def gather_waveforms(source,
network,
station,
location,
channel,
starttime,
endtime,
time_buffer=0,
merge_fill_value=0,
trim_fill_value=0,
remove_response=False,
return_failed_stations=False,
watc_url=None,
watc_username=None,
watc_password=None):
"""
Gather seismic/infrasound waveforms from IRIS or WATC FDSN, or AVO Winston,
and output a :class:`~obspy.core.stream.Stream` with station/element
coordinates attached. Optionally remove the sensitivity.
**NOTE**
Usual RTM usage is to specify a starttime/endtime that brackets the
estimated source origin time. Then time_buffer is used to download enough
extra data to account for the time required for an infrasound signal to
propagate to the farthest station.
Args:
source (str): Which source to gather waveforms from. Options are:
* `'IRIS'` – IRIS FDSN
* `'WATC'` – WATC FDSN
* `'AVO'` – AVO Winston
network (str): SEED network code [wildcards (``*``, ``?``) accepted]
station (str): SEED station code [wildcards (``*``, ``?``) accepted]
location (str): SEED location code [wildcards (``*``, ``?``) accepted]
channel (str): SEED channel code [wildcards (``*``, ``?``) accepted]
starttime (:class:`~obspy.core.utcdatetime.UTCDateTime`): Start time for
data request
endtime (:class:`~obspy.core.utcdatetime.UTCDateTime`): End time for
data request
time_buffer (int or float): Extra amount of data to download after
`endtime` [s]
merge_fill_value (bool, int, float, str, or None): Controls merging of
:class:`~obspy.core.trace.Trace` objects with identical IDs. If
`False`, no merging is performed. Otherwise, a merge is performed
with the ``fill_value`` provided to this parameter. For details,
see the docstring of :meth:`obspy.core.stream.Stream.trim`
trim_fill_value (bool, int, float, or None): Controls trimming of the
output :class:`~obspy.core.stream.Stream`, useful if precisely
uniform start and end times are desired. If `False`, no trimming is
performed. Otherwise, a trim is performed with the ``fill_value``
provided to this parameter. For details, see the docstring of
:meth:`obspy.core.stream.Stream.merge`
remove_response (bool): Toggle response removal via
:meth:`~obspy.core.trace.Trace.remove_sensitivity` or a simple
scalar multiplication
return_failed_stations (bool): If `True`, returns a list of station
codes that were requested but not downloaded. This disables the
standard failed station warning message
watc_url (str): URL for WATC FDSN server
watc_username (str): Username for WATC FDSN server
watc_password (str): Password for WATC FDSN server
Returns:
:class:`~obspy.core.stream.Stream` containing gathered waveforms. If
`return_failed_stations` is `True`, additionally returns a list
containing station codes that were requested but not downloaded
"""
# Check for issues with fill value args
if merge_fill_value is True or trim_fill_value is True:
raise ValueError('Cannot provide True to fill value parameters.')
print('--------------')
print('GATHERING DATA')
print('--------------')
# IRIS FDSN
if source == 'IRIS':
client = FDSN_Client('IRIS')
print('Reading data from IRIS FDSN...')
try:
st_out = client.get_waveforms(network,
station,
location,
channel,
starttime,
endtime + time_buffer,
attach_response=True)
except FDSNNoDataException:
st_out = Stream() # Just create an empty Stream object
# WATC FDSN
elif source == 'WATC':
print('Connecting to WATC FDSN...')
client = FDSN_Client(base_url=watc_url,
user=watc_username,
password=watc_password)
print('Successfully connected. Reading data from WATC FDSN...')
try:
st_out = client.get_waveforms(network,
station,
location,
channel,
starttime,
endtime + time_buffer,
attach_response=True)
except FDSNNoDataException:
st_out = Stream() # Just create an empty Stream object
# AVO Winston
elif source == 'AVO':
client = EW_Client('pubavo1.wr.usgs.gov',
port=16023) # 16023 is long-term
print('Reading data from AVO Winston...')
st_out = Stream() # Make empty Stream object to populate
# Brute-force "dynamic grid search" over network/station/channel/location codes
for nw in _restricted_matching('network', network, client):
for sta in _restricted_matching('station',
station,
client,
network=nw):
for cha in _restricted_matching('channel',
channel,
client,
network=nw,
station=sta):
for loc in _restricted_matching('location',
location,
client,
network=nw,
station=sta,
channel=cha):
try:
st_out += client.get_waveforms(
nw, sta, loc, cha, starttime,
endtime + time_buffer)
except KeyError:
pass
else:
raise ValueError('Unrecognized source. Valid options are \'IRIS\', '
'\'WATC\', or \'AVO\'.')
# Merge, if specified
if merge_fill_value is not False:
st_out.merge(fill_value=merge_fill_value) # Merge Traces with same ID
warnings.warn(f'Merging with "fill_value={merge_fill_value}"',
CollectionWarning)
st_out.sort()
# Check that all requested stations are present in Stream
requested_stations = station.split(',')
downloaded_stations = [tr.stats.station for tr in st_out]
failed_stations = []
for sta in requested_stations:
# The below check works with wildcards, but obviously cannot detect if
# ALL stations corresponding to a given wildcard (e.g., O??K) were
# downloaded. Thus, if careful station selection is desired, specify
# each station explicitly and the below check will then be effective.
if not fnmatch.filter(downloaded_stations, sta):
if not return_failed_stations:
# If we're not returning the failed stations, then show this
# warning message to alert the user
warnings.warn(
f'Station {sta} not downloaded from {source} '
'server for this time period.', CollectionWarning)
failed_stations.append(sta)
# If the Stream is empty, then we can stop here
if st_out.count() == 0:
print('No data downloaded.')
if return_failed_stations:
return st_out, failed_stations
else:
return st_out
# Otherwise, show what the Stream contains
print(st_out.__str__(extended=True)) # This syntax prints the WHOLE Stream
# Trim, if specified
if trim_fill_value is not False:
st_out.trim(starttime,
endtime + time_buffer,
pad=True,
fill_value=trim_fill_value)
warnings.warn(f'Trimming with "fill_value={trim_fill_value}"',
CollectionWarning)
print('Assigning coordinates...')
# Use IRIS inventory info for AVO data source
if source == 'AVO':
client = FDSN_Client('IRIS')
try:
inv = client.get_stations(network=network,
station=station,
location=location,
channel=channel,
starttime=starttime,
endtime=endtime + time_buffer,
level='channel')
except FDSNNoDataException:
inv = Inventory() # Make an empty inv
warnings.warn('Creating empty inventory.', CollectionWarning)
for tr in st_out:
try:
coords = inv.get_coordinates(tr.id)
tr.stats.longitude = coords['longitude']
tr.stats.latitude = coords['latitude']
tr.stats.elevation = coords['elevation']
except Exception as e:
if str(e) == 'No matching channel metadata found.':
warnings.warn(f'No metadata for {tr.id} found in inventory.',
CollectionWarning)
else:
raise
# Check if any Trace did NOT get coordinates assigned, and try to use JSON
# coordinates if available
for tr in st_out:
try:
tr.stats.longitude, tr.stats.latitude, tr.stats.elevation
except AttributeError:
try:
tr.stats.latitude, tr.stats.longitude,\
tr.stats.elevation = AVO_COORDS[tr.id]
warnings.warn(f'Using coordinates from JSON file for {tr.id}.',
CollectionWarning)
except KeyError:
print(f'No coordinates available for {tr.id}. Stopping.')
raise
# Remove sensitivity
if remove_response:
print('Removing sensitivity...')
for tr in st_out:
try:
# Just removing sensitivity for now. remove_response() can lead
# to errors. This should be sufficient for now. Plus some
# IRIS-AVO responses are wonky.
tr.remove_sensitivity()
except ValueError: # No response information found
# This is only set up for infrasound calibration values
try:
calib = AVO_INFRA_CALIBS[tr.id]
tr.data = tr.data * calib
warnings.warn(
'Using calibration value from JSON file for '
f'{tr.id}.', CollectionWarning)
except KeyError:
print(f'No calibration value available for {tr.id}. '
'Stopping.')
raise
print('Done')
# Return the Stream with coordinates attached (and responses removed if
# specified)
if return_failed_stations:
return st_out, failed_stations
else:
return st_out
template = tribe[0]
event = template.event
depth = event.origins[0].depth
if depth < 10:
origt = event.origins[0].time
evlat = event.origins[0].latitude
evlon = event.origins[0].longitude
tmin = origt - 0.5
tmax = origt + 5.0
name = template.name
fname = os.path.join("templates", "waveforms", "%s.mseed" % name)
stream = read(fname)
for tr in stream:
station = tr.stats.station
coords = inv.get_coordinates(tr.id, origt)
stalat = coords["latitude"]
stalon = coords["longitude"]
# distdeg = calc_dist(evlat, evlon, stalat, stalon, 6378.1)
# distkm = degrees2kilometers(distdeg)
dist = gps2dist_azimuth(evlat, evlon, stalat, stalon)[0]
tr.stats.distance = dist
stream.sort()
#stream.traces.sort(key=lambda x: x.stats.distance)
stream.trim(starttime=tmin, endtime=tmax).filter("lowpass",
freq=60)
plot_3cols(stream, event)
plt.savefig(os.path.join("templates", "waveforms",
"%s.png" % name),
dpi=300)
