Source code for openquake.hmtk.strain.regionalisation.kreemer_regionalisation

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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