openquake.hazardlib.calc package

Hazardlib calculators

Disaggregation (disagg)

openquake.hazardlib.calc.disagg contains disaggregation() as well as several aggregation functions for extracting a specific PMF from the result of disaggregation().

openquake.hazardlib.calc.disagg.build_disagg_matrix(bdata, bins, mon=<class 'openquake.baselib.performance.Monitor'>)

Parameters:

• bdata – a dictionary of probabilities of no exceedence
• bins – bin edges
• mon – a Monitor instance

Returns:

a dictionary key -> matrix|pmf for each key in bdata

openquake.hazardlib.calc.disagg.collect_bin_data(rupdata, sitecol, cmaker, iml3, truncation_level, n_epsilons, monitor=<Monitor [jenkins]>)

Parameters:

• rupdata – array of ruptures
• sitecol – a SiteCollection instance with a single site
• cmaker – a ContextMaker instance
• iml3 – an ArrayWrapper of intensities of shape (R, M, P)
• truncation_level – the truncation level
• n_epsilons – the number of epsilons
• monitor – a Monitor instance

Returns:

a dictionary (poe, imt, rlzi) -> probabilities of shape (N, E)

openquake.hazardlib.calc.disagg.disaggregate(cmaker, sitecol, rupdata, iml2, truncnorm, epsilons, monitor=<Monitor [jenkins]>)

Disaggregate (separate) PoE in different contributions.

Parameters:

• cmaker – a ContextMaker instance
• sitecol – a SiteCollection with N=1 site
• ruptures – an iterator over ruptures with the same TRT
• iml2 – a 2D array of IMLs of shape (M, P)
• truncnorm – an instance of scipy.stats.truncnorm
• epsilons – the epsilon bins
• monitor – a Monitor instance

Returns:

an AccumDict with keys (poe, imt, rlzi) and mags, dists, lons, lats

openquake.hazardlib.calc.disagg.disaggregate_pne(gsim, rupture, sctx, dctx, imt, iml, truncnorm, epsilons, eps_bands)

Disaggregate (separate) PoE of iml in different contributions each coming from epsilons distribution bins.

Other parameters are the same as for gsim.get_poes, with differences that truncation_level is required to be positive.

Returns:Contribution to probability of exceedance of iml coming from different sigma bands in the form of a 2D numpy array of probabilities with shape (n_sites, n_epsilons)

openquake.hazardlib.calc.disagg.disaggregation(sources, site, imt, iml, gsim_by_trt, truncation_level, n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width, source_filter=<openquake.hazardlib.calc.filters.SourceFilter object>, filter_distance='rjb')

Compute “Disaggregation” matrix representing conditional probability of an intensity mesaure type imt exceeding, at least once, an intensity measure level iml at a geographical location site, given rupture scenarios classified in terms of:

• rupture magnitude
• Joyner-Boore distance from rupture surface to site
• longitude and latitude of the surface projection of a rupture’s point closest to site
• epsilon: number of standard deviations by which an intensity measure level deviates from the median value predicted by a GSIM, given the rupture parameters
• rupture tectonic region type

In other words, the disaggregation matrix allows to compute the probability of each scenario with the specified properties (e.g., magnitude, or the magnitude and distance) to cause one or more exceedences of a given hazard level.

For more detailed information about the disaggregation, see for instance “Disaggregation of Seismic Hazard”, Paolo Bazzurro, C. Allin Cornell, Bulletin of the Seismological Society of America, Vol. 89, pp. 501-520, April 1999.

Parameters:

• sources – Seismic source model, as for PSHA calculator it should be an iterator of seismic sources.
• site – Site of interest to calculate disaggregation matrix for.
• imt – Instance of intensity measure type class.
• iml – Intensity measure level. A float value in units of imt.
• gsim_by_trt – Tectonic region type to GSIM objects mapping.
• truncation_level – Float, number of standard deviations for truncation of the intensity distribution.
• n_epsilons – Integer number of epsilon histogram bins in the result matrix.
• mag_bin_width – Magnitude discretization step, width of one magnitude histogram bin.
• dist_bin_width – Distance histogram discretization step, in km.
• coord_bin_width – Longitude and latitude histograms discretization step, in decimal degrees.
• source_filter – Optional source-site filter function. See openquake.hazardlib.calc.filters.

Returns:

A tuple of two items. First is itself a tuple of bin edges information for (in specified order) magnitude, distance, longitude, latitude, epsilon and tectonic region types.

Second item is 6d-array representing the full disaggregation matrix. Dimensions are in the same order as bin edges in the first item of the result tuple. The matrix can be used directly by pmf-extractor functions.

openquake.hazardlib.calc.disagg.dist_pmf(matrix)

Fold full disaggregation matrix to distance PMF.

Returns:1d array, a histogram representing distance PMF.

openquake.hazardlib.calc.disagg.get_bins(bin_edges, sid)

Returns:mags, dists, lons, lats, eps for the given sid

openquake.hazardlib.calc.disagg.lon_lat_bins(bb, coord_bin_width)

Define bin edges for disaggregation histograms.

Given bins data as provided by collect_bin_data(), this function finds edges of histograms, taking into account maximum and minimum values of magnitude, distance and coordinates as well as requested sizes/numbers of bins.

openquake.hazardlib.calc.disagg.lon_lat_pmf(matrix)

Fold full disaggregation matrix to longitude / latitude PMF.

Returns:2d array. First dimension represents longitude histogram bins, second one – latitude histogram bins.

openquake.hazardlib.calc.disagg.lon_lat_trt_pmf(matrices)

Fold full disaggregation matrices to lon / lat / TRT PMF.

Parameters:matrices – a matrix with T submatrices Returns:3d array. First dimension represents longitude histogram bins, second one latitude histogram bins, third one trt histogram bins.

openquake.hazardlib.calc.disagg.mag_dist_eps_pmf(matrix)

Fold full disaggregation matrix to magnitude / distance / epsilon PMF.

Returns:3d array. First dimension represents magnitude histogram bins, second one – distance histogram bins, third one – epsilon histogram bins.

openquake.hazardlib.calc.disagg.mag_dist_pmf(matrix)

Fold full disaggregation matrix to magnitude / distance PMF.

Returns:2d array. First dimension represents magnitude histogram bins, second one – distance histogram bins.

openquake.hazardlib.calc.disagg.mag_lon_lat_pmf(matrix)

Fold full disaggregation matrix to magnitude / longitude / latitude PMF.

Returns:3d array. First dimension represents magnitude histogram bins, second one – longitude histogram bins, third one – latitude histogram bins.

openquake.hazardlib.calc.disagg.mag_pmf(matrix)

Fold full disaggregation matrix to magnitude PMF.

Returns:1d array, a histogram representing magnitude PMF.

openquake.hazardlib.calc.disagg.trt_pmf(matrices)

Fold full disaggregation matrix to tectonic region type PMF.

Parameters:matrices – a matrix with T submatrices Returns:an array of T probabilities one per each tectonic region type

Filters (filters)

class openquake.hazardlib.calc.filters.IntegrationDistance(dic)

Bases: collections.abc.Mapping

Pickleable object wrapping a dictionary of integration distances per tectonic region type. The integration distances can be scalars or list of pairs (magnitude, distance). Here is an example using ‘default’ as tectonic region type, so that the same values will be used for all tectonic region types:

>>> maxdist = IntegrationDistance({'default': [
...          (3, 30), (4, 40), (5, 100), (6, 200), (7, 300), (8, 400)]})
>>> maxdist('Some TRT', mag=2.5)
30
>>> maxdist('Some TRT', mag=3)
30
>>> maxdist('Some TRT', mag=3.1)
40
>>> maxdist('Some TRT', mag=8)
400
>>> maxdist('Some TRT', mag=8.5)  # 2000 km are used above the maximum
2000

get_affected_box(src)

Get the enlarged bounding box of a source.

Parameters:src – a source object Returns:a bounding box (min_lon, min_lat, max_lon, max_lat)

get_bounding_box(lon, lat, trt=None, mag=None)

Build a bounding box around the given lon, lat by computing the maximum_distance at the given tectonic region type and magnitude.

Parameters:

• lon – longitude
• lat – latitude
• trt – tectonic region type, possibly None
• mag – magnitude, possibly None

Returns:

min_lon, min_lat, max_lon, max_lat

class openquake.hazardlib.calc.filters.Piecewise(x, y)

Bases: object

Given two arrays x and y of non-decreasing values, build a piecewise function associating to each x the corresponding y. If x is smaller then the minimum x, the minimum y is returned; if x is larger than the maximum x, the maximum y is returned.

class openquake.hazardlib.calc.filters.SourceFilter(sitecol, integration_distance, filename=None)

Bases: object

Filter objects have a .filter method yielding filtered sources, i.e. sources with an attribute .indices, containg the IDs of the sites within the given maximum distance. There is also a .new method that filters the sources in parallel and returns a dictionary src_group_id -> filtered sources. Filter the sources by using self.sitecol.within_bbox which is based on numpy.

close_sids(rec, trt, mag)

Parameters:

• rec – a record with fields minlon, minlat, maxlon, maxlat
• trt – tectonic region type string
• mag – magnitude

Returns:

the site indices within the bounding box enlarged by the integration distance for the given TRT and magnitude

filter(sources)

Parameters:sources – a sequence of sources Yields:sources with .indices

get_bounding_boxes(trt=None, mag=None)

Parameters:

• trt – a tectonic region type (used for the integration distance)
• mag – a magnitude (used for the integration distance)

Returns:

a list of bounding boxes, one per site

get_close_sites(source)

Returns the sites within the integration distance from the source, or None.

get_rectangle(src)

Parameters:src – a source object Returns:((min_lon, min_lat), width, height), useful for plotting

sitecol

Read the site collection from .filename and cache it

openquake.hazardlib.calc.filters.context(src)

Used to add the source_id to the error message. To be used as

with context(src):

operation_with(src)

Typically the operation is filtering a source, that can fail for tricky geometries.

openquake.hazardlib.calc.filters.getdefault(dic_with_default, key)

Parameters:

• dic_with_default – a dictionary with a ‘default’ key
• key – a key that may be present in the dictionary or not

Returns:

the value associated to the key, or to ‘default’

openquake.hazardlib.calc.filters.split_sources(srcs)

Parameters:srcs – sources Returns:a pair (split sources, split time) or just the split_sources

Ground Motion Fields (gmf)

Module gmf exports ground_motion_fields().

exception openquake.hazardlib.calc.gmf.CorrelationButNoInterIntraStdDevs(corr, gsim)

Bases: Exception

class openquake.hazardlib.calc.gmf.GmfComputer(rupture, sitecol, imts, cmaker, truncation_level=None, correlation_model=None)

Bases: object

Given an earthquake rupture, the ground motion field computer computes ground shaking over a set of sites, by randomly sampling a ground shaking intensity model.

Parameters:rupture – Rupture to calculate ground motion fields radiated from.

:param openquake.hazardlib.site.SiteCollection sitecol:

a complete SiteCollection

Parameters:

• imts – a sorted list of Intensity Measure Type strings
• cmaker – a openquake.hazardlib.gsim.base.ContextMaker instance
• truncation_level – Float, number of standard deviations for truncation of the intensity distribution, or None.
• correlation_model – Instance of correlation model object. See openquake.hazardlib.correlation. Can be None, in which case non-correlated ground motion fields are calculated. Correlation model is not used if truncation_level is zero.

compute(gsim, num_events, seed=None)

Parameters:

• gsim – a GSIM instance
• num_events – the number of seismic events
• seed – a random seed or None

Returns:

a 32 bit array of shape (num_imts, num_sites, num_events) and two arrays with shape (num_imts, num_events): sig for stddev_inter and eps for the random part

openquake.hazardlib.calc.gmf.ground_motion_fields(rupture, sites, imts, gsim, truncation_level, realizations, correlation_model=None, seed=None)

Given an earthquake rupture, the ground motion field calculator computes ground shaking over a set of sites, by randomly sampling a ground shaking intensity model. A ground motion field represents a possible ‘realization’ of the ground shaking due to an earthquake rupture.

Note

This calculator is using random numbers. In order to reproduce the same results numpy random numbers generator needs to be seeded, see http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html

Parameters:

• rupture (openquake.hazardlib.source.rupture.Rupture) – Rupture to calculate ground motion fields radiated from.
• sites (openquake.hazardlib.site.SiteCollection) – Sites of interest to calculate GMFs.
• imts – List of intensity measure type objects (see openquake.hazardlib.imt).
• gsim – Ground-shaking intensity model, instance of subclass of either GMPE or IPE.
• truncation_level – Float, number of standard deviations for truncation of the intensity distribution, or None.
• realizations – Integer number of GMF realizations to compute.
• correlation_model – Instance of correlation model object. See openquake.hazardlib.correlation. Can be None, in which case non-correlated ground motion fields are calculated. Correlation model is not used if truncation_level is zero.
• seed (int) – The seed used in the numpy random number generator

Returns:

Dictionary mapping intensity measure type objects (same as in parameter imts) to 2d numpy arrays of floats, representing different realizations of ground shaking intensity for all sites in the collection. First dimension represents sites and second one is for realizations.

openquake.hazardlib.calc.gmf.rvs(distribution, *size)

Hazard Curves (hazard_curve)

openquake.hazardlib.calc.hazard_curve implements calc_hazard_curves(). Here is an example of a classical PSHA parallel calculator computing the hazard curves per each realization in less than 20 lines of code:

import sys
import logging
from openquake.baselib import parallel
from openquake.hazardlib.calc.filters import SourceFilter
from openquake.hazardlib.calc.hazard_curve import calc_hazard_curves
from openquake.commonlib import readinput

def main(job_ini):
    logging.basicConfig(level=logging.INFO)
    oq = readinput.get_oqparam(job_ini)
    sitecol = readinput.get_site_collection(oq)
    src_filter = SourceFilter(sitecol, oq.maximum_distance)
    csm = readinput.get_composite_source_model(oq, srcfilter=src_filter)
    rlzs_assoc = csm.info.get_rlzs_assoc()
    for i, sm in enumerate(csm.source_models):
        for rlz in rlzs_assoc.rlzs_by_smodel[i]:
            gsim_by_trt = rlzs_assoc.gsim_by_trt[rlz.ordinal]
            hcurves = calc_hazard_curves(
                sm.src_groups, src_filter, oq.imtls,
                gsim_by_trt, oq.truncation_level,
                parallel.Starmap.apply)
        print('rlz=%s, hcurves=%s' % (rlz, hcurves))

if __name__ == '__main__':
    main(sys.argv[1])  # path to a job.ini file

NB: the implementation in the engine is smarter and more efficient. Here we start a parallel computation per each realization, the engine manages all the realizations at once.

openquake.hazardlib.calc.hazard_curve.calc_hazard_curves(groups, srcfilter, imtls, gsim_by_trt, truncation_level=None, apply=<function sequential_apply>, filter_distance='rjb', reqv=None)

Compute hazard curves on a list of sites, given a set of seismic source groups and a dictionary of ground shaking intensity models (one per tectonic region type).

Probability of ground motion exceedance is computed in different ways depending if the sources are independent or mutually exclusive.

Parameters:

• groups – A sequence of groups of seismic sources objects (instances of of BaseSeismicSource).
• srcfilter – A source filter over the site collection or the site collection itself
• imtls – Dictionary mapping intensity measure type strings to lists of intensity measure levels.
• gsim_by_trt – Dictionary mapping tectonic region types (members of openquake.hazardlib.const.TRT) to GMPE or IPE objects.
• truncation_level – Float, number of standard deviations for truncation of the intensity distribution.
• apply – apply function to use (default sequential_apply)
• filter_distance – The distance used to filter the ruptures (default rjb)
• reqv – If not None, an instance of RjbEquivalent

Returns:

An array of size N, where N is the number of sites, which elements are records with fields given by the intensity measure types; the size of each field is given by the number of levels in imtls.

openquake.hazardlib.calc.hazard_curve.classical(group, src_filter, gsims, param, monitor=<Monitor [jenkins]>)

Compute the hazard curves for a set of sources belonging to the same tectonic region type for all the GSIMs associated to that TRT. The arguments are the same as in calc_hazard_curves(), except for gsims, which is a list of GSIM instances.

Returns:a dictionary {grp_id: pmap} with attributes .grp_ids, .calc_times, .eff_ruptures

Stochastic Event Set (stochastic)

openquake.hazardlib.calc.stochastic contains stochastic_event_set().

openquake.hazardlib.calc.stochastic.get_rup_array(ebruptures, srcfilter=<openquake.hazardlib.calc.filters.SourceFilter object>)

Convert a list of EBRuptures into a numpy composite array, by filtering out the ruptures far away from every site

openquake.hazardlib.calc.stochastic.sample_cluster(sources, srcfilter, num_ses, param)

Yields ruptures generated by a cluster of sources.

Parameters:

• sources – A sequence of sources of the same group
• num_ses – Number of stochastic event sets
• param – a dictionary of additional parameters including ses_per_logic_tree_path

Yields:

dictionaries with keys rup_array, calc_times, eff_ruptures

openquake.hazardlib.calc.stochastic.sample_ruptures(sources, srcfilter, param, monitor=<Monitor [jenkins]>)

Parameters:

• sources – a sequence of sources of the same group
• srcfilter – SourceFilter instance used also for bounding box post filtering
• param – a dictionary of additional parameters including ses_per_logic_tree_path
• monitor – monitor instance

Yields:

dictionaries with keys rup_array, calc_times, eff_ruptures

openquake.hazardlib.calc.stochastic.stochastic_event_set(sources, source_site_filter=<openquake.hazardlib.calc.filters.SourceFilter object>)

Generates a ‘Stochastic Event Set’ (that is a collection of earthquake ruptures) representing a possible realization of the seismicity as described by a source model.

The calculator loops over sources. For each source, it loops over ruptures. For each rupture, the number of occurrence is randomly sampled by calling openquake.hazardlib.source.rupture.BaseProbabilisticRupture.sample_number_of_occurrences()

Note

This calculator is using random numbers. In order to reproduce the same results numpy random numbers generator needs to be seeded, see http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html

Parameters:

• sources – An iterator of seismic sources objects (instances of subclasses of BaseSeismicSource).
• source_site_filter – The source filter to use (default noop filter)

Returns:

Generator of Rupture objects that are contained in an event set. Some ruptures can be missing from it, others can appear one or more times in a row.