def dataFromNC(fnc,
fnav,
sv,
fsp3=None,
el_mask=30,
tlim=None,
satpos=False,
ipp=False,
ipp_alt=None):
leap_seconds = uf.getLeapSeconds(fnav)
D = gr.load(fnc, useindicators=True).sel(sv=sv)
D['time'] = np.array([np.datetime64(ttt) for ttt in D.time.values])
if tlim is not None:
if len(tlim) == 2:
D = D.where(np.logical_and(D.time >= np.datetime64(tlim[0]),
D.time <= np.datetime64(tlim[1])),
drop=True)
obstimes64 = D.time.values
dt = np.array([Timestamp(t).to_pydatetime() for t in obstimes64]) - \
datetime.timedelta(seconds = leap_seconds)
if fsp3 is None:
aer = gpsSatPosition(fnav,
dt,
sv=sv,
rx_position=D.position,
coords='aer')
else:
aer = gpsSatPositionSP3(fsp3,
dt,
sv=sv,
rx_position=D.position_geodetic,
coords='aer')
idel = (aer[1, :] >= el_mask)
aer[:, ~idel] = np.nan
D['time'] = dt
if satpos:
D['az'] = aer[0, :]
D['el'] = aer[1, :]
D['idel'] = idel
if ipp:
if ipp_alt is None:
print('Auto assigned altitude of the IPP: 250 km')
ipp_alt = 250e3
else:
ipp_alt *= 1e3
rec_lat, rec_lon, rec_alt = D.position_geodetic
fm = np.sin(np.radians(aer[1]))
r_new = ipp_alt / fm
lla_vector = np.array(
aer2geodetic(aer[0], aer[1], r_new, rec_lat, rec_lon, rec_alt))
D['ipp_lon'] = lla_vector[1]
D['ipp_lat'] = lla_vector[0]
D['ipp_alt'] = ipp_alt
return D
def dataFromNC(fnc, fnav, el_mask=30, tlim=None):
leap_seconds = gu.getLeapSeconds(fnav)
D = gr.load(fnc, useindicators=True).sel(sv=sv)
if tlim is not None:
if len(tlim) == 2:
D = D.where(np.logical_and(D.time >= np.datetime64(tlim[0]),
D.time <= np.datetime64(tlim[1])),
drop=True)
obstimes64 = D.time.values
dt = np.array([Timestamp(t).to_pydatetime() for t in obstimes64]) - \
timedelta(seconds = leap_seconds)
rx_xyz = D.position
aer = pyGnss.gpsSatPosition(fnav,
dt,
sv=sv,
rx_position=rx_xyz,
coords='aer')
idel = (aer[1] >= el_mask)
dt = dt[idel]
return dt, D, idel
def singleRx(obs, nav, sv='G23', args=['L1','S1'], tlim=None,rawplot=False,
sp=True,s4=False,polyfit=False,indicator=False,
alt=300,el_mask=30,skip=20,porder=8,tec_ch=2,
forder=5,fc=0.1,fs=1):
def _plot(x,y,title=''):
plt.figure()
plt.title(title)
plt.plot(x,y,'b')
D = xarray.open_dataset(obs, group='OBS')
rx_xyz = D.position
leap_seconds = uf.getLeapSeconds(nav)
obstimes64 = D.time.values
times = np.array([Timestamp(t).to_pydatetime() for t in obstimes64]) - \
timedelta(seconds = leap_seconds)
# define tlim ie. skip
if tlim is not None:
s = ((times>=tlim[0]) & (times<=tlim[1]))
else:
s = np.full(times.shape[0], True, dtype=bool)
s[:skip] = False
times = times[s]
# Get satellite position
aer = gpsSatPosition(nav, times, sv=sv, rx_position=rx_xyz, coords='aer')
# Elevation mask
idel = aer[1] >= el_mask
times = times[idel]
# times to output dict: Y
Y = {'times': times}
Y['rx_xyz'] = rx_xyz
Y['az'] = aer[0][idel]
Y['el'] = aer[1][idel]
for arg in args:
if not arg[1:] == 'TEC':
X = D.sel(sv=sv)[arg].values[s][idel]
# To dict
Y[arg] = X
# Indicators?
if indicator:
try:
if arg[0] == 'L' and arg[-1] != '5':
argi = arg + 'lli'
elif arg[0] == 'C' or arg[0] == 'P' or arg == 'L5':
argi = arg + 'ssi'
else:
argi = ''
Xi = D.sel(sv=sv)[argi].values[s:][idel]
Y[argi] = Xi
except Exception as e:
print (e)
if rawplot:
_plot(times,X,arg)
if arg[0] == 'L' or arg[0] == 'C':
if arg == 'C1':
X = X * f1 / c0 # To cycles
Xd = uf.phaseDetrend(X, order=porder)
if polyfit:
# To dict
Y[arg+'polyfit'] = Xd
if rawplot:
if rawplot:
_plot(times,Xd,arg+'_detrend_poly')
if sp:
Xy = uf.hpf(Xd, order=forder,fc=fc,plot=False,fs=fs)
# To dict
Y['sp'] = Xy
if rawplot:
_plot(times[100:],Xy[100:],arg+'_scint')
if arg[0] == 'S':
if s4:
Xy = AmplitudeScintillationIndex(X,60)
# To dict
Y['s4'] = Xy
if rawplot:
_plot(times,Xy,arg+'_S4')
if arg[1:] == 'TEC':
if tec_ch == 2:
C1 = D.sel(sv=sv)['C1'].values[s][idel]
L1 = D.sel(sv=sv)['L1'].values[s][idel]
C2 = D.sel(sv=sv)['P2'].values[s][idel]
L2 = D.sel(sv=sv)['L2'].values[s][idel]
elif tec_ch == 5:
C1 = D.sel(sv=sv)['C1'].values[s][idel]
L1 = D.sel(sv=sv)['L1'].values[s][idel]
C2 = D.sel(sv=sv)['C5'].values[s][idel]
L2 = D.sel(sv=sv)['L5'].values[s][idel]
sTEC = getPhaseCorrTEC(L1, L2, C1, C2,channel=tec_ch)
sTEC = sTEC - np.nanmin(sTEC)
if arg == 'sTEC':
# To dict
Y[arg] = sTEC
if rawplot:
_plot(times, sTEC,title=arg)
elif arg == 'vTEC':
vTEC = getVerticalTEC(sTEC,aer[1][idel],alt)
# To dict
Y[arg] = vTEC
if rawplot:
_plot(times, vTEC, title=arg)
# return dict with data/args
return Y
arg = 'L1'
el_mask = 30
skip = 10
porder = 8
forder = 6
fc = 0.1
fs = 1
D = xarray.open_dataset(obs, group='OBS')
# Dummy arrays
T = np.nan * np.ones(D.sizes['time'] - skip)
Ls = np.copy(T)
Ss = np.copy(T)
#
rx_xyz = D.position
leap_seconds = gu.getLeapSeconds(nav)
obstimes64 = D.time[skip:].values
obstimes_dt = np.array([Timestamp(t).to_pydatetime() for t in obstimes64]) \
- timedelta(seconds = leap_seconds)
Ds = D.sel(sv=sv)
L1 = Ds['L1'][skip:].values
S1 = Ds['S1'][skip:].values
aer = pyGnss.getSatellitePosition(rx_xyz,
sv,
obstimes_dt,
nav,
cs='aer',
dtype='georinex')
idel = (aer[1] >= el_mask)
