def observedSatellites(colSVIDs, verbose):
"""
Creates an index of observed satellites
Parameters:
colSVIDs: contains the SVIDs
Returns:
Ordered list of observed SVIDs
"""
if verbose:
sys.stdout.write(' Extracting list of observed satellites: ')
listSVIDs = sorted(list(set(colSVIDs)))
if verbose:
for index, SVPRN in enumerate(listSVIDs):
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVPRN)
sys.stdout.write('%s%d (%d)' % (gnssSystShort, gnssPRN, SVPRN))
if index < len(listSVIDs) - 1:
sys.stdout.write(', ')
sys.stdout.write('\n')
return listSVIDs
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')
signalTypesSVID = sbf2stf.observedSignalTypes(dataMeasSVID['MEAS_SIGNALTYPE'], verbose)
print('signalTypesSVID = %s' % signalTypesSVID)
def plotLockTime(SVID, signalTypes, dataMeasSVID, lliIndices, lliTOWs,
verbose):
"""
plotLockTime creates a plot of the locktime and indicates loss of locks
Parameters:
SVID: satellite ID
signalTypes: signal types to represent
dataMeasSVID: data from MeasEpoch_2 but for one SVs
indexLossOfLock: indices for the occurance of loss of lock
verbose: display interactive plot
"""
# print('\nplotLockTime' + '-' * 25)
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
# for i, signalType in enumerate(signalTypes):
# print('PLT: signalType[%d] = %s' % (i, signalType))
# print('PLT: TOW = %s (%d)' % (dataMeasSVID[i]['MEAS_TOW'], len(dataMeasSVID[i]['MEAS_TOW'])))
# print('PLT: lockTimes = %s (%d)\n' % (dataMeasSVID[i]['MEAS_LOCKTIME'], len(dataMeasSVID[i]['MEAS_LOCKTIME'])))
# print("PLT: indexLossOfLock[%d] = %s (Nr = %d)" % (i, lliIndices[i], len(lliIndices[i])))
# # myData2 = dataMeasSVID[i][lliIndices[i]]
# # print("PLT: myData2 = %s (len = %d)" % (myData2['MEAS_TOW'], len(myData2['MEAS_TOW'])))
# # print("PLT: idemand = %s (len = %d)\n" % (dataMeasSVID[i][lliIndices[i]]['MEAS_TOW'], len(dataMeasSVID[i][)lliIndices[i]]['MEAS_TOW']))
# create the plot window
# plt.style.use('BEGPIOS')
plt.style.use('ggplot')
plt.figure(1)
subPlot = plt.subplot(1, 1, 1)
# titles and axis-labels
dateString = gpstime.UTCFromWT(
float(dataMeasSVID[0]['MEAS_WNC'][0]),
float(dataMeasSVID[0]['MEAS_TOW'][0])).strftime("%d/%m/%Y")
plt.title('Lock Times for %s PRN %d (%d)' %
(gnssSyst, gnssPRN, SVID)) # , fontsize='18'
plt.ylabel('Lock Time [s]')
plt.xlabel('Time [hh:mm] (' + dateString + ')')
for index, signalType in enumerate(signalTypes):
# lockTime = dataMeasSVID[index]['MEAS_LOCKTIME']
# print("index = %d lockTime.size = %d" % (index, len(lockTime)))
sigTypeColor = mPlt.getSignalTypeColor(signalType)
utc = []
for count in range(0, len(dataMeasSVID[index])):
utc.append(
gpstime.UTCFromWT(
float(dataMeasSVID[index]['MEAS_WNC'][count]),
float(dataMeasSVID[index]['MEAS_TOW'][count])))
plt.plot(utc,
dataMeasSVID[index]['MEAS_LOCKTIME'],
color=sigTypeColor,
linestyle='',
markersize=0.75,
marker='.')
# add a marker at the LLI
utc2 = []
for count2 in range(0, len(dataMeasSVID[index][lliIndices[index]])):
utc2.append(
gpstime.UTCFromWT(
float(dataMeasSVID[index][lliIndices[index]]['MEAS_WNC']
[count2]),
float(dataMeasSVID[index][lliIndices[index]]['MEAS_TOW']
[count2])))
plt.plot(utc2,
dataMeasSVID[index][lliIndices[index]]['MEAS_LOCKTIME'],
color=sigTypeColor,
linestyle='',
markersize=7,
markerfacecolor=sigTypeColor,
marker=mPlt.mFilledMarkers[signalType %
len(mPlt.mFilledMarkers)])
# annotate the plot
annotateTxt = mSSN.GNSSSignals[signalType]['name'] + str(
': %d LLI' % len(lliIndices[index]))
subPlot.text(0.02,
0.95 - index * 0.0375,
annotateTxt,
verticalalignment='bottom',
horizontalalignment='left',
transform=subPlot.transAxes,
color=sigTypeColor,
fontsize=12)
# make x-axis a hh:mm:ss
ax = plt.gca()
xfmt = md.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
# adjust range for Y axis
axes = plt.gca()
axes.set_ylim(mPlt.adjustYAxisLimits(axes))
axes.set_xlim(mPlt.adjustXAxisLimits(axes))
plt.text(0,
-0.125,
r'$\copyright$ Alain Muls ([email protected])',
horizontalalignment='left',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
plt.text(1,
-0.125,
r'$\copyright$ Frederic Snyers ([email protected])',
horizontalalignment='right',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
# mPlt.annotateText(r'$\copyright$ Alain Muls ([email protected])', subPlot, 0, -0.12, 'left', fontsize='x-small')
# mPlt.annotateText(r'$\copyright$ Frederic Snyers ([email protected])', subPlot, 1, -0.12, 'right', fontsize='x-small')
fig = plt.gcf()
# fig.set_size_inches(12*2.5, 9*2.5)
fig.savefig('%s-%s%d-locktime.png' % (gnssSyst, gnssSystShort, gnssPRN),
dpi=fig.dpi)
if verbose:
plt.show(block=False) # block=False)
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'
# np.savetxt(nameDataMeasSVID, dataMeasSVID, fmt=colFmtMeasEpoch)
signalTypesSVID = sbf2stf.observedSignalTypes(
dataMeasSVID['MEAS_SIGNALTYPE'], verbose)
# print 'signalTypesSVID = %s' % signalTypesSVID
def plotSidePeaks(SVID, signalTypesSVID, WkNr, iTOW, deltaPR, sidePeaksTOW,
sidePeakDPR, jumpDPRNear97Indices, jumpDPRNear1465Indices,
lliTOWs, strDate, verbose):
"""
plotSidePeaks plots the difference between the code measurements on L1A (reference) and E6A and indicates where a possible side peak is noticed
Parameters:
SVID: SSN SVID of satellite
signalTypesSVID; the signal types for this SVID
WkNt: week number
iTOW: common TOWs where both code measurements are available
deltaPR: difference between PR on L1A and E61
sidePeaksTOW: list of TOWs which could be indicators of SidePeaks
sidePeakDPR: delta PR at these TOWs
jumpDPRNear97Indices: indices in sidePeaksTOW, sidePeakDPR which are closest to integer multipe of 9.7m
jumpDPRNear1465Indices: indices in sidePeaksTOW, sidePeakDPR which are closest to integer multipe of 14.65m
lliTOWs: TOW that indicate a loss of lock per signal type
strDate: observation date
verbose: ok
"""
print '-' * 50
# get info for GNSS satellite
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
SVIDColor = mPlt.getSVIDColor(SVID)
# create the plot window
# plt.style.use('BEGPIOS')
plt.style.use('ggplot')
plt.figure(2)
subPlot = plt.subplot(1, 1, 1)
# titles and axis-labels
plt.title('Side Peak Indicator for %s PRN %d (%d)' %
(gnssSyst, gnssPRN, SVID)) # , fontsize='18'
plt.ylabel(r'$\Delta$ PR (%s - %s)' %
(mSSN.GNSSSignals[16]['name'], mSSN.GNSSSignals[18]['name']))
plt.xlabel('Time [hh:mm] (' + strDate + ')')
# plot the deltaPRs vs iTOW
print 'iTOW = %s (%d)' % (iTOW, len(iTOW))
print 'deltaPR = %s (%d)' % (deltaPR, len(deltaPR))
# plot the indicators for the sidepeaks after conversion to utc
utc2 = [] # used for all possible detections
utc3 = [] # used for those that are multiple of 9.7m
utc4 = [] # used for those that are multiple of 14.65m
for count in range(0, len(sidePeaksTOW)):
utc2.append(gpstime.UTCFromWT(float(WkNr), float(sidePeaksTOW[count])))
if count in jumpDPRNear97Indices:
utc3.append(utc2[-1])
if count in jumpDPRNear1465Indices:
utc4.append(utc2[-1])
plt.plot(utc2,
sidePeakDPR,
color='orange',
linestyle='',
markersize=7,
marker='o',
markeredgecolor='orange',
markerfacecolor=None)
print 'utc2 = %s (#%d)' % (utc2, len(utc2))
print 'sidePeakDPR = %s (#%d)' % (sidePeakDPR, len(sidePeakDPR))
print 'jumpDPRNear97Indices = %s (#%d)' % (jumpDPRNear97Indices,
len(jumpDPRNear97Indices))
print 'sidePeakDPR = %s (#%d)' % (sidePeakDPR[jumpDPRNear97Indices],
len(sidePeakDPR[jumpDPRNear97Indices]))
print 'utc3 = %s (#%d)' % (utc3, len(utc3))
plt.plot(utc3,
sidePeakDPR[jumpDPRNear97Indices],
color='red',
linestyle='',
markersize=7,
marker='o',
markeredgecolor='red',
markerfacecolor=None)
plt.plot(utc4,
sidePeakDPR[jumpDPRNear1465Indices],
color='blue',
linestyle='',
markersize=7,
marker='o',
markeredgecolor='blue',
markerfacecolor=None)
# annotate to signal number of detections and number of integer multiple of 9.7m
annotateTxt = 'Side Peaks on E1A: %d' % len(utc3)
subPlot.text(0.95,
0.95,
annotateTxt,
verticalalignment='bottom',
horizontalalignment='right',
transform=subPlot.transAxes,
color='red',
fontsize=12)
# annotate to signal number of detections and number of integer multiple of 14.65m
annotateTxt = 'Side Peaks on E6A: %d' % len(utc4)
subPlot.text(0.95,
0.92,
annotateTxt,
verticalalignment='bottom',
horizontalalignment='right',
transform=subPlot.transAxes,
color='blue',
fontsize=12)
annotateTxt = 'Other: %d' % (len(utc2) - len(utc3) - len(utc4))
subPlot.text(0.95,
0.89,
annotateTxt,
verticalalignment='bottom',
horizontalalignment='right',
transform=subPlot.transAxes,
color='orange',
fontsize=12)
# transform WkNr, TOW to UTC time
utc = []
for i in range(0, len(iTOW)):
utc.append(gpstime.UTCFromWT(float(WkNr), float(iTOW[i])))
# plot the deltaPR vs UTC time
plt.plot(utc,
deltaPR,
color=SVIDColor,
linestyle='-',
linewidth=0.5,
marker='.',
markersize=3.5) # , linestyle='', marker='.', markersize=1)
for i, lliTOWsST in enumerate(lliTOWs):
print 'lliTOWs[%d] = %s' % (i, lliTOWsST)
utc2 = []
sigTypeColor = mPlt.getSignalTypeColor(signalTypesSVID[i])
# annotate the plot
annotateTxt = mSSN.GNSSSignals[signalTypesSVID[i]]['name'] + ' LLI'
subPlot.text(0.02,
0.95 - i * 0.0375,
annotateTxt,
verticalalignment='bottom',
horizontalalignment='left',
transform=subPlot.transAxes,
color=sigTypeColor,
fontsize=12)
# drax vertical line for the LLI indicators
for j, lliTOWST in enumerate(lliTOWsST):
utc2.append(gpstime.UTCFromWT(float(WkNr), lliTOWST))
# print 'lliTOWs[%d] = %s utc = %s' % (j, lliTOWST, utc2[j])
# draw a vertical line in the color of the signal type
plt.axvline(utc2[j], color=sigTypeColor)
print 'sidePeaksTOW = %s (%d)' % (sidePeaksTOW, len(sidePeaksTOW))
# print 'utc2 = %s (%d)' % (utc2, len(utc2))
# plt.plot(sidePeaksTOW, 0.5, color='red', linestyle='', markersize=7, marker=mPlt.mFilledMarkers[SVID % len(mPlt.mFilledMarkers)])
# adjust the axes to represent hh:mm:ss
ax = plt.gca()
xfmt = md.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
# adjust range for Y axis
axes = plt.gca()
axes.set_ylim(mPlt.adjustYAxisLimits(axes))
axes.set_xlim(mPlt.adjustXAxisLimits(axes))
plt.text(0,
-0.125,
r'$\copyright$ Alain Muls ([email protected])',
horizontalalignment='left',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
plt.text(1,
-0.125,
r'$\copyright$ Frederic Snyers ([email protected])',
horizontalalignment='right',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
fig = plt.gcf()
# fig.set_size_inches(12*2.5, 9*2.5)
fig.savefig('%s-%s%d-sidepeak.png' % (gnssSyst, gnssSystShort, gnssPRN),
dpi=fig.dpi)
if verbose:
plt.show()
# close the figure
plt.close()
print '-' * 50
def plotCN0(k, firstSV, listSVIDs, listST, spanElevation, spanUTC, spanJammingStart, spanJammingEnd, CN0meas, dataVisibilitySVprn, dataJammingValues, dateStr, verbose=False):
"""
plotCN0 plots the CN0 values for SVs per signalType observed
Parameters:
k is the coresponding satellite from the Visibility block
listSVIDs is list of SVIDs we have data for
listST is list of signaltypes
spanTElevation is the GPS time representation of satellites from Elevation file
spanUTC is the UTC representation of spanElevation
CN0meas contains observed CN0 for all SVs and all signalTypes
"""
# plt.style.use('ggplot')
# plt.style.use('BEGPIOS')
# first plot all SVs per signalType
# get unique list of signaltypes to determine the number of plots we have to make
uniqSTs = list(set(listST))
uniqSVs = list(set(listSVIDs))
figNr = len(uniqSTs) # nr of figures already used
# print('uniqSTs = %s' % uniqSTs)
# loop over the signalTypes
if k == firstSV:
for i, uniqSTi in enumerate(uniqSTs):
plt.figure(i)
ax = plt.gca()
ax.set_color_cycle(['purple', 'black', 'green', 'cyan', 'violet'])
# create label for identify SV and plot its CN0 value for this signalType
satLabel = []
# colors = iter(cm.rainbow(np.linspace(0, 1, len(listSVIDs))))
for j, STj in enumerate(listST):
if STj == uniqSTi:
satLabel.append(mSSN.svPRN(listSVIDs[j])[1] + str(mSSN.svPRN(listSVIDs[j])[2]))
plt.plot(spanUTC, CN0meas[j], linestyle='-', linewidth=0.5, alpha=0.75, label=satLabel[-1])
print('i = %d len = %d' % (i, np.size(uniqSTs)))
# plot annotation
plt.title('Signaltype: %s' % mSSN.GNSSSignals[uniqSTi]['name'], fontsize='x-large')
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Andrei Alex ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# add the legend
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
# print('box.x0 = %f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
# ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.3,
box.width, box.height * 0.7])
box = ax.get_position()
# print('after\nbox.x0 = %f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
plt.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(satLabel), fontsize='xx-small')
llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
# ggplot2.rstyle(ax)
fig = plt.gcf()
if verbose:
print('\nfigname = %s -- %s' % (STj, mSSN.GNSSSignals[uniqSTi]['name']))
fig.savefig('%s-CN0.png' % (mSSN.GNSSSignals[uniqSTi]['name']), dpi=fig.dpi)
if i != len(uniqSTs) - 1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# second plot all signalTypes per SVs
# find the SV identifiers ans make them unique
for i, uniqSVi in enumerate(uniqSVs):
plt.figure(i + figNr)
ax = plt.gca()
# create label for signalType and plot its SN0 for this uniqSVi
stLabel = []
colors = iter(cm.rainbow(np.linspace(0, 1, len(listST))))
for j, SVj in enumerate(listSVIDs):
if SVj == uniqSVi:
stLabel.append(mSSN.GNSSSignals[listST[j]]['name'])
print('mSSN.GNSSSignals[listST[%d]][name] = %s' % (j, mSSN.GNSSSignals[listST[j]]['name']))
print('spanUTC = %s ==> %s' % (spanUTC[0], spanUTC[-1]))
plt.plot(spanUTC, CN0meas[j], linestyle='-', color=next(colors), linewidth=0.25, alpha=0.75, label=stLabel[-1])
ax.set_ylim(0, 60)
# plot annotation
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVj)
textSVID = gnssSystShort + str(gnssPRN)
print('j = %d - SV = %s, uniqSVi = %s\n' % (i, textSVID, uniqSVi))
plt.title('Satellite: %s' % textSVID)
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Andrei Alex ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# add the legend
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
# print('box.x0 = %f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
# ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.4,
box.width, box.height * 0.6])
box = ax.get_position()
# print('after\nbox.x0 = %f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
plt.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(stLabel), fontsize='xx-small')
llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
# plt.legend(bbox_to_anchor=(0., 1.052, 1., .052), loc='lower left', ncol=np.size(stLabel), mode="expand", borderaxespad=0., fontsize=9)
plt.tight_layout(rect=(0, 0, 1, 1))
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
fig = plt.gcf()
fig.savefig('%s-%s%d-CN0.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi)
if i != len(uniqSVs)-1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# close the figure
plt.close()
for i, uniqSVi in enumerate(uniqSVs):
if k == uniqSVi:
fig = plt.figure(i + figNr)
ax = plt.gca()
ax.set_color_cycle(['purple', 'black', 'green', 'cyan', 'violet'])
# create label for signalType and plot its SN0 for this uniqSVi
stLabel = []
for j, SVj in enumerate(listSVIDs):
if SVj == uniqSVi:
stLabel.append(mSSN.GNSSSignals[listST[j]]['name'])
print('mSSN.GNSSSignals[listST[%d]][name] = %s' % (j, mSSN.GNSSSignals[listST[j]]['name']))
print('spanUTC = %s ==> %s' % (spanUTC[0], spanUTC[-1]))
# plotting CNO
ax.plot(spanUTC, CN0meas[j], linestyle='-', linewidth=0.5, alpha=1, label=stLabel[-1])
ax.set_ylim(0, 60)
# plot annotation for CN0
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVj)
textSVID = gnssSystShort + str(gnssPRN)
print('j = %d - SV = %s, uniqSVi = %s\n' % (i, textSVID, uniqSVi))
plt.title('Satellite: %s' % textSVID)
plt.xlabel('Time of ' + dateStr)
# plotting Elevation
ax2 = ax.twinx()
ax2.set_ylim(0, 90)
ax2.plot(spanElevation, dataVisibilitySVprn, linestyle='-', color='red', linewidth=0.5, alpha=0.75, label='Elevation')
ax.set_ylabel('C/NO', fontsize='x-large')
ax2.set_ylabel('Elevation', fontsize='x-large')
y_min, y_max = ax.get_ylim()
# plotting vertical lines corresponding the jamming starting and ending time
for i, j, k in zip(spanJammingStart, spanJammingEnd, dataJammingValues):
ax.axvline(i, color='k', linestyle='-')
ax.axvline(j, color='K', linestyle='-')
ax.text(i, y_min + 2, k, horizontalalignment='right', rotation='90')
ax.fill([i, i, j, j], [y_min, y_max, y_max, y_min], color='gray', alpha=0.2)
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# if k == uniqSVi:
# ax2 = plt.gca()
# ax2.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
# ax2.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Andrei Alex ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# add the legend
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
# print('box.x0 =a%f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
ax.set_position([box.x0, box.y0 + box.height * 0.4,
box.width, box.height * 0.6])
box = ax.get_position()
# print('after\nbox.x0 = %f' % box.x0)
# print('box.y0 = %f' % box.y0)
# print('box.width = %f' % box.width)
# print('box.height = %f' % box.height)
ax.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(stLabel), fontsize='xx-small')
# ax2.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='best', ncol=np.size(stLabel), fontsize='xx-small')
# plt.legend(bbox_to_anchor=(0., 1.052, 1., .052), loc='lower left', ncol=np.size(stLabel), mode="expand", borderaxespad=0., fontsize=9)
# llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
# plt.setp(llines, linewidth=4) # the legend linewidth
plt.tight_layout(rect=(0, 0, 1, 1))
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.1, box.width, box.height * 0.9])
fig.subplots_adjust(wspace=.2, hspace=.1)
fig = plt.gcf()
fig.savefig('%s-%s%d-CN0.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi, bbox_inches='tight')
if i != len(uniqSVs)-1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# close the figure
plt.close()
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 CN0 diff
measCN0diff = []
for i in range(len(measCN0span)):
measCN0diff.append(np.diff(measCN0span[i]))
# adjust the length of time span to fit the CN0 diff
UTCspan.remove(UTCspan[0])
# create the plots for each signaltype
plotCN0diff.plotCN0diff(SVIDlist, STlist, UTCspan, measCN0diff, dateString, verbose)
# calculating the mean elevation for each signal type
meanElev = []
for i in SVIDlistElev:
ELEVATIONVisibility = extractELEVATION(i, dataVisibility, verbose)
mean = np.mean(ELEVATIONVisibility)
meanElev.append(mean)
# determine the maximum difference of CN0
for i in range(len(measCN0diff)):
gnssSystCN0, gnssSystShortCN0, gnssPRNCN0 = mSSN.svPRN(SVIDlist[i])
print('Satellite %d signaltype %s has %s maximum var. at the elev. of %s ' % (gnssPRNCN0, mSSN.GNSSSignals[STlist[i]]['name'], np.nanmin(measCN0diff[i]), meanElev[i]))
sys.exit(E_SUCCESS)
def plotLockTime(SVID, signalTypes, dataMeasSVID, lliIndices, lliTOWs, verbose):
"""
plotLockTime creates a plot of the locktime and indicates loss of locks
Parameters:
SVID: satellite ID
signalTypes: signal types to represent
dataMeasSVID: data from MeasEpoch_2 but for one SVs
indexLossOfLock: indices for the occurance of loss of lock
verbose: display interactive plot
"""
# print('\nplotLockTime' + '-' * 25)
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
# for i, signalType in enumerate(signalTypes):
# print('PLT: signalType[%d] = %s' % (i, signalType))
# print('PLT: TOW = %s (%d)' % (dataMeasSVID[i]['MEAS_TOW'], len(dataMeasSVID[i]['MEAS_TOW'])))
# print('PLT: lockTimes = %s (%d)\n' % (dataMeasSVID[i]['MEAS_LOCKTIME'], len(dataMeasSVID[i]['MEAS_LOCKTIME'])))
# print("PLT: indexLossOfLock[%d] = %s (Nr = %d)" % (i, lliIndices[i], len(lliIndices[i])))
# # myData2 = dataMeasSVID[i][lliIndices[i]]
# # print("PLT: myData2 = %s (len = %d)" % (myData2['MEAS_TOW'], len(myData2['MEAS_TOW'])))
# # print("PLT: idemand = %s (len = %d)\n" % (dataMeasSVID[i][lliIndices[i]]['MEAS_TOW'], len(dataMeasSVID[i][)lliIndices[i]]['MEAS_TOW']))
# create the plot window
# plt.style.use('BEGPIOS')
plt.style.use('ggplot')
plt.figure(1)
subPlot = plt.subplot(1, 1, 1)
# titles and axis-labels
dateString = gpstime.UTCFromWT(float(dataMeasSVID[0]['MEAS_WNC'][0]), float(dataMeasSVID[0]['MEAS_TOW'][0])).strftime("%d/%m/%Y")
plt.title('Lock Times for %s PRN %d (%d)' % (gnssSyst, gnssPRN, SVID)) # , fontsize='18'
plt.ylabel('Lock Time [s]')
plt.xlabel('Time [hh:mm] (' + dateString + ')')
for index, signalType in enumerate(signalTypes):
# lockTime = dataMeasSVID[index]['MEAS_LOCKTIME']
# print("index = %d lockTime.size = %d" % (index, len(lockTime)))
sigTypeColor = mPlt.getSignalTypeColor(signalType)
utc = []
for count in range(0, len(dataMeasSVID[index])):
utc.append(gpstime.UTCFromWT(float(dataMeasSVID[index]['MEAS_WNC'][count]), float(dataMeasSVID[index]['MEAS_TOW'][count])))
plt.plot(utc, dataMeasSVID[index]['MEAS_LOCKTIME'], color=sigTypeColor, linestyle='', markersize=0.75, marker='.')
# add a marker at the LLI
utc2 = []
for count2 in range(0, len(dataMeasSVID[index][lliIndices[index]])):
utc2.append(gpstime.UTCFromWT(float(dataMeasSVID[index][lliIndices[index]]['MEAS_WNC'][count2]), float(dataMeasSVID[index][lliIndices[index]]['MEAS_TOW'][count2])))
plt.plot(utc2, dataMeasSVID[index][lliIndices[index]]['MEAS_LOCKTIME'], color=sigTypeColor, linestyle='', markersize=7, markerfacecolor=sigTypeColor, marker=mPlt.mFilledMarkers[signalType % len(mPlt.mFilledMarkers)])
# annotate the plot
annotateTxt = mSSN.GNSSSignals[signalType]['name'] + str(': %d LLI' % len(lliIndices[index]))
subPlot.text(0.02, 0.95 - index * 0.0375, annotateTxt, verticalalignment='bottom', horizontalalignment='left', transform=subPlot.transAxes, color=sigTypeColor, fontsize=12)
# make x-axis a hh:mm:ss
ax = plt.gca()
xfmt = md.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
# adjust range for Y axis
axes = plt.gca()
axes.set_ylim(mPlt.adjustYAxisLimits(axes))
axes.set_xlim(mPlt.adjustXAxisLimits(axes))
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Frederic Snyers ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# mPlt.annotateText(r'$\copyright$ Alain Muls ([email protected])', subPlot, 0, -0.12, 'left', fontsize='x-small')
# mPlt.annotateText(r'$\copyright$ Frederic Snyers ([email protected])', subPlot, 1, -0.12, 'right', fontsize='x-small')
fig = plt.gcf()
# fig.set_size_inches(12*2.5, 9*2.5)
fig.savefig('%s-%s%d-locktime.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi)
if verbose:
plt.show(block=False) # block=False)
def findSidePeaks(SVID, signalTypes, dataMeasSVID, verbose):
'''
findSidePeaks finds the side peak correlation by differencing the code measurements on E1A and E6
Parameters:
SVID: identifies the satellite
signalTypes: the signals observed for that satellite (ordered list!! so 16 (L1A) before 18 (E6A))
dataMeasSVID: the data observed for that satellite
Returns:
iTOW: the TOWs for which both signals are present
dPR: the difference between the E1A and E6A Pseudo Range measurements
sidePeakIndex: the index at which a jump in dPR is detected (exluding the first value)
jumpDPR: the difference between dPR at detected side peak and its previous value (thus jump in dPR detected)
jumpDPRNear97Indices: indices in jumpDPR identifying the elements nearest to 9.7 integer multiple
'''
print('-' * 50)
if verbose:
sys.stdout.write(' Looking for Side Peaks\n')
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
# define limits for delta PR for detecting 'possible' and 'probable' sidePeak indicators
dPRlimit = 4.0 # meter
jumpMargin = 0.05 # 5 percent margin on multiple of 9.7 m
# deterimine the intersection and get the indices on both signal types for that intersection
indexTOWIntersect = []
iMeas = [] # intersection on TOW between the signaltypes for this SVID
# get the TOW that are present for bith SignalTypes
iTOW = np.intersect1d(dataMeasSVID[0]['MEAS_TOW'], dataMeasSVID[1]['MEAS_TOW'])
# print('iTOW %s ()' % (iTOW, len(iTOW)))
for index, dataSVIDMeas in enumerate(dataMeasSVID):
mask = np.in1d(dataSVIDMeas['MEAS_TOW'], iTOW)
indexTOWIntersect.append(np.argwhere(mask).flatten())
# create intersection views on data
iMeas.append(dataSVIDMeas[indexTOWIntersect[index]])
print('indexTOWIntersect[%d] = %s (#%d)' % (index, indexTOWIntersect[index], len(indexTOWIntersect[index])))
print('iMeas[%d][MEAS_TOW] = %s (#%d)\n' % (index, iMeas[index]['MEAS_TOW'], len(iMeas[index]['MEAS_CODE'])))
# # save for debugging purposes
# fileName = 'meas%s%d-st%d.csv' % (gnssSystShort, gnssPRN, signalTypes[index])
# np.savetxt(fileName, iMeas[index], fmt=mSSN.colFmtMeasEpoch)
# determine difference between observed CODE measurements at each intersecting TOW
dPR = iMeas[0]['MEAS_CODE'] - iMeas[1]['MEAS_CODE']
print('dPR = %s (#%d)' % (dPR, len(dPR)))
# look for side-peak indicators when dPR > dPRlimit
sidePeakIndex = np.where(np.fabs(np.ediff1d(np.concatenate((np.array([0]), dPR)))) > dPRlimit)[0]
print('sidePeakIndex = %s (#%d)\n' % (sidePeakIndex, len(sidePeakIndex)))
sidePeakIndex = []
sidePeakIndex = np.where(np.fabs(np.ediff1d(dPR[0:])) > dPRlimit)[0] + 1 # add 1 since we ignore the first value for ediff1d
print('sidePeakIndex = %s (#%d)\n' % (sidePeakIndex, len(sidePeakIndex)))
print(np.ediff1d(np.concatenate((np.array([0]), dPR))))
print(np.ediff1d(dPR[0:]))
print('sidePeakIndex = %s (#%d)\n' % (sidePeakIndex, len(sidePeakIndex)))
# create array for the TOW/dPR based on the index indicators for sidePeaks
sidePeakTOWs = dataMeasSVID[0][indexTOWIntersect[0]]['MEAS_TOW'][sidePeakIndex]
sidePeakDPR = dPR[sidePeakIndex]
print('sidePeakTOWs = %s (#%d)' % (sidePeakTOWs, len(sidePeakTOWs)))
print('sidePeakDPR = %s (#%d)\n' % (sidePeakDPR, len(sidePeakDPR)))
# calculate the difference between the detected sidePeak dPR and the previous observed value of dPR
prevIndex = sidePeakIndex - 1
jumpDPR = dPR[sidePeakIndex] - dPR[prevIndex]
print('jumpDPR = %s (#%d)' % (jumpDPR, len(jumpDPR)))
print('jumpDPR = %s (#%d)' % ((abs(jumpDPR) / 9.7), len(jumpDPR)))
print('jumpDPR = %s (#%d)' % (np.rint((abs(jumpDPR) / 9.7)), len(jumpDPR)))
jumpDPRNear97 = abs((abs(jumpDPR) / 9.7) - np.rint((abs(jumpDPR) / 9.7)))
jumpDPRNear97Indices = np.where(jumpDPRNear97 < jumpMargin)[0]
print('jumpDPRNear97 = %s (#%d)' % (jumpDPRNear97Indices, len(jumpDPRNear97Indices)))
jumpDPRNear1465 = abs((abs(jumpDPR) / 14.65) - np.rint((abs(jumpDPR) / 14.65)))
jumpDPRNear1465Indices = np.where(jumpDPRNear1465 < jumpMargin)[0]
print('jumpDPRNear1465 = %s (#%d)' % (jumpDPRNear1465Indices, len(jumpDPRNear1465Indices)))
print('-' * 50)
return iTOW, dPR, sidePeakTOWs, sidePeakDPR, jumpDPR, jumpDPRNear97Indices, jumpDPRNear1465Indices
def plotCN0diff(listSVIDs, listST, spanUTC, CN0measdiff, dateStr, verbose=False):
'''
plotCN0 plots the CN0 values for SVs per signalType observed
Parameters:
listSVIDs is list of SVIDs we have data for
listST is list of signaltypes
spanUTC is the UTC representation of spanElevation
CN0measdiff contains observed CN0 variation for all SVs and all signalTypes
dateStr is the respective day of observations
'''
# get unique list of signaltypes to determine the number of plots we have to make
uniqSVs = list(set(listSVIDs))
for i, uniqSVi in enumerate(uniqSVs):
plt.figure(i)
ax = plt.gca()
# create label for signalType and plot its SN0 for this uniqSVi
stLabel = []
ax.set_color_cycle(['black', 'yellow', 'blue', 'pink'])
for j, SVj in enumerate(listSVIDs):
if SVj == uniqSVi:
stLabel.append(mSSN.GNSSSignals[listST[j]]['name'])
print('mSSN.GNSSSignals[listST[%d]][name] = %s' % (j, mSSN.GNSSSignals[listST[j]]['name']))
print('spanUTC = %s ==> %s' % (spanUTC[0], spanUTC[-1]))
print(len(spanUTC), len(CN0measdiff[j]))
plt.plot(spanUTC, CN0measdiff[j], linestyle='-', linewidth=0.25, alpha=0.75, label=stLabel[-1])
ax.set_ylim(-4, 4)
# plot annotation
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVj)
textSVID = gnssSystShort + str(gnssPRN)
print('j = %d - SV = %s, uniqSVi = %s\n' % (i, textSVID, uniqSVi))
plt.title('Satellite: %s' % textSVID)
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0 variation')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Andrei Alexandru ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.4,
box.width, box.height * 0.6])
box = ax.get_position()
plt.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(stLabel), fontsize='xx-small')
llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
plt.tight_layout(rect=(0, 0, 1, 1))
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
fig = plt.gcf()
fig.savefig('%s-%s%d-CN0.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi)
if i != len(uniqSVs)-1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# close the figure
plt.close()
def skyview(PRNs, azimuths, elevations, dateStr, hours, hoursAzims, hoursElevs):
'''
skyview creates the skyview plot for observed satellites
Parameters:
PRNs is list of PRNs of observed satellites
azimuths is aziumuts with which these satellites were observed (in degrees)
elevations is elevation angle with which these satellites were observed (in degrees)
dateStr contains the current date
hours contain the TOWs that correspond to a multiple of hours
hoursAzims, hoursElevs contain the corersponding azimuth/elevation (in degrees)
Returns:
fig is reference to created plot
'''
plt.style.use('BEGPIOS')
# rc('grid', color='#999999', linewidth=1, linestyle='-', alpha=[0].6)
rc('xtick', labelsize='x-small')
rc('ytick', labelsize='x-small')
# force square figure and square axes looks better for polar, IMO
width, height = rcParams['figure.figsize']
size = min(width, height)
# make a square figure
fig = figure(figsize=(size, size))
# set the axis (0 azimuth is North direction, azimuth indirect angle)
ax = fig.add_axes([0.10, 0.15, 0.8, 0.8], projection=u'polar') # , axisbg='#CCCCCC', alpha=0.6)
ax.set_theta_zero_location('N')
ax.set_theta_direction(-1)
# Define the xticks
ax.set_xticks(np.linspace(0, 2 * np.pi, 13))
xLabel = ['N', '30', '60', 'E', '120', '150', 'S', '210', '240', 'W', '300', '330']
ax.set_xticklabels(xLabel)
# Define the yticks
ax.set_yticks(np.linspace(0, 90, 7))
yLabel = ['', '75', '60', '45', '30', '15', '']
ax.set_yticklabels(yLabel)
# annotate for copyright and put the currecnt date
text(-0.1, 1, dateStr, horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, fontsize='large')
text(1.1, 1, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# draw a grid
grid(True)
# treat the sky track of the satellites
# for (PRN, E, Az) in sat_positions:
# ax.annotate(str(PRN),
# xy=(radians(Az), 90-E), # theta, radius
# bbox=dict(boxstyle="round", fc='green', alpha=0.5),
# horizontalalignment='center',
# verticalalignment='center')
# plot the skytracks for each PRN
colors = iter(plt.cm.rainbow(np.linspace(0, 1, len(PRNs))))
satLabel = []
for i, prn in enumerate(PRNs):
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(prn)
satLabel.append('%s%d (%d)' % (gnssSystShort, gnssPRN, prn))
azims = [radians(az) for az in azimuths[i]]
elevs = [(90 - el) for el in elevations[i]]
# print('PRN = %d' % prn)
# print('elev = %s' % elevs)
# print('azim = %s' % azims)
# ax.plot(azims, elevs, color=next(colors), linewidth=0.35, alpha=0.85, label=satLabel[-1])
ax.plot(azims, elevs, color=next(colors), marker='.', markersize=1, linestyle='None', alpha=0.85, label=satLabel[-1])
# annotate with the hour labels
hrAzims = [radians(az + 2) for az in hoursAzims[i]]
hrElevs = [(90 - el) for el in hoursElevs[i]]
for j, hr in enumerate(hours[i]):
hrAz = hrAzims[j]
hrEl = hrElevs[j]
# print('hr = %s' % hr)
hr = int((np.fmod(hr, gpstime.secsInDay)) / 3600.)
# print('hr = %s' % hr)
# print('hrAz = %d' % hrAz)
# print('hrEl = %d' % hrEl)
text(hrAz, hrEl, hr, fontsize='x-small')
# adjust the legend location
mLeg = ax.legend(bbox_to_anchor=(0.5, -0.15), loc='lower center', ncol=np.size(satLabel), fontsize='small', markerscale=4)
for legobj in mLeg.legendHandles:
legobj.set_linewidth(5.0)
# needed for having radial axis span from 0 => 90 degrees and y-labels along north axis
ax.set_rmax(90)
ax.set_rmin(0)
ax.set_rlabel_position(0)
return fig
def plotCN0diff(listSVIDs,
listST,
spanUTC,
CN0measdiff,
dateStr,
verbose=False):
'''
plotCN0 plots the CN0 values for SVs per signalType observed
Parameters:
listSVIDs is list of SVIDs we have data for
listST is list of signaltypes
spanUTC is the UTC representation of spanElevation
CN0measdiff contains observed CN0 variation for all SVs and all signalTypes
dateStr is the respective day of observations
'''
# get unique list of signaltypes to determine the number of plots we have to make
uniqSVs = list(set(listSVIDs))
for i, uniqSVi in enumerate(uniqSVs):
plt.figure(i)
ax = plt.gca()
# create label for signalType and plot its SN0 for this uniqSVi
stLabel = []
ax.set_color_cycle(['black', 'yellow', 'blue', 'pink'])
for j, SVj in enumerate(listSVIDs):
if SVj == uniqSVi:
stLabel.append(mSSN.GNSSSignals[listST[j]]['name'])
print('mSSN.GNSSSignals[listST[%d]][name] = %s' %
(j, mSSN.GNSSSignals[listST[j]]['name']))
print('spanUTC = %s ==> %s' % (spanUTC[0], spanUTC[-1]))
print(len(spanUTC), len(CN0measdiff[j]))
plt.plot(spanUTC,
CN0measdiff[j],
linestyle='-',
linewidth=0.25,
alpha=0.75,
label=stLabel[-1])
ax.set_ylim(-4, 4)
# plot annotation
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVj)
textSVID = gnssSystShort + str(gnssPRN)
print('j = %d - SV = %s, uniqSVi = %s\n' %
(i, textSVID, uniqSVi))
plt.title('Satellite: %s' % textSVID)
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0 variation')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0,
-0.125,
r'$\copyright$ Alain Muls ([email protected])',
horizontalalignment='left',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
plt.text(1,
-0.125,
r'$\copyright$ Andrei Alexandru ([email protected])',
horizontalalignment='right',
verticalalignment='bottom',
transform=ax.transAxes,
alpha=0.5,
fontsize='x-small')
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
ax.set_position(
[box.x0, box.y0 + box.height * 0.4, box.width, box.height * 0.6])
box = ax.get_position()
plt.legend(bbox_to_anchor=(box.x0 + box.width * 0.2, -0.15,
box.width * 0.6, 0.15),
loc='lower center',
ncol=np.size(stLabel),
fontsize='xx-small')
llines = plt.gca().get_legend().get_lines(
) # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
plt.tight_layout(rect=(0, 0, 1, 1))
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax = plt.subplot(111)
ax.set_position(
[box.x0, box.y0 + box.height * 0.1, box.width, box.height * 0.9])
fig = plt.gcf()
fig.savefig('%s-%s%d-CN0.png' % (gnssSyst, gnssSystShort, gnssPRN),
dpi=fig.dpi)
if i != len(uniqSVs) - 1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# close the figure
plt.close()
def plotCN0(listSVIDs, listST, spanTOW, spanUTC, CN0meas, dateStr, verbose=False):
'''
plotCN0 plots the CN0 values for SVs per signalType observed
Parameters:
listSVIDs is list of SVIDs we have data for
listST is list of signaltypes
spanTOW is the full observation time span
spanUTC is the UTC representation of spanTOW
CN0meas contains observed CN0 for all SVs and all signalTypes
'''
# plt.style.use('ggplot')
plt.style.use('BEGPIOS')
# first plot all SVs per signalType
# get unique list of signaltypes to determine the number of plots we have to make
uniqSTs = list(set(listST))
# print('uniqSTs = %s' % uniqSTs)
# loop over the signalTypes
for i, uniqSTi in enumerate(uniqSTs):
plt.figure(i)
ax = plt.gca()
# create label for identify SV and plot its CN0 value for this signalType
satLabel = []
colors = iter(cm.rainbow(np.linspace(0, 1, len(listSVIDs))))
for j, STj in enumerate(listST):
if STj == uniqSTi:
satLabel.append(mSSN.svPRN(listSVIDs[j])[1] + str(mSSN.svPRN(listSVIDs[j])[2]))
plt.plot(spanUTC, CN0meas[j], linestyle='-', color=next(colors), linewidth=0.25, alpha=0.75, label=satLabel[-1])
print('i = %d len = %d' % (i, np.size(uniqSTs)))
# plot annotation
plt.title('Signaltype: %s' % mSSN.GNSSSignals[uniqSTi]['name'], fontsize='x-large')
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Frederic Snyers ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# add the legend
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
print('box.x0 = %f' % box.x0)
print('box.y0 = %f' % box.y0)
print('box.width = %f' % box.width)
print('box.height = %f' % box.height)
# ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.3,
box.width, box.height * 0.7])
box = ax.get_position()
print('after\nbox.x0 = %f' % box.x0)
print('box.y0 = %f' % box.y0)
print('box.width = %f' % box.width)
print('box.height = %f' % box.height)
plt.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(satLabel), fontsize='xx-small')
llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
# ggplot2.rstyle(ax)
fig = plt.gcf()
if verbose:
print('\nfigname = %s -- %s' % (STj, mSSN.GNSSSignals[uniqSTi]['name']))
fig.savefig('%s-CN0.png' % (mSSN.GNSSSignals[uniqSTi]['name']), dpi=fig.dpi)
if i != len(uniqSTs)-1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# sys.exit(0)
# second plot all signalTypes per SVs
# find the SV identifiers ans make them unique
uniqSVs = list(set(listSVIDs))
print('uniqSVs = %s' % uniqSVs)
figNr = len(uniqSTs) # nr of figures already used
for i, uniqSVi in enumerate(uniqSVs):
plt.figure(i + figNr)
ax = plt.gca()
# create label for signalType and plot its SN0 for this uniqSVi
stLabel = []
colors = iter(cm.rainbow(np.linspace(0, 1, len(listST))))
for j, SVj in enumerate(listSVIDs):
if SVj == uniqSVi:
stLabel.append(mSSN.GNSSSignals[listST[j]]['name'])
print('mSSN.GNSSSignals[listST[%d]][name] = %s' % (j, mSSN.GNSSSignals[listST[j]]['name']))
print('spanUTC = %s ==> %s' % (spanUTC[0], spanUTC[-1]))
plt.plot(spanUTC, CN0meas[j],linestyle='-', color=next(colors), linewidth=0.25, alpha=0.75, label=stLabel[-1])
# plot annotation
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVj)
textSVID = gnssSystShort + str(gnssPRN)
print('j = %d - SV = %s, uniqSVi = %s\n' % (i, textSVID, uniqSVi))
plt.title('Satellite: %s' % textSVID)
plt.xlabel('Time of ' + dateStr)
plt.ylabel('C/N0')
# adjust the X-axis to represent readable time
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))
plt.xlim(spanUTC[0], spanUTC[-1])
# annotate for copyright
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Frederic Snyers ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
# add the legend
# Shrink current axis's height by x% on the bottom
box = ax.get_position()
print('box.x0 = %f' % box.x0)
print('box.y0 = %f' % box.y0)
print('box.width = %f' % box.width)
print('box.height = %f' % box.height)
# ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.4,
box.width, box.height * 0.6])
box = ax.get_position()
print('after\nbox.x0 = %f' % box.x0)
print('box.y0 = %f' % box.y0)
print('box.width = %f' % box.width)
print('box.height = %f' % box.height)
plt.legend(bbox_to_anchor=(box.x0 + box.width*0.2, -0.15, box.width*0.6, 0.15), loc='lower center', ncol=np.size(stLabel), fontsize='xx-small')
llines = plt.gca().get_legend().get_lines() # all the lines.Line2D instance in the legend
plt.setp(llines, linewidth=4) # the legend linewidth
# plt.legend(bbox_to_anchor=(0., 1.052, 1., .052), loc='lower left', ncol=np.size(stLabel), mode="expand", borderaxespad=0., fontsize=9)
# Shrink current axis's height by 10% on the bottom
box = ax.get_position()
ax = plt.subplot(111)
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
fig = plt.gcf()
fig.savefig('%s-%s%d-CN0.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi)
if i != len(uniqSVs)-1:
if verbose:
plt.show(block=False)
else:
if verbose:
plt.show()
# close the figure
plt.close()
def plotSidePeaks(SVID, signalTypesSVID, WkNr, iTOW, deltaPR, sidePeaksTOW, sidePeakDPR, jumpDPRNear97Indices, jumpDPRNear1465Indices, lliTOWs, strDate, verbose):
"""
plotSidePeaks plots the difference between the code measurements on L1A (reference) and E6A and indicates where a possible side peak is noticed
Parameters:
SVID: SSN SVID of satellite
signalTypesSVID; the signal types for this SVID
WkNt: week number
iTOW: common TOWs where both code measurements are available
deltaPR: difference between PR on L1A and E61
sidePeaksTOW: list of TOWs which could be indicators of SidePeaks
sidePeakDPR: delta PR at these TOWs
jumpDPRNear97Indices: indices in sidePeaksTOW, sidePeakDPR which are closest to integer multipe of 9.7m
jumpDPRNear1465Indices: indices in sidePeaksTOW, sidePeakDPR which are closest to integer multipe of 14.65m
lliTOWs: TOW that indicate a loss of lock per signal type
strDate: observation date
verbose: ok
"""
print '-' * 50
# get info for GNSS satellite
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
SVIDColor = mPlt.getSVIDColor(SVID)
# create the plot window
# plt.style.use('BEGPIOS')
plt.style.use('ggplot')
plt.figure(2)
subPlot = plt.subplot(1, 1, 1)
# titles and axis-labels
plt.title('Side Peak Indicator for %s PRN %d (%d)' % (gnssSyst, gnssPRN, SVID)) # , fontsize='18'
plt.ylabel(r'$\Delta$ PR (%s - %s)' % (mSSN.GNSSSignals[16]['name'], mSSN.GNSSSignals[18]['name']))
plt.xlabel('Time [hh:mm] (' + strDate + ')')
# plot the deltaPRs vs iTOW
print 'iTOW = %s (%d)' % (iTOW, len(iTOW))
print 'deltaPR = %s (%d)' % (deltaPR, len(deltaPR))
# plot the indicators for the sidepeaks after conversion to utc
utc2 = [] # used for all possible detections
utc3 = [] # used for those that are multiple of 9.7m
utc4 = [] # used for those that are multiple of 14.65m
for count in range(0, len(sidePeaksTOW)):
utc2.append(gpstime.UTCFromWT(float(WkNr), float(sidePeaksTOW[count])))
if count in jumpDPRNear97Indices:
utc3.append(utc2[-1])
if count in jumpDPRNear1465Indices:
utc4.append(utc2[-1])
plt.plot(utc2, sidePeakDPR, color='orange', linestyle='', markersize=7, marker='o', markeredgecolor='orange', markerfacecolor=None)
print 'utc2 = %s (#%d)' % (utc2, len(utc2))
print 'sidePeakDPR = %s (#%d)' % (sidePeakDPR, len(sidePeakDPR))
print 'jumpDPRNear97Indices = %s (#%d)' % (jumpDPRNear97Indices, len(jumpDPRNear97Indices))
print 'sidePeakDPR = %s (#%d)' % (sidePeakDPR[jumpDPRNear97Indices], len(sidePeakDPR[jumpDPRNear97Indices]))
print 'utc3 = %s (#%d)' % (utc3, len(utc3))
plt.plot(utc3, sidePeakDPR[jumpDPRNear97Indices], color='red', linestyle='', markersize=7, marker='o', markeredgecolor='red', markerfacecolor=None)
plt.plot(utc4, sidePeakDPR[jumpDPRNear1465Indices], color='blue', linestyle='', markersize=7, marker='o', markeredgecolor='blue', markerfacecolor=None)
# annotate to signal number of detections and number of integer multiple of 9.7m
annotateTxt = 'Side Peaks on E1A: %d' % len(utc3)
subPlot.text(0.95, 0.95, annotateTxt, verticalalignment='bottom', horizontalalignment='right', transform=subPlot.transAxes, color='red', fontsize=12)
# annotate to signal number of detections and number of integer multiple of 14.65m
annotateTxt = 'Side Peaks on E6A: %d' % len(utc4)
subPlot.text(0.95, 0.92, annotateTxt, verticalalignment='bottom', horizontalalignment='right', transform=subPlot.transAxes, color='blue', fontsize=12)
annotateTxt = 'Other: %d' % (len(utc2) - len(utc3) - len(utc4))
subPlot.text(0.95, 0.89, annotateTxt, verticalalignment='bottom', horizontalalignment='right', transform=subPlot.transAxes, color='orange', fontsize=12)
# transform WkNr, TOW to UTC time
utc = []
for i in range(0, len(iTOW)):
utc.append(gpstime.UTCFromWT(float(WkNr), float(iTOW[i])))
# plot the deltaPR vs UTC time
plt.plot(utc, deltaPR, color=SVIDColor, linestyle='-', linewidth=0.5, marker='.', markersize=3.5) # , linestyle='', marker='.', markersize=1)
for i, lliTOWsST in enumerate(lliTOWs):
print 'lliTOWs[%d] = %s' % (i, lliTOWsST)
utc2 = []
sigTypeColor = mPlt.getSignalTypeColor(signalTypesSVID[i])
# annotate the plot
annotateTxt = mSSN.GNSSSignals[signalTypesSVID[i]]['name'] + ' LLI'
subPlot.text(0.02, 0.95 - i * 0.0375, annotateTxt, verticalalignment='bottom', horizontalalignment='left', transform=subPlot.transAxes, color=sigTypeColor, fontsize=12)
# drax vertical line for the LLI indicators
for j, lliTOWST in enumerate(lliTOWsST):
utc2.append(gpstime.UTCFromWT(float(WkNr), lliTOWST))
# print 'lliTOWs[%d] = %s utc = %s' % (j, lliTOWST, utc2[j])
# draw a vertical line in the color of the signal type
plt.axvline(utc2[j], color=sigTypeColor)
print 'sidePeaksTOW = %s (%d)' % (sidePeaksTOW, len(sidePeaksTOW))
# print 'utc2 = %s (%d)' % (utc2, len(utc2))
# plt.plot(sidePeaksTOW, 0.5, color='red', linestyle='', markersize=7, marker=mPlt.mFilledMarkers[SVID % len(mPlt.mFilledMarkers)])
# adjust the axes to represent hh:mm:ss
ax = plt.gca()
xfmt = md.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
# adjust range for Y axis
axes = plt.gca()
axes.set_ylim(mPlt.adjustYAxisLimits(axes))
axes.set_xlim(mPlt.adjustXAxisLimits(axes))
plt.text(0, -0.125, r'$\copyright$ Alain Muls ([email protected])', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
plt.text(1, -0.125, r'$\copyright$ Frederic Snyers ([email protected])', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes, alpha=0.5, fontsize='x-small')
fig = plt.gcf()
# fig.set_size_inches(12*2.5, 9*2.5)
fig.savefig('%s-%s%d-sidepeak.png' % (gnssSyst, gnssSystShort, gnssPRN), dpi=fig.dpi)
if verbose:
plt.show()
# close the figure
plt.close()
print '-' * 50
