# Source code for openquake.hazardlib.gsim.faccioli_cauzzi_2006

```
# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2014-2018 GEM Foundation
#
# OpenQuake 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.
#
# OpenQuake 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 OpenQuake. If not, see <http://www.gnu.org/licenses/>.
"""
Module exports :
class:`FaccioliCauzzi2006`
"""
import numpy as np
from openquake.hazardlib.gsim.base import GMPE, CoeffsTable
from openquake.hazardlib import const
from openquake.hazardlib.imt import MMI
[docs]class FaccioliCauzzi2006(GMPE):
"""
Implements "Macroseismic Intensities for seismic scenarios estimated from
instrumentally based correlations" by E. Faccioli and C. Cauzzi
First European Conference on Earthquake Engineering and Seismology
Geneva, Switzerland, 3-8 September 2006
Paper Number: 569
Implemented by laurentiu.danciu@sed.ethz.ch
"""
DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.ACTIVE_SHALLOW_CRUST
DEFINED_FOR_INTENSITY_MEASURE_TYPES = {MMI}
DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.HORIZONTAL
DEFINED_FOR_STANDARD_DEVIATION_TYPES = {const.StdDev.TOTAL}
REQUIRES_SITES_PARAMETERS = set()
REQUIRES_RUPTURE_PARAMETERS = {'mag'}
REQUIRES_DISTANCES = {'repi'}
[docs] 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.
"""
# extract dictionaries of coefficients specific to required
# intensity measure type
C = self.COEFFS[imt]
mean = self._compute_mean(C, rup, dists)
stddevs = self._get_stddevs(
C, stddev_types, num_sites=dists.repi.shape)
return mean, stddevs
def _compute_mean(self, C, rup, dists):
"""
Compute mean value defined by equation 1/page 414
no amplification factor is applied to the equation
hence the S-factor = 0
"""
d = np.sqrt(dists.repi**2+C['h']**2)
term01 = C['c3'] * (np.log(d))
mean = C['c1'] + C['c2'] * rup.mag + term01
return mean
def _get_stddevs(self, C, stddev_types, num_sites):
"""
Return total standard deviation.
"""
stddevs = []
for stddev_type in stddev_types:
assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
stddevs.append((C['sigma']) + np.zeros(num_sites))
return stddevs
#: Coefficient table constructed from the electronic suplements of the
#: original paper - coeff in the same order as in Table 4/page 703
#: for Maw only (read last paragraph on page 701 -
#: expains what Maw should be used)
COEFFS = CoeffsTable(table="""\
IMT c1 c2 c3 h sigma
MMI 1.0157 1.2566 -0.6547 2 0.5344
""")
```