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# http://pyrocko.org - GPLv3

# The Pyrocko Developers, 21st Century

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

from __future__ import absolute_import, division

import math

import re

import fnmatch

import logging

import numpy as num

from scipy.interpolate import interp1d

from pyrocko.guts import (Object, SObject, String, StringChoice,

StringPattern, Unicode, Float, Bool, Int, TBase,

List, ValidationError, Timestamp, Tuple, Dict)

from pyrocko.guts import dump, load # noqa

from pyrocko.guts_array import literal, Array

from pyrocko.model import Location, gnss

from pyrocko import cake, orthodrome, spit, moment_tensor, trace

from pyrocko.util import num_full

from .error import StoreError

try:

new_str = unicode

except NameError:

new_str = str

guts_prefix = 'pf'

d2r = math.pi / 180.

r2d = 1.0 / d2r

km = 1000.

vicinity_eps = 1e-5

logger = logging.getLogger('pyrocko.gf.meta')

def fmt_choices(cls):

return 'choices: %s' % ', '.join(

"``'%s'``" % choice for choice in cls.choices)

class InterpolationMethod(StringChoice):

choices = ['nearest_neighbor', 'multilinear']

class SeismosizerTrace(Object):

codes = Tuple.T(

4, String.T(),

default=('', 'STA', '', 'Z'),

help='network, station, location and channel codes')

data = Array.T(

shape=(None,),

dtype=num.float32,

serialize_as='base64',

serialize_dtype=num.dtype('<f4'),

help='numpy array with data samples')

deltat = Float.T(

default=1.0,

help='sampling interval [s]')

tmin = Timestamp.T(

default=0.0,

help='time of first sample as a system timestamp [s]')

def pyrocko_trace(self):

c = self.codes

return trace.Trace(c[0], c[1], c[2], c[3],

ydata=self.data,

deltat=self.deltat,

tmin=self.tmin)

@classmethod

def from_pyrocko_trace(cls, tr, **kwargs):

d = dict(

codes=tr.nslc_id,

tmin=tr.tmin,

deltat=tr.deltat,

data=num.asarray(tr.get_ydata(), dtype=num.float32))

d.update(kwargs)

return cls(**d)

class SeismosizerResult(Object):

n_records_stacked = Int.T(optional=True, default=1)

t_stack = Float.T(optional=True, default=0.)

class Result(SeismosizerResult):

trace = SeismosizerTrace.T(optional=True)

n_shared_stacking = Int.T(optional=True, default=1)

t_optimize = Float.T(optional=True, default=0.)

class StaticResult(SeismosizerResult):

result = Dict.T(

String.T(),

Array.T(shape=(None,), dtype=num.float, serialize_as='base64'))

class GNSSCampaignResult(StaticResult):

campaign = gnss.GNSSCampaign.T(

optional=True)

class SatelliteResult(StaticResult):

theta = Array.T(

optional=True,

shape=(None,), dtype=num.float, serialize_as='base64')

phi = Array.T(

optional=True,

shape=(None,), dtype=num.float, serialize_as='base64')

class KiteSceneResult(SatelliteResult):

shape = Tuple.T()

def get_scene(self, component='displacement.los'):

try:

from kite import Scene

except ImportError:

raise ImportError('Kite not installed')

def reshape(arr):

return arr.reshape(self.shape)

displacement = self.result[component]

displacement, theta, phi = map(

reshape, (displacement, self.theta, self.phi))

sc = Scene(

displacement=displacement,

theta=theta, phi=phi,

config=self.config)

return sc

class ComponentSchemeDescription(Object):

name = String.T()

source_terms = List.T(String.T())

ncomponents = Int.T()

default_stored_quantity = String.T(optional=True)

provided_components = List.T(String.T())

component_scheme_descriptions = [

ComponentSchemeDescription(

name='elastic2',

source_terms=['m0'],

ncomponents=2,

default_stored_quantity='displacement',

provided_components=[

'n', 'e', 'd']),

ComponentSchemeDescription(

name='elastic8',

source_terms=['mnn', 'mee', 'mdd', 'mne', 'mnd', 'med'],

ncomponents=8,

default_stored_quantity='displacement',

provided_components=[

'n', 'e', 'd']),

ComponentSchemeDescription(

name='elastic10',

source_terms=['mnn', 'mee', 'mdd', 'mne', 'mnd', 'med'],

ncomponents=10,

default_stored_quantity='displacement',

provided_components=[

'n', 'e', 'd']),

ComponentSchemeDescription(

name='elastic18',

source_terms=['mnn', 'mee', 'mdd', 'mne', 'mnd', 'med'],

ncomponents=18,

default_stored_quantity='displacement',

provided_components=[

'n', 'e', 'd']),

ComponentSchemeDescription(

name='elastic5',

source_terms=['fn', 'fe', 'fd'],

ncomponents=5,

default_stored_quantity='displacement',

provided_components=[

'n', 'e', 'd']),

ComponentSchemeDescription(

name='poroelastic10',

source_terms=['pore_pressure'],

ncomponents=10,

default_stored_quantity=None,

provided_components=[

'displacement.n', 'displacement.e', 'displacement.d',

'vertical_tilt.n', 'vertical_tilt.e',

'pore_pressure',

'darcy_velocity.n', 'darcy_velocity.e', 'darcy_velocity.d'])]

# new names?

# 'mt_to_displacement_1d'

# 'mt_to_displacement_1d_ff_only'

# 'mt_to_gravity_1d'

# 'mt_to_stress_1d'

# 'explosion_to_displacement_1d'

# 'sf_to_displacement_1d'

# 'mt_to_displacement_3d'

# 'mt_to_gravity_3d'

# 'mt_to_stress_3d'

# 'pore_pressure_to_displacement_1d'

# 'pore_pressure_to_vertical_tilt_1d'

# 'pore_pressure_to_pore_pressure_1d'

# 'pore_pressure_to_darcy_velocity_1d'

component_schemes = [c.name for c in component_scheme_descriptions]

component_scheme_to_description = dict(

(c.name, c) for c in component_scheme_descriptions)

class ComponentScheme(StringChoice):

'''

Different Green's Function component schemes are available:

================= =========================================================

Name Description

================= =========================================================

``elastic10`` Elastodynamic for

:py:class:`~pyrocko.gf.meta.ConfigTypeA` and

:py:class:`~pyrocko.gf.meta.ConfigTypeB` stores, MT

sources only

``elastic8`` Elastodynamic for far-field only

:py:class:`~pyrocko.gf.meta.ConfigTypeA` and

:py:class:`~pyrocko.gf.meta.ConfigTypeB` stores,

MT sources only

``elastic2`` Elastodynamic for

:py:class:`~pyrocko.gf.meta.ConfigTypeA` and

:py:class:`~pyrocko.gf.meta.ConfigTypeB` stores, purely

isotropic sources only

``elastic5`` Elastodynamic for

:py:class:`~pyrocko.gf.meta.ConfigTypeA`

and :py:class:`~pyrocko.gf.meta.ConfigTypeB` stores, SF

sources only

``elastic18`` Elastodynamic for

:py:class:`~pyrocko.gf.meta.ConfigTypeC` stores, MT

sources only

``poroelastic10`` Poroelastic for :py:class:`~pyrocko.gf.meta.ConfigTypeA`

and :py:class:`~pyrocko.gf.meta.ConfigTypeB` stores

================= =========================================================

'''

choices = component_schemes

class Earthmodel1D(Object):

dummy_for = cake.LayeredModel

class __T(TBase):

def regularize_extra(self, val):

if isinstance(val, str):

val = cake.LayeredModel.from_scanlines(

cake.read_nd_model_str(val))

return val

def to_save(self, val):

return literal(cake.write_nd_model_str(val))

class StringID(StringPattern):

pattern = r'^[A-Za-z][A-Za-z0-9._]{0,64}$'

class ScopeType(StringChoice):

choices = [

'global',

'regional',

'local',

]

class WaveType(StringChoice):

choices = [

'full waveform',

'bodywave',

'P wave',

'S wave',

'surface wave',

]

class NearfieldTermsType(StringChoice):

choices = [

'complete',

'incomplete',

'missing',

]

class QuantityType(StringChoice):

choices = [

'displacement',

'rotation',

'velocity',

'acceleration',

'pressure',

'tilt',

'pore_pressure',

'darcy_velocity',

'vertical_tilt']

class Reference(Object):

id = StringID.T()

type = String.T()

title = Unicode.T()

journal = Unicode.T(optional=True)

volume = Unicode.T(optional=True)

number = Unicode.T(optional=True)

pages = Unicode.T(optional=True)

year = String.T()

note = Unicode.T(optional=True)

issn = String.T(optional=True)

doi = String.T(optional=True)

url = String.T(optional=True)

eprint = String.T(optional=True)

authors = List.T(Unicode.T())

publisher = Unicode.T(optional=True)

keywords = Unicode.T(optional=True)

note = Unicode.T(optional=True)

abstract = Unicode.T(optional=True)

@classmethod

def from_bibtex(cls, filename=None, stream=None):

from pybtex.database.input import bibtex

parser = bibtex.Parser()

if filename is not None:

bib_data = parser.parse_file(filename)

elif stream is not None:

bib_data = parser.parse_stream(stream)

references = []

for id_, entry in bib_data.entries.items():

d = {}

avail = entry.fields.keys()

for prop in cls.T.properties:

if prop.name == 'authors' or prop.name not in avail:

continue

d[prop.name] = entry.fields[prop.name]

if 'author' in entry.persons:

d['authors'] = []

for person in entry.persons['author']:

d['authors'].append(new_str(person))

c = Reference(id=id_, type=entry.type, **d)

references.append(c)

return references

_fpat = r'[+-]?(\d+(\.\d*)?|\.\d+)([eE][-+]?\d+)?'

_spat = StringID.pattern[1:-1]

_cake_pat = cake.PhaseDef.allowed_characters_pattern

_iaspei_pat = cake.PhaseDef.allowed_characters_pattern_classic

_ppat = r'(' \

r'cake:' + _cake_pat + \

r'|iaspei:' + _iaspei_pat + \

r'|vel_surface:' + _fpat + \

r'|vel:' + _fpat + \

r'|stored:' + _spat + \

r')'

timing_regex_old = re.compile(

r'^((first|last)?$(' + _spat + r'(\|' + _spat + r')*)$|(' +

_spat + r'))?(' + _fpat + ')?$')

timing_regex = re.compile(

r'^((first|last)?\{(' + _ppat + r'(\|' + _ppat + r')*)\}|(' +

_ppat + r'))?(' + _fpat + '(S|%)?)?$')

class PhaseSelect(StringChoice):

choices = ['', 'first', 'last']

class InvalidTimingSpecification(ValidationError):

pass

class Timing(SObject):

'''

Definition of a time instant relative to one or more named phase arrivals

Instances of this class can be used e.g. in cutting and tapering

operations. They can hold an absolute time or an offset to a named phase

arrival or group of such arrivals.

Timings can be instantiated from a simple string defintion i.e. with

``Timing(str)`` where ``str`` is something like

``'SELECT{PHASE_DEFS}[+-]OFFSET[S|%]'`` where ``'SELECT'`` is ``'first'``,

``'last'`` or empty, ``'PHASE_DEFS'`` is a ``'|'``-separated list of phase

definitions, and ``'OFFSET'`` is the time offset in seconds. If a ``'%'``

is appended, it is interpreted as percent. If the an ``'S'`` is appended

to ``'OFFSET'``, it is interpreted as a surface slowness in [s/km].

Phase definitions can be specified in either of the following ways:

* ``'stored:PHASE_ID'`` - retrieves value from stored travel time table

* ``'cake:CAKE_PHASE_DEF'`` - evaluates first arrival of phase with cake

(see :py:class:`pyrocko.cake.PhaseDef`)

* ``'vel_surface:VELOCITY'`` - arrival according to surface distance /

velocity [km/s]

* ``'vel:VELOCITY'`` - arrival according to 3D-distance / velocity [km/s]

**Examples:**

* ``'100'`` : absolute time; 100 s

* ``'{stored:P}-100'`` : 100 s before arrival of P phase according to

stored travel time table named ``'P'``

* ``'{stored:P}-5.1S'`` : 10% before arrival of P phase according to

stored travel time table named ``'P'``

* ``'{stored:P}-10%'`` : 10% before arrival of P phase according to

stored travel time table named ``'P'``

* ``'{stored:A|stored:B}'`` : time instant of phase arrival A, or B if A is

undefined for a given geometry

* ``'first{stored:A|stored:B}'`` : as above, but the earlier arrival of A

and B is chosen, if both phases are defined for a given geometry

* ``'last{stored:A|stored:B}'`` : as above but the later arrival is chosen

* ``'first{stored:A|stored:B|stored:C}-100'`` : 100 s before first out of

arrivals A, B, and C

'''

def __init__(self, s=None, **kwargs):

if s is not None:

offset_is = None

s = re.sub(r'\s+', '', s)

try:

offset = float(s.rstrip('S'))

if s.endswith('S'):

offset_is = 'slowness'

phase_defs = []

select = ''

except ValueError:

matched = False

m = timing_regex.match(s)

if m:

if m.group(3):

phase_defs = m.group(3).split('|')

elif m.group(19):

phase_defs = [m.group(19)]

else:

phase_defs = []

select = m.group(2) or ''

offset = 0.0

soff = m.group(27)

if soff:

offset = float(soff.rstrip('S%'))

if soff.endswith('S'):

offset_is = 'slowness'

elif soff.endswith('%'):

offset_is = 'percent'

matched = True

else:

m = timing_regex_old.match(s)

if m:

if m.group(3):

phase_defs = m.group(3).split('|')

elif m.group(5):

phase_defs = [m.group(5)]

else:

phase_defs = []

select = m.group(2) or ''

offset = 0.0

if m.group(6):

offset = float(m.group(6))

phase_defs = [

'stored:' + phase_def for phase_def in phase_defs]

matched = True

if not matched:

raise InvalidTimingSpecification(s)

kwargs = dict(

phase_defs=phase_defs,

select=select,

offset=offset,

offset_is=offset_is)

SObject.__init__(self, **kwargs)

def __str__(self):

s = []

if self.phase_defs:

sphases = '|'.join(self.phase_defs)

# if len(self.phase_defs) > 1 or self.select:

sphases = '{%s}' % sphases

if self.select:

sphases = self.select + sphases

s.append(sphases)

if self.offset != 0.0 or not self.phase_defs:

s.append('%+g' % self.offset)

if self.offset_is == 'slowness':

s.append('S')

elif self.offset_is == 'percent':

s.append('%')

return ''.join(s)

def evaluate(self, get_phase, args):

try:

if self.offset_is == 'slowness' and self.offset != 0.0:

phase_offset = get_phase(

'vel_surface:%g' % (1.0/self.offset))

offset = phase_offset(args)

else:

offset = self.offset

if self.phase_defs:

phases = [

get_phase(phase_def) for phase_def in self.phase_defs]

times = [phase(args) for phase in phases]

if self.offset_is == 'percent':

times = [t*(1.+offset/100.)

for t in times if t is not None]

else:

times = [t+offset for t in times if t is not None]

if not times:

return None

elif self.select == 'first':

return min(times)

elif self.select == 'last':

return max(times)

else:

return times[0]

else:

return offset

except spit.OutOfBounds:

raise OutOfBounds(args)

phase_defs = List.T(String.T())

offset = Float.T(default=0.0)

offset_is = String.T(optional=True)

select = PhaseSelect.T(

default='',

help=('Can be either ``\'%s\'``, ``\'%s\'``, or ``\'%s\'``. ' %

tuple(PhaseSelect.choices)))

def mkdefs(s):

defs = []

for x in s.split(','):

try:

defs.append(float(x))

except ValueError:

if x.startswith('!'):

defs.extend(cake.PhaseDef.classic(x[1:]))

else:

defs.append(cake.PhaseDef(x))

return defs

class TPDef(Object):

'''

Maps an arrival phase identifier to an arrival phase definition.

'''

id = StringID.T(

help='name used to identify the phase')

definition = String.T(

help='definition of the phase in either cake syntax as defined in '

':py:class:`pyrocko.cake.PhaseDef`, or, if prepended with an '

'``!``, as a *classic phase name*, or, if it is a simple '

'number, as a constant horizontal velocity.')

@property

def phases(self):

return [x for x in mkdefs(self.definition)

if isinstance(x, cake.PhaseDef)]

@property

def horizontal_velocities(self):

return [x for x in mkdefs(self.definition) if isinstance(x, float)]

class OutOfBounds(Exception):

def __init__(self, values=None, reason=None):

Exception.__init__(self)

self.values = values

self.reason = reason

self.context = None

def __str__(self):

scontext = ''

if self.context:

scontext = '\n%s' % str(self.context)

if self.reason:

scontext += '\n%s' % self.reason

if self.values:

return 'out of bounds: (%s)%s' % (

','.join('%g' % x for x in self.values), scontext)

else:

return 'out of bounds%s' % scontext

class MultiLocation(Object):

lats = Array.T(

optional=True, shape=(None,), dtype=num.float,

help='Latitudes of targets.')

lons = Array.T(

optional=True, shape=(None,), dtype=num.float,

help='Longitude of targets.')

north_shifts = Array.T(

optional=True, shape=(None,), dtype=num.float,

help='North shifts of targets.')

east_shifts = Array.T(

optional=True, shape=(None,), dtype=num.float,

help='East shifts of targets.')

elevation = Array.T(

optional=True, shape=(None,), dtype=num.float,

help='Elevations of targets.')

def __init__(self, *args, **kwargs):

self._coords5 = None

Object.__init__(self, *args, **kwargs)

@property

def coords5(self):

if self._coords5 is not None:

return self._coords5

props = [self.lats, self.lons, self.north_shifts, self.east_shifts,

self.elevation]

sizes = [p.size for p in props if p is not None]

if not sizes:

raise AttributeError('Empty StaticTarget')

if num.unique(sizes).size != 1:

raise AttributeError('Inconsistent coordinate sizes.')

self._coords5 = num.zeros((sizes[0], 5))

for idx, p in enumerate(props):

if p is not None:

self._coords5[:, idx] = p.flatten()

return self._coords5

@property

def ncoords(self):

if self.coords5.shape[0] is None:

return 0

return int(self.coords5.shape[0])

def get_latlon(self):

''' Get all coordinates as lat lon

:returns: Coordinates in Latitude, Longitude

:rtype: :class:`numpy.ndarray`, (N, 2)

'''

latlons = num.empty((self.ncoords, 2))

for i in range(self.ncoords):

latlons[i, :] = orthodrome.ne_to_latlon(*self.coords5[i, :4])

return latlons

def get_corner_coords(self):

'''Returns the corner coordinates of the multi location object

:returns: In LatLon: lower left, upper left, upper right, lower right

:rtype: tuple

'''

latlon = self.get_latlon()

ll = (latlon[:, 0].min(), latlon[:, 1].min())

ur = (latlon[:, 0].max(), latlon[:, 1].max())

return (ll, (ll[0], ur[1]), ur, (ur[0], ll[1]))

class Receiver(Location):

codes = Tuple.T(

3, String.T(),

optional=True,

help='network, station, and location codes')

def pyrocko_station(self):

from pyrocko import model

lat, lon = self.effective_latlon

return model.Station(

network=self.codes[0],

station=self.codes[1],

location=self.codes[2],

lat=lat,

lon=lon,

depth=self.depth)

def g(x, d):

if x is None:

return d

else:

return x

class UnavailableScheme(Exception):

pass

class InvalidNComponents(Exception):

pass

class DiscretizedSource(Object):

'''Base class for discretized sources.

To compute synthetic seismograms, the parameterized source models (see of

:py:class:`~pyrocko.gf.seismosizer.Source` derived classes) are first

discretized into a number of point sources. These spacio-temporal point

source distributions are represented by subclasses of the

:py:class:`DiscretizedSource`. For elastodynamic problems there is the

:py:class:`DiscretizedMTSource` for moment tensor point source

distributions and the :py:class:`DiscretizedExplosionSource` for pure

explosion/implosion type source distributions. The geometry calculations

are implemented in the base class. How Green's function components have to

be weighted and sumed is defined in the derived classes.

Like in the :py:class:`Location` class, the positions of the point sources

contained in the discretized source are defined by a common reference point

(:py:attr:`lat`, :py:attr:`lon`) and cartesian offsets to this

(:py:attr:`north_shifts`, :py:attr:`east_shifts`, :py:attr:`depths`).

Alternatively latitude and longitude of each contained point source can be

specified directly (:py:attr:`lats`, :py:attr:`lons`).

'''

times = Array.T(shape=(None,), dtype=num.float)

lats = Array.T(shape=(None,), dtype=num.float, optional=True)

lons = Array.T(shape=(None,), dtype=num.float, optional=True)

lat = Float.T(optional=True)

lon = Float.T(optional=True)

north_shifts = Array.T(shape=(None,), dtype=num.float, optional=True)

east_shifts = Array.T(shape=(None,), dtype=num.float, optional=True)

depths = Array.T(shape=(None,), dtype=num.float)

@classmethod

def check_scheme(cls, scheme):

'''

Check if given GF component scheme is supported by the class.

Raises :py:class:`UnavailableScheme` if the given scheme is not

supported by this discretized source class.

'''

if scheme not in cls.provided_schemes:

raise UnavailableScheme(

'source type "%s" does not support GF component scheme "%s"' %

(cls.__name__, scheme))

def __init__(self, **kwargs):

Object.__init__(self, **kwargs)

self._latlons = None

def __setattr__(self, name, value):

if name in ('lat', 'lon', 'north_shifts', 'east_shifts',

'lats', 'lons'):

self.__dict__['_latlons'] = None

Object.__setattr__(self, name, value)

def get_source_terms(self, scheme):

raise NotImplementedError()

def make_weights(self, receiver, scheme):

raise NotImplementedError()

@property

def effective_latlons(self):

'''

Property holding the offest-corrected lats and lons of all points.

'''

if self._latlons is None:

if self.lats is not None and self.lons is not None:

if (self.north_shifts is not None and

self.east_shifts is not None):

self._latlons = orthodrome.ne_to_latlon(

self.lats, self.lons,

self.north_shifts, self.east_shifts)

else:

self._latlons = self.lats, self.lons

else:

lat = g(self.lat, 0.0)

lon = g(self.lon, 0.0)

self._latlons = orthodrome.ne_to_latlon(

lat, lon, self.north_shifts, self.east_shifts)

return self._latlons

@property

def effective_north_shifts(self):

if self.north_shifts is not None:

return self.north_shifts

else:

return num.zeros(self.times.size)

@property

def effective_east_shifts(self):

if self.east_shifts is not None:

return self.east_shifts

else:

return num.zeros(self.times.size)

def same_origin(self, receiver):

'''

Check if receiver has same reference point.

'''

return (g(self.lat, 0.0) == receiver.lat and

g(self.lon, 0.0) == receiver.lon and

self.lats is None and self.lons is None)

def azibazis_to(self, receiver):

'''

Compute azimuths and backaziumuths to/from receiver, for all contained

points.

'''

if self.same_origin(receiver):

azis = r2d * num.arctan2(receiver.east_shift - self.east_shifts,

receiver.north_shift - self.north_shifts)

bazis = azis + 180.

else:

slats, slons = self.effective_latlons

rlat, rlon = receiver.effective_latlon

azis = orthodrome.azimuth_numpy(slats, slons, rlat, rlon)

bazis = orthodrome.azimuth_numpy(rlat, rlon, slats, slons)

return azis, bazis

def distances_to(self, receiver):

'''

Compute distances to receiver for all contained points.

'''

if self.same_origin(receiver):

return num.sqrt((self.north_shifts - receiver.north_shift)**2 +

(self.east_shifts - receiver.east_shift)**2)

else:

slats, slons = self.effective_latlons

rlat, rlon = receiver.effective_latlon

return orthodrome.distance_accurate50m_numpy(slats, slons,

rlat, rlon)

def element_coords(self, i):

if self.lats is not None and self.lons is not None:

lat = float(self.lats[i])

lon = float(self.lons[i])

else:

lat = self.lat

lon = self.lon

if self.north_shifts is not None and self.east_shifts is not None:

north_shift = float(self.north_shifts[i])

east_shift = float(self.east_shifts[i])

else:

north_shift = east_shift = 0.0

return lat, lon, north_shift, east_shift

def coords5(self):

xs = num.zeros((self.nelements, 5))

if self.lats is not None and self.lons is not None:

xs[:, 0] = self.lats

xs[:, 1] = self.lons

else:

xs[:, 0] = g(self.lat, 0.0)

xs[:, 1] = g(self.lon, 0.0)

if self.north_shifts is not None and self.east_shifts is not None:

xs[:, 2] = self.north_shifts

xs[:, 3] = self.east_shifts

xs[:, 4] = self.depths

return xs

@property

def nelements(self):

return self.times.size

@classmethod

def combine(cls, sources, **kwargs):

'''

Combine several discretized source models.

Concatenenates all point sources in the given discretized ``sources``.

Care must be taken when using this function that the external amplitude

factors and reference times of the parameterized (undiscretized)

sources match or are accounted for.

'''

first = sources[0]

if not all(type(s) == type(first) for s in sources):

raise Exception('DiscretizedSource.combine must be called with '

'sources of same type.')

latlons = []

for s in sources:

latlons.append(s.effective_latlons)

lats, lons = num.hstack(latlons)

if all((s.lats is None and s.lons is None) for s in sources):

rlats = num.array([s.lat for s in sources], dtype=num.float)

rlons = num.array([s.lon for s in sources], dtype=num.float)

same_ref = num.all(

rlats == rlats[0]) and num.all(rlons == rlons[0])

else:

same_ref = False

cat = num.concatenate

times = cat([s.times for s in sources])

depths = cat([s.depths for s in sources])

if same_ref:

lat = first.lat

lon = first.lon

north_shifts = cat([s.effective_north_shifts for s in sources])

east_shifts = cat([s.effective_east_shifts for s in sources])

lats = None

lons = None

else:

lat = None

lon = None

north_shifts = None

east_shifts = None

return cls(

times=times, lat=lat, lon=lon, lats=lats, lons=lons,

north_shifts=north_shifts, east_shifts=east_shifts,

depths=depths, **kwargs)

def centroid_position(self):

moments = self.moments()

norm = num.sum(moments)

if norm != 0.0:

w = moments / num.sum(moments)

else:

w = num.ones(moments.size)

if self.lats is not None and self.lons is not None:

lats, lons = self.effective_latlons

rlat, rlon = num.mean(lats), num.mean(lons)

n, e = orthodrome.latlon_to_ne_numpy(rlat, rlon, lats, lons)

else:

rlat, rlon = g(self.lat, 0.0), g(self.lon, 0.0)

n, e = self.north_shifts, self.east_shifts

cn = num.sum(n*w)

ce = num.sum(e*w)

clat, clon = orthodrome.ne_to_latlon(rlat, rlon, cn, ce)

if self.lats is not None and self.lons is not None:

lat = clat

lon = clon

north_shift = 0.

east_shift = 0.

else:

lat = g(self.lat, 0.0)

lon = g(self.lon, 0.0)

north_shift = cn

east_shift = ce

depth = num.sum(self.depths*w)

time = num.sum(self.times*w)

return tuple(float(x) for x in

(time, lat, lon, north_shift, east_shift, depth))

class DiscretizedExplosionSource(DiscretizedSource):

m0s = Array.T(shape=(None,), dtype=num.float)

provided_schemes = (

'elastic2',

'elastic8',

'elastic10',

)

def get_source_terms(self, scheme):

self.check_scheme(scheme)

if scheme == 'elastic2':

return self.m0s[:, num.newaxis].copy()

elif scheme in ('elastic8', 'elastic10'):

m6s = num.zeros((self.m0s.size, 6))

m6s[:, 0:3] = self.m0s[:, num.newaxis]

return m6s

else:

assert False

def make_weights(self, receiver, scheme):

self.check_scheme(scheme)

azis, bazis = self.azibazis_to(receiver)

sb = num.sin(bazis*d2r-num.pi)

cb = num.cos(bazis*d2r-num.pi)

m0s = self.m0s

n = azis.size

cat = num.concatenate

rep = num.repeat

if scheme == 'elastic2':

w_n = cb*m0s

g_n = filledi(0, n)

w_e = sb*m0s

g_e = filledi(0, n)

w_d = m0s

g_d = filledi(1, n)

elif scheme == 'elastic8':

w_n = cat((cb*m0s, cb*m0s))

g_n = rep((0, 2), n)

w_e = cat((sb*m0s, sb*m0s))

g_e = rep((0, 2), n)

w_d = cat((m0s, m0s))

g_d = rep((5, 7), n)

elif scheme == 'elastic10':

w_n = cat((cb*m0s, cb*m0s, cb*m0s))

g_n = rep((0, 2, 8), n)

w_e = cat((sb*m0s, sb*m0s, sb*m0s))

g_e = rep((0, 2, 8), n)

w_d = cat((m0s, m0s, m0s))

g_d = rep((5, 7, 9), n)

else:

assert False

return (

('displacement.n', w_n, g_n),

('displacement.e', w_e, g_e),

('displacement.d', w_d, g_d),

)

def split(self):

from pyrocko.gf.seismosizer import ExplosionSource

sources = []

for i in range(self.nelements):

lat, lon, north_shift, east_shift = self.element_coords(i)

sources.append(ExplosionSource(

time=float(self.times[i]),

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=float(self.depths[i]),

moment=float(self.m0s[i])))

return sources

def moments(self):

return self.m0s

def centroid(self):

from pyrocko.gf.seismosizer import ExplosionSource

time, lat, lon, north_shift, east_shift, depth = \

self.centroid_position()

return ExplosionSource(

time=time,

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=depth,

moment=float(num.sum(self.m0s)))

@classmethod

def combine(cls, sources, **kwargs):

'''

Combine several discretized source models.

Concatenenates all point sources in the given discretized ``sources``.

Care must be taken when using this function that the external amplitude

factors and reference times of the parameterized (undiscretized)

sources match or are accounted for.

'''

if 'm0s' not in kwargs:

kwargs['m0s'] = num.concatenate([s.m0s for s in sources])

return super(DiscretizedExplosionSource, cls).combine(sources,

**kwargs)

class DiscretizedSFSource(DiscretizedSource):

forces = Array.T(shape=(None, 3), dtype=num.float)

provided_schemes = (

'elastic5',

)

def get_source_terms(self, scheme):

self.check_scheme(scheme)

return self.forces

def make_weights(self, receiver, scheme):

self.check_scheme(scheme)

azis, bazis = self.azibazis_to(receiver)

sa = num.sin(azis*d2r)

ca = num.cos(azis*d2r)

sb = num.sin(bazis*d2r-num.pi)

cb = num.cos(bazis*d2r-num.pi)

forces = self.forces

fn = forces[:, 0]

fe = forces[:, 1]

fd = forces[:, 2]

f0 = fd

f1 = ca * fn + sa * fe

f2 = ca * fe - sa * fn

n = azis.size

if scheme == 'elastic5':

ioff = 0

cat = num.concatenate

rep = num.repeat

w_n = cat((cb*f0, cb*f1, -sb*f2))

g_n = ioff + rep((0, 1, 2), n)

w_e = cat((sb*f0, sb*f1, cb*f2))

g_e = ioff + rep((0, 1, 2), n)

w_d = cat((f0, f1))

g_d = ioff + rep((3, 4), n)

return (

('displacement.n', w_n, g_n),

('displacement.e', w_e, g_e),

('displacement.d', w_d, g_d),

)

@classmethod

def combine(cls, sources, **kwargs):

'''

Combine several discretized source models.

Concatenenates all point sources in the given discretized ``sources``.

Care must be taken when using this function that the external amplitude

factors and reference times of the parameterized (undiscretized)

sources match or are accounted for.

'''

if 'forces' not in kwargs:

kwargs['forces'] = num.vstack([s.forces for s in sources])

return super(DiscretizedSFSource, cls).combine(sources, **kwargs)

def moments(self):

return num.sum(self.forces**2, axis=1)

def centroid(self):

from pyrocko.gf.seismosizer import SFSource

time, lat, lon, north_shift, east_shift, depth = \

self.centroid_position()

fn, fe, fd = map(float, num.sum(self.forces, axis=0))

return SFSource(

time=time,

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=depth,

fn=fn,

fe=fe,

fd=fd)

class DiscretizedMTSource(DiscretizedSource):

m6s = Array.T(

shape=(None, 6), dtype=num.float,

help='rows with (m_nn, m_ee, m_dd, m_ne, m_nd, m_ed)')

provided_schemes = (

'elastic8',

'elastic10',

'elastic18',

)

def get_source_terms(self, scheme):

self.check_scheme(scheme)

return self.m6s

def make_weights(self, receiver, scheme):

self.check_scheme(scheme)

m6s = self.m6s

n = m6s.shape[0]

rep = num.repeat

if scheme == 'elastic18':

w_n = m6s.flatten()

g_n = num.tile(num.arange(0, 6), n)

w_e = m6s.flatten()

g_e = num.tile(num.arange(6, 12), n)

w_d = m6s.flatten()

g_d = num.tile(num.arange(12, 18), n)

else:

azis, bazis = self.azibazis_to(receiver)

sa = num.sin(azis*d2r)

ca = num.cos(azis*d2r)

s2a = num.sin(2.*azis*d2r)

c2a = num.cos(2.*azis*d2r)

sb = num.sin(bazis*d2r-num.pi)

cb = num.cos(bazis*d2r-num.pi)

f0 = m6s[:, 0]*ca**2 + m6s[:, 1]*sa**2 + m6s[:, 3]*s2a

f1 = m6s[:, 4]*ca + m6s[:, 5]*sa

f2 = m6s[:, 2]

f3 = 0.5*(m6s[:, 1]-m6s[:, 0])*s2a + m6s[:, 3]*c2a

f4 = m6s[:, 5]*ca - m6s[:, 4]*sa

f5 = m6s[:, 0]*sa**2 + m6s[:, 1]*ca**2 - m6s[:, 3]*s2a

cat = num.concatenate

if scheme == 'elastic8':

w_n = cat((cb*f0, cb*f1, cb*f2, -sb*f3, -sb*f4))

g_n = rep((0, 1, 2, 3, 4), n)

w_e = cat((sb*f0, sb*f1, sb*f2, cb*f3, cb*f4))

g_e = rep((0, 1, 2, 3, 4), n)

w_d = cat((f0, f1, f2))

g_d = rep((5, 6, 7), n)

elif scheme == 'elastic10':

w_n = cat((cb*f0, cb*f1, cb*f2, cb*f5, -sb*f3, -sb*f4))

g_n = rep((0, 1, 2, 8, 3, 4), n)

w_e = cat((sb*f0, sb*f1, sb*f2, sb*f5, cb*f3, cb*f4))

g_e = rep((0, 1, 2, 8, 3, 4), n)

w_d = cat((f0, f1, f2, f5))

g_d = rep((5, 6, 7, 9), n)

else:

assert False

return (

('displacement.n', w_n, g_n),

('displacement.e', w_e, g_e),

('displacement.d', w_d, g_d),

)

def split(self):

from pyrocko.gf.seismosizer import MTSource

sources = []

for i in range(self.nelements):

lat, lon, north_shift, east_shift = self.element_coords(i)

sources.append(MTSource(

time=float(self.times[i]),

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=float(self.depths[i]),

m6=self.m6s[i]))

return sources

def moments(self):

n = self.nelements

moments = num.zeros(n)

for i in range(n):

m = moment_tensor.symmat6(*self.m6s[i])

m_evals = num.linalg.eigh(m)[0]

# incorrect for non-dc sources: !!!!

m0 = num.linalg.norm(m_evals)/math.sqrt(2.)

moments[i] = m0

return moments

def centroid(self):

from pyrocko.gf.seismosizer import MTSource

time, lat, lon, north_shift, east_shift, depth = \

self.centroid_position()

return MTSource(

time=time,

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=depth,

m6=num.sum(self.m6s, axis=0))

@classmethod

def combine(cls, sources, **kwargs):

'''

Combine several discretized source models.

Concatenenates all point sources in the given discretized ``sources``.

Care must be taken when using this function that the external amplitude

factors and reference times of the parameterized (undiscretized)

sources match or are accounted for.

'''

if 'm6s' not in kwargs:

kwargs['m6s'] = num.vstack([s.m6s for s in sources])

return super(DiscretizedMTSource, cls).combine(sources, **kwargs)

class DiscretizedPorePressureSource(DiscretizedSource):

pp = Array.T(shape=(None,), dtype=num.float)

provided_schemes = (

'poroelastic10',

)

def get_source_terms(self, scheme):

self.check_scheme(scheme)

return self.pp[:, num.newaxis].copy()

def make_weights(self, receiver, scheme):

self.check_scheme(scheme)

azis, bazis = self.azibazis_to(receiver)

sb = num.sin(bazis*d2r-num.pi)

cb = num.cos(bazis*d2r-num.pi)

pp = self.pp

n = bazis.size

w_un = cb*pp

g_un = filledi(1, n)

w_ue = sb*pp

g_ue = filledi(1, n)

w_ud = pp

g_ud = filledi(0, n)

w_tn = cb*pp

g_tn = filledi(6, n)

w_te = sb*pp

g_te = filledi(6, n)

w_pp = pp

g_pp = filledi(7, n)

w_dvn = cb*pp

g_dvn = filledi(9, n)

w_dve = sb*pp

g_dve = filledi(9, n)

w_dvd = pp

g_dvd = filledi(8, n)

return (

('displacement.n', w_un, g_un),

('displacement.e', w_ue, g_ue),

('displacement.d', w_ud, g_ud),

('vertical_tilt.n', w_tn, g_tn),

('vertical_tilt.e', w_te, g_te),

('pore_pressure', w_pp, g_pp),

('darcy_velocity.n', w_dvn, g_dvn),

('darcy_velocity.e', w_dve, g_dve),

('darcy_velocity.d', w_dvd, g_dvd),

)

def moments(self):

return self.pp

def centroid(self):

from pyrocko.gf.seismosizer import PorePressurePointSource

time, lat, lon, north_shift, east_shift, depth = \

self.centroid_position()

return PorePressurePointSource(

time=time,

lat=lat,

lon=lon,

north_shift=north_shift,

east_shift=east_shift,

depth=depth,

pp=float(num.sum(self.pp)))

@classmethod

def combine(cls, sources, **kwargs):

'''

Combine several discretized source models.

Concatenenates all point sources in the given discretized ``sources``.

Care must be taken when using this function that the external amplitude

factors and reference times of the parameterized (undiscretized)

sources match or are accounted for.

'''

if 'pp' not in kwargs:

kwargs['pp'] = num.concatenate([s.pp for s in sources])

return super(DiscretizedPorePressureSource, cls).combine(sources,

**kwargs)

class Region(Object):

name = String.T(optional=True)

class RectangularRegion(Region):

lat_min = Float.T()

lat_max = Float.T()

lon_min = Float.T()

lon_max = Float.T()

class CircularRegion(Region):

lat = Float.T()

lon = Float.T()

radius = Float.T()

class Config(Object):

'''

Green's function store meta information.

Currently implemented :py:class:`~pyrocko.gf.store.Store`

configuration types are:

* :py:class:`~pyrocko.gf.meta.ConfigTypeA` - cylindrical or

spherical symmetry, 1D earth model, single receiver depth

* Problem is invariant to horizontal translations and rotations around

vertical axis.

* All receivers must be at the same depth (e.g. at the surface)

* High level index variables: ``(source_depth, receiver_distance,

component)``

* :py:class:`~pyrocko.gf.meta.ConfigTypeB` - cylindrical or

spherical symmetry, 1D earth model, variable receiver depth

* Symmetries like in Type A but has additional index for receiver depth

* High level index variables: ``(source_depth, receiver_distance,

receiver_depth, component)``

* :py:class:`~pyrocko.gf.meta.ConfigTypeC` - no symmetrical

constraints but fixed receiver positions

* Cartesian source volume around a reference point

* High level index variables: ``(ireceiver, source_depth,

source_east_shift, source_north_shift, component)``

'''

id = StringID.T(

help='Name of the store. May consist of upper and lower-case letters, '

'digits, dots and underscores. The name must start with a '

'letter.')

derived_from_id = StringID.T(

optional=True,

help='Name of the original store, if this store has been derived from '

'another one (e.g. extracted subset).')

version = String.T(

default='1.0',

optional=True,

help='User-defined version string. Use <major>.<minor> format.')

modelling_code_id = StringID.T(

optional=True,

help='Identifier of the backend used to compute the store.')

author = Unicode.T(

optional=True,

help='Comma-separated list of author names.')

author_email = String.T(

optional=True,

help="Author's contact email address.")

created_time = Timestamp.T(

optional=True,

help='Time of creation of the store.')

regions = List.T(

Region.T(),

help='Geographical regions for which the store is representative.')

scope_type = ScopeType.T(

optional=True,

help='Distance range scope of the store '

'(%s).' % fmt_choices(ScopeType))

waveform_type = WaveType.T(

optional=True,

help='Wave type stored (%s).' % fmt_choices(WaveType))

nearfield_terms = NearfieldTermsType.T(

optional=True,

help='Information about the inclusion of near-field terms in the '

'modelling (%s).' % fmt_choices(NearfieldTermsType))

description = String.T(

optional=True,

help='Free form textual description of the GF store.')

references = List.T(

Reference.T(),

help='Reference list to cite the modelling code, earth model or '

'related work.')

earthmodel_1d = Earthmodel1D.T(

optional=True,

help='Layered earth model in ND (named discontinuity) format.')

earthmodel_receiver_1d = Earthmodel1D.T(

optional=True,

help='Receiver-side layered earth model in ND format.')

can_interpolate_source = Bool.T(

optional=True,

help='Hint to indicate if the spatial sampling of the store is dense '

'enough for multi-linear interpolation at the source.')

can_interpolate_receiver = Bool.T(

optional=True,

help='Hint to indicate if the spatial sampling of the store is dense '

'enough for multi-linear interpolation at the receiver.')

frequency_min = Float.T(

optional=True,

help='Hint to indicate the lower bound of valid frequencies [Hz].')

frequency_max = Float.T(

optional=True,

help='Hint to indicate the upper bound of valid frequencies [Hz].')

sample_rate = Float.T(

optional=True,

help='Sample rate of the GF store [Hz].')

factor = Float.T(

default=1.0,

help='Gain value, factored out of the stored GF samples. '

'(may not work properly, keep at 1.0).',

optional=True)

component_scheme = ComponentScheme.T(

default='elastic10',

help='GF component scheme (%s).' % fmt_choices(ComponentScheme))

stored_quantity = QuantityType.T(

optional=True,

help='Physical quantity of stored values (%s). If not given, a '

'default is used based on the GF component scheme. The default '

'for the ``"elastic*"`` family of component schemes is '

'``"displacement"``.' % fmt_choices(QuantityType))

tabulated_phases = List.T(

TPDef.T(),

help='Mapping of phase names to phase definitions, for which travel '

'time tables are available in the GF store.')

ncomponents = Int.T(

optional=True,

help='Number of GF components. Use :gattr:`component_scheme` instead.')

uuid = String.T(

optional=True,

help='Heuristic hash value which can be used to uniquely identify the '

'GF store for practical purposes.')

reference = String.T(

optional=True,

help='Store reference name composed of the store\'s :gattr:`id` and '

'the first six letters of its :gattr:`uuid`.')

def __init__(self, **kwargs):

self._do_auto_updates = False

Object.__init__(self, **kwargs)

self._index_function = None

self._indices_function = None

self._vicinity_function = None

self.validate(regularize=True, depth=1)

self._do_auto_updates = True

self.update()

def check_ncomponents(self):

ncomponents = component_scheme_to_description[

self.component_scheme].ncomponents

if self.ncomponents is None:

self.ncomponents = ncomponents

elif ncomponents != self.ncomponents:

raise InvalidNComponents(

'ncomponents=%i incompatible with component_scheme="%s"' % (

self.ncomponents, self.component_scheme))

def __setattr__(self, name, value):

Object.__setattr__(self, name, value)

try:

self.T.get_property(name)

if self._do_auto_updates:

self.update()

except ValueError:

pass

def update(self):

self.check_ncomponents()

self._update()

self._make_index_functions()

def irecord(self, *args):

return self._index_function(*args)

def irecords(self, *args):

return self._indices_function(*args)

def vicinity(self, *args):

return self._vicinity_function(*args)

def vicinities(self, *args):

return self._vicinities_function(*args)

def grid_interpolation_coefficients(self, *args):

return self._grid_interpolation_coefficients(*args)

def nodes(self, level=None, minlevel=None):

return nodes(self.coords[minlevel:level])

def iter_nodes(self, level=None, minlevel=None):

return nditer_outer(self.coords[minlevel:level])

def iter_extraction(self, gdef, level=None):

i = 0

arrs = []

ntotal = 1

for mi, ma, inc in zip(self.mins, self.effective_maxs, self.deltas):

if gdef and len(gdef) > i:

sssn = gdef[i]

else:

sssn = (None,)*4

arr = num.linspace(*start_stop_num(*(sssn + (mi, ma, inc))))

ntotal *= len(arr)

arrs.append(arr)

i += 1

arrs.append(self.coords[-1])

return nditer_outer(arrs[:level])

def make_sum_params(self, source, receiver, implementation='c',

nthreads=0):

assert implementation in ['c', 'python']

out = []

delays = source.times

for comp, weights, icomponents in source.make_weights(

receiver,

self.component_scheme):

weights *= self.factor

args = self.make_indexing_args(source, receiver, icomponents)

delays_expanded = num.tile(delays, icomponents.size//delays.size)

out.append((comp, args, delays_expanded, weights))

return out

def short_info(self):

raise NotImplementedError('should be implemented in subclass')

def get_shear_moduli(self, lat, lon, points,

interpolation=None):

'''

Get shear moduli at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates the shear moduli

from the contained 1D velocity profile.

'''

return self.get_material_property(lat, lon, points,

parameter='shear_moduli',

interpolation=interpolation)

def get_lambda_moduli(self, lat, lon, points,

interpolation=None):

'''

Get lambda moduli at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates the lambda moduli

from the contained 1D velocity profile.

'''

return self.get_material_property(lat, lon, points,

parameter='lambda_moduli',

interpolation=interpolation)

def get_bulk_moduli(self, lat, lon, points,

interpolation=None):

'''

Get bulk moduli at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates the lambda moduli

from the contained 1D velocity profile.

'''

lambda_moduli = self.get_material_property(

lat, lon, points, parameter='lambda_moduli',

interpolation=interpolation)

shear_moduli = self.get_material_property(

lat, lon, points, parameter='shear_moduli',

interpolation=interpolation)

return lambda_moduli + (2 / 3) * shear_moduli

def get_vs(self, lat, lon, points, interpolation=None):

'''

Get Vs at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates Vs

from the contained 1D velocity profile.

'''

return self.get_material_property(lat, lon, points,

parameter='vs',

interpolation=interpolation)

def get_vp(self, lat, lon, points, interpolation=None):

'''

Get Vp at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates Vp

from the contained 1D velocity profile.

'''

return self.get_material_property(lat, lon, points,

parameter='vp',

interpolation=interpolation)

def get_rho(self, lat, lon, points, interpolation=None):

'''

Get rho at given points from contained velocity model.

:param lat: surface origin for coordinate system of ``points``

:param points: NumPy array of shape ``(N, 3)``, where each row is

a point ``(north, east, depth)``, relative to origin at

``(lat, lon)``

:param interpolation: interpolation method. Choose from

``('nearest_neighbor', 'multilinear')``

:returns: NumPy array of length N with extracted shear moduli at each

point

The default implementation retrieves and interpolates rho

from the contained 1D velocity profile.

'''

return self.get_material_property(lat, lon, points,

parameter='rho',

interpolation=interpolation)

def get_material_property(self, lat, lon, points, parameter='vs',

interpolation=None):

if interpolation is None:

raise TypeError('Interpolation method not defined! available: '

"multilinear", "nearest_neighbor")

earthmod = self.earthmodel_1d

store_depth_profile = self.get_source_depths()

z_profile = earthmod.profile('z')

if parameter == 'vs':

vs_profile = earthmod.profile('vs')

profile = num.interp(

store_depth_profile, z_profile, vs_profile)

elif parameter == 'vp':

vp_profile = earthmod.profile('vp')

profile = num.interp(

store_depth_profile, z_profile, vp_profile)

elif parameter == 'rho':

rho_profile = earthmod.profile('rho')

profile = num.interp(

store_depth_profile, z_profile, rho_profile)

elif parameter == 'shear_moduli':

vs_profile = earthmod.profile('vs')

rho_profile = earthmod.profile('rho')

store_vs_profile = num.interp(

store_depth_profile, z_profile, vs_profile)

store_rho_profile = num.interp(

store_depth_profile, z_profile, rho_profile)

profile = num.power(store_vs_profile, 2) * store_rho_profile

elif parameter == 'lambda_moduli':

vs_profile = earthmod.profile('vs')

vp_profile = earthmod.profile('vp')

rho_profile = earthmod.profile('rho')

store_vs_profile = num.interp(

store_depth_profile, z_profile, vs_profile)

store_vp_profile = num.interp(

store_depth_profile, z_profile, vp_profile)

store_rho_profile = num.interp(

store_depth_profile, z_profile, rho_profile)

profile = store_rho_profile * (

num.power(store_vp_profile, 2) -

num.power(store_vs_profile, 2) * 2)

else:

raise TypeError(

'parameter %s not available' % parameter)

if interpolation == 'multilinear':

kind = 'linear'

elif interpolation == 'nearest_neighbor':

kind = 'nearest'

else:

raise TypeError(

'Interpolation method %s not available' % interpolation)

interpolator = interp1d(store_depth_profile, profile, kind=kind)

try:

return interpolator(points[:, 2])

except ValueError:

raise OutOfBounds()

def is_static(self):

for code in ('psgrn_pscmp', 'poel'):

if self.modelling_code_id.startswith(code):

return True

return False

def is_dynamic(self):

return not self.is_static()

def get_source_depths(self):

raise NotImplementedError('must be implemented in subclass')

def get_tabulated_phase(self, phase_id):

'''

Get tabulated phase definition.

'''

for pdef in self.tabulated_phases:

if pdef.id == phase_id:

return pdef

raise StoreError('No such phase: %s' % phase_id)

def fix_ttt_holes(self, sptree, mode):

raise StoreError(

'Cannot fix travel time table holes in GF stores of type %s.'

% self.short_type)

class ConfigTypeA(Config):

'''

Cylindrical symmetry, 1D earth model, single receiver depth

* Problem is invariant to horizontal translations and rotations around

vertical axis.

* All receivers must be at the same depth (e.g. at the surface)

High level index variables: ``(source_depth, distance,

component)``

* The ``distance`` is the surface distance between source and receiver

points.

'''

receiver_depth = Float.T(

default=0.0,

help='Fixed receiver depth [m].')

source_depth_min = Float.T(

help='Minimum source depth [m].')

source_depth_max = Float.T(

help='Maximum source depth [m].')

source_depth_delta = Float.T(

help='Grid spacing of source depths [m]')

distance_min = Float.T(

help='Minimum source-receiver surface distance [m].')

distance_max = Float.T(

help='Maximum source-receiver surface distance [m].')

distance_delta = Float.T(

help='Grid spacing of source-receiver surface distance [m].')

short_type = 'A'

provided_schemes = [

'elastic2', 'elastic5', 'elastic8', 'elastic10', 'poroelastic10']

def get_surface_distance(self, args):

return args[1]

def get_distance(self, args):

return math.sqrt(args[0]**2 + args[1]**2)

def get_source_depth(self, args):

return args[0]

def get_source_depths(self):

return self.coords[0]

def get_receiver_depth(self, args):

return self.receiver_depth

def _update(self):

self.mins = num.array(

[self.source_depth_min, self.distance_min], dtype=num.float)

self.maxs = num.array(

[self.source_depth_max, self.distance_max], dtype=num.float)

self.deltas = num.array(

[self.source_depth_delta, self.distance_delta],

dtype=num.float)

self.ns = num.floor((self.maxs - self.mins) / self.deltas +

vicinity_eps).astype(num.int) + 1

self.effective_maxs = self.mins + self.deltas * (self.ns - 1)

self.deltat = 1.0/self.sample_rate

self.nrecords = num.product(self.ns) * self.ncomponents

self.coords = tuple(num.linspace(mi, ma, n) for

(mi, ma, n) in

zip(self.mins, self.effective_maxs, self.ns)) + \

(num.arange(self.ncomponents),)

self.nsource_depths, self.ndistances = self.ns

def _make_index_functions(self):

amin, bmin = self.mins

da, db = self.deltas

na, nb = self.ns

ng = self.ncomponents

def index_function(a, b, ig):

ia = int(round((a - amin) / da))

ib = int(round((b - bmin) / db))

try:

return num.ravel_multi_index((ia, ib, ig), (na, nb, ng))

except ValueError:

raise OutOfBounds()

def indices_function(a, b, ig):

ia = num.round((a - amin) / da).astype(int)

ib = num.round((b - bmin) / db).astype(int)

try:

return num.ravel_multi_index((ia, ib, ig), (na, nb, ng))

except ValueError:

for ia_, ib_, ig_ in zip(ia, ib, ig):

try:

num.ravel_multi_index((ia_, ib_, ig_), (na, nb, ng))

except ValueError:

raise OutOfBounds()

def grid_interpolation_coefficients(a, b):

ias = indi12((a - amin) / da, na)

ibs = indi12((b - bmin) / db, nb)

return ias, ibs

def vicinity_function(a, b, ig):

ias, ibs = grid_interpolation_coefficients(a, b)

if not (0 <= ig < ng):

raise OutOfBounds()

indis = []

weights = []

for ia, va in ias:

iia = ia*nb*ng

for ib, vb in ibs:

indis.append(iia + ib*ng + ig)

weights.append(va*vb)

return num.array(indis), num.array(weights)

def vicinities_function(a, b, ig):

xa = (a - amin) / da

xb = (b - bmin) / db

xa_fl = num.floor(xa)

xa_ce = num.ceil(xa)

xb_fl = num.floor(xb)

xb_ce = num.ceil(xb)

va_fl = 1.0 - (xa - xa_fl)

va_ce = (1.0 - (xa_ce - xa)) * (xa_ce - xa_fl)

vb_fl = 1.0 - (xb - xb_fl)

vb_ce = (1.0 - (xb_ce - xb)) * (xb_ce - xb_fl)

ia_fl = xa_fl.astype(num.int)

ia_ce = xa_ce.astype(num.int)

ib_fl = xb_fl.astype(num.int)

ib_ce = xb_ce.astype(num.int)

if num.any(ia_fl < 0) or num.any(ia_fl >= na):

raise OutOfBounds()

if num.any(ia_ce < 0) or num.any(ia_ce >= na):

raise OutOfBounds()

if num.any(ib_fl < 0) or num.any(ib_fl >= nb):

raise OutOfBounds()

if num.any(ib_ce < 0) or num.any(ib_ce >= nb):

raise OutOfBounds()

irecords = num.empty(a.size*4, dtype=num.int)

irecords[0::4] = ia_fl*nb*ng + ib_fl*ng + ig

irecords[1::4] = ia_ce*nb*ng + ib_fl*ng + ig

irecords[2::4] = ia_fl*nb*ng + ib_ce*ng + ig

irecords[3::4] = ia_ce*nb*ng + ib_ce*ng + ig

weights = num.empty(a.size*4, dtype=num.float)

weights[0::4] = va_fl * vb_fl

weights[1::4] = va_ce * vb_fl

weights[2::4] = va_fl * vb_ce

weights[3::4] = va_ce * vb_ce

return irecords, weights

self._index_function = index_function

self._indices_function = indices_function

self._grid_interpolation_coefficients = grid_interpolation_coefficients

self._vicinity_function = vicinity_function

self._vicinities_function = vicinities_function

def make_indexing_args(self, source, receiver, icomponents):

nc = icomponents.size

dists = source.distances_to(receiver)

n = dists.size

return (num.tile(source.depths, nc//n),

num.tile(dists, nc//n),

icomponents)

def make_indexing_args1(self, source, receiver):

return (source.depth, source.distance_to(receiver))

@property

def short_extent(self):

return '%g:%g:%g x %g:%g:%g' % (

self.source_depth_min/km,

self.source_depth_max/km,

self.source_depth_delta/km,

self.distance_min/km,

self.distance_max/km,

self.distance_delta/km)

def fix_ttt_holes(self, sptree, mode):

from pyrocko import eikonal_ext, spit

nodes = self.nodes(level=-1)

delta = self.deltas[-1]

assert num.all(delta == self.deltas)

nsources, ndistances = self.ns

points = num.zeros((nodes.shape[0], 3))

points[:, 0] = nodes[:, 1]

points[:, 2] = nodes[:, 0]

speeds = self.get_material_property(

0., 0., points,

parameter='vp' if mode == cake.P else 'vs',

interpolation='multilinear')

speeds = speeds.reshape((nsources, ndistances))

times = sptree.interpolate_many(nodes)

times[num.isnan(times)] = -1.

times = times.reshape(speeds.shape)

try:

eikonal_ext.eikonal_solver_fmm_cartesian(

speeds, times, delta)

except eikonal_ext.EikonalExtError as e:

if str(e).endswith('please check results'):

logger.debug(

'Got a warning from eikonal solver '

'- may be ok...')

else:

raise

def func(x):

ibs, ics = \

self.grid_interpolation_coefficients(*x)

t = 0

for ib, vb in ibs:

for ic, vc in ics:

t += times[ib, ic] * vb * vc

return t

return spit.SPTree(

f=func,

ftol=sptree.ftol,

xbounds=sptree.xbounds,

xtols=sptree.xtols)

class ConfigTypeB(Config):

'''

Cylindrical symmetry, 1D earth model, variable receiver depth

* Symmetries like in :py:class:`ConfigTypeA` but has additional index for

receiver depth

* High level index variables: ``(source_depth, receiver_distance,

receiver_depth, component)``

'''

receiver_depth_min = Float.T(

help='Minimum receiver depth [m].')

receiver_depth_max = Float.T(

help='Maximum receiver depth [m].')

receiver_depth_delta = Float.T(

help='Grid spacing of receiver depths [m]')

source_depth_min = Float.T(

help='Minimum source depth [m].')

source_depth_max = Float.T(

help='Maximum source depth [m].')

source_depth_delta = Float.T(

help='Grid spacing of source depths [m]')

distance_min = Float.T(

help='Minimum source-receiver surface distance [m].')

distance_max = Float.T(

help='Maximum source-receiver surface distance [m].')

distance_delta = Float.T(

help='Grid spacing of source-receiver surface distances [m].')

short_type = 'B'

provided_schemes = [

'elastic2', 'elastic5', 'elastic8', 'elastic10', 'poroelastic10']

def get_distance(self, args):

return math.sqrt((args[1] - args[0])**2 + args[2]**2)

def get_surface_distance(self, args):

return args[2]

def get_source_depth(self, args):

return args[1]

def get_receiver_depth(self, args):

return args[0]

def get_source_depths(self):

return self.coords[1]

def _update(self):

self.mins = num.array([

self.receiver_depth_min,

self.source_depth_min,

self.distance_min],

dtype=num.float)

self.maxs = num.array([

self.receiver_depth_max,

self.source_depth_max,

self.distance_max],

dtype=num.float)

self.deltas = num.array([

self.receiver_depth_delta,

self.source_depth_delta,

self.distance_delta],

dtype=num.float)

self.ns = num.floor((self.maxs - self.mins) / self.deltas +

vicinity_eps).astype(num.int) + 1

self.effective_maxs = self.mins + self.deltas * (self.ns - 1)

self.deltat = 1.0/self.sample_rate

self.nrecords = num.product(self.ns) * self.ncomponents

self.coords = tuple(num.linspace(mi, ma, n) for

(mi, ma, n) in

zip(self.mins, self.effective_maxs, self.ns)) + \

(num.arange(self.ncomponents),)

self.nreceiver_depths, self.nsource_depths, self.ndistances = self.ns

def _make_index_functions(self):

amin, bmin, cmin = self.mins

da, db, dc = self.deltas

na, nb, nc = self.ns

ng = self.ncomponents

def index_function(a, b, c, ig):

ia = int(round((a - amin) / da))

ib = int(round((b - bmin) / db))

ic = int(round((c - cmin) / dc))

try:

return num.ravel_multi_index((ia, ib, ic, ig),

(na, nb, nc, ng))

except ValueError:

raise OutOfBounds()

def indices_function(a, b, c, ig):

ia = num.round((a - amin) / da).astype(int)

ib = num.round((b - bmin) / db).astype(int)

ic = num.round((c - cmin) / dc).astype(int)

try:

return num.ravel_multi_index((ia, ib, ic, ig),

(na, nb, nc, ng))

except ValueError:

raise OutOfBounds()

def grid_interpolation_coefficients(a, b, c):

ias = indi12((a - amin) / da, na)

ibs = indi12((b - bmin) / db, nb)

ics = indi12((c - cmin) / dc, nc)

return ias, ibs, ics

def vicinity_function(a, b, c, ig):

ias, ibs, ics = grid_interpolation_coefficients(a, b, c)

if not (0 <= ig < ng):

raise OutOfBounds()

indis = []

weights = []

for ia, va in ias:

iia = ia*nb*nc*ng

for ib, vb in ibs:

iib = ib*nc*ng

for ic, vc in ics:

indis.append(iia + iib + ic*ng + ig)

weights.append(va*vb*vc)

return num.array(indis), num.array(weights)

def vicinities_function(a, b, c, ig):

xa = (a - amin) / da

xb = (b - bmin) / db

xc = (c - cmin) / dc

xa_fl = num.floor(xa)

xa_ce = num.ceil(xa)

xb_fl = num.floor(xb)

xb_ce = num.ceil(xb)

xc_fl = num.floor(xc)

xc_ce = num.ceil(xc)

va_fl = 1.0 - (xa - xa_fl)

va_ce = (1.0 - (xa_ce - xa)) * (xa_ce - xa_fl)

vb_fl = 1.0 - (xb - xb_fl)

vb_ce = (1.0 - (xb_ce - xb)) * (xb_ce - xb_fl)

vc_fl = 1.0 - (xc - xc_fl)

vc_ce = (1.0 - (xc_ce - xc)) * (xc_ce - xc_fl)

ia_fl = xa_fl.astype(num.int)

ia_ce = xa_ce.astype(num.int)

ib_fl = xb_fl.astype(num.int)

ib_ce = xb_ce.astype(num.int)

ic_fl = xc_fl.astype(num.int)

ic_ce = xc_ce.astype(num.int)

if num.any(ia_fl < 0) or num.any(ia_fl >= na):

raise OutOfBounds()

if num.any(ia_ce < 0) or num.any(ia_ce >= na):

raise OutOfBounds()

if num.any(ib_fl < 0) or num.any(ib_fl >= nb):

raise OutOfBounds()

if num.any(ib_ce < 0) or num.any(ib_ce >= nb):

raise OutOfBounds()

if num.any(ic_fl < 0) or num.any(ic_fl >= nc):

raise OutOfBounds()

if num.any(ic_ce < 0) or num.any(ic_ce >= nc):

raise OutOfBounds()

irecords = num.empty(a.size*8, dtype=num.int)

irecords[0::8] = ia_fl*nb*nc*ng + ib_fl*nc*ng + ic_fl*ng + ig

irecords[1::8] = ia_ce*nb*nc*ng + ib_fl*nc*ng + ic_fl*ng + ig

irecords[2::8] = ia_fl*nb*nc*ng + ib_ce*nc*ng + ic_fl*ng + ig

irecords[3::8] = ia_ce*nb*nc*ng + ib_ce*nc*ng + ic_fl*ng + ig

irecords[4::8] = ia_fl*nb*nc*ng + ib_fl*nc*ng + ic_ce*ng + ig

irecords[5::8] = ia_ce*nb*nc*ng + ib_fl*nc*ng + ic_ce*ng + ig

irecords[6::8] = ia_fl*nb*nc*ng + ib_ce*nc*ng + ic_ce*ng + ig

irecords[7::8] = ia_ce*nb*nc*ng + ib_ce*nc*ng + ic_ce*ng + ig

weights = num.empty(a.size*8, dtype=num.float)

weights[0::8] = va_fl * vb_fl * vc_fl

weights[1::8] = va_ce * vb_fl * vc_fl

weights[2::8] = va_fl * vb_ce * vc_fl

weights[3::8] = va_ce * vb_ce * vc_fl

weights[4::8] = va_fl * vb_fl * vc_ce

weights[5::8] = va_ce * vb_fl * vc_ce

weights[6::8] = va_fl * vb_ce * vc_ce

weights[7::8] = va_ce * vb_ce * vc_ce

return irecords, weights

self._index_function = index_function

self._indices_function = indices_function

self._grid_interpolation_coefficients = grid_interpolation_coefficients

self._vicinity_function = vicinity_function

self._vicinities_function = vicinities_function

def make_indexing_args(self, source, receiver, icomponents):

nc = icomponents.size

dists = source.distances_to(receiver)

n = dists.size

receiver_depths = num.empty(nc)

receiver_depths.fill(receiver.depth)

return (receiver_depths,

num.tile(source.depths, nc//n),

num.tile(dists, nc//n),

icomponents)

def make_indexing_args1(self, source, receiver):

return (receiver.depth,

source.depth,

source.distance_to(receiver))

@property

def short_extent(self):

return '%g:%g:%g x %g:%g:%g x %g:%g:%g' % (

self.receiver_depth_min/km,

self.receiver_depth_max/km,

self.receiver_depth_delta/km,

self.source_depth_min/km,

self.source_depth_max/km,

self.source_depth_delta/km,

self.distance_min/km,

self.distance_max/km,

self.distance_delta/km)

def fix_ttt_holes(self, sptree, mode):

from pyrocko import eikonal_ext, spit

nodes_sr = self.nodes(minlevel=1, level=-1)

delta = self.deltas[-1]

assert num.all(delta == self.deltas[1:])

nreceivers, nsources, ndistances = self.ns

points = num.zeros((nodes_sr.shape[0], 3))

points[:, 0] = nodes_sr[:, 1]

points[:, 2] = nodes_sr[:, 0]

speeds = self.get_material_property(

0., 0., points,

parameter='vp' if mode == cake.P else 'vs',

interpolation='multilinear')

speeds = speeds.reshape((nsources, ndistances))

receiver_times = []

for ireceiver in range(nreceivers):

nodes = num.hstack([

num_full(

(nodes_sr.shape[0], 1),

self.coords[0][ireceiver]),

nodes_sr])

times = sptree.interpolate_many(nodes)

times[num.isnan(times)] = -1.

times = times.reshape(speeds.shape)

try:

eikonal_ext.eikonal_solver_fmm_cartesian(

speeds, times, delta)

except eikonal_ext.EikonalExtError as e:

if str(e).endswith('please check results'):

logger.debug(

'Got a warning from eikonal solver '

'- may be ok...')

else:

raise

receiver_times.append(times)

def func(x):

ias, ibs, ics = \

self.grid_interpolation_coefficients(*x)

t = 0

for ia, va in ias:

times = receiver_times[ia]

for ib, vb in ibs:

for ic, vc in ics:

t += times[ib, ic] * va * vb * vc

return t

return spit.SPTree(

f=func,

ftol=sptree.ftol,

xbounds=sptree.xbounds,

xtols=sptree.xtols)

class ConfigTypeC(Config):

'''

No symmetrical constraints but fixed receiver positions.

* Cartesian 3D source volume around a reference point

* High level index variables: ``(ireceiver, source_depth,

source_east_shift, source_north_shift, component)``

'''

receivers = List.T(

Receiver.T(),

help='List of fixed receivers.')

source_origin = Location.T(

help='Origin of the source volume grid.')

source_depth_min = Float.T(

help='Minimum source depth [m].')

source_depth_max = Float.T(

help='Maximum source depth [m].')

source_depth_delta = Float.T(

help='Source depth grid spacing [m].')

source_east_shift_min = Float.T(

help='Minimum easting of source grid [m].')

source_east_shift_max = Float.T(

help='Maximum easting of source grid [m].')

source_east_shift_delta = Float.T(

help='Source volume grid spacing in east direction [m].')

source_north_shift_min = Float.T(

help='Minimum northing of source grid [m].')

source_north_shift_max = Float.T(

help='Maximum northing of source grid [m].')

source_north_shift_delta = Float.T(

help='Source volume grid spacing in north direction [m].')

short_type = 'C'

provided_schemes = ['elastic18']

def get_surface_distance(self, args):

ireceiver, _, source_east_shift, source_north_shift, _ = args

sorig = self.source_origin

sloc = Location(

lat=sorig.lat,

lon=sorig.lon,

north_shift=sorig.north_shift + source_north_shift,

east_shift=sorig.east_shift + source_east_shift)

return self.receivers[args[0]].distance_to(sloc)

def get_distance(self, args):

# to be improved...

ireceiver, sdepth, source_east_shift, source_north_shift, _ = args

sorig = self.source_origin

sloc = Location(

lat=sorig.lat,

lon=sorig.lon,

north_shift=sorig.north_shift + source_north_shift,

east_shift=sorig.east_shift + source_east_shift)

return math.sqrt(

self.receivers[args[0]].distance_to(sloc)**2 + sdepth**2)

def get_source_depth(self, args):

return args[1]

def get_receiver_depth(self, args):

return self.receivers[args[0]].depth

def get_source_depths(self):

return self.coords[0]

def _update(self):

self.mins = num.array([

self.source_depth_min,

self.source_east_shift_min,

self.source_north_shift_min],

dtype=num.float)

self.maxs = num.array([

self.source_depth_max,

self.source_east_shift_max,

self.source_north_shift_max],

dtype=num.float)

self.deltas = num.array([

self.source_depth_delta,

self.source_east_shift_delta,

self.source_north_shift_delta],

dtype=num.float)

self.ns = num.floor((self.maxs - self.mins) / self.deltas +

vicinity_eps).astype(num.int) + 1

self.effective_maxs = self.mins + self.deltas * (self.ns - 1)

self.deltat = 1.0/self.sample_rate

self.nreceivers = len(self.receivers)

self.nrecords = \

self.nreceivers * num.product(self.ns) * self.ncomponents

self.coords = (num.arange(self.nreceivers),) + \

tuple(num.linspace(mi, ma, n) for (mi, ma, n) in

zip(self.mins, self.effective_maxs, self.ns)) + \

(num.arange(self.ncomponents),)

self.nreceiver_depths, self.nsource_depths, self.ndistances = self.ns

self._distances_cache = {}

def _make_index_functions(self):

amin, bmin, cmin = self.mins

da, db, dc = self.deltas

na, nb, nc = self.ns

ng = self.ncomponents

nr = self.nreceivers

def index_function(ir, a, b, c, ig):

ia = int(round((a - amin) / da))

ib = int(round((b - bmin) / db))

ic = int(round((c - cmin) / dc))

try:

return num.ravel_multi_index((ir, ia, ib, ic, ig),

(nr, na, nb, nc, ng))

except ValueError:

raise OutOfBounds()

def indices_function(ir, a, b, c, ig):

ia = num.round((a - amin) / da).astype(int)

ib = num.round((b - bmin) / db).astype(int)

ic = num.round((c - cmin) / dc).astype(int)

try:

return num.ravel_multi_index((ir, ia, ib, ic, ig),

(nr, na, nb, nc, ng))

except ValueError:

raise OutOfBounds()

def vicinity_function(ir, a, b, c, ig):

ias = indi12((a - amin) / da, na)

ibs = indi12((b - bmin) / db, nb)

ics = indi12((c - cmin) / dc, nc)

if not (0 <= ir < nr):

raise OutOfBounds()

if not (0 <= ig < ng):

raise OutOfBounds()

indis = []

weights = []

iir = ir*na*nb*nc*ng

for ia, va in ias:

iia = ia*nb*nc*ng

for ib, vb in ibs:

iib = ib*nc*ng

for ic, vc in ics:

indis.append(iir + iia + iib + ic*ng + ig)

weights.append(va*vb*vc)

return num.array(indis), num.array(weights)

def vicinities_function(ir, a, b, c, ig):

xa = (a-amin) / da

xb = (b-bmin) / db

xc = (c-cmin) / dc

xa_fl = num.floor(xa)

xa_ce = num.ceil(xa)

xb_fl = num.floor(xb)

xb_ce = num.ceil(xb)

xc_fl = num.floor(xc)

xc_ce = num.ceil(xc)

va_fl = 1.0 - (xa - xa_fl)

va_ce = (1.0 - (xa_ce - xa)) * (xa_ce - xa_fl)

vb_fl = 1.0 - (xb - xb_fl)

vb_ce = (1.0 - (xb_ce - xb)) * (xb_ce - xb_fl)

vc_fl = 1.0 - (xc - xc_fl)

vc_ce = (1.0 - (xc_ce - xc)) * (xc_ce - xc_fl)

ia_fl = xa_fl.astype(num.int)

ia_ce = xa_ce.astype(num.int)

ib_fl = xb_fl.astype(num.int)

ib_ce = xb_ce.astype(num.int)

ic_fl = xc_fl.astype(num.int)

ic_ce = xc_ce.astype(num.int)

if num.any(ia_fl < 0) or num.any(ia_fl >= na):

raise OutOfBounds()

if num.any(ia_ce < 0) or num.any(ia_ce >= na):

raise OutOfBounds()

if num.any(ib_fl < 0) or num.any(ib_fl >= nb):

raise OutOfBounds()

if num.any(ib_ce < 0) or num.any(ib_ce >= nb):

raise OutOfBounds()

if num.any(ic_fl < 0) or num.any(ic_fl >= nc):

raise OutOfBounds()

if num.any(ic_ce < 0) or num.any(ic_ce >= nc):

raise OutOfBounds()

irig = ir*na*nb*nc*ng + ig

irecords = num.empty(a.size*8, dtype=num.int)

irecords[0::8] = ia_fl*nb*nc*ng + ib_fl*nc*ng + ic_fl*ng + irig

irecords[1::8] = ia_ce*nb*nc*ng + ib_fl*nc*ng + ic_fl*ng + irig

irecords[2::8] = ia_fl*nb*nc*ng + ib_ce*nc*ng + ic_fl*ng + irig

irecords[3::8] = ia_ce*nb*nc*ng + ib_ce*nc*ng + ic_fl*ng + irig

irecords[4::8] = ia_fl*nb*nc*ng + ib_fl*nc*ng + ic_ce*ng + irig

irecords[5::8] = ia_ce*nb*nc*ng + ib_fl*nc*ng + ic_ce*ng + irig

irecords[6::8] = ia_fl*nb*nc*ng + ib_ce*nc*ng + ic_ce*ng + irig

irecords[7::8] = ia_ce*nb*nc*ng + ib_ce*nc*ng + ic_ce*ng + irig

weights = num.empty(a.size*8, dtype=num.float)

weights[0::8] = va_fl * vb_fl * vc_fl

weights[1::8] = va_ce * vb_fl * vc_fl

weights[2::8] = va_fl * vb_ce * vc_fl

weights[3::8] = va_ce * vb_ce * vc_fl

weights[4::8] = va_fl * vb_fl * vc_ce

weights[5::8] = va_ce * vb_fl * vc_ce

weights[6::8] = va_fl * vb_ce * vc_ce

weights[7::8] = va_ce * vb_ce * vc_ce

return irecords, weights

self._index_function = index_function

self._indices_function = indices_function

self._vicinity_function = vicinity_function

self._vicinities_function = vicinities_function

def lookup_ireceiver(self, receiver):

k = (receiver.lat, receiver.lon,

receiver.north_shift, receiver.east_shift)

dh = min(self.source_north_shift_delta, self.source_east_shift_delta)

dv = self.source_depth_delta

for irec, rec in enumerate(self.receivers):

if (k, irec) not in self._distances_cache:

self._distances_cache[k, irec] = math.sqrt(

(receiver.distance_to(rec)/dh)**2 +

((rec.depth - receiver.depth)/dv)**2)

if self._distances_cache[k, irec] < 0.1:

return irec

raise OutOfBounds(

reason='No GFs available for receiver at (%g, %g).' %

receiver.effective_latlon)

def make_indexing_args(self, source, receiver, icomponents):

nc = icomponents.size

dists = source.distances_to(self.source_origin)

azis, _ = source.azibazis_to(self.source_origin)

source_north_shifts = - num.cos(d2r*azis) * dists

source_east_shifts = - num.sin(d2r*azis) * dists

source_depths = source.depths - self.source_origin.depth

n = dists.size

ireceivers = num.empty(nc, dtype=num.int)

ireceivers.fill(self.lookup_ireceiver(receiver))

return (ireceivers,

num.tile(source_depths, nc//n),

num.tile(source_east_shifts, nc//n),

num.tile(source_north_shifts, nc//n),

icomponents)

def make_indexing_args1(self, source, receiver):

dist = source.distance_to(self.source_origin)

azi, _ = source.azibazi_to(self.source_origin)

source_north_shift = - num.cos(d2r*azi) * dist

source_east_shift = - num.sin(d2r*azi) * dist

source_depth = source.depth - self.source_origin.depth

return (self.lookup_ireceiver(receiver),

source_depth,

source_east_shift,

source_north_shift)

@property

def short_extent(self):

return '%g:%g:%g x %g:%g:%g x %g:%g:%g' % (

self.source_depth_min/km,

self.source_depth_max/km,

self.source_depth_delta/km,

self.source_east_shift_min/km,

self.source_east_shift_max/km,

self.source_east_shift_delta/km,

self.source_north_shift_min/km,

self.source_north_shift_max/km,

self.source_north_shift_delta/km)

class Weighting(Object):

factor = Float.T(default=1.0)

class Taper(Object):

tmin = Timing.T()

tmax = Timing.T()

tfade = Float.T(default=0.0)

shape = StringChoice.T(

choices=['cos', 'linear'],

default='cos',

optional=True)

class SimplePattern(SObject):

_pool = {}

def __init__(self, pattern):

self._pattern = pattern

SObject.__init__(self)

def __str__(self):

return self._pattern

@property

def regex(self):

pool = SimplePattern._pool

if self.pattern not in pool:

rpat = '|'.join(fnmatch.translate(x) for

x in self.pattern.split('|'))

pool[self.pattern] = re.compile(rpat, re.I)

return pool[self.pattern]

def match(self, s):

return self.regex.match(s)

class WaveformType(StringChoice):

choices = ['dis', 'vel', 'acc',

'amp_spec_dis', 'amp_spec_vel', 'amp_spec_acc',

'envelope_dis', 'envelope_vel', 'envelope_acc']

class ChannelSelection(Object):

pattern = SimplePattern.T(optional=True)

min_sample_rate = Float.T(optional=True)

max_sample_rate = Float.T(optional=True)

class StationSelection(Object):

includes = SimplePattern.T()

excludes = SimplePattern.T()

distance_min = Float.T(optional=True)

distance_max = Float.T(optional=True)

azimuth_min = Float.T(optional=True)

azimuth_max = Float.T(optional=True)

class WaveformSelection(Object):

channel_selection = ChannelSelection.T(optional=True)

station_selection = StationSelection.T(optional=True)

taper = Taper.T()

# filter = FrequencyResponse.T()

waveform_type = WaveformType.T(default='dis')

weighting = Weighting.T(optional=True)

sample_rate = Float.T(optional=True)

gf_store_id = StringID.T(optional=True)

def indi12(x, n):

'''

Get linear interpolation index and weight.

'''

r = round(x)

if abs(r - x) < vicinity_eps:

i = int(r)

if not (0 <= i < n):

raise OutOfBounds()

return ((int(r), 1.),)

else:

f = math.floor(x)

i = int(f)

if not (0 <= i < n-1):

raise OutOfBounds()

v = x-f

return ((i, 1.-v), (i + 1, v))

def float_or_none(s):

units = {

'k': 1e3,

'M': 1e6,

}

factor = 1.0

if s and s[-1] in units:

factor = units[s[-1]]

s = s[:-1]

if not s:

raise ValueError('unit without a number: \'%s\'' % s)

if s:

return float(s) * factor

else:

return None

class GridSpecError(Exception):

def __init__(self, s):

Exception.__init__(self, 'invalid grid specification: %s' % s)

def parse_grid_spec(spec):

try:

result = []

for dspec in spec.split(','):

t = dspec.split('@')

num = start = stop = step = None

if len(t) == 2:

num = int(t[1])

if num <= 0:

raise GridSpecError(spec)

elif len(t) > 2:

raise GridSpecError(spec)

s = t[0]

v = [float_or_none(x) for x in s.split(':')]

if len(v) == 1:

start = stop = v[0]

if len(v) >= 2:

start, stop = v[0:2]

if len(v) == 3:

step = v[2]

if len(v) > 3 or (len(v) > 2 and num is not None):

raise GridSpecError(spec)

if step == 0.0:

raise GridSpecError(spec)

result.append((start, stop, step, num))

except ValueError:

raise GridSpecError(spec)

return result

def start_stop_num(start, stop, step, num, mi, ma, inc, eps=1e-5):

swap = step is not None and step < 0.

if start is None:

start = [mi, ma][swap]

if stop is None:

stop = [ma, mi][swap]

if step is None:

step = [inc, -inc][ma < mi]

if num is None:

if (step < 0) != (stop-start < 0):

raise GridSpecError()

num = int(round((stop-start)/step))+1

stop2 = start + (num-1)*step

if abs(stop-stop2) > eps:

num = int(math.floor((stop-start)/step))+1

stop = start + (num-1)*step

else:

stop = stop2

if start == stop:

num = 1

return start, stop, num

def nditer_outer(x):

return num.nditer(

x, op_axes=(num.identity(len(x), dtype=num.int)-1).tolist())

def nodes(xs):

ns = [x.size for x in xs]

nnodes = num.prod(ns)

ndim = len(xs)

nodes = num.empty((nnodes, ndim), dtype=xs[0].dtype)

for idim in range(ndim-1, -1, -1):

x = xs[idim]

nrepeat = num.prod(ns[idim+1:], dtype=num.int)

ntile = num.prod(ns[:idim], dtype=num.int)

nodes[:, idim] = num.repeat(num.tile(x, ntile), nrepeat)

return nodes

def filledi(x, n):

a = num.empty(n, dtype=num.int)

a.fill(x)

return a

config_type_classes = [ConfigTypeA, ConfigTypeB, ConfigTypeC]

discretized_source_classes = [

DiscretizedExplosionSource,

DiscretizedSFSource,

DiscretizedMTSource,

DiscretizedPorePressureSource]

__all__ = '''

Earthmodel1D

StringID

ScopeType

WaveformType

QuantityType

NearfieldTermsType

Reference

Region

CircularRegion

RectangularRegion

PhaseSelect

InvalidTimingSpecification

Timing

TPDef

OutOfBounds

Location

Receiver

'''.split() + [

S.__name__ for S in discretized_source_classes + config_type_classes] + '''

ComponentScheme

component_scheme_to_description

component_schemes

Config

GridSpecError

Weighting

Taper

SimplePattern

WaveformType

ChannelSelection

StationSelection

WaveformSelection

nditer_outer

dump

load

discretized_source_classes

config_type_classes

UnavailableScheme

InterpolationMethod

SeismosizerTrace

SeismosizerResult

Result

StaticResult

'''.split()

Coverage for /usr/local/lib/python3.7/dist-packages/pyrocko/gf/meta.py : 70%

1400 statements 978 run 422 missing 83 excluded