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gem/oq-engine | openquake/hazardlib/geo/surface/gridded.py | GriddedSurface.get_surface_boundaries | def get_surface_boundaries(self):
"""
:returns: (min_max lons, min_max lats)
"""
min_lon, min_lat, max_lon, max_lat = self.get_bounding_box()
return [[min_lon, max_lon]], [[min_lat, max_lat]] | python | def get_surface_boundaries(self):
min_lon, min_lat, max_lon, max_lat = self.get_bounding_box()
return [[min_lon, max_lon]], [[min_lat, max_lat]] | [
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gem/oq-engine | openquake/hazardlib/geo/surface/gridded.py | GriddedSurface.get_middle_point | def get_middle_point(self):
"""
Compute coordinates of surface middle point.
The actual definition of ``middle point`` depends on the type of
surface geometry.
:return:
instance of :class:`openquake.hazardlib.geo.point.Point`
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lons = self.mesh.lons.squeeze()
lats = self.mesh.lats.squeeze()
depths = self.mesh.depths.squeeze()
lon_bar = lons.mean()
lat_bar = lats.mean()
idx = np.argmin((lons - lon_bar)**2 + (lats - lat_bar)**2)
return Point(lons[idx], ... | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_atkinson_2011.py | BooreAtkinson2011.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
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for spec of input and result values.
"""
# get mean and std using the superclass
mean, stddevs = super... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
mean, stddevs = super().get_mean_and_stddevs(
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corr_fact = 10.0**(np.max([0, 3.888 - 0.674 * rup.mag]) -
(np.max([0, 2.9... | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_atkinson_2011.py | Atkinson2008prime.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
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for spec of input and result values.
"""
# get mean and std using the superclass
mean, stddevs = super... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
mean, stddevs = super().get_mean_and_stddevs(
sites, rup, dists, imt, stddev_types)
A08 = self.A08_COEFFS[imt]
f_ena = 10.0 ** (A08["c"] + A08["d"] * dists.rjb)
return np.log(np... | [
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gem/oq-engine | openquake/risklib/countries.py | get_country_code | def get_country_code(longname):
"""
:returns: the code of the country contained in `longname`, or a ValuError
>>> for country, code in country2code.items():
... assert get_country_code('Exp_' + country) == code, (country, code)
"""
mo = re.search(REGEX, longname, re.I)
if mo is None:
... | python | def get_country_code(longname):
mo = re.search(REGEX, longname, re.I)
if mo is None:
raise ValueError('Could not find a valid country in %s' % longname)
return country2code[COUNTRIES[mo.lastindex - 1]] | [
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gem/oq-engine | openquake/risklib/countries.py | from_exposures | def from_exposures(expnames):
"""
:returns: a dictionary E??_ -> country
"""
dic = {}
for i, expname in enumerate(expnames, 1):
cc = get_country_code(expname)
dic['E%02d_' % i] = cc
return dic | python | def from_exposures(expnames):
dic = {}
for i, expname in enumerate(expnames, 1):
cc = get_country_code(expname)
dic['E%02d_' % i] = cc
return dic | [
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gem/oq-engine | openquake/hazardlib/mfd/base.py | BaseMFD.modify | def modify(self, modification, parameters):
"""
Apply a single modification to an MFD parameters.
Reflects the modification method and calls it passing ``parameters``
as keyword arguments. See also :attr:`MODIFICATIONS`.
Modifications can be applied one on top of another. The l... | python | def modify(self, modification, parameters):
if modification not in self.MODIFICATIONS:
raise ValueError('Modification %s is not supported by %s' %
(modification, type(self).__name__))
meth = getattr(self, 'modify_%s' % modification)
meth(**parame... | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
# extracting dictionary of coefficients specific to required
#... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS[imt]
mean = (self._compute_magnitude(rup, C) +
self._compute_distance(dists, C) +
self._get_site_amplification(sites, rup, C) +
self._... | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_stddevs | def _get_stddevs(self, rup, arias, stddev_types, sites):
"""
Return standard deviations as defined in table 1, p. 200.
"""
stddevs = []
# Magnitude dependent inter-event term (Eq. 13)
if rup.mag < 4.7:
tau = 0.611
elif rup.mag > 7.6:
tau = ... | python | def _get_stddevs(self, rup, arias, stddev_types, sites):
stddevs = []
if rup.mag < 4.7:
tau = 0.611
elif rup.mag > 7.6:
tau = 0.475
else:
tau = 0.611 - 0.047 * (rup.mag - 4.7)
sigma1, sigma2 = self._get_intra_event_s... | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_intra_event_sigmas | def _get_intra_event_sigmas(self, sites):
"""
The intra-event term nonlinear and dependent on both the site class
and the expected ground motion. In this case the sigma coefficients
are determined from the site class as described below Eq. 14
"""
sigma1 = 1.18 * np.ones_l... | python | def _get_intra_event_sigmas(self, sites):
sigma1 = 1.18 * np.ones_like(sites.vs30)
sigma2 = 0.94 * np.ones_like(sites.vs30)
idx1 = np.logical_and(sites.vs30 >= 360.0, sites.vs30 < 760.0)
idx2 = sites.vs30 < 360.0
sigma1[idx1] = 1.17
sigma2[idx1] = 0.93
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._compute_magnitude | def _compute_magnitude(self, rup, C):
"""
Compute the first term of the equation described on p. 1144:
``c1 + c2 * (M - 6) + c3 * log(M / 6)``
"""
return C['c1'] + C['c2'] * (rup.mag - 6.0) +\
(C['c3'] * np.log(rup.mag / 6.0)) | python | def _compute_magnitude(self, rup, C):
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._compute_distance | def _compute_distance(self, dists, C):
"""
Compute the second term of the equation described on p. 1144:
`` c4 * np.log(sqrt(R ** 2. + h ** 2.)
"""
return C["c4"] * np.log(np.sqrt(dists.rrup ** 2. + C["h"] ** 2.)) | python | def _compute_distance(self, dists, C):
return C["c4"] * np.log(np.sqrt(dists.rrup ** 2. + C["h"] ** 2.)) | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_site_amplification | def _get_site_amplification(self, sites, rup, C):
"""
Compute the third term of the equation described on p. 1144:
``(s11 + s12 * (M - 6)) * Sc + (s21 + s22 * (M - 6)) * Sd`
"""
Sc, Sd = self._get_site_type_dummy_variables(sites)
return (C["s11"] + C["s12"] * (rup.mag - ... | python | def _get_site_amplification(self, sites, rup, C):
Sc, Sd = self._get_site_type_dummy_variables(sites)
return (C["s11"] + C["s12"] * (rup.mag - 6.0)) * Sc +\
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_site_type_dummy_variables | def _get_site_type_dummy_variables(self, sites):
"""
Get site type dummy variables, ``Sc`` (for soft and stiff soil sites)
and ``Sd`` (for rock sites).
"""
Sc = np.zeros_like(sites.vs30)
Sd = np.zeros_like(sites.vs30)
# Soft soil; Vs30 < 360 m/s. Page 199.
... | python | def _get_site_type_dummy_variables(self, sites):
Sc = np.zeros_like(sites.vs30)
Sd = np.zeros_like(sites.vs30)
Sd[sites.vs30 < 360.0] = 1
Sc[np.logical_and(sites.vs30 >= 360.0, sites.vs30 < 760.0)] = 1
return Sc, Sd | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_mechanism | def _get_mechanism(self, rup, C):
"""
Compute the fourth term of the equation described on p. 199:
``f1 * Fn + f2 * Fr``
"""
Fn, Fr = self._get_fault_type_dummy_variables(rup)
return (C['f1'] * Fn) + (C['f2'] * Fr) | python | def _get_mechanism(self, rup, C):
Fn, Fr = self._get_fault_type_dummy_variables(rup)
return (C['f1'] * Fn) + (C['f2'] * Fr) | [
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gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_fault_type_dummy_variables | def _get_fault_type_dummy_variables(self, rup):
"""
The original classification considers four style of faulting categories
(normal, strike-slip, reverse-oblique and reverse).
"""
Fn, Fr = 0, 0
if rup.rake >= -112.5 and rup.rake <= -67.5:
# normal
... | python | def _get_fault_type_dummy_variables(self, rup):
Fn, Fr = 0, 0
if rup.rake >= -112.5 and rup.rake <= -67.5:
Fn = 1
elif rup.rake >= 22.5 and rup.rake <= 157.5:
Fr = 1
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | california_basin_model | def california_basin_model(vs30):
"""
Returns the centred z1.0 (mu_z1) based on the California model
(equation 11)
"""
coeff = 570.94 ** 4.0
model = (-7.15 / 4.0) * np.log(
((vs30 ** 4.0) + coeff) / ((1360.0 ** 4.0) + coeff)
) - np.log(1000.)
return np.exp(model) | python | def california_basin_model(vs30):
coeff = 570.94 ** 4.0
model = (-7.15 / 4.0) * np.log(
((vs30 ** 4.0) + coeff) / ((1360.0 ** 4.0) + coeff)
) - np.log(1000.)
return np.exp(model) | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | japan_basin_model | def japan_basin_model(vs30):
"""
Returns the centred z1.0 (mu_z1) based on the Japan model
(equation 12)
"""
coeff = 412.39 ** 2.0
model = (-5.23 / 2.0) * np.log(
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) - np.log(1000.)
return np.exp(model) | python | def japan_basin_model(vs30):
coeff = 412.39 ** 2.0
model = (-5.23 / 2.0) * np.log(
((vs30 ** 2.0) + coeff) / ((1360.0 ** 2.0) + coeff)
) - np.log(1000.)
return np.exp(model) | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
# extracting dictionary of coefficients specific to required
#... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS[imt]
C_PGA = self.COEFFS[PGA()]
imt_per = 0 if imt.name == 'PGV' else imt.period
pga_rock = self._get_pga_on_rock(C_PGA, rup, dists)
mean = (self._get_magnitude_scalin... | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_pga_on_rock | def _get_pga_on_rock(self, C, rup, dists):
"""
Returns the median PGA on rock, which is a sum of the
magnitude and distance scaling
"""
return np.exp(self._get_magnitude_scaling_term(C, rup) +
self._get_path_scaling(C, dists, rup.mag)) | python | def _get_pga_on_rock(self, C, rup, dists):
return np.exp(self._get_magnitude_scaling_term(C, rup) +
self._get_path_scaling(C, dists, rup.mag)) | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_magnitude_scaling_term | def _get_magnitude_scaling_term(self, C, rup):
"""
Returns the magnitude scling term defined in equation (2)
"""
dmag = rup.mag - C["Mh"]
if rup.mag <= C["Mh"]:
mag_term = (C["e4"] * dmag) + (C["e5"] * (dmag ** 2.0))
else:
mag_term = C["e6"] * dmag... | python | def _get_magnitude_scaling_term(self, C, rup):
dmag = rup.mag - C["Mh"]
if rup.mag <= C["Mh"]:
mag_term = (C["e4"] * dmag) + (C["e5"] * (dmag ** 2.0))
else:
mag_term = C["e6"] * dmag
return self._get_style_of_faulting_term(C, rup) + mag_term | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_style_of_faulting_term | def _get_style_of_faulting_term(self, C, rup):
"""
Get fault type dummy variables
Fault type (Strike-slip, Normal, Thrust/reverse) is
derived from rake angle.
Rakes angles within 30 of horizontal are strike-slip,
angles from 30 to 150 are reverse, and angles from
... | python | def _get_style_of_faulting_term(self, C, rup):
if np.abs(rup.rake) <= 30.0 or (180.0 - np.abs(rup.rake)) <= 30.0:
return C["e1"]
elif rup.rake > 30.0 and rup.rake < 150.0:
return C["e3"]
else:
return C["e2"] | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_path_scaling | def _get_path_scaling(self, C, dists, mag):
"""
Returns the path scaling term given by equation (3)
"""
rval = np.sqrt((dists.rjb ** 2.0) + (C["h"] ** 2.0))
scaling = (C["c1"] + C["c2"] * (mag - self.CONSTS["Mref"])) *\
np.log(rval / self.CONSTS["Rref"])
retur... | python | def _get_path_scaling(self, C, dists, mag):
rval = np.sqrt((dists.rjb ** 2.0) + (C["h"] ** 2.0))
scaling = (C["c1"] + C["c2"] * (mag - self.CONSTS["Mref"])) *\
np.log(rval / self.CONSTS["Rref"])
return scaling + ((C["c3"] + C["Dc3"]) * (rval - self.CONSTS["Rref"])) | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_site_scaling | def _get_site_scaling(self, C, pga_rock, sites, period, rjb):
"""
Returns the site-scaling term (equation 5), broken down into a
linear scaling, a nonlinear scaling and a basin scaling term
"""
flin = self._get_linear_site_term(C, sites.vs30)
fnl = self._get_nonlinear_sit... | python | def _get_site_scaling(self, C, pga_rock, sites, period, rjb):
flin = self._get_linear_site_term(C, sites.vs30)
fnl = self._get_nonlinear_site_term(C, sites.vs30, pga_rock)
fbd = self._get_basin_depth_term(C, sites, period)
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_linear_site_term | def _get_linear_site_term(self, C, vs30):
"""
Returns the linear site scaling term (equation 6)
"""
flin = vs30 / self.CONSTS["Vref"]
flin[vs30 > C["Vc"]] = C["Vc"] / self.CONSTS["Vref"]
return C["c"] * np.log(flin) | python | def _get_linear_site_term(self, C, vs30):
flin = vs30 / self.CONSTS["Vref"]
flin[vs30 > C["Vc"]] = C["Vc"] / self.CONSTS["Vref"]
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_nonlinear_site_term | def _get_nonlinear_site_term(self, C, vs30, pga_rock):
"""
Returns the nonlinear site scaling term (equation 7)
"""
v_s = np.copy(vs30)
v_s[vs30 > 760.] = 760.
# Nonlinear controlling parameter (equation 8)
f_2 = C["f4"] * (np.exp(C["f5"] * (v_s - 360.)) -
... | python | def _get_nonlinear_site_term(self, C, vs30, pga_rock):
v_s = np.copy(vs30)
v_s[vs30 > 760.] = 760.
f_2 = C["f4"] * (np.exp(C["f5"] * (v_s - 360.)) -
np.exp(C["f5"] * 400.))
fnl = self.CONSTS["f1"] + f_2 * np.log((pga_rock + self.CONSTS["f3"]) /
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_basin_depth_term | def _get_basin_depth_term(self, C, sites, period):
"""
In the case of the base model the basin depth term is switched off.
Therefore we return an array of zeros.
"""
return np.zeros(len(sites.vs30), dtype=float) | python | def _get_basin_depth_term(self, C, sites, period):
return np.zeros(len(sites.vs30), dtype=float) | [
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_stddevs | def _get_stddevs(self, C, rup, dists, sites, stddev_types):
"""
Returns the aleatory uncertainty terms described in equations (13) to
(17)
"""
stddevs = []
num_sites = len(sites.vs30)
tau = self._get_inter_event_tau(C, rup.mag, num_sites)
phi = self._get_i... | python | def _get_stddevs(self, C, rup, dists, sites, stddev_types):
stddevs = []
num_sites = len(sites.vs30)
tau = self._get_inter_event_tau(C, rup.mag, num_sites)
phi = self._get_intra_event_phi(C,
rup.mag,
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_inter_event_tau | def _get_inter_event_tau(self, C, mag, num_sites):
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"""
base_vals = np.zeros(num_sites)
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if mag <= 4.5:
return base_vals + C["t1"]
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_intra_event_phi | def _get_intra_event_phi(self, C, mag, rjb, vs30, num_sites):
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magnitude, distance and vs30
"""
base_vals = np.zeros(num_sites)
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base_vals += C["f1"]
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base_vals += (C["f1"] + (C["f2"] - C["f1"]) * (mag - 4.5))
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gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014CaliforniaBasin._get_basin_depth_term | def _get_basin_depth_term(self, C, sites, period):
"""
In the case of the base model the basin depth term is switched off.
Therefore we return an array of zeros.
"""
if period < 0.65:
f_dz1 = np.zeros(len(sites.vs30), dtype=float)
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f_dz1 = C["... | python | def _get_basin_depth_term(self, C, sites, period):
if period < 0.65:
f_dz1 = np.zeros(len(sites.vs30), dtype=float)
else:
f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float)
f_ratio = C["f7"] / C["f6"]
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gem/oq-engine | openquake/hazardlib/gsim/pankow_pechmann_2004.py | PankowPechmann2004.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
C = self.COEFFS[imt]
M = rup.mag - 6
R = np.sqrt(dist... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS[imt]
M = rup.mag - 6
R = np.sqrt(dists.rjb ** 2 + C['h'] ** 2)
gamma = np.array([0 if v > 910. else 1 for v in sites.vs30])
mean = np.zeros_like(R)
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gem/oq-engine | openquake/hazardlib/gsim/pankow_pechmann_2004.py | PankowPechmann2004._get_stddevs | def _get_stddevs(self, C, stddev_types, num_sites):
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"""
assert all(stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
for stddev_type in stddev_types)
if self.DEFINED_FOR_INTENSITY_MEASURE_COMPONENT == 'Random horizon... | python | def _get_stddevs(self, C, stddev_types, num_sites):
assert all(stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
for stddev_type in stddev_types)
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gem/oq-engine | openquake/hazardlib/mfd/multi_mfd.py | MultiMFD.get_min_max_mag | def get_min_max_mag(self):
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"""
m1s, m2s = [], []
for mfd in self:
m1, m2 = mfd.get_min_max_mag()
m1s.append(m1)
m2s.append(m2)
return min(m1s), max(m2s) | python | def get_min_max_mag(self):
m1s, m2s = [], []
for mfd in self:
m1, m2 = mfd.get_min_max_mag()
m1s.append(m1)
m2s.append(m2)
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gem/oq-engine | openquake/hazardlib/mfd/multi_mfd.py | MultiMFD.modify | def modify(self, modification, parameters):
"""
Apply a modification to the underlying point sources, with the
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src.modify(modification, parameters) | python | def modify(self, modification, parameters):
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gem/oq-engine | openquake/hazardlib/gsim/geomatrix_1993.py | Geomatrix1993SSlabNSHMP2008._compute_mean | def _compute_mean(self, C, mag, ztor, rrup):
"""
Compute mean value as in ``subroutine getGeom`` in ``hazgridXnga2.f``
"""
gc0 = 0.2418
ci = 0.3846
gch = 0.00607
g4 = 1.7818
ge = 0.554
gm = 1.414
mean = (
gc0 + ci + ztor * gch ... | python | def _compute_mean(self, C, mag, ztor, rrup):
gc0 = 0.2418
ci = 0.3846
gch = 0.00607
g4 = 1.7818
ge = 0.554
gm = 1.414
mean = (
gc0 + ci + ztor * gch + C['gc1'] +
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gem/oq-engine | openquake/commands/abort.py | abort | def abort(job_id):
"""
Abort the given job
"""
job = logs.dbcmd('get_job', job_id) # job_id can be negative
if job is None:
print('There is no job %d' % job_id)
return
elif job.status not in ('executing', 'running'):
print('Job %d is %s' % (job.id, job.status))
r... | python | def abort(job_id):
job = logs.dbcmd('get_job', job_id)
if job is None:
print('There is no job %d' % job_id)
return
elif job.status not in ('executing', 'running'):
print('Job %d is %s' % (job.id, job.status))
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name = 'oq-job-%d' % job.id
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gem/oq-engine | openquake/baselib/sap.py | get_parentparser | def get_parentparser(parser, description=None, help=True):
"""
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:param description: string used to build a new parser if parser is None
:param help: flag used to build a new parser if parser is None
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if parser is None:
return argparse.ArgumentParser(
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elif hasattr(parser, 'parentparser'):
return parser.parentparser
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gem/oq-engine | openquake/baselib/sap.py | compose | def compose(scripts, name='main', description=None, prog=None,
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assert len(scripts) >= 1, scripts
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gem/oq-engine | openquake/baselib/sap.py | Script._add | def _add(self, name, *args, **kw):
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argname = list(self.argdict)[self._argno]
if argname != name:
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argname = list(self.argdict)[self._argno]
if argname != name:
raise NameError(
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gem/oq-engine | openquake/baselib/sap.py | Script.arg | def arg(self, name, help, type=None, choices=None, metavar=None,
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"""Describe a positional argument"""
kw = dict(help=help, type=type, choices=choices, metavar=metavar,
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default = self.argdict[name]
if default is not NODEFAULT:
... | python | def arg(self, name, help, type=None, choices=None, metavar=None,
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kw = dict(help=help, type=type, choices=choices, metavar=metavar,
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gem/oq-engine | openquake/baselib/sap.py | Script.opt | def opt(self, name, help, abbrev=None,
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type1RecurrenceModel.cumulative_value | def cumulative_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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:param float slip_moment:
:param float slip_moment:
Product of slip (cm/yr) * Area (cm ^ 2) * shear_modulus (dyne-cm)
:param float mmax:
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delta_m = mmax - mag_value
a_1 = self._get_a1(bbar, dbar, slip_moment, mmax)
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type1RecurrenceModel._get_a1 | def _get_a1(bbar, dbar, slip_moment, mmax):
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type1RecurrenceModel.incremental_value | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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delta_m = mmax - mag_value
dirac_term = np.zeros_like(mag_value)
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a_1 = self._... | python | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
delta_m = mmax - mag_value
dirac_term = np.zeros_like(mag_value)
dirac_term[np.fabs(delta_m) < 1.0E-12] = 1.0
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type2RecurrenceModel.cumulative_value | def cumulative_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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Maximum magnitude
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type2RecurrenceModel._get_a2 | def _get_a2(bbar, dbar, slip_moment, mmax):
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type3RecurrenceModel.cumulative_value | def cumulative_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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Returns the rate of events with M > mag_value
:param float slip_moment:
Product of slip (cm/yr) * Area (cm ^ 2) * shear_modulus (dyne-cm)
:param float mmax:
Maximum magnitude
:param... | python | def cumulative_value(self, slip_moment, mmax, mag_value, bbar, dbar):
delta_m = mmax - mag_value
a_3 = self._get_a3(bbar, dbar, slip_moment, mmax)
central_term = np.exp(bbar * delta_m) - 1.0 - (bbar * delta_m)
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type3RecurrenceModel._get_a3 | def _get_a3(bbar, dbar, slip_moment, mmax):
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type3RecurrenceModel.incremental_value | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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a_3 = self._get_a3(bbar, dbar, slip_moment, mmax)
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | AndersonLucoArbitrary.setUp | def setUp(self, mfd_conf):
'''
Input core configuration parameters as specified in the
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:param dict mfd_conf:
Configuration file containing the following attributes:
* 'Type' - Choose between the 1st, 2nd or 3rd type of recurrence
mo... | python | def setUp(self, mfd_conf):
self.mfd_type = mfd_conf['Model_Type']
self.mfd_model = 'Anderson & Luco (Arbitrary) ' + self.mfd_type
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self.bin_width = mfd_conf['MFD_spacing']
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | AndersonLucoArbitrary.get_mmax | def get_mmax(self, mfd_conf, msr, rake, area):
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or using the msr otherwise
:param dict mfd_config:
Configuration file (see setUp for paramters)
:param msr:
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if mfd_conf['Maximum_Magnitude']:
self.mmax = mfd_conf['Maximum_Magnitude']
else:
self.mmax = msr.get_median_mag(area, rake)
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gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | AndersonLucoArbitrary.get_mfd | def get_mfd(self, slip, area, shear_modulus=30.0):
'''
Calculates activity rate on the fault
:param float slip:
Slip rate in mm/yr
:param fault_area:
Width of the fault (km)
:param float shear_modulus:
Shear modulus of the fault (GPa)
... | python | def get_mfd(self, slip, area, shear_modulus=30.0):
slip_moment = (shear_modulus * 1E10) * (area * 1E10) * (slip / 10.)
dbar = D_VALUE * np.log(10.0)
bbar = self.b_value * np.log(10.0)
mags = np.arange(self.mmin - (self.bin_width / 2.),
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gem/oq-engine | openquake/commands/reduce_sm.py | reduce_sm | def reduce_sm(calc_id):
"""
Reduce the source model of the given (pre)calculation by discarding all
sources that do not contribute to the hazard.
"""
with datastore.read(calc_id) as dstore:
oqparam = dstore['oqparam']
info = dstore['source_info'].value
ok = info['weight'] > 0... | python | def reduce_sm(calc_id):
with datastore.read(calc_id) as dstore:
oqparam = dstore['oqparam']
info = dstore['source_info'].value
ok = info['weight'] > 0
source_ids = set(info[ok]['source_id'])
with performance.Monitor() as mon:
readinput.reduce_source_model(
... | [
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
C = self.COEFFS[imt]
mean = (
self._get_magnitude_... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS[imt]
mean = (
self._get_magnitude_term(C, rup.mag) +
self._get_distance_term(C, rup.mag, dists.rrup) +
self._get_style_of_faulting_term(C, rup.rake) +
self._get_... | [
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009._get_magnitude_term | def _get_magnitude_term(self, C, mag):
"""
Returns the magnitude scaling term.
"""
lny = C['C1'] + (C['C3'] * ((8.5 - mag) ** 2.))
if mag > 6.3:
return lny + (-C['H'] * C['C5']) * (mag - 6.3)
else:
return lny + C['C2'] * (mag - 6.3) | python | def _get_magnitude_term(self, C, mag):
lny = C['C1'] + (C['C3'] * ((8.5 - mag) ** 2.))
if mag > 6.3:
return lny + (-C['H'] * C['C5']) * (mag - 6.3)
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009._get_distance_term | def _get_distance_term(self, C, mag, rrup):
"""
Returns the distance scaling term
"""
return (C['C4'] + C['C5'] * (mag - 6.3)) *\
np.log(np.sqrt(rrup ** 2. + np.exp(C['H']) ** 2.)) | python | def _get_distance_term(self, C, mag, rrup):
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009._get_style_of_faulting_term | def _get_style_of_faulting_term(self, C, rake):
"""
Returns the style of faulting factor
"""
f_n, f_r = self._get_fault_type_dummy_variables(rake)
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f_n, f_r = self._get_fault_type_dummy_variables(rake)
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009._get_fault_type_dummy_variables | def _get_fault_type_dummy_variables(self, rake):
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Defines the fault type dummy variables for normal faulting (f_n) and
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"""
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f_n, f_r = 0, 0
if rake >= -120 and rake <= -60:
f_n = 1
elif rake >= 30 and rake <= 150:
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gem/oq-engine | openquake/hazardlib/gsim/lin_2009.py | Lin2009._get_stddevs | def _get_stddevs(self, C, stddev_types, nsites):
"""
Compute total standard deviation, see table 4.2, page 50.
"""
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stddevs = []
for stddev_type in stddev_types:
assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
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gem/oq-engine | openquake/hazardlib/imt.py | imt2tup | def imt2tup(string):
"""
>>> imt2tup('PGA')
('PGA',)
>>> imt2tup('SA(1.0)')
('SA', 1.0)
>>> imt2tup('SA(1)')
('SA', 1.0)
"""
s = string.strip()
if not s.endswith(')'):
# no parenthesis, PGA is considered the same as PGA()
return (s,)
name, rest = s.split('(', ... | python | def imt2tup(string):
s = string.strip()
if not s.endswith(')'):
return (s,)
name, rest = s.split('(', 1)
return (name,) + tuple(float(x) for x in ast.literal_eval(rest[:-1] + ',')) | [
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gem/oq-engine | openquake/baselib/slots.py | with_slots | def with_slots(cls):
"""
Decorator for a class with _slots_. It automatically defines
the methods __eq__, __ne__, assert_equal.
"""
def _compare(self, other):
for slot in self.__class__._slots_:
attr = operator.attrgetter(slot)
source = attr(self)
target =... | python | def with_slots(cls):
def _compare(self, other):
for slot in self.__class__._slots_:
attr = operator.attrgetter(slot)
source = attr(self)
target = attr(other)
if isinstance(source, numpy.ndarray):
eq = numpy.array_equal(source, target)
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | make_iml4 | def make_iml4(R, iml_disagg, imtls=None, poes_disagg=(None,), curves=()):
"""
:returns: an ArrayWrapper over a 4D array of shape (N, R, M, P)
"""
if imtls is None:
imtls = {imt: [iml] for imt, iml in iml_disagg.items()}
N = len(curves) or 1
M = len(imtls)
P = len(poes_disagg)
arr... | python | def make_iml4(R, iml_disagg, imtls=None, poes_disagg=(None,), curves=()):
if imtls is None:
imtls = {imt: [iml] for imt, iml in iml_disagg.items()}
N = len(curves) or 1
M = len(imtls)
P = len(poes_disagg)
arr = numpy.zeros((N, R, M, P))
imts = [from_string(imt) for imt in imtls]
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | collect_bin_data | def collect_bin_data(ruptures, sitecol, cmaker, iml4,
truncation_level, n_epsilons, monitor=Monitor()):
"""
:param ruptures: a list of ruptures
:param sitecol: a SiteCollection instance
:param cmaker: a ContextMaker instance
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truncation_level, n_epsilons, monitor=Monitor()):
truncnorm = scipy.stats.truncnorm(-truncation_level, truncation_level)
epsilons = numpy.linspace(truncnorm.a, truncnorm.b, n_epsilons + 1)
acc = cmaker.disaggregate(
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | lon_lat_bins | def lon_lat_bins(bb, coord_bin_width):
"""
Define bin edges for disaggregation histograms.
Given bins data as provided by :func:`collect_bin_data`, this function
finds edges of histograms, taking into account maximum and minimum values
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west, south, east, north = bb
west = numpy.floor(west / coord_bin_width) * coord_bin_width
east = numpy.ceil(east / coord_bin_width) * coord_bin_width
lon_extent = get_longitudinal_extent(west, east)
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | get_shape | def get_shape(bin_edges, sid):
"""
:returns:
the shape of the disaggregation matrix for the given site, of form
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"""
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins = bin_edges
return (len(mag_bins) - 1, len(dist_bins) - 1,
l... | python | def get_shape(bin_edges, sid):
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins = bin_edges
return (len(mag_bins) - 1, len(dist_bins) - 1,
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | build_disagg_matrix | def build_disagg_matrix(bdata, bin_edges, sid, mon=Monitor):
"""
:param bdata: a dictionary of probabilities of no exceedence
:param bin_edges: bin edges
:param sid: site index
:param mon: a Monitor instance
:returns: a dictionary key -> matrix|pmf for each key in bdata
"""
with mon('bui... | python | def build_disagg_matrix(bdata, bin_edges, sid, mon=Monitor):
with mon('build_disagg_matrix'):
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins = bin_edges
dim1, dim2, dim3, dim4, dim5 = shape = get_shape(bin_edges, sid)
mags_idx = ... | [
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | _digitize_lons | def _digitize_lons(lons, lon_bins):
"""
Return indices of the bins to which each value in lons belongs.
Takes into account the case in which longitude values cross the
international date line.
:parameter lons:
An instance of `numpy.ndarray`.
:parameter lons_bins:
An instance of ... | python | def _digitize_lons(lons, lon_bins):
if cross_idl(lon_bins[0], lon_bins[-1]):
idx = numpy.zeros_like(lons, dtype=numpy.int)
for i_lon in range(len(lon_bins) - 1):
extents = get_longitudinal_extent(lons, lon_bins[i_lon + 1])
lon_idx = extents > 0
if i_lon != 0:... | [
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | disaggregation | def disaggregation(
sources, site, imt, iml, gsim_by_trt, truncation_level,
n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width,
source_filter=filters.nofilter, filter_distance='rjb'):
"""
Compute "Disaggregation" matrix representing conditional probability of an
intensity mes... | python | def disaggregation(
sources, site, imt, iml, gsim_by_trt, truncation_level,
n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width,
source_filter=filters.nofilter, filter_distance='rjb'):
trts = sorted(set(src.tectonic_region_type for src in sources))
trt_num = dict((trt, i) for... | [
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | mag_pmf | def mag_pmf(matrix):
"""
Fold full disaggregation matrix to magnitude PMF.
:returns:
1d array, a histogram representing magnitude PMF.
"""
nmags, ndists, nlons, nlats, neps = matrix.shape
mag_pmf = numpy.zeros(nmags)
for i in range(nmags):
mag_pmf[i] = numpy.prod(
... | python | def mag_pmf(matrix):
nmags, ndists, nlons, nlats, neps = matrix.shape
mag_pmf = numpy.zeros(nmags)
for i in range(nmags):
mag_pmf[i] = numpy.prod(
[1. - matrix[i, j, k, l, m]
for j in range(ndists)
for k in range(nlons)
for l in range(nlats)
... | [
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | trt_pmf | def trt_pmf(matrices):
"""
Fold full disaggregation matrix to tectonic region type PMF.
:param matrices:
a matrix with T submatrices
:returns:
an array of T probabilities one per each tectonic region type
"""
ntrts, nmags, ndists, nlons, nlats, neps = matrices.shape
pmf = nu... | python | def trt_pmf(matrices):
ntrts, nmags, ndists, nlons, nlats, neps = matrices.shape
pmf = numpy.zeros(ntrts)
for t in range(ntrts):
pmf[t] = 1. - numpy.prod(
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gem/oq-engine | openquake/hazardlib/calc/disagg.py | lon_lat_trt_pmf | def lon_lat_trt_pmf(matrices):
"""
Fold full disaggregation matrices to lon / lat / TRT PMF.
:param matrices:
a matrix with T submatrices
:returns:
3d array. First dimension represents longitude histogram bins,
second one latitude histogram bins, third one trt histogram bins.
... | python | def lon_lat_trt_pmf(matrices):
res = numpy.array([lon_lat_pmf(mat) for mat in matrices])
return res.transpose(1, 2, 0) | [
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gem/oq-engine | openquake/commands/db.py | db | def db(cmd, args=()):
"""
Run a database command
"""
if cmd not in commands:
okcmds = '\n'.join(
'%s %s' % (name, repr(' '.join(args)) if args else '')
for name, args in sorted(commands.items()))
print('Invalid command "%s": choose one from\n%s' % (cmd, okcmds))
... | python | def db(cmd, args=()):
if cmd not in commands:
okcmds = '\n'.join(
'%s %s' % (name, repr(' '.join(args)) if args else '')
for name, args in sorted(commands.items()))
print('Invalid command "%s": choose one from\n%s' % (cmd, okcmds))
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gem/oq-engine | openquake/hmtk/faults/fault_geometries.py | SimpleFaultGeometry.get_area | def get_area(self):
'''
Calculates the area of the fault (km ** 2.) as the product of length
(km) and downdip width (km)
'''
d_z = self.lower_depth - self.upper_depth
self.downdip_width = d_z / np.sin(self.dip * np.pi / 180.)
self.surface_width = self.downdip_widt... | python | def get_area(self):
d_z = self.lower_depth - self.upper_depth
self.downdip_width = d_z / np.sin(self.dip * np.pi / 180.)
self.surface_width = self.downdip_width * np.cos(self.dip *
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gem/oq-engine | openquake/commands/download_shakemap.py | download_shakemap | def download_shakemap(id):
"""
Example of usage: utils/shakemap usp000fjta
"""
with performance.Monitor('shakemap', measuremem=True) as mon:
dest = '%s.npy' % id
numpy.save(dest, download_array(id))
print(mon)
print('Saved %s' % dest) | python | def download_shakemap(id):
with performance.Monitor('shakemap', measuremem=True) as mon:
dest = '%s.npy' % id
numpy.save(dest, download_array(id))
print(mon)
print('Saved %s' % dest) | [
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gem/oq-engine | openquake/hazardlib/stats.py | mean_curve | def mean_curve(values, weights=None):
"""
Compute the mean by using numpy.average on the first axis.
"""
if weights is None:
weights = [1. / len(values)] * len(values)
if not isinstance(values, numpy.ndarray):
values = numpy.array(values)
return numpy.average(values, axis=0, weig... | python | def mean_curve(values, weights=None):
if weights is None:
weights = [1. / len(values)] * len(values)
if not isinstance(values, numpy.ndarray):
values = numpy.array(values)
return numpy.average(values, axis=0, weights=weights) | [
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gem/oq-engine | openquake/hazardlib/stats.py | quantile_curve | def quantile_curve(quantile, curves, weights=None):
"""
Compute the weighted quantile aggregate of a set of curves.
:param quantile:
Quantile value to calculate. Should be in the range [0.0, 1.0].
:param curves:
Array of R PoEs (possibly arrays)
:param weights:
Array-like of... | python | def quantile_curve(quantile, curves, weights=None):
if not isinstance(curves, numpy.ndarray):
curves = numpy.array(curves)
R = len(curves)
if weights is None:
weights = numpy.ones(R) / R
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weights = numpy.array(weights)
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gem/oq-engine | openquake/hazardlib/stats.py | compute_pmap_stats | def compute_pmap_stats(pmaps, stats, weights, imtls):
"""
:param pmaps:
a list of R probability maps
:param stats:
a sequence of S statistic functions
:param weights:
a list of ImtWeights
:param imtls:
a DictArray of intensity measure types
:returns:
a pro... | python | def compute_pmap_stats(pmaps, stats, weights, imtls):
sids = set()
p0 = next(iter(pmaps))
L = p0.shape_y
for pmap in pmaps:
sids.update(pmap)
assert pmap.shape_y == L, (pmap.shape_y, L)
if len(sids) == 0:
raise ValueError('All empty probability maps!')
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gem/oq-engine | openquake/hazardlib/stats.py | compute_stats | def compute_stats(array, stats, weights):
"""
:param array:
an array of R elements (which can be arrays)
:param stats:
a sequence of S statistic functions
:param weights:
a list of R weights
:returns:
an array of S elements (which can be arrays)
"""
result = n... | python | def compute_stats(array, stats, weights):
result = numpy.zeros((len(stats),) + array.shape[1:], array.dtype)
for i, func in enumerate(stats):
result[i] = apply_stat(func, array, weights)
return result | [
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gem/oq-engine | openquake/hazardlib/stats.py | compute_stats2 | def compute_stats2(arrayNR, stats, weights):
"""
:param arrayNR:
an array of (N, R) elements
:param stats:
a sequence of S statistic functions
:param weights:
a list of R weights
:returns:
an array of (N, S) elements
"""
newshape = list(arrayNR.shape)
if n... | python | def compute_stats2(arrayNR, stats, weights):
newshape = list(arrayNR.shape)
if newshape[1] != len(weights):
raise ValueError('Got %d weights but %d values!' %
(len(weights), newshape[1]))
newshape[1] = len(stats)
newarray = numpy.zeros(newshape, arrayNR.dtype)
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gem/oq-engine | openquake/hazardlib/stats.py | apply_stat | def apply_stat(f, arraylist, *extra, **kw):
"""
:param f: a callable arraylist -> array (of the same shape and dtype)
:param arraylist: a list of arrays of the same shape and dtype
:param extra: additional positional arguments
:param kw: keyword arguments
:returns: an array of the same shape and... | python | def apply_stat(f, arraylist, *extra, **kw):
dtype = arraylist[0].dtype
shape = arraylist[0].shape
if dtype.names:
new = numpy.zeros(shape, dtype)
for name in dtype.names:
new[name] = f([arr[name] for arr in arraylist], *extra, **kw)
return new
else:
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gem/oq-engine | openquake/hazardlib/stats.py | set_rlzs_stats | def set_rlzs_stats(dstore, prefix, arrayNR=None):
"""
:param dstore: a DataStore object
:param prefix: dataset prefix
:param arrayNR: an array of shape (N, R, ...)
"""
if arrayNR is None:
# assume the -rlzs array is already stored
arrayNR = dstore[prefix + '-rlzs'].value
else... | python | def set_rlzs_stats(dstore, prefix, arrayNR=None):
if arrayNR is None:
arrayNR = dstore[prefix + '-rlzs'].value
else:
dstore[prefix + '-rlzs'] = arrayNR
R = arrayNR.shape[1]
if R > 1:
stats = dstore['oqparam'].hazard_stats()
statnames, statfuncs = zi... | [
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gem/oq-engine | openquake/hazardlib/gsim/toro_2002.py | ToroEtAl2002.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
assert all(stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
assert all(stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
for stddev_type in stddev_types)
C = self.COEFFS[imt]
mean = self._compute_mean(C, rup.mag, dists.rjb)
stddevs = self._co... | [
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gem/oq-engine | openquake/hazardlib/gsim/toro_2002.py | ToroEtAl2002._compute_term1 | def _compute_term1(self, C, mag):
"""
Compute magnitude dependent terms (2nd and 3rd) in equation 3
page 46.
"""
mag_diff = mag - 6
return C['c2'] * mag_diff + C['c3'] * mag_diff ** 2 | python | def _compute_term1(self, C, mag):
mag_diff = mag - 6
return C['c2'] * mag_diff + C['c3'] * mag_diff ** 2 | [
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gem/oq-engine | openquake/hazardlib/gsim/toro_2002.py | ToroEtAl2002._compute_term2 | def _compute_term2(self, C, mag, rjb):
"""
Compute distance dependent terms (4th, 5th and 6th) in equation 3
page 46. The factor 'RM' is computed according to the 2002 model
(equation 4-3).
"""
RM = np.sqrt(rjb ** 2 + (C['c7'] ** 2) *
np.exp(-1.25 + 0... | python | def _compute_term2(self, C, mag, rjb):
RM = np.sqrt(rjb ** 2 + (C['c7'] ** 2) *
np.exp(-1.25 + 0.227 * mag) ** 2)
return (-C['c4'] * np.log(RM) -
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gem/oq-engine | openquake/hazardlib/gsim/toro_2002.py | ToroEtAl2002._compute_mean | def _compute_mean(self, C, mag, rjb):
"""
Compute mean value according to equation 3, page 46.
"""
mean = (C['c1'] +
self._compute_term1(C, mag) +
self._compute_term2(C, mag, rjb))
return mean | python | def _compute_mean(self, C, mag, rjb):
mean = (C['c1'] +
self._compute_term1(C, mag) +
self._compute_term2(C, mag, rjb))
return mean | [
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gem/oq-engine | openquake/hazardlib/gsim/toro_2002.py | ToroEtAl2002._compute_stddevs | def _compute_stddevs(self, C, mag, rjb, imt, stddev_types):
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"""
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sigma_ale_m = np.interp(mag, [5.0, 5.5, 8.0],
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[C['m50'], C['m55'], C['m80']])
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gem/oq-engine | openquake/hazardlib/gsim/mgmpe/nrcan15_site_term.py | NRCan15SiteTerm.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stds_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
# Prepare sites
sites_rock = copy.deepcopy(sites)
sites_... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stds_types):
sites_rock = copy.deepcopy(sites)
sites_rock.vs30 = np.ones_like(sites_rock.vs30) * 760.
mean, stddvs = self.gmpe.get_mean_and_stddevs(sites_rock, rup, dists,
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gem/oq-engine | openquake/hazardlib/gsim/mgmpe/nrcan15_site_term.py | NRCan15SiteTerm.BA08_AB06 | def BA08_AB06(self, vs30, imt, pgar):
"""
Computes amplification factor similarly to what is done in the 2015
version of the Canada building code. An initial version of this code
was kindly provided by Michal Kolaj - Geological Survey of Canada
:param vs30:
Can be ei... | python | def BA08_AB06(self, vs30, imt, pgar):
fa = np.ones_like(vs30)
if np.isscalar(vs30):
vs30 = np.array([vs30])
if np.isscalar(pgar):
pgar = np.array([pgar])
vs = copy.copy(vs30)
vs[vs >= 2000] = 1999.
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gem/oq-engine | openquake/calculators/scenario_damage.py | scenario_damage | def scenario_damage(riskinputs, riskmodel, param, monitor):
"""
Core function for a damage computation.
:param riskinputs:
:class:`openquake.risklib.riskinput.RiskInput` objects
:param riskmodel:
a :class:`openquake.risklib.riskinput.CompositeRiskModel` instance
:param monitor:
... | python | def scenario_damage(riskinputs, riskmodel, param, monitor):
L = len(riskmodel.loss_types)
D = len(riskmodel.damage_states)
E = param['number_of_ground_motion_fields']
R = riskinputs[0].hazard_getter.num_rlzs
result = dict(d_asset=[], d_event=numpy.zeros((E, R, L, D), F64),
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gem/oq-engine | openquake/calculators/views.py | form | def form(value):
"""
Format numbers in a nice way.
>>> form(0)
'0'
>>> form(0.0)
'0.0'
>>> form(0.0001)
'1.000E-04'
>>> form(1003.4)
'1,003'
>>> form(103.4)
'103'
>>> form(9.3)
'9.30000'
>>> form(-1.2)
'-1.2'
"""
if isinstance(value, FLOAT + INT):... | python | def form(value):
if isinstance(value, FLOAT + INT):
if value <= 0:
return str(value)
elif value < .001:
return '%.3E' % value
elif value < 10 and isinstance(value, FLOAT):
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gem/oq-engine | openquake/calculators/views.py | rst_table | def rst_table(data, header=None, fmt=None):
"""
Build a .rst table from a matrix.
>>> tbl = [['a', 1], ['b', 2]]
>>> print(rst_table(tbl, header=['Name', 'Value']))
==== =====
Name Value
==== =====
a 1
b 2
==== =====
"""
if header is None and hasattr(da... | python | def rst_table(data, header=None, fmt=None):
if header is None and hasattr(data, '_fields'):
header = data._fields
try:
data.dtype.fields
except AttributeError:
header = header or ()
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gem/oq-engine | openquake/calculators/views.py | sum_tbl | def sum_tbl(tbl, kfield, vfields):
"""
Aggregate a composite array and compute the totals on a given key.
>>> dt = numpy.dtype([('name', (bytes, 10)), ('value', int)])
>>> tbl = numpy.array([('a', 1), ('a', 2), ('b', 3)], dt)
>>> sum_tbl(tbl, 'name', ['value'])['value']
array([3, 3])
"""
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pairs = [(n, tbl.dtype[n]) for n in [kfield] + vfields]
dt = numpy.dtype(pairs + [('counts', int)])
def sum_all(group):
vals = numpy.zeros(1, dt)[0]
for rec in group:
for vfield in vfields:
vals[vfield] += rec[vfield]
... | [
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>>> dt = numpy.dtype([('name', (bytes, 10)), ('value', int)])
>>> tbl = numpy.array([('a', 1), ('a', 2), ('b', 3)], dt)
>>> sum_tbl(tbl, 'name', ['value'])['value']
array([3, 3]) | [
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gem/oq-engine | openquake/calculators/views.py | view_slow_sources | def view_slow_sources(token, dstore, maxrows=20):
"""
Returns the slowest sources
"""
info = dstore['source_info'].value
info.sort(order='calc_time')
return rst_table(info[::-1][:maxrows]) | python | def view_slow_sources(token, dstore, maxrows=20):
info = dstore['source_info'].value
info.sort(order='calc_time')
return rst_table(info[::-1][:maxrows]) | [
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gem/oq-engine | openquake/calculators/views.py | view_contents | def view_contents(token, dstore):
"""
Returns the size of the contents of the datastore and its total size
"""
try:
desc = dstore['oqparam'].description
except KeyError:
desc = ''
data = sorted((dstore.getsize(key), key) for key in dstore)
rows = [(key, humansize(nbytes)) for... | python | def view_contents(token, dstore):
try:
desc = dstore['oqparam'].description
except KeyError:
desc = ''
data = sorted((dstore.getsize(key), key) for key in dstore)
rows = [(key, humansize(nbytes)) for nbytes, key in data]
total = '\n%s : %s' % (
dstore.filename, humansize... | [
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gem/oq-engine | openquake/calculators/views.py | view_job_info | def view_job_info(token, dstore):
"""
Determine the amount of data transferred from the controller node
to the workers and back in a classical calculation.
"""
data = [['task', 'sent', 'received']]
for task in dstore['task_info']:
dset = dstore['task_info/' + task]
if 'argnames' ... | python | def view_job_info(token, dstore):
data = [['task', 'sent', 'received']]
for task in dstore['task_info']:
dset = dstore['task_info/' + task]
if 'argnames' in dset.attrs:
argnames = dset.attrs['argnames'].split()
totsent = dset.attrs['sent']
sent = ['%s=%s'... | [
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gem/oq-engine | openquake/calculators/views.py | avglosses_data_transfer | def avglosses_data_transfer(token, dstore):
"""
Determine the amount of average losses transferred from the workers to the
controller node in a risk calculation.
"""
oq = dstore['oqparam']
N = len(dstore['assetcol'])
R = dstore['csm_info'].get_num_rlzs()
L = len(dstore.get_attr('risk_mod... | python | def avglosses_data_transfer(token, dstore):
oq = dstore['oqparam']
N = len(dstore['assetcol'])
R = dstore['csm_info'].get_num_rlzs()
L = len(dstore.get_attr('risk_model', 'loss_types'))
ct = oq.concurrent_tasks
size_bytes = N * R * L * 8 * ct
return (
'%d asset(s) x %d realiza... | [
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