Source code for

# - GPLv3
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------

`FDSN StationXML <>`_ input, output and data

import sys
import time
import logging
import datetime
import calendar
import math
import copy
from collections import defaultdict

import numpy as num

from pyrocko.guts import (StringChoice, StringPattern, UnicodePattern, String,
                          Unicode, Int, Float, List, Object, Timestamp,
                          ValidationError, TBase, re_tz, Any, Tuple)
from pyrocko.guts import load_xml  # noqa
from pyrocko.util import hpfloat, time_to_str, get_time_float

import pyrocko.model
from pyrocko import util, response

guts_prefix = 'sx'

guts_xmlns = ''

logger = logging.getLogger('')

conversion = {
    ('M', 'M'): None,
    ('M/S', 'M'): response.IntegrationResponse(1),
    ('M/S**2', 'M'): response.IntegrationResponse(2),
    ('M', 'M/S'): response.DifferentiationResponse(1),
    ('M/S', 'M/S'): None,
    ('M/S**2', 'M/S'): response.IntegrationResponse(1),
    ('M', 'M/S**2'): response.DifferentiationResponse(2),
    ('M/S', 'M/S**2'): response.DifferentiationResponse(1),
    ('M/S**2', 'M/S**2'): None,
    ('RAD', 'RAD'): None,
    ('RAD/S', 'RAD'): response.IntegrationResponse(1),
    ('RAD/S**2', 'RAD'): response.IntegrationResponse(2),
    ('RAD', 'RAD/S'): response.DifferentiationResponse(1),
    ('RAD/S', 'RAD/S'): None,
    ('RAD/S**2', 'RAD/S'): response.IntegrationResponse(1),
    ('RAD', 'RAD/S**2'): response.DifferentiationResponse(2),
    ('RAD/S', 'RAD/S**2'): response.DifferentiationResponse(1),
    ('RAD/S**2', 'RAD/S**2'): None}

units_to_quantity = {
    'M/S': 'velocity',
    'M': 'displacement',
    'M/S**2': 'acceleration',
    'V': 'voltage',
    'COUNT': 'counts',
    'PA': 'pressure',
    'RAD': 'rotation_displacement',
    'RAD/S': 'rotation_velocity',
    'RAD/S**2': 'rotation_acceleration'}

quantity_to_units = dict((v, k) for (k, v) in units_to_quantity.items())

units_fixes = {
    'R': 'RAD',
    'R/S': 'RAD/S',
    'R/S**2': 'RAD/S**2',
    'COUNTS': 'COUNT'}

def sanitize_units(s):
    s = s.upper()
    return units_fixes.get(s, s)

def to_quantity(units, context, delivery):

    if units is None:
        return None

    name = sanitize_units(
    if name in units_to_quantity:
        return units_to_quantity[name]
            'Units not supported by Squirrel framework: %s' % (
                name + (
                    ' (%s)' % units.description if units.description else '')),

        return 'unsupported_quantity(%s)' % units

class StationXMLError(Exception):

class Inconsistencies(StationXMLError):

class NoResponseInformation(StationXMLError):

class MultipleResponseInformation(StationXMLError):

class InconsistentResponseInformation(StationXMLError):

class InconsistentChannelLocations(StationXMLError):

class InvalidRecord(StationXMLError):
    def __init__(self, line):
        self._line = line

    def __str__(self):
        return 'Invalid record: "%s"' % self._line

_exceptions = dict(

_logs = dict(,

class DeliveryError(StationXMLError):

[docs]class Delivery(Object): def __init__(self, payload=None, log=None, errors=None, error=None): if payload is None: payload = [] if log is None: log = [] if errors is None: errors = [] if error is not None: errors.append(error) Object.__init__(self, payload=payload, log=log, errors=errors) payload = List.T(Any.T()) log = List.T(Tuple.T(3, String.T())) errors = List.T(Tuple.T(3, String.T())) def extend(self, other): self.payload.extend(other.payload) self.log.extend(other.log) self.errors.extend(other.errors) def extend_without_payload(self, other): self.log.extend(other.log) self.errors.extend(other.errors) return other.payload def emit_log(self): for name, message, context in self.log: message = '%s: %s' % (context, message) _logs[name](message) def expect(self, quiet=False): if not quiet: self.emit_log() if self.errors: name, message, context = self.errors[0] if context: message += ' (%s)' % context if len(self.errors) > 1: message += ' Additional errors pending.' raise _exceptions[name](message) return self.payload def expect_one(self, quiet=False): payload = self.expect(quiet=quiet) if len(payload) != 1: raise DeliveryError( 'Expected 1 element but got %i.' % len(payload)) return payload[0]
def wrap(s, width=80, indent=4): words = s.split() lines = [] t = [] n = 0 for w in words: if n + len(w) >= width: lines.append(' '.join(t)) n = indent t = [' '*(indent-1)] t.append(w) n += len(w) + 1 lines.append(' '.join(t)) return '\n'.join(lines) def same(x, eps=0.0): if any(type(x[0]) is not type(r) for r in x): return False if isinstance(x[0], float): return all(abs(r-x[0]) <= eps for r in x) else: return all(r == x[0] for r in x) def same_sample_rate(a, b, eps=1.0e-6): return abs(a - b) < min(a, b)*eps def evaluate1(resp, f): return resp.evaluate(num.array([f], dtype=float))[0] def check_resp(resp, value, frequency, limit_db, prelude, context): try: value_resp = num.abs(evaluate1(resp, frequency)) except response.InvalidResponseError as e: return Delivery(log=[( 'warning', 'Could not check response: %s' % str(e), context)]) if value_resp == 0.0: return Delivery(log=[( 'warning', '%s\n' ' computed response is zero' % prelude, context)]) diff_db = 20.0 * num.log10(value_resp/value) if num.abs(diff_db) > limit_db: return Delivery(log=[( 'warning', '%s\n' ' reported value: %g\n' ' computed value: %g\n' ' at frequency [Hz]: %g\n' ' factor: %g\n' ' difference [dB]: %g\n' ' limit [dB]: %g' % ( prelude, value, value_resp, frequency, value_resp/value, diff_db, limit_db), context)]) return Delivery() def tts(t): if t is None: return '<none>' else: return util.tts(t, format='%Y-%m-%d %H:%M:%S') def le_open_left(a, b): return a is None or (b is not None and a <= b) def le_open_right(a, b): return b is None or (a is not None and a <= b) def eq_open(a, b): return (a is None and b is None) \ or (a is not None and b is not None and a == b) def contains(a, b): return le_open_left(a.start_date, b.start_date) \ and le_open_right(b.end_date, a.end_date) def find_containing(candidates, node): for candidate in candidates: if contains(candidate, node): return candidate return None this_year = time.gmtime()[0]
[docs]class DummyAwareOptionalTimestamp(Object): ''' Optional timestamp with support for some common placeholder values. Some StationXML files contain arbitrary placeholder values for open end intervals, like "2100-01-01". Depending on the time range supported by the system, these dates are translated into ``None`` to prevent crashes with this type. ''' dummy_for = (hpfloat, float) dummy_for_description = 'pyrocko.util.get_time_float' class __T(TBase): def regularize_extra(self, val): time_float = get_time_float() if isinstance(val, datetime.datetime): tt = val.utctimetuple() val = time_float(calendar.timegm(tt)) + val.microsecond * 1e-6 elif isinstance(val, tt = val.timetuple() val = time_float(calendar.timegm(tt)) elif isinstance(val, str): val = val.strip() tz_offset = 0 m = if m: sh = sm = tz_offset = (int(sh)*3600 if sh else 0) \ + (int(sm)*60 if sm else 0) val = re_tz.sub('', val) if len(val) > 10 and val[10] == 'T': val = val.replace('T', ' ', 1) try: val = util.str_to_time(val) - tz_offset except util.TimeStrError: year = int(val[:4]) if sys.maxsize > 2**32: # if we're on 64bit if year > this_year + 100: return None # StationXML contained a dummy date if year < 1903: # for macOS, 1900-01-01 dummy dates return None else: # 32bit end of time is in 2038 if this_year < 2037 and year > 2037 or year < 1903: return None # StationXML contained a dummy date raise elif isinstance(val, (int, float)): val = time_float(val) else: raise ValidationError( '%s: cannot convert "%s" to type %s' % ( self.xname(), val, time_float)) return val def to_save(self, val): return time_to_str(val, format='%Y-%m-%d %H:%M:%S.9FRAC')\ .rstrip('0').rstrip('.') def to_save_xml(self, val): return time_to_str(val, format='%Y-%m-%dT%H:%M:%S.9FRAC')\ .rstrip('0').rstrip('.') + 'Z'
[docs]class Nominal(StringChoice): choices = [ 'NOMINAL', 'CALCULATED']
[docs]class Email(UnicodePattern): pattern = u'[\\w\\.\\-_]+@[\\w\\.\\-_]+'
[docs]class RestrictedStatus(StringChoice): choices = [ 'open', 'closed', 'partial']
[docs]class Type(StringChoice): choices = [ 'TRIGGERED', 'CONTINUOUS', 'HEALTH', 'GEOPHYSICAL', 'WEATHER', 'FLAG', 'SYNTHESIZED', 'INPUT', 'EXPERIMENTAL', 'MAINTENANCE', 'BEAM'] class __T(StringChoice.T): def validate_extra(self, val): if val not in self.choices: logger.warning( 'channel type: "%s" is not a valid choice out of %s' % (val, repr(self.choices)))
[docs]class PzTransferFunction(StringChoice): choices = [ 'LAPLACE (RADIANS/SECOND)', 'LAPLACE (HERTZ)', 'DIGITAL (Z-TRANSFORM)']
[docs]class Symmetry(StringChoice): choices = [ 'NONE', 'EVEN', 'ODD']
[docs]class CfTransferFunction(StringChoice): class __T(StringChoice.T): def validate(self, val, regularize=False, depth=-1): if regularize: try: val = str(val) except ValueError: raise ValidationError( '%s: cannot convert to string %s' % (self.xname, repr(val))) val = self._dummy_cls.replacements.get(val, val) self.validate_extra(val) return val choices = [ 'ANALOG (RADIANS/SECOND)', 'ANALOG (HERTZ)', 'DIGITAL'] replacements = { 'ANALOG (RAD/SEC)': 'ANALOG (RADIANS/SECOND)', 'ANALOG (HZ)': 'ANALOG (HERTZ)', }
[docs]class Approximation(StringChoice): choices = [ 'MACLAURIN']
class PhoneNumber(StringPattern): pattern = '[0-9]+-[0-9]+'
[docs]class Site(Object): ''' Description of a site location using name and optional geopolitical boundaries (country, city, etc.). ''' name = Unicode.T(default='', xmltagname='Name') description = Unicode.T(optional=True, xmltagname='Description') town = Unicode.T(optional=True, xmltagname='Town') county = Unicode.T(optional=True, xmltagname='County') region = Unicode.T(optional=True, xmltagname='Region') country = Unicode.T(optional=True, xmltagname='Country')
[docs]class ExternalReference(Object): ''' This type contains a URI and description for external data that users may want to reference in StationXML. ''' uri = String.T(xmltagname='URI') description = Unicode.T(xmltagname='Description')
[docs]class Units(Object): ''' A type to document units. Corresponds to SEED blockette 34. ''' def __init__(self, name=None, **kwargs): Object.__init__(self, name=name, **kwargs) name = String.T(xmltagname='Name') description = Unicode.T(optional=True, xmltagname='Description')
[docs]class Counter(Int): pass
[docs]class SampleRateRatio(Object): ''' Sample rate expressed as number of samples in a number of seconds. ''' number_samples = Int.T(xmltagname='NumberSamples') number_seconds = Int.T(xmltagname='NumberSeconds')
[docs]class Gain(Object): ''' Complex type for sensitivity and frequency ranges. This complex type can be used to represent both overall sensitivities and individual stage gains. The FrequencyRangeGroup is an optional construct that defines a pass band in Hertz ( FrequencyStart and FrequencyEnd) in which the SensitivityValue is valid within the number of decibels specified in FrequencyDBVariation. ''' def __init__(self, value=None, **kwargs): Object.__init__(self, value=value, **kwargs) value = Float.T(optional=True, xmltagname='Value') frequency = Float.T(optional=True, xmltagname='Frequency') def summary(self): return 'gain(%g @ %g)' % (self.value, self.frequency)
[docs]class NumeratorCoefficient(Object): i = Int.T(optional=True, xmlstyle='attribute') value = Float.T(xmlstyle='content')
[docs]class FloatNoUnit(Object): def __init__(self, value=None, **kwargs): Object.__init__(self, value=value, **kwargs) plus_error = Float.T(optional=True, xmlstyle='attribute') minus_error = Float.T(optional=True, xmlstyle='attribute') value = Float.T(xmlstyle='content')
[docs]class FloatWithUnit(FloatNoUnit): unit = String.T(optional=True, xmlstyle='attribute')
[docs]class Equipment(Object): resource_id = String.T(optional=True, xmlstyle='attribute') type = String.T(optional=True, xmltagname='Type') description = Unicode.T(optional=True, xmltagname='Description') manufacturer = Unicode.T(optional=True, xmltagname='Manufacturer') vendor = Unicode.T(optional=True, xmltagname='Vendor') model = Unicode.T(optional=True, xmltagname='Model') serial_number = String.T(optional=True, xmltagname='SerialNumber') installation_date = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='InstallationDate') removal_date = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='RemovalDate') calibration_date_list = List.T(Timestamp.T(xmltagname='CalibrationDate'))
[docs]class PhoneNumber(Object): description = Unicode.T(optional=True, xmlstyle='attribute') country_code = Int.T(optional=True, xmltagname='CountryCode') area_code = Int.T(xmltagname='AreaCode') phone_number = PhoneNumber.T(xmltagname='PhoneNumber')
[docs]class BaseFilter(Object): ''' The BaseFilter is derived by all filters. ''' resource_id = String.T(optional=True, xmlstyle='attribute') name = String.T(optional=True, xmlstyle='attribute') description = Unicode.T(optional=True, xmltagname='Description') input_units = Units.T(optional=True, xmltagname='InputUnits') output_units = Units.T(optional=True, xmltagname='OutputUnits')
[docs]class Sensitivity(Gain): ''' Sensitivity and frequency ranges. The FrequencyRangeGroup is an optional construct that defines a pass band in Hertz (FrequencyStart and FrequencyEnd) in which the SensitivityValue is valid within the number of decibels specified in FrequencyDBVariation. ''' input_units = Units.T(optional=True, xmltagname='InputUnits') output_units = Units.T(optional=True, xmltagname='OutputUnits') frequency_start = Float.T(optional=True, xmltagname='FrequencyStart') frequency_end = Float.T(optional=True, xmltagname='FrequencyEnd') frequency_db_variation = Float.T(optional=True, xmltagname='FrequencyDBVariation') def get_pyrocko_response(self): return Delivery( [response.PoleZeroResponse(constant=self.value)])
[docs]class Coefficient(FloatNoUnit): number = Counter.T(optional=True, xmlstyle='attribute')
[docs]class PoleZero(Object): ''' Complex numbers used as poles or zeros in channel response. ''' number = Int.T(optional=True, xmlstyle='attribute') real = FloatNoUnit.T(xmltagname='Real') imaginary = FloatNoUnit.T(xmltagname='Imaginary') def value(self): return self.real.value + 1J * self.imaginary.value
[docs]class ClockDrift(FloatWithUnit): unit = String.T(default='SECONDS/SAMPLE', optional=True, xmlstyle='attribute') # fixed
[docs]class Second(FloatWithUnit): ''' A time value in seconds. ''' unit = String.T(default='SECONDS', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Voltage(FloatWithUnit): unit = String.T(default='VOLTS', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Angle(FloatWithUnit): unit = String.T(default='DEGREES', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Azimuth(FloatWithUnit): ''' Instrument azimuth, degrees clockwise from North. ''' unit = String.T(default='DEGREES', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Dip(FloatWithUnit): ''' Instrument dip in degrees down from horizontal. Together azimuth and dip describe the direction of the sensitive axis of the instrument. ''' unit = String.T(default='DEGREES', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Distance(FloatWithUnit): ''' Extension of FloatWithUnit for distances, elevations, and depths. ''' unit = String.T(default='METERS', optional=True, xmlstyle='attribute')
# NOT fixed unit!
[docs]class Frequency(FloatWithUnit): unit = String.T(default='HERTZ', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class SampleRate(FloatWithUnit): ''' Sample rate in samples per second. ''' unit = String.T(default='SAMPLES/S', optional=True, xmlstyle='attribute')
# fixed unit
[docs]class Person(Object): ''' Representation of a person's contact information. A person can belong to multiple agencies and have multiple email addresses and phone numbers. ''' name_list = List.T(Unicode.T(xmltagname='Name')) agency_list = List.T(Unicode.T(xmltagname='Agency')) email_list = List.T(Email.T(xmltagname='Email')) phone_list = List.T(PhoneNumber.T(xmltagname='Phone'))
[docs]class FIR(BaseFilter): ''' Response: FIR filter. Corresponds to SEED blockette 61. FIR filters are also commonly documented using the Coefficients element. ''' symmetry = Symmetry.T(xmltagname='Symmetry') numerator_coefficient_list = List.T( NumeratorCoefficient.T(xmltagname='NumeratorCoefficient')) def summary(self): return 'fir(%i%s)' % ( self.get_ncoefficiencs(), ',sym' if self.get_effective_symmetry() != 'NONE' else '') def get_effective_coefficients(self): b = num.array( [v.value for v in self.numerator_coefficient_list], dtype=float) if self.symmetry == 'ODD': b = num.concatenate((b, b[-2::-1])) elif self.symmetry == 'EVEN': b = num.concatenate((b, b[::-1])) return b def get_effective_symmetry(self): if self.symmetry == 'NONE': b = self.get_effective_coefficients() if num.all(b - b[::-1] == 0): return ['EVEN', 'ODD'][b.size % 2] return self.symmetry def get_ncoefficiencs(self): nf = len(self.numerator_coefficient_list) if self.symmetry == 'ODD': nc = nf * 2 + 1 elif self.symmetry == 'EVEN': nc = nf * 2 else: nc = nf return nc def estimate_delay(self, deltat): nc = self.get_ncoefficiencs() if nc > 0: return deltat * (nc - 1) / 2.0 else: return 0.0 def get_pyrocko_response( self, context, deltat, delay_responses, normalization_frequency): context += self.summary() if not self.numerator_coefficient_list: return Delivery([]) b = self.get_effective_coefficients() log = [] drop_phase = self.get_effective_symmetry() != 'NONE' if not deltat: log.append(( 'error', 'Digital response requires knowledge about sampling ' 'interval. Response will be unusable.', context)) resp = response.DigitalFilterResponse( b.tolist(), [1.0], deltat or 0.0, drop_phase=drop_phase) if normalization_frequency is not None and deltat is not None: normalization_frequency = 0.0 normalization = num.abs(evaluate1(resp, normalization_frequency)) if num.abs(normalization - 1.0) > 1e-2: log.append(( 'warning', 'FIR filter coefficients are not normalized. Normalizing ' 'them. Factor: %g' % normalization, context)) resp = response.DigitalFilterResponse( (b/normalization).tolist(), [1.0], deltat, drop_phase=drop_phase) resps = [resp] if not drop_phase: resps.extend(delay_responses) return Delivery(resps, log=log)
[docs]class Coefficients(BaseFilter): ''' Response: coefficients for FIR filter. Laplace transforms or IIR filters can be expressed using type as well but the PolesAndZeros should be used instead. Corresponds to SEED blockette 54. ''' cf_transfer_function_type = CfTransferFunction.T( xmltagname='CfTransferFunctionType') numerator_list = List.T(FloatWithUnit.T(xmltagname='Numerator')) denominator_list = List.T(FloatWithUnit.T(xmltagname='Denominator')) def summary(self): return 'coef_%s(%i,%i%s)' % ( 'ABC?'[ CfTransferFunction.choices.index( self.cf_transfer_function_type)], len(self.numerator_list), len(self.denominator_list), ',sym' if self.is_symmetric_fir else '') def estimate_delay(self, deltat): nc = len(self.numerator_list) if nc > 0: return deltat * (len(self.numerator_list) - 1) / 2.0 else: return 0.0 def is_symmetric_fir(self): if len(self.denominator_list) != 0: return False b = [v.value for v in self.numerator_list] return b == b[::-1] def get_pyrocko_response( self, context, deltat, delay_responses, normalization_frequency): context += self.summary() factor = 1.0 if self.cf_transfer_function_type == 'ANALOG (HERTZ)': factor = 2.0*math.pi if not self.numerator_list and not self.denominator_list: return Delivery(payload=[]) b = num.array( [v.value*factor for v in self.numerator_list], dtype=float) a = num.array( [1.0] + [v.value*factor for v in self.denominator_list], dtype=float) log = [] resps = [] if self.cf_transfer_function_type in [ 'ANALOG (RADIANS/SECOND)', 'ANALOG (HERTZ)']: resps.append(response.AnalogFilterResponse(b, a)) elif self.cf_transfer_function_type == 'DIGITAL': if not deltat: log.append(( 'error', 'Digital response requires knowledge about sampling ' 'interval. Response will be unusable.', context)) drop_phase = self.is_symmetric_fir() resp = response.DigitalFilterResponse( b, a, deltat or 0.0, drop_phase=drop_phase) if normalization_frequency is not None and deltat is not None: normalization = num.abs(evaluate1( resp, normalization_frequency)) if num.abs(normalization - 1.0) > 1e-2: log.append(( 'warning', 'FIR filter coefficients are not normalized. ' 'Normalizing them. Factor: %g' % normalization, context)) resp = response.DigitalFilterResponse( (b/normalization).tolist(), [1.0], deltat, drop_phase=drop_phase) resps.append(resp) if not drop_phase: resps.extend(delay_responses) else: return Delivery(error=( 'ValueError', 'Unknown transfer function type: %s' % ( self.cf_transfer_function_type))) return Delivery(payload=resps, log=log)
[docs]class Latitude(FloatWithUnit): ''' Type for latitude coordinate. ''' unit = String.T(default='DEGREES', optional=True, xmlstyle='attribute') # fixed unit datum = String.T(default='WGS84', optional=True, xmlstyle='attribute')
[docs]class Longitude(FloatWithUnit): ''' Type for longitude coordinate. ''' unit = String.T(default='DEGREES', optional=True, xmlstyle='attribute') # fixed unit datum = String.T(default='WGS84', optional=True, xmlstyle='attribute')
[docs]class PolesZeros(BaseFilter): ''' Response: complex poles and zeros. Corresponds to SEED blockette 53. ''' pz_transfer_function_type = PzTransferFunction.T( xmltagname='PzTransferFunctionType') normalization_factor = Float.T( default=1.0, xmltagname='NormalizationFactor') normalization_frequency = Frequency.T( optional=True, # but required by standard xmltagname='NormalizationFrequency') zero_list = List.T(PoleZero.T(xmltagname='Zero')) pole_list = List.T(PoleZero.T(xmltagname='Pole')) def summary(self): return 'pz_%s(%i,%i)' % ( 'ABC?'[ PzTransferFunction.choices.index( self.pz_transfer_function_type)], len(self.pole_list), len(self.zero_list)) def get_pyrocko_response(self, context='', deltat=None): context += self.summary() factor = 1.0 cfactor = 1.0 if self.pz_transfer_function_type == 'LAPLACE (HERTZ)': factor = 2. * math.pi cfactor = (2. * math.pi)**( len(self.pole_list) - len(self.zero_list)) log = [] if self.normalization_factor is None \ or self.normalization_factor == 0.0: log.append(( 'warning', 'No pole-zero normalization factor given. ' 'Assuming a value of 1.0', context)) nfactor = 1.0 else: nfactor = self.normalization_factor is_digital = self.pz_transfer_function_type == 'DIGITAL (Z-TRANSFORM)' if not is_digital: resp = response.PoleZeroResponse( constant=nfactor*cfactor, zeros=[z.value()*factor for z in self.zero_list], poles=[p.value()*factor for p in self.pole_list]) else: if not deltat: log.append(( 'error', 'Digital response requires knowledge about sampling ' 'interval. Response will be unusable.', context)) resp = response.DigitalPoleZeroResponse( constant=nfactor*cfactor, zeros=[z.value()*factor for z in self.zero_list], poles=[p.value()*factor for p in self.pole_list], deltat=deltat or 0.0) if not self.normalization_frequency: log.append(( 'warning', 'Cannot check pole-zero normalization factor: ' 'No normalization frequency given.', context)) else: if is_digital and not deltat: log.append(( 'warning', 'Cannot check computed vs reported normalization ' 'factor without knowing the sampling interval.', context)) else: computed_normalization_factor = nfactor / abs(evaluate1( resp, self.normalization_frequency.value)) db = 20.0 * num.log10( computed_normalization_factor / nfactor) if abs(db) > 0.17: log.append(( 'warning', 'Computed and reported normalization factors differ ' 'by %g dB: computed: %g, reported: %g' % ( db, computed_normalization_factor, nfactor), context)) return Delivery([resp], log)
[docs]class ResponseListElement(Object): frequency = Frequency.T(xmltagname='Frequency') amplitude = FloatWithUnit.T(xmltagname='Amplitude') phase = Angle.T(xmltagname='Phase')
[docs]class Polynomial(BaseFilter): ''' Response: expressed as a polynomial (allows non-linear sensors to be described). Corresponds to SEED blockette 62. Can be used to describe a stage of acquisition or a complete system. ''' approximation_type = Approximation.T(default='MACLAURIN', xmltagname='ApproximationType') frequency_lower_bound = Frequency.T(xmltagname='FrequencyLowerBound') frequency_upper_bound = Frequency.T(xmltagname='FrequencyUpperBound') approximation_lower_bound = Float.T(xmltagname='ApproximationLowerBound') approximation_upper_bound = Float.T(xmltagname='ApproximationUpperBound') maximum_error = Float.T(xmltagname='MaximumError') coefficient_list = List.T(Coefficient.T(xmltagname='Coefficient')) def summary(self): return 'poly(%i)' % len(self.coefficient_list)
[docs]class Decimation(Object): ''' Corresponds to SEED blockette 57. ''' input_sample_rate = Frequency.T(xmltagname='InputSampleRate') factor = Int.T(xmltagname='Factor') offset = Int.T(xmltagname='Offset') delay = FloatWithUnit.T(xmltagname='Delay') correction = FloatWithUnit.T(xmltagname='Correction') def summary(self): return 'deci(%i, %g -> %g, %g)' % ( self.factor, self.input_sample_rate.value, self.input_sample_rate.value / self.factor, self.delay.value) def get_pyrocko_response(self): if self.delay and self.delay.value != 0.0: return Delivery([response.DelayResponse(delay=-self.delay.value)]) else: return Delivery([])
[docs]class Operator(Object): agency_list = List.T(Unicode.T(xmltagname='Agency')) contact_list = List.T(Person.T(xmltagname='Contact')) web_site = String.T(optional=True, xmltagname='WebSite')
[docs]class Comment(Object): ''' Container for a comment or log entry. Corresponds to SEED blockettes 31, 51 and 59. ''' id = Counter.T(optional=True, xmlstyle='attribute') value = Unicode.T(xmltagname='Value') begin_effective_time = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='BeginEffectiveTime') end_effective_time = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='EndEffectiveTime') author_list = List.T(Person.T(xmltagname='Author'))
[docs]class ResponseList(BaseFilter): ''' Response: list of frequency, amplitude and phase values. Corresponds to SEED blockette 55. ''' response_list_element_list = List.T( ResponseListElement.T(xmltagname='ResponseListElement')) def summary(self): return 'list(%i)' % len(self.response_list_element_list)
[docs]class Log(Object): ''' Container for log entries. ''' entry_list = List.T(Comment.T(xmltagname='Entry'))
[docs]class ResponseStage(Object): ''' This complex type represents channel response and covers SEED blockettes 53 to 56. ''' number = Counter.T(xmlstyle='attribute') resource_id = String.T(optional=True, xmlstyle='attribute') poles_zeros_list = List.T( PolesZeros.T(optional=True, xmltagname='PolesZeros')) coefficients_list = List.T( Coefficients.T(optional=True, xmltagname='Coefficients')) response_list = ResponseList.T(optional=True, xmltagname='ResponseList') fir = FIR.T(optional=True, xmltagname='FIR') polynomial = Polynomial.T(optional=True, xmltagname='Polynomial') decimation = Decimation.T(optional=True, xmltagname='Decimation') stage_gain = Gain.T(optional=True, xmltagname='StageGain') def summary(self): elements = [] for stuff in [ self.poles_zeros_list, self.coefficients_list, self.response_list, self.fir, self.polynomial, self.decimation, self.stage_gain]: if stuff: if isinstance(stuff, Object): elements.append(stuff.summary()) else: elements.extend(obj.summary() for obj in stuff) return '%i: %s %s -> %s' % ( self.number, ', '.join(elements), sanitize_units( if self.input_units else '?', sanitize_units( if self.output_units else '?') def get_squirrel_response_stage(self, context): from pyrocko.squirrel.model import ResponseStage delivery = Delivery() delivery_pr = self.get_pyrocko_response(context) log = delivery_pr.log delivery_pr.log = [] elements = delivery.extend_without_payload(delivery_pr) delivery.payload = [ResponseStage( input_quantity=to_quantity(self.input_units, context, delivery), output_quantity=to_quantity(self.output_units, context, delivery), input_sample_rate=self.input_sample_rate, output_sample_rate=self.output_sample_rate, elements=elements, log=log)] return delivery def get_pyrocko_response(self, context, gain_only=False): context = context + ', stage %i' % self.number responses = [] log = [] if self.stage_gain: normalization_frequency = self.stage_gain.frequency or 0.0 else: normalization_frequency = 0.0 if not gain_only: deltat = None delay_responses = [] if self.decimation: rate = self.decimation.input_sample_rate.value if rate > 0.0: deltat = 1.0 / rate delivery = self.decimation.get_pyrocko_response() if delivery.errors: return delivery delay_responses = delivery.payload log.extend(delivery.log) for pzs in self.poles_zeros_list: delivery = pzs.get_pyrocko_response(context, deltat) if delivery.errors: return delivery pz_resps = delivery.payload log.extend(delivery.log) responses.extend(pz_resps) # emulate incorrect? evalresp behaviour if pzs.normalization_frequency is not None and \ pzs.normalization_frequency.value \ != normalization_frequency \ and normalization_frequency != 0.0: try: trial = response.MultiplyResponse(pz_resps) anorm = num.abs(evaluate1( trial, pzs.normalization_frequency.value)) asens = num.abs( evaluate1(trial, normalization_frequency)) factor = anorm/asens if abs(factor - 1.0) > 0.01: log.append(( 'warning', 'PZ normalization frequency (%g) is different ' 'from stage gain frequency (%s) -> Emulating ' 'possibly incorrect evalresp behaviour. ' 'Correction factor: %g' % ( pzs.normalization_frequency.value, normalization_frequency, factor), context)) responses.append( response.PoleZeroResponse(constant=factor)) except response.InvalidResponseError as e: log.append(( 'warning', 'Could not check response: %s' % str(e), context)) if len(self.poles_zeros_list) > 1: log.append(( 'warning', 'Multiple poles and zeros records in single response ' 'stage.', context)) for cfs in self.coefficients_list + ( [self.fir] if self.fir else []): delivery = cfs.get_pyrocko_response( context, deltat, delay_responses, normalization_frequency) if delivery.errors: return delivery responses.extend(delivery.payload) log.extend(delivery.log) if len(self.coefficients_list) > 1: log.append(( 'warning', 'Multiple filter coefficients lists in single response ' 'stage.', context)) if self.response_list: log.append(( 'warning', 'Unhandled response element of type: ResponseList', context)) if self.polynomial: log.append(( 'warning', 'Unhandled response element of type: Polynomial', context)) if self.stage_gain: responses.append( response.PoleZeroResponse(constant=self.stage_gain.value)) return Delivery(responses, log) @property def input_units(self): for e in (self.poles_zeros_list + self.coefficients_list + [self.response_list, self.fir, self.polynomial]): if e is not None: return e.input_units return None @property def output_units(self): for e in (self.poles_zeros_list + self.coefficients_list + [self.response_list, self.fir, self.polynomial]): if e is not None: return e.output_units return None @property def input_sample_rate(self): if self.decimation: return self.decimation.input_sample_rate.value return None @property def output_sample_rate(self): if self.decimation: return self.decimation.input_sample_rate.value \ / self.decimation.factor return None
[docs]class Response(Object): resource_id = String.T(optional=True, xmlstyle='attribute') instrument_sensitivity = Sensitivity.T(optional=True, xmltagname='InstrumentSensitivity') instrument_polynomial = Polynomial.T(optional=True, xmltagname='InstrumentPolynomial') stage_list = List.T(ResponseStage.T(xmltagname='Stage')) @property def output_sample_rate(self): if self.stage_list: return self.stage_list[-1].output_sample_rate else: return None def check_sample_rates(self, channel): if self.stage_list: sample_rate = None for stage in self.stage_list: if stage.decimation: input_sample_rate = \ stage.decimation.input_sample_rate.value if sample_rate is not None and not same_sample_rate( sample_rate, input_sample_rate): logger.warning( 'Response stage %i has unexpected input sample ' 'rate: %g Hz (expected: %g Hz)' % ( stage.number, input_sample_rate, sample_rate)) sample_rate = input_sample_rate / stage.decimation.factor if sample_rate is not None and channel.sample_rate \ and not same_sample_rate( sample_rate, channel.sample_rate.value): logger.warning( 'Channel sample rate (%g Hz) does not match sample rate ' 'deducted from response stages information (%g Hz).' % ( channel.sample_rate.value, sample_rate)) def check_units(self): if self.instrument_sensitivity \ and self.instrument_sensitivity.input_units: units = sanitize_units( if self.stage_list: for stage in self.stage_list: if units and stage.input_units \ and sanitize_units( != units: logger.warning( 'Input units of stage %i (%s) do not match %s (%s).' % ( stage.number, units, 'output units of stage %i' if stage.number == 0 else 'sensitivity input units', units)) if stage.output_units: units = sanitize_units( else: units = None sout_units = self.instrument_sensitivity.output_units if self.instrument_sensitivity and sout_units: if units is not None and units != sanitize_units( logger.warning( 'Output units of stage %i (%s) do not match %s (%s).' % ( stage.number, units, 'sensitivity output units', sanitize_units( def _sensitivity_checkpoints(self, responses, context): delivery = Delivery() if self.instrument_sensitivity: sval = self.instrument_sensitivity.value sfreq = self.instrument_sensitivity.frequency if sval is None: delivery.log.append(( 'warning', 'No sensitivity value given.', context)) elif sval is None: delivery.log.append(( 'warning', 'Reported sensitivity value is zero.', context)) elif sfreq is None: delivery.log.append(( 'warning', 'Sensitivity frequency not given.', context)) else: trial = response.MultiplyResponse(responses) delivery.extend( check_resp( trial, sval, sfreq, 0.1, 'Instrument sensitivity value inconsistent with ' 'sensitivity computed from complete response.', context)) delivery.payload.append(response.FrequencyResponseCheckpoint( frequency=sfreq, value=sval)) return delivery def get_squirrel_response(self, context, **kwargs): from pyrocko.squirrel.model import Response if self.stage_list: delivery = Delivery() for istage, stage in enumerate(self.stage_list): delivery.extend(stage.get_squirrel_response_stage(context)) checkpoints = [] if not delivery.errors: all_responses = [] for sq_stage in delivery.payload: all_responses.extend(sq_stage.elements) checkpoints.extend(delivery.extend_without_payload( self._sensitivity_checkpoints(all_responses, context))) sq_stages = delivery.payload if sq_stages: if sq_stages[0].input_quantity is None \ and self.instrument_sensitivity is not None: sq_stages[0].input_quantity = to_quantity( self.instrument_sensitivity.input_units, context, delivery) sq_stages[-1].output_quantity = to_quantity( self.instrument_sensitivity.output_units, context, delivery) sq_stages = delivery.expect() return Response( stages=sq_stages, log=delivery.log, checkpoints=checkpoints, **kwargs) elif self.instrument_sensitivity: raise NoResponseInformation( "Only instrument sensitivity given (won't use it). (%s)." % context) else: raise NoResponseInformation( 'Empty instrument response (%s).' % context) def get_pyrocko_response( self, context, fake_input_units=None, stages=(0, 1)): if fake_input_units is not None: fake_input_units = sanitize_units(fake_input_units) delivery = Delivery() if self.stage_list: for istage, stage in enumerate(self.stage_list): delivery.extend(stage.get_pyrocko_response( context, gain_only=not ( stages is None or stages[0] <= istage < stages[1]))) elif self.instrument_sensitivity: delivery.extend(self.instrument_sensitivity.get_pyrocko_response()) delivery_cp = self._sensitivity_checkpoints(delivery.payload, context) checkpoints = delivery.extend_without_payload(delivery_cp) if delivery.errors: return delivery if fake_input_units is not None: if not self.instrument_sensitivity or \ self.instrument_sensitivity.input_units is None: delivery.errors.append(( 'NoResponseInformation', 'No input units given, so cannot convert to requested ' 'units: %s' % fake_input_units, context)) return delivery input_units = sanitize_units( conresp = None try: conresp = conversion[ fake_input_units, input_units] except KeyError: delivery.errors.append(( 'NoResponseInformation', 'Cannot convert between units: %s, %s' % (fake_input_units, input_units), context)) if conresp is not None: delivery.payload.append(conresp) for checkpoint in checkpoints: checkpoint.value *= num.abs(evaluate1( conresp, checkpoint.frequency)) delivery.payload = [ response.MultiplyResponse( delivery.payload, checkpoints=checkpoints)] return delivery
[docs] @classmethod def from_pyrocko_pz_response(cls, presponse, input_unit, output_unit, normalization_frequency=1.0): ''' Convert Pyrocko pole-zero response to StationXML response. :param presponse: Pyrocko pole-zero response :type presponse: :py:class:`~pyrocko.response.PoleZeroResponse` :param input_unit: Input unit to be reported in the StationXML response. :type input_unit: str :param output_unit: Output unit to be reported in the StationXML response. :type output_unit: str :param normalization_frequency: Frequency where the normalization factor for the StationXML response should be computed. :type normalization_frequency: float ''' norm_factor = 1.0/float(abs( evaluate1(presponse, normalization_frequency) / presponse.constant)) pzs = PolesZeros( pz_transfer_function_type='LAPLACE (RADIANS/SECOND)', normalization_factor=norm_factor, normalization_frequency=Frequency(normalization_frequency), zero_list=[PoleZero(real=FloatNoUnit(z.real), imaginary=FloatNoUnit(z.imag)) for z in presponse.zeros], pole_list=[PoleZero(real=FloatNoUnit(z.real), imaginary=FloatNoUnit(z.imag)) for z in presponse.poles]) pzs.validate() stage = ResponseStage( number=1, poles_zeros_list=[pzs], stage_gain=Gain(float(abs(presponse.constant))/norm_factor)) resp = Response( instrument_sensitivity=Sensitivity( value=stage.stage_gain.value, frequency=normalization_frequency, input_units=Units(input_unit), output_units=Units(output_unit)), stage_list=[stage]) return resp
[docs]class BaseNode(Object): ''' A base node type for derivation from: Network, Station and Channel types. ''' code = String.T(xmlstyle='attribute') start_date = DummyAwareOptionalTimestamp.T(optional=True, xmlstyle='attribute') end_date = DummyAwareOptionalTimestamp.T(optional=True, xmlstyle='attribute') restricted_status = RestrictedStatus.T(optional=True, xmlstyle='attribute') alternate_code = String.T(optional=True, xmlstyle='attribute') historical_code = String.T(optional=True, xmlstyle='attribute') description = Unicode.T(optional=True, xmltagname='Description') comment_list = List.T(Comment.T(xmltagname='Comment')) def spans(self, *args): if len(args) == 0: return True elif len(args) == 1: return ((self.start_date is None or self.start_date <= args[0]) and (self.end_date is None or args[0] <= self.end_date)) elif len(args) == 2: return ((self.start_date is None or args[1] >= self.start_date) and (self.end_date is None or self.end_date >= args[0]))
def overlaps(a, b): return ( a.start_date is None or b.end_date is None or a.start_date < b.end_date ) and ( b.start_date is None or a.end_date is None or b.start_date < a.end_date ) def check_overlaps(node_type_name, codes, nodes): errors = [] for ia, a in enumerate(nodes): for b in nodes[ia+1:]: if overlaps(a, b): errors.append( '%s epochs overlap for %s:\n' ' %s - %s\n %s - %s' % ( node_type_name, '.'.join(codes), tts(a.start_date), tts(a.end_date), tts(b.start_date), tts(b.end_date))) return errors
[docs]class Channel(BaseNode): ''' Equivalent to SEED blockette 52 and parent element for the related the response blockettes. ''' location_code = String.T(xmlstyle='attribute') external_reference_list = List.T( ExternalReference.T(xmltagname='ExternalReference')) latitude = Latitude.T(xmltagname='Latitude') longitude = Longitude.T(xmltagname='Longitude') elevation = Distance.T(xmltagname='Elevation') depth = Distance.T(xmltagname='Depth') azimuth = Azimuth.T(optional=True, xmltagname='Azimuth') dip = Dip.T(optional=True, xmltagname='Dip') type_list = List.T(Type.T(xmltagname='Type')) sample_rate = SampleRate.T(optional=True, xmltagname='SampleRate') sample_rate_ratio = SampleRateRatio.T(optional=True, xmltagname='SampleRateRatio') storage_format = String.T(optional=True, xmltagname='StorageFormat') clock_drift = ClockDrift.T(optional=True, xmltagname='ClockDrift') calibration_units = Units.T(optional=True, xmltagname='CalibrationUnits') sensor = Equipment.T(optional=True, xmltagname='Sensor') pre_amplifier = Equipment.T(optional=True, xmltagname='PreAmplifier') data_logger = Equipment.T(optional=True, xmltagname='DataLogger') equipment_list = List.T(Equipment.T(xmltagname='Equipment')) response = Response.T(optional=True, xmltagname='Response') @property def position_values(self): lat = self.latitude.value lon = self.longitude.value elevation = value_or_none(self.elevation) depth = value_or_none(self.depth) return lat, lon, elevation, depth
[docs]class Station(BaseNode): ''' This type represents a Station epoch. It is common to only have a single station epoch with the station's creation and termination dates as the epoch start and end dates. ''' latitude = Latitude.T(xmltagname='Latitude') longitude = Longitude.T(xmltagname='Longitude') elevation = Distance.T(xmltagname='Elevation') site = Site.T(default=Site.D(name=''), xmltagname='Site') vault = Unicode.T(optional=True, xmltagname='Vault') geology = Unicode.T(optional=True, xmltagname='Geology') equipment_list = List.T(Equipment.T(xmltagname='Equipment')) operator_list = List.T(Operator.T(xmltagname='Operator')) creation_date = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='CreationDate') termination_date = DummyAwareOptionalTimestamp.T( optional=True, xmltagname='TerminationDate') total_number_channels = Counter.T( optional=True, xmltagname='TotalNumberChannels') selected_number_channels = Counter.T( optional=True, xmltagname='SelectedNumberChannels') external_reference_list = List.T( ExternalReference.T(xmltagname='ExternalReference')) channel_list = List.T(Channel.T(xmltagname='Channel')) @property def position_values(self): lat = self.latitude.value lon = self.longitude.value elevation = value_or_none(self.elevation) return lat, lon, elevation
[docs]class Network(BaseNode): ''' This type represents the Network layer, all station metadata is contained within this element. The official name of the network or other descriptive information can be included in the Description element. The Network can contain 0 or more Stations. ''' total_number_stations = Counter.T(optional=True, xmltagname='TotalNumberStations') selected_number_stations = Counter.T(optional=True, xmltagname='SelectedNumberStations') station_list = List.T(Station.T(xmltagname='Station')) @property def station_code_list(self): return sorted(set(s.code for s in self.station_list)) @property def sl_code_list(self): sls = set() for station in self.station_list: for channel in station.channel_list: sls.add((station.code, channel.location_code)) return sorted(sls) def summary(self, width=80, indent=4): sls = self.sl_code_list or [(x,) for x in self.station_code_list] lines = ['%s (%i):' % (self.code, len(sls))] if sls: ssls = ['.'.join(x for x in c if x) for c in sls] w = max(len(x) for x in ssls) n = (width - indent) / (w+1) while ssls: lines.append( ' ' * indent + ' '.join(x.ljust(w) for x in ssls[:n])) ssls[:n] = [] return '\n'.join(lines)
def value_or_none(x): if x is not None: return x.value else: return None def pyrocko_station_from_channels(nsl, channels, inconsistencies='warn'): pos = lat, lon, elevation, depth = \ channels[0].position_values if not all(pos == x.position_values for x in channels): info = '\n'.join( ' %s: %s' % (x.code, x.position_values) for x in channels) mess = 'encountered inconsistencies in channel ' \ 'lat/lon/elevation/depth ' \ 'for %s.%s.%s: \n%s' % (nsl + (info,)) if inconsistencies == 'raise': raise InconsistentChannelLocations(mess) elif inconsistencies == 'warn': logger.warning(mess) logger.warning(' -> using mean values') apos = num.array([x.position_values for x in channels], dtype=float) mlat, mlon, mele, mdep = num.nansum(apos, axis=0) \ / num.sum(num.isfinite(apos), axis=0) groups = {} for channel in channels: if channel.code not in groups: groups[channel.code] = [] groups[channel.code].append(channel) pchannels = [] for code in sorted(groups.keys()): data = [ (channel.code, value_or_none(channel.azimuth), value_or_none(channel.dip)) for channel in groups[code]] azimuth, dip = util.consistency_merge( data, message='channel orientation values differ:', error=inconsistencies) pchannels.append( pyrocko.model.Channel(code, azimuth=azimuth, dip=dip)) return pyrocko.model.Station( *nsl, lat=mlat, lon=mlon, elevation=mele, depth=mdep, channels=pchannels)
[docs]class FDSNStationXML(Object): ''' Top-level type for Station XML. Required field are Source (network ID of the institution sending the message) and one or more Network containers or one or more Station containers. ''' schema_version = Float.T(default=1.0, xmlstyle='attribute') source = String.T(xmltagname='Source') sender = String.T(optional=True, xmltagname='Sender') module = String.T(optional=True, xmltagname='Module') module_uri = String.T(optional=True, xmltagname='ModuleURI') created = Timestamp.T(optional=True, xmltagname='Created') network_list = List.T(Network.T(xmltagname='Network')) xmltagname = 'FDSNStationXML' guessable_xmlns = [guts_xmlns] def __init__(self, *args, **kwargs): Object.__init__(self, *args, **kwargs) if self.created is None: self.created = time.time() def get_pyrocko_stations(self, nslcs=None, nsls=None, time=None, timespan=None, inconsistencies='warn', sloppy=False): assert inconsistencies in ('raise', 'warn') if nslcs is not None: nslcs = set(nslcs) if nsls is not None: nsls = set(nsls) tt = () if time is not None: tt = (time,) elif timespan is not None: tt = timespan ns_have = set() pstations = [] sensor_to_channels = defaultdict(list) for network in self.network_list: if not network.spans(*tt): continue for station in network.station_list: if not station.spans(*tt): continue if station.channel_list: loc_to_channels = {} for channel in station.channel_list: if not channel.spans(*tt): continue loc = channel.location_code.strip() if loc not in loc_to_channels: loc_to_channels[loc] = [] loc_to_channels[loc].append(channel) for loc in sorted(loc_to_channels.keys()): channels = loc_to_channels[loc] if nslcs is not None: channels = [channel for channel in channels if (network.code, station.code, loc, channel.code) in nslcs] if not channels: continue nsl = network.code, station.code, loc if nsls is not None and nsl not in nsls: continue for channel in channels: k = (nsl, channel.code[:-1]) if not sloppy: k += (channel.start_date, channel.end_date) sensor_to_channels[k].append(channel) else: ns = (network.code, station.code) if ns in ns_have: message = 'Duplicate station ' \ '(multiple epochs match): %s.%s ' % ns if inconsistencies == 'raise': raise Inconsistencies(message) else: logger.warning(message) ns_have.add(ns) pstations.append(pyrocko.model.Station( network.code, station.code, '*', lat=station.latitude.value, lon=station.longitude.value, elevation=value_or_none(station.elevation), name=station.description or '')) sensor_have = set() for k, channels in sensor_to_channels.items(): (nsl, bi) = k[:2] if (nsl, bi) in sensor_have: message = 'Duplicate station ' \ '(multiple epochs match): %s.%s.%s' % nsl if inconsistencies == 'raise': raise Inconsistencies(message) else: logger.warning(message) sensor_have.add((nsl, bi)) pstations.append( pyrocko_station_from_channels( nsl, channels, inconsistencies=inconsistencies)) return pstations
[docs] @classmethod def from_pyrocko_stations( cls, pyrocko_stations, add_flat_responses_from=None): ''' Generate :py:class:`FDSNStationXML` from list of :py:class;`pyrocko.model.Station` instances. :param pyrocko_stations: list of :py:class;`pyrocko.model.Station` instances. :param add_flat_responses_from: unit, 'M', 'M/S' or 'M/S**2' ''' network_dict = defaultdict(list) if add_flat_responses_from: assert add_flat_responses_from in ('M', 'M/S', 'M/S**2') extra = dict( response=Response( instrument_sensitivity=Sensitivity( value=1.0, frequency=1.0, input_units=Units(name=add_flat_responses_from)))) else: extra = {} have_offsets = set() for s in pyrocko_stations: if s.north_shift != 0.0 or s.east_shift != 0.0: have_offsets.add(s.nsl()) network, station, location = s.nsl() channel_list = [] for c in s.channels: channel_list.append( Channel( location_code=location,, latitude=Latitude(value=s.effective_lat), longitude=Longitude(value=s.effective_lon), elevation=Distance(value=s.elevation), depth=Distance(value=s.depth), azimuth=Azimuth(value=c.azimuth), dip=Dip(value=c.dip), **extra ) ) network_dict[network].append( Station( code=station, latitude=Latitude(value=s.effective_lat), longitude=Longitude(value=s.effective_lon), elevation=Distance(value=s.elevation), channel_list=channel_list) ) if have_offsets: logger.warning( 'StationXML does not support Cartesian offsets in ' 'coordinates. Storing effective lat/lon for stations: %s' % ', '.join('.'.join(nsl) for nsl in sorted(have_offsets))) timestamp = util.to_time_float(time.time()) network_list = [] for k, station_list in network_dict.items(): network_list.append( Network( code=k, station_list=station_list, total_number_stations=len(station_list))) sxml = FDSNStationXML( source='from pyrocko stations list', created=timestamp, network_list=network_list) sxml.validate() return sxml
def iter_network_stations( self, net=None, sta=None, time=None, timespan=None): tt = () if time is not None: tt = (time,) elif timespan is not None: tt = timespan for network in self.network_list: if not network.spans(*tt) or ( net is not None and network.code != net): continue for station in network.station_list: if not station.spans(*tt) or ( sta is not None and station.code != sta): continue yield (network, station) def iter_network_station_channels( self, net=None, sta=None, loc=None, cha=None, time=None, timespan=None): if loc is not None: loc = loc.strip() tt = () if time is not None: tt = (time,) elif timespan is not None: tt = timespan for network in self.network_list: if not network.spans(*tt) or ( net is not None and network.code != net): continue for station in network.station_list: if not station.spans(*tt) or ( sta is not None and station.code != sta): continue if station.channel_list: for channel in station.channel_list: if (not channel.spans(*tt) or (cha is not None and channel.code != cha) or (loc is not None and channel.location_code.strip() != loc)): continue yield (network, station, channel) def get_channel_groups(self, net=None, sta=None, loc=None, cha=None, time=None, timespan=None): groups = {} for network, station, channel in self.iter_network_station_channels( net, sta, loc, cha, time=time, timespan=timespan): net = network.code sta = station.code cha = channel.code loc = channel.location_code.strip() if len(cha) == 3: bic = cha[:2] # band and intrument code according to SEED elif len(cha) == 1: bic = '' else: bic = cha if channel.response and \ channel.response.instrument_sensitivity and \ channel.response.instrument_sensitivity.input_units: unit = sanitize_units( else: unit = None bic = (bic, unit) k = net, sta, loc if k not in groups: groups[k] = {} if bic not in groups[k]: groups[k][bic] = [] groups[k][bic].append(channel) for nsl, bic_to_channels in groups.items(): bad_bics = [] for bic, channels in bic_to_channels.items(): sample_rates = [] for channel in channels: sample_rates.append(channel.sample_rate.value) if not same(sample_rates): scs = ','.join(channel.code for channel in channels) srs = ', '.join('%e' % x for x in sample_rates) err = 'ignoring channels with inconsistent sampling ' + \ 'rates (%s.%s.%s.%s: %s)' % (nsl + (scs, srs)) logger.warning(err) bad_bics.append(bic) for bic in bad_bics: del bic_to_channels[bic] return groups def choose_channels( self, target_sample_rate=None, priority_band_code=['H', 'B', 'M', 'L', 'V', 'E', 'S'], priority_units=['M/S', 'M/S**2'], priority_instrument_code=['H', 'L'], time=None, timespan=None): nslcs = {} for nsl, bic_to_channels in self.get_channel_groups( time=time, timespan=timespan).items(): useful_bics = [] for bic, channels in bic_to_channels.items(): rate = channels[0].sample_rate.value if target_sample_rate is not None and \ rate < target_sample_rate*0.99999: continue if len(bic[0]) == 2: if bic[0][0] not in priority_band_code: continue if bic[0][1] not in priority_instrument_code: continue unit = bic[1] prio_unit = len(priority_units) try: prio_unit = priority_units.index(unit) except ValueError: pass prio_inst = len(priority_instrument_code) prio_band = len(priority_band_code) if len(channels[0].code) == 3: try: prio_inst = priority_instrument_code.index( channels[0].code[1]) except ValueError: pass try: prio_band = priority_band_code.index( channels[0].code[0]) except ValueError: pass if target_sample_rate is None: rate = -rate useful_bics.append((-len(channels), prio_band, rate, prio_unit, prio_inst, bic)) useful_bics.sort() for _, _, rate, _, _, bic in useful_bics: channels = sorted( bic_to_channels[bic], key=lambda channel: channel.code) if channels: for channel in channels: nslcs[nsl + (channel.code,)] = channel break return nslcs def get_pyrocko_response( self, nslc, time=None, timespan=None, fake_input_units=None, stages=(0, 1)): net, sta, loc, cha = nslc resps = [] for _, _, channel in self.iter_network_station_channels( net, sta, loc, cha, time=time, timespan=timespan): resp = channel.response if resp: resp.check_sample_rates(channel) resp.check_units() resps.append(resp.get_pyrocko_response( '.'.join(nslc), fake_input_units=fake_input_units, stages=stages).expect_one()) if not resps: raise NoResponseInformation('%s.%s.%s.%s' % nslc) elif len(resps) > 1: raise MultipleResponseInformation('%s.%s.%s.%s' % nslc) return resps[0] @property def n_code_list(self): return sorted(set(x.code for x in self.network_list)) @property def ns_code_list(self): nss = set() for network in self.network_list: for station in network.station_list: nss.add((network.code, station.code)) return sorted(nss) @property def nsl_code_list(self): nsls = set() for network in self.network_list: for station in network.station_list: for channel in station.channel_list: nsls.add( (network.code, station.code, channel.location_code)) return sorted(nsls) @property def nslc_code_list(self): nslcs = set() for network in self.network_list: for station in network.station_list: for channel in station.channel_list: nslcs.add( (network.code, station.code, channel.location_code, channel.code)) return sorted(nslcs) def summary(self): lst = [ 'number of n codes: %i' % len(self.n_code_list), 'number of ns codes: %i' % len(self.ns_code_list), 'number of nsl codes: %i' % len(self.nsl_code_list), 'number of nslc codes: %i' % len(self.nslc_code_list) ] return '\n'.join(lst) def summary_stages(self): data = [] for network, station, channel in self.iter_network_station_channels(): nslc = (network.code, station.code, channel.location_code, channel.code) stages = [] in_units = '?' out_units = '?' if channel.response: sens = channel.response.instrument_sensitivity if sens: in_units = sanitize_units( out_units = sanitize_units( for stage in channel.response.stage_list: stages.append(stage.summary()) data.append( (nslc, tts(channel.start_date), tts(channel.end_date), in_units, out_units, stages)) data.sort() lst = [] for nslc, stmin, stmax, in_units, out_units, stages in data: lst.append(' %s: %s - %s, %s -> %s' % ( '.'.join(nslc), stmin, stmax, in_units, out_units)) for stage in stages: lst.append(' %s' % stage) return '\n'.join(lst) def _check_overlaps(self): by_nslc = {} for network in self.network_list: for station in network.station_list: for channel in station.channel_list: nslc = (network.code, station.code, channel.location_code, channel.code) if nslc not in by_nslc: by_nslc[nslc] = [] by_nslc[nslc].append(channel) errors = [] for nslc, channels in by_nslc.items(): errors.extend(check_overlaps('Channel', nslc, channels)) return errors def check(self): errors = [] for meth in [self._check_overlaps]: errors.extend(meth()) if errors: raise Inconsistencies( 'Inconsistencies found in StationXML:\n ' + '\n '.join(errors))
def load_channel_table(stream): networks = {} stations = {} for line in stream: line = str(line.decode('ascii')) if line.startswith('#'): continue t = line.rstrip().split('|') if len(t) != 17: logger.warning('Invalid channel record: %s' % line) continue (net, sta, loc, cha, lat, lon, ele, dep, azi, dip, sens, scale, scale_freq, scale_units, sample_rate, start_date, end_date) = t try: scale = float(scale) except ValueError: scale = None try: scale_freq = float(scale_freq) except ValueError: scale_freq = None try: depth = float(dep) except ValueError: depth = 0.0 try: azi = float(azi) dip = float(dip) except ValueError: azi = None dip = None try: if net not in networks: network = Network(code=net) else: network = networks[net] if (net, sta) not in stations: station = Station( code=sta, latitude=lat, longitude=lon, elevation=ele) station.regularize() else: station = stations[net, sta] if scale: resp = Response( instrument_sensitivity=Sensitivity( value=scale, frequency=scale_freq, input_units=scale_units)) else: resp = None channel = Channel( code=cha, location_code=loc.strip(), latitude=lat, longitude=lon, elevation=ele, depth=depth, azimuth=azi, dip=dip, sensor=Equipment(description=sens), response=resp, sample_rate=sample_rate, start_date=start_date, end_date=end_date or None) channel.regularize() except ValidationError: raise InvalidRecord(line) if net not in networks: networks[net] = network if (net, sta) not in stations: stations[net, sta] = station network.station_list.append(station) station.channel_list.append(channel) return FDSNStationXML( source='created from table input', created=time.time(), network_list=sorted(networks.values(), key=lambda x: x.code)) def primitive_merge(sxs): networks = [] for sx in sxs: networks.extend(sx.network_list) return FDSNStationXML( source='merged from different sources', created=time.time(), network_list=copy.deepcopy( sorted(networks, key=lambda x: x.code))) def split_channels(sx): for nslc in sx.nslc_code_list: network_list = sx.network_list network_list_filtered = [ network for network in network_list if network.code == nslc[0]] for network in network_list_filtered: sx.network_list = [network] station_list = network.station_list station_list_filtered = [ station for station in station_list if station.code == nslc[1]] for station in station_list_filtered: network.station_list = [station] channel_list = station.channel_list station.channel_list = [ channel for channel in channel_list if (channel.location_code, channel.code) == nslc[2:4]] yield nslc, copy.deepcopy(sx) station.channel_list = channel_list network.station_list = station_list sx.network_list = network_list if __name__ == '__main__': from optparse import OptionParser util.setup_logging('', 'warning') usage = \ 'python -m check|stats|stages ' \ '<filename> [options]' description = '''Torture StationXML file.''' parser = OptionParser( usage=usage, description=description, formatter=util.BetterHelpFormatter()) (options, args) = parser.parse_args(sys.argv[1:]) if len(args) != 2: parser.print_help() sys.exit(1) action, path = args sx = load_xml(filename=path) if action == 'check': try: sx.check() except Inconsistencies as e: logger.error(e) sys.exit(1) elif action == 'stats': print(sx.summary()) elif action == 'stages': print(sx.summary_stages()) else: parser.print_help() sys.exit('unknown action: %s' % action)