# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2010-2021 GEM Foundation, G. Weatherill, M. Pagani,
# D. Monelli.
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# The Hazard Modeller's Toolkit is free software: you can redistribute
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# Earthquake Model).
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'''
Modules: openquake.hmtk.strain.regionalisation.kreemer_regionalisation implements the
class KreemerRegionalisation, which assigns a strain model to a tectonic
region according to the classification of Kreemer, Holt and Haines (2003)
'''
import os
import numpy as np
from linecache import getlines
KREEMER_GLOBAL_0506 = os.path.join(os.path.dirname(__file__),
'kreemer_polygons_area.txt')
def _build_kreemer_cell(data, loc):
'''
Constructs the "Kreemer Cell" from the input file. The Kreemer cell is
simply a set of five lines describing the four nodes of the square (closed)
:param list data:
Strain data as list of text lines (input from linecache.getlines)
:param int loc:
Pointer to location in data
:returns:
temp_poly - 5 by 2 numpy array of cell longitudes and latitudes
'''
temp_poly = np.empty([5, 2], dtype=float)
for ival in range(1, 6):
value = data[loc + ival].rstrip('\n')
value = value.lstrip(' ')
value = np.array((value.split(' ', 1))).astype(float)
temp_poly[ival - 1, :] = value.flatten()
return temp_poly
[docs]class KreemerRegionalisation(object):
'''
Class for implmenting a regionalisation using the file type defined by
Kreemer et al. (2003)
:param str filename:
Name of file
:param strain:
Strain model as instance of openquake.hmtk.strain.geodetic_strain.GeodeticStrain
'''
def __init__(self, filename=KREEMER_GLOBAL_0506):
'''
'''
self.filename = filename
self.strain = None
[docs] def get_regionalisation(self, strain_model):
'''
Gets the tectonic region type for every element inside the strain model
:paramm strain_model:
Input strain model as instance of
openquake.hmtk.strain.geodetic_strain.GeodeticStrain
:returns:
Strain model with complete regionalisation
'''
self.strain = strain_model
self.strain.data['region'] = np.array(
['IPL'
for _ in range(self.strain.get_number_observations())],
dtype='|S13')
self.strain.data['area'] = np.array(
[np.nan
for _ in range(self.strain.get_number_observations())])
regional_model = self.define_kreemer_regionalisation()
for polygon in regional_model:
self._point_in_tectonic_region(polygon)
return self.strain
def _point_in_tectonic_region(self, polygon):
'''
Returns the region type and area according to the tectonic
region
:param polygon: Dictionary containing the following attributes -
'long_lims' - Longitude limits (West, East)
'lat_lims' - Latitude limits (South, North)
'region_type' - Tectonic region type (str)
'area' - Area of cell in m ^ 2
'''
marker = np.zeros(self.strain.get_number_observations(), dtype=bool)
idlong = np.logical_and(
self.strain.data['longitude'] >= polygon['long_lims'][0],
self.strain.data['longitude'] < polygon['long_lims'][1])
id0 = np.where(np.logical_and(idlong, np.logical_and(
self.strain.data['latitude'] >= polygon['lat_lims'][0],
self.strain.data['latitude'] < polygon['lat_lims'][1])))[0]
if len(id0) > 0:
marker[id0] = True
for iloc in id0:
self.strain.data['region'][iloc] = \
polygon['region_type']
self.strain.data['area'][iloc] = polygon['area']
marker = np.logical_not(marker)
return marker
[docs] def define_kreemer_regionalisation(self, north=90., south=-90., east=180.,
west=-180.):
'''
Applies the regionalisation defined according to the regionalisation
typology of Corne Kreemer
'''
'''Applies the regionalisation of Kreemer (2003)
:param input_file:
Filename (str) of input file contraining Kreemer regionalisation
:param north:
Northern limit (decimal degrees)for consideration (float)
:param south:
Southern limit (decimal degrees)for consideration (float)
:param east:
Eastern limit (decimal degrees)for consideration (float)
:param west:
Western limit (decimal degrees)for consideration (float)
:returns: List of polygons corresonding to the Kreemer cells.
'''
input_data = getlines(self.filename)
kreemer_polygons = []
for line_loc, line in enumerate(input_data):
if '>' in line[0]:
polygon_dict = {}
# Get region type (char) and area (m ^ 2) from header
primary_data = line[2:].rstrip('\n')
primary_data = primary_data.split(' ', 1)
polygon_dict['region_type'] = primary_data[0].strip(' ')
polygon_dict['area'] = float(primary_data[1].strip(' '))
polygon_dict['cell'] = _build_kreemer_cell(input_data,
line_loc)
polygon_dict['long_lims'] = np.array([
np.min(polygon_dict['cell'][:, 0]),
np.max(polygon_dict['cell'][:, 0])])
polygon_dict['lat_lims'] = np.array([
np.min(polygon_dict['cell'][:, 1]),
np.max(polygon_dict['cell'][:, 1])])
polygon_dict['cell'] = None
if polygon_dict['long_lims'][0] >= 180.0:
polygon_dict['long_lims'] = \
polygon_dict['long_lims'] - 360.0
valid_check = [
polygon_dict['long_lims'][0] >= west,
polygon_dict['long_lims'][1] <= east,
polygon_dict['lat_lims'][0] >= south,
polygon_dict['lat_lims'][1] <= north]
if all(valid_check):
kreemer_polygons.append(polygon_dict)
return kreemer_polygons