# The Hazard Library
# Copyright (C) 2012-2023 GEM Foundation
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
Module :mod:`openquake.hazardlib.const` defines various constants.
"""
from enum import Enum
import numpy as np
[docs]class TRT(Enum):
"""
Container for constants that define some of the common Tectonic Region
Types.
"""
# Constant values correspond to the NRML schema definition.
ACTIVE_SHALLOW_CRUST = 'Active Shallow Crust'
STABLE_CONTINENTAL = 'Stable Shallow Crust'
SUBDUCTION_INTERFACE = 'Subduction Interface'
SUBDUCTION_INTRASLAB = 'Subduction IntraSlab'
UPPER_MANTLE = "Upper Mantle"
VOLCANIC = 'Volcanic'
GEOTHERMAL = 'Geothermal'
INDUCED = 'Induced'
# NB: cannot be an enum because it would break the Strong Motion Toolkit :-(
[docs]class StdDev(object):
"""
GSIM standard deviation represents ground shaking variability at a site.
"""
TOTAL = 'Total'
#: Standard deviation representing ground shaking variability
#: within different events.
INTER_EVENT = 'Inter event'
#: Standard deviation representing ground shaking variability
#: within a single event.
INTRA_EVENT = 'Intra event'
#: Total standard deviation, defined as the square root of the sum
#: of inter- and intra-event squared standard deviations, represents
#: the total ground shaking variability, and is the only one that
#: is used for calculating a probability of intensity exceedance
#: (see :func:`openquake.hazardlib.gsim.base.get_poes`).
EVENT = 'Event'
#: Used in event based calculations, correspond to TOTAL if the gsim
#: is defined for TOTAL, otherwise to the pair (INTER_EVENT, INTRA_EVENT)
ALL = 'All'
#: Compute all the standard deviations for which the GMPE is defined
StdDev.idx = {StdDev.TOTAL: 0, StdDev.INTER_EVENT: 1, StdDev.INTRA_EVENT: 2}
[docs]class IMC(Enum):
"""
The intensity measure component is the component of interest
of ground shaking for an
:mod:`intensity measure <openquake.hazardlib.imt>`.
"""
#: The horizontal component.
HORIZONTAL = 'Horizontal'
#: The median horizontal component.
MEDIAN_HORIZONTAL = 'Median horizontal'
#: Usually defined as the geometric average of the maximum
#: of the two horizontal components (which may not occur
#: at the same time).
GEOMETRIC_MEAN = 'Average Horizontal'
#: An orientation-independent alternative to :attr:`AVERAGE_HORIZONTAL`.
#: Defined at Boore et al. (2006, Bull. Seism. Soc. Am. 96, 1502-1511)
#: and is used for all the NGA GMPEs.
GMRotI50 = 'Average Horizontal (GMRotI50)'
#: The geometric mean of the records rotated into the most adverse
#: direction for the structure.
GMRotD100 = "Average Horizontal (GMRotD100)"
#: An orientation-independent alternative to :attr:`AVERAGE_HORIZONTAL`.
#: Defined at Boore et al. (2006, Bull. Seism. Soc. Am. 96, 1502-1511)
#: and is used for all the NGA GMPEs.
RotD50 = 'Average Horizontal (RotD50)'
#:
RotD100 = 'Horizontal Maximum Direction (RotD100)'
#: A randomly chosen horizontal component.
RANDOM_HORIZONTAL = 'Random horizontal'
#: The largest value obtained from two perpendicular horizontal
#: components.
GREATER_OF_TWO_HORIZONTAL = 'Greater of two horizontal'
#: The vertical component.
VERTICAL = 'Vertical'
#: "Vectorial addition: a_V = sqrt(max|a_1(t)|^2 + max|a_2(t)|^2)).
#: This means that the maximum ground amplitudes occur simultaneously on
#: the two horizontal components; this is a conservative assumption."
#: p. 53 of Douglas (2003, Earth-Sci. Rev. 61, 43-104)
VECTORIAL = 'Square root of sum of squares of peak horizontals'
#: "the peak square root of the sum of squares of two orthogonal
#: horizontal components in the time domain"
#: p. 880 of Kanno et al. (2006, Bull. Seism. Soc. Am. 96, 879-897)
PEAK_SRSS_HORIZONTAL = 'Peak square root of sum of squares of horizontals'
#: A vertical-to-horizontal spectral ratio
VERTICAL_TO_HORIZONTAL_RATIO = 'Vertical-to-Horizontal Ratio'
# #### horizontal components that can be converted into geometric means #### #
OK_COMPONENTS = ['GMRotI50', 'RANDOM_HORIZONTAL',
'GREATER_OF_TWO_HORIZONTAL', 'RotD50']
COEFF = {IMC.GMRotI50: [1, 1, 0.03, 0.04, 1],
IMC.RANDOM_HORIZONTAL: [1, 1, 0.07, 0.11, 1.05],
IMC.GREATER_OF_TWO_HORIZONTAL: [0.1, 1.117, 0.53, 1.165, 4.48, 1.195,
8.70, 1.266, 1.266],
IMC.RotD50: [0.09, 1.009, 0.58, 1.028, 4.59, 1.042, 8.93, 1.077,
1.077]}
COEFF_PGA_PGV = {IMC.GMRotI50: [1, 0.02, 1, 1, 0.03, 1],
IMC.RANDOM_HORIZONTAL: [1, 0.07, 1.03],
IMC.GREATER_OF_TWO_HORIZONTAL: [1.117, 0, 1, 1, 0, 1],
IMC.RotD50: [1.009, 0, 1, 1, 0, 1]}
# used in ContextMaker.set_conv to build the conversion coefficients
[docs]def apply_conversion(imc, imt):
"""
:param imc: IMC instance
:param imt: intensity measure type instance
:returns: conversion coefficients conv_median, conv_sigma, rstd
"""
C = COEFF[imc]
C_PGA_PGV = COEFF_PGA_PGV[imc]
if imt.string == 'PGA':
conv_median = C_PGA_PGV[0]
conv_sigma = C_PGA_PGV[1]
rstd = C_PGA_PGV[2]
elif imt.string == 'PGV':
conv_median = C_PGA_PGV[3]
conv_sigma = C_PGA_PGV[4]
rstd = C_PGA_PGV[5]
else:
T = imt.period
if imc.name in ('RotD50', 'GREATER_OF_TWO_HORIZONTAL'):
term1 = C[1] + (C[3]-C[1]) / np.log(C[2]/C[0]) * np.log(T/C[0])
term2 = C[3] + (C[5]-C[3]) / np.log(C[4]/C[2]) * np.log(T/C[2])
term3 = C[5] + (C[7]-C[5]) / np.log(C[6]/C[4]) * np.log(T/C[4])
term4 = C[8]
tmax = np.maximum(
np.minimum(term1, term2), np.minimum(term3, term4))
conv_median = np.maximum(C[1], tmax)
conv_sigma = 0
rstd = 1
else:
if T <= 0.15:
conv_median = C[0]
conv_sigma = C[2]
elif T > 0.8:
conv_median = C[1]
conv_sigma = C[3]
else:
conv_median = (C[0] + (C[1]-C[0]) *
np.log10(T/0.15) / np.log10(0.8/0.15))
conv_sigma = (C[2] + (C[3]-C[2]) *
np.log10(T/0.15) / np.log10(0.8/0.15))
rstd = C[4]
return conv_median, conv_sigma, rstd
IMC.apply_conversion = apply_conversion