def test_gtd():
iyd, utsec, stl = sd.datetime2gtd(T, glon=42)
assert_allclose(iyd, 183)
assert_allclose(utsec, (43200, 0, 43200))
assert_allclose(stl, (14.8, 2.8, 14.8))
def test_list():
iyd, utsec, stl = sd.datetime2gtd(T, glon=42)
assert (iyd == 183).all()
assert_allclose(utsec, (43200, 0, 43200, 43200))
assert_allclose(stl, (14.8, 2.8, 14.8, 14.8))
def run(time: datetime, altkm: np.ndarray, glat: float, glon: float,
f107a: float, f107: float, ap: int) -> xarray.Dataset:
altkm = np.atleast_1d(altkm).astype(float)
if isinstance(time, str):
time = parse(time)
iyd, utsec, stl = datetime2gtd(time, glon)
merid = np.empty(altkm.size, dtype=float)
zonal = np.empty(altkm.size, dtype=float)
for i, a in enumerate(altkm):
w = hwm93fort.gws5(iyd, utsec, a, glat, glon, stl, f107a, f107,
(ap, ap))
merid[i] = w[0]
zonal[i] = w[1]
# %% assemble output
winds = xarray.Dataset(
{
"meridional": ("alt_km", merid),
"zonal": ("alt_km", zonal)
},
coords={"alt_km": altkm},
attrs={
"time": time.isoformat(),
"glat": glat,
"glon": glon
},
)
return winds
def test_list():
iyd, utsec, stl = sd.datetime2gtd(T, glon=42)
assert (iyd == 183).all()
assert utsec == approx((43200, 0, 43200, 43200))
assert stl == approx((14.8, 2.8, 14.8, 14.8))
def rungtdGLOW(dtime, altkm, glat, glon, f107a, f107, ap, mass, tselecopts):
chdir(str(glowpath))
ap = atleast_1d(ap)
if ap.size == 1: ap = repeat(ap, 7)
species = ['He', 'O', 'N2', 'O2', 'Ar', 'Total', 'H', 'N', 'AnomalousO']
ttypes = ['exotemp', 'heretemp']
tselec(tselecopts) #like the msis_driver example
logging.debug('tselec options used: {}'.format(
csw.sw)) #don't use tretrv, it doesn't work
iyd, utsec, stl = datetime2gtd(dtime, glon)
altkm = atleast_1d(altkm)
dens = empty((altkm.size, 9))
temp = empty((altkm.size, 2))
meters(1) # makes output in m^-3 and kg/m^-3
for i, a in enumerate(altkm):
dens[i, :], temp[i, :] = gtd7(iyd, utsec, a, glat, glon, stl, f107a,
f107, ap, mass)
densd = DataArray(dens,
dims=['z_km', 'species'],
coords={
'z_km': altkm,
'species': species
})
tempd = DataArray(temp,
dims=['z_km', 'temperature'],
coords={
'z_km': altkm,
'temperature': ttypes
})
return densd, tempd
def test_datetime():
t = T[0]
assert isinstance(t, datetime.datetime)
iyd, utsec, stl = sd.datetime2gtd(t, glon=42)
assert iyd == 183
assert utsec == 43200
assert_allclose(stl, 14.8)
def test_dt64():
t = T[2]
assert isinstance(t, np.datetime64)
iyd, utsec, stl = sd.datetime2gtd(t, glon=42)
assert iyd == 183
assert utsec == 43200
assert_allclose(stl, 14.8)
def test_datetime():
t = T[0]
assert isinstance(t, datetime.datetime)
iyd, utsec, stl = sd.datetime2gtd(t, glon=42)
assert iyd == 183
assert utsec == 43200
assert stl == approx(14.8)
def test_glon():
glon = range(-180, 180 + 45, 45)
iyd, utsec, stl = sd.datetime2gtd(T, glon)
Estl = np.array([
np.arange(0, 24 + 3, 3),
np.arange(-12, 12 + 3, 3),
np.arange(0, 24 + 3, 3),
np.arange(0, 24 + 3, 3)
])
assert_allclose(utsec, (43200, 0, 43200, 43200))
assert_allclose(stl, Estl)
def test_glon():
glon = range(-180, 180 + 45, 45)
iyd, utsec, stl = sd.datetime2gtd(T, glon)
Estl = np.array([
np.arange(0, 24 + 3, 3),
np.arange(-12, 12 + 3, 3),
np.arange(0, 24 + 3, 3),
np.arange(0, 24 + 3, 3),
])
assert utsec == approx((43200, 0, 43200, 43200))
assert stl == approx(Estl)
def rungtd1d(time, altkm:float, glat:float, glon:float) -> xarray.Dataset:
"""
This is the "atomic" function looped by other functions
"""
# %% get solar parameters for date
f107Ap = readmonthlyApF107(time)
f107a = f107Ap['f107s'].item()
f107 = f107Ap['f107o'].item()
Ap = (f107Ap['Apo'].item(),)*7
#%%
altkm= np.atleast_1d(altkm)
glon = np.atleast_1d(glon).squeeze()
glat = np.atleast_1d(glat).squeeze()
assert isinstance(time,(np.datetime64,datetime,str)),'if you have multiple times, for loop over them'
# don't check ap, too complicated
assert isinstance(MASS,(float,int))
assert len(TSELECOPS)==25
#%%
Ap = np.atleast_1d(Ap)
if Ap.size==1:
Ap = np.repeat(Ap,7)
gtd7.tselec(TSELECOPS) #like the msis_driver example
iyd,utsec,stl = datetime2gtd(time, glon)
altkm = np.atleast_1d(altkm)
gtd7.meters(1) # makes output in m^-3 and kg/m^-3
dens = np.empty((altkm.size, len(species)))
temp = np.empty((altkm.size, len(ttypes)))
for i,a in enumerate(altkm):
dens[i,:], temp[i,:] = gtd7.gtd7(iyd, utsec, a, glat,glon, stl, f107a, f107, Ap,MASS)
dsf = {k: (('time','alt_km','lat','lon'),v[None,:,None,None]) for (k,v) in zip(species, dens.T)}
dsf.update({'Tn': (('time','alt_km','lat','lon'), temp[:,1][None,:,None,None]),
'Texo':(('time','alt_km','lat','lon'), temp[:,0][None,:,None,None])})
atmos = xarray.Dataset(dsf,
coords={'time':[time], 'alt_km':altkm, 'lat':[glat],'lon':[glon],},
attrs={'Ap':Ap,'f107':f107,'f107a':f107a,
'species':species})
return atmos
def rungtd1d(t,altkm,glat,glon,f107a,f107,ap):
"""
This is the "atomic" function looped by other functions
"""
#%%
altkm= atleast_1d(altkm)
glon = atleast_1d(glon).squeeze()
glat = atleast_1d(glat).squeeze()
assert isinstance(t,(datetime,str)),'if you have multiple times, for loop over them'
assert isinstance(f107a,(float,int))
assert isinstance(f107,(float,int))
# don't check ap, too complicated
assert isinstance(MASS,(float,int))
assert len(TSELECOPS)==25
#%%
ap = atleast_1d(ap)
if ap.size==1:
ap = repeat(ap,7)
gtd7.tselec(TSELECOPS) #like the msis_driver example
iyd,utsec,stl = datetime2gtd(t,glon)
altkm = atleast_1d(altkm)
dens = DataArray(data=empty((altkm.size, len(species))),
coords=[altkm, species],dims=['alt_km','species'])
temp = DataArray(data=empty((altkm.size, len(ttypes))),
coords=[altkm, ttypes],dims=['alt_km','temp'])
gtd7.meters(1) # makes output in m^-3 and kg/m^-3
for i,a in enumerate(altkm):
dens[i,:],temp[i,:] = gtd7.gtd7(iyd,utsec,a, glat,glon,stl, f107a,f107, ap,MASS)
return dens,temp
def test_snoem():
doy = datetime2gtd(dtime)[0]
zno, maglat, nozm = glowfort.snoem(doy, 1.75 * log(0.4 * ap), f107)
assert_allclose((nozm[12, 15], nozm[-2, -1]), (35077728.0, 1.118755e+08))
return nozm
def rungtd1d(time: Union[datetime, str, np.ndarray], altkm: np.ndarray,
glat: float, glon: float) -> xarray.Dataset:
"""
This is the "atomic" function looped by other functions
"""
time = todt64(time)
# %% get solar parameters for date
f107Ap = ga.getApF107(time, smoothdays=81)
f107a = f107Ap['f107s'].item()
f107 = f107Ap['f107'].item()
Ap = f107Ap['Ap'].item()
# %% dimensions
altkm = np.atleast_1d(altkm)
assert altkm.ndim == 1
assert isinstance(glon, (int, float))
assert isinstance(glat, (int, float))
assert isinstance(time, np.datetime64) or (time.size == 1 and isinstance(
time[0],
np.datetime64)), 'if you have multiple times, for loop over them'
# don't check ap, too complicated
assert isinstance(MASS, (float, int))
assert len(TSELECOPS) == 25
# %%
gtd7.tselec(TSELECOPS) # like the msis_driver example
iyd, utsec, stl = datetime2gtd(time, glon)
altkm = np.atleast_1d(altkm)
gtd7.meters(1) # makes output in m^-3 and kg/m^-3
# %%
if isinstance(Ap, (float, int)):
Ap = [Ap] * 7 # even if SW(9) == 1 due to f2py needs for array
dens = np.empty((altkm.size, len(species)))
temp = np.empty((altkm.size, len(ttypes)))
for i, a in enumerate(altkm):
dens[i, :], temp[i, :] = gtd7.gtd7(iyd, utsec, a, glat, glon, stl,
f107a, f107, Ap, MASS)
dsf = {
k: (('time', 'alt_km', 'lat', 'lon'), v[None, :, None, None])
for (k, v) in zip(species, dens.T)
}
dsf.update({
'Tn': (('time', 'alt_km', 'lat', 'lon'), temp[:, 1][None, :, None,
None]),
'Texo': (('time', 'alt_km', 'lat', 'lon'), temp[:, 0][None, :, None,
None])
})
atmos = xarray.Dataset(dsf,
coords={
'time': time.astype(datetime),
'alt_km': altkm,
'lat': [glat],
'lon': [glon],
},
attrs={
'Ap': Ap,
'f107': f107,
'f107a': f107a,
'species': species
})
return atmos