return flux
if __name__== "__main__":
# -------------- Here's how to create a satellite and take some flux measurements: -------------
#GLD_root = 'alex/array/home/Vaisala/feed_data/GLD'
#NLDN_root = 'alex/array/home/Vaisala/feed_data/NLDN'
GLD_root = 'GLD'
sat_TLE = ["1 40378U 15003C 15293.75287141 .00010129 00000-0 48835-3 0 9990",
"2 40378 99.1043 350.5299 0153633 201.4233 158.0516 15.09095095 39471"]
# Satellite object:
sat = Satellite(sat_TLE[0], sat_TLE[1],'Firebird 4')
# Measurement object:
f = measurement_model(database = "database_dicts.pkl", GLD_root = GLD_root, multiple_bands = True)
# ---- Do The Thing:
inTime = "2015-11-01T00:45:00"
plottime = datetime.datetime.strptime(inTime, "%Y-%m-%dT%H:%M:%S")
sat.compute(plottime)
sat.coords.transform_to('geomagnetic')
# bands is a list of energy bands to sample at (depending on database, 1 thru 8)
print "From banded measurement (all on):"
print f.get_measurement(plottime, sat.coords, mode='banded',bands=f.m.E_bands)
print "From single measurement:"
print f.get_measurement(plottime, sat.coords, mode='continuous',bands=f.m.E_bands)
odb['gActs'] = gActs
odb['previous_measurements'] = previous_measurements
odb['stored_policy'] = stored_policy
odb['num_lats'] = num_lats
odb['num_lons'] = num_lons
odb['num_times']= num_times
with open(outDir + '/odb.pkl','wb') as file:
pickle.dump(odb, file)
sat.compute(cur_time)
# Get time scaling weights:
time_weight = get_time_scaling(gTimes, sat.coords, cur_time)
sat.coords.transform_to('geomagnetic')
# Get distance interpolating weights:
map_weights = get_map_scaling(gLats, gLons, sat.coords, Rmax=smoothing_radius)
# 3d weight (lat, lon, time):
W = map_weights[:,:,None]*time_weight
print "W isnans: ",np.sum(np.isnan(W))
print "Q isnans: ",np.sum(np.isnan(Q))
action = gActs[0]
print "Starting run from ", cur_time
ind = 0 # iteration counter