def example2():
"""
Plot difference between modelled and observed field strength using Swarm A
data in August 2018 from a cdf-file.
"""
import cdflib
model = load_CHAOS_matfile(FILEPATH_CHAOS)
print(model)
cdf_file = cdflib.CDF(
'data/SW_OPER_MAGA_LR_1B_'
'20180801T000000_20180801T235959'
'_PT15S.cdf', 'r')
# print(cdf_file.cdf_info()) # print cdf info/contents
radius = cdf_file.varget('Radius') / 1000 # km
theta = 90. - cdf_file.varget('Latitude') # colat deg
phi = cdf_file.varget('Longitude') # deg
time = cdf_file.varget('Timestamp') # milli seconds since year 1
time = time / (1e3 * 3600 *
24) - 730485 # time in modified Julian date 2000
F_swarm = cdf_file.varget('F')
cdf_file.close()
theta_gsm, phi_gsm = transform_points(theta,
phi,
time=time,
reference='gsm')
index_day = np.logical_and(phi_gsm < 90, phi_gsm > -90)
index_night = np.logical_not(index_day)
# complete forward computation: pre-built not customizable (see ex. 1)
B_radius, B_theta, B_phi = model(time, radius, theta, phi)
# compute field strength and plot together with data
F = np.sqrt(B_radius**2 + B_theta**2 + B_phi**2)
print('RMSE of F: {:.5f} nT'.format(np.std(F - F_swarm)))
plt.scatter(theta_gsm[index_day],
F_swarm[index_day] - F[index_day],
s=0.5,
c='r',
label='dayside')
plt.scatter(theta_gsm[index_night],
F_swarm[index_night] - F[index_night],
s=0.5,
c='b',
label='nightside')
plt.xlabel('dipole colatitude ($^\\circ$)')
plt.ylabel('$\\mathrm{d} F$ (nT)')
plt.legend(loc=2)
plt.show()
def test_geo_to_gsm(self):
time = np.linspace(1, 100, 10)
theta_geo = np.linspace(1, 179, 10)
phi_geo = np.linspace(-180, 179, 10)
# load matfile
test = load_matfile(MATFILE_PATH, 'test_geo_to_gsm')
# reduce 2-D matrix to 1-D vectors
theta_gsm_mat = np.ravel(test['theta_gsm'])
phi_gsm_mat = np.ravel(test['phi_gsm'])
theta_gsm, phi_gsm = c.transform_points(
theta_geo, phi_geo, time=time, reference='gsm')
self.assertIsNone(np.testing.assert_allclose(theta_gsm, theta_gsm_mat))
self.assertIsNone(np.testing.assert_allclose(phi_gsm, phi_gsm_mat))