def az_decompose(hdisp, station_pos, disk_pos):
# both station_pos and disk_pos are tuples
compass_bearing = haversine.calculate_initial_compass_bearing(station_pos, disk_pos);
azimuth = 90 - compass_bearing;
xdisp = hdisp * -np.cos(azimuth * np.pi / 180);
ydisp = hdisp * -np.sin(azimuth * np.pi / 180);
return [xdisp, ydisp];
def latlon2xy(loni,lati,lon0,lat0): # returns the distance between a point and a reference in km. radius = haversine.distance([lat0,lon0], [lati,loni]); bearing = haversine.calculate_initial_compass_bearing((lat0, lon0),(lati, loni)) azimuth = 90 - bearing; x = radius * np.cos(np.deg2rad(azimuth)); y = radius * np.sin(np.deg2rad(azimuth)); return [x, y];
def cross_track_pos(target_lon, target_lat, nearrange_lon, nearrange_lat,
heading_cartesian):
# Given the heading of a plane and the coordinates of one near-range point
# Get the cross-track position of point in a coordinate system centered at (nearrange_lon, nearrange_lat) with given heading
distance = haversine.distance((target_lat, target_lon),
(nearrange_lat, nearrange_lon))
compass_bearing = haversine.calculate_initial_compass_bearing(
(nearrange_lat, nearrange_lon), (target_lat, target_lon))
# this comes as CW from north
theta = bearing_to_cartesian(compass_bearing)
# the angle of the position vector in cartesian coords
# heading_cartesian is the angle between the east unit vector and the flight direction
x0 = distance * np.cos(np.deg2rad(theta))
y0 = distance * np.sin(np.deg2rad(theta))
# in the east-north coordinate systeem
x_prime, y_prime = rotate_vector_by_angle(x0, y0, heading_cartesian)
return y_prime
def compute_prem_load(station_array, load_array, disk_radius, greensfunc, max_distance):
# For a given station and a given set of loads,
# Compute the loading on a PREM earth structure
# Max distance is in degrees
total_disp_x = [];
total_disp_y = [];
total_disp_v = [];
for i in range(len(station_array.lon)): # for each station...
# Take a set of rectangular loads and tile them into disk loads.
CircleLoads = get_disks(load_array, disk_radius, max_distance, station_array.lon[i], station_array.lat[i]);
print("Number of circles: %d" % len(CircleLoads.lon));
disk_sum_v = 0;
disk_sum_x = 0;
disk_sum_y = 0;
for j in range(np.size(CircleLoads.lon)):
dist_from_center = haversine.distance([CircleLoads.lat[j], CircleLoads.lon[j]],
[station_array.lat[i], station_array.lon[i]]); # reported in km
azimuth = haversine.calculate_initial_compass_bearing((station_array.lat[i], station_array.lon[i]),
(CircleLoads.lat[j], CircleLoads.lon[j]));
myindex = find_closest_greens(greensfunc.km,
dist_from_center); # find the nearest answer in the Green's functions
vdisp = greensfunc.vload[myindex]; # in m
hdisp = greensfunc.hload[myindex]; # in m
[xdisp, ydisp] = az_decompose(hdisp, (station_array.lat[i], station_array.lon[i]), (
CircleLoads.lat[j], CircleLoads.lon[j])); # Decompose radial into x and y components
disk_sum_v = disk_sum_v + vdisp * CircleLoads.pressure[
j] * 1000 / 9.81; # THIS SHOULD BE DIVIDED BY 9.81! the PREM code already has it. Result in mm
disk_sum_x = disk_sum_x + xdisp * CircleLoads.pressure[
j] * 1000 / 9.81; # THIS SHOULD BE DIVIDED BY 9.81! the PREM code already has it. Result in mm
disk_sum_y = disk_sum_y + ydisp * CircleLoads.pressure[
j] * 1000 / 9.81; # THIS SHOULD BE DIVIDED BY 9.81! the PREM code already has it. Result in mm
total_disp_x.append(disk_sum_x);
total_disp_y.append(disk_sum_y);
total_disp_v.append(disk_sum_v);
return total_disp_x, total_disp_y, total_disp_v; # should exactly match length of input station_array fields.
# 2016 event
event_tuples.append((40.453, -126.194))
time_list.append("2016-12-08T14:49:38.000")
name_list.append("2016 M6.6")
fig, axs = plt.subplots(4, 1, sharex=True, figsize=(10, 10))
fig.subplots_adjust(hspace=0)
# The waveform plots
xarray = []
radial = []
transverse = []
vertical = []
for i in range(len(event_tuples)):
print("working on %s" % name_list[i])
back_az = haversine.calculate_initial_compass_bearing(
pt_station, event_tuples[i])
t = UTCDateTime(time_list[i])
st = client.get_waveforms("NC",
station,
"*",
"HH*",
t,
t + num_minutes * 60,
attach_response=True)
st.remove_response(output="VEL")
st.rotate('NE->RT', back_azimuth=back_az)
tr = st[0]
# the first trace
df = tr.stats.sampling_rate
npts = tr.stats.npts
st.filter("bandpass", freqmin=fmin, freqmax=fmax)
def compute(lonbounds, latbounds, network_search, client_search, eqlon, eqlat,
starttime, endtime, fmin, fmax, num_minutes):
myclient = Client(client_search)
waveform_client = Client("NCEDC")
# this client has more waveforms than the IRIS client.
network_split = network_search.split(',')
# [BK,NC,etc].
inventory = myclient.get_stations(network=network_search,
starttime=starttime,
endtime=endtime,
minlatitude=latbounds[0],
maxlatitude=latbounds[1],
minlongitude=lonbounds[0],
maxlongitude=lonbounds[1],
level='response',
channel='?H?')
# ?H? means broadband.
# len(inventory) is the number of networks. inventory[0] is associated with the first network code.
eqtuple = (eqlat, eqlon)
# this is the required order for azimuth math.
namecodes = []
lons = []
lats = []
radials = []
transverses = []
verticals = []
for i in range(len(inventory)):
print(inventory[i])
for i in range(len(inventory)): # for each network
for j in range(len(inventory[i])): # flipping through stations
new_st = []
newcount = 0
mystation = inventory[i][j]
# a station object.
station_dictionary = mystation.get_contents()
station_name = station_dictionary['stations'][0].split(' ')[0]
# if station_name != 'GASB' and station_name != 'KHMB' and station_name != 'SUTB' and station_name != 'HATC':
# continue; # GET RID OF THIS LATER.
print("working on %s" % station_name)
all_channels = station_dictionary['channels']
print(all_channels)
channel0 = all_channels[0]
# the first channel in the list (not very specific).
channel_id = network_split[i] + '.' + channel0
channel_type = channel_id.split('.')[-1][0:2] + "*"
# something like "BH*" or "HH*" depending on what the station has.
# Parameters
coords = inventory.get_coordinates(channel_id)
pt_station = (coords['latitude'], coords['longitude'])
back_az = haversine.calculate_initial_compass_bearing(
pt_station, eqtuple)
print(pt_station)
print(eqtuple)
print(back_az)
t = UTCDateTime(starttime)
# Parameters
# Get some waveforms
print("getting waveforms:")
print(
"waveform_client.get_waveforms(%s, %s, *, %s, %s, attach_response=True)\n"
% (network_split[i], station_name, channel_type, starttime))
try:
st = waveform_client.get_waveforms(network_split[i],
station_name,
"*",
channel_type,
t,
t + num_minutes * 60,
attach_response=True)
except:
print("Could not find data for station %s. Skipping. " %
(station_name))
continue
if station_name == 'JCC':
print(
"waveform_client.get_waveforms(%s, %s, *, %s, %s, attach_response=True)\n"
% (network_split[i], station_name, "HH*", starttime))
try:
st = waveform_client.get_waveforms(network_split[i],
station_name,
"*",
"HH*",
t,
t + num_minutes * 60,
attach_response=True)
except:
print("Could not find data for station %s. Skipping. " %
(station_name))
continue
obtained_channel = []
for k in range(len(st)):
obtained_channel.append(str(st[k]).split()[0])
# appends things like 'BK.YBH.00.BHE'.
print("Got channels:")
print(obtained_channel)
# Get the data from the station, and record its amplitude.
# This is the meat of the program.
# Processing once we have the stream.
# Vertical only stations
if len(st) == 1 and obtained_channel[0][-1] == 'Z':
print("Only vertical traces")
st.remove_response(output="VEL")
st.filter("bandpass", freqmin=fmin, freqmax=fmax)
vertical = st[0]
vertical_number = np.nanmax(vertical)
radial_number = np.nan
transverse_number = np.nan
# make_plot(st, channel_id, station_name);
elif len(st) == 2:
if obtained_channel[0][-1] == 'Z':
vertical = st[0]
elif obtained_channel[1][-1] == 'Z':
vertical = st[1]
else:
print("cannot find vertical; continuing")
continue
print("Only using one vertical trace")
st.remove_response(output="VEL")
st.filter("bandpass", freqmin=fmin, freqmax=fmax)
vertical = st[0]
vertical_number = np.nanmax(vertical)
radial_number = np.nan
transverse_number = np.nan
# make_plot(st, channel_id, station_name);
# Three component stations.
elif len(st) == 3:
# We had a weird situation where JCC.BH* didn't have the same length of data. Trying a hard-coded fix with HH*.
if len(st[0].data) != len(st[1].data) or len(
st[1].data) != len(st[2].data) or len(
st[0].data) != len(st[2].data):
print("Bad data.")
try:
st = waveform_client.get_waveforms(
network_split[i],
station_name,
"*",
"HH*",
t,
t + num_minutes * 60,
attach_response=True)
except:
print(
"Could not find HH* data for station %s. Skipping. "
% (station_name))
continue
# Remove the response and rotate to transverse.
st.remove_response(output="VEL")
st.rotate('NE->RT', back_azimuth=back_az)
st.filter("bandpass", freqmin=fmin, freqmax=fmax)
make_plot(st, channel_id, station_name)
transverse = st[0]
radial = st[1]
vertical = st[2]
radial_number = np.nanmax(radial)
transverse_number = np.nanmax(transverse)
vertical_number = np.nanmax(vertical)
elif len(st) > 3:
print("Have %d traces. Removing some." % len(st))
for k in range(len(st)):
if '.00.' in obtained_channel[k]:
newcount = newcount + 1
print("Found %d trances with .00." % newcount)
if station_name == 'JCC': # JCC is so messy!
if len(st) == 6:
new_st.append(st[0])
new_st.append(st[2])
new_st.append(st[4])
# 2014 has 4 traces with different time spans. This isn't so great.
else:
print("Don't know what to do with JCC.")
continue
elif newcount == 3:
for k in range(len(st)):
if '.00.' in obtained_channel[k]:
new_st.append(st[k])
else:
print(
"Didn't find 3 .00. channels. Don't know what to do.")
continue
# Remove the response and rotate to transverse.
st.remove_response(output="VEL")
st.rotate('NE->RT', back_azimuth=back_az)
st.filter("bandpass", freqmin=fmin, freqmax=fmax)
# make_plot(st,channel_id,station_name);
transverse = st[0]
radial = st[1]
vertical = st[2]
radial_number = np.nanmax(radial)
transverse_number = np.nanmax(transverse)
vertical_number = np.nanmax(vertical)
else:
print("stream is %d traces long... not sure what to do" %
(len(st)))
print(st)
continue
# Saving data for the plotting function.
lons.append(coords['longitude'])
lats.append(coords['latitude'])
namecodes.append(station_name)
transverses.append(transverse_number)
radials.append(radial_number)
verticals.append(vertical_number)
return [namecodes, lons, lats, radials, transverses, verticals]
