# The Hazard Library
# Copyright (C) 2012-2021 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.mfd.truncated_gr` defines a Truncated
Gutenberg-Richter MFD.
"""
import math
import numpy as np
from openquake.baselib.python3compat import round
from openquake.hazardlib.mfd.base import BaseMFD
[docs]class TruncatedGRMFD(BaseMFD):
"""
Truncated Gutenberg-Richter MFD is defined in a functional form.
The annual occurrence rate for a specific bin (magnitude band)
is defined as ::
rate = 10 ** (a_val - b_val * mag_lo) - 10 ** (a_val - b_val * mag_hi)
where
* ``a_val`` is the cumulative ``a`` value (``10 ** a`` is the number
of earthquakes per year with magnitude greater than or equal to 0),
* ``b_val`` is Gutenberg-Richter ``b`` value -- the decay rate
of exponential distribution. It describes the relative size distribution
of earthquakes: a higher ``b`` value indicates a relatively larger
proportion of small events and vice versa.
* ``mag_lo`` and ``mag_hi`` are lower and upper magnitudes of a specific
bin respectively.
:param min_mag:
The lowest possible magnitude for this MFD. The first bin in the
:meth:`result histogram <get_annual_occurrence_rates>` will be aligned
to make its left border match this value.
:param max_mag:
The highest possible magnitude. The same as for ``min_mag``: the last
bin in the histogram will correspond to the magnitude value equal to
``max_mag - bin_width / 2``.
:param bin_width:
A positive float value -- the width of a single histogram bin.
Values for ``min_mag`` and ``max_mag`` don't have to be aligned with
respect to ``bin_width``. They get rounded accordingly anyway so that
both are divisible by ``bin_width`` just before converting a function
to a histogram. See :meth:`_get_min_mag_and_num_bins`.
"""
MODIFICATIONS = {'increment_max_mag', 'set_max_mag', 'increment_b',
'set_ab'}
def __init__(self, min_mag, max_mag, bin_width, a_val, b_val):
self.min_mag = min_mag
self.max_mag = max_mag
self.bin_width = bin_width
self.a_val = a_val
self.b_val = b_val
self.check_constraints()
[docs] def check_constraints(self):
"""
Checks the following constraints:
* Bin width is greater than 0.
* Minimum magnitude is positive.
* Maximum magnitude is greater than minimum magnitude
by at least one bin width (or equal to that value).
* ``b`` value is positive.
"""
if not self.bin_width > 0:
raise ValueError('bin width %g must be positive' % self.bin_width)
if not self.min_mag >= 0:
raise ValueError('minimum magnitude %g must be non-negative'
% self.min_mag)
if not self.max_mag >= self.min_mag + self.bin_width:
raise ValueError('maximum magnitude %g must be higher than '
'minimum magnitude %g by '
'bin width %g at least'
% (self.max_mag, self.min_mag, self.bin_width))
if not 0 < self.b_val:
raise ValueError('b-value %g must be non-negative' % self.b_val)
def _get_rate(self, mag):
"""
Calculate and return an annual occurrence rate for a specific bin.
:param mag:
Magnitude value corresponding to the center of the bin of interest.
:returns:
Float number, the annual occurrence rate calculated using formula
described in :class:`TruncatedGRMFD`.
"""
mag_lo = mag - self.bin_width / 2.0
mag_hi = mag + self.bin_width / 2.0
return (10 ** (self.a_val - self.b_val * mag_lo)
- 10 ** (self.a_val - self.b_val * mag_hi))
def _get_min_mag_and_num_bins(self):
"""
Estimate the number of bins in the histogram and return it
along with the first bin center abscissa (magnitude) value.
Rounds ``min_mag`` and ``max_mag`` with respect to ``bin_width``
to make the distance between them include integer number of bins.
:returns:
A tuple of two items: first bin center and total number of bins.
"""
min_mag = round(self.min_mag / self.bin_width) * self.bin_width
max_mag = round(self.max_mag / self.bin_width) * self.bin_width
if min_mag != max_mag:
min_mag += self.bin_width / 2.0
max_mag -= self.bin_width / 2.0
# here we use math round on the result of division and not just
# cast it to integer because for some magnitude values that can't
# be represented as an IEEE 754 double precisely the result can
# look like 7.999999999999 which would become 7 instead of 8
# being naively casted to int so we would lose the last bin.
num_bins = int(round((max_mag - min_mag) / self.bin_width)) + 1
return min_mag, num_bins
[docs] def get_min_max_mag(self):
"""
Return the minum magnitude
"""
min_mag, num_bins = self._get_min_mag_and_num_bins()
return min_mag, min_mag + self.bin_width * (num_bins - 1)
[docs] def get_annual_occurrence_rates(self):
"""
Calculate and return the annual occurrence rates histogram.
The result histogram has only one bin if minimum and maximum magnitude
values appear equal after rounding.
:returns:
See :meth:
`openquake.hazardlib.mfd.base.BaseMFD.get_annual_occurrence_rates`.
"""
mag, num_bins = self._get_min_mag_and_num_bins()
rates = []
for i in range(num_bins):
rate = self._get_rate(mag)
rates.append((mag, rate))
mag += self.bin_width
return rates
def _get_total_moment_rate(self):
"""
Calculate total moment rate (total energy released per unit time) ::
TMR = ((10**ai) / bi) * (10 ** (bi*max_mag) - 10 ** (bi*min_mag))
where ``ai = a + log10(b) + 9.05`` and ``bi = 1.5 - b``.
In case of ``bi == 0`` the following formula is applied::
TMR = (10 ** ai) * (max_mag - min_mag)
:returns:
Float, calculated TMR value in ``N * m / year``
(Newton-meter per year).
"""
ai = 9.05 + self.a_val + math.log10(self.b_val)
bi = 1.5 - self.b_val
if bi == 0.0:
return (10 ** ai) * (self.max_mag - self.min_mag)
else:
return (((10 ** ai) / bi) *
(10 ** (bi * self.max_mag) - 10 ** (bi * self.min_mag)))
def _set_a(self, tmr):
"""
Recalculate an ``a`` value preserving a total moment rate ``tmr`` ::
a = (log10((tmr * bi) / (10 ** (bi*max_mag) - 10 ** (bi*min_mag)))
- 9.05 - log10(b))
where ``bi = 1.5 - b``. If ``bi == 0`` the following formula is used:
a = log10(tmr / (max_mag - min_mag)) - 9.05 - log10(b)
"""
bi = 1.5 - self.b_val
if bi == 0.0:
self.a_val = (math.log10(tmr / (self.max_mag - self.min_mag))
- 9.05
- math.log10(self.b_val))
else:
self.a_val = (math.log10(tmr * bi / (10 ** (bi * self.max_mag)
- 10 ** (bi * self.min_mag)))
- 9.05
- math.log10(self.b_val))
[docs] def modify_increment_max_mag(self, value):
"""
Apply relative maximum magnitude modification.
:param value:
A float value to add to ``max_mag``.
The Gutenberg-Richter ``a`` value is :meth:`recalculated <_set_a>`
with respect to old :meth:`total moment rate <_get_total_moment_rate>`.
"""
tmr = self._get_total_moment_rate()
self.max_mag += value
# need to check constraints here because _set_a() would die
# if new max_mag <= min_mag.
self.check_constraints()
self._set_a(tmr)
[docs] def modify_set_max_mag(self, value):
"""
Apply absolute maximum magnitude modification.
:param value:
A float value to assign to ``max_mag``.
No specific recalculation of other Gutenberg-Richter parameters
is done after assigning a new value to ``max_mag``.
"""
self.max_mag = value
[docs] def modify_increment_b(self, value):
"""
Apply relative ``b``-value modification.
:param value:
A float value to add to ``b_val``.
After changing ``b_val`` the ``a_val`` is recalculated the same
way as for :meth:`modify_increment_max_mag` (with
respect to TMR).
"""
tmr = self._get_total_moment_rate()
self.b_val += value
self.check_constraints()
self._set_a(tmr)
[docs] def modify_set_ab(self, a_val, b_val):
"""
Apply absolute ``a`` and ``b`` values modification.
:param a_val:
A float value to use as a new ``a_val``.
:param b_val:
A float value to use as a new ``b_val``.
No recalculation of other Gutenberg-Richter parameters is done.
"""
self.b_val = b_val
self.a_val = a_val
[docs] @classmethod
def from_moment(cls, min_mag, max_mag, bin_width, b_val, moment_rate):
"""
:param min_mag:
The lowest possible magnitude for this MFD. The first bin in the
:meth:`result histogram <get_annual_occurrence_rates>` will be
aligned to make its left border match this value.
:param max_mag:
The highest possible magnitude. The same as for ``min_mag``: the
last bin in the histogram will correspond to the magnitude value
equal to ``max_mag - bin_width / 2``.
:param bin_width:
A positive float value -- the width of a single histogram bin.
:param b_val:
The slope of the GR relationship
:param moment_rate:
The value of scalar seismic moment per year released by this MFD.
Unit of measure is N ・m
"""
c_val = 1.5
d_val = 9.1
tmp = 0
mou = 10**(c_val * max_mag + d_val)
beta = b_val * np.log(10.0)
term2 = np.exp(-beta*(max_mag - tmp))
rate = (moment_rate * (c_val - b_val) * (1 - term2) /
(b_val * mou * term2))
a_val = np.log10(rate)
self = cls(min_mag, max_mag, bin_width, a_val, b_val)
return self
[docs] @classmethod
def from_slip_rate(cls, min_mag, max_mag, bin_width, b_val,
slip_rate, rigidity, area):
"""
Calls .from_moment with moment = slip_rate * rigidity * area
:param min_mag:
The lowest possible magnitude for this MFD. The first bin in the
:meth:`result histogram <get_annual_occurrence_rates>` will be
aligned to make its left border match this value.
:param max_mag:
The highest possible magnitude. The same as for ``min_mag``: the
last bin in the histogram will correspond to the magnitude value
equal to ``max_mag - bin_width / 2``.
:param bin_width:
A positive float value -- the width of a single histogram bin.
:param b_val:
The slope of the GR relationship
:param slip_rate:
A float defining the slip rate [mm/yr]
:param rigidity:
A float defining the rigidity [GPa]
:param area:
A float defining the area of the fault surface [km^2]
"""
mm = 1E-3 # conversion millimiters -> meters
moment_rate = (slip_rate * mm) * (rigidity * 1e9) * (area * 1e6)
self = cls.from_moment(min_mag, max_mag, bin_width, b_val, moment_rate)
self.slip_rate = slip_rate
self.rigidity = rigidity
return self