def plotSatelliteGlobalMap(rx,
sv,
obstimes,
color='r',
lw=3,
newfigure=False,
center=[-130., 50],
width=10000000,
height=7000000):
"""
plotSAtelliteGlobalMap renders a global map with a satellite view projection,
and put on the map a projection of a stallite trajectory in lat-lon format.
There is option to put more satellites as a list of satellites.
Size of the global map and the center of projection are optional parameters.
Center is in the format [lon, lat], width and height are in meters.
"""
#Add optional marks on plot
all_sky_location = [-147.43, 65.12]
if newfigure:
plt.figure()
#Create a Basemap object:
m = Basemap(width=width,
height=height,
projection='aeqd',
resolution='c',
lat_0=center[1],
lon_0=center[0])
#Plot parallels and meridians
parallels = [40, 50, 60, 70]
m.drawparallels(parallels, labels=[False, True, True, True], linewidth=2)
meridians = [-50, -90, -120, -150., -180., 150.]
m.drawmeridians(meridians, labels=[True, True, False, True], linewidth=2)
m.bluemarble()
if isinstance(sv, int):
sv_llt = pyGps.getSatellitePosition(rx,
sv,
obstimes,
navfn,
cs='wsg84')
asi_x, asi_y = m(all_sky_location[0], all_sky_location[1])
sat_x, sat_y = m(sv_llt[1], sv_llt[0])
m.plot(sat_x, sat_y, color, linewidth=lw)
m.scatter(asi_x, asi_y, marker='*', color='m',
s=25) # plot a blue dot there
else:
asi_x, asi_y = m(all_sky_location[0], all_sky_location[1])
m.scatter(asi_x, asi_y, marker='*', color='m',
s=25) # plot a blue dot there
for sat in sv:
sv_llt = pyGps.getSatellitePosition(rx,
sat,
obstimes,
navfn,
cs='wsg84')
sat_x, sat_y = m(sv_llt[1], sv_llt[0])
m.plot(sat_x, sat_y, color, linewidth=lw)
plt.show()
def tec():
aer = pyGps.getSatellitePosition(np.asarray(rx_xyz),
sv,
obstimes,
navfname,
cs='aer')
L1 = np.array(data['L1', sv, :, 'data'])
L2 = np.array(data['L2', sv, :, 'data'])
P1 = np.array(data['C1', sv, :, 'data'])
P2 = np.array(data['P2', sv, :, 'data'])
#Phase corrected TEC
sTECp = pyGps.getPhaseCorrTEC(L1, L2, P1, P2)
vTECp = pyGps.getVerticalTEC(sTECp, aer[1], 130)
tec_norm = vTECp #- vTECp[np.isfinite(vTECp[0:1000])].min()
plotGps.plotTEC(obstimes,
tec_norm,
xlabel='UT',
ylabel='vTEC [TECU]',
ylim=[0, 17],
ytick=[0, 5, 10, 14, 15, 16],
color='--m',
xlim=[
datetime.datetime(2015, 10, 7, 6, 10, 0),
datetime.datetime(2015, 10, 7, 6, 40, 0)
])
def tec_keogram_intensity5():
N_roti = 100
aer = pyGps.getSatellitePosition(np.asarray(rx_xyz),
sv,
obstimes,
navfname,
cs='aer')
L1 = np.array(data['L1', sv, :, 'data'])
L2 = np.array(data['L2', sv, :, 'data'])
P1 = np.array(data['C1', sv, :, 'data'])
P2 = np.array(data['P2', sv, :, 'data'])
l2_lli = np.array(data['L2', sv, :, 'lli'])
#Phase corrected TEC
sTECp = pyGps.getPhaseCorrTEC(L1, L2, P1, P2)
vTECp = pyGps.getVerticalTEC(sTECp, aer[1], 130)
tec_norm = vTECp - vTECp[np.isfinite(vTECp[0:1000])].min()
# Rate of TEC Index
roti = pyGps.getROTI(vTECp, N_roti)
roti_t = obstimes[0:-N_roti]
#ASI Intensity data
# Piercing point for all-sky data
aer = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
ipp_alt,
navfname,
cs='aer')
#ipp = pyGps.getIonosphericPiercingPoints(rx_xyz, sv, obstimes, ipp_alt, navfname, cs='wsg84')
#Asi intensity:
t5, intensity5 = asi.getAllSkyIntensityAER(asi_folder3,
aer[0],
aer[1],
ipp_alt,
timelim,
'558',
obstimes=obstimes)
t6, intensity6 = asi.getAllSkyIntensityAER(asi_folder3,
aer[0],
aer[1],
ipp_alt,
timelim,
'630',
obstimes=obstimes)
t4, intensity4 = asi.getAllSkyIntensityAER(asi_folder3,
aer[0],
aer[1],
ipp_alt,
timelim,
'428',
obstimes=obstimes)
# Asi Keogram
ipp_aer = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
ipp_alt,
navfname,
cs='aer')
t, el, i, el_out4 = asi.getASIKeogramIPP(asi_folder3,
ipp_aer[0],
ipp_alt,
timelim,
'558',
obstimes=obstimes,
elevation=aer[1])
# Magnetometer
mag_folder = '/home/smrak/Documents/TheMahali/magnetometer/poker_2015_10_07.csv'
mag = magnetometer.readMag(mag_folder, '2015-10-07')
b_t = mag[0][5000:]
mag_xyz = magnetometer.magHDZ2XYZ(mag, angle=True)
plotting.plot5subplot(t,
t5,
obstimes,
roti_t,
i / 1E3,
np.array(intensity5) / 1E3,
tec_norm,
roti,
el1=el,
ylabel1='Elevation [deg]',
ylabel3='vTEC [TECU]',
ylabel2='Intensity [kR]',
ylabel4='ROTI[TECU/10s]',
xlabel='UT',
ylim1=[45, 85],
color5='b',
ytick1=[45, 55, 65, 75, 85],
pcolorbar=True,
cbartick=[0, 2, 4, 6, 8],
cbartitle='Intensity [kR]',
t31=t6,
t32=t4,
y31=np.array(intensity6) / 1E3,
y32=np.array(intensity4) / 1E3,
color2='g',
color3='r',
color4='b',
legend1=True,
label2='558nm',
label3='630nm',
label4='428nm',
lli1=l2_lli,
ylim2=[0, 3.5],
ylim4=[0, 3.5],
ylim3=[0, 18],
ipp_elevation=aer[1],
ytick2=[0, 1, 2, 3],
ytick3=[0, 4, 8, 12, 16],
ytick4=[0, 0.5, 1, 1.5, 2, 2.5, 3],
Bt=b_t,
Bx=mag_xyz[0][5000:] / 1000,
ylabel5='Bx [uT]',
cbx='b',
ylim5=[12.2, 13],
ytick5=[12.2, 12.4, 12.6, 12.8],
xlim=[
datetime.datetime(2015, 10, 7, 6, 10, 0),
datetime.datetime(2015, 10, 7, 6, 40, 0)
])
def tec_keogram_intensity3():
aer = pyGps.getSatellitePosition(np.asarray(rx_xyz),
sv,
obstimes,
navfname,
cs='aer')
L1 = np.array(data['L1', sv, :, 'data'])
L2 = np.array(data['L2', sv, :, 'data'])
P1 = np.array(data['C1', sv, :, 'data'])
P2 = np.array(data['P2', sv, :, 'data'])
l2_lli = np.array(data['L2', sv, :, 'lli'])
#Phase corrected TEC
sTECp = pyGps.getPhaseCorrTEC(L1, L2, P1, P2)
vTECp = pyGps.getVerticalTEC(sTECp, aer[1], 130)
tec_norm = vTECp - vTECp[np.isfinite(vTECp[0:1000])].min()
# Rate of TEC Index
roti = pyGps.getROTI(vTECp, 10)
roti_t = obstimes[0:-10]
#ASI Intensity data
# Piercing point for all-sky data
aer = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
ipp_alt,
navfname,
cs='aer')
ipp = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
ipp_alt,
navfname,
cs='wsg84')
#Asi intensity:
t5, intensity5 = asi.getAllSkyIntensityAER(asi_folder3,
aer[0],
aer[1],
ipp_alt,
timelim,
'558',
obstimes=obstimes)
t5a, intensity5a = asi.getAllSkyIntensity(asi_folder3,
ipp[0],
ipp[1],
ipp_alt,
timelim,
'558',
obstimes=obstimes)
# Asi Keogram
ipp_aer = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
ipp_alt,
navfname,
cs='aer')
t, el, i, el_out4 = asi.getASIKeogramIPP(asi_folder3,
ipp_aer[0],
ipp_alt,
timelim,
'558',
obstimes=obstimes,
elevation=ipp[1])
plotting.plot4subplot(t,
obstimes,
t5,
roti_t,
i / 1E3,
tec_norm,
np.array(intensity5) / 1E3,
roti,
el1=el,
ylabel1='Elevation [deg]',
ylabel2='vTEC [TECU]',
ylabel3='Intensity [kR]',
ylabel4='ROTI[TECU/10s]',
xlabel='UT',
ylim1=[45, 85],
color5='b',
title1='Rx8 - PRN23, Poker Flat 10/07/2015',
ytick1=[45, 55, 65, 75, 85],
pcolorbar=True,
cbartick=[0, 2, 4, 6, 8],
cbartitle='Intensity [kR]',
t31=t5a,
y31=np.array(intensity5a) / 1E3,
color2='g',
color3='r',
legend2=True,
label2='org',
label3='int',
label4='630nm',
lli1=l2_lli,
ylim3=[0, 3.5],
ylim4=[0, 3.5],
ylim2=[0, 18],
ipp_elevation=aer[1],
ytick3=[0, 1, 2, 3],
ytick2=[0, 4, 8, 12, 16],
ytick4=[0, 0.5, 1, 1.5, 2, 2.5, 3],
xlim=[
datetime.datetime(2015, 10, 7, 6, 10, 0),
datetime.datetime(2015, 10, 7, 6, 40, 0)
])
def tec_vs_asi():
aer = pyGps.getSatellitePosition(np.asarray(rx_xyz),
sv,
obstimes,
navfname,
cs='aer')
L1 = np.array(data['L1', sv, :, 'data'])
L2 = np.array(data['L2', sv, :, 'data'])
P1 = np.array(data['C1', sv, :, 'data'])
P2 = np.array(data['P2', sv, :, 'data'])
l2_lli = np.array(data['L2', sv, :, 'lli'])
#Phase corrected TEC
sTECp = pyGps.getPhaseCorrTEC(L1, L2, P1, P2)
vTECp = pyGps.getVerticalTEC(sTECp, aer[1], 130)
tec_norm = vTECp - vTECp[np.isfinite(vTECp[0:1000])].min()
#ASI Intensity data
# Piercing point for all-sky data
# aer = pyGps.getIonosphericPiercingPoints(rx_xyz, sv, obstimes, ipp_alt,
# navfname, cs='aer')
ipp = pyGps.getIonosphericPiercingPoints(rx_xyz,
sv,
obstimes,
130E3,
navfname,
cs='wsg84')
#Asi intensity:
t5, intensity5 = asi.getAllSkyIntensity(asi_folder3,
ipp[0],
ipp[1],
130,
timelim,
'558',
obstimes=obstimes)
t4, intensity4 = asi.getAllSkyIntensity(asi_folder3,
ipp[0],
ipp[1],
130,
timelim,
'428',
obstimes=obstimes)
t6, intensity6 = asi.getAllSkyIntensity(asi_folder3,
ipp[0],
ipp[1],
130,
timelim,
'630',
obstimes=obstimes)
#Plot 2 subplots
plotting.plot2subplot(obstimes,
t5,
tec_norm, (np.array(intensity5) / 1E3),
ylabel1='vTEC [TECU]',
ylabel2='Intensity [kR]',
xlabel='UT',
lli1=l2_lli,
ylim2=[0.2, 2.6],
lm='line',
color2='g',
lli2=l2_lli,
t21=t4,
y21=(np.array(intensity4) / 1E3),
t22=t6,
y22=(np.array(intensity6) / 1E3),
label4='630nm',
color4='r',
color3='b',
label2='558nm',
label3='428nm',
legend2=True,
xlim=[
datetime.datetime(2015, 10, 7, 6, 10, 0),
datetime.datetime(2015, 10, 7, 6, 40, 0)
])