AEBS - AEJxLPL_2F and AEJxPBL_2F products - long-term temporal development¶
Demonstration of AEJxLPL_2F and AEJxPBL_2F products.
Feel free to change the SPACECRAFT, START_TIME, and END_TIME paramteres and re-run the notebook.
The notebook retrieves and displays data for the selected satellite and time range.
In [1]:
#------------------------------------------------------------------------------
# User input:
SPACECRAFT = 'A'
START_TIME = '2015-06-15T00:00:00Z'
END_TIME = '2015-06-30T00:00:00Z'
SERVER_URL = 'https://staging.viresdisc.vires.services/ows'
#------------------------------------------------------------------------------
from viresclient import SwarmRequest
from viresclient._wps.time_util import parse_datetime
# point types
MASK_EJ_TYPE = PT_EEJ = 0x1
MASK_POINT_TYPE = PT_BOUNDARY = 0x2
MASK_BOUNDARY_TYPE = PT_POLAR = 0x4
MASK_BOUNDARY_FLAG = PT_END = 0x8
PT_WEJ = PT_PEAK = PT_EQUATORIAL = PT_START = 0x0
SwarmRequest.COLLECTIONS.update({
'AEJ_LPL': ['SW_OPER_AEJ{}LPL_2F'.format(x) for x in 'ABC'],
'AEJ_PBL': ['SW_OPER_AEJ{}PBL_2F'.format(x) for x in 'ABC'],
})
SwarmRequest.PRODUCT_VARIABLES.update({
'AEJ_LPL': [
'Latitude_QD', 'Longitude_QD', 'MLT_QD',
'J_NE', 'J_QD',
],
'AEJ_PBL': [
'Latitude_QD', 'Longitude_QD', 'MLT_QD',
'J_QD', 'Flags', 'PointType',
],
})
try:
request = SwarmRequest(SERVER_URL)
start_orbit_number = request.get_orbit_number(SPACECRAFT, parse_datetime(START_TIME))
end_orbit_number = request.get_orbit_number(SPACECRAFT, parse_datetime(END_TIME))
start_time, end_time = request.get_times_for_orbits(SPACECRAFT, start_orbit_number, end_orbit_number)
print('Spacecraft: %s' % SPACECRAFT)
print('Orbit number range: %s-%s' % (start_orbit_number, end_orbit_number))
print('Start time: ', start_time)
print('End time: ', end_time)
# retrieve latitude profiles
request.set_collection('SW_OPER_AEJ%sLPL_2F' % SPACECRAFT)
request.set_products(
measurements=['Latitude_QD', 'MLT_QD', 'J_QD'],
auxiliaries=['QDOrbitDirection', 'OrbitNumber'],
sampling_step="PT5S",
)
response = request.get_between(
start_time=start_time,
end_time=end_time,
asynchronous=False,
)
print('Sources:\n\t%s' % '\n\t'.join(response.sources))
profile = response.as_xarray()
# retrieve peeks and boundaries
request.set_collection('SW_OPER_AEJ%sPBL_2F' % SPACECRAFT)
request.set_products(
measurements=['Latitude_QD', 'MLT_QD', 'J_QD', 'Flags', 'PointType'],
auxiliaries=['QDOrbitDirection', 'OrbitNumber', 'Kp'],
)
response = request.get_between(
start_time=start_time,
end_time=end_time,
asynchronous=False,
)
print('Sources:\n\t%s' % '\n\t'.join(response.sources))
boundaries = response.as_xarray()
except Exception as error:
print('ERROR: ', error)
else:
print(profile)
print(boundaries)
Spacecraft: A Orbit number range: 8727-8958 Start time: 2015-06-14 22:29:27.654007 End time: 2015-06-30 00:42:12.227101
Downloading: 100%|██████████| [ Elapsed: 00:00, Remaining: 00:00 ] (2.063MB)
Sources: SW_OPER_AEJALPL_2F_20150614T000000_20150614T235959_0101 SW_OPER_AEJALPL_2F_20150615T000000_20150615T235959_0101 SW_OPER_AEJALPL_2F_20150616T000000_20150616T235959_0101 SW_OPER_AEJALPL_2F_20150617T000000_20150617T235959_0101 SW_OPER_AEJALPL_2F_20150618T000000_20150618T235959_0101 SW_OPER_AEJALPL_2F_20150619T000000_20150619T235959_0101 SW_OPER_AEJALPL_2F_20150620T000000_20150620T235959_0101 SW_OPER_AEJALPL_2F_20150621T000000_20150621T235959_0101 SW_OPER_AEJALPL_2F_20150622T000000_20150622T235959_0101 SW_OPER_AEJALPL_2F_20150623T000000_20150623T235959_0101 SW_OPER_AEJALPL_2F_20150624T000000_20150624T235959_0101 SW_OPER_AEJALPL_2F_20150625T000000_20150625T235959_0101 SW_OPER_AEJALPL_2F_20150626T000000_20150626T235959_0101 SW_OPER_AEJALPL_2F_20150627T000000_20150627T235959_0101 SW_OPER_AEJALPL_2F_20150628T000000_20150628T235959_0101 SW_OPER_AEJALPL_2F_20150629T000000_20150629T235959_0101 SW_OPER_AEJALPL_2F_20150630T000000_20150630T235959_0101 SW_OPER_AUXAORBCNT_20131122T000000_20200625T000000_0001 SW_OPER_MAGA_LR_1B_20150614T000000_20150614T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150615T000000_20150615T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150616T000000_20150616T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150617T000000_20150617T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150618T000000_20150618T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150619T000000_20150619T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150620T000000_20150620T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150621T000000_20150621T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150622T000000_20150622T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150623T000000_20150623T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150624T000000_20150624T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150625T000000_20150625T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150626T000000_20150626T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150627T000000_20150627T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150628T000000_20150628T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150629T000000_20150629T235959_0505_MDR_MAG_LR SW_OPER_MAGA_LR_1B_20150630T000000_20150630T235959_0505_MDR_MAG_LR
Downloading: 100%|██████████| [ Elapsed: 00:00, Remaining: 00:00 ] (0.38MB)
Sources:
SW_OPER_AEJAPBL_2F_20150101T000000_20151231T235959_0101
SW_OPER_AUXAORBCNT_20131122T000000_20200625T000000_0001
SW_OPER_AUX_KP__2__19980101T013000_20200625T043000_0001
SW_OPER_MAGA_LR_1B_20150614T000000_20150614T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150615T000000_20150615T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150616T000000_20150616T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150617T000000_20150617T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150618T000000_20150618T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150619T000000_20150619T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150620T000000_20150620T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150621T000000_20150621T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150622T000000_20150622T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150623T000000_20150623T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150624T000000_20150624T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150625T000000_20150625T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150626T000000_20150626T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150627T000000_20150627T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150628T000000_20150628T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150629T000000_20150629T235959_0505_MDR_MAG_LR
SW_OPER_MAGA_LR_1B_20150630T000000_20150630T235959_0505_MDR_MAG_LR
<xarray.Dataset>
Dimensions: (Timestamp: 36830)
Coordinates:
* Timestamp (Timestamp) datetime64[ns] 2015-06-14T22:43:15.741726637 ... 2015-06-30T00:31:54.622179747
Data variables:
Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
QDOrbitDirection (Timestamp) int8 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1
Latitude (Timestamp) float64 53.05 54.05 55.05 ... -40.45 -39.45
J_QD (Timestamp) float64 14.15 16.77 19.61 ... -13.54 -12.49
Latitude_QD (Timestamp) float64 50.61 51.63 52.67 ... -51.34 -50.25
OrbitNumber (Timestamp) int32 8727 8727 8727 8727 ... 8958 8958 8958
Longitude (Timestamp) float64 -163.3 -163.2 -163.1 ... 143.5 143.6
MLT_QD (Timestamp) float64 11.42 11.41 11.4 ... 10.65 10.64 10.63
Attributes:
Sources: ['SW_OPER_AEJALPL_2F_20150614T000000_20150614T235959_010...
MagneticModels: []
RangeFilters: []
<xarray.Dataset>
Dimensions: (Timestamp: 5568)
Coordinates:
* Timestamp (Timestamp) datetime64[ns] 2015-06-14T22:45:23.191929579 ... 2015-06-30T00:31:54.622179747
Data variables:
Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
Flags (Timestamp) uint8 0 0 0 0 0 0 8 ... 132 17 17 17 17 17 17
Latitude (Timestamp) float64 61.2 77.92 81.21 ... -67.43 nan -39.45
QDOrbitDirection (Timestamp) int8 1 1 1 1 1 1 -1 -1 ... -1 -1 1 1 1 1 1 1
J_QD (Timestamp) float64 nan 107.9 nan nan ... -21.73 nan nan
Latitude_QD (Timestamp) float64 59.11 76.99 80.45 ... nan -50.25
OrbitNumber (Timestamp) int32 8727 8727 8727 8727 ... 8958 8958 8958
PointType (Timestamp) uint16 3 1 15 2 0 14 7 1 ... 14 3 6 1 0 15 10
Kp (Timestamp) float64 2.7 2.7 2.7 2.7 ... 1.0 1.0 1.0 1.0
Longitude (Timestamp) float64 -162.5 -155.9 -151.2 ... nan 143.6
MLT_QD (Timestamp) float64 11.31 10.61 10.16 ... 11.76 nan 10.63
Attributes:
Sources: ['SW_OPER_AEJAPBL_2F_20150101T000000_20151231T235959_010...
MagneticModels: []
RangeFilters: []
In [2]:
from numpy import stack
from matplotlib.pyplot import figure, subplot, show, colorbar
import matplotlib.cm as color_map
from matplotlib.colors import Normalize
%matplotlib inline
def halign_axes(ax, ax_ref):
"Align axes horizontally."
pos_ref = ax_ref.get_position()
pos = ax.get_position()
ax.set_position([pos_ref.x0, pos.y0, pos_ref.width, pos.height])
def _orbit_lat(latitude, orbit_direction):
orbit_latitude = latitude.copy()
mask = orbit_direction == -1
orbit_latitude[mask] = 180 - latitude[mask]
orbit_latitude[orbit_latitude > 180] -= 360
return orbit_latitude
def _get_pair_indices(time, pair_indicator):
idx_start = (pair_indicator == PI_START).nonzero()[0]
idx_stop = (pair_indicator == PI_STOP).nonzero()[0]
if idx_start.size > 0 and idx_stop.size > 0:
if time[idx_start[0]] > time[idx_stop[0]]:
idx_stop = idx_stop[1:]
if time[idx_start[-1]] > time[idx_stop[-1]]:
idx_start = idx_start[:-1]
assert idx_start.size == idx_start.size
return stack((idx_start, idx_stop), axis=1)
def _periodic_qd_plot(ax, is_north):
if is_north:
ylim = [45, 135]
yticks = [45, 60, 75, 90, 105, 120, 135]
ylabels = ['+45\u00B0\u2191', '+60\u00B0\u2191', '+75\u00B0\u2191', '+90\u00B0', '+75\u00B0\u2193', '+60\u00B0\u2193', '+45\u00B0\u2193']
else:
ylim = [-135, -45]
yticks = [-135, -120, -105, -90, -75, -60, -45]
ylabels = ['\u221245\u00B0\u2193', '\u221260\u00B0\u2193', '\u221275\u00B0\u2193', '\u221290\u00B0', '\u221275\u00B0\u2191', '\u221260\u00B0\u2191', '\u221245\u00B0\u2191']
ax.set_ylim(ylim)
ax.set_yticks(yticks)
ax.set_yticklabels(ylabels)
def plot_j_df(ax, is_north=True, jmax=600):
p_time = profile['Timestamp'].values
p_j_df = profile['J_QD'].values
p_lat_qd = _orbit_lat(
profile['Latitude_QD'].values,
profile['QDOrbitDirection'].values
)
b_mask = boundaries['PointType'].values & MASK_POINT_TYPE == PT_BOUNDARY
b_time = boundaries['Timestamp'].values[b_mask]
b_j_df = boundaries['J_QD'].values[b_mask]
b_lat_qd = _orbit_lat(
boundaries['Latitude_QD'].values[b_mask],
boundaries['QDOrbitDirection'].values[b_mask]
)
l_j_df = ax.scatter(p_time, p_lat_qd, c=p_j_df, s=2, cmap=color_map.RdBu, norm=Normalize(-jmax, jmax))
l_b = ax.plot(b_time, b_lat_qd, '_', c='tab:green', ms=3)
cax = colorbar(l_j_df)
cax.ax.set_ylabel("J [A/km]")
ax.grid()
ax.set_ylabel('QD-latitude')
ax.set_xlim(start_time, end_time)
_periodic_qd_plot(ax, is_north)
return ax
def plot_mlt(ax, is_north=True):
p_time = profile['Timestamp'].values
p_mlt = profile['MLT_QD'].values % 24
p_lat_qd = _orbit_lat(
profile['Latitude_QD'].values,
profile['QDOrbitDirection'].values
)
l_mlt = ax.scatter(p_time, p_lat_qd, c=p_mlt, s=2, cmap=color_map.twilight_shifted, norm=Normalize(0, 24))
cax = colorbar(l_mlt)
cax.ax.set_ylabel("MLT [hour]")
cax.set_ticks([0, 6, 12, 18, 24])
ax.grid()
ax.set_ylabel('QD-latitude')
ax.set_xlim(start_time, end_time)
_periodic_qd_plot(ax, is_north)
return ax
def plot_kp(ax, is_north=True):
b_time = boundaries['Timestamp'].values
b_kp = boundaries['Kp'].values
ax.plot(b_time, b_kp)
ax.grid()
ax.set_yticks(range(0, 10))
ax.set_ylim([-0.5, 9.5])
ax.set_xlim(start_time, end_time)
ax.set_ylabel('Kp index')
return ax
fig = figure(figsize=(18, 18), dpi=100)
jmax = 600 #A/km
ax_jn = plot_j_df(subplot(511), is_north=True, jmax=jmax)
ax_mn = plot_mlt(subplot(512), is_north=True)
ax_js = plot_j_df(subplot(513), is_north=False, jmax=jmax)
ax_ms = plot_mlt(subplot(514), is_north=False)
ax_kp = plot_kp(subplot(515))
halign_axes(ax_mn, ax_jn)
halign_axes(ax_js, ax_jn)
halign_axes(ax_ms, ax_jn)
halign_axes(ax_kp, ax_jn)
/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:17: RuntimeWarning: invalid value encountered in greater /opt/conda/lib/python3.7/site-packages/pandas/plotting/_matplotlib/converter.py:103: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters. To register the converters: >>> from pandas.plotting import register_matplotlib_converters >>> register_matplotlib_converters() warnings.warn(msg, FutureWarning)
