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# http://pyrocko.org - GPLv3
#
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------
from __future__ import absolute_import, print_function
import hashlib
import numpy as num
from pyrocko import util
from pyrocko.guts import Object, String, Timestamp, Float, Int, Unicode, \
Tuple, List
from pyrocko.model import Content
separator = '\t'
g_content_kinds = [
'undefined',
'waveform',
'station',
'channel',
'response',
'event',
'waveform_promise']
g_content_kind_ids = (
UNDEFINED, WAVEFORM, STATION, CHANNEL, RESPONSE, EVENT,
WAVEFORM_PROMISE) = range(len(g_content_kinds))
g_tmin, g_tmax = util.get_working_system_time_range()[:2]
def to_kind(kind_id):
return g_content_kinds[kind_id]
def to_kinds(kind_ids):
return [g_content_kinds[kind_id] for kind_id in kind_ids]
def to_kind_id(kind):
return g_content_kinds.index(kind)
def to_kind_ids(kinds):
return [g_content_kinds.index(kind) for kind in kinds]
g_kind_mask_all = 0xff
def to_kind_mask(kinds):
if kinds:
return sum(1 << kind_id for kind_id in to_kind_ids(kinds))
else:
return g_kind_mask_all
def str_or_none(x):
if x is None:
return None
else:
return str(x)
def float_or_none(x):
if x is None:
return None
else:
return float(x)
def int_or_none(x):
if x is None:
return None
else:
return int(x)
def int_or_g_tmin(x):
if x is None:
return g_tmin
else:
return int(x)
def int_or_g_tmax(x):
if x is None:
return g_tmax
else:
return int(x)
def tmin_or_none(x):
if x == g_tmin:
return None
else:
return x
def tmax_or_none(x):
if x == g_tmax:
return None
else:
return x
def time_or_none_to_str(x):
if x is None:
return '...'.ljust(17)
else:
return util.time_to_str(x)
g_offset_time_unit_inv = 1000000000
g_offset_time_unit = 1.0 / g_offset_time_unit_inv
def tsplit(t):
if t is None:
return None, 0.0
seconds = num.floor(t)
offset = t - seconds
return int(seconds), int(round(offset * g_offset_time_unit_inv))
def tjoin(seconds, offset, deltat):
if seconds is None:
return None
if deltat is not None and deltat < 1e-3:
return util.hpfloat(seconds) + util.hpfloat(offset*g_offset_time_unit)
else:
return seconds + offset*g_offset_time_unit
tscale_min = 1
tscale_max = 365 * 24 * 3600 # last edge is one above
tscale_logbase = 20
tscale_edges = [tscale_min]
while True:
tscale_edges.append(tscale_edges[-1]*tscale_logbase)
if tscale_edges[-1] >= tscale_max:
break
tscale_edges = num.array(tscale_edges)
def tscale_to_kscale(tscale):
# 0 <= x < tscale_edges[1]: 0
# tscale_edges[1] <= x < tscale_edges[2]: 1
# ...
# tscale_edges[len(tscale_edges)-1] <= x: len(tscale_edges)
return int(num.searchsorted(tscale_edges, tscale))
class WaveformPromise(Content):
'''
Information about a waveform potentially available at a remote site.
'''
agency = String.T(default='', help='Agency code (2-5)')
network = String.T(default='', help='Deployment/network code (1-8)')
station = String.T(default='', help='Station code (1-5)')
location = String.T(default='', help='Location code (0-2)')
channel = String.T(default='', help='Channel code (3)')
extra = String.T(default='', help='Extra/custom code')
tmin = Timestamp.T()
tmax = Timestamp.T()
deltat = Float.T(optional=True)
source_hash = String.T()
@property
def codes(self):
return (
self.agency, self.network, self.station, self.location,
self.channel, self.extra)
@property
def time_span(self):
return (self.tmin, self.tmax)
class InvalidWaveform(Exception):
pass
class WaveformOrder(Object):
source_id = String.T()
codes = Tuple.T(None, String.T())
deltat = Float.T()
tmin = Timestamp.T()
tmax = Timestamp.T()
gaps = List.T(Tuple.T(2, Timestamp.T()))
@property
def client(self):
return self.source_id.split(':')[1]
def describe(self, site='?'):
return '%s:%s %s [%s - %s]' % (
self.client, site, '.'.join(self.codes),
util.time_to_str(self.tmin), util.time_to_str(self.tmax))
def validate(self, tr):
if tr.ydata.size == 0:
raise InvalidWaveform(
'waveform with zero data samples')
if tr.deltat != self.deltat:
raise InvalidWaveform(
'incorrect sampling interval - waveform: %g s, '
'meta-data: %g s' % (
tr.deltat, self.deltat))
if not num.all(num.isfinite(tr.ydata)):
raise InvalidWaveform('waveform has NaN values')
def order_summary(orders):
codes = sorted(set(order.codes[1:-1] for order in orders))
if len(codes) >= 2:
return '%i orders, %s - %s' % (
len(orders),
'.'.join(codes[0]),
'.'.join(codes[-1]))
else:
return '%i orders, %s' % (
len(orders),
'.'.join(codes[0]))
class Station(Content):
'''
A seismic station.
'''
agency = String.T(default='', help='Agency code (2-5)')
network = String.T(default='', help='Deployment/network code (1-8)')
station = String.T(default='', help='Station code (1-5)')
location = String.T(default='', optional=True, help='Location code (0-2)')
tmin = Timestamp.T(optional=True)
tmax = Timestamp.T(optional=True)
lat = Float.T()
lon = Float.T()
elevation = Float.T(optional=True)
depth = Float.T(optional=True)
description = Unicode.T(optional=True)
@property
def codes(self):
return (
self.agency, self.network, self.station,
self.location if self.location is not None else '*')
@property
def time_span(self):
return (self.tmin, self.tmax)
def get_pyrocko_station(self):
from pyrocko import model
return model.Station(
network=self.network,
station=self.station,
location=self.location if self.location is not None else '*',
lat=self.lat,
lon=self.lon,
elevation=self.elevation,
depth=self.depth)
def _get_pyrocko_station_args(self):
return (
'*',
self.network,
self.station,
self.location if self.location is not None else '*',
self.lat,
self.lon,
self.elevation,
self.depth)
class Channel(Content):
'''
A channel of a seismic station.
'''
agency = String.T(default='', help='Agency code (2-5)')
network = String.T(default='', help='Deployment/network code (1-8)')
station = String.T(default='', help='Station code (1-5)')
location = String.T(default='', help='Location code (0-2)')
channel = String.T(default='', help='Channel code (3)')
tmin = Timestamp.T(optional=True)
tmax = Timestamp.T(optional=True)
lat = Float.T()
lon = Float.T()
elevation = Float.T(optional=True)
depth = Float.T(optional=True)
dip = Float.T(optional=True)
azimuth = Float.T(optional=True)
deltat = Float.T(optional=True)
@property
def codes(self):
return (
self.agency, self.network, self.station, self.location,
self.channel)
@property
def time_span(self):
return (self.tmin, self.tmax)
def get_pyrocko_channel(self):
from pyrocko import model
return model.Channel(
name=self.channel,
azimuth=self.azimuth,
dip=self.dip)
def _get_pyrocko_station_args(self):
return (
self.channel,
self.network,
self.station,
self.location,
self.lat,
self.lon,
self.elevation,
self.depth)
def _get_pyrocko_channel_args(self):
return (
'*',
self.channel,
self.azimuth,
self.dip)
class Response(Content):
'''
The instrument response of a seismic station channel.
'''
pass
class Event(Content):
'''
A seismic event.
'''
name = String.T(optional=True)
time = Timestamp.T()
duration = Float.T(optional=True)
lat = Float.T()
lon = Float.T()
depth = Float.T(optional=True)
magnitude = Float.T(optional=True)
def get_pyrocko_event(self):
from pyrocko import model
model.Event(
name=self.name,
time=self.time,
lat=self.lat,
lon=self.lon,
depth=self.depth,
magnitude=self.magnitude,
duration=self.duration)
@property
def time_span(self):
return (self.time, self.time)
def ehash(s):
return hashlib.sha1(s.encode('utf8')).hexdigest()
class Nut(Object):
'''
Index entry referencing an elementary piece of content.
So-called *nuts* are used in Pyrocko's Squirrel framework to hold common
meta-information about individual pieces of waveforms, stations, channels,
etc. together with the information where it was found or generated.
'''
file_path = String.T(optional=True)
file_format = String.T(optional=True)
file_mtime = Timestamp.T(optional=True)
file_size = Int.T(optional=True)
file_segment = Int.T(optional=True)
file_element = Int.T(optional=True)
kind_id = Int.T()
codes = String.T()
tmin_seconds = Timestamp.T()
tmin_offset = Int.T(default=0, optional=True)
tmax_seconds = Timestamp.T()
tmax_offset = Int.T(default=0, optional=True)
deltat = Float.T(default=0.0)
content = Content.T(optional=True)
content_in_db = False
def __init__(
self,
file_path=None,
file_format=None,
file_mtime=None,
file_size=None,
file_segment=None,
file_element=None,
kind_id=0,
codes='',
tmin_seconds=None,
tmin_offset=0,
tmax_seconds=None,
tmax_offset=0,
deltat=None,
content=None,
tmin=None,
tmax=None,
values_nocheck=None):
if values_nocheck is not None:
(self.file_path, self.file_format, self.file_mtime,
self.file_size,
self.file_segment, self.file_element,
self.kind_id, self.codes,
self.tmin_seconds, self.tmin_offset,
self.tmax_seconds, self.tmax_offset,
self.deltat) = values_nocheck
self.content = None
else:
if tmin is not None:
tmin_seconds, tmin_offset = tsplit(tmin)
if tmax is not None:
tmax_seconds, tmax_offset = tsplit(tmax)
self.kind_id = int(kind_id)
self.codes = str(codes)
self.tmin_seconds = int_or_g_tmin(tmin_seconds)
self.tmin_offset = int(tmin_offset)
self.tmax_seconds = int_or_g_tmax(tmax_seconds)
self.tmax_offset = int(tmax_offset)
self.deltat = float_or_none(deltat)
self.file_path = str_or_none(file_path)
self.file_segment = int_or_none(file_segment)
self.file_element = int_or_none(file_element)
self.file_format = str_or_none(file_format)
self.file_mtime = float_or_none(file_mtime)
self.file_size = int_or_none(file_size)
self.content = content
Object.__init__(self, init_props=False)
def __eq__(self, other):
return (isinstance(other, Nut) and
self.equality_values == other.equality_values)
def hash(self):
return ehash(','.join(str(x) for x in self.key))
def __ne__(self, other):
return not (self == other)
def get_io_backend(self):
from . import io
return io.get_backend(self.file_format)
def file_modified(self):
return self.get_io_backend().get_stats(self.file_path) \
!= (self.file_mtime, self.file_size)
@property
def dkey(self):
return (self.kind_id, self.tmin_seconds, self.tmin_offset, self.codes)
@property
def key(self):
return (
self.file_path,
self.file_segment,
self.file_element,
self.file_mtime)
@property
def equality_values(self):
return (
self.file_segment, self.file_element,
self.kind_id, self.codes,
self.tmin_seconds, self.tmin_offset,
self.tmax_seconds, self.tmax_offset, self.deltat)
@property
def tmin(self):
return tjoin(self.tmin_seconds, self.tmin_offset, self.deltat)
@property
def tmax(self):
return tjoin(self.tmax_seconds, self.tmax_offset, self.deltat)
@property
def kscale(self):
if self.tmin_seconds is None or self.tmax_seconds is None:
return 0
return tscale_to_kscale(self.tmax_seconds - self.tmin_seconds)
@property
def waveform_kwargs(self):
agency, network, station, location, channel, extra = \
self.codes.split(separator)
return dict(
agency=agency,
network=network,
station=station,
location=location,
channel=channel,
extra=extra,
tmin=self.tmin,
tmax=self.tmax,
deltat=self.deltat)
@property
def waveform_promise_kwargs(self):
agency, network, station, location, channel = \
self.codes.split(separator)
return dict(
agency=agency,
network=network,
station=station,
location=location,
channel=channel,
tmin=self.tmin,
tmax=self.tmax,
deltat=self.deltat)
@property
def station_kwargs(self):
agency, network, station, location = self.codes.split(separator)
return dict(
agency=agency,
network=network,
station=station,
location=location if location != '*' else None,
tmin=tmin_or_none(self.tmin),
tmax=tmax_or_none(self.tmax))
@property
def channel_kwargs(self):
agency, network, station, location, channel \
= self.codes.split(separator)
return dict(
agency=agency,
network=network,
station=station,
location=location,
channel=channel,
tmin=tmin_or_none(self.tmin),
tmax=tmax_or_none(self.tmax),
deltat=self.deltat)
@property
def event_kwargs(self):
return dict(
name=self.codes,
time=self.tmin,
duration=(self.tmax - self.tmin) or None)
@property
def trace_kwargs(self):
agency, network, station, location, channel, extra = \
self.codes.split(separator)
return dict(
network=network,
station=station,
location=location,
channel=channel,
tmin=self.tmin,
tmax=self.tmax-self.deltat,
deltat=self.deltat)
@property
def dummy_trace(self):
return DummyTrace(self)
@property
def codes_tuple(self):
return tuple(self.codes.split(separator))
@property
def summary(self):
if self.tmin == self.tmax:
ts = util.time_to_str(self.tmin)
else:
ts = '%s - %s' % (
util.time_to_str(self.tmin),
util.time_to_str(self.tmax))
return ' '.join((
('%s,' % to_kind(self.kind_id)).ljust(9),
('%s,' % '.'.join(self.codes.split(separator))).ljust(18),
ts))
def make_waveform_nut(
agency='', network='', station='', location='', channel='', extra='',
**kwargs):
codes = separator.join(
(agency, network, station, location, channel, extra))
return Nut(
kind_id=WAVEFORM,
codes=codes,
**kwargs)
def make_waveform_promise_nut(
agency='', network='', station='', location='', channel='', extra='',
**kwargs):
codes = separator.join(
(agency, network, station, location, channel, extra))
return Nut(
kind_id=WAVEFORM_PROMISE,
codes=codes,
**kwargs)
def make_station_nut(
agency='', network='', station='', location='', **kwargs):
codes = separator.join((agency, network, station, location))
return Nut(
kind_id=STATION,
codes=codes,
**kwargs)
def make_channel_nut(
agency='', network='', station='', location='', channel='', **kwargs):
codes = separator.join((agency, network, station, location, channel))
return Nut(
kind_id=CHANNEL,
codes=codes,
**kwargs)
def make_event_nut(name='', **kwargs):
codes = name
return Nut(
kind_id=EVENT, codes=codes,
**kwargs)
def group_channels(nuts):
by_ansl = {}
for nut in nuts:
if nut.kind_id != CHANNEL:
continue
ansl = nut.codes[:4]
if ansl not in by_ansl:
by_ansl[ansl] = {}
group = by_ansl[ansl]
k = nut.codes[4][:-1], nut.deltat, nut.tmin, nut.tmax
if k not in group:
group[k] = set()
group.add(nut.codes[4])
return by_ansl
class DummyTrace(object):
def __init__(self, nut):
self.nut = nut
self._nslc = None
@property
def tmin(self):
return self.nut.tmin
@property
def tmax(self):
return self.nut.tmax
@property
def deltat(self):
return self.nut.deltat
@property
def nslc_id(self):
if self._nslc is None:
self._nslc = self.nut.codes_tuple[1:5]
return self._nslc
@property
def network(self):
return self.nslc_id[0]
@property
def station(self):
return self.nslc_id[1]
@property
def location(self):
return self.nslc_id[2]
@property
def channel(self):
return self.nslc_id[3]
def overlaps(self, tmin, tmax):
return not (tmax < self.nut.tmin or self.nut.tmax < tmin)
__all__ = [
'to_kind',
'to_kinds',
'to_kind_id',
'to_kind_ids',
'Content',
'WaveformPromise',
'Station',
'Channel',
'Nut',
]
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