def test_rcolum_qback():
if msise00 is not None:
densd, tempd = rungtd1d(dtime, z, glat, glon, f107a, f107, [ap] * 7)
""" VCD: Vertical Column Density """
sza = test_solzen()
zcol, zvcd = glowfort.rcolum(sza, z * 1e5,
densd.loc[:, ['O', 'O2', 'N2']].values.T,
tempd.loc[:, 'Tn'])
# FIXME these tests were numerically unstable (near infinity values)
assert isclose(zcol[0, 0],
1e30) #see rcolum comments for sun below horizon 1e30
assert isclose(zvcd[2, 5], 5.97157e+28,
rtol=1e-2) #TODO changes a bit between python 2 / 3
#%% skipping EPHOTO since we care about night time more for now
znoint = test_snoemint()
# zeros because nighttime
photoi = zeros((nst, nmaj, jmax), dtype=float32, order='F')
phono = zeros((nst, jmax), dtype=float32, order='F')
glowfort.qback(zmaj=densd.loc[:, ['O', 'O2', 'N2']].values.T,
zno=znoint,
zvcd=zvcd,
photoi=photoi,
phono=phono)
#arbitrary point check
assert isclose(photoi[0, 0, 77], 1.38091e-18, rtol=1e-5)
assert isclose(phono[0, 73], 0.0, rtol=1e-5)
else:
logging.warning('skipped rcolum qback due to missing external msise00')
def test_forecast():
t = datetime(2023, 3, 31, 12)
altkm = 150.
glat = 65.
glon = -148.
atmos = msise00.rungtd1d(t, altkm, glat, glon)
assert atmos['He'].ndim == 4
assert atmos['He'].size == 1
dims = list(atmos.dims)
assert ['alt_km', 'lat', 'lon', 'time'] == dims
assert atmos['He'] == approx(4391892942848.0)
assert atmos['O'] == approx(4572213877407744.0)
assert atmos['N2'] == approx(3.699869941864858e+16)
assert atmos['O2'] == approx(8123202106556416.0)
assert atmos['Ar'] == approx(335927545167872.0)
assert atmos['Total'] == approx(2.2950290556877917e-09)
assert atmos['N'] == approx(2154773479424.0)
assert atmos['AnomalousO'] == approx(8.750423680563095e-16)
assert atmos.species == [
'He', 'O', 'N2', 'O2', 'Ar', 'Total', 'H', 'N', 'AnomalousO'
]
assert atmos['Tn'] == approx(666.9913330078125)
assert atmos['Texo'] == approx(922.104736328125)
def test_gtd1d():
t = datetime(2013, 3, 31, 12)
altkm = 150.
glat = 65.
glon = -148.
atmos = msise00.rungtd1d(t, altkm, glat, glon)
assert atmos['He'].ndim == 4
assert atmos['He'].size == 1
dims = list(atmos.dims)
assert ['alt_km', 'lat', 'lon', 'time'] == dims
assert atmos['He'] == approx(11908118740992.0)
assert atmos['O'] == approx(1.306165589835776e+16)
assert atmos['N2'] == approx(3.051389580214272e+16)
assert atmos['O2'] == approx(2664322295660544.0)
assert atmos['Ar'] == approx(67772830711808.0)
assert atmos['Total'] == approx(1.9115256044699436e-09)
assert atmos['N'] == approx(9171036536832.0)
assert atmos['AnomalousO'] == approx(5.380620096337701e-15)
assert atmos.species == [
'He', 'O', 'N2', 'O2', 'Ar', 'Total', 'H', 'N', 'AnomalousO'
]
assert atmos['Tn'] == approx(681.584167)
assert atmos['Texo'] == approx(941.289246)
def reesiono(T: Union[str, datetime], altkm: np.ndarray, E: np.ndarray,
glat: float, glon: float, isotropic: bool, verbose: bool,
datfn: Path) -> xarray.DataArray:
# other assertions covered inside modules
assert isinstance(isotropic, bool)
if abs(glat) < 45.:
logging.error('This model was intended for auroral precipitation.')
if isinstance(T, str):
T = parse(T)
time = np.atleast_1d(T)
assert isinstance(time[0], datetime)
# %% MSIS
if isotropic:
logging.debug('isotropic pitch angle flux')
else:
logging.debug('field-aligned pitch angle flux')
Qt = xarray.DataArray(data=np.empty((time.size, altkm.size, E.size)),
coords=[time, altkm, E],
dims=['time', 'alt_km', 'energy'])
# %% loop
for t in time:
iono = rungtd1d(t, altkm, glat, glon)
Q = ionization_profile_from_flux(E, iono, isotropic, datfn, verbose)
Qt.loc[t, ...] = Q
return Qt
def test_snoemint():
if msise00 is not None:
densd, tempd = rungtd1d(dtime, z, glat, glon, f107a, f107, [ap] * 7)
# (nighttime background ionization)
print(tempd)
znoint = glowfort.snoemint(dtime.strftime('%Y%j'), glat, glon, f107,
ap, z, tempd.loc[:, 'Tn'])
assert_allclose(znoint[[28, 143]], (1.262170e+08, 3.029169e+01),
rtol=1e-5) #arbitrary
return znoint
else:
logging.warning(
'skipped test_snoemint() due to missing external msise00')
def makefig7(datfn: Path):
"""
Energy deposition (W Eqn A1) plots
"""
z = loadaltenergrid(80., 200)[0]
iono = msise00.rungtd1d(tp, z, llp[0], llp[1], f107a=150., f107=150., ap=4.,
mass=48., # leave mass=48. !
tselecopts=np.array([1, 1, 1, 1, 1, 1, 1, 1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], float))
# NOTE kg m^-2 *10 = g cm^-2
rho = iono.loc[:, 'Total'] * 10. # mass density of atmosphere [g cm^-3]
# eqn A1 Sergienko 1993
W = energy_deg(Eplot, isotropic, rho)
fig7(W, z, Eplot)
def test_gtd1d():
t = datetime(2013, 3, 31, 12, tzinfo=UTC)
altkm = 150.
glat = 65.
glon = -148.
f107a = 100
f107 = 100
ap = 4
dens, temp = rungtd1d(t, altkm, glat, glon, f107a, f107, ap)
assert_allclose(dens.values[0, :-1], [
1.19930062e+13, 1.25792119e+16, 2.92461331e+16, 2.75184702e+15,
6.24779497e+13, 1.84406768e-09, 8.54530523e+11, 8.42101896e+12
])
assert (dens.species.values == [
'He', 'O', 'N2', 'O2', 'Ar', 'Total', 'H', 'N', 'AnomalousO'
]).all()
assert_allclose(temp.values[0, :], [848.71148682, 645.71972656])
p.add_argument('-c',
'--latlon',
help='geodetic coordinates of simulation',
default=(65, -147.5),
type=float)
p.add_argument('--f107', type=float, default=200.)
p.add_argument('--f107a', type=float, default=200.)
p.add_argument('--ap', type=int, default=4)
p = p.parse_args()
altkm = np.arange(p.alt[0], p.alt[1], p.alt[2])
dtime = parse(p.time)
#%% IRI
iono = runiri(dtime, altkm, p.latlon, p.f107, p.f107a, ap=p.ap)
#%% MSIS
dens, temp = rungtd1d(dtime, altkm, p.latlon[0], p.latlon[1], p.f107a,
p.f107, p.ap)
#%% IGRF
Bx, By, Bz, B0 = runigrf12(dtime,
isv=0,
itype=1,
alt=altkm,
glat=p.latlon[0],
glon=p.latlon[1])[:4]
B0 = B0 / 1e9 #[T]
#%% compute electron-neutral collison frequency
"""
Thrane & Piggot, The collision frequency in the E- and D-regions of the ionosphere, 1966, JATP.
vm essentially matches Fig. 1 of this paper.
This paper argues that Tn~Te in the D and E region ionosphere.
"""
T = iono.loc[:, 'Te']
from argparse import ArgumentParser
p = ArgumentParser()
p.add_argument('--alt',help='START STOP STEP altitude [km]',type=float,nargs=3,default=(50,150,1.))
p.add_argument('-t','--time',help='datetime of simulation',default='2012-07-21T12')
p.add_argument('-c','--latlon',help='geodetic coordinates of simulation',default=(65,-147.5),type=float)
p.add_argument('--f107',type=float,default=200.)
p.add_argument('--f107a',type=float,default=200.)
p.add_argument('--ap',type=int,default=4)
p = p.parse_args()
altkm = np.arange(p.alt[0], p.alt[1], p.alt[2])
dtime = parse(p.time)
#%% IRI
iono = runiri(dtime,altkm,p.latlon,p.f107, p.f107a, ap=p.ap)
#%% MSIS
dens,temp = rungtd1d(dtime, altkm, p.latlon[0], p.latlon[1], p.f107a, p.f107, p.ap)
#%% IGRF
Bx,By,Bz,B0 = runigrf12(dtime,isv=0,itype=1,
alt=altkm, glat=p.latlon[0], glon=p.latlon[1])[:4]
B0 = B0/1e9 #[T]
#%% compute electron-neutral collison frequency
"""
Thrane & Piggot, The collision frequency in the E- and D-regions of the ionosphere, 1966, JATP.
vm essentially matches Fig. 1 of this paper.
This paper argues that Tn~Te in the D and E region ionosphere.
"""
T = iono.loc[:,'Te']
T[np.isnan(T)] = temp.loc[:,'Tn']
E = 3/2*kb_evK*T # [eV]
# [Hz] monoenergetic electron-neutral collision freq