# http://pyrocko.org - GPLv3
#
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------
'''
.. _coordinate-system-names:
Coordinate systems
..................
Coordinate system names commonly used in source models.
================= ============================================
Name Description
================= ============================================
``'xyz'`` northing, easting, depth in [m]
``'xy'`` northing, easting in [m]
``'latlon'`` latitude, longitude in [deg]
``'lonlat'`` longitude, latitude in [deg]
``'latlondepth'`` latitude, longitude in [deg], depth in [m]
================= ============================================
'''
from __future__ import absolute_import, division, print_function
from collections import defaultdict
from functools import cmp_to_key
import time
import math
import os
import re
import logging
try:
import resource
except ImportError:
resource = None
from hashlib import sha1
import numpy as num
from scipy.interpolate import RegularGridInterpolator
from pyrocko.guts import (Object, Float, String, StringChoice, List,
Timestamp, Int, SObject, ArgumentError, Dict,
ValidationError, Bool)
from pyrocko.guts_array import Array
from pyrocko import moment_tensor as pmt
from pyrocko import trace, util, config, model, eikonal_ext
from pyrocko.orthodrome import ne_to_latlon
from pyrocko.model import Location
from pyrocko.modelling import OkadaSource, make_okada_coefficient_matrix, \
okada_ext, invert_fault_dislocations_bem
from . import meta, store, ws
from .tractions import TractionField, DirectedTractions
from .targets import Target, StaticTarget, SatelliteTarget
pjoin = os.path.join
guts_prefix = 'pf'
d2r = math.pi / 180.
r2d = 180. / math.pi
km = 1e3
logger = logging.getLogger('pyrocko.gf.seismosizer')
def cmp_none_aware(a, b):
if isinstance(a, tuple) and isinstance(b, tuple):
for xa, xb in zip(a, b):
rv = cmp_none_aware(xa, xb)
if rv != 0:
return rv
return 0
anone = a is None
bnone = b is None
if anone and bnone:
return 0
if anone:
return -1
if bnone:
return 1
return bool(a > b) - bool(a < b)
def xtime():
return time.time()
[docs]class SeismosizerError(Exception):
pass
[docs]class BadRequest(SeismosizerError):
pass
class DuplicateStoreId(Exception):
pass
class NoDefaultStoreSet(Exception):
pass
class ConversionError(Exception):
pass
[docs]class NoSuchStore(BadRequest):
def __init__(self, store_id=None, dirs=None):
BadRequest.__init__(self)
self.store_id = store_id
self.dirs = dirs
def __str__(self):
if self.store_id is not None:
rstr = 'no GF store with id "%s" found.' % self.store_id
else:
rstr = 'GF store not found.'
if self.dirs is not None:
rstr += ' Searched folders:\n %s' % '\n '.join(sorted(self.dirs))
return rstr
def ufloat(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)
return float(s) * factor
def ufloat_or_none(s):
if s:
return ufloat(s)
else:
return None
def int_or_none(s):
if s:
return int(s)
else:
return None
def nonzero(x, eps=1e-15):
return abs(x) > eps
def permudef(ln, j=0):
if j < len(ln):
k, v = ln[j]
for y in v:
ln[j] = k, y
for s in permudef(ln, j + 1):
yield s
ln[j] = k, v
return
else:
yield ln
def arr(x):
return num.atleast_1d(num.asarray(x))
def discretize_rect_source(deltas, deltat, time, north, east, depth,
strike, dip, length, width,
anchor, velocity=None, stf=None,
nucleation_x=None, nucleation_y=None,
decimation_factor=1, pointsonly=False,
plane_coords=False,
aggressive_oversampling=False):
if stf is None:
stf = STF()
if not velocity and not pointsonly:
raise AttributeError('velocity is required in time mode')
mindeltagf = float(num.min(deltas))
if velocity:
mindeltagf = min(mindeltagf, deltat * velocity)
ln = length
wd = width
if aggressive_oversampling:
nl = int((2. / decimation_factor) * num.ceil(ln / mindeltagf)) + 1
nw = int((2. / decimation_factor) * num.ceil(wd / mindeltagf)) + 1
else:
nl = int((1. / decimation_factor) * num.ceil(ln / mindeltagf)) + 1
nw = int((1. / decimation_factor) * num.ceil(wd / mindeltagf)) + 1
n = int(nl * nw)
dl = ln / nl
dw = wd / nw
xl = num.linspace(-0.5 * (ln - dl), 0.5 * (ln - dl), nl)
xw = num.linspace(-0.5 * (wd - dw), 0.5 * (wd - dw), nw)
points = num.zeros((n, 3), dtype=num.float)
points[:, 0] = num.tile(xl, nw)
points[:, 1] = num.repeat(xw, nl)
if nucleation_x is not None:
dist_x = num.abs(nucleation_x - points[:, 0])
else:
dist_x = num.zeros(n)
if nucleation_y is not None:
dist_y = num.abs(nucleation_y - points[:, 1])
else:
dist_y = num.zeros(n)
dist = num.sqrt(dist_x**2 + dist_y**2)
times = dist / velocity
anch_x, anch_y = map_anchor[anchor]
points[:, 0] -= anch_x * 0.5 * length
points[:, 1] -= anch_y * 0.5 * width
if plane_coords:
return points, dl, dw, nl, nw
rotmat = num.asarray(
pmt.euler_to_matrix(dip * d2r, strike * d2r, 0.0))
points = num.dot(rotmat.T, points.T).T
points[:, 0] += north
points[:, 1] += east
points[:, 2] += depth
if pointsonly:
return points, dl, dw, nl, nw
xtau, amplitudes = stf.discretize_t(deltat, time)
nt = xtau.size
points2 = num.repeat(points, nt, axis=0)
times2 = (times[:, num.newaxis] + xtau[num.newaxis, :]).ravel()
amplitudes2 = num.tile(amplitudes, n)
return points2, times2, amplitudes2, dl, dw, nl, nw
def check_rect_source_discretisation(points2, nl, nw, store):
# We assume a non-rotated fault plane
N_CRITICAL = 8
points = points2.T.reshape((3, nl, nw))
if points.size <= N_CRITICAL:
logger.warning('RectangularSource is defined by only %d sub-sources!'
% points.size)
return True
distances = num.sqrt(
(points[0, 0, :] - points[0, 1, :])**2 +
(points[1, 0, :] - points[1, 1, :])**2 +
(points[2, 0, :] - points[2, 1, :])**2)
depths = points[2, 0, :]
vs_profile = store.config.get_vs(
lat=0., lon=0.,
points=num.repeat(depths[:, num.newaxis], 3, axis=1),
interpolation='multilinear')
min_wavelength = vs_profile * (store.config.deltat * 2)
if not num.all(min_wavelength > distances / 2):
return False
return True
def outline_rect_source(strike, dip, length, width, anchor):
ln = length
wd = width
points = num.array(
[[-0.5 * ln, -0.5 * wd, 0.],
[0.5 * ln, -0.5 * wd, 0.],
[0.5 * ln, 0.5 * wd, 0.],
[-0.5 * ln, 0.5 * wd, 0.],
[-0.5 * ln, -0.5 * wd, 0.]])
anch_x, anch_y = map_anchor[anchor]
points[:, 0] -= anch_x * 0.5 * length
points[:, 1] -= anch_y * 0.5 * width
rotmat = num.asarray(
pmt.euler_to_matrix(dip * d2r, strike * d2r, 0.0))
return num.dot(rotmat.T, points.T).T
def from_plane_coords(
strike, dip, length, width, depth, x_plane_coords, y_plane_coords,
lat=0., lon=0.,
north_shift=0, east_shift=0,
anchor='top', cs='xy'):
ln = length
wd = width
x_abs = []
y_abs = []
if not isinstance(x_plane_coords, list):
x_plane_coords = [x_plane_coords]
y_plane_coords = [y_plane_coords]
for x_plane, y_plane in zip(x_plane_coords, y_plane_coords):
points = num.array(
[[-0.5 * ln * x_plane, -0.5 * wd * y_plane, 0.],
[0.5 * ln * x_plane, -0.5 * wd * y_plane, 0.],
[0.5 * ln * x_plane, 0.5 * wd * y_plane, 0.],
[-0.5 * ln * x_plane, 0.5 * wd * y_plane, 0.],
[-0.5 * ln * x_plane, -0.5 * wd * y_plane, 0.]])
anch_x, anch_y = map_anchor[anchor]
points[:, 0] -= anch_x * 0.5 * length
points[:, 1] -= anch_y * 0.5 * width
rotmat = num.asarray(
pmt.euler_to_matrix(dip * d2r, strike * d2r, 0.0))
points = num.dot(rotmat.T, points.T).T
points[:, 0] += north_shift
points[:, 1] += east_shift
points[:, 2] += depth
if cs in ('latlon', 'lonlat'):
latlon = ne_to_latlon(lat, lon,
points[:, 0], points[:, 1])
latlon = num.array(latlon).T
x_abs.append(latlon[1:2, 1])
y_abs.append(latlon[2:3, 0])
if cs == 'xy':
x_abs.append(points[1:2, 1])
y_abs.append(points[2:3, 0])
if cs == 'lonlat':
return y_abs, x_abs
else:
return x_abs, y_abs
def points_on_rect_source(
strike, dip, length, width, anchor,
discretized_basesource=None, points_x=None, points_y=None):
ln = length
wd = width
if isinstance(points_x, list) or isinstance(points_x, float):
points_x = num.array([points_x])
if isinstance(points_y, list) or isinstance(points_y, float):
points_y = num.array([points_y])
if discretized_basesource:
ds = discretized_basesource
nl_patches = ds.nl + 1
nw_patches = ds.nw + 1
npoints = nl_patches * nw_patches
points = num.zeros((npoints, 3))
ln_patches = num.array([il for il in range(nl_patches)])
wd_patches = num.array([iw for iw in range(nw_patches)])
points_ln =\
2 * ((ln_patches - num.min(ln_patches)) / num.ptp(ln_patches)) - 1
points_wd =\
2 * ((wd_patches - num.min(wd_patches)) / num.ptp(wd_patches)) - 1
for il in range(nl_patches):
for iw in range(nw_patches):
points[il * nw_patches + iw, :] = num.array([
points_ln[il] * ln * 0.5,
points_wd[iw] * wd * 0.5, 0.0])
elif points_x.any() and points_y.any():
points = num.zeros(shape=((len(points_x), 3)))
for i, (x, y) in enumerate(zip(points_x, points_y)):
points[i, :] = num.array(
[x * 0.5 * ln, y * 0.5 * wd, 0.0])
anch_x, anch_y = map_anchor[anchor]
points[:, 0] -= anch_x * 0.5 * ln
points[:, 1] -= anch_y * 0.5 * wd
rotmat = num.asarray(
pmt.euler_to_matrix(dip * d2r, strike * d2r, 0.0))
return num.dot(rotmat.T, points.T).T
class InvalidGridDef(Exception):
pass
[docs]class Range(SObject):
'''
Convenient range specification.
Equivalent ways to sepecify the range [ 0., 1000., ... 10000. ]::
Range('0 .. 10k : 1k')
Range(start=0., stop=10e3, step=1e3)
Range(0, 10e3, 1e3)
Range('0 .. 10k @ 11')
Range(start=0., stop=10*km, n=11)
Range(0, 10e3, n=11)
Range(values=[x*1e3 for x in range(11)])
Depending on the use context, it can be possible to omit any part of the
specification. E.g. in the context of extracting a subset of an already
existing range, the existing range's specification values would be filled
in where missing.
The values are distributed with equal spacing, unless the ``spacing``
argument is modified. The values can be created offset or relative to an
external base value with the ``relative`` argument if the use context
supports this.
The range specification can be expressed with a short string
representation::
'start .. stop @ num | spacing, relative'
'start .. stop : step | spacing, relative'
most parts of the expression can be omitted if not needed. Whitespace is
allowed for readability but can also be omitted.
'''
start = Float.T(optional=True)
stop = Float.T(optional=True)
step = Float.T(optional=True)
n = Int.T(optional=True)
values = Array.T(optional=True, dtype=float, shape=(None,))
spacing = StringChoice.T(
choices=['lin', 'log', 'symlog'],
default='lin',
optional=True)
relative = StringChoice.T(
choices=['', 'add', 'mult'],
default='',
optional=True)
pattern = re.compile(r'^((?P<start>.*)\.\.(?P<stop>[^@|:]*))?'
r'(@(?P<n>[^|]+)|:(?P<step>[^|]+))?'
r'(\|(?P<stuff>.+))?$')
def __init__(self, *args, **kwargs):
d = {}
if len(args) == 1:
d = self.parse(args[0])
elif len(args) in (2, 3):
d['start'], d['stop'] = [float(x) for x in args[:2]]
if len(args) == 3:
d['step'] = float(args[2])
for k, v in kwargs.items():
if k in d:
raise ArgumentError('%s specified more than once' % k)
d[k] = v
SObject.__init__(self, **d)
def __str__(self):
def sfloat(x):
if x is not None:
return '%g' % x
else:
return ''
if self.values:
return ','.join('%g' % x for x in self.values)
if self.start is None and self.stop is None:
s0 = ''
else:
s0 = '%s .. %s' % (sfloat(self.start), sfloat(self.stop))
s1 = ''
if self.step is not None:
s1 = [' : %g', ':%g'][s0 == ''] % self.step
elif self.n is not None:
s1 = [' @ %i', '@%i'][s0 == ''] % self.n
if self.spacing == 'lin' and self.relative == '':
s2 = ''
else:
x = []
if self.spacing != 'lin':
x.append(self.spacing)
if self.relative != '':
x.append(self.relative)
s2 = ' | %s' % ','.join(x)
return s0 + s1 + s2
@classmethod
def parse(cls, s):
s = re.sub(r'\s+', '', s)
m = cls.pattern.match(s)
if not m:
try:
vals = [ufloat(x) for x in s.split(',')]
except Exception:
raise InvalidGridDef(
'"%s" is not a valid range specification' % s)
return dict(values=num.array(vals, dtype=float))
d = m.groupdict()
try:
start = ufloat_or_none(d['start'])
stop = ufloat_or_none(d['stop'])
step = ufloat_or_none(d['step'])
n = int_or_none(d['n'])
except Exception:
raise InvalidGridDef(
'"%s" is not a valid range specification' % s)
spacing = 'lin'
relative = ''
if d['stuff'] is not None:
t = d['stuff'].split(',')
for x in t:
if x in cls.spacing.choices:
spacing = x
elif x and x in cls.relative.choices:
relative = x
else:
raise InvalidGridDef(
'"%s" is not a valid range specification' % s)
return dict(start=start, stop=stop, step=step, n=n, spacing=spacing,
relative=relative)
def make(self, mi=None, ma=None, inc=None, base=None, eps=1e-5):
if self.values:
return self.values
start = self.start
stop = self.stop
step = self.step
n = self.n
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 and inc is not None:
step = [inc, -inc][ma < mi]
if start is None or stop is None:
raise InvalidGridDef(
'Cannot use range specification "%s" without start '
'and stop in this context' % self)
if step is None and n is None:
step = stop - start
if n is None:
if (step < 0) != (stop - start < 0):
raise InvalidGridDef(
'Range specification "%s" has inconsistent ordering '
'(step < 0 => stop > start)' % self)
n = int(round((stop - start) / step)) + 1
stop2 = start + (n - 1) * step
if abs(stop - stop2) > eps:
n = int(math.floor((stop - start) / step)) + 1
stop = start + (n - 1) * step
else:
stop = stop2
if start == stop:
n = 1
if self.spacing == 'lin':
vals = num.linspace(start, stop, n)
elif self.spacing in ('log', 'symlog'):
if start > 0. and stop > 0.:
vals = num.exp(num.linspace(num.log(start),
num.log(stop), n))
elif start < 0. and stop < 0.:
vals = -num.exp(num.linspace(num.log(-start),
num.log(-stop), n))
else:
raise InvalidGridDef(
'Log ranges should not include or cross zero '
'(in range specification "%s").' % self)
if self.spacing == 'symlog':
nvals = - vals
vals = num.concatenate((nvals[::-1], vals))
if self.relative in ('add', 'mult') and base is None:
raise InvalidGridDef(
'Cannot use relative range specification in this context.')
vals = self.make_relative(base, vals)
return list(map(float, vals))
def make_relative(self, base, vals):
if self.relative == 'add':
vals += base
if self.relative == 'mult':
vals *= base
return vals
class GridDefElement(Object):
param = meta.StringID.T()
rs = Range.T()
def __init__(self, shorthand=None, **kwargs):
if shorthand is not None:
t = shorthand.split('=')
if len(t) != 2:
raise InvalidGridDef(
'Invalid grid specification element: %s' % shorthand)
sp, sr = t[0].strip(), t[1].strip()
kwargs['param'] = sp
kwargs['rs'] = Range(sr)
Object.__init__(self, **kwargs)
def shorthand(self):
return self.param + ' = ' + str(self.rs)
class GridDef(Object):
elements = List.T(GridDefElement.T())
def __init__(self, shorthand=None, **kwargs):
if shorthand is not None:
t = shorthand.splitlines()
tt = []
for x in t:
x = x.strip()
if x:
tt.extend(x.split(';'))
elements = []
for se in tt:
elements.append(GridDef(se))
kwargs['elements'] = elements
Object.__init__(self, **kwargs)
def shorthand(self):
return '; '.join(str(x) for x in self.elements)
class Cloneable(object):
def __iter__(self):
return iter(self.T.propnames)
def __getitem__(self, k):
if k not in self.keys():
raise KeyError(k)
return getattr(self, k)
def __setitem__(self, k, v):
if k not in self.keys():
raise KeyError(k)
return setattr(self, k, v)
def clone(self, **kwargs):
'''
Make a copy of the object.
A new object of the same class is created and initialized with the
parameters of the object on which this method is called on. If
``kwargs`` are given, these are used to override any of the
initialization parameters.
'''
d = dict(self)
for k in d:
v = d[k]
if isinstance(v, Cloneable):
d[k] = v.clone()
d.update(kwargs)
return self.__class__(**d)
@classmethod
def keys(cls):
'''
Get list of the source model's parameter names.
'''
return cls.T.propnames
[docs]class STF(Object, Cloneable):
'''
Base class for source time functions.
'''
def __init__(self, effective_duration=None, **kwargs):
if effective_duration is not None:
kwargs['duration'] = effective_duration / \
self.factor_duration_to_effective()
Object.__init__(self, **kwargs)
@classmethod
def factor_duration_to_effective(cls):
return 1.0
def centroid_time(self, tref):
return tref
@property
def effective_duration(self):
return self.duration * self.factor_duration_to_effective()
def discretize_t(self, deltat, tref):
tl = math.floor(tref / deltat) * deltat
th = math.ceil(tref / deltat) * deltat
if tl == th:
return num.array([tl], dtype=float), num.ones(1)
else:
return (
num.array([tl, th], dtype=float),
num.array([th - tref, tref - tl], dtype=float) / deltat)
def base_key(self):
return (type(self).__name__,)
g_unit_pulse = STF()
def sshift(times, amplitudes, tshift, deltat):
t0 = math.floor(tshift / deltat) * deltat
t1 = math.ceil(tshift / deltat) * deltat
if t0 == t1:
return times, amplitudes
amplitudes2 = num.zeros(amplitudes.size + 1, dtype=float)
amplitudes2[:-1] += (t1 - tshift) / deltat * amplitudes
amplitudes2[1:] += (tshift - t0) / deltat * amplitudes
times2 = num.arange(times.size + 1, dtype=float) * \
deltat + times[0] + t0
return times2, amplitudes2
[docs]class BoxcarSTF(STF):
'''
Boxcar type source time function.
.. figure :: /static/stf-BoxcarSTF.svg
:width: 40%
:align: center
:alt: boxcar source time function
'''
duration = Float.T(
default=0.0,
help='duration of the boxcar')
anchor = Float.T(
default=0.0,
help='anchor point with respect to source.time: ('
'-1.0: left -> source duration [0, T] ~ hypocenter time, '
' 0.0: center -> source duration [-T/2, T/2] ~ centroid time, '
'+1.0: right -> source duration [-T, 0] ~ rupture end time)')
@classmethod
def factor_duration_to_effective(cls):
return 1.0
def centroid_time(self, tref):
return tref - 0.5 * self.duration * self.anchor
def discretize_t(self, deltat, tref):
tmin_stf = tref - self.duration * (self.anchor + 1.) * 0.5
tmax_stf = tref + self.duration * (1. - self.anchor) * 0.5
tmin = round(tmin_stf / deltat) * deltat
tmax = round(tmax_stf / deltat) * deltat
nt = int(round((tmax - tmin) / deltat)) + 1
times = num.linspace(tmin, tmax, nt)
amplitudes = num.ones_like(times)
if times.size > 1:
t_edges = num.linspace(
tmin - 0.5 * deltat, tmax + 0.5 * deltat, nt + 1)
t = tmin_stf + self.duration * num.array(
[0.0, 0.0, 1.0, 1.0], dtype=float)
f = num.array([0., 1., 1., 0.], dtype=float)
amplitudes = util.plf_integrate_piecewise(t_edges, t, f)
amplitudes /= num.sum(amplitudes)
tshift = (num.sum(amplitudes * times) - self.centroid_time(tref))
return sshift(times, amplitudes, -tshift, deltat)
def base_key(self):
return (type(self).__name__, self.duration, self.anchor)
[docs]class TriangularSTF(STF):
'''
Triangular type source time function.
.. figure :: /static/stf-TriangularSTF.svg
:width: 40%
:align: center
:alt: triangular source time function
'''
duration = Float.T(
default=0.0,
help='baseline of the triangle')
peak_ratio = Float.T(
default=0.5,
help='fraction of time compared to duration, '
'when the maximum amplitude is reached')
anchor = Float.T(
default=0.0,
help='anchor point with respect to source.time: ('
'-1.0: left -> source duration [0, T] ~ hypocenter time, '
' 0.0: center -> source duration [-T/2, T/2] ~ centroid time, '
'+1.0: right -> source duration [-T, 0] ~ rupture end time)')
@classmethod
def factor_duration_to_effective(cls, peak_ratio=None):
if peak_ratio is None:
peak_ratio = cls.peak_ratio.default()
return math.sqrt((peak_ratio**2 - peak_ratio + 1.0) * 2.0 / 3.0)
def __init__(self, effective_duration=None, **kwargs):
if effective_duration is not None:
kwargs['duration'] = effective_duration / \
self.factor_duration_to_effective(
kwargs.get('peak_ratio', None))
STF.__init__(self, **kwargs)
@property
def centroid_ratio(self):
ra = self.peak_ratio
rb = 1.0 - ra
return self.peak_ratio + (rb**2 / 3. - ra**2 / 3.) / (ra + rb)
def centroid_time(self, tref):
ca = self.centroid_ratio
cb = 1.0 - ca
if self.anchor <= 0.:
return tref - ca * self.duration * self.anchor
else:
return tref - cb * self.duration * self.anchor
@property
def effective_duration(self):
return self.duration * self.factor_duration_to_effective(
self.peak_ratio)
def tminmax_stf(self, tref):
ca = self.centroid_ratio
cb = 1.0 - ca
if self.anchor <= 0.:
tmin_stf = tref - ca * self.duration * (self.anchor + 1.)
tmax_stf = tmin_stf + self.duration
else:
tmax_stf = tref + cb * self.duration * (1. - self.anchor)
tmin_stf = tmax_stf - self.duration
return tmin_stf, tmax_stf
def discretize_t(self, deltat, tref):
tmin_stf, tmax_stf = self.tminmax_stf(tref)
tmin = round(tmin_stf / deltat) * deltat
tmax = round(tmax_stf / deltat) * deltat
nt = int(round((tmax - tmin) / deltat)) + 1
if nt > 1:
t_edges = num.linspace(
tmin - 0.5 * deltat, tmax + 0.5 * deltat, nt + 1)
t = tmin_stf + self.duration * num.array(
[0.0, self.peak_ratio, 1.0], dtype=float)
f = num.array([0., 1., 0.], dtype=float)
amplitudes = util.plf_integrate_piecewise(t_edges, t, f)
amplitudes /= num.sum(amplitudes)
else:
amplitudes = num.ones(1)
times = num.linspace(tmin, tmax, nt)
return times, amplitudes
def base_key(self):
return (
type(self).__name__, self.duration, self.peak_ratio, self.anchor)
[docs]class HalfSinusoidSTF(STF):
'''
Half sinusoid type source time function.
.. figure :: /static/stf-HalfSinusoidSTF.svg
:width: 40%
:align: center
:alt: half-sinusouid source time function
'''
duration = Float.T(
default=0.0,
help='duration of the half-sinusoid (baseline)')
anchor = Float.T(
default=0.0,
help='anchor point with respect to source.time: ('
'-1.0: left -> source duration [0, T] ~ hypocenter time, '
' 0.0: center -> source duration [-T/2, T/2] ~ centroid time, '
'+1.0: right -> source duration [-T, 0] ~ rupture end time)')
exponent = Int.T(
default=1,
help='set to 2 to use square of the half-period sinusoidal function.')
def __init__(self, effective_duration=None, **kwargs):
if effective_duration is not None:
kwargs['duration'] = effective_duration / \
self.factor_duration_to_effective(
kwargs.get('exponent', 1))
STF.__init__(self, **kwargs)
@classmethod
def factor_duration_to_effective(cls, exponent):
if exponent == 1:
return math.sqrt(3.0 * math.pi**2 - 24.0) / math.pi
elif exponent == 2:
return math.sqrt(math.pi**2 - 6) / math.pi
else:
raise ValueError('Exponent for HalfSinusoidSTF must be 1 or 2.')
@property
def effective_duration(self):
return self.duration * self.factor_duration_to_effective(self.exponent)
def centroid_time(self, tref):
return tref - 0.5 * self.duration * self.anchor
def discretize_t(self, deltat, tref):
tmin_stf = tref - self.duration * (self.anchor + 1.) * 0.5
tmax_stf = tref + self.duration * (1. - self.anchor) * 0.5
tmin = round(tmin_stf / deltat) * deltat
tmax = round(tmax_stf / deltat) * deltat
nt = int(round((tmax - tmin) / deltat)) + 1
if nt > 1:
t_edges = num.maximum(tmin_stf, num.minimum(tmax_stf, num.linspace(
tmin - 0.5 * deltat, tmax + 0.5 * deltat, nt + 1)))
if self.exponent == 1:
fint = -num.cos(
(t_edges - tmin_stf) * (math.pi / self.duration))
elif self.exponent == 2:
fint = (t_edges - tmin_stf) / self.duration \
- 1.0 / (2.0 * math.pi) * num.sin(
(t_edges - tmin_stf) * (2.0 * math.pi / self.duration))
else:
raise ValueError(
'Exponent for HalfSinusoidSTF must be 1 or 2.')
amplitudes = fint[1:] - fint[:-1]
amplitudes /= num.sum(amplitudes)
else:
amplitudes = num.ones(1)
times = num.linspace(tmin, tmax, nt)
return times, amplitudes
def base_key(self):
return (type(self).__name__, self.duration, self.anchor)
class SmoothRampSTF(STF):
'''
Smooth-ramp type source time function for near-field displacement.
Based on moment function of double-couple point source proposed by Bruestle
and Mueller (PEPI, 1983).
.. [1] W. Bruestle, G. Mueller (1983), Moment and duration of shallow
earthquakes from Love-wave modelling for regional distances, PEPI 32,
312-324.
.. figure :: /static/stf-SmoothRampSTF.svg
:width: 40%
:alt: smooth ramp source time function
'''
duration = Float.T(
default=0.0,
help='duration of the ramp (baseline)')
rise_ratio = Float.T(
default=0.5,
help='fraction of time compared to duration, '
'when the maximum amplitude is reached')
anchor = Float.T(
default=0.0,
help='anchor point with respect to source.time: ('
'-1.0: left -> source duration ``[0, T]`` ~ hypocenter time, '
'0.0: center -> source duration ``[-T/2, T/2]`` ~ centroid time, '
'+1.0: right -> source duration ``[-T, 0]`` ~ rupture end time)')
def discretize_t(self, deltat, tref):
tmin_stf = tref - self.duration * (self.anchor + 1.) * 0.5
tmax_stf = tref + self.duration * (1. - self.anchor) * 0.5
tmin = round(tmin_stf / deltat) * deltat
tmax = round(tmax_stf / deltat) * deltat
D = round((tmax - tmin) / deltat) * deltat
nt = int(round(D / deltat)) + 1
times = num.linspace(tmin, tmax, nt)
if nt > 1:
rise_time = self.rise_ratio * self.duration
amplitudes = num.ones_like(times)
tp = tmin + rise_time
ii = num.where(times <= tp)
t_inc = times[ii]
a = num.cos(num.pi * (t_inc - tmin_stf) / rise_time)
b = num.cos(3 * num.pi * (t_inc - tmin_stf) / rise_time) - 1.0
amplitudes[ii] = (9. / 16.) * (1 - a + (1. / 9.) * b)
amplitudes /= num.sum(amplitudes)
else:
amplitudes = num.ones(1)
return times, amplitudes
def base_key(self):
return (type(self).__name__,
self.duration, self.rise_ratio, self.anchor)
[docs]class ResonatorSTF(STF):
'''
Simple resonator like source time function.
.. math ::
f(t) = 0 for t < 0
f(t) = e^{-t/tau} * sin(2 * pi * f * t)
.. figure :: /static/stf-SmoothRampSTF.svg
:width: 40%
:alt: smooth ramp source time function
'''
duration = Float.T(
default=0.0,
help='decay time')
frequency = Float.T(
default=1.0,
help='resonance frequency')
def discretize_t(self, deltat, tref):
tmin_stf = tref
tmax_stf = tref + self.duration * 3
tmin = math.floor(tmin_stf / deltat) * deltat
tmax = math.ceil(tmax_stf / deltat) * deltat
times = util.arange2(tmin, tmax, deltat)
amplitudes = num.exp(-(times - tref) / self.duration) \
* num.sin(2.0 * num.pi * self.frequency * (times - tref))
return times, amplitudes
def base_key(self):
return (type(self).__name__,
self.duration, self.frequency)
[docs]class STFMode(StringChoice):
choices = ['pre', 'post']
[docs]class Source(Location, Cloneable):
'''
Base class for all source models.
'''
name = String.T(optional=True, default='')
time = Timestamp.T(
default=Timestamp.D('1970-01-01 00:00:00'),
help='source origin time.')
stf = STF.T(
optional=True,
help='source time function.')
stf_mode = STFMode.T(
default='post',
help='whether to apply source time function in pre or '
'post-processing.')
def __init__(self, **kwargs):
Location.__init__(self, **kwargs)
[docs] def update(self, **kwargs):
'''
Change some of the source models parameters.
Example::
>>> from pyrocko import gf
>>> s = gf.DCSource()
>>> s.update(strike=66., dip=33.)
>>> print(s)
--- !pf.DCSource
depth: 0.0
time: 1970-01-01 00:00:00
magnitude: 6.0
strike: 66.0
dip: 33.0
rake: 0.0
'''
for (k, v) in kwargs.items():
self[k] = v
[docs] def grid(self, **variables):
'''
Create grid of source model variations.
:returns: :py:class:`SourceGrid` instance.
Example::
>>> from pyrocko import gf
>>> base = DCSource()
>>> R = gf.Range
>>> for s in base.grid(R('
'''
return SourceGrid(base=self, variables=variables)
[docs] def base_key(self):
'''
Get key to decide about source discretization / GF stack sharing.
When two source models differ only in amplitude and origin time, the
discretization and the GF stacking can be done only once for a unit
amplitude and a zero origin time and the amplitude and origin times of
the seismograms can be applied during post-processing of the synthetic
seismogram.
For any derived parameterized source model, this method is called to
decide if discretization and stacking of the source should be shared.
When two source models return an equal vector of values discretization
is shared.
'''
return (self.depth, self.lat, self.north_shift,
self.lon, self.east_shift, self.time, type(self).__name__) + \
self.effective_stf_pre().base_key()
[docs] def get_factor(self):
'''
Get the scaling factor to be applied during post-processing.
Discretization of the base seismogram is usually done for a unit
amplitude, because a common factor can be efficiently multiplied to
final seismograms. This eliminates to do repeat the stacking when
creating seismograms for a series of source models only differing in
amplitude.
This method should return the scaling factor to apply in the
post-processing (often this is simply the scalar moment of the source).
'''
return 1.0
[docs] def effective_stf_pre(self):
'''
Return the STF applied before stacking of the Green's functions.
This STF is used during discretization of the parameterized source
models, i.e. to produce a temporal distribution of point sources.
Handling of the STF before stacking of the GFs is less efficient but
allows to use different source time functions for different parts of
the source.
'''
if self.stf is not None and self.stf_mode == 'pre':
return self.stf
else:
return g_unit_pulse
[docs] def effective_stf_post(self):
'''
Return the STF applied after stacking of the Green's fuctions.
This STF is used in the post-processing of the synthetic seismograms.
Handling of the STF after stacking of the GFs is usually more efficient
but is only possible when a common STF is used for all subsources.
'''
if self.stf is not None and self.stf_mode == 'post':
return self.stf
else:
return g_unit_pulse
def _dparams_base(self):
return dict(times=arr(self.time),
lat=self.lat, lon=self.lon,
north_shifts=arr(self.north_shift),
east_shifts=arr(self.east_shift),
depths=arr(self.depth))
def _hash(self):
sha = sha1()
for k in self.base_key():
sha.update(str(k).encode())
return sha.hexdigest()
def _dparams_base_repeated(self, times):
if times is None:
return self._dparams_base()
nt = times.size
north_shifts = num.repeat(self.north_shift, nt)
east_shifts = num.repeat(self.east_shift, nt)
depths = num.repeat(self.depth, nt)
return dict(times=times,
lat=self.lat, lon=self.lon,
north_shifts=north_shifts,
east_shifts=east_shifts,
depths=depths)
def pyrocko_event(self, store=None, target=None, **kwargs):
duration = None
if self.stf:
duration = self.stf.effective_duration
return model.Event(
lat=self.lat,
lon=self.lon,
north_shift=self.north_shift,
east_shift=self.east_shift,
time=self.time,
name=self.name,
depth=self.depth,
duration=duration,
**kwargs)
def outline(self, cs='xyz'):
points = num.atleast_2d(num.zeros([1, 3]))
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
else:
return latlon[:, ::-1]
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
if ev.depth is None:
raise ConversionError(
'Cannot convert event object to source object: '
'no depth information available')
stf = None
if ev.duration is not None:
stf = HalfSinusoidSTF(effective_duration=ev.duration)
d = dict(
name=ev.name,
time=ev.time,
lat=ev.lat,
lon=ev.lon,
north_shift=ev.north_shift,
east_shift=ev.east_shift,
depth=ev.depth,
stf=stf)
d.update(kwargs)
return cls(**d)
def get_magnitude(self):
raise NotImplementedError(
'%s does not implement get_magnitude()'
% self.__class__.__name__)
[docs]class SourceWithMagnitude(Source):
'''
Base class for sources containing a moment magnitude.
'''
magnitude = Float.T(
default=6.0,
help='Moment magnitude Mw as in [Hanks and Kanamori, 1979]')
def __init__(self, **kwargs):
if 'moment' in kwargs:
mom = kwargs.pop('moment')
if 'magnitude' not in kwargs:
kwargs['magnitude'] = float(pmt.moment_to_magnitude(mom))
Source.__init__(self, **kwargs)
@property
def moment(self):
return float(pmt.magnitude_to_moment(self.magnitude))
@moment.setter
def moment(self, value):
self.magnitude = float(pmt.moment_to_magnitude(value))
def pyrocko_event(self, store=None, target=None, **kwargs):
return Source.pyrocko_event(
self, store, target,
magnitude=self.magnitude,
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
if ev.magnitude:
d.update(magnitude=ev.magnitude)
d.update(kwargs)
return super(SourceWithMagnitude, cls).from_pyrocko_event(ev, **d)
def get_magnitude(self):
return self.magnitude
[docs]class DerivedMagnitudeError(ValidationError):
pass
[docs]class SourceWithDerivedMagnitude(Source):
class __T(Source.T):
def validate_extra(self, val):
Source.T.validate_extra(self, val)
val.check_conflicts()
[docs] def check_conflicts(self):
'''
Check for parameter conflicts.
To be overloaded in subclasses. Raises :py:exc:`DerivedMagnitudeError`
on conflicts.
'''
pass
def get_magnitude(self, store=None, target=None):
raise DerivedMagnitudeError('No magnitude set.')
def get_moment(self, store=None, target=None):
return float(pmt.magnitude_to_moment(
self.get_magnitude(store, target)))
def pyrocko_moment_tensor(self, store=None, target=None):
raise NotImplementedError(
'%s does not implement pyrocko_moment_tensor()'
% self.__class__.__name__)
def pyrocko_event(self, store=None, target=None, **kwargs):
try:
mt = self.pyrocko_moment_tensor(store, target)
magnitude = self.get_magnitude()
except (DerivedMagnitudeError, NotImplementedError):
mt = None
magnitude = None
return Source.pyrocko_event(
self, store, target,
moment_tensor=mt,
magnitude=magnitude,
**kwargs)
[docs]class ExplosionSource(SourceWithDerivedMagnitude):
'''
An isotropic explosion point source.
'''
magnitude = Float.T(
optional=True,
help='moment magnitude Mw as in [Hanks and Kanamori, 1979]')
volume_change = Float.T(
optional=True,
help='volume change of the explosion/implosion or '
'the contracting/extending magmatic source. [m^3]')
discretized_source_class = meta.DiscretizedExplosionSource
def __init__(self, **kwargs):
if 'moment' in kwargs:
mom = kwargs.pop('moment')
if 'magnitude' not in kwargs:
kwargs['magnitude'] = float(pmt.moment_to_magnitude(mom))
SourceWithDerivedMagnitude.__init__(self, **kwargs)
[docs] def base_key(self):
return SourceWithDerivedMagnitude.base_key(self) + \
(self.volume_change,)
[docs] def check_conflicts(self):
if self.magnitude is not None and self.volume_change is not None:
raise DerivedMagnitudeError(
'Magnitude and volume_change are both defined.')
def get_magnitude(self, store=None, target=None):
self.check_conflicts()
if self.magnitude is not None:
return self.magnitude
elif self.volume_change is not None:
moment = self.volume_change * \
self.get_moment_to_volume_change_ratio(store, target)
return float(pmt.moment_to_magnitude(abs(moment)))
else:
return float(pmt.moment_to_magnitude(1.0))
def get_volume_change(self, store=None, target=None):
self.check_conflicts()
if self.volume_change is not None:
return self.volume_change
elif self.magnitude is not None:
moment = float(pmt.magnitude_to_moment(self.magnitude))
return moment / self.get_moment_to_volume_change_ratio(
store, target)
else:
return 1.0 / self.get_moment_to_volume_change_ratio(store)
def get_moment_to_volume_change_ratio(self, store, target=None):
if store is None:
raise DerivedMagnitudeError(
'Need earth model to convert between volume change and '
'magnitude.')
points = num.array(
[[self.north_shift, self.east_shift, self.depth]], dtype=float)
interpolation = target.interpolation if target else 'multilinear'
try:
shear_moduli = store.config.get_shear_moduli(
self.lat, self.lon,
points=points,
interpolation=interpolation)[0]
except meta.OutOfBounds:
raise DerivedMagnitudeError(
'Could not get shear modulus at source position.')
return float(3. * shear_moduli)
[docs] def get_factor(self):
return 1.0
def discretize_basesource(self, store, target=None):
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
amplitudes *= self.get_moment(store, target) * math.sqrt(2. / 3.)
if self.volume_change is not None:
if self.volume_change < 0.:
amplitudes *= -1
return meta.DiscretizedExplosionSource(
m0s=amplitudes,
**self._dparams_base_repeated(times))
def pyrocko_moment_tensor(self, store=None, target=None):
a = self.get_moment(store, target) * math.sqrt(2. / 3.)
return pmt.MomentTensor(m=pmt.symmat6(a, a, a, 0., 0., 0.))
[docs]class RectangularExplosionSource(ExplosionSource):
'''
Rectangular or line explosion source.
'''
discretized_source_class = meta.DiscretizedExplosionSource
strike = Float.T(
default=0.0,
help='strike direction in [deg], measured clockwise from north')
dip = Float.T(
default=90.0,
help='dip angle in [deg], measured downward from horizontal')
length = Float.T(
default=0.,
help='length of rectangular source area [m]')
width = Float.T(
default=0.,
help='width of rectangular source area [m]')
anchor = StringChoice.T(
choices=['top', 'top_left', 'top_right', 'center', 'bottom',
'bottom_left', 'bottom_right'],
default='center',
optional=True,
help='Anchor point for positioning the plane, can be: top, center or'
'bottom and also top_left, top_right,bottom_left,'
'bottom_right, center_left and center right')
nucleation_x = Float.T(
optional=True,
help='horizontal position of rupture nucleation in normalized fault '
'plane coordinates (-1 = left edge, +1 = right edge)')
nucleation_y = Float.T(
optional=True,
help='down-dip position of rupture nucleation in normalized fault '
'plane coordinates (-1 = upper edge, +1 = lower edge)')
velocity = Float.T(
default=3500.,
help='speed of explosion front [m/s]')
aggressive_oversampling = Bool.T(
default=False,
help='Aggressive oversampling for basesource discretization. '
'When using \'multilinear\' interpolation oversampling has'
' practically no effect.')
[docs] def base_key(self):
return Source.base_key(self) + (self.strike, self.dip, self.length,
self.width, self.nucleation_x,
self.nucleation_y, self.velocity,
self.anchor)
def discretize_basesource(self, store, target=None):
if self.nucleation_x is not None:
nucx = self.nucleation_x * 0.5 * self.length
else:
nucx = None
if self.nucleation_y is not None:
nucy = self.nucleation_y * 0.5 * self.width
else:
nucy = None
stf = self.effective_stf_pre()
points, times, amplitudes, dl, dw, nl, nw = discretize_rect_source(
store.config.deltas, store.config.deltat,
self.time, self.north_shift, self.east_shift, self.depth,
self.strike, self.dip, self.length, self.width, self.anchor,
self.velocity, stf=stf, nucleation_x=nucx, nucleation_y=nucy)
amplitudes /= num.sum(amplitudes)
amplitudes *= self.get_moment(store, target)
return meta.DiscretizedExplosionSource(
lat=self.lat,
lon=self.lon,
times=times,
north_shifts=points[:, 0],
east_shifts=points[:, 1],
depths=points[:, 2],
m0s=amplitudes)
def outline(self, cs='xyz'):
points = outline_rect_source(self.strike, self.dip, self.length,
self.width, self.anchor)
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
else:
return latlon[:, ::-1]
def get_nucleation_abs_coord(self, cs='xy'):
if self.nucleation_x is None:
return None, None
coords = from_plane_coords(self.strike, self.dip, self.length,
self.width, self.depth, self.nucleation_x,
self.nucleation_y, lat=self.lat,
lon=self.lon, north_shift=self.north_shift,
east_shift=self.east_shift, cs=cs)
return coords
[docs]class DCSource(SourceWithMagnitude):
'''
A double-couple point source.
'''
strike = Float.T(
default=0.0,
help='strike direction in [deg], measured clockwise from north')
dip = Float.T(
default=90.0,
help='dip angle in [deg], measured downward from horizontal')
rake = Float.T(
default=0.0,
help='rake angle in [deg], '
'measured counter-clockwise from right-horizontal '
'in on-plane view')
discretized_source_class = meta.DiscretizedMTSource
[docs] def base_key(self):
return Source.base_key(self) + (self.strike, self.dip, self.rake)
[docs] def get_factor(self):
return float(pmt.magnitude_to_moment(self.magnitude))
def discretize_basesource(self, store, target=None):
mot = pmt.MomentTensor(
strike=self.strike, dip=self.dip, rake=self.rake)
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
return meta.DiscretizedMTSource(
m6s=mot.m6()[num.newaxis, :] * amplitudes[:, num.newaxis],
**self._dparams_base_repeated(times))
def pyrocko_moment_tensor(self, store=None, target=None):
return pmt.MomentTensor(
strike=self.strike,
dip=self.dip,
rake=self.rake,
scalar_moment=self.moment)
def pyrocko_event(self, store=None, target=None, **kwargs):
return SourceWithMagnitude.pyrocko_event(
self, store, target,
moment_tensor=self.pyrocko_moment_tensor(store, target),
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
mt = ev.moment_tensor
if mt:
(strike, dip, rake), _ = mt.both_strike_dip_rake()
d.update(
strike=float(strike),
dip=float(dip),
rake=float(rake),
magnitude=float(mt.moment_magnitude()))
d.update(kwargs)
return super(DCSource, cls).from_pyrocko_event(ev, **d)
[docs]class CLVDSource(SourceWithMagnitude):
'''
A pure CLVD point source.
'''
discretized_source_class = meta.DiscretizedMTSource
azimuth = Float.T(
default=0.0,
help='azimuth direction of largest dipole, clockwise from north [deg]')
dip = Float.T(
default=90.,
help='dip direction of largest dipole, downward from horizontal [deg]')
[docs] def base_key(self):
return Source.base_key(self) + (self.azimuth, self.dip)
[docs] def get_factor(self):
return float(pmt.magnitude_to_moment(self.magnitude))
@property
def m6(self):
a = math.sqrt(4. / 3.) * self.get_factor()
m = pmt.symmat6(-0.5 * a, -0.5 * a, a, 0., 0., 0.)
rotmat1 = pmt.euler_to_matrix(
d2r * (self.dip - 90.),
d2r * (self.azimuth - 90.),
0.)
m = rotmat1.T * m * rotmat1
return pmt.to6(m)
@property
def m6_astuple(self):
return tuple(self.m6.tolist())
def discretize_basesource(self, store, target=None):
factor = self.get_factor()
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
return meta.DiscretizedMTSource(
m6s=self.m6[num.newaxis, :] * amplitudes[:, num.newaxis] / factor,
**self._dparams_base_repeated(times))
def pyrocko_moment_tensor(self, store=None, target=None):
return pmt.MomentTensor(m=pmt.symmat6(*self.m6_astuple))
def pyrocko_event(self, store=None, target=None, **kwargs):
mt = self.pyrocko_moment_tensor(store, target)
return Source.pyrocko_event(
self, store, target,
moment_tensor=self.pyrocko_moment_tensor(store, target),
magnitude=float(mt.moment_magnitude()),
**kwargs)
[docs]class VLVDSource(SourceWithDerivedMagnitude):
'''
Volumetric linear vector dipole source.
This source is a parameterization for a restricted moment tensor point
source, useful to represent dyke or sill like inflation or deflation
sources. The restriction is such that the moment tensor is rotational
symmetric. It can be represented by a superposition of a linear vector
dipole (here we use a CLVD for convenience) and an isotropic component. The
restricted moment tensor has 4 degrees of freedom: 2 independent
eigenvalues and 2 rotation angles orienting the the symmetry axis.
In this parameterization, the isotropic component is controlled by
``volume_change``. To define the moment tensor, it must be converted to the
scalar moment of the the MT's isotropic component. For the conversion, the
shear modulus at the source's position must be known. This value is
extracted from the earth model defined in the GF store in use.
The CLVD part by controlled by its scalar moment :math:`M_0`:
``clvd_moment``. The sign of ``clvd_moment`` is used to switch between a
positiv or negativ CLVD (the sign of the largest eigenvalue).
'''
discretized_source_class = meta.DiscretizedMTSource
azimuth = Float.T(
default=0.0,
help='azimuth direction of symmetry axis, clockwise from north [deg].')
dip = Float.T(
default=90.,
help='dip direction of symmetry axis, downward from horizontal [deg].')
volume_change = Float.T(
default=0.,
help='volume change of the inflation/deflation [m^3].')
clvd_moment = Float.T(
default=0.,
help='scalar moment :math:`M_0` of the CLVD component [Nm]. The sign '
'controls the sign of the CLVD (the sign of its largest '
'eigenvalue).')
def get_moment_to_volume_change_ratio(self, store, target):
if store is None or target is None:
raise DerivedMagnitudeError(
'Need earth model to convert between volume change and '
'magnitude.')
points = num.array(
[[self.north_shift, self.east_shift, self.depth]], dtype=float)
try:
shear_moduli = store.config.get_shear_moduli(
self.lat, self.lon,
points=points,
interpolation=target.interpolation)[0]
except meta.OutOfBounds:
raise DerivedMagnitudeError(
'Could not get shear modulus at source position.')
return float(3. * shear_moduli)
[docs] def base_key(self):
return Source.base_key(self) + \
(self.azimuth, self.dip, self.volume_change, self.clvd_moment)
def get_magnitude(self, store=None, target=None):
mt = self.pyrocko_moment_tensor(store, target)
return float(pmt.moment_to_magnitude(mt.moment))
def get_m6(self, store, target):
a = math.sqrt(4. / 3.) * self.clvd_moment
m_clvd = pmt.symmat6(-0.5 * a, -0.5 * a, a, 0., 0., 0.)
rotmat1 = pmt.euler_to_matrix(
d2r * (self.dip - 90.),
d2r * (self.azimuth - 90.),
0.)
m_clvd = rotmat1.T * m_clvd * rotmat1
m_iso = self.volume_change * \
self.get_moment_to_volume_change_ratio(store, target)
m_iso = pmt.symmat6(m_iso, m_iso, m_iso, 0.,
0., 0.,) * math.sqrt(2. / 3)
m = pmt.to6(m_clvd) + pmt.to6(m_iso)
return m
def get_moment(self, store=None, target=None):
return float(pmt.magnitude_to_moment(
self.get_magnitude(store, target)))
def get_m6_astuple(self, store, target):
m6 = self.get_m6(store, target)
return tuple(m6.tolist())
def discretize_basesource(self, store, target=None):
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
m6 = self.get_m6(store, target)
m6 *= amplitudes / self.get_factor()
return meta.DiscretizedMTSource(
m6s=m6[num.newaxis, :],
**self._dparams_base_repeated(times))
def pyrocko_moment_tensor(self, store=None, target=None):
m6_astuple = self.get_m6_astuple(store, target)
return pmt.MomentTensor(m=pmt.symmat6(*m6_astuple))
[docs]class MTSource(Source):
'''
A moment tensor point source.
'''
discretized_source_class = meta.DiscretizedMTSource
mnn = Float.T(
default=1.,
help='north-north component of moment tensor in [Nm]')
mee = Float.T(
default=1.,
help='east-east component of moment tensor in [Nm]')
mdd = Float.T(
default=1.,
help='down-down component of moment tensor in [Nm]')
mne = Float.T(
default=0.,
help='north-east component of moment tensor in [Nm]')
mnd = Float.T(
default=0.,
help='north-down component of moment tensor in [Nm]')
med = Float.T(
default=0.,
help='east-down component of moment tensor in [Nm]')
def __init__(self, **kwargs):
if 'm6' in kwargs:
for (k, v) in zip('mnn mee mdd mne mnd med'.split(),
kwargs.pop('m6')):
kwargs[k] = float(v)
Source.__init__(self, **kwargs)
@property
def m6(self):
return num.array(self.m6_astuple)
@property
def m6_astuple(self):
return (self.mnn, self.mee, self.mdd, self.mne, self.mnd, self.med)
@m6.setter
def m6(self, value):
self.mnn, self.mee, self.mdd, self.mne, self.mnd, self.med = value
[docs] def base_key(self):
return Source.base_key(self) + self.m6_astuple
def discretize_basesource(self, store, target=None):
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
return meta.DiscretizedMTSource(
m6s=self.m6[num.newaxis, :] * amplitudes[:, num.newaxis],
**self._dparams_base_repeated(times))
def get_magnitude(self, store=None, target=None):
m6 = self.m6
return pmt.moment_to_magnitude(
math.sqrt(num.sum(m6[0:3]**2) + 2.0 * num.sum(m6[3:6]**2)) /
math.sqrt(2.))
def pyrocko_moment_tensor(self, store=None, target=None):
return pmt.MomentTensor(m=pmt.symmat6(*self.m6_astuple))
def pyrocko_event(self, store=None, target=None, **kwargs):
mt = self.pyrocko_moment_tensor(store, target)
return Source.pyrocko_event(
self, store, target,
moment_tensor=self.pyrocko_moment_tensor(store, target),
magnitude=float(mt.moment_magnitude()),
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
mt = ev.moment_tensor
if mt:
d.update(m6=tuple(map(float, mt.m6())))
else:
if ev.magnitude is not None:
mom = pmt.magnitude_to_moment(ev.magnitude)
v = math.sqrt(2. / 3.) * mom
d.update(m6=(v, v, v, 0., 0., 0.))
d.update(kwargs)
return super(MTSource, cls).from_pyrocko_event(ev, **d)
map_anchor = {
'center': (0.0, 0.0),
'center_left': (-1.0, 0.0),
'center_right': (1.0, 0.0),
'top': (0.0, -1.0),
'top_left': (-1.0, -1.0),
'top_right': (1.0, -1.0),
'bottom': (0.0, 1.0),
'bottom_left': (-1.0, 1.0),
'bottom_right': (1.0, 1.0)}
[docs]class RectangularSource(SourceWithDerivedMagnitude):
'''
Classical Haskell source model modified for bilateral rupture.
'''
discretized_source_class = meta.DiscretizedMTSource
magnitude = Float.T(
optional=True,
help='moment magnitude Mw as in [Hanks and Kanamori, 1979]')
strike = Float.T(
default=0.0,
help='strike direction in [deg], measured clockwise from north')
dip = Float.T(
default=90.0,
help='dip angle in [deg], measured downward from horizontal')
rake = Float.T(
default=0.0,
help='rake angle in [deg], '
'measured counter-clockwise from right-horizontal '
'in on-plane view')
length = Float.T(
default=0.,
help='length of rectangular source area [m]')
width = Float.T(
default=0.,
help='width of rectangular source area [m]')
anchor = StringChoice.T(
choices=['top', 'top_left', 'top_right', 'center', 'bottom',
'bottom_left', 'bottom_right'],
default='center',
optional=True,
help='Anchor point for positioning the plane, can be: ``top, center '
'bottom, top_left, top_right,bottom_left,'
'bottom_right, center_left, center right``.')
nucleation_x = Float.T(
optional=True,
help='horizontal position of rupture nucleation in normalized fault '
'plane coordinates (``-1.`` = left edge, ``+1.`` = right edge)')
nucleation_y = Float.T(
optional=True,
help='down-dip position of rupture nucleation in normalized fault '
'plane coordinates (``-1.`` = upper edge, ``+1.`` = lower edge)')
velocity = Float.T(
default=3500.,
help='speed of rupture front [m/s]')
slip = Float.T(
optional=True,
help='Slip on the rectangular source area [m]')
opening_fraction = Float.T(
default=0.,
help='Determines fraction of slip related to opening. '
'(``-1``: pure tensile closing, '
'``0``: pure shear, '
'``1``: pure tensile opening)')
decimation_factor = Int.T(
optional=True,
default=1,
help='Sub-source decimation factor, a larger decimation will'
' make the result inaccurate but shorten the necessary'
' computation time (use for testing puposes only).')
aggressive_oversampling = Bool.T(
default=False,
help='Aggressive oversampling for basesource discretization. '
'When using \'multilinear\' interpolation oversampling has'
' practically no effect.')
def __init__(self, **kwargs):
if 'moment' in kwargs:
mom = kwargs.pop('moment')
if 'magnitude' not in kwargs:
kwargs['magnitude'] = float(pmt.moment_to_magnitude(mom))
SourceWithDerivedMagnitude.__init__(self, **kwargs)
[docs] def base_key(self):
return SourceWithDerivedMagnitude.base_key(self) + (
self.magnitude,
self.slip,
self.strike,
self.dip,
self.rake,
self.length,
self.width,
self.nucleation_x,
self.nucleation_y,
self.velocity,
self.decimation_factor,
self.anchor)
[docs] def check_conflicts(self):
if self.magnitude is not None and self.slip is not None:
raise DerivedMagnitudeError(
'Magnitude and slip are both defined.')
def get_magnitude(self, store=None, target=None):
self.check_conflicts()
if self.magnitude is not None:
return self.magnitude
elif self.slip is not None:
if None in (store, target):
raise DerivedMagnitudeError(
'Magnitude for a rectangular source with slip defined '
'can only be derived when earth model and target '
'interpolation method are available.')
amplitudes = self._discretize(store, target)[2]
if amplitudes.ndim == 2:
# CLVD component has no net moment, leave out
return float(pmt.moment_to_magnitude(
num.sum(num.abs(amplitudes[0:2, :]).sum())))
else:
return float(pmt.moment_to_magnitude(num.sum(amplitudes)))
else:
return float(pmt.moment_to_magnitude(1.0))
[docs] def get_factor(self):
return 1.0
def get_slip_tensile(self):
return self.slip * self.opening_fraction
def get_slip_shear(self):
return self.slip - abs(self.get_slip_tensile)
def _discretize(self, store, target):
if self.nucleation_x is not None:
nucx = self.nucleation_x * 0.5 * self.length
else:
nucx = None
if self.nucleation_y is not None:
nucy = self.nucleation_y * 0.5 * self.width
else:
nucy = None
stf = self.effective_stf_pre()
points, times, amplitudes, dl, dw, nl, nw = discretize_rect_source(
store.config.deltas, store.config.deltat,
self.time, self.north_shift, self.east_shift, self.depth,
self.strike, self.dip, self.length, self.width, self.anchor,
self.velocity, stf=stf, nucleation_x=nucx, nucleation_y=nucy,
decimation_factor=self.decimation_factor,
aggressive_oversampling=self.aggressive_oversampling)
if self.slip is not None:
if target is not None:
interpolation = target.interpolation
else:
interpolation = 'nearest_neighbor'
logger.warn(
'no target information available, will use '
'"nearest_neighbor" interpolation when extracting shear '
'modulus from earth model')
shear_moduli = store.config.get_shear_moduli(
self.lat, self.lon,
points=points,
interpolation=interpolation)
tensile_slip = self.get_slip_tensile()
shear_slip = self.slip - abs(tensile_slip)
amplitudes_total = [shear_moduli * shear_slip]
if tensile_slip != 0:
bulk_moduli = store.config.get_bulk_moduli(
self.lat, self.lon,
points=points,
interpolation=interpolation)
tensile_iso = bulk_moduli * tensile_slip
tensile_clvd = (2. / 3.) * shear_moduli * tensile_slip
amplitudes_total.extend([tensile_iso, tensile_clvd])
amplitudes_total = num.vstack(amplitudes_total).squeeze() * \
amplitudes * dl * dw
else:
# normalization to retain total moment
amplitudes_norm = amplitudes / num.sum(amplitudes)
moment = self.get_moment(store, target)
amplitudes_total = [
amplitudes_norm * moment * (1 - abs(self.opening_fraction))]
if self.opening_fraction != 0.:
amplitudes_total.append(
amplitudes_norm * self.opening_fraction * moment)
amplitudes_total = num.vstack(amplitudes_total).squeeze()
return points, times, num.atleast_1d(amplitudes_total), dl, dw, nl, nw
def discretize_basesource(self, store, target=None):
points, times, amplitudes, dl, dw, nl, nw = self._discretize(
store, target)
mot = pmt.MomentTensor(
strike=self.strike, dip=self.dip, rake=self.rake)
m6s = num.repeat(mot.m6()[num.newaxis, :], times.size, axis=0)
if amplitudes.ndim == 1:
m6s[:, :] *= amplitudes[:, num.newaxis]
elif amplitudes.ndim == 2:
# shear MT components
rotmat1 = pmt.euler_to_matrix(
d2r * self.dip, d2r * self.strike, d2r * -self.rake)
m6s[:, :] *= amplitudes[0, :][:, num.newaxis]
if amplitudes.shape[0] == 2:
# tensile MT components - moment/magnitude input
tensile = pmt.symmat6(1., 1., 3., 0., 0., 0.)
rot_tensile = pmt.to6(rotmat1.T * tensile * rotmat1)
m6s_tensile = rot_tensile[
num.newaxis, :] * amplitudes[1, :][:, num.newaxis]
m6s += m6s_tensile
elif amplitudes.shape[0] == 3:
# tensile MT components - slip input
iso = pmt.symmat6(1., 1., 1., 0., 0., 0.)
clvd = pmt.symmat6(-1., -1., 2., 0., 0., 0.)
rot_iso = pmt.to6(rotmat1.T * iso * rotmat1)
rot_clvd = pmt.to6(rotmat1.T * clvd * rotmat1)
m6s_iso = rot_iso[
num.newaxis, :] * amplitudes[1, :][:, num.newaxis]
m6s_clvd = rot_clvd[
num.newaxis, :] * amplitudes[2, :][:, num.newaxis]
m6s += m6s_iso + m6s_clvd
else:
raise ValueError('Unknwown amplitudes shape!')
else:
raise ValueError(
'Unexpected dimension of {}'.format(amplitudes.ndim))
ds = meta.DiscretizedMTSource(
lat=self.lat,
lon=self.lon,
times=times,
north_shifts=points[:, 0],
east_shifts=points[:, 1],
depths=points[:, 2],
m6s=m6s,
dl=dl,
dw=dw,
nl=nl,
nw=nw)
return ds
def outline(self, cs='xyz'):
points = outline_rect_source(self.strike, self.dip, self.length,
self.width, self.anchor)
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat', 'latlondepth'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
elif cs == 'lonlat':
return latlon[:, ::-1]
else:
return num.concatenate(
(latlon, points[:, 2].reshape((len(points), 1))),
axis=1)
def points_on_source(self, cs='xyz', **kwargs):
points = points_on_rect_source(
self.strike, self.dip, self.length, self.width,
self.anchor, **kwargs)
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat', 'latlondepth'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
elif cs == 'lonlat':
return latlon[:, ::-1]
else:
return num.concatenate(
(latlon, points[:, 2].reshape((len(points), 1))),
axis=1)
def get_nucleation_abs_coord(self, cs='xy'):
if self.nucleation_x is None:
return None, None
coords = from_plane_coords(self.strike, self.dip, self.length,
self.width, self.depth, self.nucleation_x,
self.nucleation_y, lat=self.lat,
lon=self.lon, north_shift=self.north_shift,
east_shift=self.east_shift, cs=cs)
return coords
def pyrocko_moment_tensor(self, store=None, target=None):
return pmt.MomentTensor(
strike=self.strike,
dip=self.dip,
rake=self.rake,
scalar_moment=self.get_moment(store, target))
def pyrocko_event(self, store=None, target=None, **kwargs):
return SourceWithDerivedMagnitude.pyrocko_event(
self, store, target,
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
mt = ev.moment_tensor
if mt:
(strike, dip, rake), _ = mt.both_strike_dip_rake()
d.update(
strike=float(strike),
dip=float(dip),
rake=float(rake),
magnitude=float(mt.moment_magnitude()))
d.update(kwargs)
return super(RectangularSource, cls).from_pyrocko_event(ev, **d)
[docs]class PseudoDynamicRupture(SourceWithDerivedMagnitude):
'''
Combined Eikonal and Okada quasi-dynamic rupture model.
Details are described in :doc:`/topics/pseudo-dynamic-rupture`.
Note: attribute `stf` is not used so far, but kept for future applications.
'''
discretized_source_class = meta.DiscretizedMTSource
strike = Float.T(
default=0.0,
help='Strike direction in [deg], measured clockwise from north.')
dip = Float.T(
default=0.0,
help='Dip angle in [deg], measured downward from horizontal.')
length = Float.T(
default=10. * km,
help='Length of rectangular source area in [m].')
width = Float.T(
default=5. * km,
help='Width of rectangular source area in [m].')
anchor = StringChoice.T(
choices=['top', 'top_left', 'top_right', 'center', 'bottom',
'bottom_left', 'bottom_right'],
default='center',
optional=True,
help='Anchor point for positioning the plane, can be: ``top, center, '
'bottom, top_left, top_right, bottom_left, '
'bottom_right, center_left, center_right``.')
nucleation_x__ = Array.T(
default=num.array([0.]),
dtype=num.float,
serialize_as='list',
help='Horizontal position of rupture nucleation in normalized fault '
'plane coordinates (``-1.`` = left edge, ``+1.`` = right edge).')
nucleation_y__ = Array.T(
default=num.array([0.]),
dtype=num.float,
serialize_as='list',
help='Down-dip position of rupture nucleation in normalized fault '
'plane coordinates (``-1.`` = upper edge, ``+1.`` = lower edge).')
nucleation_time__ = Array.T(
optional=True,
help='Time in [s] after origin, when nucleation points defined by '
'``nucleation_x`` and ``nucleation_y`` rupture.',
dtype=num.float,
serialize_as='list')
gamma = Float.T(
default=0.8,
help='Scaling factor between rupture velocity and S-wave velocity: '
r':math:`v_r = \gamma * v_s`.')
nx = Int.T(
default=2,
help='Number of discrete source patches in x direction (along '
'strike).')
ny = Int.T(
default=2,
help='Number of discrete source patches in y direction (down dip).')
slip = Float.T(
optional=True,
help='Maximum slip of the rectangular source [m]. '
'Setting the slip the tractions/stress field '
'will be normalized to accomodate the desired maximum slip.')
rake = Float.T(
optional=True,
help='Rake angle in [deg], '
'measured counter-clockwise from right-horizontal '
'in on-plane view. Rake is translated into homogenous tractions '
'in strike and up-dip direction. ``rake`` is mutually exclusive '
'with tractions parameter.')
patches = List.T(
OkadaSource.T(),
optional=True,
help='List of all boundary elements/sub faults/fault patches.')
patch_mask__ = Array.T(
dtype=num.bool,
serialize_as='list',
shape=(None,),
optional=True,
help='Mask for all boundary elements/sub faults/fault patches. True '
'leaves the patch in the calculation, False excludes the patch.')
tractions = TractionField.T(
optional=True,
help='Traction field the rupture plane is exposed to. See the'
':py:mod:`pyrocko.gf.tractions` module for more details. '
'If ``tractions=None`` and ``rake`` is given'
' :py:class:`~pyrocko.gf.tractions.DirectedTractions` will'
' be used.')
coef_mat = Array.T(
optional=True,
help='Coefficient matrix linking traction and dislocation field.',
dtype=num.float,
shape=(None, None))
eikonal_decimation = Int.T(
optional=True,
default=1,
help='Sub-source eikonal factor, a smaller eikonal factor will'
' increase the accuracy of rupture front calculation but'
' increases also the computation time.')
decimation_factor = Int.T(
optional=True,
default=1,
help='Sub-source decimation factor, a larger decimation will'
' make the result inaccurate but shorten the necessary'
' computation time (use for testing puposes only).')
nthreads = Int.T(
optional=True,
default=1,
help='Number of threads for Okada forward modelling, '
'matrix inversion and calculation of point subsources. '
'Note: for small/medium matrices 1 thread is most efficient.')
pure_shear = Bool.T(
optional=True,
default=False,
help='Calculate only shear tractions and omit tensile tractions.')
smooth_rupture = Bool.T(
default=True,
help='Smooth the tractions by weighting partially ruptured'
' fault patches.')
aggressive_oversampling = Bool.T(
default=False,
help='Aggressive oversampling for basesource discretization. '
'When using \'multilinear\' interpolation oversampling has'
' practically no effect.')
def __init__(self, **kwargs):
SourceWithDerivedMagnitude.__init__(self, **kwargs)
self._interpolators = {}
self.check_conflicts()
@property
def nucleation_x(self):
return self.nucleation_x__
@nucleation_x.setter
def nucleation_x(self, nucleation_x):
if isinstance(nucleation_x, list):
nucleation_x = num.array(nucleation_x)
elif not isinstance(
nucleation_x, num.ndarray) and nucleation_x is not None:
nucleation_x = num.array([nucleation_x])
self.nucleation_x__ = nucleation_x
@property
def nucleation_y(self):
return self.nucleation_y__
@nucleation_y.setter
def nucleation_y(self, nucleation_y):
if isinstance(nucleation_y, list):
nucleation_y = num.array(nucleation_y)
elif not isinstance(nucleation_y, num.ndarray) \
and nucleation_y is not None:
nucleation_y = num.array([nucleation_y])
self.nucleation_y__ = nucleation_y
@property
def nucleation(self):
nucl_x, nucl_y = self.nucleation_x, self.nucleation_y
if (nucl_x is None) or (nucl_y is None):
return None
assert nucl_x.shape[0] == nucl_y.shape[0]
return num.concatenate(
(nucl_x[:, num.newaxis], nucl_y[:, num.newaxis]), axis=1)
@nucleation.setter
def nucleation(self, nucleation):
if isinstance(nucleation, list):
nucleation = num.array(nucleation)
assert nucleation.shape[1] == 2
self.nucleation_x = nucleation[:, 0]
self.nucleation_y = nucleation[:, 1]
@property
def nucleation_time(self):
return self.nucleation_time__
@nucleation_time.setter
def nucleation_time(self, nucleation_time):
if not isinstance(nucleation_time, num.ndarray) \
and nucleation_time is not None:
nucleation_time = num.array([nucleation_time])
self.nucleation_time__ = nucleation_time
@property
def patch_mask(self):
if (self.patch_mask__ is not None and
self.patch_mask__.shape == (self.nx * self.ny,)):
return self.patch_mask__
else:
return num.ones(self.nx * self.ny, dtype=bool)
@patch_mask.setter
def patch_mask(self, patch_mask):
if isinstance(patch_mask, list):
patch_mask = num.array(patch_mask)
self.patch_mask__ = patch_mask
[docs] def get_tractions(self):
'''
Get source traction vectors.
If :py:attr:`rake` is given, unit length directed traction vectors
(:py:class:`~pyrocko.gf.tractions.DirectedTractions`) are returned,
else the given :py:attr:`tractions` are used.
:returns:
Traction vectors per patch.
:rtype:
:py:class:`~numpy.ndarray`: ``(n_patches, 3)``.
'''
if self.rake is not None:
if num.isnan(self.rake):
raise ValueError('Rake must be a real number, not NaN.')
logger.warning(
'Tractions are derived based on the given source rake.')
tractions = DirectedTractions(rake=self.rake)
else:
tractions = self.tractions
return tractions.get_tractions(self.nx, self.ny, self.patches)
[docs] def base_key(self):
return SourceWithDerivedMagnitude.base_key(self) + (
self.slip,
self.strike,
self.dip,
self.rake,
self.length,
self.width,
float(self.nucleation_x.mean()),
float(self.nucleation_y.mean()),
self.decimation_factor,
self.anchor,
self.pure_shear,
self.gamma,
tuple(self.patch_mask))
[docs] def check_conflicts(self):
if self.tractions and self.rake:
raise AttributeError(
'Tractions and rake are mutually exclusive.')
if self.tractions is None and self.rake is None:
self.rake = 0.
def get_magnitude(self, store=None, target=None):
self.check_conflicts()
if self.slip is not None or self.tractions is not None:
if store is None:
raise DerivedMagnitudeError(
'Magnitude for a rectangular source with slip or '
'tractions defined can only be derived when earth model '
'is set.')
moment_rate, calc_times = self.discretize_basesource(
store, target=target).get_moment_rate(store.config.deltat)
deltat = num.concatenate((
(num.diff(calc_times)[0],),
num.diff(calc_times)))
return float(pmt.moment_to_magnitude(
num.sum(moment_rate * deltat)))
else:
return float(pmt.moment_to_magnitude(1.0))
[docs] def get_factor(self):
return 1.0
[docs] def outline(self, cs='xyz'):
'''
Get source outline corner coordinates.
:param cs:
:ref:`Output coordinate system <coordinate-system-names>`.
:type cs:
optional, str
:returns:
Corner points in desired coordinate system.
:rtype:
:py:class:`~numpy.ndarray`: ``(5, [2, 3])``.
'''
points = outline_rect_source(self.strike, self.dip, self.length,
self.width, self.anchor)
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat', 'latlondepth'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
elif cs == 'lonlat':
return latlon[:, ::-1]
else:
return num.concatenate(
(latlon, points[:, 2].reshape((len(points), 1))),
axis=1)
[docs] def points_on_source(self, cs='xyz', **kwargs):
'''
Convert relative plane coordinates to geographical coordinates.
Given x and y coordinates (relative source coordinates between -1.
and 1.) are converted to desired geographical coordinates. Coordinates
need to be given as :py:class:`~numpy.ndarray` arguments ``points_x``
and ``points_y``.
:param cs:
:ref:`Output coordinate system <coordinate-system-names>`.
:type cs:
optional, str
:returns:
Point coordinates in desired coordinate system.
:rtype:
:py:class:`~numpy.ndarray`: ``(n_points, [2, 3])``.
'''
points = points_on_rect_source(
self.strike, self.dip, self.length, self.width,
self.anchor, **kwargs)
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
if cs == 'xyz':
return points
elif cs == 'xy':
return points[:, :2]
elif cs in ('latlon', 'lonlat', 'latlondepth'):
latlon = ne_to_latlon(
self.lat, self.lon, points[:, 0], points[:, 1])
latlon = num.array(latlon).T
if cs == 'latlon':
return latlon
elif cs == 'lonlat':
return latlon[:, ::-1]
else:
return num.concatenate(
(latlon, points[:, 2].reshape((len(points), 1))),
axis=1)
def pyrocko_moment_tensor(self, store=None, target=None):
# TODO: Now this should be slip, then it depends on the store.
# TODO: default to tractions is store is not given?
tractions = self.get_tractions()
tractions = tractions.mean(axis=0)
rake = num.arctan2(tractions[1], tractions[0]) # arctan2(dip, slip)
return pmt.MomentTensor(
strike=self.strike,
dip=self.dip,
rake=rake,
scalar_moment=self.get_moment(store, target))
def pyrocko_event(self, store=None, target=None, **kwargs):
return SourceWithDerivedMagnitude.pyrocko_event(
self, store, target,
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
mt = ev.moment_tensor
if mt:
(strike, dip, rake), _ = mt.both_strike_dip_rake()
d.update(
strike=float(strike),
dip=float(dip),
rake=float(rake))
d.update(kwargs)
return super(PseudoDynamicRupture, cls).from_pyrocko_event(ev, **d)
def _discretize_points(self, store, *args, **kwargs):
'''
Discretize source plane with equal vertical and horizontal spacing.
Additional ``*args`` and ``**kwargs`` are passed to
:py:meth:`points_on_source`.
:param store:
Green's function database (needs to cover whole region of the
source).
:type store:
:py:class:`~pyrocko.gf.store.Store`
:returns:
Number of points in strike and dip direction, distance
between adjacent points, coordinates (latlondepth) and coordinates
(xy on fault) for discrete points.
:rtype:
(int, int, float, :py:class:`~numpy.ndarray`,
:py:class:`~numpy.ndarray`).
'''
anch_x, anch_y = map_anchor[self.anchor]
npoints = int(self.width // km) + 1
points = num.zeros((npoints, 3))
points[:, 1] = num.linspace(-1., 1., npoints)
points[:, 1] = (points[:, 1] - anch_y) * self.width/2
rotmat = num.asarray(
pmt.euler_to_matrix(self.dip*d2r, self.strike*d2r, 0.0))
points = num.dot(rotmat.T, points.T).T
points[:, 2] += self.depth
vs_min = store.config.get_vs(
self.lat, self.lon, points,
interpolation='nearest_neighbor')
vr_min = max(vs_min.min(), .5*km) * self.gamma
oversampling = 10.
delta_l = self.length / (self.nx * oversampling)
delta_w = self.width / (self.ny * oversampling)
delta = self.eikonal_decimation * num.min([
store.config.deltat * vr_min / oversampling,
delta_l, delta_w] + [
deltas for deltas in store.config.deltas])
delta = delta_w / num.ceil(delta_w / delta)
nx = int(num.ceil(self.length / delta)) + 1
ny = int(num.ceil(self.width / delta)) + 1
rem_l = (nx-1)*delta - self.length
lim_x = rem_l / self.length
points_xy = num.zeros((nx * ny, 2))
points_xy[:, 0] = num.repeat(
num.linspace(-1.-lim_x, 1.+lim_x, nx), ny)
points_xy[:, 1] = num.tile(
num.linspace(-1., 1., ny), nx)
points = self.points_on_source(
points_x=points_xy[:, 0],
points_y=points_xy[:, 1],
**kwargs)
return nx, ny, delta, points, points_xy
def _discretize_rupture_v(self, store, interpolation='nearest_neighbor',
points=None):
'''
Get rupture velocity for discrete points on source plane.
:param store:
Green's function database (needs to cover the whole region of the
source)
:type store:
optional, :py:class:`~pyrocko.gf.store.Store`
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:param points:
Coordinates on fault (-1.:1.) of discrete points.
:type points:
optional, :py:class:`~numpy.ndarray`: ``(n_points, 2)``
:returns:
Rupture velocity assumed as :math:`v_s * \\gamma` for discrete
points.
:rtype:
:py:class:`~numpy.ndarray`: ``(n_points, )``.
'''
if points is None:
_, _, _, points, _ = self._discretize_points(store, cs='xyz')
return store.config.get_vs(
self.lat, self.lon,
points=points,
interpolation=interpolation) * self.gamma
[docs] def discretize_time(
self, store, interpolation='nearest_neighbor',
vr=None, times=None, *args, **kwargs):
'''
Get rupture start time for discrete points on source plane.
:param store:
Green's function database (needs to cover whole region of the
source)
:type store:
:py:class:`~pyrocko.gf.store.Store`
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:param vr:
Array, containing rupture user defined rupture velocity values.
:type vr:
optional, :py:class:`~numpy.ndarray`
:param times:
Array, containing zeros, where rupture is starting, real positive
numbers at later secondary nucleation points and -1, where time
will be calculated. If not given, rupture starts at nucleation_x,
nucleation_y. Times are given for discrete points with equal
horizontal and vertical spacing.
:type times:
optional, :py:class:`~numpy.ndarray`
:returns:
Coordinates (latlondepth), coordinates (xy), rupture velocity,
rupture propagation time of discrete points.
:rtype:
:py:class:`~numpy.ndarray`: ``(n_points, 3)``,
:py:class:`~numpy.ndarray`: ``(n_points, 2)``,
:py:class:`~numpy.ndarray`: ``(n_points_dip, n_points_strike)``,
:py:class:`~numpy.ndarray`: ``(n_points_dip, n_points_strike)``.
'''
nx, ny, delta, points, points_xy = self._discretize_points(
store, cs='xyz')
if vr is None or vr.shape != tuple((nx, ny)):
if vr:
logger.warning(
'Given rupture velocities are not in right shape: '
'(%i, %i), but needed is (%i, %i).', *vr.shape + (nx, ny))
vr = self._discretize_rupture_v(store, interpolation, points)\
.reshape(nx, ny)
if vr.shape != tuple((nx, ny)):
logger.warning(
'Given rupture velocities are not in right shape. Therefore'
' standard rupture velocity array is used.')
def initialize_times():
nucl_x, nucl_y = self.nucleation_x, self.nucleation_y
if nucl_x.shape != nucl_y.shape:
raise ValueError(
'Nucleation coordinates have different shape.')
dist_points = num.array([
num.linalg.norm(points_xy - num.array([x, y]).ravel(), axis=1)
for x, y in zip(nucl_x, nucl_y)])
nucl_indices = num.argmin(dist_points, axis=1)
if self.nucleation_time is None:
nucl_times = num.zeros_like(nucl_indices)
else:
if self.nucleation_time.shape == nucl_x.shape:
nucl_times = self.nucleation_time
else:
raise ValueError(
'Nucleation coordinates and times have different '
'shapes')
t = num.full(nx * ny, -1.)
t[nucl_indices] = nucl_times
return t.reshape(nx, ny)
if times is None:
times = initialize_times()
elif times.shape != tuple((nx, ny)):
times = initialize_times()
logger.warning(
'Given times are not in right shape. Therefore standard time'
' array is used.')
eikonal_ext.eikonal_solver_fmm_cartesian(
speeds=vr, times=times, delta=delta)
return points, points_xy, vr, times
[docs] def get_vr_time_interpolators(
self, store, interpolation='nearest_neighbor', force=False,
**kwargs):
'''
Get interpolators for rupture velocity and rupture time.
Additional ``**kwargs`` are passed to :py:meth:`discretize_time`.
:param store:
Green's function database (needs to cover whole region of the
source).
:type store:
:py:class:`~pyrocko.gf.store.Store`
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:param force:
Force recalculation of the interpolators (e.g. after change of
nucleation point locations/times). Default is ``False``.
:type force:
optional, bool
'''
interp_map = {'multilinear': 'linear', 'nearest_neighbor': 'nearest'}
if interpolation not in interp_map:
raise TypeError(
'Interpolation method %s not available' % interpolation)
if not self._interpolators.get(interpolation, False) or force:
_, points_xy, vr, times = self.discretize_time(
store, **kwargs)
if self.length <= 0.:
raise ValueError(
'length must be larger then 0. not %g' % self.length)
if self.width <= 0.:
raise ValueError(
'width must be larger then 0. not %g' % self.width)
nx, ny = times.shape
anch_x, anch_y = map_anchor[self.anchor]
points_xy[:, 0] = (points_xy[:, 0] - anch_x) * self.length / 2.
points_xy[:, 1] = (points_xy[:, 1] - anch_y) * self.width / 2.
self._interpolators[interpolation] = (
nx, ny, times, vr,
RegularGridInterpolator(
(points_xy[::ny, 0], points_xy[:ny, 1]), times,
method=interp_map[interpolation]),
RegularGridInterpolator(
(points_xy[::ny, 0], points_xy[:ny, 1]), vr,
method=interp_map[interpolation]))
return self._interpolators[interpolation]
[docs] def discretize_patches(
self, store, interpolation='nearest_neighbor', force=False,
grid_shape=(),
**kwargs):
'''
Get rupture start time and OkadaSource elements for points on rupture.
All source elements and their corresponding center points are
calculated and stored in the :py:attr:`patches` attribute.
Additional ``**kwargs`` are passed to :py:meth:`discretize_time`.
:param store:
Green's function database (needs to cover whole region of the
source).
:type store:
:py:class:`~pyrocko.gf.store.Store`
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:param force:
Force recalculation of the vr and time interpolators ( e.g. after
change of nucleation point locations/times). Default is ``False``.
:type force:
optional, bool
:param grid_shape:
Desired sub fault patch grid size (nlength, nwidth). Either factor
or grid_shape should be set.
:type grid_shape:
optional, tuple of int
'''
nx, ny, times, vr, time_interpolator, vr_interpolator = \
self.get_vr_time_interpolators(
store,
interpolation=interpolation, force=force, **kwargs)
anch_x, anch_y = map_anchor[self.anchor]
al = self.length / 2.
aw = self.width / 2.
al1 = -(al + anch_x * al)
al2 = al - anch_x * al
aw1 = -aw + anch_y * aw
aw2 = aw + anch_y * aw
assert num.abs([al1, al2]).sum() == self.length
assert num.abs([aw1, aw2]).sum() == self.width
def get_lame(*a, **kw):
shear_mod = store.config.get_shear_moduli(*a, **kw)
lamb = store.config.get_vp(*a, **kw)**2 \
* store.config.get_rho(*a, **kw) - 2. * shear_mod
return shear_mod, lamb / (2. * (lamb + shear_mod))
shear_mod, poisson = get_lame(
self.lat, self.lon,
num.array([[self.north_shift, self.east_shift, self.depth]]),
interpolation=interpolation)
okada_src = OkadaSource(
lat=self.lat, lon=self.lon,
strike=self.strike, dip=self.dip,
north_shift=self.north_shift, east_shift=self.east_shift,
depth=self.depth,
al1=al1, al2=al2, aw1=aw1, aw2=aw2,
poisson=poisson.mean(),
shearmod=shear_mod.mean(),
opening=kwargs.get('opening', 0.))
if not (self.nx and self.ny):
if grid_shape:
self.nx, self.ny = grid_shape
else:
self.nx = nx
self.ny = ny
source_disc, source_points = okada_src.discretize(self.nx, self.ny)
shear_mod, poisson = get_lame(
self.lat, self.lon,
num.array([src.source_patch()[:3] for src in source_disc]),
interpolation=interpolation)
if (self.nx, self.ny) != (nx, ny):
times_interp = time_interpolator(source_points[:, :2])
vr_interp = vr_interpolator(source_points[:, :2])
else:
times_interp = times.T.ravel()
vr_interp = vr.T.ravel()
for isrc, src in enumerate(source_disc):
src.vr = vr_interp[isrc]
src.time = times_interp[isrc] + self.time
self.patches = source_disc
[docs] def discretize_basesource(self, store, target=None):
'''
Prepare source for synthetic waveform calculation.
:param store:
Green's function database (needs to cover whole region of the
source).
:type store:
:py:class:`~pyrocko.gf.store.Store`
:param target:
Target information.
:type target:
optional, :py:class:`~pyrocko.gf.targets.Target`
:returns:
Source discretized by a set of moment tensors and times.
:rtype:
:py:class:`~pyrocko.gf.meta.DiscretizedMTSource`
'''
if not target:
interpolation = 'nearest_neighbor'
else:
interpolation = target.interpolation
if not self.patches:
self.discretize_patches(store, interpolation)
if self.coef_mat is None:
self.calc_coef_mat()
delta_slip, slip_times = self.get_delta_slip(store)
npatches = self.nx * self.ny
ntimes = slip_times.size
anch_x, anch_y = map_anchor[self.anchor]
pln = self.length / self.nx
pwd = self.width / self.ny
patch_coords = num.array([
(p.ix, p.iy)
for p in self.patches]).reshape(self.nx, self.ny, 2)
# boundary condition is zero-slip
# is not valid to avoid unwished interpolation effects
slip_grid = num.zeros((self.nx + 2, self.ny + 2, ntimes, 3))
slip_grid[1:-1, 1:-1, :, :] = \
delta_slip.reshape(self.nx, self.ny, ntimes, 3)
slip_grid[0, 0, :, :] = slip_grid[1, 1, :, :]
slip_grid[0, -1, :, :] = slip_grid[1, -2, :, :]
slip_grid[-1, 0, :, :] = slip_grid[-2, 1, :, :]
slip_grid[-1, -1, :, :] = slip_grid[-2, -2, :, :]
slip_grid[1:-1, 0, :, :] = slip_grid[1:-1, 1, :, :]
slip_grid[1:-1, -1, :, :] = slip_grid[1:-1, -2, :, :]
slip_grid[0, 1:-1, :, :] = slip_grid[1, 1:-1, :, :]
slip_grid[-1, 1:-1, :, :] = slip_grid[-2, 1:-1, :, :]
def make_grid(patch_parameter):
grid = num.zeros((self.nx + 2, self.ny + 2))
grid[1:-1, 1:-1] = patch_parameter.reshape(self.nx, self.ny)
grid[0, 0] = grid[1, 1]
grid[0, -1] = grid[1, -2]
grid[-1, 0] = grid[-2, 1]
grid[-1, -1] = grid[-2, -2]
grid[1:-1, 0] = grid[1:-1, 1]
grid[1:-1, -1] = grid[1:-1, -2]
grid[0, 1:-1] = grid[1, 1:-1]
grid[-1, 1:-1] = grid[-2, 1:-1]
return grid
lamb = self.get_patch_attribute('lamb')
mu = self.get_patch_attribute('shearmod')
lamb_grid = make_grid(lamb)
mu_grid = make_grid(mu)
coords_x = num.zeros(self.nx + 2)
coords_x[1:-1] = patch_coords[:, 0, 0]
coords_x[0] = coords_x[1] - pln / 2
coords_x[-1] = coords_x[-2] + pln / 2
coords_y = num.zeros(self.ny + 2)
coords_y[1:-1] = patch_coords[0, :, 1]
coords_y[0] = coords_y[1] - pwd / 2
coords_y[-1] = coords_y[-2] + pwd / 2
slip_interp = RegularGridInterpolator(
(coords_x, coords_y, slip_times),
slip_grid, method='nearest')
lamb_interp = RegularGridInterpolator(
(coords_x, coords_y),
lamb_grid, method='nearest')
mu_interp = RegularGridInterpolator(
(coords_x, coords_y),
mu_grid, method='nearest')
# discretize basesources
mindeltagf = min(tuple(
(self.length / self.nx, self.width / self.ny) +
tuple(store.config.deltas)))
nl = int((1. / self.decimation_factor) *
num.ceil(pln / mindeltagf)) + 1
nw = int((1. / self.decimation_factor) *
num.ceil(pwd / mindeltagf)) + 1
nsrc_patch = int(nl * nw)
dl = pln / nl
dw = pwd / nw
patch_area = dl * dw
xl = num.linspace(-0.5 * (pln - dl), 0.5 * (pln - dl), nl)
xw = num.linspace(-0.5 * (pwd - dw), 0.5 * (pwd - dw), nw)
base_coords = num.zeros((nsrc_patch, 3), dtype=num.float)
base_coords[:, 0] = num.tile(xl, nw)
base_coords[:, 1] = num.repeat(xw, nl)
base_coords = num.tile(base_coords, (npatches, 1))
center_coords = num.zeros((npatches, 3))
center_coords[:, 0] = num.repeat(
num.arange(self.nx) * pln + pln / 2, self.ny) - self.length / 2
center_coords[:, 1] = num.tile(
num.arange(self.ny) * pwd + pwd / 2, self.nx) - self.width / 2
base_coords -= center_coords.repeat(nsrc_patch, axis=0)
nbaselocs = base_coords.shape[0]
base_interp = base_coords.repeat(ntimes, axis=0)
base_times = num.tile(slip_times, nbaselocs)
base_interp[:, 0] -= anch_x * self.length / 2
base_interp[:, 1] -= anch_y * self.width / 2
base_interp[:, 2] = base_times
_, _, _, _, time_interpolator, _ = self.get_vr_time_interpolators(
store, interpolation=interpolation)
time_eikonal_max = time_interpolator.values.max()
nbasesrcs = base_interp.shape[0]
delta_slip = slip_interp(base_interp).reshape(nbaselocs, ntimes, 3)
lamb = lamb_interp(base_interp[:, :2]).ravel()
mu = mu_interp(base_interp[:, :2]).ravel()
if False:
try:
import matplotlib.pyplot as plt
coords = base_coords.copy()
norm = num.sum(num.linalg.norm(delta_slip, axis=2), axis=1)
plt.scatter(coords[:, 0], coords[:, 1], c=norm)
plt.show()
except AttributeError:
pass
base_interp[:, 2] = 0.
rotmat = num.asarray(
pmt.euler_to_matrix(self.dip * d2r, self.strike * d2r, 0.0))
base_interp = num.dot(rotmat.T, base_interp.T).T
base_interp[:, 0] += self.north_shift
base_interp[:, 1] += self.east_shift
base_interp[:, 2] += self.depth
slip_strike = delta_slip[:, :, 0].ravel()
slip_dip = delta_slip[:, :, 1].ravel()
slip_norm = delta_slip[:, :, 2].ravel()
slip_shear = num.linalg.norm([slip_strike, slip_dip], axis=0)
slip_rake = r2d * num.arctan2(slip_dip, slip_strike)
m6s = okada_ext.patch2m6(
strikes=num.full(nbasesrcs, self.strike, dtype=num.float),
dips=num.full(nbasesrcs, self.dip, dtype=num.float),
rakes=slip_rake,
disl_shear=slip_shear,
disl_norm=slip_norm,
lamb=lamb,
mu=mu,
nthreads=self.nthreads)
m6s *= patch_area
dl = -self.patches[0].al1 + self.patches[0].al2
dw = -self.patches[0].aw1 + self.patches[0].aw2
base_times[base_times > time_eikonal_max] = time_eikonal_max
ds = meta.DiscretizedMTSource(
lat=self.lat,
lon=self.lon,
times=base_times + self.time,
north_shifts=base_interp[:, 0],
east_shifts=base_interp[:, 1],
depths=base_interp[:, 2],
m6s=m6s,
dl=dl,
dw=dw,
nl=self.nx,
nw=self.ny)
return ds
[docs] def calc_coef_mat(self):
'''
Calculate coefficients connecting tractions and dislocations.
'''
if not self.patches:
raise ValueError(
'Patches are needed. Please calculate them first.')
self.coef_mat = make_okada_coefficient_matrix(
self.patches, nthreads=self.nthreads, pure_shear=self.pure_shear)
[docs] def get_patch_attribute(self, attr):
'''
Get patch attributes.
:param attr:
Name of selected attribute (see
:py:class`pyrocko.modelling.okada.OkadaSource`).
:type attr:
str
:returns:
Array with attribute value for each fault patch.
:rtype:
:py:class:`~numpy.ndarray`
'''
if not self.patches:
raise ValueError(
'Patches are needed. Please calculate them first.')
return num.array([getattr(p, attr) for p in self.patches])
[docs] def get_slip(
self,
time=None,
scale_slip=True,
interpolation='nearest_neighbor',
**kwargs):
'''
Get slip per subfault patch for given time after rupture start.
:param time:
Time after origin [s], for which slip is computed. If not
given, final static slip is returned.
:type time:
optional, float > 0.
:param scale_slip:
If ``True`` and :py:attr:`slip` given, all slip values are scaled
to fit the given maximum slip.
:type scale_slip:
optional, bool
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:returns:
Inverted dislocations (:math:`u_{strike}, u_{dip}, u_{tensile}`)
for each source patch.
:rtype:
:py:class:`~numpy.ndarray`: ``(n_sources, 3)``
'''
if self.patches is None:
raise ValueError(
'Please discretize the source first (discretize_patches())')
npatches = len(self.patches)
tractions = self.get_tractions()
time_patch_max = self.get_patch_attribute('time').max() - self.time
time_patch = time
if time is None:
time_patch = time_patch_max
if self.coef_mat is None:
self.calc_coef_mat()
if tractions.shape != (npatches, 3):
raise AttributeError(
'The traction vector is of invalid shape.'
' Required shape is (npatches, 3)')
patch_mask = num.ones(npatches, dtype=num.bool)
if self.patch_mask is not None:
patch_mask = self.patch_mask
times = self.get_patch_attribute('time') - self.time
times[~patch_mask] = time_patch + 1. # exlcude unmasked patches
relevant_sources = num.nonzero(times <= time_patch)[0]
disloc_est = num.zeros_like(tractions)
if self.smooth_rupture:
patch_activation = num.zeros(npatches)
nx, ny, times, vr, time_interpolator, vr_interpolator = \
self.get_vr_time_interpolators(
store, interpolation=interpolation)
# Getting the native Eikonal grid, bit hackish
points_x = num.round(time_interpolator.grid[0], decimals=2)
points_y = num.round(time_interpolator.grid[1], decimals=2)
times_eikonal = time_interpolator.values
time_max = time
if time is None:
time_max = times_eikonal.max()
for ip, p in enumerate(self.patches):
ul = num.round((p.ix + p.al1, p.iy + p.aw1), decimals=2)
lr = num.round((p.ix + p.al2, p.iy + p.aw2), decimals=2)
idx_length = num.logical_and(
points_x >= ul[0], points_x <= lr[0])
idx_width = num.logical_and(
points_y >= ul[1], points_y <= lr[1])
times_patch = times_eikonal[num.ix_(idx_length, idx_width)]
if times_patch.size == 0:
raise AttributeError('could not use smooth_rupture')
patch_activation[ip] = \
(times_patch <= time_max).sum() / times_patch.size
if time_patch == 0 and time_patch != time_patch_max:
patch_activation[ip] = 0.
patch_activation[~patch_mask] = 0. # exlcude unmasked patches
relevant_sources = num.nonzero(patch_activation > 0.)[0]
if relevant_sources.size == 0:
return disloc_est
indices_disl = num.repeat(relevant_sources * 3, 3)
indices_disl[1::3] += 1
indices_disl[2::3] += 2
disloc_est[relevant_sources] = invert_fault_dislocations_bem(
stress_field=tractions[relevant_sources, :].ravel(),
coef_mat=self.coef_mat[indices_disl, :][:, indices_disl],
pure_shear=self.pure_shear, nthreads=self.nthreads,
epsilon=None,
**kwargs)
if self.smooth_rupture:
disloc_est *= patch_activation[:, num.newaxis]
if scale_slip and self.slip is not None:
disloc_tmax = num.zeros(npatches)
indices_disl = num.repeat(num.nonzero(patch_mask)[0] * 3, 3)
indices_disl[1::3] += 1
indices_disl[2::3] += 2
disloc_tmax[patch_mask] = num.linalg.norm(
invert_fault_dislocations_bem(
stress_field=tractions[patch_mask, :].ravel(),
coef_mat=self.coef_mat[indices_disl, :][:, indices_disl],
pure_shear=self.pure_shear, nthreads=self.nthreads,
epsilon=None,
**kwargs), axis=1)
disloc_tmax_max = disloc_tmax.max()
if disloc_tmax_max == 0.:
logger.warning(
'slip scaling not performed. Maximum slip is 0.')
disloc_est *= self.slip / disloc_tmax_max
return disloc_est
[docs] def get_delta_slip(
self,
store=None,
deltat=None,
delta=True,
interpolation='nearest_neighbor',
**kwargs):
'''
Get slip change snapshots.
The time interval, within which the slip changes are computed is
determined by the sampling rate of the Green's function database or
``deltat``. Additional ``**kwargs`` are passed to :py:meth:`get_slip`.
:param store:
Green's function database (needs to cover whole region of of the
source). Its sampling interval is used as time increment for slip
difference calculation. Either ``deltat`` or ``store`` should be
given.
:type store:
optional, :py:class:`~pyrocko.gf.store.Store`
:param deltat:
Time interval for slip difference calculation [s]. Either
``deltat`` or ``store`` should be given.
:type deltat:
optional, float
:param delta:
If ``True``, slip differences between two time steps are given. If
``False``, cumulative slip for all time steps.
:type delta:
optional, bool
:param interpolation:
Interpolation method to use (choose between ``'nearest_neighbor'``
and ``'multilinear'``).
:type interpolation:
optional, str
:returns:
Displacement changes(:math:`\\Delta u_{strike},
\\Delta u_{dip} , \\Delta u_{tensile}`) for each source patch and
time; corner times, for which delta slip is computed. The order of
displacement changes array is:
.. math::
&[[\\\\
&[\\Delta u_{strike, patch1, t1},
\\Delta u_{dip, patch1, t1},
\\Delta u_{tensile, patch1, t1}],\\\\
&[\\Delta u_{strike, patch1, t2},
\\Delta u_{dip, patch1, t2},
\\Delta u_{tensile, patch1, t2}]\\\\
&], [\\\\
&[\\Delta u_{strike, patch2, t1}, ...],\\\\
&[\\Delta u_{strike, patch2, t2}, ...]]]\\\\
:rtype: :py:class:`~numpy.ndarray`: ``(n_sources, n_times, 3)``,
:py:class:`~numpy.ndarray`: ``(n_times, )``
'''
if store and deltat:
raise AttributeError(
'Argument collision. '
'Please define only the store or the deltat argument.')
if store:
deltat = store.config.deltat
if not deltat:
raise AttributeError('Please give a GF store or set deltat.')
npatches = len(self.patches)
_, _, _, _, time_interpolator, _ = self.get_vr_time_interpolators(
store, interpolation=interpolation)
tmax = time_interpolator.values.max()
calc_times = num.arange(0., tmax + deltat, deltat)
calc_times[calc_times > tmax] = tmax
disloc_est = num.zeros((npatches, calc_times.size, 3))
for itime, t in enumerate(calc_times):
disloc_est[:, itime, :] = self.get_slip(
time=t, scale_slip=False, **kwargs)
if self.slip:
disloc_tmax = num.linalg.norm(
self.get_slip(scale_slip=False, time=tmax),
axis=1)
disloc_tmax_max = disloc_tmax.max()
if disloc_tmax_max == 0.:
logger.warning(
'Slip scaling not performed. Maximum slip is 0.')
else:
disloc_est *= self.slip / disloc_tmax_max
if not delta:
return disloc_est, calc_times
# if we have only one timestep there is no gradient
if calc_times.size > 1:
disloc_init = disloc_est[:, 0, :]
disloc_est = num.diff(disloc_est, axis=1)
disloc_est = num.concatenate((
disloc_init[:, num.newaxis, :], disloc_est), axis=1)
calc_times = calc_times
return disloc_est, calc_times
[docs] def get_slip_rate(self, *args, **kwargs):
'''
Get slip rate inverted from patches.
The time interval, within which the slip rates are computed is
determined by the sampling rate of the Green's function database or
``deltat``. Additional ``*args`` and ``**kwargs`` are passed to
:py:meth:`get_delta_slip`.
:returns:
Slip rates (:math:`\\Delta u_{strike}/\\Delta t`,
:math:`\\Delta u_{dip}/\\Delta t, \\Delta u_{tensile}/\\Delta t`)
for each source patch and time; corner times, for which slip rate
is computed. The order of sliprate array is:
.. math::
&[[\\\\
&[\\Delta u_{strike, patch1, t1}/\\Delta t,
\\Delta u_{dip, patch1, t1}/\\Delta t,
\\Delta u_{tensile, patch1, t1}/\\Delta t],\\\\
&[\\Delta u_{strike, patch1, t2}/\\Delta t,
\\Delta u_{dip, patch1, t2}/\\Delta t,
\\Delta u_{tensile, patch1, t2}/\\Delta t]], [\\\\
&[\\Delta u_{strike, patch2, t1}/\\Delta t, ...],\\\\
&[\\Delta u_{strike, patch2, t2}/\\Delta t, ...]]]\\\\
:rtype: :py:class:`~numpy.ndarray`: ``(n_sources, n_times, 3)``,
:py:class:`~numpy.ndarray`: ``(n_times, )``
'''
ddisloc_est, calc_times = self.get_delta_slip(
*args, delta=True, **kwargs)
dt = num.concatenate(
[(num.diff(calc_times)[0], ), num.diff(calc_times)])
slip_rate = num.linalg.norm(ddisloc_est, axis=2) / dt
return slip_rate, calc_times
[docs] def get_moment_rate_patches(self, *args, **kwargs):
'''
Get scalar seismic moment rate for each patch individually.
Additional ``*args`` and ``**kwargs`` are passed to
:py:meth:`get_slip_rate`.
:returns:
Seismic moment rate for each source patch and time; corner times,
for which patch moment rate is computed based on slip rate. The
order of the moment rate array is:
.. math::
&[\\\\
&[(\\Delta M / \\Delta t)_{patch1, t1},
(\\Delta M / \\Delta t)_{patch1, t2}, ...],\\\\
&[(\\Delta M / \\Delta t)_{patch2, t1},
(\\Delta M / \\Delta t)_{patch, t2}, ...],\\\\
&[...]]\\\\
:rtype: :py:class:`~numpy.ndarray`: ``(n_sources, n_times)``,
:py:class:`~numpy.ndarray`: ``(n_times, )``
'''
slip_rate, calc_times = self.get_slip_rate(*args, **kwargs)
shear_mod = self.get_patch_attribute('shearmod')
p_length = self.get_patch_attribute('length')
p_width = self.get_patch_attribute('width')
dA = p_length * p_width
mom_rate = shear_mod[:, num.newaxis] * slip_rate * dA[:, num.newaxis]
return mom_rate, calc_times
[docs] def get_moment_rate(self, store, target=None, deltat=None):
'''
Get seismic source moment rate for the total source (STF).
:param store:
Green's function database (needs to cover whole region of of the
source). Its ``deltat`` [s] is used as time increment for slip
difference calculation. Either ``deltat`` or ``store`` should be
given.
:type store:
:py:class:`~pyrocko.gf.store.Store`
:param target:
Target information, needed for interpolation method.
:type target:
optional, :py:class:`~pyrocko.gf.targets.Target`
:param deltat:
Time increment for slip difference calculation [s]. If not given
``store.deltat`` is used.
:type deltat:
optional, float
:return:
Seismic moment rate [Nm/s] for each time; corner times, for which
moment rate is computed. The order of the moment rate array is:
.. math::
&[\\\\
&(\\Delta M / \\Delta t)_{t1},\\\\
&(\\Delta M / \\Delta t)_{t2},\\\\
&...]\\\\
:rtype:
:py:class:`~numpy.ndarray`: ``(n_times, )``,
:py:class:`~numpy.ndarray`: ``(n_times, )``
'''
if not deltat:
deltat = store.config.deltat
return self.discretize_basesource(
store, target=target).get_moment_rate(deltat)
[docs] def get_moment(self, *args, **kwargs):
'''
Get seismic cumulative moment.
Additional ``*args`` and ``**kwargs`` are passed to
:py:meth:`get_magnitude`.
:returns:
Cumulative seismic moment in [Nm].
:rtype:
float
'''
return float(pmt.magnitude_to_moment(self.get_magnitude(
*args, **kwargs)))
[docs] def rescale_slip(self, magnitude=None, moment=None, **kwargs):
'''
Rescale source slip based on given target magnitude or seismic moment.
Rescale the maximum source slip to fit the source moment magnitude or
seismic moment to the given target values. Either ``magnitude`` or
``moment`` need to be given. Additional ``**kwargs`` are passed to
:py:meth:`get_moment`.
:param magnitude:
Target moment magnitude :math:`M_\\mathrm{w}` as in
[Hanks and Kanamori, 1979]
:type magnitude:
optional, float
:param moment:
Target seismic moment :math:`M_0` [Nm].
:type moment:
optional, float
'''
if self.slip is None:
self.slip = 1.
logger.warning('No slip found for rescaling. '
'An initial slip of 1 m is assumed.')
if magnitude is None and moment is None:
raise ValueError(
'Either target magnitude or moment need to be given.')
moment_init = self.get_moment(**kwargs)
if magnitude is not None:
moment = pmt.magnitude_to_moment(magnitude)
self.slip *= moment / moment_init
[docs]class DoubleDCSource(SourceWithMagnitude):
'''
Two double-couple point sources separated in space and time.
Moment share between the sub-sources is controlled by the
parameter mix.
The position of the subsources is dependent on the moment
distribution between the two sources. Depth, east and north
shift are given for the centroid between the two double-couples.
The subsources will positioned according to their moment shares
around this centroid position.
This is done according to their delta parameters, which are
therefore in relation to that centroid.
Note that depth of the subsources therefore can be
depth+/-delta_depth. For shallow earthquakes therefore
the depth has to be chosen deeper to avoid sampling
above surface.
'''
strike1 = Float.T(
default=0.0,
help='strike direction in [deg], measured clockwise from north')
dip1 = Float.T(
default=90.0,
help='dip angle in [deg], measured downward from horizontal')
azimuth = Float.T(
default=0.0,
help='azimuth to second double-couple [deg], '
'measured at first, clockwise from north')
rake1 = Float.T(
default=0.0,
help='rake angle in [deg], '
'measured counter-clockwise from right-horizontal '
'in on-plane view')
strike2 = Float.T(
default=0.0,
help='strike direction in [deg], measured clockwise from north')
dip2 = Float.T(
default=90.0,
help='dip angle in [deg], measured downward from horizontal')
rake2 = Float.T(
default=0.0,
help='rake angle in [deg], '
'measured counter-clockwise from right-horizontal '
'in on-plane view')
delta_time = Float.T(
default=0.0,
help='separation of double-couples in time (t2-t1) [s]')
delta_depth = Float.T(
default=0.0,
help='difference in depth (z2-z1) [m]')
distance = Float.T(
default=0.0,
help='distance between the two double-couples [m]')
mix = Float.T(
default=0.5,
help='how to distribute the moment to the two doublecouples '
'mix=0 -> m1=1 and m2=0; mix=1 -> m1=0, m2=1')
stf1 = STF.T(
optional=True,
help='Source time function of subsource 1 '
'(if given, overrides STF from attribute :py:gattr:`Source.stf`)')
stf2 = STF.T(
optional=True,
help='Source time function of subsource 2 '
'(if given, overrides STF from attribute :py:gattr:`Source.stf`)')
discretized_source_class = meta.DiscretizedMTSource
[docs] def base_key(self):
return (
self.time, self.depth, self.lat, self.north_shift,
self.lon, self.east_shift, type(self).__name__) + \
self.effective_stf1_pre().base_key() + \
self.effective_stf2_pre().base_key() + (
self.strike1, self.dip1, self.rake1,
self.strike2, self.dip2, self.rake2,
self.delta_time, self.delta_depth,
self.azimuth, self.distance, self.mix)
[docs] def get_factor(self):
return self.moment
def effective_stf1_pre(self):
return self.stf1 or self.stf or g_unit_pulse
def effective_stf2_pre(self):
return self.stf2 or self.stf or g_unit_pulse
[docs] def effective_stf_post(self):
return g_unit_pulse
def split(self):
a1 = 1.0 - self.mix
a2 = self.mix
delta_north = math.cos(self.azimuth * d2r) * self.distance
delta_east = math.sin(self.azimuth * d2r) * self.distance
dc1 = DCSource(
lat=self.lat,
lon=self.lon,
time=self.time - self.delta_time * a2,
north_shift=self.north_shift - delta_north * a2,
east_shift=self.east_shift - delta_east * a2,
depth=self.depth - self.delta_depth * a2,
moment=self.moment * a1,
strike=self.strike1,
dip=self.dip1,
rake=self.rake1,
stf=self.stf1 or self.stf)
dc2 = DCSource(
lat=self.lat,
lon=self.lon,
time=self.time + self.delta_time * a1,
north_shift=self.north_shift + delta_north * a1,
east_shift=self.east_shift + delta_east * a1,
depth=self.depth + self.delta_depth * a1,
moment=self.moment * a2,
strike=self.strike2,
dip=self.dip2,
rake=self.rake2,
stf=self.stf2 or self.stf)
return [dc1, dc2]
def discretize_basesource(self, store, target=None):
a1 = 1.0 - self.mix
a2 = self.mix
mot1 = pmt.MomentTensor(strike=self.strike1, dip=self.dip1,
rake=self.rake1, scalar_moment=a1)
mot2 = pmt.MomentTensor(strike=self.strike2, dip=self.dip2,
rake=self.rake2, scalar_moment=a2)
delta_north = math.cos(self.azimuth * d2r) * self.distance
delta_east = math.sin(self.azimuth * d2r) * self.distance
times1, amplitudes1 = self.effective_stf1_pre().discretize_t(
store.config.deltat, self.time - self.delta_time * a1)
times2, amplitudes2 = self.effective_stf2_pre().discretize_t(
store.config.deltat, self.time + self.delta_time * a2)
nt1 = times1.size
nt2 = times2.size
ds = meta.DiscretizedMTSource(
lat=self.lat,
lon=self.lon,
times=num.concatenate((times1, times2)),
north_shifts=num.concatenate((
num.repeat(self.north_shift - delta_north * a1, nt1),
num.repeat(self.north_shift + delta_north * a2, nt2))),
east_shifts=num.concatenate((
num.repeat(self.east_shift - delta_east * a1, nt1),
num.repeat(self.east_shift + delta_east * a2, nt2))),
depths=num.concatenate((
num.repeat(self.depth - self.delta_depth * a1, nt1),
num.repeat(self.depth + self.delta_depth * a2, nt2))),
m6s=num.vstack((
mot1.m6()[num.newaxis, :] * amplitudes1[:, num.newaxis],
mot2.m6()[num.newaxis, :] * amplitudes2[:, num.newaxis])))
return ds
def pyrocko_moment_tensor(self, store=None, target=None):
a1 = 1.0 - self.mix
a2 = self.mix
mot1 = pmt.MomentTensor(strike=self.strike1, dip=self.dip1,
rake=self.rake1,
scalar_moment=a1 * self.moment)
mot2 = pmt.MomentTensor(strike=self.strike2, dip=self.dip2,
rake=self.rake2,
scalar_moment=a2 * self.moment)
return pmt.MomentTensor(m=mot1.m() + mot2.m())
def pyrocko_event(self, store=None, target=None, **kwargs):
return SourceWithMagnitude.pyrocko_event(
self, store, target,
moment_tensor=self.pyrocko_moment_tensor(store, target),
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
mt = ev.moment_tensor
if mt:
(strike, dip, rake), _ = mt.both_strike_dip_rake()
d.update(
strike1=float(strike),
dip1=float(dip),
rake1=float(rake),
strike2=float(strike),
dip2=float(dip),
rake2=float(rake),
mix=0.0,
magnitude=float(mt.moment_magnitude()))
d.update(kwargs)
source = super(DoubleDCSource, cls).from_pyrocko_event(ev, **d)
source.stf1 = source.stf
source.stf2 = HalfSinusoidSTF(effective_duration=0.)
source.stf = None
return source
[docs]class RingfaultSource(SourceWithMagnitude):
'''
A ring fault with vertical doublecouples.
'''
diameter = Float.T(
default=1.0,
help='diameter of the ring in [m]')
sign = Float.T(
default=1.0,
help='inside of the ring moves up (+1) or down (-1)')
strike = Float.T(
default=0.0,
help='strike direction of the ring plane, clockwise from north,'
' in [deg]')
dip = Float.T(
default=0.0,
help='dip angle of the ring plane from horizontal in [deg]')
npointsources = Int.T(
default=360,
help='number of point sources to use')
discretized_source_class = meta.DiscretizedMTSource
[docs] def base_key(self):
return Source.base_key(self) + (
self.strike, self.dip, self.diameter, self.npointsources)
[docs] def get_factor(self):
return self.sign * self.moment
def discretize_basesource(self, store=None, target=None):
n = self.npointsources
phi = num.linspace(0, 2.0 * num.pi, n, endpoint=False)
points = num.zeros((n, 3))
points[:, 0] = num.cos(phi) * 0.5 * self.diameter
points[:, 1] = num.sin(phi) * 0.5 * self.diameter
rotmat = num.array(pmt.euler_to_matrix(
self.dip * d2r, self.strike * d2r, 0.0))
points = num.dot(rotmat.T, points.T).T # !!! ?
points[:, 0] += self.north_shift
points[:, 1] += self.east_shift
points[:, 2] += self.depth
m = num.array(pmt.MomentTensor(strike=90., dip=90., rake=-90.,
scalar_moment=1.0 / n).m())
rotmats = num.transpose(
[[num.cos(phi), num.sin(phi), num.zeros(n)],
[-num.sin(phi), num.cos(phi), num.zeros(n)],
[num.zeros(n), num.zeros(n), num.ones(n)]], (2, 0, 1))
ms = num.zeros((n, 3, 3))
for i in range(n):
mtemp = num.dot(rotmats[i].T, num.dot(m, rotmats[i]))
ms[i, :, :] = num.dot(rotmat.T, num.dot(mtemp, rotmat))
m6s = num.vstack((ms[:, 0, 0], ms[:, 1, 1], ms[:, 2, 2],
ms[:, 0, 1], ms[:, 0, 2], ms[:, 1, 2])).T
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
nt = times.size
return meta.DiscretizedMTSource(
times=num.tile(times, n),
lat=self.lat,
lon=self.lon,
north_shifts=num.repeat(points[:, 0], nt),
east_shifts=num.repeat(points[:, 1], nt),
depths=num.repeat(points[:, 2], nt),
m6s=num.repeat(m6s, nt, axis=0) * num.tile(
amplitudes, n)[:, num.newaxis])
[docs]class CombiSource(Source):
'''
Composite source model.
'''
discretized_source_class = meta.DiscretizedMTSource
subsources = List.T(Source.T())
def __init__(self, subsources=[], **kwargs):
if not subsources:
raise BadRequest(
'Need at least one sub-source to create a CombiSource object.')
lats = num.array(
[subsource.lat for subsource in subsources], dtype=float)
lons = num.array(
[subsource.lon for subsource in subsources], dtype=float)
lat, lon = lats[0], lons[0]
if not num.all(lats == lat) and num.all(lons == lon):
subsources = [s.clone() for s in subsources]
for subsource in subsources[1:]:
subsource.set_origin(lat, lon)
depth = float(num.mean([p.depth for p in subsources]))
time = float(num.mean([p.time for p in subsources]))
north_shift = float(num.mean([p.north_shift for p in subsources]))
east_shift = float(num.mean([p.east_shift for p in subsources]))
kwargs.update(
time=time,
lat=float(lat),
lon=float(lon),
north_shift=north_shift,
east_shift=east_shift,
depth=depth)
Source.__init__(self, subsources=subsources, **kwargs)
[docs] def get_factor(self):
return 1.0
def discretize_basesource(self, store, target=None):
dsources = []
for sf in self.subsources:
ds = sf.discretize_basesource(store, target)
ds.m6s *= sf.get_factor()
dsources.append(ds)
return meta.DiscretizedMTSource.combine(dsources)
[docs]class SFSource(Source):
'''
A single force point source.
Supported GF schemes: `'elastic5'`.
'''
discretized_source_class = meta.DiscretizedSFSource
fn = Float.T(
default=0.,
help='northward component of single force [N]')
fe = Float.T(
default=0.,
help='eastward component of single force [N]')
fd = Float.T(
default=0.,
help='downward component of single force [N]')
def __init__(self, **kwargs):
Source.__init__(self, **kwargs)
[docs] def base_key(self):
return Source.base_key(self) + (self.fn, self.fe, self.fd)
[docs] def get_factor(self):
return 1.0
def discretize_basesource(self, store, target=None):
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
forces = amplitudes[:, num.newaxis] * num.array(
[[self.fn, self.fe, self.fd]], dtype=float)
return meta.DiscretizedSFSource(forces=forces,
**self._dparams_base_repeated(times))
def pyrocko_event(self, store=None, target=None, **kwargs):
return Source.pyrocko_event(
self, store, target,
**kwargs)
@classmethod
def from_pyrocko_event(cls, ev, **kwargs):
d = {}
d.update(kwargs)
return super(SFSource, cls).from_pyrocko_event(ev, **d)
[docs]class PorePressurePointSource(Source):
'''
Excess pore pressure point source.
For poro-elastic initial value problem where an excess pore pressure is
brought into a small source volume.
'''
discretized_source_class = meta.DiscretizedPorePressureSource
pp = Float.T(
default=1.0,
help='initial excess pore pressure in [Pa]')
[docs] def base_key(self):
return Source.base_key(self)
[docs] def get_factor(self):
return self.pp
def discretize_basesource(self, store, target=None):
return meta.DiscretizedPorePressureSource(pp=arr(1.0),
**self._dparams_base())
[docs]class PorePressureLineSource(Source):
'''
Excess pore pressure line source.
The line source is centered at (north_shift, east_shift, depth).
'''
discretized_source_class = meta.DiscretizedPorePressureSource
pp = Float.T(
default=1.0,
help='initial excess pore pressure in [Pa]')
length = Float.T(
default=0.0,
help='length of the line source [m]')
azimuth = Float.T(
default=0.0,
help='azimuth direction, clockwise from north [deg]')
dip = Float.T(
default=90.,
help='dip direction, downward from horizontal [deg]')
[docs] def base_key(self):
return Source.base_key(self) + (self.azimuth, self.dip, self.length)
[docs] def get_factor(self):
return self.pp
def discretize_basesource(self, store, target=None):
n = 2 * int(math.ceil(self.length / num.min(store.config.deltas))) + 1
a = num.linspace(-0.5 * self.length, 0.5 * self.length, n)
sa = math.sin(self.azimuth * d2r)
ca = math.cos(self.azimuth * d2r)
sd = math.sin(self.dip * d2r)
cd = math.cos(self.dip * d2r)
points = num.zeros((n, 3))
points[:, 0] = self.north_shift + a * ca * cd
points[:, 1] = self.east_shift + a * sa * cd
points[:, 2] = self.depth + a * sd
return meta.DiscretizedPorePressureSource(
times=util.num_full(n, self.time),
lat=self.lat,
lon=self.lon,
north_shifts=points[:, 0],
east_shifts=points[:, 1],
depths=points[:, 2],
pp=num.ones(n) / n)
[docs]class Request(Object):
'''
Synthetic seismogram computation request.
::
Request(**kwargs)
Request(sources, targets, **kwargs)
'''
sources = List.T(
Source.T(),
help='list of sources for which to produce synthetics.')
targets = List.T(
Target.T(),
help='list of targets for which to produce synthetics.')
@classmethod
def args2kwargs(cls, args):
if len(args) not in (0, 2, 3):
raise BadRequest('Invalid arguments.')
if len(args) == 2:
return dict(sources=args[0], targets=args[1])
else:
return {}
def __init__(self, *args, **kwargs):
kwargs.update(self.args2kwargs(args))
sources = kwargs.pop('sources', [])
targets = kwargs.pop('targets', [])
if isinstance(sources, Source):
sources = [sources]
if isinstance(targets, Target) or isinstance(targets, StaticTarget):
targets = [targets]
Object.__init__(self, sources=sources, targets=targets, **kwargs)
@property
def targets_dynamic(self):
return [t for t in self.targets if isinstance(t, Target)]
@property
def targets_static(self):
return [t for t in self.targets if isinstance(t, StaticTarget)]
@property
def has_dynamic(self):
return True if len(self.targets_dynamic) > 0 else False
@property
def has_statics(self):
return True if len(self.targets_static) > 0 else False
def subsources_map(self):
m = defaultdict(list)
for source in self.sources:
m[source.base_key()].append(source)
return m
def subtargets_map(self):
m = defaultdict(list)
for target in self.targets:
m[target.base_key()].append(target)
return m
def subrequest_map(self):
ms = self.subsources_map()
mt = self.subtargets_map()
m = {}
for (ks, ls) in ms.items():
for (kt, lt) in mt.items():
m[ks, kt] = (ls, lt)
return m
[docs]class ProcessingStats(Object):
t_perc_get_store_and_receiver = Float.T(default=0.)
t_perc_discretize_source = Float.T(default=0.)
t_perc_make_base_seismogram = Float.T(default=0.)
t_perc_make_same_span = Float.T(default=0.)
t_perc_post_process = Float.T(default=0.)
t_perc_optimize = Float.T(default=0.)
t_perc_stack = Float.T(default=0.)
t_perc_static_get_store = Float.T(default=0.)
t_perc_static_discretize_basesource = Float.T(default=0.)
t_perc_static_sum_statics = Float.T(default=0.)
t_perc_static_post_process = Float.T(default=0.)
t_wallclock = Float.T(default=0.)
t_cpu = Float.T(default=0.)
n_read_blocks = Int.T(default=0)
n_results = Int.T(default=0)
n_subrequests = Int.T(default=0)
n_stores = Int.T(default=0)
n_records_stacked = Int.T(default=0)
[docs]class Response(Object):
'''
Resonse object to a synthetic seismogram computation request.
'''
request = Request.T()
results_list = List.T(List.T(meta.SeismosizerResult.T()))
stats = ProcessingStats.T()
[docs] def pyrocko_traces(self):
'''
Return a list of requested
:class:`~pyrocko.trace.Trace` instances.
'''
traces = []
for results in self.results_list:
for result in results:
if not isinstance(result, meta.Result):
continue
traces.append(result.trace.pyrocko_trace())
return traces
[docs] def kite_scenes(self):
'''
Return a list of requested
:class:`~kite.scenes` instances.
'''
kite_scenes = []
for results in self.results_list:
for result in results:
if isinstance(result, meta.KiteSceneResult):
sc = result.get_scene()
kite_scenes.append(sc)
return kite_scenes
[docs] def static_results(self):
'''
Return a list of requested
:class:`~pyrocko.gf.meta.StaticResult` instances.
'''
statics = []
for results in self.results_list:
for result in results:
if not isinstance(result, meta.StaticResult):
continue
statics.append(result)
return statics
[docs] def iter_results(self, get='pyrocko_traces'):
'''
Generator function to iterate over results of request.
Yields associated :py:class:`Source`,
:class:`~pyrocko.gf.targets.Target`,
:class:`~pyrocko.trace.Trace` instances in each iteration.
'''
for isource, source in enumerate(self.request.sources):
for itarget, target in enumerate(self.request.targets):
result = self.results_list[isource][itarget]
if get == 'pyrocko_traces':
yield source, target, result.trace.pyrocko_trace()
elif get == 'results':
yield source, target, result
[docs] def snuffle(self, **kwargs):
'''
Open *snuffler* with requested traces.
'''
trace.snuffle(self.pyrocko_traces(), **kwargs)
[docs]class Engine(Object):
'''
Base class for synthetic seismogram calculators.
'''
[docs] def get_store_ids(self):
'''
Get list of available GF store IDs
'''
return []
class Rule(object):
pass
class VectorRule(Rule):
def __init__(self, quantity, differentiate=0, integrate=0):
self.components = [quantity + '.' + c for c in 'ned']
self.differentiate = differentiate
self.integrate = integrate
def required_components(self, target):
n, e, d = self.components
sa, ca, sd, cd = target.get_sin_cos_factors()
comps = []
if nonzero(ca * cd):
comps.append(n)
if nonzero(sa * cd):
comps.append(e)
if nonzero(sd):
comps.append(d)
return tuple(comps)
def apply_(self, target, base_seismogram):
n, e, d = self.components
sa, ca, sd, cd = target.get_sin_cos_factors()
if nonzero(ca * cd):
data = base_seismogram[n].data * (ca * cd)
deltat = base_seismogram[n].deltat
else:
data = 0.0
if nonzero(sa * cd):
data = data + base_seismogram[e].data * (sa * cd)
deltat = base_seismogram[e].deltat
if nonzero(sd):
data = data + base_seismogram[d].data * sd
deltat = base_seismogram[d].deltat
if self.differentiate:
data = util.diff_fd(self.differentiate, 4, deltat, data)
if self.integrate:
raise NotImplementedError('Integration is not implemented yet.')
return data
class HorizontalVectorRule(Rule):
def __init__(self, quantity, differentiate=0, integrate=0):
self.components = [quantity + '.' + c for c in 'ne']
self.differentiate = differentiate
self.integrate = integrate
def required_components(self, target):
n, e = self.components
sa, ca, _, _ = target.get_sin_cos_factors()
comps = []
if nonzero(ca):
comps.append(n)
if nonzero(sa):
comps.append(e)
return tuple(comps)
def apply_(self, target, base_seismogram):
n, e = self.components
sa, ca, _, _ = target.get_sin_cos_factors()
if nonzero(ca):
data = base_seismogram[n].data * ca
else:
data = 0.0
if nonzero(sa):
data = data + base_seismogram[e].data * sa
if self.differentiate:
deltat = base_seismogram[e].deltat
data = util.diff_fd(self.differentiate, 4, deltat, data)
if self.integrate:
raise NotImplementedError('Integration is not implemented yet.')
return data
class ScalarRule(Rule):
def __init__(self, quantity, differentiate=0):
self.c = quantity
def required_components(self, target):
return (self.c, )
def apply_(self, target, base_seismogram):
data = base_seismogram[self.c].data.copy()
deltat = base_seismogram[self.c].deltat
if self.differentiate:
data = util.diff_fd(self.differentiate, 4, deltat, data)
return data
class StaticDisplacement(Rule):
def required_components(self, target):
return tuple(['displacement.%s' % c for c in list('ned')])
def apply_(self, target, base_statics):
if isinstance(target, SatelliteTarget):
los_fac = target.get_los_factors()
base_statics['displacement.los'] =\
(los_fac[:, 0] * -base_statics['displacement.d'] +
los_fac[:, 1] * base_statics['displacement.e'] +
los_fac[:, 2] * base_statics['displacement.n'])
return base_statics
channel_rules = {
'displacement': [VectorRule('displacement')],
'rotation': [VectorRule('rotation')],
'velocity': [
VectorRule('velocity'),
VectorRule('displacement', differentiate=1)],
'acceleration': [
VectorRule('acceleration'),
VectorRule('velocity', differentiate=1),
VectorRule('displacement', differentiate=2)],
'pore_pressure': [ScalarRule('pore_pressure')],
'vertical_tilt': [HorizontalVectorRule('vertical_tilt')],
'darcy_velocity': [VectorRule('darcy_velocity')],
}
static_rules = {
'displacement': [StaticDisplacement()]
}
class OutOfBoundsContext(Object):
source = Source.T()
target = Target.T()
distance = Float.T()
components = List.T(String.T())
def process_dynamic_timeseries(work, psources, ptargets, engine, nthreads=0):
dsource_cache = {}
tcounters = list(range(6))
store_ids = set()
sources = set()
targets = set()
for itarget, target in enumerate(ptargets):
target._id = itarget
for w in work:
_, _, isources, itargets = w
sources.update([psources[isource] for isource in isources])
targets.update([ptargets[itarget] for itarget in itargets])
store_ids = set([t.store_id for t in targets])
for isource, source in enumerate(psources):
components = set()
for itarget, target in enumerate(targets):
rule = engine.get_rule(source, target)
components.update(rule.required_components(target))
for store_id in store_ids:
store_targets = [t for t in targets if t.store_id == store_id]
sample_rates = set([t.sample_rate for t in store_targets])
interpolations = set([t.interpolation for t in store_targets])
base_seismograms = []
store_targets_out = []
for samp_rate in sample_rates:
for interp in interpolations:
engine_targets = [
t for t in store_targets if t.sample_rate == samp_rate
and t.interpolation == interp]
if not engine_targets:
continue
store_targets_out += engine_targets
base_seismograms += engine.base_seismograms(
source,
engine_targets,
components,
dsource_cache,
nthreads)
for iseis, seismogram in enumerate(base_seismograms):
for tr in seismogram.values():
if tr.err != store.SeismosizerErrorEnum.SUCCESS:
e = SeismosizerError(
'Seismosizer failed with return code %i\n%s' % (
tr.err, str(
OutOfBoundsContext(
source=source,
target=store_targets[iseis],
distance=source.distance_to(
store_targets[iseis]),
components=components))))
raise e
for seismogram, target in zip(base_seismograms, store_targets_out):
try:
result = engine._post_process_dynamic(
seismogram, source, target)
except SeismosizerError as e:
result = e
yield (isource, target._id, result), tcounters
def process_dynamic(work, psources, ptargets, engine, nthreads=0):
dsource_cache = {}
for w in work:
_, _, isources, itargets = w
sources = [psources[isource] for isource in isources]
targets = [ptargets[itarget] for itarget in itargets]
components = set()
for target in targets:
rule = engine.get_rule(sources[0], target)
components.update(rule.required_components(target))
for isource, source in zip(isources, sources):
for itarget, target in zip(itargets, targets):
try:
base_seismogram, tcounters = engine.base_seismogram(
source, target, components, dsource_cache, nthreads)
except meta.OutOfBounds as e:
e.context = OutOfBoundsContext(
source=sources[0],
target=targets[0],
distance=sources[0].distance_to(targets[0]),
components=components)
raise
n_records_stacked = 0
t_optimize = 0.0
t_stack = 0.0
for _, tr in base_seismogram.items():
n_records_stacked += tr.n_records_stacked
t_optimize += tr.t_optimize
t_stack += tr.t_stack
try:
result = engine._post_process_dynamic(
base_seismogram, source, target)
result.n_records_stacked = n_records_stacked
result.n_shared_stacking = len(sources) *\
len(targets)
result.t_optimize = t_optimize
result.t_stack = t_stack
except SeismosizerError as e:
result = e
tcounters.append(xtime())
yield (isource, itarget, result), tcounters
def process_static(work, psources, ptargets, engine, nthreads=0):
for w in work:
_, _, isources, itargets = w
sources = [psources[isource] for isource in isources]
targets = [ptargets[itarget] for itarget in itargets]
for isource, source in zip(isources, sources):
for itarget, target in zip(itargets, targets):
components = engine.get_rule(source, target)\
.required_components(target)
try:
base_statics, tcounters = engine.base_statics(
source, target, components, nthreads)
except meta.OutOfBounds as e:
e.context = OutOfBoundsContext(
source=sources[0],
target=targets[0],
distance=float('nan'),
components=components)
raise
result = engine._post_process_statics(
base_statics, source, target)
tcounters.append(xtime())
yield (isource, itarget, result), tcounters
[docs]class LocalEngine(Engine):
'''
Offline synthetic seismogram calculator.
:param use_env: if ``True``, fill :py:attr:`store_superdirs` and
:py:attr:`store_dirs` with paths set in environment variables
GF_STORE_SUPERDIRS and GF_STORE_DIRS.
:param use_config: if ``True``, fill :py:attr:`store_superdirs` and
:py:attr:`store_dirs` with paths set in the user's config file.
The config file can be found at :file:`~/.pyrocko/config.pf`
.. code-block :: python
gf_store_dirs: ['/home/pyrocko/gf_stores/ak135/']
gf_store_superdirs: ['/home/pyrocko/gf_stores/']
'''
store_superdirs = List.T(
String.T(),
help='directories which are searched for Green\'s function stores')
store_dirs = List.T(
String.T(),
help='additional individual Green\'s function store directories')
default_store_id = String.T(
optional=True,
help='default store ID to be used when a request does not provide '
'one')
def __init__(self, **kwargs):
use_env = kwargs.pop('use_env', False)
use_config = kwargs.pop('use_config', False)
Engine.__init__(self, **kwargs)
if use_env:
env_store_superdirs = os.environ.get('GF_STORE_SUPERDIRS', '')
env_store_dirs = os.environ.get('GF_STORE_DIRS', '')
if env_store_superdirs:
self.store_superdirs.extend(env_store_superdirs.split(':'))
if env_store_dirs:
self.store_dirs.extend(env_store_dirs.split(':'))
if use_config:
c = config.config()
self.store_superdirs.extend(c.gf_store_superdirs)
self.store_dirs.extend(c.gf_store_dirs)
self._check_store_dirs_type()
self._id_to_store_dir = {}
self._open_stores = {}
self._effective_default_store_id = None
def _check_store_dirs_type(self):
for sdir in ['store_dirs', 'store_superdirs']:
if not isinstance(self.__getattribute__(sdir), list):
raise TypeError("{} of {} is not of type list".format(
sdir, self.__class__.__name__))
def _get_store_id(self, store_dir):
store_ = store.Store(store_dir)
store_id = store_.config.id
store_.close()
return store_id
def _looks_like_store_dir(self, store_dir):
return os.path.isdir(store_dir) and \
all(os.path.isfile(pjoin(store_dir, x)) for x in
('index', 'traces', 'config'))
def iter_store_dirs(self):
store_dirs = set()
for d in self.store_superdirs:
if not os.path.exists(d):
logger.warning('store_superdir not available: %s' % d)
continue
for entry in os.listdir(d):
store_dir = os.path.realpath(pjoin(d, entry))
if self._looks_like_store_dir(store_dir):
store_dirs.add(store_dir)
for store_dir in self.store_dirs:
store_dirs.add(os.path.realpath(store_dir))
return store_dirs
def _scan_stores(self):
for store_dir in self.iter_store_dirs():
store_id = self._get_store_id(store_dir)
if store_id not in self._id_to_store_dir:
self._id_to_store_dir[store_id] = store_dir
else:
if store_dir != self._id_to_store_dir[store_id]:
raise DuplicateStoreId(
'GF store ID %s is used in (at least) two '
'different stores. Locations are: %s and %s' %
(store_id, self._id_to_store_dir[store_id], store_dir))
[docs] def get_store_dir(self, store_id):
'''
Lookup directory given a GF store ID.
'''
if store_id not in self._id_to_store_dir:
self._scan_stores()
if store_id not in self._id_to_store_dir:
raise NoSuchStore(store_id, self.iter_store_dirs())
return self._id_to_store_dir[store_id]
[docs] def get_store_ids(self):
'''
Get list of available store IDs.
'''
self._scan_stores()
return sorted(self._id_to_store_dir.keys())
def effective_default_store_id(self):
if self._effective_default_store_id is None:
if self.default_store_id is None:
store_ids = self.get_store_ids()
if len(store_ids) == 1:
self._effective_default_store_id = self.get_store_ids()[0]
else:
raise NoDefaultStoreSet()
else:
self._effective_default_store_id = self.default_store_id
return self._effective_default_store_id
[docs] def get_store(self, store_id=None):
'''
Get a store from the engine.
:param store_id: identifier of the store (optional)
:returns: :py:class:`~pyrocko.gf.store.Store` object
If no ``store_id`` is provided the store
associated with the :py:gattr:`default_store_id` is returned.
Raises :py:exc:`NoDefaultStoreSet` if :py:gattr:`default_store_id` is
undefined.
'''
if store_id is None:
store_id = self.effective_default_store_id()
if store_id not in self._open_stores:
store_dir = self.get_store_dir(store_id)
self._open_stores[store_id] = store.Store(store_dir)
return self._open_stores[store_id]
def get_store_config(self, store_id):
store = self.get_store(store_id)
return store.config
def get_store_extra(self, store_id, key):
store = self.get_store(store_id)
return store.get_extra(key)
[docs] def close_cashed_stores(self):
'''
Close and remove ids from cashed stores.
'''
store_ids = []
for store_id, store_ in self._open_stores.items():
store_.close()
store_ids.append(store_id)
for store_id in store_ids:
self._open_stores.pop(store_id)
def get_rule(self, source, target):
cprovided = self.get_store(target.store_id).get_provided_components()
if isinstance(target, StaticTarget):
quantity = target.quantity
available_rules = static_rules
elif isinstance(target, Target):
quantity = target.effective_quantity()
available_rules = channel_rules
try:
for rule in available_rules[quantity]:
cneeded = rule.required_components(target)
if all(c in cprovided for c in cneeded):
return rule
except KeyError:
pass
raise BadRequest(
'No rule to calculate "%s" with GFs from store "%s" '
'for source model "%s".' % (
target.effective_quantity(),
target.store_id,
source.__class__.__name__))
def _cached_discretize_basesource(self, source, store, cache, target):
if (source, store) not in cache:
cache[source, store] = source.discretize_basesource(store, target)
return cache[source, store]
def base_seismograms(self, source, targets, components, dsource_cache,
nthreads=0):
target = targets[0]
interp = set([t.interpolation for t in targets])
if len(interp) > 1:
raise BadRequest('Targets have different interpolation schemes.')
rates = set([t.sample_rate for t in targets])
if len(rates) > 1:
raise BadRequest('Targets have different sample rates.')
store_ = self.get_store(target.store_id)
receivers = [t.receiver(store_) for t in targets]
if target.sample_rate is not None:
deltat = 1. / target.sample_rate
rate = target.sample_rate
else:
deltat = None
rate = store_.config.sample_rate
tmin = num.fromiter(
(t.tmin for t in targets), dtype=float, count=len(targets))
tmax = num.fromiter(
(t.tmax for t in targets), dtype=float, count=len(targets))
itmin = num.floor(tmin * rate).astype(num.int64)
itmax = num.ceil(tmax * rate).astype(num.int64)
nsamples = itmax - itmin + 1
mask = num.isnan(tmin)
itmin[mask] = 0
nsamples[mask] = -1
base_source = self._cached_discretize_basesource(
source, store_, dsource_cache, target)
base_seismograms = store_.calc_seismograms(
base_source, receivers, components,
deltat=deltat,
itmin=itmin, nsamples=nsamples,
interpolation=target.interpolation,
optimization=target.optimization,
nthreads=nthreads)
for i, base_seismogram in enumerate(base_seismograms):
base_seismograms[i] = store.make_same_span(base_seismogram)
return base_seismograms
def base_seismogram(self, source, target, components, dsource_cache,
nthreads):
tcounters = [xtime()]
store_ = self.get_store(target.store_id)
receiver = target.receiver(store_)
if target.tmin and target.tmax is not None:
rate = store_.config.sample_rate
itmin = int(num.floor(target.tmin * rate))
itmax = int(num.ceil(target.tmax * rate))
nsamples = itmax - itmin + 1
else:
itmin = None
nsamples = None
tcounters.append(xtime())
base_source = self._cached_discretize_basesource(
source, store_, dsource_cache, target)
tcounters.append(xtime())
if target.sample_rate is not None:
deltat = 1. / target.sample_rate
else:
deltat = None
base_seismogram = store_.seismogram(
base_source, receiver, components,
deltat=deltat,
itmin=itmin, nsamples=nsamples,
interpolation=target.interpolation,
optimization=target.optimization,
nthreads=nthreads)
tcounters.append(xtime())
base_seismogram = store.make_same_span(base_seismogram)
tcounters.append(xtime())
return base_seismogram, tcounters
def base_statics(self, source, target, components, nthreads):
tcounters = [xtime()]
store_ = self.get_store(target.store_id)
if target.tsnapshot is not None:
rate = store_.config.sample_rate
itsnapshot = int(num.floor(target.tsnapshot * rate))
else:
itsnapshot = None
tcounters.append(xtime())
base_source = source.discretize_basesource(store_, target=target)
tcounters.append(xtime())
base_statics = store_.statics(
base_source,
target,
itsnapshot,
components,
target.interpolation,
nthreads)
tcounters.append(xtime())
return base_statics, tcounters
def _post_process_dynamic(self, base_seismogram, source, target):
base_any = next(iter(base_seismogram.values()))
deltat = base_any.deltat
itmin = base_any.itmin
rule = self.get_rule(source, target)
data = rule.apply_(target, base_seismogram)
factor = source.get_factor() * target.get_factor()
if factor != 1.0:
data = data * factor
stf = source.effective_stf_post()
times, amplitudes = stf.discretize_t(
deltat, 0.0)
# repeat end point to prevent boundary effects
padded_data = num.empty(data.size + amplitudes.size, dtype=float)
padded_data[:data.size] = data
padded_data[data.size:] = data[-1]
data = num.convolve(amplitudes, padded_data)
tmin = itmin * deltat + times[0]
tr = meta.SeismosizerTrace(
codes=target.codes,
data=data[:-amplitudes.size],
deltat=deltat,
tmin=tmin)
return target.post_process(self, source, tr)
def _post_process_statics(self, base_statics, source, starget):
rule = self.get_rule(source, starget)
data = rule.apply_(starget, base_statics)
factor = source.get_factor()
if factor != 1.0:
for v in data.values():
v *= factor
return starget.post_process(self, source, base_statics)
[docs] def process(self, *args, **kwargs):
'''
Process a request.
::
process(**kwargs)
process(request, **kwargs)
process(sources, targets, **kwargs)
The request can be given a a :py:class:`Request` object, or such an
object is created using ``Request(**kwargs)`` for convenience.
:returns: :py:class:`Response` object
'''
if len(args) not in (0, 1, 2):
raise BadRequest('Invalid arguments.')
if len(args) == 1:
kwargs['request'] = args[0]
elif len(args) == 2:
kwargs.update(Request.args2kwargs(args))
request = kwargs.pop('request', None)
status_callback = kwargs.pop('status_callback', None)
calc_timeseries = kwargs.pop('calc_timeseries', True)
nprocs = kwargs.pop('nprocs', None)
nthreads = kwargs.pop('nthreads', 1)
if nprocs is not None:
nthreads = nprocs
if request is None:
request = Request(**kwargs)
if resource:
rs0 = resource.getrusage(resource.RUSAGE_SELF)
rc0 = resource.getrusage(resource.RUSAGE_CHILDREN)
tt0 = xtime()
# make sure stores are open before fork()
store_ids = set(target.store_id for target in request.targets)
for store_id in store_ids:
self.get_store(store_id)
source_index = dict((x, i) for (i, x) in
enumerate(request.sources))
target_index = dict((x, i) for (i, x) in
enumerate(request.targets))
m = request.subrequest_map()
skeys = sorted(m.keys(), key=cmp_to_key(cmp_none_aware))
results_list = []
for i in range(len(request.sources)):
results_list.append([None] * len(request.targets))
tcounters_dyn_list = []
tcounters_static_list = []
nsub = len(skeys)
isub = 0
# Processing dynamic targets through
# parimap(process_subrequest_dynamic)
if calc_timeseries:
_process_dynamic = process_dynamic_timeseries
else:
_process_dynamic = process_dynamic
if request.has_dynamic:
work_dynamic = [
(i, nsub,
[source_index[source] for source in m[k][0]],
[target_index[target] for target in m[k][1]
if not isinstance(target, StaticTarget)])
for (i, k) in enumerate(skeys)]
for ii_results, tcounters_dyn in _process_dynamic(
work_dynamic, request.sources, request.targets, self,
nthreads):
tcounters_dyn_list.append(num.diff(tcounters_dyn))
isource, itarget, result = ii_results
results_list[isource][itarget] = result
if status_callback:
status_callback(isub, nsub)
isub += 1
# Processing static targets through process_static
if request.has_statics:
work_static = [
(i, nsub,
[source_index[source] for source in m[k][0]],
[target_index[target] for target in m[k][1]
if isinstance(target, StaticTarget)])
for (i, k) in enumerate(skeys)]
for ii_results, tcounters_static in process_static(
work_static, request.sources, request.targets, self,
nthreads=nthreads):
tcounters_static_list.append(num.diff(tcounters_static))
isource, itarget, result = ii_results
results_list[isource][itarget] = result
if status_callback:
status_callback(isub, nsub)
isub += 1
if status_callback:
status_callback(nsub, nsub)
tt1 = time.time()
if resource:
rs1 = resource.getrusage(resource.RUSAGE_SELF)
rc1 = resource.getrusage(resource.RUSAGE_CHILDREN)
s = ProcessingStats()
if request.has_dynamic:
tcumu_dyn = num.sum(num.vstack(tcounters_dyn_list), axis=0)
t_dyn = float(num.sum(tcumu_dyn))
perc_dyn = map(float, tcumu_dyn / t_dyn * 100.)
(s.t_perc_get_store_and_receiver,
s.t_perc_discretize_source,
s.t_perc_make_base_seismogram,
s.t_perc_make_same_span,
s.t_perc_post_process) = perc_dyn
else:
t_dyn = 0.
if request.has_statics:
tcumu_static = num.sum(num.vstack(tcounters_static_list), axis=0)
t_static = num.sum(tcumu_static)
perc_static = map(float, tcumu_static / t_static * 100.)
(s.t_perc_static_get_store,
s.t_perc_static_discretize_basesource,
s.t_perc_static_sum_statics,
s.t_perc_static_post_process) = perc_static
s.t_wallclock = tt1 - tt0
if resource:
s.t_cpu = (
(rs1.ru_utime + rs1.ru_stime + rc1.ru_utime + rc1.ru_stime) -
(rs0.ru_utime + rs0.ru_stime + rc0.ru_utime + rc0.ru_stime))
s.n_read_blocks = (
(rs1.ru_inblock + rc1.ru_inblock) -
(rs0.ru_inblock + rc0.ru_inblock))
n_records_stacked = 0.
for results in results_list:
for result in results:
if not isinstance(result, meta.Result):
continue
shr = float(result.n_shared_stacking)
n_records_stacked += result.n_records_stacked / shr
s.t_perc_optimize += result.t_optimize / shr
s.t_perc_stack += result.t_stack / shr
s.n_records_stacked = int(n_records_stacked)
if t_dyn != 0.:
s.t_perc_optimize /= t_dyn * 100
s.t_perc_stack /= t_dyn * 100
return Response(
request=request,
results_list=results_list,
stats=s)
[docs]class RemoteEngine(Engine):
'''
Client for remote synthetic seismogram calculator.
'''
site = String.T(default=ws.g_default_site, optional=True)
url = String.T(default=ws.g_url, optional=True)
def process(self, request=None, status_callback=None, **kwargs):
if request is None:
request = Request(**kwargs)
return ws.seismosizer(url=self.url, site=self.site, request=request)
g_engine = None
def get_engine(store_superdirs=[]):
global g_engine
if g_engine is None:
g_engine = LocalEngine(use_env=True, use_config=True)
for d in store_superdirs:
if d not in g_engine.store_superdirs:
g_engine.store_superdirs.append(d)
return g_engine
[docs]class SourceGroup(Object):
def __getattr__(self, k):
return num.fromiter((getattr(s, k) for s in self),
dtype=float)
def __iter__(self):
raise NotImplementedError(
'This method should be implemented in subclass.')
def __len__(self):
raise NotImplementedError(
'This method should be implemented in subclass.')
[docs]class SourceList(SourceGroup):
sources = List.T(Source.T())
def append(self, s):
self.sources.append(s)
def __iter__(self):
return iter(self.sources)
def __len__(self):
return len(self.sources)
[docs]class SourceGrid(SourceGroup):
base = Source.T()
variables = Dict.T(String.T(), Range.T())
order = List.T(String.T())
def __len__(self):
n = 1
for (k, v) in self.make_coords(self.base):
n *= len(list(v))
return n
def __iter__(self):
for items in permudef(self.make_coords(self.base)):
s = self.base.clone(**{k: v for (k, v) in items})
s.regularize()
yield s
def ordered_params(self):
ks = list(self.variables.keys())
for k in self.order + list(self.base.keys()):
if k in ks:
yield k
ks.remove(k)
if ks:
raise Exception('Invalid parameter "%s" for source type "%s".' %
(ks[0], self.base.__class__.__name__))
def make_coords(self, base):
return [(param, self.variables[param].make(base=base[param]))
for param in self.ordered_params()]
source_classes = [
Source,
SourceWithMagnitude,
SourceWithDerivedMagnitude,
ExplosionSource,
RectangularExplosionSource,
DCSource,
CLVDSource,
VLVDSource,
MTSource,
RectangularSource,
PseudoDynamicRupture,
DoubleDCSource,
RingfaultSource,
CombiSource,
SFSource,
PorePressurePointSource,
PorePressureLineSource,
]
stf_classes = [
STF,
BoxcarSTF,
TriangularSTF,
HalfSinusoidSTF,
ResonatorSTF,
]
__all__ = '''
SeismosizerError
BadRequest
NoSuchStore
DerivedMagnitudeError
STFMode
'''.split() + [S.__name__ for S in source_classes + stf_classes] + '''
Request
ProcessingStats
Response
Engine
LocalEngine
RemoteEngine
source_classes
get_engine
Range
SourceGroup
SourceList
SourceGrid
map_anchor
'''.split()
