Source code for pyrocko.squirrel.model

# http://pyrocko.org - GPLv3
#
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------

'''
Data model and content types handled by the Squirrel framework.

Squirrel uses flat content types to represent waveform, station, channel,
response, event, and a few other objects. A common subset of the information in
these objects is indexed in the database, currently: kind, codes, time interval
and sampling rate. The :py:class:`Nut` objects encapsulate this information
together with information about where and how to get the associated bulk data.

Further content types are defined here to handle waveform orders, waveform
promises, data coverage and sensor information.
'''

from __future__ import absolute_import, print_function

import re
import fnmatch
import math
import hashlib
from os import urandom
from base64 import urlsafe_b64encode
from collections import defaultdict, namedtuple

import numpy as num

from pyrocko import util
from pyrocko.guts import Object, SObject, String, Timestamp, Float, Int, \
    Unicode, Tuple, List, StringChoice, Any, Dict, clone
from pyrocko.model import squirrel_content, Location
from pyrocko.response import FrequencyResponse, MultiplyResponse, \
    IntegrationResponse, DifferentiationResponse, simplify_responses, \
    FrequencyResponseCheckpoint

from .error import ConversionError, SquirrelError

d2r = num.pi / 180.
r2d = 1.0 / d2r


guts_prefix = 'squirrel'


def mkvec(x, y, z):
    return num.array([x, y, z], dtype=float)


def are_orthogonal(vecs, eps=0.01):
    return all(abs(
        num.dot(vecs[i], vecs[j]) < eps
        for (i, j) in [(0, 1), (1, 2), (2, 0)]))


g_codes_pool = {}


[docs]class CodesError(SquirrelError): pass
[docs]class Codes(SObject): pass
def normalize_nslce(*args, **kwargs): if args and kwargs: raise ValueError('Either *args or **kwargs accepted, not both.') if len(args) == 1: if isinstance(args[0], str): args = tuple(args[0].split('.')) elif isinstance(args[0], tuple): args = args[0] else: raise ValueError('Invalid argument type: %s' % type(args[0])) nargs = len(args) if nargs == 5: t = args elif nargs == 4: t = args + ('',) elif nargs == 0: d = dict( network='', station='', location='', channel='', extra='') d.update(kwargs) t = tuple(kwargs.get(k, '') for k in ( 'network', 'station', 'location', 'channel', 'extra')) else: raise CodesError( 'Does not match NSLC or NSLCE codes pattern: %s' % '.'.join(args)) if '.'.join(t).count('.') != 4: raise CodesError( 'Codes may not contain a ".": "%s", "%s", "%s", "%s", "%s"' % t) return t CodesNSLCEBase = namedtuple( 'CodesNSLCEBase', [ 'network', 'station', 'location', 'channel', 'extra'])
[docs]class CodesNSLCE(CodesNSLCEBase, Codes): ''' Codes denominating a seismic channel (NSLC or NSLCE). FDSN/SEED style NET.STA.LOC.CHA is accepted or NET.STA.LOC.CHA.EXTRA, where the EXTRA part in the latter form can be used to identify a custom processing applied to a channel. ''' __slots__ = () __hash__ = CodesNSLCEBase.__hash__ as_dict = CodesNSLCEBase._asdict def __new__(cls, *args, safe_str=None, **kwargs): nargs = len(args) if nargs == 1 and isinstance(args[0], CodesNSLCE): return args[0] elif nargs == 1 and isinstance(args[0], CodesNSL): t = (args[0].nsl) + ('*', '*') elif nargs == 1 and isinstance(args[0], CodesX): t = ('*', '*', '*', '*', '*') elif safe_str is not None: t = safe_str.split('.') else: t = normalize_nslce(*args, **kwargs) x = CodesNSLCEBase.__new__(cls, *t) return g_codes_pool.setdefault(x, x) def __init__(self, *args, **kwargs): Codes.__init__(self) def __str__(self): if self.extra == '': return '.'.join(self[:-1]) else: return '.'.join(self) def __eq__(self, other): if not isinstance(other, CodesNSLCE): other = CodesNSLCE(other) return CodesNSLCEBase.__eq__(self, other) def matches(self, pattern): if not isinstance(pattern, CodesNSLCE): pattern = CodesNSLCE(pattern) return match_codes(pattern, self) @property def safe_str(self): return '.'.join(self) @property def nslce(self): return self[:4] @property def nslc(self): return self[:4] @property def nsl(self): return self[:3] @property def ns(self): return self[:2] def as_tuple(self): return tuple(self) def replace(self, **kwargs): x = CodesNSLCEBase._replace(self, **kwargs) return g_codes_pool.setdefault(x, x)
def normalize_nsl(*args, **kwargs): if args and kwargs: raise ValueError('Either *args or **kwargs accepted, not both.') if len(args) == 1: if isinstance(args[0], str): args = tuple(args[0].split('.')) elif isinstance(args[0], tuple): args = args[0] else: raise ValueError('Invalid argument type: %s' % type(args[0])) nargs = len(args) if nargs == 3: t = args elif nargs == 0: d = dict( network='', station='', location='') d.update(kwargs) t = tuple(kwargs.get(k, '') for k in ( 'network', 'station', 'location')) else: raise CodesError( 'Does not match NSL codes pattern: %s' % '.'.join(args)) if '.'.join(t).count('.') != 2: raise CodesError( 'Codes may not contain a ".": "%s", "%s", "%s"' % t) return t CodesNSLBase = namedtuple( 'CodesNSLBase', [ 'network', 'station', 'location'])
[docs]class CodesNSL(CodesNSLBase, Codes): ''' Codes denominating a seismic station (NSL). NET.STA.LOC is accepted, slightly different from SEED/StationXML, where LOC is part of the channel. By setting location='*' is possible to get compatible behaviour in most cases. ''' __slots__ = () __hash__ = CodesNSLBase.__hash__ as_dict = CodesNSLBase._asdict def __new__(cls, *args, safe_str=None, **kwargs): nargs = len(args) if nargs == 1 and isinstance(args[0], CodesNSL): return args[0] elif nargs == 1 and isinstance(args[0], CodesNSLCE): t = args[0].nsl elif nargs == 1 and isinstance(args[0], CodesX): t = ('*', '*', '*') elif safe_str is not None: t = safe_str.split('.') else: t = normalize_nsl(*args, **kwargs) x = CodesNSLBase.__new__(cls, *t) return g_codes_pool.setdefault(x, x) def __init__(self, *args, **kwargs): Codes.__init__(self) def __str__(self): return '.'.join(self) def __eq__(self, other): if not isinstance(other, CodesNSL): other = CodesNSL(other) return CodesNSLBase.__eq__(self, other) def matches(self, pattern): if not isinstance(pattern, CodesNSL): pattern = CodesNSL(pattern) return match_codes(pattern, self) @property def safe_str(self): return '.'.join(self) @property def ns(self): return self[:2] @property def nsl(self): return self[:3] def as_tuple(self): return tuple(self) def replace(self, **kwargs): x = CodesNSLBase._replace(self, **kwargs) return g_codes_pool.setdefault(x, x)
CodesXBase = namedtuple( 'CodesXBase', [ 'name'])
[docs]class CodesX(CodesXBase, Codes): ''' General purpose codes for anything other than channels or stations. ''' __slots__ = () __hash__ = CodesXBase.__hash__ __eq__ = CodesXBase.__eq__ as_dict = CodesXBase._asdict def __new__(cls, name='', safe_str=None): if isinstance(name, CodesX): return name elif isinstance(name, (CodesNSLCE, CodesNSL)): name = '*' elif safe_str is not None: name = safe_str else: if '.' in name: raise CodesError('Code may not contain a ".": %s' % name) x = CodesXBase.__new__(cls, name) return g_codes_pool.setdefault(x, x) def __init__(self, *args, **kwargs): Codes.__init__(self) def __str__(self): return '.'.join(self) @property def safe_str(self): return '.'.join(self) @property def ns(self): return self[:2] def as_tuple(self): return tuple(self) def replace(self, **kwargs): x = CodesXBase._replace(self, **kwargs) return g_codes_pool.setdefault(x, x)
g_codes_patterns = {} def match_codes(pattern, codes): spattern = pattern.safe_str scodes = codes.safe_str if spattern not in g_codes_patterns: rpattern = re.compile(fnmatch.translate(spattern), re.I) g_codes_patterns[spattern] = rpattern rpattern = g_codes_patterns[spattern] return bool(rpattern.match(scodes)) g_content_kinds = [ 'undefined', 'waveform', 'station', 'channel', 'response', 'event', 'waveform_promise'] g_codes_classes = [ CodesX, CodesNSLCE, CodesNSL, CodesNSLCE, CodesNSLCE, CodesX, CodesNSLCE] g_codes_classes_ndot = { 0: CodesX, 2: CodesNSL, 3: CodesNSLCE, 4: CodesNSLCE} def to_codes_simple(kind_id, codes_safe_str): return g_codes_classes[kind_id](safe_str=codes_safe_str) def to_codes(kind_id, obj): return g_codes_classes[kind_id](obj) def to_codes_guess(s): try: return g_codes_classes_ndot[s.count('.')](s) except KeyError: raise CodesError('Cannot guess codes type: %s' % s) # derived list class to enable detection of already preprocessed codes patterns class codes_patterns_list(list): pass def codes_patterns_for_kind(kind_id, codes): if isinstance(codes, codes_patterns_list): return codes if isinstance(codes, list): lcodes = codes_patterns_list() for sc in codes: lcodes.extend(codes_patterns_for_kind(kind_id, sc)) return lcodes codes = to_codes(kind_id, codes) lcodes = codes_patterns_list() lcodes.append(codes) if kind_id == STATION: lcodes.append(codes.replace(location='[*]')) return lcodes 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] try: g_tmin_queries = max(g_tmin, util.str_to_time_fillup('1900-01-01')) except Exception: g_tmin_queries = g_tmin 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) def codes_to_str_abbreviated(codes, indent=' '): codes = [str(x) for x in codes] if len(codes) > 20: scodes = '\n' + util.ewrap(codes[:10], indent=indent) \ + '\n%s[%i more]\n' % (indent, len(codes) - 20) \ + util.ewrap(codes[-10:], indent=' ') else: scodes = '\n' + util.ewrap(codes, indent=indent) \ if codes else '<none>' return scodes 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 t = util.to_time_float(t) if type(t) is float: t = round(t, 5) else: t = round(t, 9) seconds = num.floor(t) offset = t - seconds return int(seconds), int(round(offset * g_offset_time_unit_inv)) def tjoin(seconds, offset): if seconds is None: return None return util.to_time_float(seconds) \ + util.to_time_float(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))
[docs]@squirrel_content class Station(Location): ''' A seismic station. ''' codes = CodesNSL.T() tmin = Timestamp.T(optional=True) tmax = Timestamp.T(optional=True) description = Unicode.T(optional=True) def __init__(self, **kwargs): kwargs['codes'] = CodesNSL(kwargs['codes']) Location.__init__(self, **kwargs) @property def time_span(self): return (self.tmin, self.tmax) def get_pyrocko_station(self): from pyrocko import model return model.Station(*self._get_pyrocko_station_args()) def _get_pyrocko_station_args(self): return ( self.codes.network, self.codes.station, self.codes.location, self.lat, self.lon, self.elevation, self.depth, self.north_shift, self.east_shift)
@squirrel_content class ChannelBase(Location): codes = CodesNSLCE.T() tmin = Timestamp.T(optional=True) tmax = Timestamp.T(optional=True) deltat = Float.T(optional=True) def __init__(self, **kwargs): kwargs['codes'] = CodesNSLCE(kwargs['codes']) Location.__init__(self, **kwargs) @property def time_span(self): return (self.tmin, self.tmax) def _get_sensor_args(self): def getattr_rep(k): if k == 'codes': return self.codes.replace( channel=self.codes.channel[:-1] + '?') else: return getattr(self, k) return tuple(getattr_rep(k) for k in ChannelBase.T.propnames) def _get_channel_args(self, component): def getattr_rep(k): if k == 'codes': return self.codes.replace( channel=self.codes.channel[:-1] + component) else: return getattr(self, k) return tuple(getattr_rep(k) for k in ChannelBase.T.propnames) def _get_pyrocko_station_args(self): return ( self.codes.network, self.codes.station, self.codes.location, self.lat, self.lon, self.elevation, self.depth, self.north_shift, self.east_shift)
[docs]class Channel(ChannelBase): ''' A channel of a seismic station. ''' dip = Float.T(optional=True) azimuth = Float.T(optional=True) def get_pyrocko_channel(self): from pyrocko import model return model.Channel(*self._get_pyrocko_channel_args()) def _get_pyrocko_channel_args(self): return ( self.codes.channel, self.azimuth, self.dip) @property def orientation_enz(self): if None in (self.azimuth, self.dip): return None n = math.cos(self.azimuth*d2r)*math.cos(self.dip*d2r) e = math.sin(self.azimuth*d2r)*math.cos(self.dip*d2r) d = math.sin(self.dip*d2r) return mkvec(e, n, -d)
def cut_intervals(channels): channels = list(channels) times = set() for channel in channels: if channel.tmin is not None: times.add(channel.tmin) if channel.tmax is not None: times.add(channel.tmax) times = sorted(times) if len(times) < 2: return channels channels_out = [] for channel in channels: tstart = channel.tmin for t in times: if (channel.tmin is None or channel.tmin < t) \ and (channel.tmax is None or t < channel.tmax): channel_out = clone(channel) channel_out.tmin = tstart channel_out.tmax = t channels_out.append(channel_out) tstart = t if channel.tmax is None: channel_out = clone(channel) channel_out.tmin = tstart channels_out.append(channel_out) return channels_out
[docs]class Sensor(ChannelBase): ''' Representation of a channel group. ''' channels = List.T(Channel.T()) @classmethod def from_channels(cls, channels): channels = cut_intervals(channels) groups = defaultdict(list) for channel in channels: groups[channel._get_sensor_args()].append(channel) return [ cls(channels=channels, **dict(zip(ChannelBase.T.propnames, args))) for args, channels in groups.items()] def channel_vectors(self): return num.vstack( [channel.orientation_enz for channel in self.channels]) def projected_channels(self, system, component_names): return [ Channel( azimuth=math.atan2(e, n) * r2d, dip=-math.asin(z) * r2d, **dict(zip( ChannelBase.T.propnames, self._get_channel_args(comp)))) for comp, (e, n, z) in zip(component_names, system)] def matrix_to(self, system, epsilon=1e-7): m = num.dot(system, self.channel_vectors().T) m[num.abs(m) < epsilon] = 0.0 return m def projection_to(self, system, component_names): return ( self.matrix_to(system), self.channels, self.projected_channels(system, component_names)) def projection_to_enz(self): return self.projection_to(num.identity(3), 'ENZ') def projection_to_trz(self, source, azimuth=None): if azimuth is not None: assert source is None else: azimuth = source.azibazi_to(self)[1] + 180. return self.projection_to(num.array([ [math.cos(azimuth*d2r), -math.sin(azimuth*d2r), 0.], [math.sin(azimuth*d2r), math.cos(azimuth*d2r), 0.], [0., 0., 1.]], dtype=float), 'TRZ') def project_to_enz(self, traces): from pyrocko import trace matrix, in_channels, out_channels = self.projection_to_enz() return trace.project(traces, matrix, in_channels, out_channels) def project_to_trz(self, source, traces, azimuth=None): from pyrocko import trace matrix, in_channels, out_channels = self.projection_to_trz( source, azimuth=azimuth) return trace.project(traces, matrix, in_channels, out_channels)
observational_quantities = [ 'acceleration', 'velocity', 'displacement', 'pressure', 'rotation-displacement', 'rotation-velocity', 'rotation-acceleration', 'temperature'] technical_quantities = [ 'voltage', 'counts'] class QuantityType(StringChoice): ''' Choice of observational or technical quantity. SI units are used for all quantities, where applicable. ''' choices = observational_quantities + technical_quantities class ResponseStage(Object): ''' Representation of a response stage. Components of a seismic recording system are represented as a sequence of response stages, e.g. sensor, pre-amplifier, digitizer, digital downsampling. ''' input_quantity = QuantityType.T(optional=True) input_sample_rate = Float.T(optional=True) output_quantity = QuantityType.T(optional=True) output_sample_rate = Float.T(optional=True) elements = List.T(FrequencyResponse.T()) log = List.T(Tuple.T(3, String.T())) @property def stage_type(self): if self.input_quantity in observational_quantities \ and self.output_quantity in observational_quantities: return 'conversion' if self.input_quantity in observational_quantities \ and self.output_quantity == 'voltage': return 'sensor' elif self.input_quantity == 'voltage' \ and self.output_quantity == 'voltage': return 'electronics' elif self.input_quantity == 'voltage' \ and self.output_quantity == 'counts': return 'digitizer' elif self.input_quantity == 'counts' \ and self.output_quantity == 'counts' \ and self.input_sample_rate != self.output_sample_rate: return 'decimation' elif self.input_quantity in observational_quantities \ and self.output_quantity == 'counts': return 'combination' else: return 'unknown' @property def summary(self): irate = self.input_sample_rate orate = self.output_sample_rate factor = None if irate and orate: factor = irate / orate return 'ResponseStage, ' + ( '%s%s => %s%s%s' % ( self.input_quantity or '?', ' @ %g Hz' % irate if irate else '', self.output_quantity or '?', ' @ %g Hz' % orate if orate else '', ' :%g' % factor if factor else '') ) def get_effective(self): return MultiplyResponse(responses=list(self.elements)) D = 'displacement' V = 'velocity' A = 'acceleration' g_converters = { (V, D): IntegrationResponse(1), (A, D): IntegrationResponse(2), (D, V): DifferentiationResponse(1), (A, V): IntegrationResponse(1), (D, A): DifferentiationResponse(2), (V, A): DifferentiationResponse(1)} def response_converters(input_quantity, output_quantity): if input_quantity is None or input_quantity == output_quantity: return [] if output_quantity is None: raise ConversionError('Unspecified target quantity.') try: return [g_converters[input_quantity, output_quantity]] except KeyError: raise ConversionError('No rule to convert from "%s" to "%s".' % ( input_quantity, output_quantity))
[docs]@squirrel_content class Response(Object): ''' The instrument response of a seismic station channel. ''' codes = CodesNSLCE.T() tmin = Timestamp.T(optional=True) tmax = Timestamp.T(optional=True) stages = List.T(ResponseStage.T()) checkpoints = List.T(FrequencyResponseCheckpoint.T()) deltat = Float.T(optional=True) log = List.T(Tuple.T(3, String.T())) def __init__(self, **kwargs): kwargs['codes'] = CodesNSLCE(kwargs['codes']) Object.__init__(self, **kwargs) @property def time_span(self): return (self.tmin, self.tmax) @property def nstages(self): return len(self.stages) @property def input_quantity(self): return self.stages[0].input_quantity if self.stages else None @property def output_quantity(self): return self.stages[-1].input_quantity if self.stages else None @property def output_sample_rate(self): return self.stages[-1].output_sample_rate if self.stages else None @property def stages_summary(self): def grouped(xs): xs = list(xs) g = [] for i in range(len(xs)): g.append(xs[i]) if i+1 < len(xs) and xs[i+1] != xs[i]: yield g g = [] if g: yield g return '+'.join( '%s%s' % (g[0], '(%i)' % len(g) if len(g) > 1 else '') for g in grouped(stage.stage_type for stage in self.stages)) @property def summary(self): orate = self.output_sample_rate return '%s %-16s %s' % ( self.__class__.__name__, self.str_codes, self.str_time_span) \ + ', ' + ', '.join(( '%s => %s' % ( self.input_quantity or '?', self.output_quantity or '?') + (' @ %g Hz' % orate if orate else ''), self.stages_summary, )) def get_effective(self, input_quantity=None): try: elements = response_converters(input_quantity, self.input_quantity) except ConversionError as e: raise ConversionError(str(e) + ' (%s)' % self.summary) elements.extend( stage.get_effective() for stage in self.stages) return MultiplyResponse(responses=simplify_responses(elements))
@squirrel_content class Event(Object): ''' 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() def random_name(n=8): return urlsafe_b64encode(urandom(n)).rstrip(b'=').decode('ascii')
[docs]@squirrel_content class WaveformPromise(Object): ''' Information about a waveform potentially downloadable from a remote site. In the Squirrel framework, waveform promises are used to permit download of selected waveforms from a remote site. They are typically generated by calls to :py:meth:`~pyrocko.squirrel.base.Squirrel.update_waveform_promises`. Waveform promises are inserted and indexed in the database similar to normal waveforms. When processing a waveform query, e.g. from :py:meth:`~pyrocko.squirrel.base.Squirrel.get_waveform`, and no local waveform is available for the queried time span, a matching promise can be resolved, i.e. an attempt is made to download the waveform from the remote site. The promise is removed after the download attempt (except when a network error occurs). This prevents Squirrel from making unnecessary queries for waveforms missing at the remote site. ''' codes = CodesNSLCE.T() tmin = Timestamp.T() tmax = Timestamp.T() deltat = Float.T(optional=True) source_hash = String.T() def __init__(self, **kwargs): kwargs['codes'] = CodesNSLCE(kwargs['codes']) Object.__init__(self, **kwargs) @property def time_span(self): return (self.tmin, self.tmax)
class InvalidWaveform(Exception): pass class WaveformOrder(Object): ''' Waveform request information. ''' source_id = String.T() codes = CodesNSLCE.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, str(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_list = sorted(set(order.codes for order in orders)) if len(codes_list) > 3: return '%i order%s: %s - %s' % ( len(orders), util.plural_s(orders), str(codes_list[0]), str(codes_list[1])) else: return '%i order%s: %s' % ( len(orders), util.plural_s(orders), ', '.join(str(codes) for codes in codes_list))
[docs]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 = Codes.T() tmin_seconds = Int.T(default=0) tmin_offset = Int.T(default=0, optional=True) tmax_seconds = Int.T(default=0) tmax_offset = Int.T(default=0, optional=True) deltat = Float.T(default=0.0) content = Any.T(optional=True) raw_content = Dict.T(String.T(), Any.T()) 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=CodesX(''), tmin_seconds=None, tmin_offset=0, tmax_seconds=None, tmax_offset=0, deltat=None, content=None, raw_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, codes_safe_str, self.tmin_seconds, self.tmin_offset, self.tmax_seconds, self.tmax_offset, self.deltat) = values_nocheck self.codes = to_codes_simple(self.kind_id, codes_safe_str) self.deltat = self.deltat or None self.raw_content = {} 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 = 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 if raw_content is None: self.raw_content = {} else: self.raw_content = raw_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) def diff(self, other): names = [ 'file_segment', 'file_element', 'kind_id', 'codes', 'tmin_seconds', 'tmin_offset', 'tmax_seconds', 'tmax_offset', 'deltat'] d = [] for name, a, b in zip( names, self.equality_values, other.equality_values): if a != b: d.append((name, a, b)) return d @property def tmin(self): return tjoin(self.tmin_seconds, self.tmin_offset) @tmin.setter def tmin(self, t): self.tmin_seconds, self.tmin_offset = tsplit(t) @property def tmax(self): return tjoin(self.tmax_seconds, self.tmax_offset) @tmax.setter def tmax(self, t): self.tmax_seconds, self.tmax_offset = tsplit(t) @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): network, station, location, channel, extra = self.codes return dict( 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): return dict( codes=self.codes, tmin=self.tmin, tmax=self.tmax, deltat=self.deltat) @property def station_kwargs(self): network, station, location = self.codes return dict( codes=self.codes, tmin=tmin_or_none(self.tmin), tmax=tmax_or_none(self.tmax)) @property def channel_kwargs(self): network, station, location, channel, extra = self.codes return dict( codes=self.codes, tmin=tmin_or_none(self.tmin), tmax=tmax_or_none(self.tmax), deltat=self.deltat) @property def response_kwargs(self): return dict( codes=self.codes, 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): network, station, location, channel, extra = self.codes return dict( network=network, station=station, location=location, channel=channel, extra=extra, tmin=self.tmin, tmax=self.tmax-self.deltat, deltat=self.deltat) @property def dummy_trace(self): return DummyTrace(self) @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,' % str(self.codes)).ljust(18), ts))
def make_waveform_nut(**kwargs): return Nut(kind_id=WAVEFORM, **kwargs) def make_waveform_promise_nut(**kwargs): return Nut(kind_id=WAVEFORM_PROMISE, **kwargs) def make_station_nut(**kwargs): return Nut(kind_id=STATION, **kwargs) def make_channel_nut(**kwargs): return Nut(kind_id=CHANNEL, **kwargs) def make_response_nut(**kwargs): return Nut(kind_id=RESPONSE, **kwargs) def make_event_nut(**kwargs): return Nut(kind_id=EVENT, **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.codes = nut.codes self.meta = {} @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): return self.codes.nslc @property def network(self): return self.codes.network @property def station(self): return self.codes.station @property def location(self): return self.codes.location @property def channel(self): return self.codes.channel @property def extra(self): return self.codes.extra def overlaps(self, tmin, tmax): return not (tmax < self.nut.tmin or self.nut.tmax < tmin) def duration_to_str(t): if t > 24*3600: return '%gd' % (t / (24.*3600.)) elif t > 3600: return '%gh' % (t / 3600.) elif t > 60: return '%gm' % (t / 60.) else: return '%gs' % t
[docs]class Coverage(Object): ''' Information about times covered by a waveform or other time series data. ''' kind_id = Int.T( help='Content type.') pattern = Codes.T( help='The codes pattern in the request, which caused this entry to ' 'match.') codes = Codes.T( help='NSLCE or NSL codes identifier of the time series.') deltat = Float.T( help='Sampling interval [s]', optional=True) tmin = Timestamp.T( help='Global start time of time series.', optional=True) tmax = Timestamp.T( help='Global end time of time series.', optional=True) changes = List.T( Tuple.T(2, Any.T()), help='List of change points, with entries of the form ' '``(time, count)``, where a ``count`` of zero indicates start of ' 'a gap, a value of 1 start of normal data coverage and a higher ' 'value duplicate or redundant data coverage.') @classmethod def from_values(cls, args): pattern, codes, deltat, tmin, tmax, changes, kind_id = args return cls( kind_id=kind_id, pattern=pattern, codes=codes, deltat=deltat, tmin=tmin, tmax=tmax, changes=changes) @property def summary(self): ts = '%s - %s,' % ( util.time_to_str(self.tmin), util.time_to_str(self.tmax)) srate = self.sample_rate return ' '.join(( ('%s,' % to_kind(self.kind_id)).ljust(9), ('%s,' % str(self.codes)).ljust(18), ts, '%10.3g,' % srate if srate else '', '%4i' % len(self.changes), '%s' % duration_to_str(self.total))) @property def sample_rate(self): if self.deltat is None: return None elif self.deltat == 0.0: return 0.0 else: return 1.0 / self.deltat @property def labels(self): srate = self.sample_rate return ( ('%s' % str(self.codes)), '%.3g' % srate if srate else '') @property def total(self): total_t = None for tmin, tmax, _ in self.iter_spans(): total_t = (total_t or 0.0) + (tmax - tmin) return total_t def iter_spans(self): last = None for (t, count) in self.changes: if last is not None: last_t, last_count = last if last_count > 0: yield last_t, t, last_count last = (t, count)
__all__ = [ 'to_codes', 'to_codes_guess', 'to_codes_simple', 'to_kind', 'to_kinds', 'to_kind_id', 'to_kind_ids', 'CodesError', 'Codes', 'CodesNSLCE', 'CodesNSL', 'CodesX', 'Station', 'Channel', 'Sensor', 'Response', 'Nut', 'Coverage', 'WaveformPromise', ]