def test_north():
# north-ish angles
assert is_channel_north(0)
assert is_channel_north(44)
assert is_channel_north(136)
assert is_channel_north(224)
assert not is_channel_north(90)
assert not is_channel_north(45)
assert not is_channel_north(314)
assert not is_channel_north(134)
def test_north():
# north-ish angles
assert is_channel_north(0)
assert is_channel_north(44)
assert is_channel_north(136)
assert is_channel_north(224)
assert not is_channel_north(90)
assert not is_channel_north(45)
assert not is_channel_north(314)
assert not is_channel_north(134)
def read_fdsn(filename):
"""Read Obspy data file (SAC, MiniSEED, etc).
Args:
filename (str):
Path to data file.
kwargs (ref):
Other arguments will be ignored.
Returns:
Stream: StationStream object.
"""
logging.debug("Starting read_fdsn.")
if not is_fdsn(filename):
raise Exception('%s is not a valid Obspy file format.' % filename)
streams = []
tstream = read(filename)
xmlfile = _get_station_file(filename, tstream)
inventory = read_inventory(xmlfile)
traces = []
for ttrace in tstream:
trace = StationTrace(data=ttrace.data,
header=ttrace.stats,
inventory=inventory)
location = ttrace.stats.location
trace.stats.channel = get_channel_name(
trace.stats.sampling_rate, trace.stats.channel[1] == 'N',
inventory.get_orientation(trace.id)['dip'] in [90, -90]
or trace.stats.channel[2] == 'Z',
is_channel_north(inventory.get_orientation(trace.id)['azimuth']))
if trace.stats.location == '':
trace.stats.location = '--'
network = ttrace.stats.network
if network in LOCATION_CODES:
codes = LOCATION_CODES[network]
if location in codes:
sdict = codes[location]
if sdict['free_field']:
trace.stats.standard.structure_type = 'free_field'
else:
trace.stats.standard.structure_type = sdict['description']
head, tail = os.path.split(filename)
trace.stats['standard']['source_file'] = tail or os.path.basename(head)
traces.append(trace)
stream = StationStream(traces=traces)
streams.append(stream)
return streams
def _read_header(filename):
# read in first 88 lines
with open(filename, "rt") as myfile:
header = [next(myfile) for x in range(HEADER_LINES)]
header_dict = {}
lastkey = ""
for line in header:
if not len(line.strip()):
continue
if ":" in line:
colidx = line.find(":")
key = line[0:colidx].strip()
value = line[colidx + 1:].strip()
if not len(key):
key = lastkey + "$"
lastkey = key
header_dict[key] = value
# create a list of dictionaries for channel spec
channels = [{}, {}, {}]
channels[0]["standard"] = {}
channels[1]["standard"] = {}
channels[2]["standard"] = {}
station = header_dict["CLAVE DE LA ESTACION"]
channels[0]["station"] = station
channels[1]["station"] = station
channels[2]["station"] = station
channels[0]["network"] = NETWORK
channels[1]["network"] = NETWORK
channels[2]["network"] = NETWORK
# unam provides the start *time* of the record, but not the date.
# it is up to us to determine whether midnight has occurred between
# eq time and record start time.
# the hour/min/sec of trigger time
(rhour, rminute,
rsecond) = header_dict["HORA DE LA PRIMERA MUESTRA (GMT)"].split(":")
dtsecs = (int(rhour) * 3600) + (int(rminute) * 60) + (float(rsecond))
startdt = timedelta(seconds=dtsecs)
eqdatestr = header_dict["FECHA DEL SISMO [GMT]"]
eqdate = datetime.strptime(eqdatestr, "%Y/%m/%d")
# the hour, minute and second of origin
eqtimestr = header_dict["HORA EPICENTRO (GMT)"]
try:
eqtime = datetime.strptime(f"{eqdatestr} {eqtimestr}", TIMEFMT1)
except ValueError:
eqtime = datetime.strptime(f"{eqdatestr} {eqtimestr}", TIMEFMT2)
# if the origin time and record start time are more than 10 minutes
# apart (in either direction), then assume that we need to add 1 day
# to the record start time.
starttime = eqdate + startdt
dt = np.abs((starttime - eqtime).total_seconds())
if dt > MAX_TIME_DIFF:
starttime = eqdate + timedelta(days=1) + startdt
channels[0]["starttime"] = starttime
channels[1]["starttime"] = starttime
channels[2]["starttime"] = starttime
# get record durations for each channel
durstr = header_dict["DURACION DEL REGISTRO (s), C1-C6"].lstrip("/")
durations = [float(dur) for dur in durstr.split("/")]
channels[0]["duration"] = durations[0]
channels[1]["duration"] = durations[1]
channels[2]["duration"] = durations[2]
# get deltas
delta_strings = header_dict["INTERVALO DE MUESTREO, C1-C6 (s)"].split("/")
deltas = [float(delta) for delta in delta_strings[1:]]
channels[0]["delta"] = deltas[0]
channels[1]["delta"] = deltas[1]
channels[2]["delta"] = deltas[2]
# get sampling rates
channels[0]["sampling_rate"] = 1 / deltas[0]
channels[1]["sampling_rate"] = 1 / deltas[1]
channels[2]["sampling_rate"] = 1 / deltas[2]
# get channel orientations
azstrings = header_dict["ORIENTACION C1-C6 (rumbo;orientacion)"].split("/")
az1, az1_vert = _get_azimuth(azstrings[1])
az2, az2_vert = _get_azimuth(azstrings[2])
az3, az3_vert = _get_azimuth(azstrings[3])
channels[0]["standard"]["horizontal_orientation"] = az1
channels[1]["standard"]["horizontal_orientation"] = az2
channels[2]["standard"]["horizontal_orientation"] = az3
channels[0]["standard"]["vertical_orientation"] = np.nan
channels[1]["standard"]["vertical_orientation"] = np.nan
channels[2]["standard"]["vertical_orientation"] = np.nan
az1_north = is_channel_north(az1)
az2_north = is_channel_north(az2)
az3_north = is_channel_north(az3)
channels[0]["channel"] = get_channel_name(channels[0]["sampling_rate"],
True, az1_vert, az1_north)
channels[1]["channel"] = get_channel_name(channels[1]["sampling_rate"],
True, az2_vert, az2_north)
channels[2]["channel"] = get_channel_name(channels[2]["sampling_rate"],
True, az3_vert, az3_north)
# get channel npts
npts_strings = header_dict["NUM. TOTAL DE MUESTRAS, C1-C6"].split("/")
npts_list = [float(npts) for npts in npts_strings[1:]]
channels[0]["npts"] = npts_list[0]
channels[1]["npts"] = npts_list[1]
channels[2]["npts"] = npts_list[2]
# locations
channels[0]["location"] = "--"
channels[1]["location"] = "--"
channels[1]["location"] = "--"
# get station coordinates
coord1 = header_dict["COORDENADAS DE LA ESTACION"]
coord2 = header_dict["COORDENADAS DE LA ESTACION$"]
if "LAT" in coord1:
latitude = float(re.search(FLOATRE, coord1).group())
longitude = float(re.search(FLOATRE, coord2).group())
if coord1.strip().endswith("S"):
latitude *= -1
if coord2.strip().endswith("W"):
longitude *= -1
else:
latitude = re.search(FLOATRE, coord2)
longitude = re.search(FLOATRE, coord1)
if coord1.strip().endswith("W"):
longitude *= -1
if coord2.strip().endswith("S"):
latitude *= -1
elevation = float(header_dict["ALTITUD (msnm)"])
cdict = {
"latitude": latitude,
"longitude": longitude,
"elevation": elevation
}
channels[0]["coordinates"] = cdict
channels[1]["coordinates"] = cdict
channels[2]["coordinates"] = cdict
# fill in other standard stuff
standard0 = channels[0]["standard"]
standard1 = channels[1]["standard"]
standard2 = channels[2]["standard"]
standard0["units_type"] = "acc"
standard1["units_type"] = "acc"
standard2["units_type"] = "acc"
standard0["source_format"] = SOURCE_FORMAT
standard1["source_format"] = SOURCE_FORMAT
standard2["source_format"] = SOURCE_FORMAT
standard0["instrument"] = header_dict["MODELO DEL ACELEROGRAFO"]
standard1["instrument"] = header_dict["MODELO DEL ACELEROGRAFO"]
standard2["instrument"] = header_dict["MODELO DEL ACELEROGRAFO"]
standard0["sensor_serial_number"] = header_dict[
"NUMERO DE SERIE DEL ACELEROGRAFO"]
standard1["sensor_serial_number"] = header_dict[
"NUMERO DE SERIE DEL ACELEROGRAFO"]
standard2["sensor_serial_number"] = header_dict[
"NUMERO DE SERIE DEL ACELEROGRAFO"]
standard0["process_level"] = PROCESS_LEVELS["V1"]
standard1["process_level"] = PROCESS_LEVELS["V1"]
standard2["process_level"] = PROCESS_LEVELS["V1"]
standard0["process_time"] = ""
standard1["process_time"] = ""
standard2["process_time"] = ""
standard0["station_name"] = header_dict["NOMBRE DE LA ESTACION"]
standard1["station_name"] = header_dict["NOMBRE DE LA ESTACION"]
standard2["station_name"] = header_dict["NOMBRE DE LA ESTACION"]
standard0["structure_type"] = ""
standard1["structure_type"] = ""
standard2["structure_type"] = ""
standard0["corner_frequency"] = np.nan
standard1["corner_frequency"] = np.nan
standard2["corner_frequency"] = np.nan
standard0["units"] = "cm/s/s"
standard1["units"] = "cm/s/s"
standard2["units"] = "cm/s/s"
periods = _get_periods(header_dict["FREC. NAT. DE SENSORES, C1-C6, (Hz)"])
standard0["instrument_period"] = periods[0]
standard1["instrument_period"] = periods[1]
standard2["instrument_period"] = periods[2]
dampings = _get_dampings(header_dict["AMORTIGUAMIENTO DE SENSORES, C1-C6"])
standard0["instrument_damping"] = dampings[0]
standard1["instrument_damping"] = dampings[1]
standard2["instrument_damping"] = dampings[2]
with open(filename, "rt") as myfile:
header = [next(myfile) for x in range(HEADER_PLUS_COMMENT)]
clines = header[89:102]
comments = " ".join(clines).strip()
standard0["comments"] = comments
standard1["comments"] = comments
standard2["comments"] = comments
head, tail = os.path.split(filename)
source_file = tail or os.path.basename(head)
standard0["source_file"] = source_file
standard1["source_file"] = source_file
standard2["source_file"] = source_file
standard0["source"] = SOURCE
standard1["source"] = SOURCE
standard2["source"] = SOURCE
decfactor = float(header_dict["FACTOR DE DECIMACION"])
standard0["instrument_sensitivity"] = decfactor
standard1["instrument_sensitivity"] = decfactor
standard2["instrument_sensitivity"] = decfactor
standard0["volts_to_counts"] = np.nan
standard1["volts_to_counts"] = np.nan
standard2["volts_to_counts"] = np.nan
return channels
def _read_header(filename):
# read in first 88 lines
with open(filename, 'rt') as myfile:
header = [next(myfile) for x in range(HEADER_LINES)]
header_dict = {}
lastkey = ''
for line in header:
if not len(line.strip()):
continue
if ':' in line:
colidx = line.find(':')
key = line[0:colidx].strip()
value = line[colidx + 1:].strip()
if not len(key):
key = lastkey + '$'
lastkey = key
header_dict[key] = value
# create a list of dictionaries for channel spec
channels = [{}, {}, {}]
channels[0]['standard'] = {}
channels[1]['standard'] = {}
channels[2]['standard'] = {}
station = header_dict['CLAVE DE LA ESTACION']
channels[0]['station'] = station
channels[1]['station'] = station
channels[2]['station'] = station
channels[0]['network'] = NETWORK
channels[1]['network'] = NETWORK
channels[2]['network'] = NETWORK
# unam provides the start *time* of the record, but not the date.
# it is up to us to determine whether midnight has occurred between
# eq time and record start time.
# the hour/min/sec of trigger time
(rhour, rminute,
rsecond) = header_dict['HORA DE LA PRIMERA MUESTRA (GMT)'].split(':')
dtsecs = (int(rhour) * 3600) + (int(rminute) * 60) + (float(rsecond))
startdt = timedelta(seconds=dtsecs)
eqdatestr = header_dict['FECHA DEL SISMO [GMT]']
eqdate = datetime.strptime(eqdatestr, '%Y/%m/%d')
# the hour, minute and second of origin
eqtimestr = header_dict['HORA EPICENTRO (GMT)']
try:
eqtime = datetime.strptime('%s %s' % (eqdatestr, eqtimestr), TIMEFMT1)
except ValueError:
eqtime = datetime.strptime('%s %s' % (eqdatestr, eqtimestr), TIMEFMT2)
# if the origin time and record start time are more than 10 minutes
# apart (in either direction), then assume that we need to add 1 day
# to the record start time.
starttime = eqdate + startdt
dt = np.abs((starttime - eqtime).total_seconds())
if dt > MAX_TIME_DIFF:
starttime = eqdate + timedelta(days=1) + startdt
channels[0]['starttime'] = starttime
channels[1]['starttime'] = starttime
channels[2]['starttime'] = starttime
# get record durations for each channel
durstr = header_dict['DURACION DEL REGISTRO (s), C1-C6'].lstrip('/')
durations = [float(dur) for dur in durstr.split('/')]
channels[0]['duration'] = durations[0]
channels[1]['duration'] = durations[1]
channels[2]['duration'] = durations[2]
# get deltas
delta_strings = header_dict['INTERVALO DE MUESTREO, C1-C6 (s)'].split('/')
deltas = [float(delta) for delta in delta_strings[1:]]
channels[0]['delta'] = deltas[0]
channels[1]['delta'] = deltas[1]
channels[2]['delta'] = deltas[2]
# get sampling rates
channels[0]['sampling_rate'] = 1 / deltas[0]
channels[1]['sampling_rate'] = 1 / deltas[1]
channels[2]['sampling_rate'] = 1 / deltas[2]
# get channel orientations
azstrings = header_dict['ORIENTACION C1-C6 (rumbo;orientacion)'].split('/')
az1, az1_vert = _get_azimuth(azstrings[1])
az2, az2_vert = _get_azimuth(azstrings[2])
az3, az3_vert = _get_azimuth(azstrings[3])
channels[0]['standard']['horizontal_orientation'] = az1
channels[1]['standard']['horizontal_orientation'] = az2
channels[2]['standard']['horizontal_orientation'] = az3
channels[0]['standard']['vertical_orientation'] = np.nan
channels[1]['standard']['vertical_orientation'] = np.nan
channels[2]['standard']['vertical_orientation'] = np.nan
az1_north = is_channel_north(az1)
az2_north = is_channel_north(az2)
az3_north = is_channel_north(az3)
channels[0]['channel'] = get_channel_name(channels[0]['sampling_rate'],
True, az1_vert, az1_north)
channels[1]['channel'] = get_channel_name(channels[1]['sampling_rate'],
True, az2_vert, az2_north)
channels[2]['channel'] = get_channel_name(channels[2]['sampling_rate'],
True, az3_vert, az3_north)
# get channel npts
npts_strings = header_dict['NUM. TOTAL DE MUESTRAS, C1-C6'].split('/')
npts_list = [float(npts) for npts in npts_strings[1:]]
channels[0]['npts'] = npts_list[0]
channels[1]['npts'] = npts_list[1]
channels[2]['npts'] = npts_list[2]
# locations
channels[0]['location'] = '--'
channels[1]['location'] = '--'
channels[1]['location'] = '--'
# get station coordinates
coord1 = header_dict['COORDENADAS DE LA ESTACION']
coord2 = header_dict['COORDENADAS DE LA ESTACION$']
if 'LAT' in coord1:
latitude = float(re.search(FLOATRE, coord1).group())
longitude = float(re.search(FLOATRE, coord2).group())
if coord1.strip().endswith('S'):
latitude *= -1
if coord2.strip().endswith('W'):
longitude *= -1
else:
latitude = re.search(FLOATRE, coord2)
longitude = re.search(FLOATRE, coord1)
if coord1.strip().endswith('W'):
longitude *= -1
if coord2.strip().endswith('S'):
latitude *= -1
elevation = float(header_dict['ALTITUD (msnm)'])
cdict = {
'latitude': latitude,
'longitude': longitude,
'elevation': elevation
}
channels[0]['coordinates'] = cdict
channels[1]['coordinates'] = cdict
channels[2]['coordinates'] = cdict
# fill in other standard stuff
channels[0]['standard']['units_type'] = 'acc'
channels[1]['standard']['units_type'] = 'acc'
channels[2]['standard']['units_type'] = 'acc'
channels[0]['standard']['source_format'] = SOURCE_FORMAT
channels[1]['standard']['source_format'] = SOURCE_FORMAT
channels[2]['standard']['source_format'] = SOURCE_FORMAT
channels[0]['standard']['instrument'] = header_dict[
'MODELO DEL ACELEROGRAFO']
channels[1]['standard']['instrument'] = header_dict[
'MODELO DEL ACELEROGRAFO']
channels[2]['standard']['instrument'] = header_dict[
'MODELO DEL ACELEROGRAFO']
channels[0]['standard']['sensor_serial_number'] = header_dict[
'NUMERO DE SERIE DEL ACELEROGRAFO']
channels[1]['standard']['sensor_serial_number'] = header_dict[
'NUMERO DE SERIE DEL ACELEROGRAFO']
channels[2]['standard']['sensor_serial_number'] = header_dict[
'NUMERO DE SERIE DEL ACELEROGRAFO']
channels[0]['standard']['process_level'] = PROCESS_LEVELS['V1']
channels[1]['standard']['process_level'] = PROCESS_LEVELS['V1']
channels[2]['standard']['process_level'] = PROCESS_LEVELS['V1']
channels[0]['standard']['process_time'] = ''
channels[1]['standard']['process_time'] = ''
channels[2]['standard']['process_time'] = ''
channels[0]['standard']['station_name'] = header_dict[
'NOMBRE DE LA ESTACION']
channels[1]['standard']['station_name'] = header_dict[
'NOMBRE DE LA ESTACION']
channels[2]['standard']['station_name'] = header_dict[
'NOMBRE DE LA ESTACION']
channels[0]['standard']['structure_type'] = ''
channels[1]['standard']['structure_type'] = ''
channels[2]['standard']['structure_type'] = ''
channels[0]['standard']['corner_frequency'] = np.nan
channels[1]['standard']['corner_frequency'] = np.nan
channels[2]['standard']['corner_frequency'] = np.nan
channels[0]['standard']['units'] = 'cm/s/s'
channels[1]['standard']['units'] = 'cm/s/s'
channels[2]['standard']['units'] = 'cm/s/s'
periods = _get_periods(header_dict['FREC. NAT. DE SENSORES, C1-C6, (Hz)'])
channels[0]['standard']['instrument_period'] = periods[0]
channels[1]['standard']['instrument_period'] = periods[1]
channels[2]['standard']['instrument_period'] = periods[2]
dampings = _get_dampings(header_dict['AMORTIGUAMIENTO DE SENSORES, C1-C6'])
channels[0]['standard']['instrument_damping'] = dampings[0]
channels[1]['standard']['instrument_damping'] = dampings[1]
channels[2]['standard']['instrument_damping'] = dampings[2]
with open(filename, 'rt') as myfile:
header = [next(myfile) for x in range(HEADER_PLUS_COMMENT)]
clines = header[89:102]
comments = ' '.join(clines).strip()
channels[0]['standard']['comments'] = comments
channels[1]['standard']['comments'] = comments
channels[2]['standard']['comments'] = comments
head, tail = os.path.split(filename)
source_file = tail or os.path.basename(head)
channels[0]['standard']['source_file'] = source_file
channels[1]['standard']['source_file'] = source_file
channels[2]['standard']['source_file'] = source_file
channels[0]['standard']['source'] = SOURCE
channels[1]['standard']['source'] = SOURCE
channels[2]['standard']['source'] = SOURCE
decfactor = float(header_dict['FACTOR DE DECIMACION'])
channels[0]['standard']['instrument_sensitivity'] = decfactor
channels[1]['standard']['instrument_sensitivity'] = decfactor
channels[2]['standard']['instrument_sensitivity'] = decfactor
return channels
