def test_search():
eventlist = search(starttime=datetime(1994,1,17,12,30),
endtime=datetime(1994,1,18,12,35),
minmagnitude=6.6)
event = eventlist[0]
assert event.id == 'ci3144585'
events = search(minmagnitude=9.0,maxmagnitude=9.9,
updatedafter=datetime(2010,1,1))
events = search(maxmagnitude=0.1,
starttime=datetime(2017,1,1),
endtime=datetime(2017,1,30))
def test_summary():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'vcr_summary.yaml')
with vcr.use_cassette(tape_file):
eventlist = search(starttime=datetime(1994, 1, 17, 12, 30),
endtime=datetime(1994, 1, 18, 12, 35),
minmagnitude=6.6)
event = eventlist[0]
cmp = 'ci3144585 1994-01-17 12:30:55.390000 (34.213,-118.537) 18.2 km M6.7'
assert str(event) == cmp
assert event.id == 'ci3144585'
assert event.time == datetime(1994, 1, 17, 12, 30, 55, 390000)
assert event.latitude == 34.213
assert event.longitude == -118.537
assert event.depth == 18.202
assert event.magnitude == 6.7
assert 'cdi' in event.properties
assert event['cdi'] == 8.6
assert event.hasProduct('shakemap')
assert not event.hasProduct('foo')
try:
event['foo']
assert 1 == 2
except AttributeError:
pass
assert event.hasProperty('cdi')
assert not event.hasProperty('foo')
assert isinstance(event.getDetailEvent(), DetailEvent)
durl = 'https://earthquake.usgs.gov/fdsnws/event/1/query?eventid=ci3144585&format=geojson'
assert event.getDetailURL() == durl
try:
detail = event.getDetailEvent(includedeleted=True,
includesuperseded=True)
assert 1 == 2
except RuntimeError:
pass
# find an event that has multiple versions of shakemap to test
# include superseded
# official20110311054624120_30
eventlist = search(starttime=datetime(2011, 3, 11, 0, 0),
endtime=datetime(2011, 3, 12, 0, 0),
minmagnitude=8.8)
honshu = eventlist[0]
detail = honshu.getDetailEvent(includesuperseded=True)
shakemaps = detail.getProducts('shakemap', version=VersionOption.ALL)
assert shakemaps[1].source == 'atlas'
assert event.toDict()['depth'] == 18.202
def test_get_summary_data_frame():
events = search(starttime=datetime(1994,6,1),
endtime=datetime(1994,10,6),
minmagnitude=8.0,maxmagnitude=9.0,verbose=True)
df = get_summary_data_frame(events)
assert len(df) == 2
assert df.iloc[0]['magnitude'] == 8.2
def test_summary():
eventlist = search(starttime=datetime(1994, 1, 17, 12, 30),
endtime=datetime(1994, 1, 18, 12, 35),
minmagnitude=6.6)
event = eventlist[0]
assert str(
event
) == 'ci3144585 1994-01-17 12:30:55.390000 (34.213,-118.537) 18.2 km M6.7'
assert event.id == 'ci3144585'
assert event.time == datetime(1994, 1, 17, 12, 30, 55, 390000)
assert event.latitude == 34.213
assert event.longitude == -118.537
assert event.depth == 18.202
assert event.magnitude == 6.7
assert 'cdi' in event.properties
assert event['cdi'] == 8.6
assert event.hasProduct('shakemap')
assert event.hasProduct('foo') == False
try:
event['foo']
assert 1 == 2
except AttributeError as ae:
pass
assert event.hasProperty('cdi')
assert event.hasProperty('foo') == False
assert isinstance(event.getDetailEvent(), DetailEvent)
durl = 'https://earthquake.usgs.gov/fdsnws/event/1/query?eventid=ci3144585&format=geojson'
assert event.getDetailURL() == durl
try:
detail = event.getDetailEvent(includedeleted=True,
includesuperseded=True)
assert 1 == 2
except RuntimeError as re:
pass
#find an event that has multiple versions of shakemap to test includesuperseded
#official20110311054624120_30
eventlist = search(starttime=datetime(2011, 3, 11, 0, 0),
endtime=datetime(2011, 3, 12, 0, 0),
minmagnitude=8.8)
honshu = eventlist[0]
detail = honshu.getDetailEvent(includesuperseded=True)
shakemaps = detail.getProducts('shakemap', version=VersionOption.ALL)
assert shakemaps[1].source == 'atlas'
assert event.toDict()['depth'] == 18.202
def fetch_day(mag=0):
d = fetch_date()
y, m, d = d.year, d.month, d.day
events = search(starttime=datetime(y,m,d,0,0),
endtime=datetime(y,m,d,23,59), minmagnitude=mag)
return [{'time': '{}-{}-{}'.format(y, m, d), 'event': dict(i.toDict()), 'props': fetch_properties(i)} for i in events]
def test_get_detail_data_frame():
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0,
maxmagnitude=9.0)
all_mags = get_detail_data_frame(events,
get_all_magnitudes=True,
verbose=True)
assert all_mags.iloc[0]['magnitude'] == 8.2
def test_search():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'vcr_search.yaml')
with vcr.use_cassette(tape_file):
eventlist = search(starttime=datetime(1994, 1, 17, 12, 30),
endtime=datetime(1994, 1, 18, 12, 35),
minmagnitude=6.6)
event = eventlist[0]
assert event.id == 'ci3144585'
events = search(minmagnitude=9.0, maxmagnitude=9.9,
starttime=datetime(2008, 1, 1),
endtime=datetime(2010, 2, 1),
updatedafter=datetime(2010, 1, 1))
events = search(maxmagnitude=0.1,
starttime=datetime(2017, 1, 1),
endtime=datetime(2017, 1, 30))
def test_get_summary_data_frame():
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0,
maxmagnitude=9.0,
verbose=True)
df = get_summary_data_frame(events)
assert len(df) == 2
assert df.iloc[0]['magnitude'] == 8.2
def test_get_detail_data_frame():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'vcr_detail_frame.yaml')
with vcr.use_cassette(tape_file):
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0, maxmagnitude=9.0)
all_mags = get_detail_data_frame(
events, get_all_magnitudes=True, verbose=True)
assert all_mags.iloc[0]['magnitude'] == 8.2
def test_get_detail_data_frame():
cassettes, datadir = get_datadir()
tape_file = os.path.join(cassettes, 'dataframes_detailed.yaml')
with vcr.use_cassette(tape_file):
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0,
maxmagnitude=9.0)
all_mags = get_detail_data_frame(events, get_all_magnitudes=True)
assert all_mags.iloc[0]['magnitude'] == 8.2
def test_search():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'search_search.yaml')
with vcr.use_cassette(tape_file):
eventlist = search(starttime=datetime(1994, 1, 17, 12, 30),
endtime=datetime(1994, 1, 18, 12, 35),
minmagnitude=6.6)
event = eventlist[0]
assert event.id == 'ci3144585'
events = search(minmagnitude=9.0,
maxmagnitude=9.9,
starttime=datetime(2008, 1, 1),
endtime=datetime(2010, 2, 1),
updatedafter=datetime(2010, 1, 1))
events = search(maxmagnitude=0.1,
starttime=datetime(2017, 1, 1),
endtime=datetime(2017, 1, 30))
def seismes(num_page=5, refresh=1):
date_now = datetime.now()
date_last_hour= date_now - timedelta(hours = num_page)
eventlist = search(starttime = date_last_hour,
endtime = date_now,
minmagnitude = 0)
listseismes = lastseismes(eventlist)
lenlist = len(listseismes)
return render_template('map_v2_1.html', listseismes=listseismes, refresh=refresh, lenlist=lenlist)
def test_get_summary_data_frame():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'vcr_summary_frame.yaml')
with vcr.use_cassette(tape_file):
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0, maxmagnitude=9.0, verbose=True)
df = get_summary_data_frame(events)
assert len(df) == 2
assert df.iloc[0]['magnitude'] == 8.2
def test_get_summary_data_frame():
cassettes, datadir = get_datadir()
tape_file = os.path.join(cassettes, 'dataframes_summary.yaml')
with vcr.use_cassette(tape_file):
events = search(starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0, maxmagnitude=9.0)
df = get_summary_data_frame(events)
assert len(df) == 2
assert df.iloc[0]['magnitude'] == 8.2
def test_get_detail_data_frame():
cassettes, datadir = get_datadir()
tape_file = os.path.join(cassettes, "dataframes_detailed.yaml")
with vcr.use_cassette(tape_file, record_mode="new_episodes"):
events = search.search(
starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0,
maxmagnitude=9.0,
)
all_mags = get_detail_data_frame(events, get_all_magnitudes=True)
assert all_mags.iloc[0]["magnitude"] == 8.2
def test_url_error():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'search_error.yaml')
with vcr.use_cassette(tape_file):
passed = True
try:
eventlist = search(starttime=datetime(1994, 1, 17, 12, 30),
endtime=datetime(1994, 1, 18, 12, 35),
minmagnitude=6.6,
host="error")
except Exception as e:
passed = False
assert passed == False
def test_get_summary_data_frame():
cassettes, datadir = get_datadir()
tape_file = os.path.join(cassettes, "dataframes_summary.yaml")
with vcr.use_cassette(tape_file, record_mode="new_episodes"):
events = search.search(
starttime=datetime(1994, 6, 1),
endtime=datetime(1994, 10, 6),
minmagnitude=8.0,
maxmagnitude=9.0,
)
df = get_summary_data_frame(events)
assert len(df) == 2
assert df.iloc[0]["magnitude"] == 8.2
def test_scenario():
datadir = get_datadir()
tape_file = os.path.join(datadir, 'search_scenario.yaml')
with vcr.use_cassette(tape_file):
try:
eventlist = search(starttime=datetime(2013, 10, 10, 12, 0),
endtime=datetime(2013, 10, 10, 12, 30, 0),
minmagnitude=0,
maxmagnitude=9.9,
scenario=True)
assert eventlist[0].id == 'ak013d08buqb'
except Exception as e:
raise AssertionError('Scenario search failed with "%s".' %
(str(e)))
def seismes_v2(date_format, refresh=1):
date_now = datetime.now()
if date_format == 0:
date_past= date_now - timedelta(hours = date_now.hour)
elif date_format == 1:
date_past = date_now - timedelta(days = date_now.weekday())
elif date_format == 2:
date_past = date_now - timedelta(days = date_now.day)
eventlist = search(starttime = date_past,
endtime = date_now,
minmagnitude = 0)
listseismes = lastseismes(eventlist)
lenlist = len(listseismes)
return render_template('map_v2_1.html', listseismes=listseismes, refresh=refresh, lenlist=lenlist)
def load_catalog(self, extra_comcat_params):
"""
Uses the libcomcat api (https://github.com/usgs/libcomcat) to parse the ComCat database for event information for
California.
The default parameters are given from the California testing region defined by the CSEP1 template files. starttime
and endtime are exepcted to be datetime objects with the UTC timezone.
Enough information needs to be provided in order to calculate a start date and end date.
1) start_time and end_time
2) start_time and duration_in_years
3) epoch_time and end_time
4) epoch_time and duration_in_years
If start_time and start_epoch are both supplied, program will default to using start_time.
If end_time and time_delta are both supplied, program will default to using end_time.
This requires an internet connection and will fail if the script has no access to the server.
Args:
extra_comcat_params (dict): pass additional parameters to libcomcat
"""
from libcomcat.search import search
# get eventlist from Comcat
eventlist = search(minmagnitude=self.min_magnitude,
minlatitude=self.min_latitude,
maxlatitude=self.max_latitude,
minlongitude=self.min_longitude,
maxlongitude=self.max_longitude,
starttime=self.start_time,
endtime=self.end_time,
**extra_comcat_params)
# eventlist is converted to ndarray in _get_catalog_as_ndarray called from setter
self.catalog = eventlist
# update state because we just loaded a new catalog
self.date_accessed = datetime.datetime.utcnow()
self._update_catalog_stats()
return self
def find_events(target, buffer):
"""
Libcomcat query for potential matching events to the target.
Args:
target (dictionary):
Dictionary of target event mag, time, and
location values.
buffer (dictionary): Dictionary of time, magnitude,
and distance buffers.
Returns:
usgs_events (list): List of Libcomcat SummaryEvents.
"""
usgs_event = search(
starttime=target['time'] - buffer['time'],
endtime=target['time'] + buffer['time'],
latitude=target['lat'],
longitude=target['lon'],
maxradiuskm=buffer['dist'],
maxmagnitude=target['mag'] + buffer['mag'],
minmagnitude=target['mag'] - buffer['mag'])
return usgs_event
def updateSequences(self, stime):
etime = stime + timedelta(days=1)
events = search(starttime=stime,
endtime=etime,
minlatitude=-90,
maxlatitude=90,
minlongitude=-180,
maxlongitude=180,
minmagnitude=0.0,
maxmagnitude=9.9)
todayframe = get_summary_data_frame(events)
todaydata = get_day_counts(GDICT, todayframe)
todaygrid = Grid2D(data=todaydata, geodict=GDICT)
for row in range(0, GDICT.ny):
for col in range(0, GDICT.nx):
if row == 19 and col == 29:
foo = 1
clat, clon = GDICT.getLatLon(row, col)
tvalue = todaygrid._data[row, col]
mvalue = self._meangrid._data[row, col]
svalue = self._stdgrid._data[row, col]
# thresh = tvalue > mvalue + svalue * 3
thresh = tvalue > MINEQ
xmin = clon - GDICT.dx / 2
xmax = clon + GDICT.dx / 2
ymin = clat - GDICT.dy / 2
ymax = clat + GDICT.dy / 2
if thresh:
c1 = todayframe['latitude'] > ymin
c2 = todayframe['latitude'] <= ymax
c3 = todayframe['longitude'] > xmin
c4 = todayframe['longitude'] <= xmax
cluster = todayframe[c1 & c2 & c3 & c4].copy()
class_frame, pproj = self.get_clusters(cluster, clon, clat)
self.insertSequences(class_frame, pproj)
# call a method that filters out clusters that don't match the definition
# of an earthquake sequence.
self.cleanSequences()
def main():
parser = get_parser()
args = parser.parse_args()
setup_logger(args.logfile, args.loglevel)
latitude = None
longitude = None
radiuskm = None
lonmin = latmin = lonmax = latmax = None
if args.radius:
latitude = args.radius[0]
longitude = args.radius[1]
radiuskm = args.radius[2]
if args.bounds:
lonmin, lonmax, latmin, latmax = args.bounds
# fix longitude bounds when crossing dateline
if lonmin > lonmax and lonmax >= -180:
lonmin -= 360
else:
lonmin, lonmax, latmin, latmax = None, None, None, None
minmag = 0.0
maxmag = 9.9
if args.magRange:
minmag = args.magRange[0]
maxmag = args.magRange[1]
if args.bounds and args.radius:
print('Please specify either a bounding box OR radius search.')
sys.exit(1)
if args.eventid:
event = get_event_by_id(args.eventid, includesuperseded=args.all)
events = [event]
else:
events = search(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
maxmagnitude=maxmag,
minmagnitude=minmag,
producttype='losspager',
host=args.host)
if not len(events):
print('No events found matching your search criteria. Exiting.')
sys.exit(0)
dataframe = None
nevents = len(events)
i = 1
for event in events:
logging.debug('Processing event %s (%i of %i).\n' %
(event.id, i, nevents))
if isinstance(event, SummaryEvent):
detail = event.getDetailEvent(includesuperseded=args.all)
else:
detail = event
df = get_pager_data_frame(detail,
get_losses=args.get_losses,
get_country_exposures=args.get_countries,
get_all_versions=args.all)
if dataframe is None:
dataframe = df
else:
dataframe = pd.concat([dataframe, df])
if dataframe is not None:
logging.debug('Created table...saving %i records to %s.\n' %
(len(dataframe), args.filename))
if args.format == 'excel':
dataframe.to_excel(args.filename, index=False)
elif args.format == 'tab':
dataframe.to_csv(args.filename, sep='\t', index=False)
else:
dataframe.to_csv(args.filename, index=False, chunksize=1000)
add_headers(args.filename, args.format)
print('%i records saved to %s.' % (len(dataframe), args.filename))
else:
sys.stderr.write('No Pager products found for requested event(s)\n')
sys.exit(0)
def main():
parser = get_parser()
args = parser.parse_args()
# make sure we don't have -e option AND --numdays option
if args.endTime is not None and args.numdays is not None:
msg = ('You must specify end time or number of days since '
'start time, not both. Exiting.')
print(msg)
sys.exit(1)
if not args.endTime and args.numdays:
args.endTime = args.startTime + timedelta(args.numdays)
setup_logger(args.logfile, args.loglevel)
tsum = (args.bounds is not None) + \
(args.radius is not None) + (args.country is not None)
if tsum != 1:
logging.error(
'Please specify a bounding box, radius, or country code.')
sys.exit(1)
latitude = None
longitude = None
radiuskm = None
lonmin = latmin = lonmax = latmax = None
bounds = None
if args.radius:
latitude = args.radius[0]
longitude = args.radius[1]
radiuskm = args.radius[2]
if args.bounds:
lonmin, lonmax, latmin, latmax = args.bounds
# fix longitude bounds when crossing dateline
if lonmin > lonmax and lonmax >= -180:
lonmin -= 360
else:
lonmin, lonmax, latmin, latmax = None, None, None, None
bounds = (lonmin, lonmax, latmin, latmax)
if args.country:
ccode = args.country
if not check_ccode(ccode):
curl = 'https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2'
fmt = ('%s is not a valid ISO 3166 country code. '
'See %s for the list.')
tpl = (ccode, curl)
logging.error(fmt % tpl)
sys.exit(1)
bounds = get_country_bounds(ccode, args.buffer) # this returns a list
minmag = 0.0
maxmag = 9.9
if args.magRange:
minmag = args.magRange[0]
maxmag = args.magRange[1]
minsig = 0
maxsig = 5000
if args.sigRange:
minsig = args.sigRange[0]
maxsig = args.sigRange[1]
if args.getCount:
if isinstance(bounds, tuple) or bounds is None:
nevents = count(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
maxmagnitude=maxmag,
minmagnitude=minmag,
minsig=minsig,
maxsig=maxsig,
producttype=args.limitByProductType)
else:
for lonmin, lonmax, latmin, latmax in bounds:
nevents = 0
nevents += count(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
minsig=minsig,
maxsig=maxsig,
maxmagnitude=maxmag,
minmagnitude=minmag,
producttype=args.limitByProductType)
print('There are %i events matching input criteria.' % nevents)
sys.exit(0)
if isinstance(bounds, tuple) or bounds is None:
events = search(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
maxmagnitude=maxmag,
minmagnitude=minmag,
minsig=minsig,
maxsig=maxsig,
producttype=args.limitByProductType,
host=args.host,
eventtype=args.event_type,
alertlevel=args.alert_level)
else:
events = []
for i, tbounds in enumerate(bounds):
lonmin, lonmax, latmin, latmax = tbounds
fmt = 'Checking bounds %i of %i for %s...\n'
tpl = (i + 1, len(bounds), ccode)
logging.debug(fmt % tpl)
tevents = search(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
maxmagnitude=maxmag,
minmagnitude=minmag,
minsig=minsig,
maxsig=maxsig,
producttype=args.limitByProductType,
host=args.host,
eventtype=args.event_type,
alertlevel=args.alert_level)
events += tevents
if not len(events):
logging.info('No events found matching your search criteria. Exiting.')
sys.exit(0)
if (args.getAngles != 'none' or
args.getAllMags or
args.getComponents != 'none'):
logging.info(
'Fetched %i events...creating table.\n' % (len(events)))
supp = args.getMomentSupplement
df = get_detail_data_frame(events, get_all_magnitudes=args.getAllMags,
get_tensors=args.getComponents,
get_focals=args.getAngles,
get_moment_supplement=supp)
else:
logging.info(
'Fetched %i events...creating summary table.\n' % (len(events)))
df = get_summary_data_frame(events)
# order the columns so that at least the initial parameters come the way
# we want them...
first_columns = list(events[0].toDict().keys())
col_list = list(df.columns)
for column in first_columns:
try:
col_list.remove(column)
except Exception as e:
x = 1
df = df[first_columns + col_list]
if args.country:
df = filter_by_country(df, ccode, buffer_km=args.buffer)
logging.info('Created table...saving %i records to %s.\n' %
(len(df), args.filename))
if args.format == 'excel':
df.to_excel(args.filename, index=False)
elif args.format == 'tab':
df.to_csv(args.filename, sep='\t', index=False)
else:
df.to_csv(args.filename, index=False, chunksize=1000)
logging.info('%i records saved to %s.' % (len(df), args.filename))
sys.exit(0)
def main():
"""
Read in data and add comcat IDs, download rupture file if available.
"""
eq_df = pd.read_csv(EVENT_FILE, sep=" ", header=None, names=EVENT_COLS)
eq_df['comcat_id'] = ''
nrows = eq_df.shape[0]
for i in range(nrows):
print('i = %i' % i)
eqmag = float(eq_df['mag'][i])
dmag = 0.3
min_mag = eqmag - dmag
max_mag = eqmag + dmag
edate = eq_df['date'][i]
etime = eq_df['time'][i]
edatetime = edate + ' ' + etime
eqdatetime = datetime.datetime.strptime(edatetime, '%Y/%m/%d %H:%M:%S')
start_time = eqdatetime - datetime.timedelta(1) # -1 day
end_time = eqdatetime + datetime.timedelta(1) # +1 day
dll = 0.1
eq_lat = float(eq_df['lat'][i])
min_latitude = eq_lat - dll
max_latitude = eq_lat + dll
eq_lon = float(eq_df['lon'][i])
min_longitude = eq_lon - dll
max_longitude = eq_lon + dll
summary_list = search(starttime=start_time,
endtime=end_time,
minlatitude=min_latitude,
maxlatitude=max_latitude,
minlongitude=min_longitude,
maxlongitude=max_longitude,
minmagnitude=min_mag,
maxmagnitude=max_mag)
if len(summary_list):
summary_event = summary_list[0]
detail = summary_event.getDetailEvent()
eq_df.at[i, 'comcat_id'] = detail.id
if (eqmag >= 5.5) & (detail.hasProduct('shakemap')):
outdir = os.path.join('..', 'data', 'ruptures', detail.id)
if not os.path.exists(outdir):
os.makedirs(outdir)
shake = detail.getProducts('shakemap', source='preferred')[0]
outfile = os.path.join(outdir, 'rupture.json')
shake.getContent('rupture.json', outfile)
# If it is a point source, no need for it so remove it.
rup = get_rupture(origin, outfile)
if isinstance(rup, PointRupture):
shutil.rmtree(outdir)
new_file = 'events_comcat.csv'
eq_df.to_csv(new_file, index=True)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 11 12:00:47 2020
code to download earthquake catalog
remember to load correct environment in order to use the libcomcat library
@author: talongi
"""
from libcomcat.dataframes import get_summary_data_frame, get_detail_data_frame
from libcomcat.search import search, DetailEvent
from datetime import datetime
events = search(starttime=datetime(2006, 10, 30),
endtime=datetime(2006, 11, 15),
minlatitude=40.4,
maxlatitude=40.6,
minlongitude=-125,
maxlongitude=-123)
detail_events = get_detail_data_frame(events)
#detail_events.to_csv('/auto/home/talongi/Cascadia/Data_tables/Events/ANSS_1980-2019_detailed.csv')
#%%
#find nans
import numpy as np
import pandas as pd
index_match = []
for i, x in enumerate(detail_events.nc_np1_strike):
if type(x) == str:
def main():
parser = get_parser()
args = parser.parse_args()
# --host and --scenario are mutually exclusive
if args.host is not None and args.scenario:
print(
'--host and --scenario options are mutually exclusive. Please choose one.'
)
sys.exit(1)
setup_logger(args.logfile, args.loglevel)
if args.eventid:
detail = get_event_by_id(args.eventid,
includesuperseded=True,
scenario=args.scenario)
_get_product_from_detail(detail,
args.product,
args.contents,
args.outputFolder,
args.version,
args.source,
list_only=args.list_only)
sys.exit(0)
tsum = (args.bounds is not None) + \
(args.radius is not None) + (args.country is not None)
if tsum != 1:
print('Please specify a bounding box, radius, or country code.')
sys.exit(1)
latitude = None
longitude = None
radiuskm = None
lonmin = latmin = lonmax = latmax = None
if args.startTime is None:
starttime = datetime.utcnow() - timedelta(days=30)
print('You did not specify a search start time, defaulting to %s' %
str(starttime))
else:
starttime = args.startTime
if args.endTime is None:
endtime = datetime.utcnow()
print('You did not specify a search end time, defaulting to %s' %
str(endtime))
else:
endtime = args.endTime
bounds = None
if args.radius:
latitude = args.radius[0]
longitude = args.radius[1]
radiuskm = args.radius[2]
if args.bounds:
lonmin, lonmax, latmin, latmax = args.bounds
# fix longitude bounds when crossing dateline
if lonmin > lonmax and lonmax >= -180:
lonmin -= 360
else:
lonmin, lonmax, latmin, latmax = None, None, None, None
bounds = (lonmin, lonmax, latmin, latmax)
if args.country:
ccode = args.country
if not check_ccode(ccode):
curl = 'https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2'
fmt = '%s is not a valid ISO 3166 country code. See %s for the list.'
tpl = (ccode, curl)
print(fmt % tpl)
sys.exit(1)
bounds = get_country_bounds(ccode, args.buffer) # this returns a list
minmag = 0.0
maxmag = 9.9
if args.magRange:
minmag = args.magRange[0]
maxmag = args.magRange[1]
if isinstance(bounds, tuple) or bounds is None:
events = search(starttime=starttime,
endtime=endtime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
producttype=args.product,
eventtype=args.eventType,
maxmagnitude=maxmag,
minmagnitude=minmag,
scenario=args.scenario,
host=args.host)
else:
events = []
for i, tbounds in enumerate(bounds):
lonmin, lonmax, latmin, latmax = tbounds
tevents = search(starttime=starttime,
endtime=endtime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
producttype=args.product,
eventtype=args.eventType,
maxmagnitude=maxmag,
minmagnitude=minmag,
scenario=args.scenario,
host=args.host)
events += tevents
if not len(events):
print('No events found matching your search criteria. Exiting.')
sys.exit(0)
if args.country:
ids = [event.id for event in events]
lats = [event.latitude for event in events]
lons = [event.longitude for event in events]
df = pd.DataFrame({'id': ids, 'latitude': lats, 'longitude': lons})
df2 = filter_by_country(df, ccode, buffer_km=args.buffer)
events = [event for event in events if event.id in df2['id'].unique()]
for event in events:
logging.debug('Retrieving products for event %s...' % event.id)
if not event.hasProduct(args.product):
continue
try:
detail = event.getDetailEvent(includesuperseded=True,
scenario=args.scenario)
except Exception as e:
print(
'Failed to retrieve detail event for event %s... continuing.' %
event.id)
continue
_get_product_from_detail(detail,
args.product,
args.contents,
args.outputFolder,
args.version,
args.source,
list_only=args.list_only)
sys.exit(0)
def main():
parser = get_parser()
args = parser.parse_args()
setup_logger(args.logfile, args.loglevel)
if args.eventid:
detail = get_event_by_id(args.eventid, catalog=args.catalog)
try:
df = get_phase_dataframe(detail, args.catalog)
filename = save_dataframe(
df, args.directory, detail, args.format, catalog=args.catalog)
print('Saved phase data for %s to %s' % (detail.id, filename))
sys.exit(0)
except Exception as e:
fmt = ('Could not extract the phase data due to the '
'following error: \n"%s"\n\nExiting.')
print(fmt % (str(e)))
sys.exit(1)
if args.bounds and args.radius:
print('Please specify either a bounding box OR radius search.')
sys.exit(1)
if not os.path.isdir(args.directory):
os.makedirs(args.directory)
latitude = None
longitude = None
radiuskm = None
lonmin = latmin = lonmax = latmax = None
starttime = endtime = None
if args.radius:
latitude = args.radius[0]
longitude = args.radius[1]
radiuskm = args.radius[2]
if args.bounds:
lonmin, lonmax, latmin, latmax = args.bounds
# fix longitude bounds when crossing dateline
if lonmin > lonmax and lonmax >= -180:
lonmin -= 360
minmag = 0.0
maxmag = 9.9
if args.magRange:
minmag = args.magRange[0]
maxmag = args.magRange[1]
events = search(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
catalog=args.catalog,
contributor=args.contributor,
maxmagnitude=maxmag,
minmagnitude=minmag)
if not len(events):
print('No events found matching your search criteria. Exiting.')
sys.exit(0)
for event in events:
if not event.hasProduct('phase-data'):
continue
try:
detail = event.getDetailEvent()
try:
df = get_phase_dataframe(detail, args.catalog)
except Exception as e:
fmt = ('Could not get phase dataframe for '
'event %. Error "%s". Continuing.')
tpl = (detail.id, str(e))
print(fmt % tpl)
filename = save_dataframe(
df, args.directory, detail, args.format, catalog=args.catalog)
print('Saved phase data for %s to %s' % (event.id, filename))
except Exception as e:
print('Failed to retrieve phase data for event %s. Error "%s"... continuing.' % (
event.id, str(e)))
continue
def main(args):
intervalno = args.intervalno
directory = args.directory
if intervalno > 11:
if args.previous is not None:
previous = args.previous
else:
print ('previous file required at input if interval no > 11.')
print ('enter previous file with flag -p previousFile at input')
print ('Exiting ...')
exit()
os.system('mkdir %s'%directory)
if intervalno == 1:
start = datetime(1900, 1, 1)
finish = datetime(1970, 1, 1)
if intervalno == 2:
start = datetime(1970, 1, 1)
finish = datetime(1980, 1, 1)
if intervalno == 3:
start = datetime(1980, 1, 1)
finish = datetime(1990, 1, 1)
if intervalno == 4:
start = datetime(1990, 1, 1)
finish = datetime(1995, 1, 1)
if intervalno == 5:
start = datetime(1995, 1, 1)
finish = datetime(2000, 1, 1)
if intervalno == 6:
start = datetime(2000, 1, 1)
finish = datetime(2005, 1, 1)
if intervalno == 7:
start = datetime(2005, 1, 1)
finish = datetime(2010, 1, 1)
if intervalno == 8:
start = datetime(2010, 1, 1)
finish = datetime(2012, 1, 1)
if intervalno == 9:
start = datetime(2012, 1, 1)
finish = datetime(2014, 1, 1)
if intervalno == 10:
start = datetime(2014, 1, 1)
finish = datetime(2016, 1, 1)
if intervalno == 11:
start = datetime(2016, 1, 1)
finish = datetime.utcnow()
if intervalno > 11:
predata = pd.read_csv(previous)
predata['time'] = pd.to_datetime(predata['time'])
start = predata['time'].max()
finish = datetime.utcnow()
print (start)
print (finish)
#define magnitude range of earthquakes to search over for shallow earthquakes
#(these are whatever magnitude range is defined in the catalogues)
min_mag = 3.0
max_mag = 9.9
magrange = (min_mag, max_mag)
#define depth to search over
min_sh = 0
max_sh = 900
depthrange_sh = (min_sh, max_sh)
#define grid size and extent of search (representative of lower left corner)
if intervalno > 11:
grid = 50.0
else:
grid = 10.0
lonmin, lonmax = -180, 180
latmin, latmax = -75, 75
#define grid of searches (representative of lower left corner)
xall = np.arange(lonmin,lonmax,grid)
yall = np.arange(latmin,latmax,grid)
lons1,lats1 = np.meshgrid(xall,yall)
#flatten into list of lower left corners
lllons = lons1.flatten()
lllats = lats1.flatten()
#define lists representing upper right corners
urlons = lllons+grid
urlats = lllats+grid
#combine into one array (lonmin,lonmax,latmin,latmax)
bounds = np.zeros((len(lllons),4))
bounds[:,0] = lllons
bounds[:,1] = urlons
bounds[:,2] = lllats
bounds[:,3] = urlats
iterations = len(bounds)
lllatfail = []
lllonfail = []
urlatfail = []
urlonfail = []
totdf = pd.DataFrame()
num = 0
for i, line in enumerate(bounds):
bounds = line
#to follow along with the progress of data querying
#since there are a lot of iterations, only print every so often
k = 100
if i % k == 0:
print ('Now querying grid %s of %s' % (i, iterations))
searchlist = search(starttime=start, endtime=finish, minlatitude=bounds[2], maxlatitude=bounds[3], minlongitude=bounds[0], maxlongitude=bounds[1], minmagnitude=3.0)
if len(searchlist) > 0:
detaildf = get_detail_data_frame(searchlist,get_tensors='preferred',get_moment_supplement=True)
totdf = pd.concat([totdf,detaildf])
print (bounds,len(detaildf),len(totdf))
if len(totdf) > 5000:
totdf.to_csv('%s/%s_%i.%i.csv'%(directory,directory,intervalno,num),header=True,index=False,na_rep=np.nan)
num += 1
totdf = pd.DataFrame()
totdf.to_csv('%s/%s_%i.csv'%(directory,directory,intervalno),header=True,index=False,na_rep=np.nan)
def main(args):
intervalno = args.intervalno
directory = args.directory
if intervalno > 11:
if args.previous is not None:
previous = args.previous
else:
print('previous file required at input if interval no > 11.')
print('enter previous file with flag -p previousFile at input')
print('Exiting ...')
exit()
os.system('mkdir %s' % directory)
if intervalno == 1:
start = datetime(1900, 1, 1)
finish = datetime(1970, 1, 1)
if intervalno == 2:
start = datetime(1970, 1, 1)
finish = datetime(1980, 1, 1)
if intervalno == 3:
start = datetime(1980, 1, 1)
finish = datetime(1990, 1, 1)
if intervalno == 4:
start = datetime(1990, 1, 1)
finish = datetime(1995, 1, 1)
if intervalno == 5:
start = datetime(1995, 1, 1)
finish = datetime(2000, 1, 1)
if intervalno == 6:
start = datetime(2000, 1, 1)
finish = datetime(2005, 1, 1)
if intervalno == 7:
start = datetime(2005, 1, 1)
finish = datetime(2010, 1, 1)
if intervalno == 8:
start = datetime(2010, 1, 1)
finish = datetime(2012, 1, 1)
if intervalno == 9:
start = datetime(2012, 1, 1)
finish = datetime(2014, 1, 1)
if intervalno == 10:
start = datetime(2014, 1, 1)
finish = datetime(2016, 1, 1)
if intervalno == 11:
start = datetime(2016, 1, 1)
finish = datetime.utcnow()
if intervalno > 11:
predata = pd.read_csv(previous)
predata['time'] = pd.to_datetime(predata['time'])
start = predata['time'].max()
finish = datetime.utcnow()
print(start)
print(finish)
#define magnitude range of earthquakes to search over for shallow earthquakes
#(these are whatever magnitude range is defined in the catalogues)
min_mag = 3.0
max_mag = 9.9
magrange = (min_mag, max_mag)
#define depth to search over
min_sh = 0
max_sh = 900
depthrange_sh = (min_sh, max_sh)
#define grid size and extent of search (representative of lower left corner)
if intervalno > 11:
grid = 50.0
else:
grid = 10.0
lonmin, lonmax = -180, 180
latmin, latmax = -75, 75
#define grid of searches (representative of lower left corner)
xall = np.arange(lonmin, lonmax, grid)
yall = np.arange(latmin, latmax, grid)
lons1, lats1 = np.meshgrid(xall, yall)
#flatten into list of lower left corners
lllons = lons1.flatten()
lllats = lats1.flatten()
#define lists representing upper right corners
urlons = lllons + grid
urlats = lllats + grid
#combine into one array (lonmin,lonmax,latmin,latmax)
bounds = np.zeros((len(lllons), 4))
bounds[:, 0] = lllons
bounds[:, 1] = urlons
bounds[:, 2] = lllats
bounds[:, 3] = urlats
iterations = len(bounds)
lllatfail = []
lllonfail = []
urlatfail = []
urlonfail = []
totdf = pd.DataFrame()
num = 0
for i, line in enumerate(bounds):
bounds = line
#to follow along with the progress of data querying
#since there are a lot of iterations, only print every so often
k = 100
if i % k == 0:
print('Now querying grid %s of %s' % (i, iterations))
searchlist = search(starttime=start,
endtime=finish,
minlatitude=bounds[2],
maxlatitude=bounds[3],
minlongitude=bounds[0],
maxlongitude=bounds[1],
minmagnitude=3.0)
if len(searchlist) > 0:
detaildf = get_detail_data_frame(searchlist,
get_tensors='preferred',
get_moment_supplement=True)
totdf = pd.concat([totdf, detaildf])
print(bounds, len(detaildf), len(totdf))
if len(totdf) > 5000:
totdf.to_csv('%s/%s_%i.%i.csv' %
(directory, directory, intervalno, num),
header=True,
index=False,
na_rep=np.nan)
num += 1
totdf = pd.DataFrame()
totdf.to_csv('%s/%s_%i.csv' % (directory, directory, intervalno),
header=True,
index=False,
na_rep=np.nan)
def get_event_comcat(shakefile, timewindow=60, degwindow=0.3, magwindow=0.2):
"""
Find an event in comcat, searching first by event id and if that
fails searching by magnitude, time, and location.
Args:
shakefile (str): path to shakemap .xml file of event to find
timewindow (float): width of time window to search around time defined
in shakefile (in seconds)
degwindow (float): width of area to search around location specified in
shakefile (in degrees).
magwindow (float): width of magnitude window to search around the
magnitude specified in shakefile.
Returns:
None if event not found, else tuple (info, detail, shakemap) where,
* info: json formatted dictionary of info.json for the event
* detail: event detail from comcat
* shakemap: shakemap of event found (from comcat)
"""
header_dicts = getHeaderData(shakefile)
grid_dict = header_dicts[0]
event_dict = header_dicts[1]
version = grid_dict['shakemap_version']
try:
eid = event_dict['event_id']
net = 'us'
if 'event_network' in event_dict:
net = event_dict['event_network']
if not eid.startswith(net):
eid = net + eid
detail = get_event_by_id(eid, includesuperseded=True)
except:
lat = event_dict['lat']
lon = event_dict['lon']
mag = event_dict['magnitude']
time = event_dict['event_timestamp']
starttime = time - timedelta(seconds=timewindow)
endtime = time + timedelta(seconds=timewindow)
minlat = lat - degwindow
minlon = lon - degwindow
maxlat = lat + degwindow
maxlon = lon + degwindow
minmag = max(0, mag - magwindow)
maxmag = min(10, mag + magwindow)
events = search(starttime=starttime,
endtime=endtime,
minmagnitude=minmag,
maxmagnitude=maxmag,
minlatitude=minlat,
minlongitude=minlon,
maxlatitude=maxlat,
maxlongitude=maxlon)
if not len(events):
return None
detail = events[0].getDetailEvent()
allversions = detail.getProducts('shakemap', version=VersionOption.ALL)
# Find the right version
vers = [allv.version for allv in allversions]
idx = np.where(np.array(vers) == version)[0][0]
shakemap = allversions[idx]
infobytes, url = shakemap.getContentBytes('info.json')
info = json.loads(infobytes.decode('utf-8'))
return info, detail, shakemap
def main():
parser = get_parser()
args = parser.parse_args()
setup_logger(args.logfile, args.loglevel)
latitude = None
longitude = None
radiuskm = None
lonmin = latmin = lonmax = latmax = None
if args.radius:
latitude = args.radius[0]
longitude = args.radius[1]
radiuskm = args.radius[2]
if args.bounds:
lonmin, lonmax, latmin, latmax = args.bounds
# fix longitude bounds when crossing dateline
if lonmin > lonmax and lonmax >= -180:
lonmin -= 360
else:
lonmin, lonmax, latmin, latmax = None, None, None, None
minmag = 0.0
maxmag = 9.9
if args.magRange:
minmag = args.magRange[0]
maxmag = args.magRange[1]
if args.getCount:
nevents = count(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
maxmagnitude=maxmag,
minmagnitude=minmag,
verbose=args.verbose)
print('There are %i events matching input criteria.' % nevents)
sys.exit(0)
if args.bounds and args.radius:
print('Please specify either a bounding box OR radius search.')
sys.exit(1)
events = search(starttime=args.startTime,
endtime=args.endTime,
updatedafter=args.after,
minlatitude=latmin,
maxlatitude=latmax,
minlongitude=lonmin,
maxlongitude=lonmax,
latitude=latitude,
longitude=longitude,
maxradiuskm=radiuskm,
maxmagnitude=maxmag,
minmagnitude=minmag,
verbose=args.verbose)
if not len(events):
print('No events found matching your search criteria. Exiting.')
sys.exit(0)
# create a dataframe with these columns - we'll add more later
df = pd.DataFrame(columns=['id', 'time', 'lat', 'lon', 'depth',
'location', 'url', 'hypo_src'])
ievent = 1
for event in events:
id_list = event['ids'].split(',')[1:-1]
source = event.id.replace(event['code'], '')
row = pd.Series(data={'id': event.id,
'time': event.time,
'lat': event.latitude,
'lon': event.longitude,
'depth': event.depth,
'location': event.location,
'url': event.url,
'hypo_src': source})
imag = 1
if args.verbose:
tpl = (event.id, ievent, len(events), len(id_list))
print('Parsing event %s (%i of %i) - %i origins' % tpl)
ievent += 1
errors = []
mags = {}
for eid in id_list:
magtypes, msg = get_all_mags(eid)
if args.verbose and len(msg):
print(msg)
mags.update(magtypes)
imag += 1
row = pd.concat([row, pd.Series(mags)])
df = df.append(row, ignore_index=True)
if len(errors):
print('Some events could not be retrieved:')
for error in errors:
print('\t%s' % error)
if args.format == 'excel':
df.to_excel(args.filename, index=False)
else:
df.to_csv(args.filename, index=False)
print('%i records saved to %s.' % (len(df), args.filename))
sys.exit(0)
from datetime import datetime
from libcomcat.dataframes import get_detail_data_frame
from libcomcat.search import search, get_event_by_id
summary_events = search(starttime=datetime(2010, 1, 1, 00, 00),
endtime=datetime(2019, 12, 31, 23, 59),
minlatitude=45,
maxlatitude=72,
minlongitude=-180,
maxlongitude=-125,
minmagnitude=4)
detail_df = get_detail_data_frame(summary_events,
get_tensors='all',
get_focals='all',
get_moment_supplement=True)
detail_df.to_pickle('usgs_alaska_2010.p')
def searchComCatforLandslides(starttime, endtime, lslat, lslon, network,
station):
"""
Returns dataframe of landslides that were recorded in ComCat between
starttime and endtime, in addition to other ComCat info.
INPUTS
starttime (UTCDateTime) - earliest time earthquakes in ComCat must
have occurred to be removed from stream object
endtime (UTCDateTime) - latest time earthquakes in ComCat must have occurred
to be removed from stream object
lslat (float) - latitudinal coordinate of landslide (make negative for south
of Equator)
lslon (float) - longitudinal coordinate of landslide (make negative for west
of Prime Meridian)
network (str) - seismic network code corresponding to station closest to
landslide, comma separated in a single string
Example: 'NF,IW,RE,TA,UU'
station (str) - name of seismic station closest to landslide, three letter
string that is not case-sensitive
Example: 'BFR,WOY,TCR,WTM'
OUTPUT
lsdf - pandas dataframe containing event IDs of landslides and potential
landslides in ComCat ('id'), event dates and times ('date'), event
coordinates ('latitude' and 'longitude'), magnitude ('magnitude'), depth
('depth'), distance to landslide we are searching for in km ('distance'),
and event type in ComCat ('eventtype').
"""
# Convert UTCDateTimes into datetimes
eqstartdt = starttime.datetime
eqenddt = endtime.datetime
# Get list of earthquakes during time window from ComCat
tempquakes = search(starttime=eqstartdt, endtime=eqenddt, minmagnitude=2.0)
quakeids = []
quakedates = []
quakelats = []
quakelons = []
quakedepths = []
quakemags = []
quakedistskm = []
quaketypes = []
# Save attributes to lists
for quake in tempquakes:
quakeids.append(quake.id)
quakedates.append(quake.time)
quakelats.append(quake.latitude)
quakelons.append(quake.longitude)
quakedepths.append(quake.depth)
quakemags.append(quake.magnitude)
quakedistskm.append(quake.distance)
quaketypes.append('earthquake')
# Get list of landslides during time window from ComCat
tempslides = search(starttime=eqstartdt,
endtime=eqenddt,
minmagnitude=2.0,
eventtype='landslide')
# Save attributes to lists
for slide in tempslides:
quakeids.append(slide.id)
quakedates.append(slide.time)
quakelats.append(slide.latitude)
quakelons.append(slide.longitude)
quakedepths.append(slide.depth)
quakemags.append(slide.magnitude)
quaketypes.append('landslide')
# Calculate distance between landslides
dkm, ddeg = calcCoordDistance(lslat, lslon, slide.latitude,
slide.longitude)
quakedistskm.append(dkm)
# Combine quake lists into pandas dataframe
lsdf = pd.DataFrame({
'id': quakeids,
'date': quakedates,
'latitude': quakelats,
'longitude': quakelons,
'depth': quakedepths,
'magnitude': quakemags,
'distance': quakedistskm,
'event type': quaketypes
})
if len(lsdf) > 0:
# Filter events by magnitude
minmag = 2.0
maxmag = 5.0
# Create dataframe to hold quakes we don't think are landslides
remove_lsdf = lsdf[(lsdf.magnitude > maxmag) |
(lsdf.magnitude < minmag)]
lsdf = lsdf[(lsdf.magnitude <= maxmag) & (lsdf.magnitude >= minmag)]
# Filter events by depth (looking for shallow earthquakes)
maxdepth = 7.0 # km
remove_lsdf = remove_lsdf.append(lsdf[lsdf.depth > maxdepth])
lsdf = lsdf[lsdf.depth <= maxdepth]
# Filter events by distance from landslide
maxdist = 10.0 # km
remove_lsdf = remove_lsdf.append(lsdf[lsdf.distance > maxdist])
lsdf = lsdf[lsdf.distance <= maxdist]
# Include events if event type is 'landslide', regardless of magnitude,
# depth, or distance
lsdf = lsdf.append(
remove_lsdf[remove_lsdf['event type'] == 'landslide'])
return (lsdf)
def test_get_detail_data_frame():
events = search(starttime=datetime(1994,6,1),
endtime=datetime(1994,10,6),
minmagnitude=8.0,maxmagnitude=9.0)
all_mags = get_detail_data_frame(events,get_all_magnitudes=True,verbose=True)
assert all_mags.iloc[0]['magnitude'] == 8.2
def getQuakeDict(starttime, endtime, network, station):
"""
Determines when earthquakes from ComCat arrived at seismic station closest
to landslide, returns dictionary containing earthquake arrival times and
other identifying information.
INPUTS
starttime (UTCDateTime) - earliest time earthquakes in ComCat must
have occurred to be returned
endtime (UTCDateTime) - latest time earthquakes in ComCat must have
occurred to be returned
network (str) - seismic network code corresponding to station closest to
landslide, comma separated in a single string
Example: 'NF,IW,RE,TA,UU'
station (str) - name of seismic station closest to landslide, three letter
string that is not case-sensitive
Example: 'BFR,WOY,TCR,WTM'
OUTPUT
quakedict - dictionary containing full earthquake summaries from ComCat
('summary'), earthquake IDs in ComCat ('id'), dates and times ('date'),
coordinates of earthquake epicenter ('latitude' and 'longitude'), depth
to earthquake epicenter ('depth'), distance of earthquake to landslide
in km ('distance'), earthquake magnitude ('magnitude'), calculated
arrival time of earthquake at seismic station closest to landslide
('arrival time'), and event type ('event type') -- 'earthquake' for
all events here.
"""
# Get coordinates of nearest station to landslide
stationlat, stationlon = getStationCoordinates(network, station)
# Get list of earthquakes that happened between starttime and endtime
# from ComCat
eqstartdt = starttime.datetime
eqenddt = endtime.datetime
tempquakes = search(starttime=eqstartdt,
endtime=eqenddt,
minmagnitude=0.5,
mindepth=0.0)
quakeids = []
quakedates = []
quakelats = []
quakelons = []
quakedepths = []
quakemags = []
# Save attributes to lists
for quake in tempquakes:
quakeids.append(quake.id)
quakedates.append(quake.time)
quakelats.append(quake.latitude)
quakelons.append(quake.longitude)
quakedepths.append(quake.depth)
quakemags.append(quake.magnitude)
# Create dictionary for attributes
quakedict = {}
eqkeys = [
'id', 'date', 'latitude', 'longitude', 'depth', 'distance',
'magnitude', 'arrival time', 'event type'
]
for key in eqkeys:
quakedict[key] = []
quakedict['id'] = [quakeid for quakeid in quakeids]
quakedict['date'] = [quakedate for quakedate in quakedates]
quakedict['latitude'] = [quakelat for quakelat in quakelats]
quakedict['longitude'] = [quakelon for quakelon in quakelons]
quakedict['depth'] = [quakedepth for quakedepth in quakedepths]
quakedict['magnitude'] = [quakemag for quakemag in quakemags]
quakedict['event type'] = ['earthquake'] * len(quakeids)
quakedistskm, arrivaltimes = findEQArrivalTimes(network, station,
quakedict)
quakedict['distance'] = [quakedist for quakedist in quakedistskm]
quakedict['arrival time'] = [arrivaltime for arrivaltime in arrivaltimes]
return (quakedict)
def main():
pd.set_option('display.width', 1000)
pd.set_option('display.max_rows', 1000)
pd.set_option('display.max_colwidth', -1)
pd.set_option('display.max_columns', 1000)
pd.set_option("display.colheader_justify", "left")
parser = get_parser()
args = parser.parse_args()
setup_logger(args.logfile, args.loglevel)
# make sure that input products are in the list of supported products
if not set(args.products) <= set(PRODUCTS):
unsupported = list(set(args.products) - set(PRODUCTS))
fmt = 'The following event products are not supported: '
print(fmt % (','.join(unsupported)))
sys.exit(1)
# make sure that excluded products are in the list of supported products
if not set(args.exclude_products) <= set(PRODUCTS):
unsupported = list(set(args.exclude_products) - set(PRODUCTS))
fmt = ('The following event products you want to exclude '
'are not supported: ')
print(fmt % (','.join(unsupported)))
sys.exit(1)
# web output and directory output are mutually exclusive
if args.outdir and args.web:
msg = '''The -o and -w options are mutually exclusive, meaning
that you cannot choose to write files to a directory and print
HTML output to the screen simultaneously. Please choose one of
those two options and try again.
'''
print(msg)
sys.exit(1)
if args.products:
products = args.products
else:
products = PRODUCTS
if args.exclude_products:
products = set(products) - set(args.exclude_products)
try:
dataframe, event = get_history_data_frame(args.eventid, products)
except Exception as e:
fmt = '''Failed to retrieve event history data for
event %s. Error message is as follows. Exiting.
"%s"
'''
tpl = (args.eventid, str(e))
print(fmt % tpl)
sys.exit(1)
if args.radius:
radius_km = args.radius[0]
radius_secs = args.radius[1]
stime = event.time - timedelta(seconds=radius_secs)
etime = event.time + timedelta(seconds=radius_secs)
eventlist = search(starttime=stime,
endtime=etime,
latitude=event.latitude,
longitude=event.longitude,
maxradiuskm=radius_km)
for tevent in eventlist:
if tevent.id == event.id:
continue
detail = tevent.getDetailEvent(includesuperseded=True)
tframe = get_history_data_frame(detail, products)
newframe = _mod_tframe(event, tevent, tframe)
dataframe = dataframe.append(newframe, ignore_index=True)
# now re-sort by update time
dataframe = dataframe.sort_values('Update Time')
dataframe = dataframe[PRODUCT_COLUMNS]
else:
# since "Authoritative Event ID" and "Associated" columns are only applicable when
# we're including other events in our results, drop those columns
# if we're not doing that.
drop_columns = ['Authoritative Event ID', 'Associated']
dataframe = dataframe.drop(drop_columns, axis='columns')
if args.outdir is not None and not os.path.isdir(args.outdir):
os.makedirs(args.outdir)
if args.split:
df_products = dataframe['Product'].unique().tolist()
available_products = set(df_products) & set(products)
# TODO: Consider merging phase-data and origin products
# somehow in this process
for product in available_products:
pframe = split_history_frame(dataframe, product=product)
simplify_times(pframe)
if args.web:
web_print(event, pframe)
else:
outfile = save_dataframe(args.outdir,
args.format,
event,
pframe,
product=product)
print('%i rows saved to %s' % (len(pframe), outfile))
sys.exit(0)
if args.outdir:
outfile = save_dataframe(args.outdir,
args.format,
event,
dataframe,
product=None)
print('%i rows saved to %s' % (len(dataframe), outfile))
elif args.web:
simplify_times(dataframe)
web_print(event, dataframe)
sys.exit(0)
def main(args):
events = search(starttime=args.start,
endtime=args.end,
minlatitude=args.latmin,
maxlatitude=args.latmax,
minlongitude=args.lonmin,
maxlongitude=args.lonmax,
producttype='shakemap',
maxmagnitude=args.magRange[1],
minmagnitude=args.magRange[0])
print('%i events found containing ShakeMaps.' % len(events))
# Create the GeoDict to which the ShakeMaps will be resampled
stack_dict = GeoDict.createDictFromBox(args.lonmin, args.lonmax,
args.latmin, args.latmax,
args.resolution, args.resolution)
nrows, ncols = stack_dict.ny, stack_dict.nx
imts = {}
layer_names = {}
event_info = {}
layer_count = {}
ic = 0
for event in events:
tnow = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')
if ic % 10 == 0:
print('%s: Attempting to fetch ShakeMap for %s (%i of %i)' %
(tnow, event.id, ic, len(events)))
ic += 1
event_info[event.id] = event.toDict()
try:
detail = event.getDetailEvent()
except Exception as e:
fmt = 'Could not retrieve detail data for event %s, error "%s". Skipping.'
print(fmt % (event.id, str(e)))
continue
if not detail.hasProduct('shakemap'):
print(
'Event %s appears not to have a ShakeMap after all... skipping.'
% detail.id)
shakemap = detail.getProducts('shakemap')[0]
try:
f, gridfile = tempfile.mkstemp()
os.close(f)
shakemap.getContent('grid.xml', gridfile)
shakegrid = ShakeGrid.load(gridfile,
samplegeodict=stack_dict,
resample=True,
doPadding=True)
imtlist = list(shakegrid.getLayerNames())
# remove the things that are not ground motions
kill_list = ['stdpga', 'urat', 'svel']
for layer in kill_list:
if layer in imtlist:
imtlist.remove(layer)
for imt in imtlist:
imtdata = shakegrid.getLayer(imt).getData()
if imt not in imts:
imts[imt] = np.zeros((nrows, ncols, len(events)))
layer_count[imt] = 0
idx = 0
layer_names[imt] = [event.id]
else:
idx = layer_count[imt] + 1
layer_names[imt].append(event.id)
layer_count[imt] = layer_count[imt] + 1
imts[imt][:, :, idx] = imtdata
except Exception as e:
print('Error fetching ShakeMap grid from %s - "%s". Skipping.' %
(event.id, str(e)))
finally:
os.remove(gridfile)
# make sure all imts have valid grids in each vertical layer
# trim off any layers that don't have any data in them.
for imtname, imtcube in imts.items():
height_diff = len(events) - (layer_count[imtname] + 1)
if height_diff:
top_layer = layer_count[imtname]
imts[imtname] = imtcube[:, :, 0:top_layer]
# now create an HDF file, and stuff our data and metadata into it
stack_file = GridHDFContainer.create(args.outputfile)
stack_file.setDictionary('layer_names', layer_names)
stack_file.setDictionary('event', event_info)
metadata = stack_dict.asDict()
for imtname, imtcube in imts.items():
stack_file.setArray(imtname,
imtcube,
metadata=metadata,
compression=True)
stack_file.close()
