def gnssir_guts(station, year, doy, snr_type, extension, lsp):
"""
my attempt to separate the inputs to the code and the guts of the code
inputs are station name, year, day of year (integers)
snr_type is an integer (99, 66, etc). lsp is a json
"""
# make sure environment variables exist. set to current directory if not
g.check_environ_variables()
e1 = lsp['e1']
e2 = lsp['e2']
minH = lsp['minH']
maxH = lsp['maxH']
ediff = lsp['ediff']
NReg = lsp['NReg']
PkNoise = lsp['PkNoise']
azval = lsp['azval']
naz = int(len(azval) / 2)
freqs = lsp['freqs']
reqAmp = lsp['reqAmp']
plot_screen = lsp['plt_screen']
onesat = lsp['onesat']
screenstats = lsp['screenstats']
azval = lsp['azval']
d = g.doy2ymd(year, doy)
month = d.month
day = d.day
dmjd, fracS = g.mjd(year, month, day, 0, 0, 0)
xdir = os.environ['REFL_CODE']
ann = g.make_nav_dirs(year) # make sure directories are there for orbits
g.result_directories(station, year,
extension) # make directories for the LSP results
# this defines the minimum number of points in an arc. This depends entirely on the sampling
# rate for the receiver, so you should not assume this value is relevant to your case.
minNumPts = 20
p, T, irefr = set_refraction_params(station, dmjd, lsp)
# only doing one day at a time for now - but have started defining the needed inputs for using it
twoDays = False
obsfile2 = '' # dummy value for name of file for the day before, when we get to that
fname, resultExist = g.LSPresult_name(station, year, doy, extension)
if (resultExist):
print('Results already exist on disk')
if (lsp['overwriteResults'] == False) & (resultExist == True):
allGood = 0
print(
'>>>>> The result file exists for this day and you have selected the do not overwrite option'
)
sys.exit()
print('go ahead and access SNR data - first define SNR filename')
obsfile, obsfileCmp, snre = g.define_and_xz_snr(station, year, doy,
snr_type)
print(obsfile, 'snrexistence', snre, ' and ', snr_type)
if (not snre) and (not lsp['seekRinex']):
print(
'SNR file does not exist and you have set the seekRinex variable to False'
)
print('Use rinex2snr.py to make SNR files')
sys.exit()
if (not snre) and lsp['seekRinex']:
print('SNR file does not exist. I will try to make a GPS only file.')
rate = 'low'
dec_rate = 0
orbtype = 'nav'
g.quick_rinex_snrC(year, doy, station, snr_type, orbtype, rate,
dec_rate)
allGood, sat, ele, azi, t, edot, s1, s2, s5, s6, s7, s8, snrE = snr.read_snr_multiday(
obsfile, obsfile2, twoDays)
snr.compress_snr_files(lsp['wantCompression'], obsfile, obsfile2, twoDays)
# SNR exists - go ahead
if (allGood == 1):
ele = apply_refraction_corr(lsp, ele, p, T)
fout, frej = g.open_outputfile(station, year, doy, extension)
# main loop a given list of frequencies
total_arcs = 0
ct = 0
for f in freqs:
if plot_screen: fig, (ax1, ax2) = plt.subplots(2, 1)
rj = 0
gj = 0
print('**** looking at frequency ', f, ' ReqAmp', reqAmp[ct],
' doy ', doy, 'YYYY/MM/DD', year, month, day)
# get the list of satellites for this frequency
if onesat == None:
satlist = g.find_satlist(f, snrE)
else:
satlist = onesat
if (int(satlist[0]) < 100) and (f > 100):
print('wrong satellite name for this frequency')
for satNu in satlist:
#if screenstats: print('Satellite', satNu)
for a in range(naz):
az1 = azval[(a * 2)]
az2 = azval[(a * 2 + 1)]
x, y, Nv, cf, UTCtime, avgAzim, avgEdot, Edot2, delT = g.window_data(
s1, s2, s5, s6, s7, s8, sat, ele, azi, t, edot, f, az1,
az2, e1, e2, satNu, lsp['polyV'], lsp['pele'],
screenstats)
MJD = g.getMJD(year, month, day, UTCtime)
if Nv > minNumPts:
maxF, maxAmp, eminObs, emaxObs, riseSet, px, pz = g.strip_compute(
x, y, cf, maxH, lsp['desiredP'], lsp['polyV'],
minH)
nij = pz[(px > NReg[0]) & (px < NReg[1])]
Noise = 0
if (len(nij) > 0):
Noise = np.mean(nij)
iAzim = int(avgAzim)
okPk = True
if abs(maxF -
minH) < 0.10: # peak too close to min value
okPk = False
print(
'found a peak too close to the edge of the restricted RH region'
)
if okPk & (delT < lsp['delTmax']) & (
eminObs <
(e1 + ediff)) & (emaxObs > (e2 - ediff)) & (
maxAmp > reqAmp[ct]) & (maxAmp / Noise >
PkNoise):
fout.write(
" {0:4.0f} {1:3.0f} {2:6.3f} {3:3.0f} {4:6.3f} {5:6.2f} {6:6.2f} {7:6.2f} {8:6.2f} {9:4.0f} {10:3.0f} {11:2.0f} {12:8.5f} {13:6.2f} {14:7.2f} {15:12.6f} {16:1.0f} \n"
.format(year, doy, maxF, satNu, UTCtime,
avgAzim, maxAmp, eminObs, emaxObs, Nv,
f, riseSet, Edot2, maxAmp / Noise,
delT, MJD, irefr))
gj += 1
if screenstats:
T = g.nicerTime(UTCtime)
print(
'SUCCESS Azimuth {0:3.0f} Sat {1:3.0f} RH {2:7.3f} m PkNoise {3:4.1f} Amp {4:4.1f} Fr{5:3.0f} UTC {6:5s} DT {7:3.0f} '
.format(iAzim, satNu, maxF, maxAmp / Noise,
maxAmp, f, T, round(delT)))
if plot_screen:
local_update_plot(x, y, px, pz, ax1, ax2)
else:
rj += 1
if screenstats:
print(
'FAILED QC for Azimuth {0:.1f} Satellite {1:2.0f} UTC {2:5.2f}'
.format(iAzim, satNu, UTCtime))
g.write_QC_fails(delT, lsp['delTmax'], eminObs,
emaxObs, e1, e2, ediff,
maxAmp, Noise, PkNoise,
reqAmp[ct])
print(
'================================================================================='
)
print(' Frequency ', f, ' good arcs:', gj, ' rejected arcs:',
rj)
print(
'================================================================================='
)
total_arcs = gj + total_arcs
# close the output files
ct += 1
#'Yes' if fruit == 'Apple' else 'No'
if plot_screen: plot2screen(station, f, ax1, ax2, lsp['pltname'])
fout.close()
def main():
# make surer environment variables are set
g.check_environ_variables()
xdir = os.environ['REFL_CODE']
# must input start and end year
parser = argparse.ArgumentParser()
parser.add_argument("station", help="station name", type=str)
# optional inputs: filename to output daily RH results
parser.add_argument("-year", default='None', type=str, help="restrict to years beginning with")
parser.add_argument("-txtfile", default='None', type=str, help="output (plain text)")
parser.add_argument("-csvfile", default='None', type=str, help="output (csv)")
parser.add_argument("-jsonfile", default='None', type=str, help="output (json)")
parser.add_argument("-plt", default='None', type=str, help="set to False to suppress plots")
args = parser.parse_args()
# these are required
station = args.station
# these are optional
txtfile = args.txtfile
csvfile = args.csvfile
jsonfile = args.jsonfile
writetxt = True
if txtfile == 'None':
writetxt = False
writecsv = True
if csvfile == 'None':
writecsv = False
writejson = True
if jsonfile == 'None':
writejson = False
if args.year == 'None':
year = 2020
else:
year=int(args.year)
if args.plt == 'False':
plt= False
else:
plt = True
# where the summary files will be written to
txtdir = xdir + '/Files'
if not os.path.exists(txtdir):
os.makedirs(txtdir)
direc = xdir + '/' + str(year) + '/results/' + station + '/'
tv = np.empty(shape=[0, 17])
if os.path.isdir(direc):
all_files = os.listdir(direc)
#print('Number of files in ', year1, len(all_files))
for f in all_files:
fname = direc + f
a = np.loadtxt(fname,comments='%')
tv = np.append(tv, a,axis=0)
#print(tv.shape)
t=tv[:,0] + (tv[:,1] + tv[:,4]/24)/365.25
rh = tv[:,2]
# sort the data
ii = np.argsort(t)
t = t[ii] ; rh = rh[ii]
# store it all in a new variable
ntv = tv[ii,:]
#
Plt.figure()
Plt.plot(t, rh,'.')
Plt.ylabel('Reflector Height (m)')
Plt.title('GNSS station: ' + station)
Plt.gca().invert_yaxis()
Plt.grid()
# default is to show the plot
#if plt:
#Plt.show()
# always make a png file
plotname = txtdir + '/' + station + '_subdaily_RH.png'
Plt.savefig(plotname)
print('png file saved as: ', plotname)
splines_for_dummies(t,rh,plt)
# apply time tags to a new variable
N,M = np.shape(ntv)
if writejson:
outfile = txtdir + '/' + jsonfile
if writecsv:
outfile = txtdir + '/' + csvfile
if writetxt:
outfile = txtdir + '/' + txtfile
if (writecsv) and (writetxt) :
print('You cannot simultaneously write out a csvfile and a txtfile')
print('Default to writing only a txtfile')
writecsv = False
if (writejson):
print('you picked the json output')
o = {}
N= len(ntv)
column_names = ['timestamp','rh','sat','freq','ampl','azim','edotf','mjd']
# this worked - but didn't have names, so not useful
#o['station'] = station
#o['data'] = ntv[:,[0,1,2,4,15,3]].tolist()
# give my numpy variables names
# to make a string
# x=datetime.datetime(2018,9,15)
# print(x.strftime("%b %d %Y %H:%M:%S"))
year = ntv[:,0].tolist()
year =[str(int(year[i])) for i in range(N)];
doy = ntv[:,1].tolist()
doy=[str(int(doy[i])) for i in range(N)];
UTChour = ntv[:,4].tolist()
UTChour = [str(UTChour[i]) for i in range(N)];
timestamp = [quickTr(ntv[i,0], ntv[i,1], ntv[i,4]) for i in range(N)]
rh = ntv[:,2].tolist()
rh=[str(rh[i]) for i in range(N)];
sat = ntv[:,3].tolist()
sat =[int(sat[i]) for i in range(N)];
freq = ntv[:,10].tolist()
freq =[int(freq[i]) for i in range(N)];
ampl = ntv[:,6].tolist()
ampl =[str(ampl[i]) for i in range(N)];
azim = ntv[:,5].tolist()
azim =[str(azim[i]) for i in range(N)];
edotf = ntv[:,12].tolist()
edotf =[str(edotf[i]) for i in range(N)];
mjd = ntv[:,15].tolist()
mjd=[str(mjd[i]) for i in range(N)];
# now attempt to zip them
l = zip(timestamp,rh,sat,freq,ampl,azim,edotf,mjd)
dzip = [dict(zip(column_names, next(l))) for i in range(N)]
# make a dictionary with metadata and data
o={}
lat = "0"; lon = "0";
firstline = {'name': station, 'latitude': lat, 'longitude': lon}
o['metadata'] = firstline
o['data'] = dzip
outf = outfile
print(outfile)
with open(outf,'w+') as outf:
json.dump(o,outf,indent=4)
#close(outf)
if (writecsv) or (writetxt):
print('Results are being written to : ', outfile)
fout = open(outfile, 'w+')
write_out_header(fout,station)
for i in np.arange(0,N,1):
year = int(ntv[i,0]); doy = int(ntv[i,1])
year, month, day, cyyyy,cdoy, YMD = g.ydoy2useful(year,doy)
rh = ntv[i,2]; UTCtime = ntv[i,4]; mjd = ntv[i,15]
ctime = g.nicerTime(UTCtime); ctime2 = ctime[0:2] + ' ' + ctime[3:5]
if writecsv:
fout.write(" {0:4.0f},{1:3.0f},{2:7.3f},{3:3.0f},{4:7.3f},{5:8.2f},{6:7.2f},{7:5.2f}, {8:3.0f},{9:8.5f}, {10:2.0f}, {11:2.0f},{12:2s},{13:2s},{14:15.6f} \n".format(year, doy, rh,ntv[i,3],UTCtime,ntv[i,5],ntv[i,6],ntv[i,13],ntv[i,10],ntv[i,12],month,day,ctime[0:2],ctime[3:5] ,mjd ))
else:
fout.write(" {0:4.0f} {1:3.0f} {2:7.3f} {3:3.0f} {4:7.3f} {5:8.2f} {6:7.2f} {7:5.2f} {8:3.0f} {9:8.5f} {10:2.0f} {11:2.0f} {12:5s} {13:15.6f} \n".format(year, doy, rh,ntv[i,3],UTCtime,ntv[i,5],ntv[i,6],ntv[i,13],ntv[i,10],ntv[i,12],month,day,ctime2,mjd ))
fout.close()
def quickLook_function(station, year, doy, snr_type,f,e1,e2,minH,maxH,reqAmp,pele,satsel,PkNoise,fortran):
"""
inputs:
station name (4 char), year, day of year
snr_type is the file extension (i.e. 99, 66 etc)
f is frequency (1, 2, 5), etc
e1 and e2 are the elevation angle limits in degrees for the LSP
minH and maxH are the allowed LSP limits in meters
reqAmp is LSP amplitude significance criterion
pele is the elevation angle limits for the polynomial removal. units: degrees
KL 20may10 pk2noise value is now sent from main function, which can be set online
KL 20aug07 added fortran boolean
"""
# make sure environment variables exist
g.check_environ_variables()
if not os.path.isdir('logs'):
subprocess.call(['mkdir', 'logs'])
webapp = False
# orbit directories
ann = g.make_nav_dirs(year)
# titles in 4 quadrants - for webApp
titles = ['Northwest', 'Southwest','Northeast', 'Southeast']
# define where the axes are located
bx = [0,1,0,1]; by = [0,0,1,1]; bz = [1,3,2,4]
# various defaults - ones the user doesn't change in this quick Look code
delTmax = 70
polyV = 4 # polynomial order for the direct signal
desiredP = 0.01 # 1 cm precision
ediff = 2 # this is a QC value, eliminates small arcs
#four_in_one = True # put the plots together
minNumPts = 20
#noise region for LSP QC. these are meters
NReg = [minH, maxH]
#print('Refl. Ht. Noise Region used: ', NReg)
# for quickLook, we use the four geographic quadrants - these are azimuth angles in degrees
azval = [270, 360, 180, 270, 0, 90, 90, 180]
naz = int(len(azval)/2) # number of azimuth pairs
pltname = 'temp.png' # default plot
requireAmp = reqAmp[0]
screenstats = True
# to avoid having to do all the indenting over again
# this allows snr file to live in main directory
# not sure that that is all that useful as I never let that happen
obsfile = g.define_quick_filename(station,year,doy,snr_type)
if os.path.isfile(obsfile):
print('>>>> The snr file exists ',obsfile)
else:
if True:
#print('looking for the SNR file on disk')
obsfile, obsfileCmp, snre = g.define_and_xz_snr(station,year,doy,snr_type)
if snre:
dkfjaklj = True
#print('file exists on disk')
else:
print('>>>> The SNR the file does not exist ',obsfile)
print('This code used to try and make one for you, but I have removed this option.')
print('Please us rinex2snr and make a SNR file')
sys.exit()
#print('I will try to pick up a RINEX file ')
#print('and translate it for you. This will be GPS only.')
#print('For now I will check all the official archives for you.')
#rate = 'low'; dec_rate = 0; archive = 'all';
#rinex.conv2snr(year, doy, station, int(snr_type), 'nav',rate,dec_rate,archive,fortran)
#if os.path.isfile(obsfile):
# print('the SNR file now exists')
#else:
# print('the RINEX file did not exist, had no SNR data, or failed to convert, so exiting.')
allGood,sat,ele,azi,t,edot,s1,s2,s5,s6,s7,s8,snrE = read_snr_simple(obsfile)
if allGood == 1:
# make output file for the quickLook RRH values, just so you can give them a quick look see
rhout = open('logs/rh.txt','w+')
amax = 0
minEdataset = np.min(ele)
print('minimum elevation angle (degrees) for this dataset: ', minEdataset)
if minEdataset > (e1+0.5):
print('It looks like the receiver had an elevation mask')
e1 = minEdataset
if webapp:
fig = Figure(figsize=(10,6), dpi=120)
axes = fig.subplots(2, 2)
else:
#plt.figure()
# trying to help Kelly
plt.figure(figsize=(10,6))
for a in range(naz):
if not webapp:
plt.subplot(2,2,bz[a])
plt.title(titles[a])
az1 = azval[(a*2)] ; az2 = azval[(a*2 + 1)]
# this means no satellite list was given, so get them all
if satsel == None:
satlist = g.find_satlist(f,snrE)
else:
satlist = [satsel]
for satNu in satlist:
x,y,Nv,cf,UTCtime,avgAzim,avgEdot,Edot2,delT= g.window_data(s1,s2,s5,s6,s7,s8,sat,ele,azi,t,edot,f,az1,az2,e1,e2,satNu,polyV,pele,screenstats)
if Nv > minNumPts:
maxF, maxAmp, eminObs, emaxObs,riseSet,px,pz= g.strip_compute(x,y,cf,maxH,desiredP,polyV,minH)
nij = pz[(px > NReg[0]) & (px < NReg[1])]
Noise = 0
iAzim = int(avgAzim)
if (len(nij) > 0):
Noise = np.mean(nij)
else:
Noise = 1; iAzim = 0 # made up numbers
if (delT < delTmax) & (eminObs < (e1 + ediff)) & (emaxObs > (e2 - ediff)) & (maxAmp > requireAmp) & (maxAmp/Noise > PkNoise):
T = g.nicerTime(UTCtime)
rhout.write('SUCCESS Azimuth {0:3.0f} RH {1:6.3f} m, Sat {2:3.0f} Freq {3:3.0f} Amp {4:4.1f} PkNoise {5:3.1f} UTC {6:5s} \n '.format(
avgAzim,maxF,satNu,f,maxAmp,maxAmp/Noise,T))
if not webapp:
plt.plot(px,pz,linewidth=1.5)
else:
axes[bx[a],by[a]].plot(px,pz,linewidth=2)
axes[bx[a],by[a]].set_title(titles[a])
else:
if not webapp:
plt.plot(px,pz,'gray',linewidth=0.5)
# i do not know how to add a grid using these version of matplotlib
tt = 'GNSS-IR results: ' + station.upper() + ' Freq:' + str(f) + ' ' + str(year) + '/' + str(doy)
aaa, bbb = plt.ylim()
amax = max(amax, bbb) # do not know how to implement this ...
if (a == 3) or (a==1):
plt.xlabel('reflector height (m)')
plt.suptitle(tt, fontsize=12)
rhout.close()
print('Reflector Height results are stored in a file called logs/rh.txt')
if webapp:
fig.savefig('temp.png', format="png")
else:
plt.show()
else:
print('some kind of problem with SNR file, so I am exiting the code politely.')
def main():
# make surer environment variables are set
g.check_environ_variables()
xdir = os.environ['REFL_CODE']
# must input start and end year
parser = argparse.ArgumentParser()
parser.add_argument("station", help="station name", type=str)
# optional inputs: filename to output daily RH results
parser.add_argument("-year",
default='None',
type=str,
help="restrict to years beginning with")
parser.add_argument("-txtfile",
default='None',
type=str,
help="output (plain text)")
parser.add_argument("-csvfile",
default='None',
type=str,
help="output (csv)")
parser.add_argument("-plt",
default='None',
type=str,
help="set to False to suppress plots")
args = parser.parse_args()
# these are required
station = args.station
# these are optional
txtfile = args.txtfile
csvfile = args.csvfile
if args.plt == 'False':
plt = False
else:
plt = True
writetxt = True
writecsv = True
if txtfile == 'None':
writetxt = False
if csvfile == 'None':
writecsv = False
if args.year == 'None':
year = 2020
else:
year = int(args.year)
# where the summary files will be written to
txtdir = xdir + '/Files'
if not os.path.exists(txtdir):
os.makedirs(txtdir)
direc = xdir + '/' + str(year) + '/results/' + station + '/'
tv = np.empty(shape=[0, 17])
if os.path.isdir(direc):
all_files = os.listdir(direc)
#print('Number of files in ', year1, len(all_files))
for f in all_files:
fname = direc + f
a = np.loadtxt(fname, comments='%')
tv = np.append(tv, a, axis=0)
#print(tv.shape)
Plt.figure()
t = tv[:, 0] + (tv[:, 1] + tv[:, 4] / 24) / 365.25
rh = tv[:, 2]
Plt.plot(t, rh, '.')
Plt.ylabel('Reflector Height (m)')
Plt.title('GNSS station: ' + station)
Plt.gca().invert_yaxis()
Plt.grid()
# default is to show the plot
if plt:
Plt.show()
# always make a png file
plotname = txtdir + '/' + station + '_subdaily_RH.png'
Plt.savefig(plotname)
print('png file saved as: ', plotname)
ii = np.argsort(t)
# apply time tags to a new variable
ntv = tv[ii, :]
N, M = np.shape(ntv)
#txtfile = station + '_subdaily_rh.txt'
#csvfile = station + '_subdaily_rh.csv'
if writecsv:
outfile = txtdir + '/' + csvfile
if writetxt:
outfile = txtdir + '/' + txtfile
if (writecsv) and (writetxt):
print('You cannot simultaneously write out a csvfile and a txtfile')
print('Default to writing only a txtfile')
writecsv = False
if (writecsv) or (writetxt):
print('Results are being written to : ', outfile)
fout = open(outfile, 'w+')
write_out_header(fout, station)
for i in np.arange(0, N, 1):
year = int(ntv[i, 0])
doy = int(ntv[i, 1])
year, month, day, cyyyy, cdoy, YMD = g.ydoy2useful(year, doy)
rh = ntv[i, 2]
UTCtime = ntv[i, 4]
mjd = ntv[i, 15]
ctime = g.nicerTime(UTCtime)
ctime2 = ctime[0:2] + ' ' + ctime[3:5]
if writecsv:
fout.write(
" {0:4.0f},{1:3.0f},{2:7.3f},{3:3.0f},{4:7.3f},{5:8.2f},{6:7.2f},{7:5.2f}, {8:3.0f},{9:8.5f}, {10:2.0f}, {11:2.0f},{12:2s},{13:2s},{14:15.6f} \n"
.format(year, doy, rh, ntv[i, 3], UTCtime, ntv[i, 5],
ntv[i, 6], ntv[i, 13], ntv[i, 10], ntv[i, 12],
month, day, ctime[0:2], ctime[3:5], mjd))
else:
fout.write(
" {0:4.0f} {1:3.0f} {2:7.3f} {3:3.0f} {4:7.3f} {5:8.2f} {6:7.2f} {7:5.2f} {8:3.0f} {9:8.5f} {10:2.0f} {11:2.0f} {12:5s} {13:15.6f} \n"
.format(year, doy, rh, ntv[i, 3], UTCtime, ntv[i, 5],
ntv[i, 6], ntv[i, 13], ntv[i, 10], ntv[i, 12],
month, day, ctime2, mjd))
fout.close()
def quickLook_function(station, year, doy, snr_type, f, e1, e2, minH, maxH,
reqAmp, pele, satsel, PkNoise, fortran, pltscreen):
"""
inputs:
station name (4 char), year, day of year
snr_type is the file extension (i.e. 99, 66 etc)
f is frequency (1, 2, 5), etc
e1 and e2 are the elevation angle limits in degrees for the LSP
minH and maxH are the allowed LSP limits in meters
reqAmp is LSP amplitude significance criterion
pele is the elevation angle limits for the polynomial removal. units: degrees
KL 20may10 pk2noise value is now sent from main function, which can be set online
KL 20aug07 added fortran boolean
KL 21feb06 return data from the plots so that Jupyter notebooks can use them.
also added pltscreen variable so that the default plots are not always displayed
"""
# return data to Jupyter Notebook people, good results
nw = {}
sw = {}
ne = {}
se = {}
# failed periodograms
failnw = {}
failsw = {}
failne = {}
failse = {}
list1 = {}
# list of satellites in each quadrant
list1['NW'] = []
list1['NE'] = []
list1['SW'] = []
list1['SE'] = []
list1['failNW'] = []
list1['failNE'] = []
list1['failSW'] = []
list1['failSE'] = []
# try the kelly way
data = {
'NW': {},
'SW': {},
'NE': {},
'SE': {},
'fNW': {},
'fSW': {},
'fNE': {},
'fSE': {}
}
# make sure environment variables exist
g.check_environ_variables()
if not os.path.isdir('logs'):
subprocess.call(['mkdir', 'logs'])
webapp = False
# orbit directories
ann = g.make_nav_dirs(year)
# titles in 4 quadrants - for webApp
titles = ['Northwest', 'Southwest', 'Northeast', 'Southeast']
stitles = ['NW', 'SW', 'NE', 'SE']
# define where the axes are located
bx = [0, 1, 0, 1]
by = [0, 0, 1, 1]
bz = [1, 3, 2, 4]
# various defaults - ones the user doesn't change in this quick Look code
delTmax = 70
polyV = 4 # polynomial order for the direct signal
desiredP = 0.01 # 1 cm precision
ediff = 2 # this is a QC value, eliminates small arcs
#four_in_one = True # put the plots together
minNumPts = 20
#noise region for LSP QC. these are meters
NReg = [minH, maxH]
#print('Refl. Ht. Noise Region used: ', NReg)
# for quickLook, we use the four geographic quadrants - these are azimuth angles in degrees
azval = [270, 360, 180, 270, 0, 90, 90, 180]
naz = int(len(azval) / 2) # number of azimuth pairs
pltname = 'temp.png' # default plot
requireAmp = reqAmp[0]
screenstats = True
# to avoid having to do all the indenting over again
# this allows snr file to live in main directory
# not sure that that is all that useful as I never let that happen
obsfile = g.define_quick_filename(station, year, doy, snr_type)
if os.path.isfile(obsfile):
print('>>>> The snr file exists ', obsfile)
else:
if True:
#print('looking for the SNR file on disk')
obsfile, obsfileCmp, snre = g.define_and_xz_snr(
station, year, doy, snr_type)
if snre:
dkfjaklj = True
#print('file exists on disk')
else:
print('>>>> The SNR the file does not exist ', obsfile)
print(
'This code used to try and make one for you, but I have removed this option.'
)
print('Please us rinex2snr and make a SNR file')
sys.exit()
allGood, sat, ele, azi, t, edot, s1, s2, s5, s6, s7, s8, snrE = read_snr_simple(
obsfile)
if allGood == 1:
# make output file for the quickLook RRH values, just so you can give them a quick look see
rhout = open('logs/rh.txt', 'w+')
amax = 0
minEdataset = np.min(ele)
print('minimum elevation angle (degrees) for this dataset: ',
minEdataset)
if minEdataset > (e1 + 0.5):
print('It looks like the receiver had an elevation mask')
e1 = minEdataset
if pltscreen:
plt.figure(figsize=(10, 6))
for a in range(naz):
if pltscreen:
plt.subplot(2, 2, bz[a])
plt.title(titles[a])
az1 = azval[(a * 2)]
az2 = azval[(a * 2 + 1)]
# this means no satellite list was given, so get them all
if satsel == None:
satlist = g.find_satlist(f, snrE)
else:
satlist = [satsel]
for satNu in satlist:
x, y, Nv, cf, UTCtime, avgAzim, avgEdot, Edot2, delT = g.window_data(
s1, s2, s5, s6, s7, s8, sat, ele, azi, t, edot, f, az1,
az2, e1, e2, satNu, polyV, pele, screenstats)
if Nv > minNumPts:
maxF, maxAmp, eminObs, emaxObs, riseSet, px, pz = g.strip_compute(
x, y, cf, maxH, desiredP, polyV, minH)
nij = pz[(px > NReg[0]) & (px < NReg[1])]
Noise = 0
iAzim = int(avgAzim)
if (len(nij) > 0):
Noise = np.mean(nij)
else:
Noise = 1
iAzim = 0 # made up numbers
if (delT < delTmax) & (eminObs < (e1 + ediff)) & (
emaxObs >
(e2 - ediff)) & (maxAmp > requireAmp) & (maxAmp / Noise
> PkNoise):
T = g.nicerTime(UTCtime)
rhout.write(
'SUCCESS Azimuth {0:3.0f} RH {1:6.3f} m, Sat {2:3.0f} Freq {3:3.0f} Amp {4:4.1f} PkNoise {5:3.1f} UTC {6:5s} \n '
.format(avgAzim, maxF, satNu, f, maxAmp,
maxAmp / Noise, T))
if pltscreen:
plt.plot(px, pz, linewidth=1.5)
if a == 0:
nw[satNu] = [px, pz]
list1['NW'].append(satNu)
elif a == 1:
sw[satNu] = [px, pz]
list1['SW'].append(satNu)
elif a == 2:
ne[satNu] = [px, pz]
list1['NE'].append(satNu)
elif a == 3:
se[satNu] = [px, pz]
list1['SE'].append(satNu)
idc = stitles[a]
data[idc][satNu] = [px, pz]
else:
# these are failed tracks
if pltscreen:
plt.plot(px, pz, 'gray', linewidth=0.5)
if a == 0:
failnw[satNu] = [px, pz]
list1['failNW'].append(satNu)
elif a == 1:
failsw[satNu] = [px, pz]
list1['failSW'].append(satNu)
elif a == 2:
failne[satNu] = [px, pz]
list1['failNE'].append(satNu)
elif a == 3:
failse[satNu] = [px, pz]
list1['failSE'].append(satNu)
idc = 'f' + stitles[a]
data[idc][satNu] = [px, pz]
# i do not know how to add a grid using these version of matplotlib
tt = 'GNSS-IR results: ' + station.upper() + ' Freq:' + g.ftitle(
f) + ' Year/DOY:' + str(year) + ',' + str(doy)
if pltscreen:
aaa, bbb = plt.ylim()
amax = max(amax, bbb) # do not know how to implement this ...
if (a == 3) or (a == 1):
plt.xlabel('reflector height (m)')
if (a == 1) or (a == 0):
plt.ylabel('volts/volts')
rhout.close()
print(
'preliminary reflector height results are stored in a file called logs/rh.txt'
)
# do not plot if sending data to Jupyter Notebooks
if pltscreen:
plt.suptitle(tt, fontsize=12)
plt.show()
else:
print(
'some kind of problem with SNR file, so I am exiting the code politely.'
)
return data