Exemplo n.º 1
0
    # for all the CN0 data per Signaltype and SVID => add NaN for missing data
    # for index, signalType in enumerate(signalTypesSVID):

    print('\nmeasTOW = %d - %d - %d' %
          (len(measTOW), len(measTOW[0]), len(measTOW[-1])))
    print(measTOW[0])
    print(measTOW[-1])
    for i, measTOWi in enumerate(measTOW):
        print('measTOW[%d] = %f - %f' % (i, measTOWi[0], measTOWi[-1]))
    for i, measCN0i in enumerate(measCN0):
        print('measCN0[%d] = %f - %f' % (i, measCN0i[0], measCN0i[-1]))

    for i, SVID in enumerate(SVIDlist):
        print('Observed SV %d - SignalType = %d' % (SVID, STlist[i]))

    # adjust the measCNO arrays to fill with NaN as to fit the TOWall array for plotting
    measCN0span = []

    for i in range(len(measCN0)):
        measCN0span.append(fillDataGaps(TOWspan, measTOW[i], measCN0[i]))

    for i in range(len(measCN0)):
        print('measCN0span[%d] = %s (%d)' %
              (i, measCN0span[i], len(measCN0span[i])))

    # create the plots for each signaltype
    plotCN0.plotCN0(SVIDlist, STlist, TOWspan, UTCspan, measCN0span,
                    dateString, verbose)

    sys.exit(E_SUCCESS)
Exemplo n.º 2
0
    print('UTCspan = %s => %s (%d)' % (UTCspan[0], UTCspan[-1], np.size(UTCspan)))

    # for all the CN0 data per Signaltype and SVID => add NaN for missing data
    # for index, signalType in enumerate(signalTypesSVID):
    print('\nmeasTOW = %d - %d - %d' % (len(measTOW), len(measTOW[0]), len(measTOW[-1])))

    for i, measTOWi in enumerate(measTOW):
        print('measTOW[%d] = %f - %f' % (i, measTOWi[0], measTOWi[-1]))
    for i, measCN0i in enumerate(measCN0):
        print('measCN0[%d] = %f - %f' % (i, measCN0i[0], measCN0i[-1]))

    for i, SVID in enumerate(SVIDlist):
        print('Observed SV %d - SignalType = %d' % (SVID, STlist[i]))

    # adjust the measCNO arrays to fill with NaN as to fit the TOWall array for plotting
    measCN0span = []

    for i in range(len(measCN0)):
        measCN0span.append(fillDataGaps(TOWspan, measTOW[i], measCN0[i]))

    for i in range(len(measCN0)):
        print('measCN0span[%d] = %s (%d)' % (i, measCN0span[i], len(measCN0span[i])))
    # creates the lists of elevation and the coresponding Tow
    fSV = SVIDsVis[0]
    for i in SVIDsVis:
            ELEVATIONVisibility, ELEVATIONTow = extractELEVATION(i, dataVisibility, visibilityTOW, verbose)
            ELEVATIONTowUTC = plotCN0.TOW2UTC(1873, ELEVATIONTow)
            plotCN0.plotCN0(i, fSV, SVIDlist, STlist, ELEVATIONTowUTC, UTCspan, JammingStartTime, JammingEndTime, measCN0span, ELEVATIONVisibility, JammingValues, dateString, verbose)
    # create the plots for each signaltype
    sys.exit(E_SUCCESS)
Exemplo n.º 3
0
    print ('TOWspan = %f => %f (%d)' % (TOWspan[0], TOWspan[-1], np.size(TOWspan)))
    print ('UTCspan = %s => %s (%d)' % (UTCspan[0], UTCspan[-1], np.size(UTCspan)))

    # for all the CN0 data per Signaltype and SVID => add NaN for missing data
    # for index, signalType in enumerate(signalTypesSVID):

    print('\nmeasTOW = %d - %d - %d' % (len(measTOW), len(measTOW[0]), len(measTOW[-1])))
    print(measTOW[0])
    print(measTOW[-1])
    for i, measTOWi in enumerate(measTOW):
        print('measTOW[%d] = %f - %f' % (i, measTOWi[0], measTOWi[-1]))
    for i, measCN0i in enumerate(measCN0):
        print('measCN0[%d] = %f - %f' % (i, measCN0i[0], measCN0i[-1]))

    for i,SVID in enumerate(SVIDlist):
        print('Observed SV %d - SignalType = %d' % (SVID, STlist[i]))

    # adjust the measCNO arrays to fill with NaN as to fit the TOWall array for plotting
    measCN0span = []

    for i in range(len(measCN0)):
        measCN0span.append(fillDataGaps(TOWspan, measTOW[i], measCN0[i]))

    for i in range(len(measCN0)):
        print('measCN0span[%d] = %s (%d)' % (i, measCN0span[i], len(measCN0span[i])))

    # create the plots for each signaltype
    plotCN0.plotCN0(SVIDlist, STlist, TOWspan, UTCspan, measCN0span, dateString, verbose)

    sys.exit(E_SUCCESS)
Exemplo n.º 4
0
    for i, measTOWi in enumerate(measTOW):
        print('measTOW[%d] = %f - %f' % (i, measTOWi[0], measTOWi[-1]))
    for i, measCN0i in enumerate(measCN0):
        print('measCN0[%d] = %f - %f' % (i, measCN0i[0], measCN0i[-1]))

    for i, SVID in enumerate(SVIDlist):
        print('Observed SV %d - SignalType = %d' % (SVID, STlist[i]))

    # adjust the measCNO arrays to fill with NaN as to fit the TOWall array for plotting
    measCN0span = []

    for i in range(len(measCN0)):
        measCN0span.append(fillDataGaps(TOWspan, measTOW[i], measCN0[i]))

    for i in range(len(measCN0)):
        print('measCN0span[%d] = %s (%d)' %
              (i, measCN0span[i], len(measCN0span[i])))
    # creates the lists of elevation and the coresponding Tow
    fSV = SVIDsVis[0]
    for i in SVIDsVis:
        ELEVATIONVisibility, ELEVATIONTow = extractELEVATION(
            i, dataVisibility, visibilityTOW, verbose)
        ELEVATIONTowUTC = plotCN0.TOW2UTC(1873, ELEVATIONTow)
        plotCN0.plotCN0(i, fSV, SVIDlist, STlist, ELEVATIONTowUTC, UTCspan,
                        JammingStartTime, JammingEndTime, measCN0span,
                        ELEVATIONVisibility, JammingValues, dateString,
                        verbose)
    # create the plots for each signaltype
    sys.exit(E_SUCCESS)