Source code for openquake.hazardlib.site

# -*- coding: utf-8 -*-
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#
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"""
Module :mod:`openquake.hazardlib.site` defines :class:`Site`.
"""
import numpy
from shapely import geometry
from openquake.baselib.general import split_in_blocks, not_equal
from openquake.hazardlib.geo.utils import fix_lon, cross_idl
from openquake.hazardlib.geo.mesh import Mesh


[docs]class Site(object): """ Site object represents a geographical location defined by its position as well as its soil characteristics. :param location: Instance of :class:`~openquake.hazardlib.geo.point.Point` representing where the site is located. :param vs30: Average shear wave velocity in the top 30 m, in m/s. :param vs30measured: Boolean value, ``True`` if ``vs30`` was measured on that location and ``False`` if it was inferred. :param z1pt0: Vertical distance from earth surface to the layer where seismic waves start to propagate with a speed above 1.0 km/sec, in meters. :param z2pt5: Vertical distance from earth surface to the layer where seismic waves start to propagate with a speed above 2.5 km/sec, in km. :raises ValueError: If any of ``vs30``, ``z1pt0`` or ``z2pt5`` is zero or negative. .. note:: :class:`Sites <Site>` are pickleable """ def __init__(self, location, vs30=numpy.nan, vs30measured=False, z1pt0=numpy.nan, z2pt5=numpy.nan, **extras): if not numpy.isnan(vs30) and vs30 <= 0: raise ValueError('vs30 must be positive') if not numpy.isnan(z1pt0) and z1pt0 <= 0: raise ValueError('z1pt0 must be positive') if not numpy.isnan(z2pt5) and z2pt5 <= 0: raise ValueError('z2pt5 must be positive') self.location = location self.vs30 = vs30 self.vs30measured = vs30measured self.z1pt0 = z1pt0 self.z2pt5 = z2pt5 for param, val in extras.items(): assert param in site_param_dt, param setattr(self, param, val) def __str__(self): """ >>> import openquake.hazardlib >>> loc = openquake.hazardlib.geo.point.Point(1, 2, 3) >>> str(Site(loc, 760.0, True, 100.0, 5.0)) '<Location=<Latitude=2.000000, Longitude=1.000000, Depth=3.0000>, \ Vs30=760.0000, Vs30Measured=True, Depth1.0km=100.0000, Depth2.5km=5.0000>' """ return ( "<Location=%s, Vs30=%.4f, Vs30Measured=%r, Depth1.0km=%.4f, " "Depth2.5km=%.4f>") % ( self.location, self.vs30, self.vs30measured, self.z1pt0, self.z2pt5) def __hash__(self): return hash((self.location.x, self.location.y)) def __eq__(self, other): return (self.location.x, self.location.y) == ( other.location.x, other.location.y) def __repr__(self): """ >>> import openquake.hazardlib >>> loc = openquake.hazardlib.geo.point.Point(1, 2, 3) >>> site = Site(loc, 760.0, True, 100.0, 5.0) >>> str(site) == repr(site) True """ return self.__str__()
def _extract(array_or_float, indices): try: # if array return array_or_float[indices] except TypeError: # if float return array_or_float # dtype of each valid site parameter site_param_dt = { 'sids': numpy.uint32, 'lons': numpy.float64, 'lats': numpy.float64, 'depths': numpy.float64, 'lon': numpy.float64, 'lat': numpy.float64, 'depth': numpy.float64, 'vs30': numpy.float64, 'vs30measured': numpy.bool, 'z1pt0': numpy.float64, 'z2pt5': numpy.float64, 'backarc': numpy.bool, # parameters for geotechnic hazard 'liquefaction_susceptibility': numpy.int16, 'landsliding_susceptibility': numpy.int16, 'dw': numpy.float64, 'yield_acceleration': numpy.float64, 'slope': numpy.float64, 'cti': numpy.float64, 'dc': numpy.float64, 'dr': numpy.float64, 'dwb': numpy.float64, 'hwater': numpy.float64, 'precip': numpy.float64 }
[docs]class SiteCollection(object): __doc__ = """\ A collection of :class:`sites <Site>`. Instances of this class are intended to represent a large collection of sites in a most efficient way in terms of memory usage. The most common usage is to instantiate it as `SiteCollection.from_points`, by passing the set of required parameters, which must be a subset of the following parameters: %s .. note:: If a :class:`SiteCollection` is created from sites containing only lon and lat, iterating over the collection will yield :class:`Sites <Site>` with a reference depth of 0.0 (the sea level). Otherwise, it is possible to model the sites on a realistic topographic surface by specifying the `depth` of each site. :param sites: A list of instances of :class:`Site` class. """ % '\n'.join(' - %s: %s' % item for item in sorted(site_param_dt.items()) if item[0] not in ('lon', 'lat'))
[docs] @classmethod def from_shakemap(cls, shakemap_array): """ Build a site collection from a shakemap array """ self = object.__new__(cls) self.complete = self n = len(shakemap_array) dtype = numpy.dtype([(p, site_param_dt[p]) for p in 'sids lons lats depths vs30'.split()]) self.array = arr = numpy.zeros(n, dtype) arr['sids'] = numpy.arange(n, dtype=numpy.uint32) arr['lons'] = shakemap_array['lon'] arr['lats'] = shakemap_array['lat'] arr['depths'] = numpy.zeros(n) arr['vs30'] = shakemap_array['vs30'] arr.flags.writeable = False return self
[docs] @classmethod # this is the method used by the engine def from_points(cls, lons, lats, depths=None, sitemodel=None, req_site_params=()): """ Build the site collection from :param lons: a sequence of longitudes :param lats: a sequence of latitudes :param depths: a sequence of depths (or None) :param sitemodel: None or an object containing site parameters as attributes :param req_site_params: a sequence of required site parameters, possibly empty """ if depths is None: depths = numpy.zeros(len(lons)) assert len(lons) == len(lats) == len(depths), (len(lons), len(lats), len(depths)) self = object.__new__(cls) self.complete = self req = ['sids', 'lons', 'lats', 'depths'] + sorted( par for par in req_site_params if par not in ('lons', 'lats')) if 'vs30' in req and 'vs30measured' not in req: req.append('vs30measured') self.dtype = numpy.dtype([(p, site_param_dt[p]) for p in req]) self.array = arr = numpy.zeros(len(lons), self.dtype) arr['sids'] = numpy.arange(len(lons), dtype=numpy.uint32) arr['lons'] = fix_lon(numpy.array(lons)) arr['lats'] = numpy.array(lats) arr['depths'] = numpy.array(depths) if sitemodel is None: pass elif hasattr(sitemodel, 'reference_vs30_value'): # sitemodel is actually an OqParam instance self._set('vs30', sitemodel.reference_vs30_value) self._set('vs30measured', sitemodel.reference_vs30_type == 'measured') self._set('z1pt0', sitemodel.reference_depth_to_1pt0km_per_sec) self._set('z2pt5', sitemodel.reference_depth_to_2pt5km_per_sec) else: for name in sitemodel.dtype.names: if name not in ('lon', 'lat'): self._set(name, sitemodel[name]) return self
def _set(self, param, value): # param comes from the file site_model.xml file which usually contains # a lot of parameters; the parameters that are not required are ignored if param in self.array.dtype.names: # is required self.array[param] = value xyz = Mesh.xyz
[docs] def filtered(self, indices): """ :param indices: a subset of indices in the range [0 .. tot_sites - 1] :returns: a filtered SiteCollection instance if `indices` is a proper subset of the available indices, otherwise returns the full SiteCollection """ if len(indices) == len(self): return self new = object.__new__(self.__class__) indices = numpy.uint32(sorted(indices)) new.array = self.array[indices] new.complete = self.complete return new
[docs] def make_complete(self): """ Turns the site collection into a complete one, if needed """ # reset the site indices from 0 to N-1 and set self.complete to self self.array['sids'] = numpy.arange(len(self), dtype=numpy.uint32) self.complete = self
def __init__(self, sites): """ Build a complete SiteCollection from a list of Site objects """ dtlist = ([(p, site_param_dt[p]) for p in ('sids', 'lons', 'lats', 'depths')] + [(p, site_param_dt[p]) for p in sorted(vars(sites[0])) if p in site_param_dt]) self.array = arr = numpy.zeros(len(sites), dtlist) self.complete = self for i in range(len(arr)): arr['sids'][i] = i arr['lons'][i] = sites[i].location.longitude arr['lats'][i] = sites[i].location.latitude arr['depths'][i] = sites[i].location.depth arr['vs30'][i] = sites[i].vs30 arr['vs30measured'][i] = sites[i].vs30measured arr['z1pt0'][i] = sites[i].z1pt0 arr['z2pt5'][i] = sites[i].z2pt5 # protect arrays from being accidentally changed. it is useful # because we pass these arrays directly to a GMPE through # a SiteContext object and if a GMPE is implemented poorly it could # modify the site values, thereby corrupting site and all the # subsequent calculation. note that this doesn't protect arrays from # being changed by calling itemset() arr.flags.writeable = False def __eq__(self, other): return not self.__ne__(other) def __ne__(self, other): return not_equal(self.array, other.array) def __toh5__(self): return self.array, {} def __fromh5__(self, array, attrs): self.array = array self.complete = self @property def mesh(self): """Return a mesh with the given lons, lats, and depths""" return Mesh(self.lons, self.lats, self.depths)
[docs] def at_sea_level(self): """True if all depths are zero""" return (self.depths == 0).all()
# used in the engine when computing the hazard statistics
[docs] def split_in_tiles(self, hint): """ Split a SiteCollection into a set of tiles (SiteCollection instances). :param hint: hint for how many tiles to generate """ tiles = [] for seq in split_in_blocks(range(len(self)), hint or 1): sc = SiteCollection.__new__(SiteCollection) sc.array = self.array[numpy.array(seq, int)] tiles.append(sc) return tiles
def __iter__(self): """ Iterate through all :class:`sites <Site>` in the collection, yielding one at a time. """ params = self.array.dtype.names[4:] # except sids, lons, lats, depths for i, location in enumerate(self.mesh): kw = {p: self.array[i][p] for p in params} yield Site(location, **kw)
[docs] def filter(self, mask): """ Create a SiteCollection with only a subset of sites. :param mask: Numpy array of boolean values of the same length as the site collection. ``True`` values should indicate that site with that index should be included into the filtered collection. :returns: A new :class:`SiteCollection` instance, unless all the values in ``mask`` are ``True``, in which case this site collection is returned, or if all the values in ``mask`` are ``False``, in which case method returns ``None``. New collection has data of only those sites that were marked for inclusion in the mask. """ assert len(mask) == len(self), (len(mask), len(self)) if mask.all(): # all sites satisfy the filter, return # this collection unchanged return self if not mask.any(): # no sites pass the filter, return None return None # extract indices of Trues from the mask indices, = mask.nonzero() return self.filtered(indices)
[docs] def within(self, region): """ :param region: a shapely polygon :returns: a filtered SiteCollection of sites within the region """ mask = numpy.array([ geometry.Point(rec['lons'], rec['lats']).within(region) for rec in self.array]) return self.filter(mask)
[docs] def within_bbox(self, bbox): """ :param bbox: a quartet (min_lon, min_lat, max_lon, max_lat) :returns: site IDs within the bounding box """ min_lon, min_lat, max_lon, max_lat = bbox lons, lats = self.array['lons'], self.array['lats'] if cross_idl(lons.min(), lons.max()) or cross_idl(min_lon, max_lon): lons = lons % 360 min_lon, max_lon = min_lon % 360, max_lon % 360 mask = (min_lon < lons) * (lons < max_lon) * \ (min_lat < lats) * (lats < max_lat) return mask.nonzero()[0]
def __getstate__(self): return dict(array=self.array, complete=self.complete) def __getitem__(self, sid): """ Return a site record """ return self.array[sid] def __getattr__(self, name): if name not in site_param_dt: raise AttributeError(name) return self.array[name] def __len__(self): """ Return the number of sites in the collection. """ return len(self.array) def __repr__(self): total_sites = len(self.complete.array) return '<SiteCollection with %d/%d sites>' % ( len(self), total_sites)