# determine current weeknumber and subsequent date from SBF data
WkNr = int(dataMeas['MEAS_WNC'][0])
dateString = gpstime.UTCFromWT(WkNr, float(
dataMeas['MEAS_TOW'][0])).strftime("%d/%m/%Y")
if verbose:
print('WkNr = %d - dateString = %s' % (WkNr, dateString))
# correct the smoothed PR Code and work with the raw PR
dataMeas['MEAS_CODE'] = sbf2stf.removeSmoothing(
dataMeas['MEAS_CODE'], dataExtra['EXTRA_SMOOTHINGCORR'],
dataExtra['EXTRA_MPCORR'])
# print('rawPR = %s\n' % dataMeas['MEAS_CODE'])
# find list of SVIDs and SignalTypes observed
SVIDs = sbf2stf.observedSatellites(dataMeas['MEAS_SVID'], verbose)
signalTypes = sbf2stf.observedSignalTypes(dataMeas['MEAS_SIGNALTYPE'],
verbose)
# create the CN0 plots for all SVs and SignalTypes
indexSignalType = []
dataMeasSignalType = []
# storing data in arrays per SV and per signalType
measTOW = [] # TOWs with measurements
measCN0 = [] # CNO values @ measTOW
STlist = [] # list of signaltypes traversed
SVIDlist = [] # list of SVIDs traversed
# extract first TOW and CN0 arrays for all SVs and signaltypes
for SVID in SVIDs:
# read the MeasExtra data into numpy array
dataExtra = sbf2stf.readMeasExtra(sbf2stfConverted[SBF2STFOPTS.index(option)], verbose)
else:
print(' wrong option %s given.' % option)
sys.exit(E_WRONG_OPTION)
# check whether the same signaltypes are on corresponsing lines after sorting
if not sbf2stf.verifySignalTypeOrder(dataMeas['MEAS_SIGNALTYPE'], dataExtra['EXTRA_SIGNALTYPE'], dataMeas['MEAS_TOW'], verbose):
sys.exit(E_SIGNALTYPE_MISMATCH)
# correct the smoothed PR Code and work with the raw PR
dataMeas['MEAS_CODE'] = sbf2stf.removeSmoothing(dataMeas['MEAS_CODE'], dataExtra['EXTRA_SMOOTHINGCORR'], dataExtra['EXTRA_MPCORR'])
# print('dataMeas['MEAS_CODE'] = %s\n' % dataMeas['MEAS_CODE'])
# find list of SVIDs observed
SVIDs = sbf2stf.observedSatellites(dataMeas['MEAS_SVID'], verbose)
for SVID in SVIDs:
print('=' * 50)
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
print('SVID = %d - %s - %s%d' % (SVID, gnssSyst, gnssSystShort, gnssPRN))
indexSVID = sbf2stf.indicesSatellite(SVID, dataMeas['MEAS_SVID'], verbose)
dataMeasSVID = dataMeas[indexSVID]
print("indexSVID = %s" % indexSVID)
# store temporaray results ONLY for inspection
nameDataMeasSVID = str(SVID) + '.csv'
print('nameDataMeasSVID = %s' % nameDataMeasSVID)
print('dataMeasSVID = %s' % dataMeasSVID)
np.savetxt(nameDataMeasSVID, dataMeasSVID, fmt='%i,%.1f,%i,%i,%i,%i,%i,%.2f,%.2f,%.2f,%.2f,%i,%i,%i')
print('dataChanSt = %s' % dataChanSt)
print('dataChanSt[0] = %s' % dataChanSt[0])
# determine current weeknumber and subsequent date from SBF data
WkNr = int(dataChanSt['CHST_WNC'][0])
dateString = gpstime.UTCFromWT(WkNr, float(dataChanSt['CHST_TOW'][0])).strftime("%d/%m/%Y")
if verbose:
print('WkNr = %d - dateString = %s' % (WkNr, dateString))
# create subset with only valid elevation angles
indexValid = sbf2stf.findValidElevation(dataChanSt['CHST_Elevation'], verbose)
dataChanStValid = dataChanSt[indexValid]
# find the list of SVIDs with valid elev/azim data
SVIDs = sbf2stf.observedSatellites(dataChanStValid['CHST_SVID'], verbose)
# extract for each satellite the elevation and azimuth angles
prnElev = []
prnAzim = []
prnHour = []
prnHourElev = []
prnHourAzim = []
for i, PRN in enumerate(SVIDs):
print('PRN = %d' % PRN)
indexPRN = sbf2stf.indicesSatellite(PRN, dataChanStValid['CHST_SVID'], verbose)
prnElev.append(dataChanStValid[indexPRN]['CHST_Elevation'])
prnAzim.append(dataChanStValid[indexPRN]['CHST_Azimuth'])
# retain only multiples of hours to display
prnTime = dataChanStValid[indexPRN]['CHST_TOW']
# check whether the same signaltypes are on corresponsing lines after sorting
if not sbf2stf.verifySignalTypeOrder(dataMeas['MEAS_SIGNALTYPE'], dataExtra['EXTRA_SIGNALTYPE'], dataMeas['MEAS_TOW'], verbose):
sys.exit(E_SIGNALTYPE_MISMATCH)
# determine current weeknumber and subsequent date from SBF data
WkNr = int(dataMeas['MEAS_WNC'][0])
dateString = gpstime.UTCFromWT(WkNr, float(dataMeas['MEAS_TOW'][0])).strftime("%d/%m/%Y")
if verbose:
print('WkNr = %d - dateString = %s' % (WkNr, dateString))
# correct the smoothed PR Code and work with the raw PR
dataMeas['MEAS_CODE'] = sbf2stf.removeSmoothing(dataMeas['MEAS_CODE'], dataExtra['EXTRA_SMOOTHINGCORR'], dataExtra['EXTRA_MPCORR'])
# print('rawPR = %s\n' % dataMeas['MEAS_CODE'])
# find list of SVIDs from MeasEpoch and SatVisibility blocks and SignalTypes observed
SVIDs = sbf2stf.observedSatellites(dataMeas['MEAS_SVID'], verbose)
SVIDsVis = sbf2stf.observedSatellites(dataVisibility['VISIBILITY_SVID'], verbose)
signalTypes = sbf2stf.observedSignalTypes(dataMeas['MEAS_SIGNALTYPE'], verbose)
# storing data in arrays per SV and per signalType
indexSignalType = []
dataMeasSignalType = []
measTOW = [] # TOWs with measurements
measTOWElev = []
measCN0 = [] # CNO diff @ measTOW
measCN0Elev = []
STlist = [] # list of signaltypes traversed
SVIDlist = [] # list of SVIDs traversed for CN0
SVIDlistElev = [] # list of SVIDs traversed for Elev
ELEVATIONVisibility = [] # list of Elevation traversed
print('dataChanSt[0] = %s' % dataChanSt[0])
# determine current weeknumber and subsequent date from SBF data
WkNr = int(dataChanSt['CHST_WNC'][0])
dateString = gpstime.UTCFromWT(WkNr, float(
dataChanSt['CHST_TOW'][0])).strftime("%d/%m/%Y")
if verbose:
print('WkNr = %d - dateString = %s' % (WkNr, dateString))
# create subset with only valid elevation angles
indexValid = sbf2stf.findValidElevation(dataChanSt['CHST_Elevation'],
verbose)
dataChanStValid = dataChanSt[indexValid]
# find the list of SVIDs with valid elev/azim data
SVIDs = sbf2stf.observedSatellites(dataChanStValid['CHST_SVID'], verbose)
# extract for each satellite the elevation and azimuth angles
prnElev = []
prnAzim = []
prnHour = []
prnHourElev = []
prnHourAzim = []
for i, PRN in enumerate(SVIDs):
print('PRN = %d' % PRN)
indexPRN = sbf2stf.indicesSatellite(PRN, dataChanStValid['CHST_SVID'],
verbose)
prnElev.append(dataChanStValid[indexPRN]['CHST_Elevation'])
prnAzim.append(dataChanStValid[indexPRN]['CHST_Azimuth'])
# retain only multiples of hours to display
