def _extract_index_values_seed(filename):
"""
Reads SEED files and extracts some keys per channel.
"""
try:
p = Parser(filename)
except:
msg = "Not a valid SEED file?"
raise StationCacheError(msg)
channels = p.getInventory()["channels"]
channels = [
[
_i["channel_id"],
int(_i["start_date"].timestamp),
int(_i["end_date"].timestamp) if _i["end_date"] else None,
_i["latitude"],
_i["longitude"],
_i["elevation_in_m"],
_i["local_depth_in_m"],
]
for _i in channels
]
return channels
def stats_from_dataless(self, metadata_path=None):
"""
Function that returns a (1,N) shaped array of the station names
from a dataless SEED file.
"""
if metadata_path is None:
metadata_path = self.metadata_path
sp = Parser(metadata_path)
metadata = Parser.getInventory(sp)
stats = np.asarray(
[stat['station_id'] for stat in metadata['stations']])
return stats
def stats_from_dataless(self, metadata_path=None):
"""
Function that returns a (1,N) shaped array of the station names
from a dataless SEED file.
"""
if metadata_path is None:
metadata_path = self.metadata_path
sp = Parser(metadata_path)
metadata = Parser.getInventory(sp)
stats = np.asarray([stat['station_id'] for
stat in metadata['stations']])
return stats
def _extract_index_values_seed(self, filename):
"""
Reads SEED files and extracts some keys per channel.
"""
try:
p = Parser(filename)
except:
msg = "Could not read SEED file '%s'." % filename
raise ValueError(msg)
channels = p.getInventory()["channels"]
channels = [[
_i["channel_id"],
int(_i["start_date"].timestamp),
int(_i["end_date"].timestamp) if _i["end_date"] else None,
_i["latitude"], _i["longitude"], _i["elevation_in_m"],
_i["local_depth_in_m"]
] for _i in channels]
return channels
def locs_from_dataless(self, metadata_path=None):
"""
Function that returns a numpy (2,N) shaped array of the longitude
latitude coordinates (in degree, decimal) from a dataless SEED file.
"""
if metadata_path is None:
metadata_path = self.metadata_path
sp = Parser(metadata_path)
metadata = Parser.getInventory(sp)
lats = np.asarray([float(i['latitude']) for i in metadata['channels']])
lons = np.asarray(
[float(i['longitude']) for i in metadata['channels']])
elev = np.asarray(
[float(i['elevation_in_m']) for i in metadata['channels']])
return np.column_stack((lons, lats, elev))
def _read_SEED(string_io):
"""
Attempt to read the file as a SEED file. If it not a valid SEED file,
it will return False.
"""
try:
parser = Parser(string_io)
except:
return False
if len(str(parser)) == 0:
return False
channels = parser.getInventory()["channels"]
for channel in channels:
channel_id = channel.pop("channel_id")
del channel["sampling_rate"]
net, sta, loc, cha = channel_id.split(".")
channel["network"] = net
channel["station"] = sta
channel["location"] = loc
channel["channel"] = cha
if not channel["end_date"]:
time = channel["start_date"] + 2 * 86400
else:
time = channel["start_date"] + 0.5 * (channel["end_date"] -
channel["start_date"])
try:
location = parser.getCoordinates(channel_id, time)
channel["latitude"] = location["latitude"]
channel["longitude"] = location["longitude"]
channel["elevation"] = location["elevation"]
channel["local_depth"] = location["local_depth"]
except:
msg = ("Cannot retrieve location for channel. This happens when "
"overlapping time periods are defined in the SEED file. "
"Please fix the file. Contents of the file:\n")
msg += str(parser)
raise InvalidObjectError(msg)
channel["format"] = parser._format
return channels
def locs_from_dataless(self, metadata_path=None):
"""
Function that returns a numpy (2,N) shaped array of the longitude
latitude coordinates (in degree, decimal) from a dataless SEED file.
"""
if metadata_path is None:
metadata_path = self.metadata_path
sp = Parser(metadata_path)
metadata = Parser.getInventory(sp)
lats = np.asarray([float(i['latitude']) for i
in metadata['channels']])
lons = np.asarray([float(i['longitude']) for i
in metadata['channels']])
elev = np.asarray([float(i['elevation_in_m']) for i
in metadata['channels']])
return np.column_stack((lons, lats, elev))
plt.grid()
plt.savefig("/Users/lion/Desktop/SourceRadius.pdf")
if __name__ == "__main__":
# Read all instrument responses.
widgets = ['Parsing instrument responses...', progressbar.Percentage(),
' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(widgets=widgets,
maxval=len(STATION_FILES)).start()
parsers = {}
# Read all waveform files.
for _i, xseed in enumerate(STATION_FILES):
pbar.update(_i)
parser = Parser(xseed)
channels = [c['channel_id'] for c in parser.getInventory()['channels']]
parsers_ = dict.fromkeys(channels, parser)
if any([k in parsers for k in parsers_.keys()]):
msg = "Channel(s) defined in more than one metadata file."
warnings.warn(msg)
parsers.update(parsers_)
pbar.finish()
# Parse all waveform files.
widgets = ['Indexing waveform files... ', progressbar.Percentage(),
' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(widgets=widgets,
maxval=len(WAVEFORM_FILES)).start()
waveform_index = {}
# Read all waveform files.
for _i, waveform in enumerate(WAVEFORM_FILES):
minlongitude = 110.0
maxlatitude = 0.0
maxlongitude = 160.0
plt.figure(1)
colours = ["black", "blue", "green", "yellow", "purple",
"orange", "white", "red", "brown"]
dataless_files = glob.glob('/home/boland/Dropbox/University/UniMelb/AGOS/PROGRAMS/dataless/*.dataless')
for index, files in enumerate(dataless_files):
network = os.path.basename(files).split('.')[0]
sp = Parser(files)
info = sp.getInventory()
coordinates = [(i['longitude'], i['latitude'], i['channel_id'])
for i in info['channels'][:] if i['channel_id'][-3:] == "BHZ"]
#dataless_inventories = []
#if USE_DATALESSPAZ:
# with warnings.catch_warnings():
# warnings.simplefilter('ignore')
# dataless_inventories = psstation.get_dataless_inventories(DATALESS_DIR,
# verbose=True)
# info = dataless_inventories.getInventory()
# coordinates = [(i['longitude'], i['latitude'], i['channel_id'])
plt.figure(1)
colours = [
"black", "blue", "green", "yellow", "purple", "orange", "white", "red",
"brown"
]
dataless_files = glob.glob(
'/home/boland/Dropbox/University/UniMelb/AGOS/PROGRAMS/dataless/*.dataless'
)
for index, files in enumerate(dataless_files):
network = os.path.basename(files).split('.')[0]
sp = Parser(files)
info = sp.getInventory()
coordinates = [(i['longitude'], i['latitude'], i['channel_id'])
for i in info['channels'][:]
if i['channel_id'][-3:] == "BHZ"]
#dataless_inventories = []
#if USE_DATALESSPAZ:
# with warnings.catch_warnings():
# warnings.simplefilter('ignore')
# dataless_inventories = psstation.get_dataless_inventories(DATALESS_DIR,
# verbose=True)
# info = dataless_inventories.getInventory()
# coordinates = [(i['longitude'], i['latitude'], i['channel_id'])
plt.grid()
plt.savefig("/Users/lion/Desktop/SourceRadius.pdf")
if __name__ == "__main__":
# Read all instrument responses.
widgets = ['Parsing instrument responses...', progressbar.Percentage(),
' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(widgets=widgets,
maxval=len(STATION_FILES)).start()
parsers = {}
# Read all waveform files.
for _i, xseed in enumerate(STATION_FILES):
pbar.update(_i)
parser = Parser(xseed)
channels = [c['channel_id'] for c in parser.getInventory()['channels']]
parsers_ = dict.fromkeys(channels, parser)
if any([k in parsers for k in parsers_.keys()]):
msg = "Channel(s) defined in more than one metadata file."
warnings.warn(msg)
parsers.update(parsers_)
pbar.finish()
# Parse all waveform files.
widgets = ['Indexing waveform files... ', progressbar.Percentage(),
' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(widgets=widgets,
maxval=len(WAVEFORM_FILES)).start()
waveform_index = {}
# Read all waveform files.
for _i, waveform in enumerate(WAVEFORM_FILES):
def get_station_details(self, request, network, station):
session = self.env.db.session(bind=self.env.db.engine)
try:
query = session.query(StationObject)\
.filter(StationObject.network == network)\
.filter(StationObject.station == station).one()
except sqlalchemy.orm.exc.NoResultFound:
session.close()
msg = "Station %s.%s could not be found." % (network, station)
raise NotFoundError(msg)
result = {
"network_code": query.network,
"network_name": "",
"station_code": query.station,
"station_name": "",
"latitude": query.latitude,
"longitude": query.longitude,
"elevation_in_m": query.elevation_in_m,
"local_depth_in_m": query.local_depth_in_m,
"channels": []}
# Also parse information about all channels.
for channel in query.channel:
md = channel.channel_metadata
if md:
md = md[0]
info = {
"channel_code": channel.channel,
"location_code": channel.location,
"start_date": str(md.starttime) if md else None,
"end_date": str(md.starttime) if md else None,
"instrument": "",
"sampling_rate": "",
"format": md.format if md else None,
"channel_filepath_id": md.filepath_id if md else None}
# Attempt to get long descriptions for the station and network
# codes. This is only possible for SEED and XSEED files.
if info["format"] and info["format"].lower() in ["seed", "xseed"]:
parser = Parser(md.filepath.filepath)
inv = parser.getInventory()
if not result["network_name"] and inv["networks"]:
for network in inv["networks"]:
if network["network_code"] != result["network_code"]:
continue
result["network_name"] = network["network_name"]
break
if not result["station_name"] and inv["stations"]:
for station in inv["stations"]:
station_code = station["station_id"].split(".")[1]
if station_code != result["station_code"]:
continue
result["station_name"] = station["station_name"]
for channel in inv["channels"]:
location_code, channel_code = \
channel["channel_id"].split(".")[2:]
if location_code == info["location_code"] and \
channel_code == info["channel_code"]:
info["start_date"] = str(channel["start_date"])
info["end_date"] = str(channel["end_date"])
info["instrument"] = channel["instrument"]
info["sampling_rate"] = channel["sampling_rate"]
result["channels"].append({"channel": info})
session.close()
return formatResults(request, [result])
