# Source code for openquake.hmtk.strain.geodetic_strain

```
# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# LICENSE
#
# Copyright (C) 2010-2023 GEM Foundation, G. Weatherill, M. Pagani,
# D. Monelli.
#
# The Hazard Modeller's Toolkit 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.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>
#
# DISCLAIMER
#
# The software Hazard Modeller's Toolkit (openquake.hmtk) provided herein
# is released as a prototype implementation on behalf of
# scientists and engineers working within the GEM Foundation (Global
# Earthquake Model).
#
# It is distributed for the purpose of open collaboration and in the
# hope that it will be useful to the scientific, engineering, disaster
# risk and software design communities.
#
# The software is NOT distributed as part of GEM's OpenQuake suite
# (https://www.globalquakemodel.org/tools-products) and must be considered as a
# separate entity. The software provided herein is designed and implemented
# by scientific staff. It is not developed to the design standards, nor
# subject to same level of critical review by professional software
# developers, as GEM's OpenQuake software suite.
#
# Feedback and contribution to the software is welcome, and can be
# directed to the hazard scientific staff of the GEM Model Facility
# (hazard@globalquakemodel.org).
#
# The Hazard Modeller's Toolkit (openquake.hmtk) is therefore distributed
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
#
# The GEM Foundation, and the authors of the software, assume no
# liability for use of the software.
"""
:class:`openquake.hmtk.strain.geodectic_strain.GeodeticStain` is a
core class for storage and implementation of a geodetic strain rate
model
"""
import numpy as np
from copy import deepcopy
DATA_VARIABLES = ["longitude", "latitude", "exx", "eyy", "exy"]
[docs]class GeodeticStrain(object):
"""
:class:`openquake.hmtk.strain.geodetic_strain.GeodeticStrain` describes
the geodetic strain model
:param dict data:
Strain data in the form of a dictionary where is vector of attributes
is stored under the correponding dictionary key (i.e.
- longitude - Longitude of point
- latitude - Latitiude of point
- exx - xx-component of strain tensor
- eyy - yy-component of strain tensor
- exy - xy-component of strain tensor
:param numpy.ndarray seismicity_rate:
Seismicity rate at each point associated with the strain model
:param numpy.ndarray target_magnitudes:
Magnitudes for the corresponding activity rates
:param list data_variables:
List of strain data attributes in the current class
"""
def __init__(self):
"""Instantiates"""
self.data = None
self.regions = None
self.seismicity_rate = None
self.regionalisation = None
self.target_magnitudes = None
self.data_variables = []
[docs] def get_secondary_strain_data(self, strain_data=None):
"""
Calculate the following and add to data dictionary:
1) 2nd invarient of strain
2) Dilatation rate
3) e1h and e2h
4) err
:param dict strain_data:
Strain data dictionary (as described) - will overwrite current
data if input
"""
if strain_data:
self.data = strain_data
if not isinstance(self.data, dict):
raise ValueError("Strain data not input or incorrectly formatted")
# Check to ensure essential attributes are in data dictionary
for essential_key in DATA_VARIABLES:
if essential_key not in self.data:
print(self.data)
raise ValueError(
"Essential strain information %s missing!" % essential_key
)
self.data_variables = deepcopy(DATA_VARIABLES)
# Second Invarient
self.data["2nd_inv"] = np.sqrt(
(self.data["exx"] ** 2.0)
+ (self.data["eyy"] ** 2.0)
+ 2.0 * (self.data["exy"] ** 2.0)
)
# Dilatation
self.data["dilatation"] = self.data["exx"] + self.data["eyy"]
# err
self.data["err"] = -1.0 * self.data["dilatation"]
center_normal_rate = (self.data["exx"] + self.data["eyy"]) / 2.0
radius_rate = np.sqrt(
(self.data["exx"] - center_normal_rate) ** 2.0
+ (self.data["exy"] ** 2.0)
)
# e1h and e2h
self.data["e1h"] = center_normal_rate - radius_rate
self.data["e2h"] = center_normal_rate + radius_rate
self.data["area"] = np.zeros(self.get_number_observations())
self.data_variables.extend(
["2nd_inv", "dilatation", "err", "e1h", "e2h"]
)
[docs] def get_number_observations(self):
"""
Returns the number of observations in the data file
"""
if isinstance(self.data, dict) and ("exx" in self.data.keys()):
return len(self.data["exx"])
else:
return 0
```