def test_getDststarTuple(self):
"""getDststar should give known results from tuple input (regression)"""
real_ans = np.array([ 6.39592274, 7.5959423 , -2.44532089, 16.2867821 ,
11.01399987, 17.01362653, 13.6810416 , -34.3206288 ,
-12.22368788, 1.03764047, -9.03424456])
ans = em.getDststar(self.ticks, model=(7.26, 11), dbase='Test')
np.testing.assert_almost_equal(real_ans, ans)
def test_getDststarError(self):
"""getDststar should give known exceptions on bad input"""
real_ans = np.array([-30.80228229, -26.85289053, -11.2457748 , -17.98012397,
-16.1640001 , -13.64888467, -14.75155876, -10.43928609,
-21.22360883, -8.49354146, -3.29620967])
ans = em.getDststar(self.ticks, dbase='Test')
self.assertRaises(ValueError, em.getDststar, self.ticks, model='bad')
self.assertRaises(ValueError, em.getDststar, self.ticks, model={'a':7.26, 'b':11})
def initialSW():
"""Construct initial estimate of hourly solar wind parameters"""
st = dt.datetime(1989, 3, 12)
en = dt.datetime(1989, 3, 15)
hourly = getKondrashovSW()
# Keep IMF By and n, set V to Boteler/Nagatsuma
t_ssc1 = dt.datetime(1989, 3, 13, 1, 27)
t_ssc2 = dt.datetime(1989, 3, 13, 7, 43)
t_cme = dt.datetime(1989, 3, 13, 16)
t_turn = dt.datetime(1989, 3, 14, 2)
# Set Bx positive, in accordance with ISEE-3 data, Vy/Vz->0
hourly['Bx'] = dm.dmfilled(hourly['By'].shape, fillval=3)
hourly['Vy'] = dm.dmfilled(hourly['By'].shape, fillval=0)
hourly['Vz'] = dm.dmfilled(hourly['By'].shape, fillval=0)
# Before first SSC
inds_before_1 = tb.tOverlapHalf([dt.datetime(1989, 3, 12), t_ssc1],
hourly['DateTime'])
hourly['V_sw'][inds_before_1] = 400
# Between first and ssecond SSC
inds_between_12 = tb.tOverlapHalf([t_ssc1, t_ssc2], hourly['DateTime'])
hourly['V_sw'][inds_between_12] = 550
# IMF turns north around 1989-03-14T02:00:00 according to inverse Burton and Kondrashov
inds_mainphase = tb.tOverlapHalf([t_ssc2, t_turn], hourly['DateTime'])
hourly['V_sw'][inds_mainphase] = 983
# Then have speed decay towards IMP-8 measurement which is ballpark 820 km/s
inds_rest = tb.tOverlapHalf([t_turn, hourly['DateTime'][-1]],
hourly['DateTime'])
hourly['V_sw'][inds_rest] = np.linspace(983, 820, len(inds_rest))
# Now we have speed, estimate temperature
hourly['Plasma_temp'] = emp.getExpectedSWTemp(hourly['V_sw'],
model='XB15',
units='K')
inds_cme = tb.tOverlapHalf([t_cme, en], hourly['DateTime'])
hourly['Plasma_temp'][
inds_cme] /= 3 # reduce by factor of 3 for CME-like temp
# Get "Kondrashov VBs" using V from Boteler/Nagatsuma
hourly['VBs_K'] = 1e-3 * hourly['V_sw'] * rectify(
-1 * hourly['Bz']) # mV/m
# Now get VBs from inverse Burton
ky_dat = kyo.fetch('dst', (st.year, st.month, st.day),
(en.year, en.month, en.day))
inds = tb.tOverlapHalf([st, en], ky_dat['time'])
# Pressure correct here using n and V
hourly = calc_P(hourly)
hourly['Dst'] = ky_dat['dst'][inds]
dst_star = emp.getDststar(hourly, model='OBrien')
hourly['VBs_OB'] = 1e-3 * inverseOBrienMcPherron(dst_star)
# Make new Bz from VBs_OB
hourly['Bz_OB'] = -1e3 * hourly['VBs_OB'] / hourly['V_sw'] # nT
return hourly
def test_getDststarOmnivals(self):
"""getDststar should give known result using omnival dict input"""
dst, pdyn = -10.0, 5.0
real_ans = dst - np.sqrt(pdyn)
ans = em.getDststar({'Pdyn': pdyn, 'Dst': dst}, model=(1,0))
np.testing.assert_almost_equal(real_ans, ans)
def makeSW_v2():
"""Construct initial estimate of hourly solar wind parameters"""
st = dt.datetime(1989, 3, 12)
en = dt.datetime(1989, 3, 15)
hourly = getKondrashovSW()
# Keep IMF By and n, set V to Boteler/Nagatsuma
t_ssc1 = dt.datetime(1989, 3, 13, 1, 27)
t_ssc2 = dt.datetime(1989, 3, 13, 7, 43)
t_cme = dt.datetime(1989, 3, 13, 16)
t_turn = dt.datetime(1989, 3, 14, 2)
# Set Bx positive, in accordance with ISEE-3 data, Vy/Vz->0
hourly['Bx'] = dm.dmfilled(hourly['By'].shape, fillval=3)
hourly['Vy'] = dm.dmfilled(hourly['By'].shape, fillval=0)
hourly['Vz'] = dm.dmfilled(hourly['By'].shape, fillval=0)
# Before first SSC
inds_before_1 = tb.tOverlapHalf([dt.datetime(1989, 3, 12), t_ssc1],
hourly['DateTime'])
hourly['V_sw'][inds_before_1] = 400
# Between first and ssecond SSC
inds_between_12 = tb.tOverlapHalf([t_ssc1, t_ssc2], hourly['DateTime'])
hourly['V_sw'][inds_between_12] = 550
# IMF turns north around 1989-03-14T02:00:00 according to inverse Burton and Kondrashov
inds_mainphase = tb.tOverlapHalf([t_ssc2, t_turn], hourly['DateTime'])
hourly['V_sw'][inds_mainphase] = 983
# Then have speed decay towards IMP-8 measurement which is ballpark 820 km/s
inds_rest = tb.tOverlapHalf([t_turn, hourly['DateTime'][-1]],
hourly['DateTime'])
hourly['V_sw'][inds_rest] = np.linspace(983, 820, len(inds_rest))
# Now we have speed, estimate temperature
hourly['Plasma_temp'] = emp.getExpectedSWTemp(hourly['V_sw'],
model='XB15',
units='K')
inds_cme = tb.tOverlapHalf([t_cme, en], hourly['DateTime'])
hourly['Plasma_temp'][
inds_cme] /= 3 # reduce by factor of 3 for CME-like temp
# Get "Kondrashov VBs" using V from Boteler/Nagatsuma
hourly['VBs_K'] = 1e-3 * hourly['V_sw'] * rectify(
-1 * hourly['Bz']) # mV/m
# Now get VBs from inverse Burton
ky_dat = kyo.fetch('dst', (st.year, st.month, st.day),
(en.year, en.month, en.day))
inds = tb.tOverlapHalf([st, en], ky_dat['time'])
# Substitute density curve from Sept. 2017 (double shock)
sep17 = pybats.ImfInput(
filename=
'/home/smorley/projects/github/advect1d/IMF_201709_advect_filt.dat',
load=True)
den_inds = tb.tOverlapHalf(
[t_ssc1 - dt.timedelta(hours=25), hourly['DateTime'][-1]],
hourly['DateTime'])
nhours = len(den_inds)
# Keep the opening 8 hours from Kondrashov (2017 event gets high)
hourly['Den_P'][den_inds[9:]] = 2 + (sep17['rho'][::60][9:nhours] * 2)
# After shocks, ensure number density doesn't drop below 10 (keeps M_A over 2)
after_ssc2 = hourly['DateTime'] > t_ssc2
under_lim = hourly['Den_P'] <= 10
limit_inds = np.logical_and(after_ssc2, under_lim)
hourly['Den_P'][limit_inds] = 10
# Pressure correct here using n and V
hourly = calc_P(hourly)
hourly['Dst'] = ky_dat['dst'][inds]
dst_star = emp.getDststar(hourly, model='OBrien')
hourly['VBs_OB'] = 1e-3 * inverseOBrienMcPherron(dst_star)
# Make new Bz from VBs_OB
hourly['Bz_OB'] = -1e3 * hourly['VBs_OB'] / hourly['V_sw'] # nT
return hourly
