape)), axis=1)
pos_correction = position.PosVelDelta(denu, system="enu", ref_pos=dset.site_pos, time=dset.time)
else:
log.fatal(f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray.")
# Add center of mass corrections
if use_cmc:
# Equation (7.20) in [1]
coeff_cmc = apriori.get("atmospheric_tides_cmc")
cmc = (
coeff_cmc["A1"][None, :] * np.cos(omega_1 * t)[:, None]
+ coeff_cmc["B1"][None, :] * np.sin(omega_1 * t)[:, None]
+ coeff_cmc["A2"][None, :] * np.cos(omega_2 * t)[:, None]
+ coeff_cmc["B2"][None, :] * np.sin(omega_2 * t)[:, None]
)
if position.is_position(dset.site_pos):
cmc_correction = position.PositionDelta(cmc, system="trs", ref_pos=dset.site_pos, time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
cmc = np.concatenate((cmc, np.zeros(cmc.shape)), axis=1)
cmc_correction = position.PosVelDelta(cmc, system="trs", ref_pos=dset.site_pos, time=dset.time)
pos_correction = pos_correction.trs + cmc_correction.trs
return pos_correction.gcrs
def ocean_tides_station(dset, amplitudes, phases, correction_cache):
"""Calculate the ocean tide corrections for a station
Ocean tide corrections are returned in meters in the Geocentric Celestial Reference System for each observation.
Args:
dset: A Dataset containing model data.
Returns:
Numpy array with ocean tide corrections in meters.
"""
denu = np.zeros((dset.num_obs, 3))
use_cmc = config.tech.ocean_tides_cmc.bool
# Calculate correction
for obs, site_id in enumerate(dset.site_id):
if site_id not in amplitudes:
# Warn about missing Ocean Tides Coefficients
if site_id in _WARNED_MISSING:
continue
station = dset.unique("station", site_id=site_id)[0]
log.error(
f"Missing ocean loading coefficients for site id {site_id!r} ({station}). Correction set to zero."
)
_WARNED_MISSING.add(site_id)
continue
cache_key = (dset.station[obs], dset.time.utc.datetime[obs])
if cache_key in correction_cache:
denu[obs] = correction_cache[cache_key]
else:
epoch = [float(t) for t in dset.time.utc[obs].yday.split(":")]
dup, dsouth, dwest = iers.hardisp(epoch, amplitudes[site_id],
phases[site_id], 1, 1.0)
# Correction in topocentric (east, north, up) coordinates
denu[obs] = np.array([-dwest[0], -dsouth[0], dup[0]])
correction_cache[cache_key] = denu[obs]
if position.is_position(dset.site_pos):
pos_correction = position.PositionDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
denu = np.concatenate((denu, np.zeros(denu.shape)), axis=1)
pos_correction = position.PosVelDelta(denu,
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
else:
log.fatal(
f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray."
)
# Center of mass corrections
if use_cmc:
coeff_cmc = apriori.get("ocean_tides_cmc")
in_phase = coeff_cmc["in_phase"]
cross_phase = coeff_cmc["cross_phase"]
cmc = np.zeros((dset.num_obs, 3))
for obs, time in enumerate(dset.time.utc):
year, doy = time.datetime.year, float(
time.datetime.strftime("%j")) + time.mjd_frac
angle = iers.arg2(year, doy)[:, None]
cmc[obs] += np.sum(in_phase * np.cos(angle) +
cross_phase * np.sin(angle),
axis=0)
if position.is_position(dset.site_pos):
cmc_correction = position.PositionDelta(cmc,
system="trs",
ref_pos=dset.site_pos,
time=dset.time)
elif position.is_posvel(dset.site_pos):
# set velocity to zero
cmc = np.concatenate((cmc, np.zeros(cmc.shape)), axis=1)
cmc_correction = position.PosVelDelta(cmc,
system="trs",
ref_pos=dset.site_pos,
time=dset.time)
pos_correction = pos_correction.trs + cmc_correction
return pos_correction.gcrs
def eccentricity_vector_station(ecc, dset):
"""Calculate the eccentricity vector for a station.
Corrections are returned in meters in the Geocentric
Celestial Reference System for each observation.
Args:
dset: A Dataset containing model data
Returns:
Numpy array: GCRS corrections in meters.
"""
if position.is_position(dset.site_pos):
ecc_vector = position.PositionDelta(np.zeros((dset.num_obs, 3)),
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
elif position.is_posvel(dset.site_pos):
ecc_vector = position.PosVelDelta(np.zeros((dset.num_obs, 6)),
system="enu",
ref_pos=dset.site_pos,
time=dset.time)
else:
log.fatal(
f"dset.site_pos{dset.default_field_suffix} is not a PositionArray or PosVelArray."
)
fieldnames = config.tech.eccentricity.identifier.list
fielddata = [dset[field] for field in fieldnames]
if len(fieldnames) > 1:
keys = set(tuple(zip(*fielddata)))
else:
keys = fielddata[0].tolist()
for key in keys:
if len(fieldnames) > 1:
filters = dict(zip(fieldnames, key))
else:
filters = dict(zip(fieldnames, [key]))
if key not in ecc:
ecc_vector[dset.filter(**filters), 0:3] = np.zeros(3)
if key in _WARNED_MISSING:
continue
log.warn(
f"Missing eccentricity data for {key}. Vector set to zero.")
_WARNED_MISSING.add(key)
continue
if ecc[key]["coord_type"] == "ENU":
ecc_vector[dset.filter(**filters), 0:3] = ecc[key]["vector"]
ecc_vector = ecc_vector.trs
for key in keys:
if len(fieldnames) > 1:
filters = dict(zip(fieldnames, key))
else:
filters = dict(zip(fieldnames, [key]))
if key not in ecc:
ecc_vector[dset.filter(**filters), 0:3] = np.zeros(3)
continue
if ecc[key]["coord_type"] == "XYZ":
ecc_vector[dset.filter(**filters), 0:3] = ecc[key]["vector"]
return ecc_vector.gcrs
def satellite_phase_center_offset(
self,
dset: "Dataset",
sys_freq: Union[None, Dict[str, Dict[str, str]]] = None
) -> "PosVelDeltaArray":
"""Determine satellite phase center offset correction vectors given in ITRS
Satellite phase center offset (PCO) corrections are frequency dependent. The argument 'sys_freq' defines, which
frequencies for a given GNSS should be used. If two frequencies for a GNSS are given, then the PCO is
determined as ionospheric-free linear combination. If 'sys_freq' is not defined as input argument, then
'sys_freq' is generated based on the given observation types in dataset 'dset'.
Args:
dset: Model data.
sys_freq: Dictionary with frequency or frequency combination given for GNSS identifier:
sys_freq = { <sys_id>: <freq> } (e.g. sys_freq = {'E': 'E1', 'G': 'L1_L2'} )
Returns:
Satellite phase center offset correction vectors given in ITRS in meter
"""
# GNSS Freq number GNSS freq
# L<num>/C<num>
# ___________________________________________
# C (BeiDou): 2 'B1'
# 7 'B2'
# 6 'B3'
# G (GPS): 1 'L1'
# 2 'L2'
# 5 'L5'
# R (GLONASS): 1 'G1'
# 2 'G2'
# 3 'G3'
# E (Galileo): 1 'E1'
# 8 'E5 (E5a+E5b)'
# 5 'E5a'
# 7 'E5b'
# 6 'E6'
# I (IRNSS): 5 'L5'
# 9 'S'
# J (QZSS): 1 'L1'
# 2 'L2'
# 5 'L5'
# 6 'LEX'
# S (SBAS): 1 'L1'
# 5 'L5'
obstype_to_gnss_freq = {
"C": {
"2": "B1",
"7": "B2",
"6": "B3"
},
"E": {
"1": "E1",
"8": "E5",
"5": "E5a",
"7": "E5b",
"6": "E6"
},
"G": {
"1": "L1",
"2": "L2",
"5": "L5"
},
"I": {
"5": "L5",
"9": "S"
},
"J": {
"1": "L1",
"2": "L2",
"5": "L5",
"6": "LEX"
},
"R": {
"1": "G1",
"2": "G2",
"3": "G3"
},
"S": {
"1": "L1",
"5": "L5"
},
}
correction = position.PosVelDelta(val=np.zeros((dset.num_obs, 6)),
system="yaw",
ref_pos=dset.sat_posvel,
time=dset.time)
used_date = None
# Get GNSS frequency based on observation type
if sys_freq is None:
sys_freq = dict()
obstypes = dset.meta["obstypes"]
for sys in obstypes:
freqs = {o[1] for o in obstypes[sys]}
sys_freq[sys] = "_".join(f"{obstype_to_gnss_freq[sys][f]}"
for f in sorted(freqs))
# Loop over all satellites given in RINEX observation file and configuration file
for sat in dset.unique("satellite"):
# Skip satellites, which are not given in ANTEX file
if sat not in self.data:
log.warn(
f"Satellite {sat} is not given in ANTEX file {self.file_path}. That means no satellite antenna "
f"phase center offset correction can be applied for satellite {sat}."
)
continue
# Get array with information about, when observation are available for the given satellite (indicated by True)
idx = dset.filter(satellite=sat)
# Get used date
used_date = self._used_date(sat, dset.analysis["rundate"])
if used_date is None:
continue
# Add PCO to Dataset meta
pco_sat = self.get_pco_sat(sat, sys_freq, used_date)
dset.meta.setdefault("pco_sat",
dict()).update({sat: pco_sat.tolist()})
correction[idx] = np.repeat(np.append(pco_sat,
np.zeros(3))[None, :],
np.sum(idx),
axis=0)
# Transform PCO given in satellite body-fixed reference frame (for GPS and Galileo assumed to be aligned
# to yaw-steering reference frame) to ITRS
return correction.trs
