def _update_map_views(self, sat_state):
""" Updates the map views of the visualizer with the given satellite data.
Parameters
----------
sat_state : SatState
The satellite data to use
"""
sat_pos = np.array([
sat_state.position.x, sat_state.position.y, sat_state.position.z
]) * 1000
# calculate where (latitude and longitude) nadir vector points
nadir_ll = None
nadir_los = los_to_earth(sat_pos, sat_state.nadir)
if nadir_los is not None:
nadir_ll = np.hstack(
pm.eci2geodetic(nadir_los[0], nadir_los[1], nadir_los[2],
sat_state.timestamp)[:2])
# calculate where (latitude and longitude) satellite body minus_z axis points
minus_z_ll = None
minus_z_normalized = self._sc_body_eci[2] / norm(self._sc_body_eci[2])
minus_z_los = los_to_earth(sat_pos, minus_z_normalized)
if minus_z_los is not None:
minus_z_ll = np.hstack(
pm.eci2geodetic(minus_z_los[0], minus_z_los[1], minus_z_los[2],
sat_state.timestamp)[:2])
self._update_flat_map_view(sat_state, nadir_ll, minus_z_ll)
def test_eci2geodetic(use_astropy):
pytest.importorskip("numpy")
if use_astropy:
pytest.importorskip("astropy")
eci = [-2981784, 5207055, 3161595]
utc = datetime(2019, 1, 4, 12)
lla = pm.eci2geodetic(*eci, utc, use_astropy=use_astropy)
rel = 0.0001 if use_astropy else 0.01
assert lla == approx([27.881, -163.722, 408850.65], rel=rel)
def plotnav(nav: xarray.DataArray):
if not isinstance(nav, xarray.DataArray):
return
ax = figure().gca()
if nav.name == 'S':
# WARNING: This conversion isn't verified.
lat, lon, alt = eci2geodetic(nav.loc[:, ['X', 'Y', 'Z']] * 1e3,
nav.t.to_pandas().tolist())
ax.plot(lon, lat)
ax.set_xlabel('glon [deg]')
ax.set_ylabel('glat [deg]')
print('lat lon', lat, lon)
print('altitude [km]', alt / 1e3)
def plotnav(nav: xarray.Dataset):
if nav is None:
return
if not 'X' in nav:
return
ax = figure().gca()
# WARNING: This conversion isn't verified.
lat, lon, alt = eci2geodetic(nav[['X', 'Y', 'Z']] * 1e3, nav.time)
ax.plot(lon, lat)
ax.set_xlabel('glon [deg]')
ax.set_ylabel('glat [deg]')
print('lat lon', lat, lon)
print('altitude [km]', alt / 1e3)
def test_eci():
tlla = (42, -82, 200)
teci = (-3.977913815668146e6, -2.582332196263046e6, 4.250818828152067e6)
t = datetime(2013, 1, 15, 12, 0, 5, tzinfo=UTC)
lla = asarray(pm.eci2geodetic(teci, t)).squeeze()
assert_allclose(lla, tlla, rtol=0.2)
assert_allclose(
pm.eci2ecef(teci, t).squeeze(),
[649012.04640917, -4697980.55129606, 4250818.82815207])
assert_allclose(
pm.ecef2eci([649012.04640917, -4697980.55129606, 4250818.82815207],
t).squeeze(), teci)
assert_allclose(
asarray(pm.eci2aer(teci, 42, -100, 0, t)).squeeze(),
[83.73050, -6.614478, 1.473510e6])
def test_eci_vallado():
t = '2013-01-15T12:00:05'
lla = pm.eci2geodetic(eci0, t, useastropy=False)
assert lla == approx(lla0, rel=0.2)
eci1 = pm.eci2ecef(eci0, t, useastropy=False)
assert eci1 == approx(
[649012.04640917, -4697980.55129606, 4250818.82815207], rel=0.001)
assert pm.ecef2eci(eci1, t, useastropy=False) == approx(eci0, rel=0.001)
aer1 = pm.eci2aer(eci0, 42, -100, 0, t, useastropy=False)
assert aer1 == approx([83.73050, -6.614478, 1.473510e6], rel=0.001)
assert pm.aer2eci(*aer1, 42, -100, 0, t,
useastropy=False) == approx(eci0, rel=0.001)
with pytest.raises(ValueError):
pm.aer2eci(aer1[0], aer1[1], -1, 42, -100, 0, t, useastropy=False)
def test_eci_astropy():
pytest.importorskip('astropy')
t = '2013-01-15T12:00:05'
lla = pm.eci2geodetic(eci0, t)
assert lla == approx(lla0, rel=0.2)
eci1 = pm.eci2ecef(eci0, t)
assert eci1 == approx(
[649012.04640917, -4697980.55129606, 4250818.82815207])
assert pm.ecef2eci(eci1, t) == approx(eci0)
aer1 = pm.eci2aer(eci0, 42, -100, 0, t)
assert aer1 == approx([83.73050, -6.614478, 1.473510e6])
assert pm.aer2eci(*aer1, 42, -100, 0, t) == approx(eci0)
with pytest.raises(ValueError):
pm.aer2eci(aer1[0], aer1[1], -1, 42, -100, 0, t)
def iridium_ncdf(fn,day,tlim,ellim, camlla):
assert len(ellim) == 2,'must specify elevation limits'
fn = Path(fn).expanduser()
day = forceutc(day)
#%% get all sats psuedo SV number
with Dataset(str(fn),'r') as f:
#psv_border = nonzero(diff(f['pseudo_sv_num'])!=0)[0] #didn't work because of consequtively reused psv #unique doesn't work because psv's can be recycled
psv_border = (diff(f['time'])<0).nonzero()[0] + 1 #note unequal number of samples per satellite, +1 for how diff() is defined
#%% iterate over psv, but remember different number of time samples for each sv.
# since we are only interested in one satellite at a time, why not just iterate one by one, throwing away uninteresting results
# qualified by crossing of FOV.
#%% consider only satellites above az,el limits for this location
#TODO assumes only one satellite meets elevation and time criteria
lind = [0,0] #init
for i in psv_border:
lind = [lind[1],i]
cind = arange(lind[0],lind[1]-1,dtype=int) # all times for this SV
#now handle times for this SV
t = array([day + timedelta(hours=h) for h in f['time'][cind].astype(float)])
if tlim:
mask = (tlim[0] <= t) & (t <= tlim[1])
t = t[mask]
cind = cind[mask]
#now filter by az,el criteria
az,el,r = eci2aer(f['pos_eci'][cind,:], camlla[0], camlla[1], camlla[2],t)
if ellim and ((ellim[0] <= el) & (el <= ellim[1])).any():
# print(t)
#print('sat psv {}'.format(f['pseudo_sv_num'][i]))
eci = f['pos_eci'][cind,:]
lat,lon,alt = eci2geodetic(eci,t)
x,y,z = eci2ecef(eci,t)
#print('ecef {} {} {}'.format(x,y,z))
ecef = DataFrame(index=t, columns=['x','y','z'], data=column_stack((x,y,z)))
lla = DataFrame(index=t, columns=['lat','lon','alt'], data=column_stack((lat,lon,alt)))
aer = DataFrame(index=t, columns=['az','el','srng'], data=column_stack((az,el,r)))
return ecef,lla,aer,eci
print('no FOV crossings for your time span were found.')
return (None,None)
def test_eci(self):
if numpy is None or astropy is None:
logging.warning('ECI not tested')
return
teci = (-3.977913815668146e6, -2.582332196263046e6,
4.250818828152067e6)
t = datetime(2013, 1, 15, 12, 0, 5, tzinfo=UTC)
lla = numpy.asarray(pm.eci2geodetic(teci, t)).squeeze()
assert_allclose(lla, lla0, rtol=0.2)
assert_allclose(
pm.eci2ecef(teci, t).squeeze(),
[649012.04640917, -4697980.55129606, 4250818.82815207])
assert_allclose(
pm.ecef2eci([649012.04640917, -4697980.55129606, 4250818.82815207],
t).squeeze(), teci)
assert_allclose(
numpy.asarray(pm.eci2aer(teci, 42, -100, 0, t)).squeeze(),
[83.73050, -6.614478, 1.473510e6])
def igrffx(eci_vec, time):
#import igrf12
import numpy
import pyIGRF
import pymap3d
from pymap3d import ecef2eci
import navpy
from navpy import ned2ecef
import datetime
from datetime import datetime
import astropy
#eci_vec is a xyz vector in ECI km
#output B_ECI is a 3 item array in units of T
#get our lat long and alt from ECI
geod = pymap3d.eci2geodetic(1000 * eci_vec, time, useastropy=True)
latitude = geod[0][0] #degrees
longitude = geod[1][0] #degrees
altitude = geod[2] #meters
#call igrf to get b vector in NED
#mag = igrf12.igrf('2019-01-12', glat=latitude, glon=longitude, alt_km=altitude/1000)
b = pyIGRF.igrf_value(latitude, longitude, altitude / 1000, 2019)
#combine NED components back into an array
#NED = numpy.array([b_north,b_east,b_down])
NED = b[3:6]
#convert from NED to ECEF
ECEF = navpy.ned2ecef(NED, latitude, longitude, altitude)
#convert from ECEF to ECI
B_ECI = (pymap3d.ecef2eci(ECEF, time, useastropy=True)) * 10**(-9)
return B_ECI
def RAY_INTERSECT_WGS84_TERRAIN(point,
ray_dir,
t,
DEM_FILE_LOCATION=None,
nom_height=0):
lat, lon, height = RAY_INTERSECT_WGS84(point, ray_dir, t)
s, height_min = Height_From_DEM(lon, lat, DEM_FILE_LOCATION)
if (s == 0):
return RAY_INTERSECT_WGS84(point, ray_dir, t)
#print(Max_Local_Height_From_DEM(lon,lat,DEM_FILE_LOCATION,scale=(5,5)))
s, (max_lat, max_lon,
max_height) = Max_Local_Height_From_DEM(lon,
lat,
DEM_FILE_LOCATION,
scale=(5, 5))
if (s == 0):
return RAY_INTERSECT_WGS84(point, ray_dir, t)
eci_ter = pm.ecef2eci(pm.geodetic2ecef(lat, lon, height), t)
#print([(max_lon,max_lat),max_height, t])
eci_ter_lmax = pm.ecef2eci(pm.geodetic2ecef(max_lat, max_lon, max_height),
t)
#print(mid_llh[2],height_mid
xd = ray_dir[0] #-31.46071792#-
yd = ray_dir[1] #58.59611618#-
zd = ray_dir[2] #27.47631664#-
xc = -point[0]
yc = -point[1]
zc = -point[2]
xn = eci_ter_lmax[0]
yn = eci_ter_lmax[1]
zn = eci_ter_lmax[2]
#print(xn,yn,zn)
t_par = (((xn)**2 + (yn)**2 + (zn)**2) - (xc * xn) - (yc * yn) -
(zc * zn)) / (xd * xn + yd * yn + zd * zn)
rez = np.array([xc + t_par * xd, yc + t_par * yd, zc + t_par * zd])
#print(pm.eci2geodetic((rez),t))
#print(eci_ter)
height_delta = 9999999999
eci_ter_mid = (eci_ter + rez) / 2
height_delta_old = 9898989898
while (abs(height_delta) > 5 and height_delta_old != height_delta):
#print(str(height_delta)+': height delta')
mid_llh = pm.eci2geodetic(eci_ter_mid, t) #latlonheight
s, height_mid = Height_From_DEM(mid_llh[1], mid_llh[0],
DEM_FILE_LOCATION)
if (s == 0):
return RAY_INTERSECT_WGS84(point, ray_dir, t)
#print(mid_llh[2],height_mid[2],mid_llh[2]-height_mid[2])
height_delta_old = height_delta
height_delta = mid_llh[2] - height_mid[2]
if (height_delta < 0):
eci_ter_mid_new = (rez + eci_ter_mid) / 2
eci_ter = eci_ter_mid
eci_ter_mid = eci_ter_mid_new
else:
eci_ter_mid_new = (eci_ter_mid + eci_ter) / 2
rez = eci_ter_mid
eci_ter_mid = eci_ter_mid_new
#print(mid_llh)
return (mid_llh)
def test_eci_geodetic(useastropy):
pytest.importorskip("numpy")
t = "2013-01-15T12:00:05"
lla = pm.eci2geodetic(*eci0, t, useastropy=useastropy)
assert lla == approx(lla0, rel=0.2)
def test_eci_geodetic(useastropy):
t = '2013-01-15T12:00:05'
lla = pm.eci2geodetic(*eci0, t, useastropy=useastropy)
assert lla == approx(lla0, rel=0.2)
def test_eci_geodetic(useastropy):
t = '2013-01-15T12:00:05'
lla = pm.eci2geodetic(*eci0, t, useastropy=useastropy)
assert lla == approx(lla0, rel=0.2)
