def getENUTrackDict(start,stop,hour_window = 12,flights_of_interest=[]):
'''
This will return a dict with the trajectories of each plane observed in the
period of time specified (given in UTC timestamps).
'''
unique_flights,all_vals = getTracks(start,stop,hour_window=hour_window)
if numpy.size(flights_of_interest) != 0:
unique_flights = [u.replace(' ','') for u in unique_flights]
all_vals[:,0] = [u.replace(' ','') for u in all_vals[:,0]]
unique_flights = unique_flights[numpy.isin(unique_flights,flights_of_interest)]
all_vals = all_vals[numpy.isin(all_vals[:,0],flights_of_interest),:]
if numpy.size(all_vals) != 0:
lat = all_vals[:,2].astype(float)
lon = all_vals[:,3].astype(float)
alt = all_vals[:,4].astype(float)*0.3048 #Expressing alt in meters now.
timestamps = all_vals[:,1].astype(float)
flight_tracks_ENU = {}
origin = info.loadAntennaZeroLocation(deploy_index = 1) #Antenna 0
for unique_flight in unique_flights:
flight_cut = all_vals[:,0] == unique_flight
enu = pm.geodetic2enu(lat[flight_cut],lon[flight_cut],alt[flight_cut],origin[0],origin[1],origin[2]) #converts to ENU
ts = timestamps[flight_cut]
# x, y, z, t
flight_tracks_ENU[unique_flight.replace(' ','')] = numpy.vstack((numpy.asarray(enu),ts[None,:])).T
return flight_tracks_ENU, all_vals
else:
return [], []
def getENUTrackDict(start,
stop,
min_approach_cut_km,
hour_window=12,
flights_of_interest=[],
origin=None,
deploy_index=None):
'''
This will return a dict with the trajectories of each plane observed in the
period of time specified (given in UTC timestamps).
origin should be a tuple in the same format as returned by loadAntennaZeroLocation (latitude,longtidue,elevation)
'''
try:
if deploy_index is None:
deploy_index = info.returnDefaultDeploy()
unique_flights, all_vals = getTracks(start,
stop,
min_approach_cut_km,
hour_window=hour_window)
if numpy.size(flights_of_interest) != 0:
unique_flights = unique_flights[numpy.isin(unique_flights,
flights_of_interest)]
all_vals = all_vals[numpy.isin(all_vals['names'],
flights_of_interest)]
if numpy.size(all_vals) != 0:
flight_tracks_ENU = {}
if origin is None:
origin = info.loadAntennaZeroLocation(
deploy_index=deploy_index) #Antenna 0
for unique_flight in unique_flights:
flight_cut = numpy.where(all_vals['names'] == unique_flight)[0]
flight_cut = flight_cut[numpy.unique(
all_vals['timestamps'][flight_cut], return_index=True
)[1]] #Removing repeated timestamps per flight
ts = all_vals['timestamps'][flight_cut]
#cut = numpy.logical_and(cut,numpy.isin(numpy.arange(len(cut)),numpy.unique(file['timestamps'][...],return_index=True)[1])) #bool cut of first occurance of each timestamp to remove repeated.
enu = pm.geodetic2enu(all_vals['lat'][flight_cut],
all_vals['lon'][flight_cut],
all_vals['alt'][flight_cut], origin[0],
origin[1], origin[2]) #converts to ENU
sorted_track_indices = numpy.argsort(ts)
# x, y, z, t
flight_tracks_ENU[unique_flight] = numpy.vstack(
(numpy.asarray(enu), ts[None, :])).T[sorted_track_indices]
return flight_tracks_ENU, all_vals
else:
return {}, []
except Exception as e:
print('Error in getENUTrackDict.')
print(e)
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
print(exc_type, fname, exc_tb.tb_lineno)
sine_subtract_min_freq_GHz = 0.03
sine_subtract_max_freq_GHz = 0.09
sine_subtract_percent = 0.03
hilbert=False
final_corr_length = 2**10
trigger_types = [1,3]#[2]
plot_maps = True
sum_events = False #If true will add all plots together, if False will loop over runs in runs.
lognorm = True
cmap = 'YlOrRd'#'binary'#'coolwarm'
subset_cm = plt.cm.get_cmap('autumn', 10)
origin = info.loadAntennaZeroLocation(deploy_index=deploy_index)
latlonel_khsv = numpy.array([36.008611, -115.005556, 3316*0.3048 + 10]) #Height on google maps is ~ 3316 feet, which I convert to meters and add additional height for the tower it is on.
enu_khsv = numpy.array(pm.geodetic2enu(latlonel_khsv[0],latlonel_khsv[1],latlonel_khsv[2],origin[0],origin[1],origin[2]))
distance_m = numpy.linalg.norm(enu_khsv)
zenith_deg = numpy.rad2deg(numpy.arccos(enu_khsv[2]/distance_m))
elevation_deg = 90.0 - numpy.rad2deg(numpy.arccos(enu_khsv[2]/distance_m))
azimuth_deg = numpy.rad2deg(numpy.arctan2(enu_khsv[1],enu_khsv[0]))
try:
if True:
center_dir = 'E'
apply_phase_response = True
reader = Reader(datapath,run)
cor = Correlator(reader, upsample=2**16, n_phi=720, n_theta=720, waveform_index_range=(None,None),crit_freq_low_pass_MHz=crit_freq_low_pass_MHz, crit_freq_high_pass_MHz=crit_freq_high_pass_MHz, low_pass_filter_order=low_pass_filter_order, high_pass_filter_order=high_pass_filter_order, plot_filter=False,apply_phase_response=apply_phase_response, tukey=False, sine_subtract=True)
# mean_corr_values, fig, ax = cor.map(eventid, 'hpol', include_baselines=numpy.array([0,1,2,3,4,5]), plot_map=True, plot_corr=False, hilbert=False, interactive=False, max_method=None, waveforms=None, verbose=True, mollweide=True, center_dir=center_dir, circle_zenith=None, circle_az=None, radius=1.0, time_delay_dict={},window_title=None,add_airplanes=False)
ds = dataSlicerSingleRun(reader, impulsivity_dset_key, time_delays_dset_key, map_direction_dset_key,\
plot_freq_classification_colors = True #PLF,LF,HF,PHF,BB
freq_classications = ['PLF', 'LF', 'HF', 'PHF', 'BB']
freq_colors_cm = plt.cm.get_cmap('Set3', len(freq_classications))
freq_colors = freq_colors_cm(numpy.linspace(0, 1, len(freq_classications)))
freq_color_dict = {}
for i, key in enumerate(freq_classications):
freq_color_dict[key] = {}
freq_color_dict[key]['c'] = numpy.array([freq_colors[i]])
freq_color_dict[key]['labeled_yet'] = False
# freq_colors = plt.cm.get_cmap('plasma',len(freq_classications)-1)#-1 because BB will be black
known_planes, calibrated_trigtime, output_tracks = pt.getKnownPlaneTracks()
origin = info.loadAntennaZeroLocation(
deploy_index=1) #This is what ENU is with respect to.
antennas_physical, antennas_phase_hpol, antennas_phase_vpol = info.loadAntennaLocationsENU(
)
antennas_phase_start = antennas_phase_hpol
print('Loading in cable delays.')
cable_delays = info.loadCableDelays()[mode]
if plot_planes == True:
plane_fig = plt.figure()
plane_fig.canvas.set_window_title('3D Plane Tracks')
plane_ax = plane_fig.add_subplot(111, projection='3d')
plane_ax.scatter(0, 0, 0, label='Antenna 0', c='k')
plane_polys = {}
interpolated_plane_locations = {}
#This is just to demonstrate the difference.
final_corr_length = 2**17
crit_freq_low_pass_MHz = [
80, 70, 70, 70, 70, 70, 60, 70
] #Filters here are attempting to correct for differences in signals from pulsers.
low_pass_filter_order = [0, 8, 8, 8, 10, 8, 3, 8]
crit_freq_high_pass_MHz = 65
high_pass_filter_order = 12
apply_phase_response = True
hilbert = False
#Load antenna position information from the info.py script
origin = info.loadAntennaZeroLocation() #Assuming default_deploy
antennas_physical, antennas_phase_hpol, antennas_phase_vpol = info.loadAntennaLocationsENU(
) #Assuming default_deploy
#Create a Reader object for the specific run.
reader = Reader(datapath, run)
print('The run associated with this reader is:')
print(reader.run)
print('This run has %i events' % (reader.N()))
#Create a TimeDelayCalculator object for the specified run. Note that if the above parameters haven't been change
tdc_raw = TimeDelayCalculator(reader,
final_corr_length=final_corr_length,
crit_freq_low_pass_MHz=None,
crit_freq_high_pass_MHz=None,
low_pass_filter_order=None,