def write2HDF(data, h5fn, wl):
obstimes = data.time.values.astype(datetime)
ts = gu.datetime2posix(obstimes)
az = data.az[1]
el = data.el[1]
images = data[wl].values
N = az.shape[0]
lat0 = data.lat
lon0 = data.lon
alt0 = data.alt_m
try:
f = h5py.File(h5fn, 'w')
d = f.create_group('DASC')
d.attrs[u'converted'] = datetime.now().strftime('%Y-%m-%d')
d.attrs[u'wavelength'] = '{}'.format(wl)
d.attrs[u'image resolution'] = '{}'.format(N)
d.attrs[u'PKR camera lon'] = '{}'.format(lon0)
d.attrs[u'PKR camera lat'] = '{}'.format(lat0)
d.attrs[u'PKR camera alt'] = '{}'.format(alt0)
h5time = d.create_dataset('time', data=ts)
h5time.attrs[u'time format'] = 'time format in POSIX time'
d.create_dataset('az', data=az)
d.create_dataset('el', data=el)
h5img = d.create_dataset('img', data=images, compression=9)
h5img.chunks
h5img.attrs[u'Coordinates'] = 'Ntimes x Naz x Nel'
# close file
f.close()
except Exception as e:
raise (e)
def correctSampling(t,y,Ts=1):
if isinstance(t[0], datetime.datetime):
ts = gnssUtils.datetime2posix(t)
else:
ts = t
time_series = np.arange(int(ts[0]),int(ts[-1])+1,Ts)
y_out = np.nan*np.ones((time_series.shape[0]))
idt = np.where(np.isin(time_series,ts))[0]
y_out[idt] = y
return time_series, y_out
def _alignTimes(tlist, teclist, polylist, residuallist, fs):
tmin = []
tmax = []
for i in range(len(tlist)):
tmin.append(tlist[i].min())
tmax.append(tlist[i].max())
tstart = max(gnssUtils.datetime2posix(tmin))
tend = min(gnssUtils.datetime2posix(tmax))
t = []
tec2 = []
poly2 = []
res2 = []
for i in range(len(teclist)):
tt, tec1 = correctSampling(tlist[i], teclist[i], fs=fs)
tt, poly1 = correctSampling(tlist[i], polylist[i], fs=fs)
tt, res1 = correctSampling(tlist[i], residuallist[i], fs=fs)
tt = np.array(tt)
idt = np.where((tt>=tstart) & (tt<=tend))[0]
t.append(tt[idt])
tec2.append(tec1[idt])
poly2.append(poly1[idt])
res2.append(res1[idt])
return t, tec2, poly2, res2
def feed2hdf(t,
tec,
lat=[],
lon=[],
fn='/home/smrak/Documents/eclipse/surav/233.h5'):
if isinstance(t[0], datetime):
t = gnssUtils.datetime2posix(t)
f = h5py.File(fn, 'w')
gr = f.create_group('data')
gr.create_dataset('times', data=t)
gr.create_dataset('dtec', data=tec)
gr.attrs['lon'] = lon
gr.attrs['lat'] = lat
f.close()
return
def writeInterpolated2HDF(t,
lon,
lat,
h,
images,
h5fn,
lon0=0,
lat0=0,
alt0=0,
N=None,
wl=0):
if isinstance(t[0], datetime):
t = gu.datetime2posix(t)
if N == 0 or N is None:
N = lon.shape[0]
try:
f = h5py.File(h5fn, 'w')
d = f.create_group('DASC')
d.attrs[u'converted'] = datetime.now().strftime('%Y-%m-%d')
d.attrs[u'wavelength'] = '{}'.format(wl)
d.attrs[u'image resolution'] = '{}'.format(N)
d.attrs[u'PKR camera lon'] = '{}'.format(lon0)
d.attrs[u'PKR camera lat'] = '{}'.format(lat0)
d.attrs[u'PKR camera alt'] = '{}'.format(alt0)
h5time = d.create_dataset('time', data=t)
h5time.attrs[u'time format'] = 'time format in POSIX time'
d.create_dataset('lon', data=lon)
d.create_dataset('lat', data=lat)
H = d.create_dataset('alt', data=h)
H.attrs[u'Mapping height'] = '{}'.format(h)
h5img = d.create_dataset('img', data=images, compression=9)
h5img.chunks
h5img.attrs[u'Coordinates'] = 'Ntimes x Nlon x Nlat'
# Close file
f.close()
except Exception as e:
raise (e)
def save2HDF(t, lon, lat, images, h5fn):
if isinstance(t[0], datetime):
t = gu.datetime2posix(t)
try:
f = h5py.File(h5fn, 'w')
d = f.create_group('GPSTEC')
d.attrs[u'converted'] = datetime.now().strftime('%Y-%m-%d %H:%M')
h5time = d.create_dataset('time', data=t)
h5time.attrs[u'time format'] = 'time format in POSIX time'
d.create_dataset('lon', data=lon)
d.create_dataset('lat', data=lat)
h5img = d.create_dataset('im',
data=images,
compression='gzip',
compression_opts=9)
h5img.chunks
# Close file
f.close()
except Exception as e:
if 'f' in locals():
f.close()
raise (e)
tmp = np.rot90(im[i], rot)
title = 'DASC: {} UT'.format(t[i])
imgname = datetime.strftime(t[i], '%H%M%S') + '.png'
tmp[tmp <= 200] = np.nan
fig = asiplot.plotIMpolar(xgrid,
ygrid,
tmp,
title=title,
figure=True,
clim=[300, 600],
cmap='Greys_r',
norm_gamma=0.5,
savefn=savepolar + imgname)
if w2f:
ts = gu.datetime2posix(t)
try:
f = h5py.File(h5fn, 'w')
d = f.create_group('DASC')
d.attrs[u'converted'] = datetime.now().strftime('%Y-%m-%d')
d.attrs[u'wavelength'] = '{}'.format(wl)
d.attrs[u'image resolution'] = '{}'.format(N)
d.attrs[u'PKR camera lon'] = '{}'.format(lon)
d.attrs[u'PKR camera lat'] = '{}'.format(lat)
d.attrs[u'PKR camera alt'] = '{}'.format(alt)
h5time = d.create_dataset('time', data=ts)
h5time.attrs[u'time format'] = 'time format in POSIX time'
d.create_dataset('xgrid', data=xgrid)
d.create_dataset('ygrid', data=ygrid)
h5img = d.create_dataset('img', data=im, compression=9)
h5img.chunks
print(e)
# if P.log:
# LOG.write(str(e) + '\n')
# pass
# else:
# print (e)
except Exception as e:
print(e)
# if P.log:
# with open(logfn, 'a') as LOG:
# LOG.write(str(e) + '\n')
# LOG.close()
# else:
# print (e)
th5 = gu.datetime2posix(t.astype(datetime))
# Dealing with duplicate file names
if os.path.exists(savefn):
head = os.path.splitext(savefn)[0]
c = 0
while os.path.exists(savefn):
try:
c = int(os.path.splitext(savefn)[0].split('_')[-1])
c += 1
except:
c += 1
savefn = head + '_' + str(c) + '.h5'
# putting the output file togather
if P.log:
def getKeogram(filename,
skip=1,
X=40,
lim=[-110, -70],
direction='lat',
timelim=[],
im_filter=1,
fillPixel_iter=0,
integrate=2,
spectogram=0,
totality=0):
"""
Direction lat: Fixed LAT, look along lon
"""
data = h5py.File(filename, 'r')
time = data['data/time'][::skip]
xgrid = data['data/xgrid'].value
ygrid = data['data/ygrid'].value
im = data['data/im'][::skip][:][:]
#--------------------------------------------------------------------------#
if len(timelim) > 0:
tl_posix = gu.datetime2posix(timelim)
idt = np.where((time >= tl_posix[0]) & (time <= tl_posix[1]))[0]
im = im[idt, :, :]
time = time[idt]
#--------------------------------------------------------------------------#
if direction == 'lon':
idy = np.where((ygrid >= lim[0]) & (ygrid <= lim[1]))[0]
if integrate <= 1:
idx = abs(xgrid - X).argmin()
keogram = im[:, idx, idy]
elif integrate > 1:
idx = abs(xgrid - X).argmin()
idx = np.array(
[idx - int(integrate / 2), idx, idx + int(integrate / 2)])
imstack = im[:, idx, idy[0]:idy[-1]]
keogram = np.nan * np.zeros((imstack.shape[0], imstack.shape[2]))
for i in range(imstack.shape[0]):
for j in range(imstack.shape[2]):
N = sum(np.isfinite(imstack[i, :, j]))
if N > 0:
keogram[i,
j] = sum(np.nan_to_num(imstack[i, :, j])) / N
Y = ygrid[idy]
elif direction == 'lat':
idx = np.where((xgrid >= lim[0]) & (xgrid <= lim[1]))[0]
if integrate <= 1:
idy = abs(ygrid - X).argmin()
keogram = im[:, idx, idy]
elif integrate > 1:
idy = abs(ygrid - X).argmin()
idy = np.array(
[idy - int(integrate / 2), idy, idy + int(integrate / 2)])
imstack = im[:, idx[0]:idx[-1], idy]
keogram = np.nan * np.zeros((imstack.shape[0], imstack.shape[1]))
for i in range(imstack.shape[0]):
for j in range(imstack.shape[1]):
N = sum(np.isfinite(imstack[i, j, :]))
if N > 0:
keogram[i,
j] = sum(np.nan_to_num(imstack[i, j, :])) / N
Y = xgrid[idx]
elif direction == 'custom':
if totality:
totality_path = h5py.File(
'/home/smrak/Documents/eclipse/totality.h5', 'r')
Xt = totality_path['path/center_lon'].value
Yt = totality_path['path/center_lat'].value - 1
Xt, Yt = interpolateTotality(Xt,
Yt,
lon0=-150,
lon1=-50,
order=5,
resolution=0.3)
else:
Xt = np.array([-100, -93.75, -87.5, -81.2])
Yt = np.array([44, 39.5, 35, 30.5])
Xt = np.array([-95, -90])
Yt = np.array([44, 35])
Xt, Yt = interpolateTotality(Xt,
Yt,
lon0=Xt[0],
lon1=Xt[-1],
order=1,
resolution=0.02)
# plt.plot(Xt,Yt)
idx = np.where((xgrid >= lim[0]) & (xgrid <= lim[1]))[0]
idy = []
keogram = np.nan * np.ones((time.shape[0], xgrid[idx].shape[0]))
for x in xgrid[idx]:
idX = abs(x - Xt).argmin()
Yt_approx = Yt[idX]
tmp = abs(ygrid - Yt_approx).argmin()
idy.append(tmp)
idy = np.array(idy)
if integrate <= 1:
keogram = im[:, idx, idy]
else:
imkeogram = np.nan * np.ones(
(time.shape[0], xgrid[idx].shape[0], integrate + 1))
intrange = np.arange(-int(integrate / 2), int(integrate / 2) + 1)
for i in range(intrange.shape[0]):
imkeogram[:, :, i] = im[:, idx, idy + intrange[i]]
for i in range(imkeogram.shape[0]):
for j in range(imkeogram.shape[1]):
N = sum(np.isfinite(imkeogram[i, j, :]))
if N > 0:
keogram[i,
j] = sum(np.nan_to_num(imkeogram[i, j, :])) / N
Y = xgrid[idx]
dt = [datetime.datetime.utcfromtimestamp(t) for t in time]
if fillPixel_iter > 0:
keogram = fillPixels(keogram, N=fillPixel_iter)
if im_filter:
keogram = ndimage.median_filter(keogram, 3)
if spectogram:
if direction == 'lat':
n = Y.shape[0]
d = round(ygrid[1] - ygrid[0], 1) * 111 * np.cos(np.deg2rad(X))
else:
n = Y.shape[0]
d = round(ygrid[1] - ygrid[0], 1) * 111
k = np.fft.fftfreq(n, d=d)
k = 2 * np.pi * k[1:int((n - 1) / 2)]
specto = np.nan * np.zeros((keogram.shape[0], k.shape[0]))
# print (keogram.shape, Y.shape, specto.shape, n, k.shape)
for j in range(keogram.shape[0]):
x = np.nan_to_num(keogram[j])
Sx = np.abs(np.fft.fft(x))
Sx = Sx[1:int((n - 1) / 2)]
specto[j, :] = Sx
return [dt, keogram, Y], [k, specto]
else:
return [dt, keogram, Y]
tidim = plt.scatter(X[0], X[1], c=tec.T,
s=8, cmap=cmap,
transform=ccrs.PlateCarree())
else:
tidim = plt.pcolormesh(xgrid,ygrid,tec.T,cmap=cmap,transform=ccrs.PlateCarree())
plt.clim(clim)
# Fig utils
cbar = plt.colorbar(mappable=tidim, #cax=cax,
ticks=[clim[0], clim[0]/2, 0, clim[1]/2, clim[1]])
cbar.set_label('$\Delta$TEC [TECu]')
if MASK:
from dateutil import parser
from pyGnss import gnssUtils
dt = parser.parse(T)
tposix = gnssUtils.datetime2posix([dt])
mask_x, mask_y, mask = gps2d.getEUVMask(tposix[0],
EUVDIR='C:\\Users\\smrak\\Google Drive\BU\\Projects\\Eclipse2017\\data\\Drob\\HiResFull300\\')
penumbra_levels = [0.2,1,40]
levels = linspace(penumbra_levels[0],penumbra_levels[1],penumbra_levels[2])
lw = 1
plt.contour(mask_x, mask_y, mask.T, levels, colors='w', #cmap='Greys_r',#colors='w',
linewidths=lw, transform=ccrs.PlateCarree())
if NEXRAD:
if 'title' in vars():
title += '\n NEXRAD: ' + nqimage[7:-4]
else:
title = 'NEXRAD: ' + nqimage[7:-4]
X, Y, Z = gps2d.returnNEXRAD(nexradfolder, downsample=16, darg=nqimage, RGB=RGB)
if not RGB:
def main(F, el_mask = None, odir = None):
global tsps
D = h5py.File(F, 'r')
el_mask = 30
maxjump = 1.6 + (np.sqrt(tsps) - 1)
eps = 1 * np.sqrt(30/tsps)
polynom_list = np.arange(0,20)
el_mask_in = (el_mask - 10) if (el_mask - 10) >= 8 else 8
print ('Reading in receiver names')
t0 = datetime.now()
rxn_all = np.asanyarray([row[12].decode() for row in D['Data/Table Layout'][()]])
rxn = np.unique(rxn_all)
print ('Read in {}.\nReading in satellite number'.format(datetime.now()-t0))
t0 = datetime.now()
sv_unique = np.unique(np.asanyarray([row[13] for row in D['Data/Table Layout'][()]]))
sv_index = np.arange(sv_unique.size)
sv_list = {}
for i, s in enumerate(sv_unique):
sv_list[str(s)] = sv_index[i]
print ('Read in {}.\nReading in observations times'.format(datetime.now()-t0))
obstimes = np.unique(np.asanyarray([datetime.utcfromtimestamp(row[9]) for row in D['Data/Table Layout'][()]]))
obstimes_unix = gu.datetime2posix(obstimes)
print ('Read in {}.\n'.format(datetime.now()-t0))
D.close()
# Out-filename
if odir is None:
odir = os.path.split(F)[0]
sfn = str(obstimes[0].year) + '_' + obstimes[0].strftime('%m%dT%H%M') + '-' + obstimes[-1].strftime('%m%dT%H%M') + '_' + 'madrigallos' + '_' + str(el_mask) +'el_' + str(tsps) + 's' + '_roti'
savefn = os.path.join(odir, sfn + '.h5')
# Duplicate file names
if os.path.exists(savefn):
head = os.path.splitext(savefn)[0]
c = 0
while os.path.exists(savefn):
try:
c = int(os.path.splitext(savefn)[0].split('_')[-1])
c += 1
except:
c += 1
savefn = head + '_' + str(c) + '.h5'
logfn = os.path.splitext(savefn)[0] + '.log'
LOG = open(logfn, 'w')
LOG.close()
print ('Init arrays')
TEC = np.nan * np.zeros((obstimes.size, sv_unique.size, rxn.size), dtype=np.float16)
DTEC = np.nan * np.zeros((obstimes.size, sv_unique.size, rxn.size), dtype=np.float16)
ROTI = np.nan * np.zeros((obstimes.size, sv_unique.size, rxn.size), dtype=np.float16)
AZ = np.nan * np.zeros((obstimes.size, sv_unique.size, rxn.size), dtype=np.float16)
EL = np.nan * np.zeros((obstimes.size, sv_unique.size, rxn.size), dtype=np.float16)
RXP = np.nan * np.zeros((rxn.size, 3), dtype=np.float16)
print ('Saving to: {}'.format(savefn))
h5file = h5py.File(savefn, 'w')
h5file.create_dataset('obstimes', data=obstimes_unix)
h5file.create_dataset('stec', data=TEC, compression='gzip', compression_opts=9)
h5file.create_dataset('res', data=DTEC, compression='gzip', compression_opts=9)
h5file.create_dataset('roti', data=ROTI, compression='gzip', compression_opts=9)
h5file.create_dataset('az', data=AZ, compression='gzip', compression_opts=9)
h5file.create_dataset('el', data=EL, compression='gzip', compression_opts=9)
h5file.create_dataset('rx_positions', data=RXP, compression='gzip', compression_opts=9)
asciiListN = [n.encode("ascii", "ignore") for n in rxn]
h5file.create_dataset('rx_name', (len(asciiListN),1),'S4', asciiListN)
h5file.close()
del TEC, DTEC, ROTI, AZ, EL, RXP
print ('Arrays erased')
for irx, rx in enumerate(rxn):
if irx == 0:
with open(logfn, 'a') as LOG:
LOG.write('Processing {}/{}.\n'.format(irx+1, rxn.size))
LOG.close()
else:
with open(logfn, 'a') as LOG:
LOG.write('Processing {}/{}. It took {} to process last RX data. \n'.format(irx+1, rxn.size, datetime.now()-t0))
LOG.close()
t0 = datetime.now()
try:
D = h5py.File(F, 'r')
idrx = np.isin(rxn_all, rx)
sv_all = np.asanyarray([row[13] for row in D['Data/Table Layout'][idrx]])
svn = np.unique(sv_all)
rx_lat = D['Data/Table Layout'][idrx][0][-4]
rx_lon = D['Data/Table Layout'][idrx][0][-3]
D.close()
h5file = h5py.File(savefn, 'a')
h5file['rx_positions'][irx, 0] = rx_lat
h5file['rx_positions'][irx, 1] = rx_lon
h5file['rx_positions'][irx, 2] = 0
h5file.close()
del rx_lat, rx_lon
for isv, sv in enumerate(svn):
vtec = np.nan * np.ones(obstimes.size, dtype=np.float16)
elv = np.nan * np.ones(obstimes.size, dtype=np.float16)
azm = np.nan * np.ones(obstimes.size, dtype=np.float16)
idsv = np.isin(sv_all, sv)
ids = sv_list[str(sv)]
D = h5py.File(F, 'r')
t = np.asanyarray([datetime.utcfromtimestamp(row[9]) for row in D['Data/Table Layout'][idrx][idsv] ])
idt = np.isin(obstimes, t)
vtec[idt] = np.asanyarray([row[18] for row in D['Data/Table Layout'][idrx][idsv] ])
elv[idt] = np.asanyarray([row[-5] for row in D['Data/Table Layout'][idrx][idsv] ])
azm[idt] = np.asanyarray([row[-6] for row in D['Data/Table Layout'][idrx][idsv] ])
D.close()
idel0 = np.nan_to_num(elv) < el_mask_in
idel = np.nan_to_num(elv) < el_mask
vtec[idel0] = np.nan
try:
idx, intervals = getIntervals(vtec, maxgap=5, maxjump=maxjump)
tecd, err_list = tecdPerLOS(vtec, intervals, polynom_list=polynom_list, eps=eps)
tecd[idel] = np.nan
rot = np.hstack((np.nan, (np.diff(vtec) / tsps)))
roti = scintillation.sigmaTEC(rot, 10) # 5 min
roti[idel] = np.nan
vtec[idel] = np.nan
h5file = h5py.File(savefn, 'a')
h5file['stec'][:, isv, irx] = vtec
h5file['roti'][:, isv, irx] = roti
h5file['res'][:, isv, irx] = tecd
h5file['el'][:, isv, irx] = elv
h5file['az'][:, isv, irx] = azm
h5file.close()
del vtec, tecd, elv, azm, roti, rot, idx, intervals, idel0, idel
except:
del vtec, elv, azm
del idrx, idsv, ids
except:
pass
with open(logfn, 'a') as LOG:
LOG.write('Processing Done')
LOG.close()
return 0
def returnGlobalTEC(date='', datafolder='', timelim=[]):
if isinstance(date, str) and date != '':
try:
yy = date[2:4]
mm = date[5:7]
dd = date[-2:]
except:
raise ('Date has to be given in a format YYYY-MM-DD')
if datafolder == '' or datafolder is None:
datafolder = 'C:\\Users\\smrak\\Google Drive\\BU\\Projects\\steve\\data\\gps\\'
# Open the data
try:
if os.path.isdir(datafolder):
fnstruct = 'gps' + yy + mm + dd + 'g.002.hdf5'
fn = datafolder + fnstruct
elif os.path.isfile(datafolder):
fn = datafolder
else:
raise ('Something went wrong. datafolder format is not recognized')
f = h5py.File(fn, 'r')
obstimes = f['Data/Table Layout']['ut2_unix']
xgrid = arange(-180, 180)
ygrid = arange(-90, 90)
except Exception as e:
raise (e)
# Time resolution
if timelim is None or len(timelim) == 0:
iterate = obstimes
elif len(timelim) > 0 and isinstance(timelim[0], datetime):
tlim = gu.datetime2posix(timelim)
IDT = (obstimes >= tlim[0]) & (obstimes <= tlim[1])
iterate = unique(obstimes[IDT])
else:
raise ('timelim argument has to be a dateime.datetime object, with \
with a length 2 (start,stop)')
# Make an empty array to read in the data
imstack = nan * ones((iterate.shape[0], xgrid.shape[0], ygrid.shape[0]))
for i, t in enumerate(iterate):
print('Reading in image {}/{}'.format(i + 1, iterate.shape[0]))
im = nan * ones((xgrid.shape[0], ygrid.shape[0]))
data_t = f['Data/Table Layout']['ut2_unix']
idt = abs(data_t - t).argmin()
idT = isin(data_t, data_t[idt])
data_lon = f['Data/Table Layout']['glon'][idT]
data_lat = f['Data/Table Layout']['gdlat'][idT]
data_tec = f['Data/Table Layout']['tec'][idT]
for k in range(data_tec.shape[0]):
idx = where(xgrid == data_lon[k])
idy = where(ygrid == data_lat[k])
im[idx, idy] = data_tec[k]
imstack[i, :, :] = im
dt = array([datetime.utcfromtimestamp(t) for t in iterate])
out = {'time': dt, 'xgrid': xgrid, 'ygrid': ygrid, 'tecim': imstack}
return out
tidim = plt.pcolormesh(xgrid,
ygrid,
IM.T,
cmap=cmap,
transform=ccrs.PlateCarree())
plt.clim(clim)
# Fig utils
cbar = plt.colorbar(
mappable=tidim, #cax=cax,
ticks=[clim[0], clim[0] / 2, 0, clim[1] / 2, clim[1]])
cbar.set_label('$\Delta$TEC [TECu]')
if MASK:
from pyGnss import gnssUtils
# dt = parser.parse(t[i])
tposix = gnssUtils.datetime2posix([t[i]])
mask_x, mask_y, mask = gps2d.getEUVMask(
tposix[0],
EUVDIR=
'C:\\Users\\smrak\\Google Drive\BU\\Projects\\Eclipse2017\\data\\Drob\\HiResFull300\\'
)
if isinstance(mask, ndarray):
penumbra_levels = [0.2, 1, 50]
levels1 = linspace(penumbra_levels[0], penumbra_levels[1],
penumbra_levels[2])
lw = 1
plt.contour(
mask_x,
mask_y,
mask.T,
levels1,
def createTimeArray(timelim,Ts=1):
ts = gnssUtils.datetime2posix(timelim)
t = range(int(ts[0]), int(ts[1])+1)
t = np.arange(int(ts[0]), int(ts[1])+1, Ts)
return t
rxlistfn = stream.get('rxlist')
savefn = stream.get('savefn')
DATADIR = stream.get('datadir') + year + '/' + day + '/'
NAVDIR = stream.get('navdir')
if (savefn[-3:] != '.h5') or (savefn[-5:] != '.hdf5'):
savefn += '.h5'
rxlist, rxpos = ec.getRxListCoordinates(filename=rxlistfn)
rxlist, rxpos = ec.rxFilter(rxlist, rxpos, latlim=latlim, lonlim=lonlim)
print ("Number of receivers in the list: ", len(rxlist))
sv = np.arange(1,33)
tlim = [datetime.datetime.strptime('{} {} 0 0 0'.format(year, day),'%Y %j %H %M %S'),
datetime.datetime.strptime('{} {} 0 0 0'.format(year, str(int(day)+1)),'%Y %j %H %M %S')]
obstimes_ts = gnssUtils.datetime2posix(tlim)
time_save = np.arange(obstimes_ts[0],obstimes_ts[1],Ts)
residuals = np.nan*np.zeros((time_save.shape[0], sv.shape[0], len(rxlist)))
latitudes = np.nan*np.zeros((time_save.shape[0], sv.shape[0], len(rxlist)))
longitudes = np.nan*np.zeros((time_save.shape[0], sv.shape[0], len(rxlist)))
for j in range(len(rxlist)):
print ('Processing station: '+str(j+1)+'/'+str(len(rxlist)))
try:
rx = rxlist[j]
yamlfile = DATADIR+'/'+ rx + '.yaml'
navfile = NAVDIR + '/brdc' + day + '0.'+year[-2:]+'n'
hdffile = DATADIR + rx + '.h5'
data = read_hdf(hdffile)
