def test1(self):
        site1_pga_poe_expected = [0.0639157, 0.03320212, 0.02145989]
        site2_pga_poe_expected = [0.06406232, 0.02965879, 0.01864331]
        site1_pgd_poe_expected = [0.16146619, 0.1336553]
        site2_pgd_poe_expected = [0.15445961, 0.13437589]

        curves = hazard_curves_poissonian(self.sources, self.sites, self.imts,
                                          self.time_span, self.gsims,
                                          self.truncation_level)

        self.assertIsInstance(curves, dict)
        self.assertEqual(set(curves.keys()), set([imt.PGA(), imt.PGD()]))

        pga_curves = curves[imt.PGA()]
        self.assertIsInstance(pga_curves, numpy.ndarray)
        self.assertEqual(pga_curves.shape, (2, 3))  # two sites, three IMLs
        site1_pga_poe, site2_pga_poe = pga_curves
        self.assertTrue(numpy.allclose(site1_pga_poe, site1_pga_poe_expected),
                        str(site1_pga_poe))
        self.assertTrue(numpy.allclose(site2_pga_poe, site2_pga_poe_expected),
                        str(site2_pga_poe))

        pgd_curves = curves[imt.PGD()]
        self.assertIsInstance(pgd_curves, numpy.ndarray)
        self.assertEqual(pgd_curves.shape, (2, 2))  # two sites, two IMLs
        site1_pgd_poe, site2_pgd_poe = pgd_curves
        self.assertTrue(numpy.allclose(site1_pgd_poe, site1_pgd_poe_expected),
                        str(site1_pgd_poe))
        self.assertTrue(numpy.allclose(site2_pgd_poe, site2_pgd_poe_expected),
                        str(site2_pgd_poe))
Пример #2
0
    def test1(self):
        site1_pga_poe_expected = [0.0639157, 0.03320212, 0.02145989]
        site2_pga_poe_expected = [0.06406232, 0.02965879, 0.01864331]
        site1_pgd_poe_expected = [0.16146619, 0.1336553]
        site2_pgd_poe_expected = [0.15445961, 0.13437589]

        curves = hazard_curves_poissonian(self.sources, self.sites, self.imts,
                                          self.time_span, self.gsims,
                                          self.truncation_level)

        self.assertIsInstance(curves, dict)
        self.assertEqual(set(curves.keys()), set([imt.PGA(), imt.PGD()]))

        pga_curves = curves[imt.PGA()]
        self.assertIsInstance(pga_curves, numpy.ndarray)
        self.assertEqual(pga_curves.shape, (2, 3))  # two sites, three IMLs
        site1_pga_poe, site2_pga_poe = pga_curves
        self.assertTrue(numpy.allclose(site1_pga_poe, site1_pga_poe_expected),
                        str(site1_pga_poe))
        self.assertTrue(numpy.allclose(site2_pga_poe, site2_pga_poe_expected),
                        str(site2_pga_poe))

        pgd_curves = curves[imt.PGD()]
        self.assertIsInstance(pgd_curves, numpy.ndarray)
        self.assertEqual(pgd_curves.shape, (2, 2))  # two sites, two IMLs
        site1_pgd_poe, site2_pgd_poe = pgd_curves
        self.assertTrue(numpy.allclose(site1_pgd_poe, site1_pgd_poe_expected),
                        str(site1_pgd_poe))
        self.assertTrue(numpy.allclose(site2_pgd_poe, site2_pgd_poe_expected),
                        str(site2_pgd_poe))
    def test_source_errors(self):
        # exercise `hazard_curves_poissonian` in the case of an exception,
        # whereby we expect the source_id to be reported in the error message

        fail_source = self.FailSource(self.source2.source_id,
                                      self.source2.ruptures,
                                      self.source2.time_span)
        sources = iter([self.source1, fail_source])

        with self.assertRaises(RuntimeError) as ae:
            hazard_curves_poissonian(sources, self.sites, self.imts,
                                     self.time_span, self.gsims,
                                     self.truncation_level)
        expected_error = (
            'An error occurred with source id=2. Error: Something bad happened'
        )
        self.assertEqual(expected_error, ae.exception.message)
Пример #4
0
    def test_source_errors(self):
        # exercise `hazard_curves_poissonian` in the case of an exception,
        # whereby we expect the source_id to be reported in the error message

        fail_source = self.FailSource(self.source2.source_id,
                                      self.source2.ruptures,
                                      self.source2.time_span)
        sources = iter([self.source1, fail_source])

        with self.assertRaises(RuntimeError) as ae:
            hazard_curves_poissonian(sources, self.sites, self.imts,
                                     self.time_span, self.gsims,
                                     self.truncation_level)
        expected_error = (
            'An error occurred with source id=2. Error: Something bad happened'
        )
        self.assertEqual(expected_error, ae.exception.message)
    def test_point_sources(self):
        sources = [
            openquake.hazardlib.source.PointSource(
                source_id='point1', name='point1',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
                    min_mag=4, bin_width=1, occurrence_rates=[5]
                ),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0.0,
                                                           dip=90.0,
                                                           rake=0.0))
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship=
                openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 10)
            ),
            openquake.hazardlib.source.PointSource(
                source_id='point2', name='point2',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
                    min_mag=4, bin_width=2, occurrence_rates=[5, 6, 7]
                ),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0,
                                                           dip=90,
                                                           rake=0.0)),
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship=
                openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 11)
            ),
        ]
        sites = [openquake.hazardlib.site.Site(Point(11, 10), 1, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 16), 2, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.6), 3, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.7), 4, True, 2, 3)]
        sitecol = openquake.hazardlib.site.SiteCollection(sites)

        from openquake.hazardlib.gsim.sadigh_1997 import SadighEtAl1997
        gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: SadighEtAl1997()}
        truncation_level = 1
        time_span = 1.0
        imts = {openquake.hazardlib.imt.PGA(): [0.1, 0.5, 1.3]}

        from openquake.hazardlib.calc import filters
        source_site_filter = self.SitesCounterSourceFilter(
            filters.source_site_distance_filter(30)
        )
        rupture_site_filter = self.SitesCounterRuptureFilter(
            filters.rupture_site_distance_filter(30)
        )
        hazard_curves_poissonian(
            iter(sources), sitecol, imts, time_span, gsims, truncation_level,
            source_site_filter=source_site_filter,
            rupture_site_filter=rupture_site_filter
        )
        # there are two sources and four sites. The first source contains only
        # one rupture, the second source contains three ruptures.
        #
        # the first source has 'maximum projection radius' of 0.707 km
        # the second source has 'maximum projection radius' of 500.0 km
        #
        # the epicentral distances for source 1 are: [ 109.50558394,
        # 667.16955987,   66.71695599,   77.83644865]
        # the epicentral distances for source 2 are: [ 155.9412148 ,
        # 555.97463322,   44.47797066,   33.35847799]
        #
        # Considering that the source site filtering distance is set to 30 km,
        # for source 1, all sites have epicentral distance larger than
        # 0.707 + 30 km. This means that source 1 ('point 1') is not considered
        # in the calculation because too far.
        # for source 2, the 1st, 3rd and 4th sites have epicentral distances
        # smaller than 500.0 + 30 km. This means that source 2 ('point 2') is
        # considered in the calculation for site 1, 3, and 4.
        #
        # JB distances for rupture 1 in source 2 are: [ 155.43860273,
        #  555.26752644,   43.77086388,   32.65137121]
        # JB distances for rupture 2 in source 2 are: [ 150.98882575,
        #  548.90356541,   37.40690285,   26.28741018]
        # JB distances for rupture 3 in source 2 are: [ 109.50545819,
        # 55.97463322,    0.        ,    0.        ]
        # 
        # Considering that the rupture site filtering distance is set to 30 km,
        # rupture 1 (magnitude 4) is not considered because too far, rupture 2
        # (magnitude 6) affect only the 4th site, rupture 3 (magnitude 8)
        # affect the 3rd and 4th sites.
        self.assertEqual(source_site_filter.counts,
                         [('point2', [1, 3, 4])])
        self.assertEqual(rupture_site_filter.counts,
                         [(6, [4]), (8, [3, 4])])
Пример #6
0
    def test1(self):
        truncation_level = 3.4
        imts = {imt.PGA(): [1, 2, 3], imt.PGD(): [2, 4]}
        time_span = 49.2

        rup11 = self.FakeRupture(0.23, const.TRT.ACTIVE_SHALLOW_CRUST)
        rup12 = self.FakeRupture(0.15, const.TRT.ACTIVE_SHALLOW_CRUST)
        rup21 = self.FakeRupture(0.04, const.TRT.VOLCANIC)
        source1 = self.FakeSource([rup11, rup12], time_span=time_span)
        source2 = self.FakeSource([rup21], time_span=time_span)
        sources = iter([source1, source2])
        site1 = Site(Point(10, 20), 1, True, 2, 3)
        site2 = Site(Point(20, 30), 2, False, 4, 5)
        sites = SiteCollection([site1, site2])

        gsim1 = self.FakeGSIM(truncation_level, imts, poes={
            (site1.location.latitude, rup11, imt.PGA()): [0.1, 0.05, 0.03],
            (site2.location.latitude, rup11, imt.PGA()): [0.11, 0.051, 0.034],
            (site1.location.latitude, rup12, imt.PGA()): [0.12, 0.052, 0.035],
            (site2.location.latitude, rup12, imt.PGA()): [0.13, 0.053, 0.036],

            (site1.location.latitude, rup11, imt.PGD()): [0.4, 0.33],
            (site2.location.latitude, rup11, imt.PGD()): [0.39, 0.331],
            (site1.location.latitude, rup12, imt.PGD()): [0.38, 0.332],
            (site2.location.latitude, rup12, imt.PGD()): [0.37, 0.333],
        })
        gsim2 = self.FakeGSIM(truncation_level, imts, poes={
            (site1.location.latitude, rup21, imt.PGA()): [0.5, 0.3, 0.2],
            (site2.location.latitude, rup21, imt.PGA()): [0.4, 0.2, 0.1],

            (site1.location.latitude, rup21, imt.PGD()): [0.24, 0.08],
            (site2.location.latitude, rup21, imt.PGD()): [0.14, 0.09],
        })
        gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: gsim1,
                 const.TRT.VOLCANIC: gsim2}

        site1_pga_poe_expected = [0.0639157, 0.03320212, 0.02145989]
        site2_pga_poe_expected = [0.06406232, 0.02965879, 0.01864331]
        site1_pgd_poe_expected = [0.16146619, 0.1336553]
        site2_pgd_poe_expected = [0.15445961, 0.13437589]

        curves = hazard_curves_poissonian(sources, sites, imts, time_span,
                                          gsims, truncation_level)
        self.assertIsInstance(curves, dict)
        self.assertEqual(set(curves.keys()), set([imt.PGA(), imt.PGD()]))

        pga_curves = curves[imt.PGA()]
        self.assertIsInstance(pga_curves, numpy.ndarray)
        self.assertEqual(pga_curves.shape, (2, 3))  # two sites, three IMLs
        site1_pga_poe, site2_pga_poe = pga_curves
        self.assertTrue(numpy.allclose(site1_pga_poe, site1_pga_poe_expected),
                        str(site1_pga_poe))
        self.assertTrue(numpy.allclose(site2_pga_poe, site2_pga_poe_expected),
                        str(site2_pga_poe))

        pgd_curves = curves[imt.PGD()]
        self.assertIsInstance(pgd_curves, numpy.ndarray)
        self.assertEqual(pgd_curves.shape, (2, 2))  # two sites, two IMLs
        site1_pgd_poe, site2_pgd_poe = pgd_curves
        self.assertTrue(numpy.allclose(site1_pgd_poe, site1_pgd_poe_expected),
                        str(site1_pgd_poe))
        self.assertTrue(numpy.allclose(site2_pgd_poe, site2_pgd_poe_expected),
                        str(site2_pgd_poe))
Пример #7
0
    def test_point_sources(self):
        sources = [
            openquake.hazardlib.source.PointSource(source_id='point1', name='point1',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(min_mag=4, bin_width=1,
                                                   occurrence_rates=[5]),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0.0, dip=90.0, rake=0.0))
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship = openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 10)
            ),
            openquake.hazardlib.source.PointSource(source_id='point2', name='point2',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(min_mag=4, bin_width=2,
                                                   occurrence_rates=[5, 6, 7]),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0, dip=90, rake=0.0)),
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship = openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 11)
            ),
        ]
        sites = [openquake.hazardlib.site.Site(Point(11, 10), 1, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 16), 2, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.6), 3, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.7), 4, True, 2, 3)]
        sitecol = openquake.hazardlib.site.SiteCollection(sites)

        from openquake.hazardlib.gsim.sadigh_1997 import SadighEtAl1997
        gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: SadighEtAl1997()}
        truncation_level = 1
        time_span = 1.0
        imts = {openquake.hazardlib.imt.PGA(): [0.1, 0.5, 1.3]}

        from openquake.hazardlib.calc import filters
        source_site_filter = self.SitesCounterSourceFilter(
            filters.source_site_distance_filter(30)
        )
        rupture_site_filter = self.SitesCounterRuptureFilter(
            filters.rupture_site_distance_filter(30)
        )
        hazard_curves_poissonian(
            iter(sources), sitecol, imts, time_span, gsims, truncation_level,
            source_site_filter=source_site_filter,
            rupture_site_filter=rupture_site_filter
        )
        # there are two sources and four sites. first source should
        # be filtered completely since it is too far from all the sites.
        # the second one should take only three sites -- all except (10, 16).
        # it generates three ruptures with magnitudes 4, 6 and 8, from which
        # the first one doesn't affect any of sites and should be ignored,
        # second only affects site (10, 10.7) and the last one affects all
        # three.
        self.assertEqual(source_site_filter.counts,
                         [('point2', [1, 3, 4])])
        self.assertEqual(rupture_site_filter.counts,
                         [(6, [4]), (8, [1, 3, 4])])
Пример #8
0
    def test_point_sources(self):
        sources = [
            openquake.hazardlib.source.PointSource(
                source_id='point1', name='point1',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
                    min_mag=4, bin_width=1, occurrence_rates=[5]
                ),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0.0,
                                                           dip=90.0,
                                                           rake=0.0))
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship=
                openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 10)
            ),
            openquake.hazardlib.source.PointSource(
                source_id='point2', name='point2',
                tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
                mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
                    min_mag=4, bin_width=2, occurrence_rates=[5, 6, 7]
                ),
                nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
                    (1, openquake.hazardlib.geo.NodalPlane(strike=0,
                                                           dip=90,
                                                           rake=0.0)),
                ]),
                hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
                upper_seismogenic_depth=0.0,
                lower_seismogenic_depth=10.0,
                magnitude_scaling_relationship=
                openquake.hazardlib.scalerel.PeerMSR(),
                rupture_aspect_ratio=2,
                rupture_mesh_spacing=1.0,
                location=Point(10, 11)
            ),
        ]
        sites = [openquake.hazardlib.site.Site(Point(11, 10), 1, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 16), 2, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.6), 3, True, 2, 3),
                 openquake.hazardlib.site.Site(Point(10, 10.7), 4, True, 2, 3)]
        sitecol = openquake.hazardlib.site.SiteCollection(sites)

        from openquake.hazardlib.gsim.sadigh_1997 import SadighEtAl1997
        gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: SadighEtAl1997()}
        truncation_level = 1
        time_span = 1.0
        imts = {openquake.hazardlib.imt.PGA(): [0.1, 0.5, 1.3]}

        from openquake.hazardlib.calc import filters
        source_site_filter = self.SitesCounterSourceFilter(
            filters.source_site_distance_filter(30)
        )
        rupture_site_filter = self.SitesCounterRuptureFilter(
            filters.rupture_site_distance_filter(30)
        )
        hazard_curves_poissonian(
            iter(sources), sitecol, imts, time_span, gsims, truncation_level,
            source_site_filter=source_site_filter,
            rupture_site_filter=rupture_site_filter
        )
        # there are two sources and four sites. first source should
        # be filtered completely since it is too far from all the sites.
        # the second one should take only three sites -- all except (10, 16).
        # it generates three ruptures with magnitudes 4, 6 and 8, from which
        # the first one doesn't affect any of sites and should be ignored,
        # second only affects site (10, 10.7) and the last one affects all
        # three.
        self.assertEqual(source_site_filter.counts,
                         [('point2', [1, 3, 4])])
        self.assertEqual(rupture_site_filter.counts,
                         [(6, [4]), (8, [1, 3, 4])])