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# http://pyrocko.org - GPLv3 

# 

# The Pyrocko Developers, 21st Century 

# ---|P------/S----------~Lg---------- 

from __future__ import absolute_import, division 

 

import numpy as num 

import math 

 

from . import meta 

from pyrocko.guts import Timestamp, Tuple, String, Float, Object,\ 

StringChoice, Int 

from pyrocko.guts_array import Array 

from pyrocko.model import gnss 

from pyrocko.orthodrome import distance_accurate50m_numpy 

from pyrocko.util import num_full_like 

 

d2r = num.pi / 180. 

 

 

class BadTarget(Exception): 

pass 

 

 

class Filter(Object): 

pass 

 

 

class OptimizationMethod(StringChoice): 

choices = ['enable', 'disable'] 

 

 

def component_orientation(source, target, component): 

''' 

Get component and azimuth for standard components R, T, Z, N, and E. 

 

:param source: :py:class:`pyrocko.gf.Location` object 

:param target: :py:class:`pyrocko.gf.Location` object 

:param component: string ``'R'``, ``'T'``, ``'Z'``, ``'N'`` or ``'E'`` 

''' 

 

_, bazi = source.azibazi_to(target) 

 

azi, dip = { 

'T': (bazi + 270., 0.), 

'R': (bazi + 180., 0.), 

'N': (0., 0.), 

'E': (90., 0.), 

'Z': (0., -90.)}[component] 

 

return azi, dip 

 

 

class Target(meta.Receiver): 

''' 

A seismogram computation request for a single component, including 

its post-processing parmeters. 

''' 

 

quantity = meta.QuantityType.T( 

optional=True, 

help='Measurement quantity type (e.g. "displacement", "pressure", ...)' 

'If not given, it is guessed from the channel code.' 

'Beware: If velocity is requested, the velocity is not directly' 

'retrieved. Instead a numpy.diff is run on the retrieved' 

'displacements, with lower accuracy. For high accuracy we' 

'recommend using the Pyrocko object DifferentiationResponse.') 

 

codes = Tuple.T( 

4, String.T(), default=('', 'STA', '', 'Z'), 

help='network, station, location and channel codes to be set on ' 

'the response trace.') 

 

elevation = Float.T( 

default=0.0, 

help='station surface elevation in [m]') 

 

store_id = meta.StringID.T( 

optional=True, 

help='ID of Green\'s function store to use for the computation. ' 

'If not given, the processor may use a system default.') 

 

sample_rate = Float.T( 

optional=True, 

help='sample rate to produce. ' 

'If not given the GF store\'s default sample rate is used. ' 

'GF store specific restrictions may apply.') 

 

interpolation = meta.InterpolationMethod.T( 

default='nearest_neighbor', 

help='Interpolation method between Green\'s functions. Supported are' 

' ``nearest_neighbor`` and ``multilinear``') 

 

optimization = OptimizationMethod.T( 

default='enable', 

optional=True, 

help='disable/enable optimizations in weight-delay-and-sum operation') 

 

tmin = Timestamp.T( 

optional=True, 

help='time of first sample to request in [s]. ' 

'If not given, it is determined from the Green\'s functions.') 

 

tmax = Timestamp.T( 

optional=True, 

help='time of last sample to request in [s]. ' 

'If not given, it is determined from the Green\'s functions.') 

 

azimuth = Float.T( 

optional=True, 

help='azimuth of sensor component in [deg], clockwise from north. ' 

'If not given, it is guessed from the channel code.') 

 

dip = Float.T( 

optional=True, 

help='dip of sensor component in [deg], ' 

'measured downward from horizontal. ' 

'If not given, it is guessed from the channel code.') 

 

filter = Filter.T( 

optional=True, 

help='frequency response filter.') 

 

def base_key(self): 

return (self.store_id, self.sample_rate, self.interpolation, 

self.optimization, 

self.tmin, self.tmax, 

self.elevation, self.depth, self.north_shift, self.east_shift, 

self.lat, self.lon) 

 

def effective_quantity(self): 

if self.quantity is not None: 

return self.quantity 

 

# guess from channel code 

cha = self.codes[-1].upper() 

if len(cha) == 3: 

# use most common SEED conventions here, however units have to be 

# guessed, because they are not uniquely defined by the conventions 

if cha[-2] in 'HL': # high gain, low gain seismometer 

return 'velocity' 

if cha[-2] == 'N': # accelerometer 

return 'acceleration' 

if cha[-2] == 'D': # hydrophone, barometer, ... 

return 'pressure' 

if cha[-2] == 'A': # tiltmeter 

return 'tilt' 

elif len(cha) == 2: 

if cha[-2] == 'U': 

return 'displacement' 

if cha[-2] == 'V': 

return 'velocity' 

elif len(cha) == 1: 

if cha in 'NEZ': 

return 'displacement' 

if cha == 'P': 

return 'pressure' 

 

raise BadTarget('cannot guess measurement quantity type from channel ' 

'code "%s"' % cha) 

 

def receiver(self, store): 

rec = meta.Receiver(**dict(meta.Receiver.T.inamevals(self))) 

return rec 

 

def component_code(self): 

cha = self.codes[-1].upper() 

if cha: 

return cha[-1] 

else: 

return ' ' 

 

def effective_azimuth(self): 

if self.azimuth is not None: 

return self.azimuth 

elif self.component_code() in 'NEZ': 

return {'N': 0., 'E': 90., 'Z': 0.}[self.component_code()] 

 

raise BadTarget('cannot determine sensor component azimuth for ' 

'%s.%s.%s.%s' % self.codes) 

 

def effective_dip(self): 

if self.dip is not None: 

return self.dip 

elif self.component_code() in 'NEZ': 

return {'N': 0., 'E': 0., 'Z': -90.}[self.component_code()] 

 

raise BadTarget('cannot determine sensor component dip') 

 

def get_sin_cos_factors(self): 

azi = self.effective_azimuth() 

dip = self.effective_dip() 

sa = math.sin(azi*d2r) 

ca = math.cos(azi*d2r) 

sd = math.sin(dip*d2r) 

cd = math.cos(dip*d2r) 

return sa, ca, sd, cd 

 

def get_factor(self): 

return 1.0 

 

def post_process(self, engine, source, tr): 

return meta.Result(trace=tr) 

 

 

class StaticTarget(meta.MultiLocation): 

''' 

A computation request for a spatial multi-location target of 

static/geodetic quantities. 

''' 

quantity = meta.QuantityType.T( 

optional=True, 

default='displacement', 

help='Measurement quantity type, for now only `displacement` is' 

'supported.') 

 

interpolation = meta.InterpolationMethod.T( 

default='nearest_neighbor', 

help='Interpolation method between Green\'s functions. Supported are' 

' ``nearest_neighbor`` and ``multilinear``') 

 

tsnapshot = Timestamp.T( 

optional=True, 

help='time of the desired snapshot in [s], ' 

'If not given, the first sample is taken. If the desired sample' 

' exceeds the length of the Green\'s function store,' 

' the last sample is taken.') 

 

store_id = meta.StringID.T( 

optional=True, 

help='ID of Green\'s function store to use for the computation. ' 

'If not given, the processor may use a system default.') 

 

def base_key(self): 

return (self.store_id, 

self.coords5.shape, 

self.quantity, 

self.tsnapshot, 

self.interpolation) 

 

@property 

def ntargets(self): 

''' Number of targets held by instance. ''' 

return self.ncoords 

 

def get_targets(self): 

''' Discretizes the multilocation target into a list of 

:class:`Target:` 

 

:returns: :class:`Target` 

:rtype: list 

''' 

targets = [] 

for i in range(self.ntargets): 

targets.append( 

Target( 

lat=float(self.coords5[i, 0]), 

lon=float(self.coords5[i, 1]), 

north_shift=float(self.coords5[i, 2]), 

east_shift=float(self.coords5[i, 3]), 

elevation=float(self.coords5[i, 4]))) 

return targets 

 

def distance_to(self, source): 

src_lats = num_full_like(self.lats, fill_value=source.lat) 

src_lons = num_full_like(self.lons, fill_value=source.lon) 

 

target_coords = self.get_latlon() 

target_lats = target_coords[:, 0] 

target_lons = target_coords[:, 1] 

return distance_accurate50m_numpy( 

src_lats, src_lons, target_lats, target_lons) 

 

def post_process(self, engine, source, statics): 

return meta.StaticResult(result=statics) 

 

 

class SatelliteTarget(StaticTarget): 

''' 

A computation request for a spatial multi-location target of 

static/geodetic quantities measured from a satellite instrument. 

The line of sight angles are provided and projecting 

post-processing is applied. 

''' 

theta = Array.T( 

shape=(None,), 

dtype=num.float, 

serialize_as='base64-compat', 

help='Horizontal angle towards satellite\'s line of sight in radians.' 

'\n\n .. important::\n\n' 

' :math:`0` is **east** and' 

' :math:`\\frac{\\pi}{2}` is **north**.\n\n') 

 

phi = Array.T( 

shape=(None,), 

dtype=num.float, 

serialize_as='base64-compat', 

help='Theta is look vector elevation angle towards satellite from' 

' horizon in radians. Matrix of theta towards satellite\'s' 

' line of sight.' 

'\n\n .. important::\n\n' 

' :math:`-\\frac{\\pi}{2}` is **down** and' 

' :math:`\\frac{\\pi}{2}` is **up**.\n\n') 

 

def __init__(self, *args, **kwargs): 

super(SatelliteTarget, self).__init__(*args, **kwargs) 

self._los_factors = None 

 

def get_los_factors(self): 

if (self.theta.size != self.phi.size != self.lats.size): 

raise AttributeError('LOS angles inconsistent with provided' 

' coordinate shape.') 

if self._los_factors is None: 

self._los_factors = num.empty((self.theta.shape[0], 3)) 

self._los_factors[:, 0] = num.sin(self.theta) 

self._los_factors[:, 1] = num.cos(self.theta) * num.cos(self.phi) 

self._los_factors[:, 2] = num.cos(self.theta) * num.sin(self.phi) 

return self._los_factors 

 

def post_process(self, engine, source, statics): 

return meta.SatelliteResult( 

result=statics, 

theta=self.theta, phi=self.phi) 

 

 

class KiteSceneTarget(SatelliteTarget): 

 

shape = Tuple.T( 

2, Int.T(), 

optional=False, 

help='Shape of the displacement vectors.') 

 

def __init__(self, scene, **kwargs): 

size = scene.displacement.size 

 

if scene.frame.spacing == 'meter': 

lats = num.full(size, scene.frame.llLat) 

lons = num.full(size, scene.frame.llLon) 

north_shifts = scene.frame.gridN.data.flatten() 

east_shifts = scene.frame.gridE.data.flatten() 

 

elif scene.frame.spacing == 'degree': 

lats = scene.frame.gridN.data.flatten() + scene.frame.llLat 

lons = scene.frame.gridE.data.flatten() + scene.frame.llLon 

north_shifts = num.zeros(size) 

east_shifts = num.zeros(size) 

 

self.scene = scene 

 

super(KiteSceneTarget, self).__init__( 

lats=lats, lons=lons, 

north_shifts=north_shifts, east_shifts=east_shifts, 

theta=scene.theta.flatten(), 

phi=scene.phi.flatten(), 

shape=scene.shape, **kwargs) 

 

def post_process(self, engine, source, statics): 

res = meta.KiteSceneResult( 

result=statics, 

theta=self.theta, phi=self.phi, 

shape=self.scene.shape) 

res.config = self.scene.config 

return res 

 

 

class GNSSCampaignTarget(StaticTarget): 

 

def post_process(self, engine, source, statics): 

campaign = gnss.GNSSCampaign() 

 

for ista in range(self.ntargets): 

north = gnss.GNSSComponent( 

shift=float(statics['displacement.n'][ista])) 

east = gnss.GNSSComponent( 

shift=float(statics['displacement.e'][ista])) 

up = gnss.GNSSComponent( 

shift=-float(statics['displacement.d'][ista])) 

 

coords = self.coords5 

station = gnss.GNSSStation( 

lat=float(coords[ista, 0]), 

lon=float(coords[ista, 1]), 

east_shift=float(coords[ista, 2]), 

north_shift=float(coords[ista, 3]), 

elevation=float(coords[ista, 4]), 

north=north, 

east=east, 

up=up) 

 

campaign.add_station(station) 

 

return meta.GNSSCampaignResult(result=statics, campaign=campaign)