def test_exception_maxalt():
with pytest.raises(ValueError):
aacgmv2.convert(60, 0, 2001, dtObj)
with pytest.raises(ValueError):
aacgmv2.convert(60, 0, [300, 2001], dtObj)
# the following should not raise exceptions
aacgmv2.convert(60, 0, 2001, dtObj, trace=True)
aacgmv2.convert(60, 0, 2001, dtObj, allowtrace=True)
aacgmv2.convert(60, 0, 2001, dtObj, badidea=True)
def f4():
plt.figure(figsize=(6.88,6.74))
#geographic coordinates
ax1, projection1 = gcc.create_map(
2, 2, 1, 'pol', 90, 50, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
ax1.plot([45,45],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([225,225],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([105,105],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([285,285],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.scatter(
0, 90, color='r', transform=ccrs.PlateCarree(), zorder=10,
label='North Pole')
ax1.text(0,1,'(a)', transform = plt.gca().transAxes)
plt.legend(loc=[0.5,1.1])
ax2, projection2 = gcc.create_map(
2, 2, 2, 'pol', -50, -90, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
ax2.scatter(
0, -90, color='b', transform=ccrs.PlateCarree(),label='South Pole')
ax2.text(0,1,'(b)', transform = plt.gca().transAxes)
plt.legend(loc=[-0.1,1.1])
#geomagnetic coordinates
ax3, projection3 = gcc.create_map(
2, 2, 3, 'pol', 90, 50, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
mlatn,mlonn = convert(90,0,0,date=dt.date(2002,3,21))
for k in range(24):
mltn = convert_mlt(mlonn[0],dtime=dt.datetime(2003,3,21,k))
ax3.scatter(mltn*15,mlatn[0],color='r',transform=ccrs.PlateCarree())
ax3.scatter(180,75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
ax3.text(0,1,'(c)', transform = plt.gca().transAxes)
ax4, projection4 = gcc.create_map(
2, 2, 4, 'pol', -50, -90, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
mlats,mlons = convert(-90,0,0,date=dt.date(2002,3,21))
for k in range(24):
mlts = convert_mlt(mlons[0],dtime=dt.datetime(2003,3,21,k))
ax4.scatter(mlts*15,mlats[0],color='b',transform=ccrs.PlateCarree())
ax4.scatter(180,-75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
ax4.text(0,1,'(d)', transform = plt.gca().transAxes)
plt.savefig(
'/Users/guod/Documents/Pole_Density_MLT_Change/Figures/'
'000_Pole_Feature.pdf')
return
def test_convert_list(self):
"""Test conversion for list input"""
self.lat, self.lon = aacgmv2.convert([60], [0], [300], self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
self.lat, self.lon = aacgmv2.convert([60, 61], [0, 0], [300, 300],
self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (2, )
np.testing.assert_allclose(self.lat, [58.2258, 59.3186], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685, 81.6140], rtol=1e-4)
def test_convert_location_failure(self):
"""Test conversion with a bad location"""
self.lat, self.lon = aacgmv2.convert([0], [0], [0], self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
assert np.all([np.isnan(self.lat), np.isnan(self.lon)])
def test_convert_single_val(self):
"""Test conversion for a single value"""
self.lat, self.lon = aacgmv2.convert(60, 0, 300, self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
def test_convert_arr_single(self):
"""Test conversion for array input with one element"""
self.lat, self.lon = aacgmv2.convert(np.array([60]), np.array([0]),
np.array([300]), self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
def test_convert_arr_mix(self):
"""Test conversion for an array and floats"""
self.lat, self.lon = aacgmv2.convert(np.array([60, 61]), 0, 300,
self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (2, )
np.testing.assert_allclose(self.lat, [58.2258, 59.3186], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685, 81.6140], rtol=1e-4)
def test_warning_below_ground_convert(self):
""" Test that a warning is issued if altitude is below zero"""
import logbook
lwarn = u"conversion not intended for altitudes < 0 km"
with logbook.TestHandler() as handler:
self.lat, self.lon = aacgmv2.convert([60], [0], [-1], self.dtime)
assert handler.has_warning(lwarn)
handler.close()
def get_flight_route(i,does_this_route_pass_through_arctic,airport_code,dest_airports):
### returns a pandas dataframe with the flight route info
### or returns None if the flight does not pass through the Arctic
if not does_this_route_pass_through_arctic[i]:
return None
folderpath = 'gis_temp/'
layername = airport_code+'-'+dest_airports.loc[i].code
mag_lat = [dest_airports.loc[i].code+' mag lat']; mag_lon = [dest_airports.loc[i].code+' mag lon']
gc_lat = [dest_airports.loc[i].code+' lat']; gc_lon = [dest_airports.loc[i].code+' lon']
with open(folderpath+'/'+layername+'.geojson') as json_file:
data = json.load(json_file)
if len(data['features'][0]['geometry']['coordinates'][0]) == 2: #if everything is working as expected
for j in range(len(data['features'][0]['geometry']['coordinates'][:])):
lon,lat = data['features'][0]['geometry']['coordinates'][j]
mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(),
a2g=False, trace=False, allowtrace=False,
badidea=False, geocentric=False)
mag_lat.append(mg_lat[0])
mag_lon.append(mg_lon[0])
gc_lat.append(lat)
gc_lon.append(lon)
else: #anti-meridian crossing, they split the results into two groups so the len will be a lot longer
for j in range(len(data['features'][0]['geometry']['coordinates'][0][:])):
lon,lat = data['features'][0]['geometry']['coordinates'][0][j]
mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(),
a2g=False, trace=False, allowtrace=False,
badidea=False, geocentric=False)
mag_lat.append(mg_lat[0])
mag_lon.append(mg_lon[0])
gc_lat.append(lat)
gc_lon.append(lon)
for j in range(len(data['features'][0]['geometry']['coordinates'][1][:])):
lon,lat = data['features'][0]['geometry']['coordinates'][1][j]
mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(),
a2g=False, trace=False, allowtrace=False,
badidea=False, geocentric=False)
mag_lat.append(mg_lat[0])
mag_lon.append(mg_lon[0])
gc_lat.append(lat)
gc_lon.append(lon)
df = pd.DataFrame.from_records([gc_lat,gc_lon,mag_lat,mag_lon])
return df
def test_convert_result_values_shape():
lat, lon = aacgmv2.convert(np.array([[60, 61, 62],
[63, 64, 65]]),
0, 300, dtObj)
aacgmv2._aacgmv2.setDateTime(*date)
assert (lat[0, 0], lon[0, 0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, G2A)
assert (lat[0, 1], lon[0, 1], 1) == aacgmv2._aacgmv2.aacgmConvert(61, 0, 300, G2A)
assert (lat[0, 2], lon[0, 2], 1) == aacgmv2._aacgmv2.aacgmConvert(62, 0, 300, G2A)
assert (lat[1, 0], lon[1, 0], 1) == aacgmv2._aacgmv2.aacgmConvert(63, 0, 300, G2A)
assert (lat[1, 1], lon[1, 1], 1) == aacgmv2._aacgmv2.aacgmConvert(64, 0, 300, G2A)
assert (lat[1, 2], lon[1, 2], 1) == aacgmv2._aacgmv2.aacgmConvert(65, 0, 300, G2A)
def solar_conductance(self, dt, mlats, mlts, return_f107=False):
"""
Estimate the solar conductance using methods from:
Cousins, E. D. P., T. Matsuo, and A. D. Richmond (2015), Mapping
high-latitude ionospheric electrodynamics with SuperDARN and AMPERE
--which cites--
Asgeir Brekke, Joran Moen, Observations of high latitude ionospheric conductances
Maybe is not good for SZA for southern hemisphere? Don't know
Going to use absolute value of latitude because that's what's done
in Cousins IDL code.
"""
# Find the closest hourly f107 value
# to the current time to specifiy the conductance
f107 = ovation_utilities.get_daily_f107(dt)
if hasattr(self, '_f107'):
log.warning(
('Warning: Overriding real F107 {0}'.format(f107) +
'with secret instance property _f107 {0}'.format(self._f107) +
'this is for debugging and will not' +
'produce accurate results for a particular date.'))
f107 = self._f107
# print "F10.7 = %f" % (f107)
# Convert from magnetic to geocentric using the AACGMv2 python library
flatmlats, flatmlts = mlats.flatten(), mlts.flatten()
flatmlons = aacgmv2.convert_mlt(flatmlts, dt, m2a=True)
try:
glats, glons = aacgmv2.convert(flatmlats,
flatmlons,
110. * np.ones_like(flatmlats),
date=dt,
a2g=True,
geocentric=False)
except AttributeError:
# convert method was deprecated
glats, glons, r = aacgmv2.convert_latlon_arr(flatmlats,
flatmlons,
110.,
dt,
method_code='A2G')
sigp, sigh = brekke_moen_solar_conductance(dt, glats, glons, f107)
sigp_unflat = sigp.reshape(mlats.shape)
sigh_unflat = sigh.reshape(mlats.shape)
if return_f107:
return sigp_unflat, sigh_unflat, f107
else:
return sigp_unflat, sigh_unflat
def test_output_type():
lat, lon = aacgmv2.convert(60, 0, 300, dtObj)
print(type(lat))
print(lat.shape)
print(lat.size)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
lat, lon = aacgmv2.convert([60], [0], [300], dtObj)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
lat, lon = aacgmv2.convert([60, 61], [0, 0], [300, 300], dtObj)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
lat, lon = aacgmv2.convert([60, 61, 62], 0, 300, dtObj)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
lat, lon = aacgmv2.convert(np.array([60, 61, 62]), 0, 300, dtObj)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
lat, lon = aacgmv2.convert(np.array([[60, 61, 62], [63, 64, 65]]), 0, 300, dtObj)
assert isinstance(lat, np.ndarray)
assert isinstance(lon, np.ndarray)
def test_convert_mult_array_mix(self):
"""Test conversion for a multi-dim array and floats"""
self.lat, self.lon = aacgmv2.convert(
np.array([[60, 61, 62], [63, 64, 65]]), 0, 300, self.dtime)
assert isinstance(self.lat, np.ndarray)
assert isinstance(self.lon, np.ndarray)
assert self.lat.shape == self.lon.shape and self.lat.shape == (2, 3)
np.testing.assert_allclose(
self.lat,
[[58.2258, 59.3186, 60.4040], [61.4820, 62.5528, 63.6164]],
rtol=1e-4)
np.testing.assert_allclose(
self.lon,
[[81.1685, 81.6140, 82.0872], [82.5909, 83.1286, 83.7039]],
rtol=1e-4)
def test_output_shape_size():
lat, lon = aacgmv2.convert(60, 0, 300, dtObj)
assert lat.shape == tuple()
assert lon.shape == tuple()
assert lat.size == 1
assert lon.size == 1
lat, lon = aacgmv2.convert([60], [0], [300], dtObj)
assert lat.shape == (1,)
assert lon.shape == (1,)
assert lat.size == 1
assert lon.size == 1
lat, lon = aacgmv2.convert([60, 61], [0, 0], [300, 300], dtObj)
assert lat.shape == (2,)
assert lon.shape == (2,)
assert lat.size == 2
assert lon.size == 2
lat, lon = aacgmv2.convert([60, 61, 62], 0, 300, dtObj)
assert lat.shape == (3,)
assert lon.shape == (3,)
assert lat.size == 3
assert lon.size == 3
lat, lon = aacgmv2.convert(np.array([60, 61, 62]), 0, 300, dtObj)
assert lat.shape == (3,)
assert lon.shape == (3,)
assert lat.size == 3
assert lon.size == 3
lat, lon = aacgmv2.convert(np.array([[60, 61, 62],
[63, 64, 65]]),
0, 300, dtObj)
assert lat.shape == (2, 3)
assert lon.shape == (2, 3)
assert lat.size == 6
assert lon.size == 6
def test_convert_result_values_badidea():
lat, lon = aacgmv2.convert(60, 0, [300, 5000], dtObj, badidea=True)
aacgmv2._aacgmv2.setDateTime(*date)
assert (lat[0], lon[0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, BADIDEA)
assert (lat[1], lon[1], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 5000, BADIDEA)
def test_convert_result_values_geocentric():
lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj, geocentric=True)
aacgmv2._aacgmv2.setDateTime(*date)
lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, GEOCENTRIC)
assert lat_p == lat_c
assert lon_p == lon_c
def test_convert_result_values_A2G_trace():
lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj, a2g=True, trace=True)
aacgmv2._aacgmv2.setDateTime(*date)
lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, A2G | TRACE)
assert lat_p == lat_c
assert lon_p == lon_c
def test_convert_result_values_allowtrace():
lat, lon = aacgmv2.convert(60, 0, [300, 5000], dtObj, allowtrace=True)
aacgmv2._aacgmv2.setDateTime(*date)
assert (lat[0], lon[0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, ALLOWTRACE)
assert (lat[1], lon[1], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 5000, ALLOWTRACE)
def figure2_3(run=1):
plt.close('all')
plt.figure(figsize=(8.28, 9.25))
if run==1:
g = g1
else:
g = g2
rholevels = [np.linspace(8, 16, 21)*1e-10, np.linspace(1,4,21)*1e-11,
np.linspace(0.5, 8,21)*1e-13]
rhoticks = [np.arange(8, 17, 2)*1e-10, np.arange(1,5,1)*1e-11,
np.arange(1, 9, 2)*1e-13]
templevels = [np.linspace(600, 800, 21), np.linspace(900,1500,21),
np.linspace(900, 1500,21)]
tempticks = [np.arange(600, 900, 100), np.arange(900,1600,200),
np.arange(900, 1600, 200)]
labels =[('(a)','(b)','(c)'), ('(d)','(e)','(f)'), ('(g)','(h)','(i)')]
qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
for ialt, alt in enumerate([150, 300, 600]):
alt_ind = np.argmin(np.abs(g['Altitude'][0, 0, 2:-2]/1000-alt))+2
alt_str = '%6.0f' % (g['Altitude'][0, 0, alt_ind]/1000)
ax, projection = gcc.create_map(
3, 3, ialt+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g, 'polar', useLT=True),
coastlines=False, lonticklabel=[1,1,1,1])
# density
lon0, lat0, zdata0 = g3ca.contour_data('Rho', g, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
hc = ax.contourf(
lon0, lat0, zdata0, rholevels[ialt], transform=ccrs.PlateCarree(),
cmap='jet', extend='both')
gcapos = ax.get_position()
axcb = [
gcapos.x0, gcapos.y0+0.028, gcapos.width, gcapos.height/20]
axcb = plt.axes(axcb)
hcb = plt.colorbar(
hc, cax=axcb, extendrect=True, ticks=rhoticks[ialt],
orientation='horizontal')
# wind
lon0, lat0, ewind, nwind = g3ca.vector_data(g, 'neutral', alt=alt)
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0, lat0, ewind, nwind, plot_type='polar', projection=projection)
hq = ax.quiver(
lon0, lat0, ewind, nwind, scale=1000, scale_units='inches',
regrid_shape=20)
ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)
ax.set_title('%s km' % alt_str, y=1.08)
if ialt == 0:
plt.text(
-0.2, 0.5, r'$\rho$ and wind', rotation=90,
transform=ax.transAxes, verticalalignment='center')
plt.text(0, 0.9, labels[0][ialt],transform=ax.transAxes,color='r')
#----------------------------------------------------------------------
ax, projection = gcc.create_map(
3, 3, ialt+4, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g, 'polar', useLT=True),
coastlines=False, lonticklabel=[1,1,1,1])
# temperature
lon0, lat0, zdata0 = g3ca.contour_data('Temperature', g, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
hc = ax.contourf(
lon0, lat0, zdata0, templevels[ialt], transform=ccrs.PlateCarree(),
cmap='jet', extend='both')
gcapos = ax.get_position()
axcb = [
gcapos.x0, gcapos.y0-0.017, gcapos.width, gcapos.height/20]
axcb = plt.axes(axcb)
hcb = plt.colorbar(
hc, cax=axcb, extendrect=True, ticks=tempticks[ialt],
orientation='horizontal')
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)
if ialt == 0:
plt.text(
-0.2, 0.5, 'Temperature (K)', rotation=90,
transform=ax.transAxes, verticalalignment='center')
plt.text(0, 0.9, labels[1][ialt],transform=ax.transAxes,color='r')
#----------------------------------------------------------------------
ax, projection = gcc.create_map(
3, 3, ialt+7, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g, 'polar', useLT=True),
coastlines=False, lonticklabel=[1,1,1,1])
# ion drift
lon0, lat0, ewind, nwind = g3ca.vector_data(g, 'ion', alt=alt)
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0, lat0, ewind, nwind, plot_type='polar', projection=projection)
if run == 2:
ewind, nwind = 0.1*ewind, 0.1*nwind
hq = ax.quiver(
lon0, lat0, ewind, nwind, scale=1000, scale_units='inches',
regrid_shape=20)
ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)
if ialt == 0:
plt.text(
-0.2, 0.5, 'Ion Drift', rotation=90,
transform=ax.transAxes, verticalalignment='center')
plt.text(0, 0.9, labels[2][ialt],transform=ax.transAxes,color='r')
plt.subplots_adjust(wspace=0.25, hspace=0.25, top=0.95, bottom=0.05)
if run==1:
plt.savefig(savepath+'Figure2.eps')
plt.savefig(savepath+'Figure2.jpeg')
else:
plt.savefig(savepath+'Figure3.eps')
plt.savefig(savepath+'Figure3.jpeg')
return
def figure5_7(alt=150):
times = pd.to_datetime([
'2003-03-22 00:00:00', '2003-03-22 00:30:00', '2003-03-22 01:00:00',
'2003-03-22 02:00:00', '2003-03-22 03:00:00', '2003-03-22 06:00:00'])
plt.close('all')
plt.figure(figsize=(9.5, 9.25))
xtitle = [
r'$-\nabla\cdot w$', r'$-\nabla\cdot u$',
r'$-\frac{w\cdot\nabla\rho}{\rho}$',
r'$-\frac{u\cdot\nabla\rho}{\rho}$',
r'$\frac{\partial \rho}{\rho\partial t}$',
r'$\delta\rho$ (%)']
ylabel = times.strftime('%H:%M')
qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
for itime, time in enumerate(times):
strtime = time.strftime('%y%m%d_%H%M')
fn1 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_no_shrink_iondrift_4_1/data/3DALL_t%s*.bin' % strtime)
fn2 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_shrink_iondrift_4_c1/data/3DALL_t%s*.bin' % strtime)
g1 = gitm.read(fn1[0])
g2 = gitm.read(fn2[0])
lon1 = g1['Longitude']
lat1 = g1['Latitude']
alt1 = g1['Altitude']
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt1
omega = 2*pi/(24*3600)
rho1 = np.array(g1['Rho'])
nwind1 = g1['V!Dn!N (north)']
ewind1 = g1['V!Dn!N (east)'] + omega*RR*np.cos(lat1)
uwind1 = g1['V!Dn!N (up)']
div_rhov1 = \
(cr.calc_div_hozt(lon1, lat1, alt1, rho1*nwind1, rho1*ewind1)\
+cr.calc_div_vert(alt1, rho1*uwind1))/rho1
vert_divv1 = cr.calc_div_vert(alt1, uwind1)
hozt_divv1 = cr.calc_div_hozt(lon1, lat1, alt1, nwind1, ewind1)
vert_vgradrho1 = uwind1*cr.calc_rusanov_alts_ausm(alt1,rho1)/rho1
hozt_vgradrho1 = \
(nwind1*cr.calc_rusanov_lats(lat1,alt1,rho1)\
+ewind1*cr.calc_rusanov_lons(lon1,lat1,alt1,rho1))/rho1
dc1 = [
vert_divv1, hozt_divv1, vert_vgradrho1, hozt_vgradrho1,
div_rhov1, rho1]
lon2 = g2['Longitude']
lat2 = g2['Latitude']
alt2 = g2['Altitude']
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt2
omega = 2*pi/(24*3600)
rho2 = g2['Rho']
nwind2 = g2['V!Dn!N (north)']
ewind2 = g2['V!Dn!N (east)'] + omega*RR*np.cos(lat2)
uwind2 = g2['V!Dn!N (up)']
div_rhov2 = \
(cr.calc_div_hozt(lon2, lat2, alt2, rho2*nwind2, rho2*ewind2)\
+cr.calc_div_vert(alt2, rho2*uwind2))/rho2
vert_divv2 = cr.calc_div_vert(alt2, uwind2)
hozt_divv2 = cr.calc_div_hozt(lon2, lat2, alt2, nwind2, ewind2)
vert_vgradrho2 = uwind2*cr.calc_rusanov_alts_ausm(alt2,rho2)/rho2
hozt_vgradrho2 = \
(nwind2*cr.calc_rusanov_lats(lat2,alt2,rho2)\
+ewind2*cr.calc_rusanov_lons(lon2,lat2,alt2,rho2))/rho2
dc2 = [
vert_divv2, hozt_divv2, vert_vgradrho2, hozt_vgradrho2,
div_rhov2, rho2]
alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
for idc in range(6):
lonticklabel = [0, 0, 0, 0]
if idc == 0:
lonticklabel[3] = lonticklabel[-1]+1
if idc == 5:
lonticklabel[1] = lonticklabel[-1]+1
if itime == 0:
lonticklabel[0] = lonticklabel[-2]+1
if itime == 5:
lonticklabel[2] = lonticklabel[-2]+1
ax, projection = gcc.create_map(
6, 6, itime*6+idc+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False, lonticklabel=lonticklabel)
g1['temp'] = -(dc1[idc] - dc2[idc])
if idc==5:
g1['temp'] = 100*(dc1[idc] - dc2[idc])/dc2[idc]
lon0, lat0, zdata0 = g3ca.contour_data('temp', g1, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
levels = np.linspace(-8,8,21)*1e-5
if idc==5:
levels = np.linspace(-30,30,21)
hc = ax.contourf(
lon0, lat0, zdata0, levels,
transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
# wind difference
alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(
g1, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(
g2, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
lon0, lat0, ewind1-ewind2, nwind1-nwind2,
plot_type='polar', projection=projection)
hq = ax.quiver(
lon0, lat0, ewind0, nwind0, scale=1500,
scale_units='inches', regrid_shape=20, headwidth=5)
ax.scatter(
qlon, qlat, s=10, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=10, transform=ccrs.PlateCarree(),
zorder=1000)
if idc==0:
plt.text(
-0.3, 0.5, ylabel[itime], rotation=90,
transform=ax.transAxes, verticalalignment='center')
if itime==0:
plt.title(xtitle[idc], y=1.15, fontsize=14)
texts = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)']
plt.text(0.05,1,texts[idc],transform=plt.gca().transAxes,
color='r')
if itime==5:
axp = ax.get_position()
cax = [axp.x0, axp.y0-0.03, axp.x1-axp.x0, 1/20*(axp.y1-axp.y0)]
cax = plt.axes(cax)
ticks = np.arange(-8e-5, 8.1e-5, 4e-5) if idc<5 else \
np.arange(-30, 31, 15)
hcb = plt.colorbar(
hc, cax=cax, extendrect=True, orientation='horizontal',
ticks=ticks)
if idc<5:
hcb.formatter.set_powerlimits((0,0))
hcb.update_ticks()
plt.subplots_adjust(wspace=0, hspace=0)
if alt==300:
plt.savefig(savepath+'Figure5.eps')
plt.savefig(savepath+'Figure5.jpeg')
if alt==600:
plt.savefig(savepath+'Figure7.eps')
plt.savefig(savepath+'Figure7.jpeg')
return
def geo2mag(lat, lon, alt):
#Latitudes range from -90 to 90.
#Longitudes range from -180 to 180. (Maybe, who knows -- http://ccmc.gsfc.nasa.gov/requests/instant/ranges.php
#Verified with http://ccmc.gsfc.nasa.gov/requests/instant/instant1.php?model=AACGM&type=1
mlat, mlon = convert(lat, lon, alt, None)
return mlat
def test_exception_lat90():
with pytest.raises(ValueError):
aacgmv2.convert(91, 0, 300, dtObj)
with pytest.raises(ValueError):
aacgmv2.convert(-91, 0, 300, dtObj)
with pytest.raises(ValueError):
aacgmv2.convert([60, 91], 0, 300, dtObj)
with pytest.raises(ValueError):
aacgmv2.convert([60, -91], 0, 300, dtObj)
# the following should not raise exceptions
aacgmv2.convert(90, 0, 300, dtObj)
aacgmv2.convert(-90, 0, 300, dtObj)
def f4():
plt.figure(figsize=(6.88, 6.74))
#geographic coordinates
ax1, projection1 = gcc.create_map(2,
2,
1,
'pol',
90,
50,
0,
coastlines=False,
useLT=True,
dlat=10,
lonticklabel=(1, 1, 1, 1))
ax1.plot([45, 45], [50, 90], 'k--', transform=ccrs.PlateCarree())
ax1.plot([225, 225], [50, 90], 'k--', transform=ccrs.PlateCarree())
ax1.plot([105, 105], [50, 90], 'k--', transform=ccrs.PlateCarree())
ax1.plot([285, 285], [50, 90], 'k--', transform=ccrs.PlateCarree())
ax1.scatter(0,
90,
color='r',
transform=ccrs.PlateCarree(),
zorder=10,
label='North Pole')
ax1.text(0, 1, '(a)', transform=plt.gca().transAxes)
plt.legend(loc=[0.5, 1.1])
ax2, projection2 = gcc.create_map(2,
2,
2,
'pol',
-50,
-90,
0,
coastlines=False,
useLT=True,
dlat=10,
lonticklabel=(1, 1, 1, 1))
ax2.scatter(0,
-90,
color='b',
transform=ccrs.PlateCarree(),
label='South Pole')
ax2.text(0, 1, '(b)', transform=plt.gca().transAxes)
plt.legend(loc=[-0.1, 1.1])
#geomagnetic coordinates
ax3, projection3 = gcc.create_map(2,
2,
3,
'pol',
90,
50,
0,
coastlines=False,
useLT=True,
dlat=10,
lonticklabel=(1, 1, 1, 1))
mlatn, mlonn = convert(90, 0, 0, date=dt.date(2002, 3, 21))
for k in range(24):
mltn = convert_mlt(mlonn[0], dtime=dt.datetime(2003, 3, 21, k))
ax3.scatter(mltn * 15,
mlatn[0],
color='r',
transform=ccrs.PlateCarree())
ax3.scatter(180, 75, s=50, c='k', marker='x', transform=ccrs.PlateCarree())
ax3.text(0, 1, '(c)', transform=plt.gca().transAxes)
ax4, projection4 = gcc.create_map(2,
2,
4,
'pol',
-50,
-90,
0,
coastlines=False,
useLT=True,
dlat=10,
lonticklabel=(1, 1, 1, 1))
mlats, mlons = convert(-90, 0, 0, date=dt.date(2002, 3, 21))
for k in range(24):
mlts = convert_mlt(mlons[0], dtime=dt.datetime(2003, 3, 21, k))
ax4.scatter(mlts * 15,
mlats[0],
color='b',
transform=ccrs.PlateCarree())
ax4.scatter(180,
-75,
s=50,
c='k',
marker='x',
transform=ccrs.PlateCarree())
ax4.text(0, 1, '(d)', transform=plt.gca().transAxes)
plt.savefig('/Users/guod/Documents/Pole_Density_MLT_Change/Figures/'
'000_Pole_Feature.pdf')
return
def plot_06ut_18ut(ns='SH', alt=150, tf=[1, 0, 0, 0, 0, 0]):
# 0:rho and wind; 1: diff rho and wind; 2:ion drag; 3:vni; 4:ion convection
# 5:ion density; 6:electron density;
path = '/home/guod/simulation_output/momentum_analysis/run_shrink_dipole_1_c1/UA/data'
fn1 = path + '/3DALL_t030322_060002.bin'
fn2 = path + '/3DALL_t030322_180002.bin'
g11 = [gitm.read(fn1), gitm.read(fn2)] # shrink, dipole
#print(g11[0]['Altitude'][0,0,np.argmin(np.abs(g11[0]['Altitude'][0,0,:]-150*1000))])
path = '/home/guod/simulation_output/momentum_analysis/run_shrink_igrf_1_c1/UA/data'
fn1 = path + '/3DALL_t030322_060002.bin'
fn2 = path + '/3DALL_t030322_180003.bin'
g12 = [gitm.read(fn1), gitm.read(fn2)] # shrink, igrf
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_dipole_1_1/UA/data'
fn1 = path + '/3DALL_t030322_060000.bin'
fn2 = path + '/3DALL_t030322_180001.bin'
g21 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, diple
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/UA/data'
fn1 = path + '/3DALL_t030322_060001.bin'
fn2 = path + '/3DALL_t030322_180002.bin'
g22 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, igrf
if ns == 'SH':
nlat, slat = -50, -90
elif ns == 'NH':
nlat, slat = 90, 50
glats, glons = convert(-90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
glatn, glonn = convert(90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
fign = ['(a)', '(b)', '(c)', '(d)']
# Rho and wind
if tf[0]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='Rho',
vector=True,
neuion='neu',
useLT=True,
coastlines=False,
levels=np.linspace(0.8e-9, 1.6e-9, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.text(0, 1, fign[k], fontsize=14, transform=plt.gca().transAxes)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0.8e-9, 1.7e-9, 0.2e-9))
cax.set_xlabel(r'$\rho (kg/m^3)$')
plt.quiverkey(hq[0], 0.5, 0.12, 500, '500m/s', coordinates='figure')
plt.savefig(savepath + '2' + ns + 'RhoWind.jpeg')
plt.savefig(savepath + '2' + ns + 'RhoWind.eps')
# ion drag
if tf[1]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
gtemp[0]['iondrag'] = \
gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']*\
np.sqrt((gtemp[0]['V!Di!N (east)']-gtemp[0]['V!Dn!N (east)'])**2 +\
(gtemp[0]['V!Di!N (north)']-gtemp[0]['V!Dn!N (north)'])**2)
gtemp[1]['iondrag'] = \
gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']*\
np.sqrt((gtemp[1]['V!Di!N (east)']-gtemp[1]['V!Dn!N (east)'])**2 +\
(gtemp[1]['V!Di!N (north)']-gtemp[1]['V!Dn!N (north)'])**2)
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='iondrag',
vector=False,
neuion='neu',
useLT=True,
coastlines=False,
levels=np.linspace(0, 0.05, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0, 0.051, 0.01))
cax.set_xlabel(r'Ion Drag $(m/s^2)$')
plt.savefig(savepath + '3' + ns + 'IonDrag.jpeg')
plt.savefig(savepath + '3' + ns + 'IonDrag.eps')
# vni
if tf[2]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
gtemp[0]['vni'] = \
gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']
gtemp[1]['vni'] = \
gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='vni',
vector=False,
neuion='neu',
useLT=True,
coastlines=False,
levels=np.linspace(0, 0.0002, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0, 0.00021, 0.0001))
cax.set_xlabel(r'$\nu_{ni}$ $(s^{-1})$')
plt.savefig(savepath + '4' + ns + 'vni.jpeg')
plt.savefig(savepath + '4' + ns + 'vni.eps')
# ion convection
if tf[3]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
gtemp[0]['vi'] = np.sqrt(gtemp[0]['V!Di!N (east)']**2 +
gtemp[0]['V!Di!N (north)']**2)
gtemp[1]['vi'] = np.sqrt(gtemp[1]['V!Di!N (east)']**2 +
gtemp[1]['V!Di!N (north)']**2)
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='vi',
vector=True,
neuion='ion',
useLT=True,
coastlines=False,
levels=np.linspace(0, 1000, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0, 1001, 200))
cax.set_xlabel(r'Vi (m/s)')
plt.savefig(savepath + '5' + ns + 'IonV.jpeg')
plt.savefig(savepath + '5' + ns + 'IonV.eps')
# ion density
if tf[4]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='rhoi',
vector=False,
neuion='neu',
useLT=True,
coastlines=False,
levels=np.linspace(0, 12e-15, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0, 12.1e-15, 3e-15))
cax.set_xlabel(r'$\rho_i$ $(kg/m^3)$')
plt.savefig(savepath + '6' + ns + 'Rhoi.jpeg')
plt.savefig(savepath + '6' + ns + 'Rhoi.eps')
# electron density
if tf[5]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
ax, projection, hc, hq = plot_polar_contour_vector(
2,
2,
k + 1,
gtemp[k % 2],
nlat,
slat,
alt,
contour=True,
zstr='e-',
vector=False,
neuion='neu',
useLT=True,
coastlines=False,
levels=np.linspace(0, 0.9e12, 21))
if k in [0, 1]:
ax.scatter(glons,
glats,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(glonn,
glatn,
transform=ccrs.PlateCarree(),
s=55,
c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=55,
c='w',
zorder=100)
if k in [0, 1]:
plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k == 0 else 'Dipole'
plt.text(-0.2,
0.5,
text,
fontsize=14,
verticalalignment='center',
transform=plt.gca().transAxes,
rotation=90)
plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(hc[0],
cax=cax,
orientation='horizontal',
ticks=np.arange(0, 0.31e12, 0.1e12))
cax.set_xlabel(r'Ne ($m^{-3}$)')
# plt.savefig(savepath+'7'+ns+'Ne.jpeg')
# plt.savefig(savepath+'7'+ns+'Ne.eps')
return
def test_convert_lat_failure(self):
"""Test error return for co-latitudes above 90 for an array"""
with pytest.raises(AssertionError):
aacgmv2.convert([91, 60, -91], 0, 300, self.dtime)
def figure1():
plt.close('all')
fig = plt.figure(figsize=(5.41, 8.54))
ax = fig.add_subplot(111, projection='3d')
levels = [np.linspace(6.1e-10, 17.8e-10,21), np.linspace(1.1e-10, 2.7e-10, 21),
np.linspace(1.3e-11, 3.9e-11,21), np.linspace(2.6e-12, 9.503e-12,21),
np.linspace(4.3e-13, 2.71e-12,21), np.linspace(7.4e-14, 8.2e-13,21)]
olat = -40
olatr = np.abs(olat)/180*pi
glats, glons = convert(-90,0,0,date=dt.date(2003,3,22), a2g=True)
glats, glons = glats/180*pi, glons/180*pi
artalt = [10, 200, 380, 540, 680, 820]
realalt = [150, 200, 300, 400, 500, 600]
for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
lat0, lon0 = lat0/180*pi, lon0/180*pi
ilat = lat0[:, 0]<=olat/180*pi
lat0, lon0, rho1 = lat0[ilat,:], lon0[ilat,:], rho1[ilat,:]
r = lat0+pi/2
theta = lon0
x = r*np.cos(theta)
x = -x # for sorthern hemisphere
y = r*np.sin(theta)
v = rho1
print (np.min(v), np.max(v))
ax.contourf(
x, y, v, zdir='z', offset=artalt[ik], levels=levels[ik],
cmap='jet', zorder=100)
ax.scatter(
-(glats+pi/2)*np.cos(glons), (glats+pi/2)*np.sin(glons),
artalt[ik], s=50, c='k', zorder=200)
for rtick in np.arange(10,50,10)/180*pi:
thetatick = np.arange(0, 2*pi, 0.01)
xtick = rtick*np.cos(thetatick)
ytick = rtick*np.sin(thetatick)
hp = ax.plot(
xtick,ytick, artalt[ik], color='0.7',linestyle=':',
zorder = 300, linewidth=0.8)
plt.subplots_adjust(top=1,bottom=0)
ax.set_xlim(-olatr, olatr)
ax.set_ylim(-olatr, olatr)
ax.set_zlim(0,800)
ax.axis('off')
for ik, alt in enumerate(artalt):
ialt = np.argmin(np.abs(g1['Altitude'][0,0,:]/1000-realalt[ik]))
ax.plot([-olatr, -olatr+0.1], [-olatr, -olatr], alt, color='k')
ax.text(-olatr-0.1, -olatr, alt,
'%.0f km'%(g1['Altitude'][0,0,ialt]/1000),
verticalalignment='center')
ax.plot([-olatr, -olatr], [-olatr, -olatr], [artalt[0], artalt[-1]], color='k')
ax.text(-olatr-0.3, 0, artalt[-1], '06', horizontalalignment='center',
zdir='x', zorder=1000)
ax.text(0, -olatr-0.3, artalt[-1], '00', horizontalalignment='center',
zdir='x', zorder=1000)
ax.text(olatr+0.3, 0, artalt[-1], '18', horizontalalignment='center',
zdir='x', zorder=1000)
ax.text(0, olatr+0.3, artalt[-1], '12', horizontalalignment='center',
zdir='x', zorder=1000)
plt.show()
return
def figure4():
plt.close('all')
plt.figure(figsize=(8.28, 9.25))
labels =[('(a)','(b)','(c)'), ('(d)','(e)','(f)'), ('(g)','(h)','(i)')]
qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
ylim = [[0.6e-9,1.6e-9], [1.5e-11, 4e-11], [1e-13, 9e-13]]
for ialt, alt in enumerate([150, 300, 600]):
alt_ind = np.argmin(np.abs(g1['Altitude'][0, 0, 2:-2]/1000-alt))+2
alt_str = '%6.0f' % (g1['Altitude'][0, 0, alt_ind]/1000)
rho1, rho2 = g1['Rho'], g2['Rho']
rhod = 100*(rho1-rho2)/rho2
lats, lons = g1['Latitude'], g1['Longitude']
#----------------------------------------------------------------------
ax, projection = gcc.create_map(
3, 3, ialt+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False, lonticklabel=[1,1,1,1])
# density difference
lon1, lat1, zdata1 = g3ca.contour_data('Rho', g1, alt=alt)
lon2, lat2, zdata2 = g3ca.contour_data('Rho', g2, alt=alt)
fp = (lat1[:,0]>slat) & (lat1[:,0]<nlat)
lon0, lat0 = lon1[fp, :], lat1[fp,:]
zdata0 = (100*(zdata1-zdata2)/zdata2)[fp, :]
print(zdata0.min())
hc = ax.contourf(
lon0, lat0, zdata0, np.linspace(-30,30,21),
transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
# colorbar
gcapos = ax.get_position()
axcb = [
gcapos.x0, gcapos.y0+0.035, gcapos.width, gcapos.height/20]
axcb = plt.axes(axcb)
hcb = plt.colorbar(
hc, cax=axcb, extendrect=True, ticks=np.arange(-30, 31, 15),
orientation='horizontal')
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
lon0, lat0, ewind1-ewind2, nwind1-nwind2, plot_type='polar',
projection=projection)
hq = ax.quiver(
lon0, lat0, ewind0, nwind0, scale=1000, scale_units='inches',
regrid_shape=20, headwidth=5)
ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')
# magnetic pole
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)
latt1 = [-90, nlat]
lont1 = [15*(12-ut), 15*(12-ut)]
ax.plot(lont1, latt1, transform = ccrs.PlateCarree(), c='g')
latt1 = [-90, nlat]
lont1 = [15*(0-ut), 15*(0-ut)]
ax.plot(lont1, latt1, transform = ccrs.PlateCarree(), c='g')
ax.set_title('%s km' % alt_str, y=1.07)
if ialt==0:
ax.text(-0.2, 0.5, r'$\delta \rho$ (%)',
transform=ax.transAxes,rotation=90, fontsize=14,
verticalalignment='center', horizontalalignment='center')
plt.text(
0.05, 0.9, labels[0][ialt],transform=ax.transAxes,color='r')
#----------------------------------------------------------------------
# density in run1 and run2
plt.subplot(3,3,ialt+7)
ilat = (lats[0,:,0]/pi*180<nlat) &(lats[0,:,0]/pi*180>slat)
lt = 12
ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
plt.plot(
180+lats[ilt,ilat,alt_ind]/pi*180,rho1[ilt,ilat,alt_ind], 'r',
label = 'Run 1')
plt.plot(
180+lats[ilt,ilat,alt_ind]/pi*180,rho2[ilt,ilat,alt_ind], 'b',
label = 'Run 2')
plt.legend(loc='upper center')
lat_1, rho_11, rho_12, rho_1d = \
180+lats[ilt,2,alt_ind]/pi*180, rho1[ilt,2, alt_ind], \
rho2[ilt,2, alt_ind], rhod[ilt,2,alt_ind]
lt = 0
ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
plt.plot(-lats[ilt,ilat,alt_ind]/pi*180,rho1[ilt,ilat,alt_ind], 'r')
plt.plot(-lats[ilt,ilat,alt_ind]/pi*180,rho2[ilt,ilat,alt_ind], 'b')
lat_2, rho_21, rho_22, rho_2d = \
-lats[ilt,2,alt_ind]/pi*180, rho1[ilt,2, alt_ind], \
rho2[ilt,2, alt_ind], rhod[ilt,2,alt_ind]
plt.plot([lat_1,lat_2], [rho_11,rho_21], 'r')
plt.plot([lat_1,lat_2], [rho_12,rho_22], 'b')
plt.grid('on')
plt.xlim([-nlat,180+nlat])
plt.ylim(ylim[ialt])
plt.xticks(np.arange(-nlat,181+nlat,30),
np.concatenate(
[np.arange(nlat,-90,-30), np.arange(-90,nlat+1,30)]))
if ialt==0:
plt.ylabel(r'$\rho$ (kg/m$^3$)', fontsize=14)
plt.xlabel('Latitude')
plt.text(
0.05, 0.9, labels[2][ialt],transform=plt.gca().transAxes,color='r')
#----------------------------------------------------------------------
# density difference
plt.subplot(3,3,ialt+4)
lt = 12
ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
plt.plot(
180+lats[ilt,ilat,alt_ind]/pi*180,rhod[ilt,ilat,alt_ind], 'k')
lt = 0
ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
plt.plot(
-lats[ilt,ilat,alt_ind]/pi*180,rhod[ilt,ilat,alt_ind], 'k')
plt.plot([lat_1,lat_2], [rho_1d,rho_2d], 'k')
plt.grid('on')
plt.xlim([-nlat,180+nlat])
plt.xticks(np.arange(-nlat,181+nlat,30),
np.concatenate(
[np.arange(nlat,-90,-30), np.arange(-90,nlat+1,30)]))
plt.ylim(-35, 5)
plt.yticks(np.arange(-30, 0.1, 10))
if ialt==0:
plt.ylabel(r'$\delta\rho$ (%)', fontsize=14)
plt.xlabel('Latitude')
plt.text(
0.05, 0.9, labels[1][ialt],transform=plt.gca().transAxes,color='r')
plt.subplots_adjust(wspace=0.25, hspace=0.25, top=0.95, bottom=0.05)
plt.savefig(savepath+'Figure4.eps')
plt.savefig(savepath+'Figure4.jpeg')
return
def test_warning_below_ground():
with pytest.warns(UserWarning):
aacgmv2.convert(60, 0, -1, dtObj)
with pytest.warns(UserWarning):
aacgmv2.convert(60, 0, [300, -1], dtObj)
def test_convert_maxalt_failure(self):
"""For an array, test failure for an altitude too high for
coefficients"""
with pytest.raises(ValueError):
aacgmv2.convert([60], [0], [2001], self.dtime)
def readDay(hemiSN,
dt,
deltaT=2,
fileType='grdex',
src=None,
fileName=None,
custType='grdex',
noCache=False):
"""Read one day and hemisphere of SuperDARN data
(All of these other options are passed through just_sam to DavitPy)
Parameters
----------
hemiSN: N or S
dt : TYPE
Description
deltaT : int, optional
Description
fileType : str, optional
Description
src : None, optional
Description
fileName : None, optional
Description
custType : str, optional
Description
noCache : bool, optional
Description
Returns
-------
TYPE
Description
"""
#import davitpy.models.aacgm as aacgm
#def _sdGridLoad(sTime,eTime,deltaT,hemi,fileType,src,fileName,custType,noCache,estd=False,TWidth=None):
#SAM uses different hemisphere naming convention
if hemiSN is 'N':
hemi = 'north'
elif hemiSN is 'S':
hemi = 'south'
#Load in data in 2 minute chunks
sdList = _sdGridLoad(dt,
dt + datetime.timedelta(days=1),
deltaT,
hemi,
fileType,
src,
fileName,
custType,
noCache,
estd=False,
TWidth=None)
#Split out data into numpy arrays
#Each sdI is a griddata object from pydarn.sdio.sdDataTypes
startdts, enddts = [], []
mlats, mlons, mltlons, vels, verrs, azms, rids = [], [], [], [], [], [], []
eloss, eerrs = [], [] #Electric fields will be compute inplace
bigrfs = []
for sdI in sdList:
if sdI.vector.mlat is None or sdI.vector.mlon is None:
print sdI.vector
continue
startdts.append(sdI.sTime)
enddts.append(sdI.eTime)
mlat = np.asarray(sdI.vector.mlat)
mlats.append(mlat)
#Do in-band MLT conversion
mlon = np.asarray(sdI.vector.mlon)
y, M, d = sdI.sTime.year, sdI.sTime.month, sdI.sTime.day
h, m, s = sdI.sTime.hour, sdI.sTime.minute, sdI.sTime.second
# mltDef = aacgm.mltFromYmdhms(y,M,d,h,m,s,0.0) * 15.
# mltDef is the rotation that needs to be applied,
# and lon is the AACGM longitude.
# use modulo so new longitude is between 0 & 360
# mlt_lon = np.mod((mlon + mltDef), 360.)
mlt_lon = aacgmv2.convert_mlt(mlon, sdI.sTime, False) ## sishen added
mlons.append(mlon) #Actual mlon
mltlons.append(mlt_lon) #MLT in degrees
#Convert to electric field
vel = np.asarray(sdI.vector.velmedian)
verr = np.asarray(sdI.vector.velsd)
vels.append(vel)
verrs.append(verr)
# Where do superDARN returns come from?
approx_alt = 300.
#Could use either Apex-Python or AACGMv2 package
#for magnetic to geocentric conversion
gdlat, gdlon = aacgmv2.convert(mlat,
mlon,
approx_alt,
date=sdI.sTime,
a2g=True)
#gdlat,gdlon = ac.apex2geo(mlat,mlon,approx_alt)
Be, Bn, Bu = igrfpy.getmainfield(sdI.sTime,
gdlat,
gdlon,
np.ones_like(gdlat) * approx_alt,
geocentric=False,
silent=True)
Bu = np.abs(np.array(Bu)) # It returns lists
# Convert SuperDARN Vlos to E-field
# (Should be using IGRF...just using constant instead)
# Will change after compare with SAM
#Bconst = 0.5e-4
bigrfs.append(Bu * 1.0e-9)
eloss.append(vel * Bu * 1.0e-9)
eerrs.append(verr * Bu * 1.0e-9)
azms.append(np.asarray(sdI.vector.kvect)) #degrees
rids.append(np.asarray(sdI.vector.stid)) #station id num
return (startdts, enddts, mlats, mlons, mltlons, vels, verrs, eloss, eerrs,
azms, rids, bigrfs)
def test_convert_datetime_date(self):
"""Test conversion with date and datetime input"""
self.lat, self.lon = aacgmv2.convert([60], [0], [300], self.ddate)
np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
def test_forbidden():
mlat, mlon = aacgmv2.convert(7, 0, 0)
assert np.isnan(mlat)
assert np.isnan(mlon)
def test_convert_result_values_G2A_coeff():
lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj)
aacgmv2._aacgmv2.setDateTime(*date)
lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, G2A)
assert lat_p == lat_c
assert lon_p == lon_c
def plot_06ut_18ut(ns='SH',alt=150,tf=[1,0,0,0,0,0]):
# 0:rho and wind; 1: diff rho and wind; 2:ion drag; 3:vni; 4:ion convection
# 5:ion density; 6:electron density;
path = '/home/guod/simulation_output/momentum_analysis/run_shrink_dipole_1_c1/UA/data'
fn1 = path+'/3DALL_t030322_060002.bin'
fn2 = path+'/3DALL_t030322_180002.bin'
g11 = [gitm.read(fn1), gitm.read(fn2)] # shrink, dipole
#print(g11[0]['Altitude'][0,0,np.argmin(np.abs(g11[0]['Altitude'][0,0,:]-150*1000))])
path = '/home/guod/simulation_output/momentum_analysis/run_shrink_igrf_1_c1/UA/data'
fn1 = path+'/3DALL_t030322_060002.bin'
fn2 = path+'/3DALL_t030322_180003.bin'
g12 = [gitm.read(fn1), gitm.read(fn2)] # shrink, igrf
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_dipole_1_1/UA/data'
fn1 = path+'/3DALL_t030322_060000.bin'
fn2 = path+'/3DALL_t030322_180001.bin'
g21 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, diple
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/UA/data'
fn1 = path+'/3DALL_t030322_060001.bin'
fn2 = path+'/3DALL_t030322_180002.bin'
g22 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, igrf
if ns == 'SH':
nlat, slat = -50, -90
elif ns == 'NH':
nlat, slat = 90, 50
glats, glons = convert(-90, 0, 0, date=dt.date(2003,1,1), a2g=True)
glatn, glonn = convert(90, 0, 0, date=dt.date(2003,1,1), a2g=True)
fign=['(a)','(b)','(c)','(d)']
# Rho and wind
if tf[0]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='Rho',
vector=True, neuion='neu', useLT=True, coastlines=False,
levels=np.linspace(0.8e-9, 1.6e-9, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.text(
0, 1, fign[k], fontsize=14, transform=plt.gca().transAxes)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0.8e-9, 1.7e-9, 0.2e-9))
cax.set_xlabel(r'$\rho (kg/m^3)$')
plt.quiverkey(hq[0], 0.5,0.12, 500, '500m/s',coordinates='figure')
plt.savefig(savepath+'2'+ns+'RhoWind.jpeg')
plt.savefig(savepath+'2'+ns+'RhoWind.eps')
# ion drag
if tf[1]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
gtemp[0]['iondrag'] = \
gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']*\
np.sqrt((gtemp[0]['V!Di!N (east)']-gtemp[0]['V!Dn!N (east)'])**2 +\
(gtemp[0]['V!Di!N (north)']-gtemp[0]['V!Dn!N (north)'])**2)
gtemp[1]['iondrag'] = \
gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']*\
np.sqrt((gtemp[1]['V!Di!N (east)']-gtemp[1]['V!Dn!N (east)'])**2 +\
(gtemp[1]['V!Di!N (north)']-gtemp[1]['V!Dn!N (north)'])**2)
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='iondrag',
vector=False, neuion='neu', useLT=True, coastlines=False,
levels=np.linspace(0, 0.05, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0, 0.051, 0.01))
cax.set_xlabel(r'Ion Drag $(m/s^2)$')
plt.savefig(savepath+'3'+ns+'IonDrag.jpeg')
plt.savefig(savepath+'3'+ns+'IonDrag.eps')
# vni
if tf[2]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
gtemp[0]['vni'] = \
gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']
gtemp[1]['vni'] = \
gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='vni',
vector=False, neuion='neu', useLT=True, coastlines=False,
levels=np.linspace(0, 0.0002, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0, 0.00021, 0.0001))
cax.set_xlabel(r'$\nu_{ni}$ $(s^{-1})$')
plt.savefig(savepath+'4'+ns+'vni.jpeg')
plt.savefig(savepath+'4'+ns+'vni.eps')
# ion convection
if tf[3]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
gtemp[0]['vi'] = np.sqrt(
gtemp[0]['V!Di!N (east)']**2 + gtemp[0]['V!Di!N (north)']**2)
gtemp[1]['vi'] = np.sqrt(
gtemp[1]['V!Di!N (east)']**2 + gtemp[1]['V!Di!N (north)']**2)
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='vi',
vector=True, neuion='ion', useLT=True, coastlines=False,
levels=np.linspace(0, 1000, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0, 1001, 200))
cax.set_xlabel(r'Vi (m/s)')
plt.savefig(savepath+'5'+ns+'IonV.jpeg')
plt.savefig(savepath+'5'+ns+'IonV.eps')
# ion density
if tf[4]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='rhoi',
vector=False, neuion='neu', useLT=True, coastlines=False,
levels=np.linspace(0, 12e-15, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0, 12.1e-15, 3e-15))
cax.set_xlabel(r'$\rho_i$ $(kg/m^3)$')
plt.savefig(savepath+'6'+ns+'Rhoi.jpeg')
plt.savefig(savepath+'6'+ns+'Rhoi.eps')
# electron density
if tf[5]:
plt.figure(1, figsize=(8, 7.55))
for k in range(4):
gtemp = g22 if k in [0, 1] else g21
calc_rhoi(gtemp[0])
calc_rhoi(gtemp[1])
ax, projection, hc, hq = plot_polar_contour_vector(
2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='e-',
vector=False, neuion='neu', useLT=True, coastlines=False,
levels=np.linspace(0, 0.9e12, 21))
if k in [0, 1]:
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
if k in [0, 1]:
plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
if k in [0, 2]:
text = 'IGRF' if k==0 else 'Dipole'
plt.text(
-0.2, 0.5, text, fontsize=14, verticalalignment='center',
transform=plt.gca().transAxes, rotation=90)
plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
cax = plt.axes([0.3, 0.08, 0.4, 0.02])
plt.colorbar(
hc[0], cax=cax, orientation='horizontal',
ticks=np.arange(0, 0.31e12, 0.1e12))
cax.set_xlabel(r'Ne ($m^{-3}$)')
# plt.savefig(savepath+'7'+ns+'Ne.jpeg')
# plt.savefig(savepath+'7'+ns+'Ne.eps')
return
def figure5_7_refer(alt=300):
times = pd.to_datetime([
'2003-03-22 00:00:00', '2003-03-22 00:30:00', '2003-03-22 01:00:00',
'2003-03-22 02:00:00', '2003-03-22 03:00:00', '2003-03-22 06:00:00'])
plt.close('all')
plt.figure(figsize=(3, 9.25))
ylabel = times.strftime('%H:%M')
qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
for itime, time in enumerate(times):
strtime = time.strftime('%y%m%d_%H%M')
fn1 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_no_shrink_iondrift_4_1/data/3DALL_t%s*.bin' % strtime)
fn2 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_shrink_iondrift_4_c1/data/3DALL_t%s*.bin' % strtime)
g1 = gitm.read(fn1[0])
g2 = gitm.read(fn2[0])
lon1, lat1, alt1, T1 = \
g1['Longitude'], g1['Latitude'], g1['Altitude'], g1['Temperature']
lon2, lat2, alt2, T2 = \
g2['Longitude'], g2['Latitude'], g2['Altitude'], g2['Temperature']
alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
lonticklabel=[0, 1, 0, 1]
if itime == 0:
lonticklabel[0] = 1
if itime == 5:
lonticklabel[2] = 1
ax, projection = gcc.create_map(
6, 1, itime+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False, lonticklabel=lonticklabel)
g1['temp'] = T1-T2
lon0, lat0, zdata0 = g3ca.contour_data('temp', g1, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
hc = ax.contourf(
lon0, lat0, zdata0, levels=np.linspace(-60, 60, 21),
transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(
g1, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(
g2, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
lon0, lat0, ewind1-ewind2, nwind1-nwind2,
plot_type='polar', projection=projection)
hq = ax.quiver(
lon0, lat0, ewind0, nwind0, scale=1500,
scale_units='inches', regrid_shape=20, headwidth=5)
ax.scatter(
qlon, qlat, s=10, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=10, transform=ccrs.PlateCarree(),
zorder=1000)
plt.text(
-0.3, 0.5, ylabel[itime], rotation=90,
transform=ax.transAxes, verticalalignment='center')
if itime==0:
plt.title(r'$T_d$ (K)', y=1.15)
if itime==5:
axp = ax.get_position()
cax = [axp.x0, axp.y0-0.03, axp.x1-axp.x0, 1/20*(axp.y1-axp.y0)]
cax = plt.axes(cax)
ticks = np.arange(-60, 61, 20)
hcb = plt.colorbar(
hc, cax=cax, extendrect=True, orientation='horizontal',
ticks=ticks)
plt.subplots_adjust(wspace=0, hspace=0)
plt.show()
return
def test_convert_datetime_date():
lat_1, lon_1 = aacgmv2.convert(60, 0, 300, dt.date(2013, 12, 1))
lat_2, lon_2 = aacgmv2.convert(60, 0, 300, dt.datetime(2013, 12, 1, 0, 0, 0))
assert lat_1 == lat_2
assert lon_1 == lon_2
def test_convert_time_failure(self):
"""Test conversion with a bad time"""
with pytest.raises(AssertionError):
self.lat, self.lon = aacgmv2.convert([60], [0], [300], None)
lonticklabel=(1, 1, 1, 1))
ax2.scatter(0, -90, color='b', transform=ccrs.PlateCarree())
#geomagnetic coordinates
ax3, projection3 = gcc.create_map(2,
2,
3,
'pol',
90,
50,
0,
coastlines=False,
useLT=True,
dlat=10,
lonticklabel=(1, 1, 1, 1))
mlatn, mlonn = convert(90, 0, 0, date=dt.date(2002, 3, 21))
for k in range(24):
mltn = convert_mlt(mlonn[0], dtime=dt.datetime(2003, 3, 21, k))
ax3.scatter(mltn * 15, mlatn[0], color='r', transform=ccrs.PlateCarree())
ax3.scatter(180, 75, s=50, c='k', marker='x', transform=ccrs.PlateCarree())
ax4, projection4 = gcc.create_map(2,
2,
4,
'pol',
-50,
-90,
0,
coastlines=False,
useLT=True,
dlat=10,
g2 = gitm.read(path2)
fig = plt.figure(figsize=(5.41, 8.54))
ax = fig.add_subplot(111, projection='3d')
levels = [
np.linspace(6.1e-10, 17.8e-10, 21),
np.linspace(1.1e-10, 2.7e-10, 21),
np.linspace(1.3e-11, 3.9e-11, 21),
np.linspace(2.6e-12, 9.503e-12, 21),
np.linspace(4.3e-13, 2.71e-12, 21),
np.linspace(7.4e-14, 8.2e-13, 21)
]
olat = -40
olatr = np.abs(olat) / 180 * np.pi
glats, glons = convert(-90, 0, 0, date=dt.date(2003, 3, 22), a2g=True)
glats, glons = glats / 180 * pi, glons / 180 * pi
artalt = [10, 200, 380, 540, 680, 820]
realalt = [150, 200, 300, 400, 500, 600]
for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
lon0, lat0, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
lat0, lon0 = lat0 / 180 * pi, lon0 / 180 * pi
ilat = lat0[:, 0] <= olat / 180 * np.pi
lat0, lon0, rho1, rho2 = \
lat0[ilat,:], lon0[ilat,:], rho1[ilat,:], rho2[ilat,:]
r = lat0 + pi / 2
theta = lon0
x = r * np.cos(theta)
x = -x # for sorthern hemisphere
dlat=10, lonticklabel=(1, 1, 1, 1))
ax1.plot([45,45],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([225,225],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([105,105],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([285,285],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.scatter(0, 90, color='r', transform=ccrs.PlateCarree(), zorder=10)
ax2, projection2 = gcc.create_map(
2, 2, 2, 'pol', -50, -90, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
ax2.scatter(0, -90, color='b', transform=ccrs.PlateCarree())
#geomagnetic coordinates
ax3, projection3 = gcc.create_map(
2, 2, 3, 'pol', 90, 50, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
mlatn,mlonn = convert(90,0,0,date=dt.date(2002,3,21))
for k in range(24):
mltn = convert_mlt(mlonn[0],dtime=dt.datetime(2003,3,21,k))
ax3.scatter(mltn*15,mlatn[0],color='r',transform=ccrs.PlateCarree())
ax3.scatter(180,75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
ax4, projection4 = gcc.create_map(
2, 2, 4, 'pol', -50, -90, 0, coastlines=False,useLT=True,
dlat=10, lonticklabel=(1, 1, 1, 1))
mlats,mlons = convert(-90,0,0,date=dt.date(2002,3,21))
for k in range(24):
mlts = convert_mlt(mlons[0],dtime=dt.datetime(2003,3,21,k))
ax4.scatter(mlts*15,mlats[0],color='b',transform=ccrs.PlateCarree())
ax4.scatter(180,-75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
plt.savefig('/Users/guod/Documents/Thesis/006SciFig/work3_001.eps')
#plt.show()
def plot_rho_wind_ut(ns='SH', alt=150):
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/data'
fn01 = path+'/3DALL_t030323_000000.bin'
fn02 = path+'/3DALL_t030323_030000.bin'
fn03 = path+'/3DALL_t030323_060001.bin'
fn04 = path+'/3DALL_t030323_090002.bin'
fn05 = path+'/3DALL_t030323_120000.bin'
fn06 = path+'/3DALL_t030323_150001.bin'
fn07 = path+'/3DALL_t030323_180000.bin'
fn08 = path+'/3DALL_t030323_210002.bin'
fn09 = path+'/3DALL_t030324_000000.bin'
fn2 = [fn01, fn02, fn03, fn04, fn05, fn06, fn07, fn08, fn09]
if ns=='SH':
nlat, slat = -50, -90
elif ns=='NH':
nlat, slat = 90, 50
glats, glons = convert(-90, 0, 0, date=dt.date(2003,1,1), a2g=True)
glatn, glonn = convert(90, 0, 0, date=dt.date(2003,1,1), a2g=True)
fig1 = plt.figure(1, figsize=(5.28,8.49))
titf = ['(a)','(b)','(c)','(d)','(e)','(f)','(g)','(h)']
for k in range(8):
g2 = gitm.read(fn2[k])
title = 'UT: '+g2['time'].strftime('%H')
lon2, lat2, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
ilat2 = (lat2[:,0]>=slat) & (lat2[:,0]<=nlat)
min_div_mean = \
np.min(rho2[ilat2, :]) / \
(np.mean(rho2[ilat2, :]*np.cos(lat2[ilat2, :]/180*np.pi)) /\
np.mean(np.cos(lat2[ilat2,:]/180*np.pi)))
print(ns,': ',100*(min_div_mean-1))
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2,'neu',alt=alt)
if k ==0:
lonticklabel = [1, 0, 0, 1]
elif k==1:
lonticklabel = [1, 1, 0, 0]
elif k in [2, 4]:
lonticklabel = [0, 0, 0, 1]
elif k in [3, 5]:
lonticklabel = [0, 1, 0, 0]
elif k==6:
lonticklabel = [0, 0, 1, 1]
elif k==7:
lonticklabel = [0, 1, 1, 0]
olat=False if k<7 else True
# No shrink
plt.figure(1)
centrallon = g3ca.calculate_centrallon(g2, 'pol', useLT=True)
ax, projection = gcc.create_map(
4,2,k+1, 'pol', nlat, slat, centrallon, coastlines=False,
dlat=10, useLT=True, lonticklabel=lonticklabel, olat=olat)
hc1 = ax.contourf(lon2, lat2, rho2, np.linspace(0.8e-9, 1.6e-9),
transform=ccrs.PlateCarree(),cmap='jet', extend='both')
lon9, lat9, ewind9, nwind9 = g3ca.convert_vector(
lon2, lat2, ewind2, nwind2, 'pol', projection)
hq1 = ax.quiver(
lon9,lat9,ewind9,nwind9,scale=1500,scale_units='inches',
regrid_shape=20)
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=35, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=35, c='k')
ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=35, c='w', zorder=100)
ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=35, c='w', zorder=100)
plt.title(titf[k]+' '+title,x=0,y=0.93)
plt.figure(1)
plt.subplots_adjust(
hspace=0.01, wspace=0.01, left=0.05, right=0.95, top=0.95, bottom=0.12)
cax = plt.axes([0.25,0.07,0.5,0.02])
hcb = plt.colorbar(
hc1,cax=cax,orientation='horizontal',ticks=np.arange(0.8,1.7,0.2)*1e-9)
hcb.set_label(r'$\rho$ (kg/$m^3$)')
plt.quiverkey(hq1, 0.5,0.12, 500, '500m/s',coordinates='figure')
plt.savefig(savepath+'1'+ns+'AllUT.eps')
plt.savefig(savepath+'1'+ns+'AllUT.jpeg')
return
def plot_rho_wind_ut(ns='SH', alt=150):
path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/data'
fn01 = path + '/3DALL_t030323_000000.bin'
fn02 = path + '/3DALL_t030323_030000.bin'
fn03 = path + '/3DALL_t030323_060001.bin'
fn04 = path + '/3DALL_t030323_090002.bin'
fn05 = path + '/3DALL_t030323_120000.bin'
fn06 = path + '/3DALL_t030323_150001.bin'
fn07 = path + '/3DALL_t030323_180000.bin'
fn08 = path + '/3DALL_t030323_210002.bin'
fn09 = path + '/3DALL_t030324_000000.bin'
fn2 = [fn01, fn02, fn03, fn04, fn05, fn06, fn07, fn08, fn09]
if ns == 'SH':
nlat, slat = -50, -90
elif ns == 'NH':
nlat, slat = 90, 50
glats, glons = convert(-90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
glatn, glonn = convert(90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
fig1 = plt.figure(1, figsize=(5.28, 8.49))
titf = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)', '(g)', '(h)']
for k in range(8):
g2 = gitm.read(fn2[k])
title = 'UT: ' + g2['time'].strftime('%H')
lon2, lat2, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
ilat2 = (lat2[:, 0] >= slat) & (lat2[:, 0] <= nlat)
min_div_mean = \
np.min(rho2[ilat2, :]) / \
(np.mean(rho2[ilat2, :]*np.cos(lat2[ilat2, :]/180*np.pi)) /\
np.mean(np.cos(lat2[ilat2,:]/180*np.pi)))
print(ns, ': ', 100 * (min_div_mean - 1))
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2, 'neu', alt=alt)
if k == 0:
lonticklabel = [1, 0, 0, 1]
elif k == 1:
lonticklabel = [1, 1, 0, 0]
elif k in [2, 4]:
lonticklabel = [0, 0, 0, 1]
elif k in [3, 5]:
lonticklabel = [0, 1, 0, 0]
elif k == 6:
lonticklabel = [0, 0, 1, 1]
elif k == 7:
lonticklabel = [0, 1, 1, 0]
olat = False if k < 7 else True
# No shrink
plt.figure(1)
centrallon = g3ca.calculate_centrallon(g2, 'pol', useLT=True)
ax, projection = gcc.create_map(4,
2,
k + 1,
'pol',
nlat,
slat,
centrallon,
coastlines=False,
dlat=10,
useLT=True,
lonticklabel=lonticklabel,
olat=olat)
hc1 = ax.contourf(lon2,
lat2,
rho2,
np.linspace(0.8e-9, 1.6e-9),
transform=ccrs.PlateCarree(),
cmap='jet',
extend='both')
lon9, lat9, ewind9, nwind9 = g3ca.convert_vector(
lon2, lat2, ewind2, nwind2, 'pol', projection)
hq1 = ax.quiver(lon9,
lat9,
ewind9,
nwind9,
scale=1500,
scale_units='inches',
regrid_shape=20)
ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=35, c='k')
ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=35, c='k')
ax.scatter(0,
90,
transform=ccrs.PlateCarree(),
s=35,
c='w',
zorder=100)
ax.scatter(0,
-90,
transform=ccrs.PlateCarree(),
s=35,
c='w',
zorder=100)
plt.title(titf[k] + ' ' + title, x=0, y=0.93)
plt.figure(1)
plt.subplots_adjust(hspace=0.01,
wspace=0.01,
left=0.05,
right=0.95,
top=0.95,
bottom=0.12)
cax = plt.axes([0.25, 0.07, 0.5, 0.02])
hcb = plt.colorbar(hc1,
cax=cax,
orientation='horizontal',
ticks=np.arange(0.8, 1.7, 0.2) * 1e-9)
hcb.set_label(r'$\rho$ (kg/$m^3$)')
plt.quiverkey(hq1, 0.5, 0.12, 500, '500m/s', coordinates='figure')
plt.savefig(savepath + '1' + ns + 'AllUT.eps')
plt.savefig(savepath + '1' + ns + 'AllUT.jpeg')
return
path1 = '/home/guod/simulation_output/momentum_analysis/'+\
'run_shrink_iondrift_4_c1/data/3DALL_t030322_060000.bin'
path2 = '/home/guod/simulation_output/momentum_analysis/'+\
'run_no_shrink_iondrift_4_1/data/3DALL_t030322_060000.bin'
g1 = gitm.read(path1)
g2 = gitm.read(path2)
fig = plt.figure(figsize=(5.41, 8.54))
ax = fig.add_subplot(111, projection='3d')
levels = [np.linspace(6.1e-10, 17.8e-10,21), np.linspace(1.1e-10, 2.7e-10, 21),
np.linspace(1.3e-11, 3.9e-11,21), np.linspace(2.6e-12, 9.503e-12,21),
np.linspace(4.3e-13, 2.71e-12,21), np.linspace(7.4e-14, 8.2e-13,21)]
olat = -40
olatr = np.abs(olat)/180*np.pi
glats, glons = convert(-90,0,0,date=dt.date(2003,3,22), a2g=True)
glats, glons = glats/180*pi, glons/180*pi
artalt = [10, 200, 380, 540, 680, 820]
realalt = [150, 200, 300, 400, 500, 600]
for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
lon0, lat0, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
lat0, lon0 = lat0/180*pi, lon0/180*pi
ilat = lat0[:, 0]<=olat/180*np.pi
lat0, lon0, rho1, rho2 = \
lat0[ilat,:], lon0[ilat,:], rho1[ilat,:], rho2[ilat,:]
r = lat0+pi/2
theta = lon0
x = r*np.cos(theta)
x = -x # for sorthern hemisphere