コード例 #1
0
ファイル: origin_test.py プロジェクト: usgs/shakemap
def test_origin():
    fault_text = """30.979788       103.454422      1
31.691615       104.419160      1
31.723569       104.374760      1
32.532213       105.220821      1
32.641450       105.135050      20
31.846790       104.246202      20
31.942158       104.205286      20
31.290105       103.284388      20
30.979788       103.454422      1"""
    event_text = """<?xml version="1.0" encoding="US-ASCII" standalone="yes"?>
<earthquake id="2008ryan" lat="30.9858" lon="103.3639" mag="7.9" year="2008" month="05" day="12" hour="06" minute="28" second="01" timezone="GMT" depth="19.0" locstring="EASTERN SICHUAN, CHINA" created="1211173621" otime="1210573681" type="" />
    """
    source_text = "mech=RS"
    ffile = io.StringIO(fault_text)
    efile = io.StringIO(event_text)
    sfile = io.StringIO(source_text)
    origin = Origin.fromFile(efile, sourcefile=sfile)

    testdict = {'mag': 7.9,
                'id': '2008ryan',
                'locstring': 'EASTERN SICHUAN, CHINA',
                'mech': 'RS',
                'lon': 103.3639,
                'lat': 30.9858,
                'depth': 19.0}
    for key in testdict.keys():
        value = eval('origin.%s' % key)
        if type(value) is str:
            assert testdict[key] == value
        if type(value) is float:
            np.testing.assert_almost_equal(testdict[key], value)
コード例 #2
0
ファイル: virtualipe_test.py プロジェクト: usgs/shakemap
def test_virtualipe():

    #
    # Set up the GMPE, IPE, and GMICE
    #
    gmpe_cy14 = ChiouYoungs2014()
    gmpe = MultiGMPE.from_list([gmpe_cy14], [1.0])
    gmice = WGRW12()
    ipe = VirtualIPE.fromFuncs(gmpe, gmice)

    #
    # Use the Calexico event info
    #
    homedir = os.path.dirname(os.path.abspath(__file__))
    datadir = os.path.abspath(os.path.join(homedir, '..', 'data',
            'eventdata', 'Calexico', 'input'))

    #
    # Read the event, origin, and rupture files and produce Rupture and Origin
    # objects
    #
    inputfile = os.path.join(datadir, 'stationlist_dat.xml')
    dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
    eventfile = os.path.join(datadir, 'event.xml')
    rupturefile = os.path.join(datadir, 'wei_fault.txt')

    origin_obj = Origin.fromFile(eventfile)
    rupture_obj = read_rupture_file(origin_obj, rupturefile)
    rx = rupture_obj.getRuptureContext([gmpe])
    rx.rake = 45.

    smdx = 0.0083333333
    smdy = 0.0083333333
    lonspan = 6.0
    latspan = 4.0
    vs30filename = os.path.join(datadir, '..', 'vs30', 'vs30.grd')

    sites_obj_grid = Sites.fromCenter(
            rx.hypo_lon, rx.hypo_lat, lonspan, latspan,
            smdx, smdy, defaultVs30=760.0, vs30File=vs30filename,
            vs30measured_grid=None, padding=False, resample=False
        )

    npts = 200
    lats = np.empty(npts)
    lons = np.empty(npts)
    depths = np.zeros(npts)
    for i in range(npts):
        lats[i] = rx.hypo_lat
        lons[i] = rx.hypo_lon + i * 0.01
    lldict = {'lats': lats, 'lons': lons}

    sx = sites_obj_grid.getSitesContext(lldict=lldict, rock_vs30=760.0)

    dobj = Distance(gmpe, lons, lats, depths, rupture_obj)
    dx = dobj.getDistanceContext()

    sd_types = [oqconst.StdDev.TOTAL]
    mmi_const_vs30, mmi_sd_const_vs30 = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)

# These prints are just so a human can examine the outputs
#    print(mmi_const_vs30)
#    print(mmi_sd_const_vs30)

    sx = sites_obj_grid.getSitesContext(lldict=lldict)
    mmi_variable_vs30, mmi_sd_variable_vs30 = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)

#    print(mmi_variable_vs30)
#    print(mmi_sd_variable_vs30)

    sd_types = [oqconst.StdDev.TOTAL, oqconst.StdDev.INTRA_EVENT, 
                oqconst.StdDev.INTER_EVENT]
    mmi_variable_vs30_intra, mmi_sd_variable_vs30_intra = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)

#    print(mmi_variable_vs30_intra)
#    print(mmi_sd_variable_vs30_intra)
#    assert(0)      # Assert causes test to fail and prints to be displayed

    #
    # Try with PGA
    #
    gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(PGV)
    gmpe.ALL_GMPES_HAVE_PGV = False
    ipe = VirtualIPE.fromFuncs(gmpe, gmice)
    mmi_pga, mmi_sd_pga = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
    #
    # Try with SA(1.0)
    #
    gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(PGA)
    ipe = VirtualIPE.fromFuncs(gmpe, gmice)
    mmi_psa, mmi_sd_psa = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)

    #
    # This should raise an exception because the IMT isn't MMI
    #
    with pytest.raises(ValueError) as e:
        mmi_psa, mmi_sd_psa = \
                ipe.get_mean_and_stddevs(sx, rx, dx, PGA(), sd_types)
    #
    # This should raise an exception because no valid IMTs are available
    #
    gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(SA)
    with pytest.raises(ShakeMapException) as e:
        ipe = VirtualIPE.fromFuncs(gmpe, gmice)

    #
    # Now do a GMPE that uses Rjb instead of Rrup
    #
    gmpe_ba14 = BooreEtAl2014()
    gmpe = MultiGMPE.from_list([gmpe_ba14], [1.0])
    ipe = VirtualIPE.fromFuncs(gmpe, gmice)
    rx = rupture_obj.getRuptureContext([gmpe])
    rx.rake = 45.
    dobj = Distance(gmpe, lons, lats, depths, rupture_obj)
    dx = dobj.getDistanceContext()

    mmi_rjb, mmi_sd_rjb = \
            ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
    
    #
    # Test the results against a known standard
    #
    savefile = os.path.abspath(os.path.join(homedir, '..', 'data',
            'eventdata', 'Calexico', 'virtualipe_test', 'savefile.npz'))

    #
    # If things change, set remake_save to True, and it will rebuild the
    # saved data file against which the comparisons are done
    # Remember to set this back to False once you've remade the test datafile
    #
    remake_save = False
    if remake_save:
        np.savez_compressed(savefile,
                mmi_const_vs30 = mmi_const_vs30,
                mmi_sd_const_vs30 = mmi_sd_const_vs30[0],
                mmi_variable_vs30 = mmi_variable_vs30,
                mmi_sd_variable_vs30 = mmi_sd_variable_vs30[0],
                mmi_variable_vs30_intra = mmi_variable_vs30_intra,
                mmi_sd_variable_vs30_total = mmi_sd_variable_vs30_intra[0],
                mmi_sd_variable_vs30_intra = mmi_sd_variable_vs30_intra[1],
                mmi_sd_variable_vs30_inter = mmi_sd_variable_vs30_intra[2],
                mmi_pga = mmi_pga,
                mmi_sd_pga = mmi_sd_pga[0],
                mmi_psa = mmi_psa,
                mmi_sd_psa = mmi_sd_psa[0],
                mmi_rjb = mmi_rjb,
                mmi_sd_rjb = mmi_sd_rjb[0])

    td = np.load(savefile)

    assert(np.allclose(td['mmi_const_vs30'], mmi_const_vs30))
    assert(np.allclose(td['mmi_sd_const_vs30'], mmi_sd_const_vs30[0]))
    assert(np.allclose(td['mmi_variable_vs30'], mmi_variable_vs30))
    assert(np.allclose(td['mmi_sd_variable_vs30'], mmi_sd_variable_vs30[0]))
    assert(np.allclose(td['mmi_variable_vs30_intra'], mmi_variable_vs30_intra))
    assert(np.allclose(td['mmi_sd_variable_vs30_total'], 
        mmi_sd_variable_vs30_intra[0]))
    assert(np.allclose(td['mmi_sd_variable_vs30_intra'], 
        mmi_sd_variable_vs30_intra[1]))
    assert(np.allclose(td['mmi_sd_variable_vs30_inter'], 
        mmi_sd_variable_vs30_intra[2]))
    assert(np.allclose(td['mmi_pga'], mmi_pga))
    assert(np.allclose(td['mmi_sd_pga'], mmi_sd_pga[0]))
    assert(np.allclose(td['mmi_psa'], mmi_psa))
    assert(np.allclose(td['mmi_sd_psa'], mmi_sd_psa[0]))
    assert(np.allclose(td['mmi_rjb'], mmi_rjb))
    assert(np.allclose(td['mmi_sd_rjb'], mmi_sd_rjb[0]))

    # The total uncertainties should be greater than the intra-event
    assert(np.all(mmi_sd_variable_vs30[0] > mmi_sd_variable_vs30_intra[1]))

    # The combined intra and inter-event uncertainty should be equal
    # to the total
    tot = np.sqrt(mmi_sd_variable_vs30_intra[1]**2 + mmi_sd_variable_vs30_intra[2]**2)
    assert(np.allclose(tot, mmi_sd_variable_vs30_intra[0], rtol=1e-2))