def __computeDT(self, period): """ Computes DT -- the distance taper term. """ slat = self._lat slon = self._lon site_z = np.zeros_like(slat) ddict = get_distance('rrup', slat, slon, site_z, self._rup) Rrup = np.reshape(ddict['rrup'], (-1, )) nsite = len(Rrup) if self._simpleDT: # eqn 3.10 R1 = 35 R2 = 70 DT = np.ones(nsite) ix = tuple([(Rrup > R1) & (Rrup < R2)]) DT[ix] = 2 - Rrup[ix] / R1 DT[Rrup >= R2] = 0 else: # eqn 3.9 if period >= 1: R1 = 20 + 10 * np.log(period) R2 = 2 * (20 + 10 * np.log(period)) else: R1 = 20 R2 = 40 DT = np.ones(nsite) # As written in report: # DT[(Rrup > R1) & (Rrup < R2)] = \ # 2 - Rrup[(Rrup > R1) & (Rrup < R2)]/(20 + 10 * np.log(period)) # Modification: DT[(Rrup > R1) & (Rrup < R2)] = 2 - \ Rrup[(Rrup > R1) & (Rrup < R2)] / R1 # Note: it is not clear if the above modification is 'correct' # but it gives results that make more sense DT[Rrup >= R2] = 0 DT = np.reshape(DT, slat.shape) self._DT = DT
def __computeDT(self, period): """ Computes DT -- the distance taper term. """ slat = self._lat slon = self._lon site_z = np.zeros_like(slat) ddict = get_distance('rrup', slat, slon, site_z, self._rup) Rrup = np.reshape(ddict['rrup'], (-1, )) nsite = len(Rrup) if self._simpleDT: # eqn 3.10 R1 = 35 R2 = 70 DT = np.ones(nsite) ix = [(Rrup > R1) & (Rrup < R2)] DT[ix] = 2 - Rrup[ix] / R1 DT[Rrup >= R2] = 0 else: # eqn 3.9 if period >= 1: R1 = 20 + 10 * np.log(period) R2 = 2 * (20 + 10 * np.log(period)) else: R1 = 20 R2 = 40 DT = np.ones(nsite) # As written in report: # DT[(Rrup > R1) & (Rrup < R2)] = \ # 2 - Rrup[(Rrup > R1) & (Rrup < R2)]/(20 + 10 * np.log(period)) # Modification: DT[(Rrup > R1) & (Rrup < R2)] = 2 - \ Rrup[(Rrup > R1) & (Rrup < R2)] / R1 # Note: it is not clear if the above modification is 'correct' # but it gives results that make more sense DT[Rrup >= R2] = 0 DT = np.reshape(DT, slat.shape) self._DT = DT
def __init__(self, origin, rup, lat, lon, depth, T): """ Constructor for bayless2013. Args: origin: Shakemap Origin object. rup: Shakemap Rupture object. lat: Numpy array of latitudes. lon: Numpy array of longitudes. depth: Numpy array of depths (km); down is positive. T: Period; Currently, only acceptable values are 0.5, 0.75, 1, 1.5, 2, 3, 4, 5, 7.5, 10. """ self._origin = origin self._rup = rup self._rake = origin.rake self._M = origin.mag self._hyp = origin.getHypo() self._lon = lon self._lat = lat self._dep = depth self._T = T # Lists of widths and lengths for each quad in the rupture self._W = self._rup.getIndividualWidths() self._L = self._rup.getIndividualTopLengths() # Number of quads self._nq = len(self._W) # Currently assuming that the rake is the same on all subruptures . self.__getSlipCategory() # Rupture weights are supposed to be based on seismic moment. # Since moment is proportional to area, lets just use area # for now area = self._W * self._L self.weights = area / np.sum(area) # Put in pseudo-hypocenters for each quad self.__setPseudoHypocenters() self._fd = 0 for i in range(self._nq): self.i = i # Compute some genral stuff that is required for all mechanisms dtypes = ['rrup', 'rx', 'ry0'] dists = get_distance(dtypes, self._lat, self._lon, self._dep, self._rup) self.__Rrup = np.reshape(dists['rrup'], self._lat.shape) self.__Rx = np.reshape(dists['rx'], self._lat.shape) self.__Ry = np.reshape(dists['ry0'], self._lat.shape) # NOTE: use Rx and Ry to compute Az in 'computeAz'. It is probably # possible to make this a lot faster by avoiding the # calculation of these distances each time. # Az is the NGA definition of source-to-site azimuth for a finite # rupture. See Kaklamanos et al. (2011) Figure 2 for illustration. self.__computeAz() # uses Rx and Ry, which are for the i-th quad. # Magnitude taper (does not depend on mechanism) if self._M <= 5.0: self._T_Mw = 0.0 elif (self._M > 5.0) and (self._M < 6.5): self._T_Mw = 1.0 - (6.5 - self._M) / 1.5 else: self._T_Mw = 1.0 if self.SlipCategory == 'SS': self.__computeSS() self._fd = self._fd + self.weights[i] * self._fd_SS elif self.SlipCategory == 'DS': self.__computeDS() self._fd = self._fd + self.weights[i] * self._fd_DS else: # Compute both SS and DS self.__computeSS() self.__computeDS() # Normalize rake to reference angle sintheta = np.abs(np.sin(np.radians(self._rake))) costheta = np.abs(np.cos(np.radians(self._rake))) refrake = np.arctan2(sintheta, costheta) # Compute weights: DipWeight = refrake / (np.pi / 2.0) StrikeWeight = 1.0 - DipWeight fdcombined = StrikeWeight * self._fd_SS + DipWeight * \ self._fd_DS self._fd = self._fd + self.weights[i] * fdcombined
def test_multisegment_discordant(): # The one thing that isn't check above is discordancy for segments # with multiple quads. For this, we need a synthetic example. x0 = np.array([0, 1, -1, 10, 9, 7]) y0 = np.array([0, 10, 20, 40, 35, 30]) z0 = np.array([0, 0, 0, 0, 0, 0]) x1 = np.array([1, -1, 0, 9, 7, 6]) y1 = np.array([10, 20, 30, 35, 30, 25]) z1 = np.array([0, 0, 0, 0, 0, 0]) x2 = np.array([3, 1, 2, 7, 5, 4]) y2 = np.array([10, 20, 30, 35, 30, 25]) z2 = np.array([10, 10, 10, 10, 10, 10]) x3 = np.array([2, 3, 1, 8, 7, 5]) y3 = np.array([0, 10, 20, 40, 35, 30]) z3 = np.array([10, 10, 10, 10, 10, 10]) epilat = 32.15270 epilon = -115.30500 proj = geo.utils.get_orthographic_projection( epilon - 1, epilon + 1, epilat + 1, epilat - 1) lon0, lat0 = proj(x0, y0, reverse=True) lon1, lat1 = proj(x1, y1, reverse=True) lon2, lat2 = proj(x2, y2, reverse=True) lon3, lat3 = proj(x3, y3, reverse=True) # Make an Origin object; most of the 'event' values don't matter for # this example origin = Origin({'lat': 0, 'lon': 0, 'depth': 0, 'mag': 7.2, 'eventsourcecode': ''}) rup = QuadRupture.fromVertices( lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3, origin, group_index=[0, 0, 0, 1, 1, 1]) # Sites buf = 0.25 lat = np.linspace(np.nanmin(rup.lats) - buf, np.nanmax(rup.lats) + buf, 20) lon = np.linspace(np.nanmin(rup.lons) - buf, np.nanmax(rup.lons) + buf, 20) lons, lats = np.meshgrid(lon, lat) dep = np.zeros_like(lons) x, y = proj(lon, lat) rupx, rupy = proj(rup.lons, rup.lats) # Calculate U and T dtypes = ['U', 'T'] dists = get_distance(dtypes, lats, lons, dep, rup) targetU = np.array( [[-28.53228275, -28.36479713, -28.20139732, -28.0407734, -27.88135558, -27.72144153, -27.55935946, -27.39362017, -27.22300147, -27.04653062, -26.86338215, -26.67275638, -26.47381287, -26.26569449, -26.04762427, -25.81902477, -25.57961136, -25.32943282, -25.06885791, -24.79852214], [-23.53750292, -23.3748086, -23.21793537, -23.06521934, -22.91449689, -22.76331684, -22.60928211, -22.45042208, -22.28542121, -22.11355532, -21.93435402, -21.74720475, -21.55115107, -21.34497916, -21.12749377, -20.89781118, -20.6555466, -20.40086149, -20.13439948, -19.85716145], [-18.53499939, -18.37689929, -18.22732841, -18.08427516, -17.94468687, -17.80472632, -17.66045115, -17.50880802, -17.3484421, -17.17963435, -17.0032098, -16.81921732, -16.62638972, -16.42258419, -16.20564846, -15.9741218, -15.72753538, -15.4663671, -15.19180844, -14.9054813], [-13.52283359, -13.36797542, -13.22589288, -13.09466537, -12.97028551, -12.84653536, -12.71591089, -12.57212088, -12.41335561, -12.24319318, -12.06681006, -11.88598424, -11.69798166, -11.49796348, -11.28169605, -11.04691388, -10.79343174, -10.52262594, -10.23677602, -9.93851158], [-8.49936685, -8.34357094, -8.20650964, -8.08786858, -7.98403171, -7.88628837, -7.78005273, -7.64833307, -7.48359988, -7.29992491, -7.11862682, -6.94410189, -6.76618701, -6.5727842, -6.35634881, -6.11465447, -5.84925708, -5.56369035, -5.26212482, -4.94857454], [-3.46638168, -3.30047216, -3.15914418, -3.04618465, -2.96252939, -2.90194067, -2.84436315, -2.75029014, -2.56983592, -2.33744275, -2.1512136, -1.99833104, -1.84066354, -1.6541107, -1.43071517, -1.17252753, -0.88592286, -0.57817222, -0.25582315, 0.07585567], [1.56416954, 1.75393848, 1.9183586, 2.04909316, 2.13723278, 2.17776584, 2.18272501, 2.20967639, 2.37405656, 2.65073289, 2.80205222, 2.90973407, 3.05124404, 3.2505182, 3.50336116, 3.7967575, 4.11742779, 4.45465822, 4.80070204, 5.15033407], [6.5633489, 6.78740885, 6.99419348, 7.17551069, 7.31963558, 7.4113505, 7.43666779, 7.40177458, 7.40517136, 7.58520044, 7.62013169, 7.71596777, 7.90558457, 8.17213015, 8.49008681, 8.83763176, 9.19937294, 9.56556659, 9.9305469, 10.29132309], [11.48996073, 11.74301446, 11.99016964, 12.22782156, 12.44984059, 12.6446727, 12.78798484, 12.82584849, 12.61992833, 12.26579742, 12.32166685, 12.54665462, 12.86628045, 13.23578462, 13.62571822, 14.01882924, 14.40617707, 14.78388296, 15.15089889, 15.5076165], [16.31383216, 16.57376544, 16.83189511, 17.08626411, 17.33309437, 17.56429108, 17.76005623, 17.85853532, 17.57101025, 17.32637346, 17.45075419, 17.77199513, 18.16933168, 18.58284635, 18.9891851, 19.37985879, 19.75324557, 20.11079653, 20.4549905, 20.78837053], [21.03975749, 21.28450315, 21.5243142, 21.75603974, 21.97469496, 22.17298057, 22.34310053, 22.49668569, 22.73940191, 22.70030633, 22.95351405, 23.35967832, 23.75891016, 24.14867803, 24.51536915, 24.85878249, 25.18398203, 25.49615514, 25.79932964, 26.09638269], [25.70484089, 25.92709225, 26.14280395, 26.35119497, 26.55363501, 26.75827099, 26.9915523, 27.31779086, 27.77993211, 27.71070831, 28.13624949, 28.723482, 29.25285078, 29.66404032, 30.00169474, 30.30044315, 30.57916576, 30.84804427, 31.1126134, 31.37586841], [30.35406633, 30.5585145, 30.75843356, 30.95627127, 31.15811912, 31.3763124, 31.63114968, 31.94156189, 32.23691802, 32.38759301, 32.86915665, 33.83467935, 34.46125278, 34.89905345, 35.25111257, 35.55095664, 35.82150686, 36.07720619, 36.32643896, 36.57385362], [35.0222379, 35.21734711, 35.41081942, 35.60589495, 35.80774808, 36.02313791, 36.25826988, 36.51619168, 36.81025966, 37.21777129, 37.86674108, 38.66578072, 39.25203723, 39.78060643, 40.20815617, 40.5606039, 40.86634527, 41.14457482, 41.40732554, 41.66197722], [39.73046099, 39.92514041, 40.12152415, 40.32316112, 40.5350467, 40.76393316, 41.01937758, 41.3172128, 41.68596492, 42.16604148, 42.77622755, 43.447503, 44.03771478, 44.55012468, 45.00551259, 45.40376857, 45.75505135, 46.07204699, 46.36554362, 46.64361367], [44.4876174, 44.68959464, 44.89710008, 45.11420443, 45.34646809, 45.60143197, 45.88932906, 46.22363997, 46.61975585, 47.0884227, 47.62307543, 48.1913408, 48.74937117, 49.26945799, 49.74327902, 50.17123158, 50.55810895, 50.91098842, 51.23731582, 51.54375617], [49.29279265, 49.50696882, 49.73006999, 49.96625305, 50.22080319, 50.50022572, 50.81209441, 51.1642666, 51.56290694, 52.00913021, 52.49553006, 53.00565389, 53.51861282, 54.01614414, 54.48672101, 54.9254339, 55.33212663, 55.70951516, 56.06170563, 56.39317058], [54.13906629, 54.3671694, 54.60643024, 54.86053563, 55.13377911, 55.43088558, 55.75658576, 56.1148189, 56.50752978, 56.93329478, 57.38640012, 57.85715119, 58.33367994, 58.80451404, 59.26065475, 59.69644542, 60.10938419, 60.49940252, 60.86803179, 61.21767916], [59.01741908, 59.25887491, 59.51248349, 59.78119592, 60.06816694, 60.37651862, 60.70895927, 61.0672529, 61.45160192, 61.86010542, 62.28853397, 62.73062937, 63.17894547, 63.62598375, 64.06523791, 64.49185106, 64.90281064, 65.2967858, 65.67377362, 66.03469546], [63.9193099, 64.17236414, 64.4376317, 64.71732366, 65.01362255, 65.32847988, 65.66334836, 66.0188704, 66.39457546, 66.7886684, 67.19800022, 67.61828012, 68.04451487, 68.47157851, 68.89476917, 69.31022713, 69.71515194, 70.10782673, 70.4875021, 70.85420436]] ) np.testing.assert_allclose(targetU, dists['U'], atol=0.01) targetT = np.array( [[-2.27427469e+01, -1.97498544e+01, -1.67512900e+01, -1.37464632e+01, -1.07350712e+01, -7.71715083e+00, -4.69305811e+00, -1.66336318e+00, 1.37131605e+00, 4.41047613e+00, 7.45381136e+00, 1.05011799e+01, 1.35524779e+01, 1.66074913e+01, 1.96657949e+01, 2.27267294e+01, 2.57894503e+01, 2.88530154e+01, 3.19164798e+01, 3.49789747e+01], [-2.30778766e+01, -2.00896906e+01, -1.70950973e+01, -1.40931667e+01, -1.10834219e+01, -8.06600712e+00, -5.04171582e+00, -2.01179123e+00, 1.02248614e+00, 4.06025218e+00, 7.10129626e+00, 1.01459367e+01, 1.31946312e+01, 1.62475702e+01, 1.93044511e+01, 2.23644788e+01, 2.54265185e+01, 2.84892997e+01, 3.15515954e+01, 3.46123426e+01], [-2.33971472e+01, -2.04144525e+01, -1.74245193e+01, -1.44256870e+01, -1.14169177e+01, -8.39830615e+00, -5.37141115e+00, -2.33902937e+00, 6.95823925e-01, 3.73133431e+00, 6.76769593e+00, 9.80663091e+00, 1.28500821e+01, 1.58991008e+01, 1.89534737e+01, 2.20119662e+01, 2.50728111e+01, 2.81341606e+01, 3.11943854e+01, 3.42522163e+01], [-2.36965870e+01, -2.07206976e+01, -1.77370901e+01, -1.47426715e+01, -1.17347885e+01, -8.71247709e+00, -5.67801094e+00, -2.63761285e+00, 4.00625914e-01, 3.43182302e+00, 6.45782532e+00, 9.48491128e+00, 1.25187545e+01, 1.55616657e+01, 1.86127822e+01, 2.16694756e+01, 2.47286680e+01, 2.77876297e+01, 3.08443066e+01, 3.38973527e+01], [-2.39698399e+01, -2.10022612e+01, -1.80281475e+01, -1.50423801e+01, -1.20388157e+01, -9.01204040e+00, -5.96160398e+00, -2.89867328e+00, 1.52194374e-01, 3.17268218e+00, 6.17334725e+00, 9.17699572e+00, 1.21964990e+01, 1.52330975e+01, 1.82821226e+01, 2.13375815e+01, 2.43943933e+01, 2.74490375e+01, 3.04994435e+01, 3.35446330e+01], [-2.42070742e+01, -2.12471979e+01, -1.82855675e+01, -1.53163304e+01, -1.23296744e+01, -9.31127857e+00, -6.24535210e+00, -3.12882361e+00, -2.24460581e-02, 2.95354485e+00, 5.89215412e+00, 8.86387424e+00, 1.18748249e+01, 1.49128245e+01, 1.79640055e+01, 2.10182501e+01, 2.40696313e+01, 2.71153177e+01, 3.01543919e+01, 3.31869788e+01], [-2.43971375e+01, -2.14368866e+01, -1.84826148e+01, -1.55321207e+01, -1.25786621e+01, -9.60654678e+00, -6.58612151e+00, -3.48118311e+00, -3.16555025e-01, 2.61618307e+00, 5.53740540e+00, 8.52666510e+00, 1.15623361e+01, 1.46149780e+01, 1.76674294e+01, 2.07125025e+01, 2.37483764e+01, 2.67756033e+01, 2.97955606e+01, 3.28097430e+01], [-2.45384925e+01, -2.15583842e+01, -1.85874288e+01, -1.56290738e+01, -1.26867853e+01, -9.76140655e+00, -6.84407754e+00, -3.90089971e+00, -8.41806596e-01, 2.14754495e+00, 5.18583472e+00, 8.26271822e+00, 1.13266091e+01, 1.43684333e+01, 1.73916223e+01, 2.04017469e+01, 2.34034936e+01, 2.64002111e+01, 2.93941282e+01, 3.23866586e+01], [-2.46576775e+01, -2.16355610e+01, -1.86129545e+01, -1.55919156e+01, -1.25763765e+01, -9.57306672e+00, -6.59044329e+00, -3.62352541e+00, -5.92041388e-01, 2.33255341e+00, 5.29498494e+00, 8.24834463e+00, 1.11833819e+01, 1.41167617e+01, 1.70571082e+01, 2.00065102e+01, 2.29645946e+01, 2.59302937e+01, 2.89023967e+01, 3.18797332e+01], [-2.48161623e+01, -2.17489533e+01, -1.86651328e+01, -1.55589864e+01, -1.24224388e+01, -9.24466730e+00, -6.01521475e+00, -2.75148770e+00, 3.89519039e-01, 2.99589525e+00, 5.45696689e+00, 8.01247078e+00, 1.07291540e+01, 1.35565782e+01, 1.64461360e+01, 1.93723515e+01, 2.23222250e+01, 2.52881249e+01, 2.82650171e+01, 3.12494172e+01], [-2.50857405e+01, -2.20002811e+01, -1.88926336e+01, -1.57550887e+01, -1.25770789e+01, -9.34497451e+00, -6.04430316e+00, -2.67290100e+00, 5.40854953e-01, 2.30509492e+00, 3.58183843e+00, 6.23701436e+00, 9.28727128e+00, 1.23205706e+01, 1.53428945e+01, 1.83666035e+01, 2.13934954e+01, 2.44218171e+01, 2.74496472e+01, 3.04757209e+01], [-2.55082697e+01, -2.24454912e+01, -1.93710045e+01, -1.62824768e+01, -1.31767102e+01, -1.00469827e+01, -6.86985653e+00, -3.54681638e+00, 1.07062999e-01, 3.34891657e-01, -1.70694750e-01, 3.57896940e+00, 7.17013928e+00, 1.05232789e+01, 1.37976070e+01, 1.70230221e+01, 2.02076136e+01, 2.33576919e+01, 2.64794914e+01, 2.95785985e+01], [-2.60778515e+01, -2.30695744e+01, -2.00684150e+01, -1.70790651e+01, -1.41074315e+01, -1.11587507e+01, -8.23273307e+00, -5.33306966e+00, -2.80144302e+00, -1.84760416e+00, -1.05368779e+00, 1.26163211e+00, 4.90086292e+00, 8.53883059e+00, 1.20996577e+01, 1.55589098e+01, 1.89237978e+01, 2.22114952e+01, 2.54390313e+01, 2.86203790e+01], [-2.67537229e+01, -2.38123298e+01, -2.08964272e+01, -1.80168638e+01, -1.51896230e+01, -1.24401995e+01, -9.81536176e+00, -7.41008520e+00, -5.38073414e+00, -3.78262975e+00, -2.29669890e+00, -3.53057240e-01, 3.13642477e+00, 6.97021789e+00, 1.07026969e+01, 1.42945488e+01, 1.77655640e+01, 2.11406146e+01, 2.44409375e+01, 2.76832489e+01], [-2.74832153e+01, -2.46028623e+01, -2.17593854e+01, -1.89653378e+01, -1.62381218e+01, -1.36022404e+01, -1.10914555e+01, -8.74572618e+00, -6.58963863e+00, -4.58336507e+00, -2.57607747e+00, -2.67233150e-01, 2.82788692e+00, 6.36737407e+00, 9.93334021e+00, 1.34440609e+01, 1.68846862e+01, 2.02577163e+01, 2.35710668e+01, 2.68337230e+01], [-2.82199728e+01, -2.53838486e+01, -2.25869234e+01, -1.98388981e+01, -1.71512612e+01, -1.45365893e+01, -1.20059297e+01, -9.56220853e+00, -7.18799023e+00, -4.83006994e+00, -2.39120744e+00, 2.51308627e-01, 3.17331949e+00, 6.33022626e+00, 9.61428455e+00, 1.29426788e+01, 1.62705993e+01, 1.95770961e+01, 2.28539081e+01, 2.60992146e+01], [-2.89332200e+01, -2.61222251e+01, -2.33461951e+01, -2.06105222e+01, -1.79200485e+01, -1.52776479e+01, -1.26817390e+01, -1.01225741e+01, -7.57801870e+00, -5.01122873e+00, -2.37434916e+00, 3.78303328e-01, 3.27093827e+00, 6.29527723e+00, 9.41912399e+00, 1.26046423e+01, 1.58204753e+01, 1.90448689e+01, 2.22643265e+01, 2.54712657e+01], [-2.96082809e+01, -2.68067500e+01, -2.40331802e+01, -2.12894659e+01, -1.85760763e+01, -1.58910124e+01, -1.32284735e+01, -1.05774862e+01, -7.92111801e+00, -5.23724922e+00, -2.50179068e+00, 3.05790568e-01, 3.19666197e+00, 6.16975035e+00, 9.21353475e+00, 1.23109519e+01, 1.54443017e+01, 1.85982825e+01, 2.17611016e+01, 2.49243957e+01], [-3.02420504e+01, -2.74395034e+01, -2.46578094e+01, -2.18967353e+01, -1.91546206e+01, -1.64278219e+01, -1.37101816e+01, -1.09927140e+01, -8.26378719e+00, -5.51007519e+00, -2.71836365e+00, 1.22111758e-01, 3.01754598e+00, 5.96851903e+00, 8.97043180e+00, 1.20150997e+01, 1.50927299e+01, 1.81935916e+01, 2.13090724e+01, 2.44321477e+01], [-3.08377073e+01, -2.80281994e+01, -2.52335334e+01, -2.24524366e+01, -1.96825082e+01, -1.69199811e+01, -1.41595768e+01, -1.13945492e+01, -8.61701306e+00, -5.81861191e+00, -2.99148017e+00, -1.29317230e-01, 2.77170749e+00, 5.71249079e+00, 8.69110042e+00, 1.17033684e+01, 1.47437429e+01, 1.78061436e+01, 2.08846464e+01, 2.39739290e+01]] ) np.testing.assert_allclose(targetT, dists['T'], atol=0.01)
def __init__(self, origin, rup, lat, lon, depth, T): """ Constructor for bayless2013. Args: origin: Shakemap Origin object. rup: Shakemap Rupture object. lat: Numpy array of latitudes. lon: Numpy array of longitudes. depth: Numpy array of depths (km); down is positive. T: Period; Currently, only acceptable values are 0.5, 0.75, 1, 1.5, 2, 3, 4, 5, 7.5, 10. """ self._origin = origin self._rup = rup self._rake = origin.rake self._M = origin.mag self._hyp = origin.getHypo() self._lon = lon self._lat = lat self._dep = depth self._T = T # Lists of widths and lengths for each quad in the rupture self._W = self._rup.getIndividualWidths() self._L = self._rup.getIndividualTopLengths() # Number of quads self._nq = len(self._W) # Currently assuming that the rake is the same on all subruptures . self.__getSlipCategory() # Rupture weights are supposed to be based on seismic moment. # Since moment is proportional to area, lets just use area # for now area = self._W * self._L self.weights = area / np.sum(area) # Put in pseudo-hypocenters for each quad self.__setPseudoHypocenters() self._fd = 0 for i in range(self._nq): self.i = i # Compute some genral stuff that is required for all mechanisms dtypes = ['rrup', 'rx', 'ry0'] dists = get_distance(dtypes, self._lat, self._lon, self._dep, self._rup) self.__Rrup = np.reshape(dists['rrup'], self._lat.shape) self.__Rx = np.reshape(dists['rx'], self._lat.shape) self.__Ry = np.reshape(dists['ry0'], self._lat.shape) # NOTE: use Rx and Ry to compute Az in 'computeAz'. It is probably # possible to make this a lot faster by avoiding the # calculation of these distances each time. # Az is the NGA definition of source-to-site azimuth for a finite # rupture. See Kaklamanos et al. (2011) Figure 2 for illustration. self.__computeAz() # uses Rx and Ry, which are for the i-th quad. # Magnitude taper (does not depend on mechanism) if self._M <= 5.0: self._T_Mw = 0.0 elif (self._M > 5.0) and (self._M < 6.5): self._T_Mw = 1.0 - (6.5 - self._M) / 1.5 else: self._T_Mw = 1.0 if self.SlipCategory == 'SS': self.__computeSS() self._fd = self._fd + self.weights[i] * self._fd_SS elif self.SlipCategory == 'DS': self.__computeDS() self._fd = self._fd + self.weights[i] * self._fd_DS else: # Compute both SS and DS self.__computeSS() self.__computeDS() # Normalize rake to reference angle sintheta = np.abs(np.sin(np.radians(self._rake))) costheta = np.abs(np.cos(np.radians(self._rake))) refrake = np.arctan2(sintheta, costheta) # Compute weights: DipWeight = refrake / (np.pi / 2.0) StrikeWeight = 1.0 - DipWeight fdcombined = StrikeWeight * self._fd_SS + DipWeight * \ self._fd_DS self._fd = self._fd + self.weights[i] * fdcombined
def test_multisegment_discordant(): # The one thing that isn't check above is discordancy for segments # with multiple quads. For this, we need a synthetic example. x0 = np.array([0, 1, -1, 10, 9, 7]) y0 = np.array([0, 10, 20, 40, 35, 30]) z0 = np.array([0, 0, 0, 0, 0, 0]) x1 = np.array([1, -1, 0, 9, 7, 6]) y1 = np.array([10, 20, 30, 35, 30, 25]) z1 = np.array([0, 0, 0, 0, 0, 0]) x2 = np.array([3, 1, 2, 7, 5, 4]) y2 = np.array([10, 20, 30, 35, 30, 25]) z2 = np.array([10, 10, 10, 10, 10, 10]) x3 = np.array([2, 3, 1, 8, 7, 5]) y3 = np.array([0, 10, 20, 40, 35, 30]) z3 = np.array([10, 10, 10, 10, 10, 10]) epilat = 32.15270 epilon = -115.30500 proj = geo.utils.get_orthographic_projection(epilon - 1, epilon + 1, epilat + 1, epilat - 1) lon0, lat0 = proj(x0, y0, reverse=True) lon1, lat1 = proj(x1, y1, reverse=True) lon2, lat2 = proj(x2, y2, reverse=True) lon3, lat3 = proj(x3, y3, reverse=True) # Make an Origin object; most of the 'event' values don't matter for # this example origin = Origin({ 'lat': 0, 'lon': 0, 'depth': 0, 'mag': 7.2, 'eventsourcecode': '' }) rup = QuadRupture.fromVertices(lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3, origin, group_index=[0, 0, 0, 1, 1, 1]) # Sites buf = 0.25 lat = np.linspace(np.nanmin(rup.lats) - buf, np.nanmax(rup.lats) + buf, 20) lon = np.linspace(np.nanmin(rup.lons) - buf, np.nanmax(rup.lons) + buf, 20) lons, lats = np.meshgrid(lon, lat) dep = np.zeros_like(lons) x, y = proj(lon, lat) rupx, rupy = proj(rup.lons, rup.lats) # Calculate U and T dtypes = ['U', 'T'] dists = get_distance(dtypes, lats, lons, dep, rup) targetU = np.array( [[ -28.53228275, -28.36479713, -28.20139732, -28.0407734, -27.88135558, -27.72144153, -27.55935946, -27.39362017, -27.22300147, -27.04653062, -26.86338215, -26.67275638, -26.47381287, -26.26569449, -26.04762427, -25.81902477, -25.57961136, -25.32943282, -25.06885791, -24.79852214 ], [ -23.53750292, -23.3748086, -23.21793537, -23.06521934, -22.91449689, -22.76331684, -22.60928211, -22.45042208, -22.28542121, -22.11355532, -21.93435402, -21.74720475, -21.55115107, -21.34497916, -21.12749377, -20.89781118, -20.6555466, -20.40086149, -20.13439948, -19.85716145 ], [ -18.53499939, -18.37689929, -18.22732841, -18.08427516, -17.94468687, -17.80472632, -17.66045115, -17.50880802, -17.3484421, -17.17963435, -17.0032098, -16.81921732, -16.62638972, -16.42258419, -16.20564846, -15.9741218, -15.72753538, -15.4663671, -15.19180844, -14.9054813 ], [ -13.52283359, -13.36797542, -13.22589288, -13.09466537, -12.97028551, -12.84653536, -12.71591089, -12.57212088, -12.41335561, -12.24319318, -12.06681006, -11.88598424, -11.69798166, -11.49796348, -11.28169605, -11.04691388, -10.79343174, -10.52262594, -10.23677602, -9.93851158 ], [ -8.49936685, -8.34357094, -8.20650964, -8.08786858, -7.98403171, -7.88628837, -7.78005273, -7.64833307, -7.48359988, -7.29992491, -7.11862682, -6.94410189, -6.76618701, -6.5727842, -6.35634881, -6.11465447, -5.84925708, -5.56369035, -5.26212482, -4.94857454 ], [ -3.46638168, -3.30047216, -3.15914418, -3.04618465, -2.96252939, -2.90194067, -2.84436315, -2.75029014, -2.56983592, -2.33744275, -2.1512136, -1.99833104, -1.84066354, -1.6541107, -1.43071517, -1.17252753, -0.88592286, -0.57817222, -0.25582315, 0.07585567 ], [ 1.56416954, 1.75393848, 1.9183586, 2.04909316, 2.13723278, 2.17776584, 2.18272501, 2.20967639, 2.37405656, 2.65073289, 2.80205222, 2.90973407, 3.05124404, 3.2505182, 3.50336116, 3.7967575, 4.11742779, 4.45465822, 4.80070204, 5.15033407 ], [ 6.5633489, 6.78740885, 6.99419348, 7.17551069, 7.31963558, 7.4113505, 7.43666779, 7.40177458, 7.40517136, 7.58520044, 7.62013169, 7.71596777, 7.90558457, 8.17213015, 8.49008681, 8.83763176, 9.19937294, 9.56556659, 9.9305469, 10.29132309 ], [ 11.48996073, 11.74301446, 11.99016964, 12.22782156, 12.44984059, 12.6446727, 12.78798484, 12.82584849, 12.61992833, 12.26579742, 12.32166685, 12.54665462, 12.86628045, 13.23578462, 13.62571822, 14.01882924, 14.40617707, 14.78388296, 15.15089889, 15.5076165 ], [ 16.31383216, 16.57376544, 16.83189511, 17.08626411, 17.33309437, 17.56429108, 17.76005623, 17.85853532, 17.57101025, 17.32637346, 17.45075419, 17.77199513, 18.16933168, 18.58284635, 18.9891851, 19.37985879, 19.75324557, 20.11079653, 20.4549905, 20.78837053 ], [ 21.03975749, 21.28450315, 21.5243142, 21.75603974, 21.97469496, 22.17298057, 22.34310053, 22.49668569, 22.73940191, 22.70030633, 22.95351405, 23.35967832, 23.75891016, 24.14867803, 24.51536915, 24.85878249, 25.18398203, 25.49615514, 25.79932964, 26.09638269 ], [ 25.70484089, 25.92709225, 26.14280395, 26.35119497, 26.55363501, 26.75827099, 26.9915523, 27.31779086, 27.77993211, 27.71070831, 28.13624949, 28.723482, 29.25285078, 29.66404032, 30.00169474, 30.30044315, 30.57916576, 30.84804427, 31.1126134, 31.37586841 ], [ 30.35406633, 30.5585145, 30.75843356, 30.95627127, 31.15811912, 31.3763124, 31.63114968, 31.94156189, 32.23691802, 32.38759301, 32.86915665, 33.83467935, 34.46125278, 34.89905345, 35.25111257, 35.55095664, 35.82150686, 36.07720619, 36.32643896, 36.57385362 ], [ 35.0222379, 35.21734711, 35.41081942, 35.60589495, 35.80774808, 36.02313791, 36.25826988, 36.51619168, 36.81025966, 37.21777129, 37.86674108, 38.66578072, 39.25203723, 39.78060643, 40.20815617, 40.5606039, 40.86634527, 41.14457482, 41.40732554, 41.66197722 ], [ 39.73046099, 39.92514041, 40.12152415, 40.32316112, 40.5350467, 40.76393316, 41.01937758, 41.3172128, 41.68596492, 42.16604148, 42.77622755, 43.447503, 44.03771478, 44.55012468, 45.00551259, 45.40376857, 45.75505135, 46.07204699, 46.36554362, 46.64361367 ], [ 44.4876174, 44.68959464, 44.89710008, 45.11420443, 45.34646809, 45.60143197, 45.88932906, 46.22363997, 46.61975585, 47.0884227, 47.62307543, 48.1913408, 48.74937117, 49.26945799, 49.74327902, 50.17123158, 50.55810895, 50.91098842, 51.23731582, 51.54375617 ], [ 49.29279265, 49.50696882, 49.73006999, 49.96625305, 50.22080319, 50.50022572, 50.81209441, 51.1642666, 51.56290694, 52.00913021, 52.49553006, 53.00565389, 53.51861282, 54.01614414, 54.48672101, 54.9254339, 55.33212663, 55.70951516, 56.06170563, 56.39317058 ], [ 54.13906629, 54.3671694, 54.60643024, 54.86053563, 55.13377911, 55.43088558, 55.75658576, 56.1148189, 56.50752978, 56.93329478, 57.38640012, 57.85715119, 58.33367994, 58.80451404, 59.26065475, 59.69644542, 60.10938419, 60.49940252, 60.86803179, 61.21767916 ], [ 59.01741908, 59.25887491, 59.51248349, 59.78119592, 60.06816694, 60.37651862, 60.70895927, 61.0672529, 61.45160192, 61.86010542, 62.28853397, 62.73062937, 63.17894547, 63.62598375, 64.06523791, 64.49185106, 64.90281064, 65.2967858, 65.67377362, 66.03469546 ], [ 63.9193099, 64.17236414, 64.4376317, 64.71732366, 65.01362255, 65.32847988, 65.66334836, 66.0188704, 66.39457546, 66.7886684, 67.19800022, 67.61828012, 68.04451487, 68.47157851, 68.89476917, 69.31022713, 69.71515194, 70.10782673, 70.4875021, 70.85420436 ]]) np.testing.assert_allclose(targetU, dists['U'], atol=0.01) targetT = np.array([ [ -2.27427469e+01, -1.97498544e+01, -1.67512900e+01, -1.37464632e+01, -1.07350712e+01, -7.71715083e+00, -4.69305811e+00, -1.66336318e+00, 1.37131605e+00, 4.41047613e+00, 7.45381136e+00, 1.05011799e+01, 1.35524779e+01, 1.66074913e+01, 1.96657949e+01, 2.27267294e+01, 2.57894503e+01, 2.88530154e+01, 3.19164798e+01, 3.49789747e+01 ], [ -2.30778766e+01, -2.00896906e+01, -1.70950973e+01, -1.40931667e+01, -1.10834219e+01, -8.06600712e+00, -5.04171582e+00, -2.01179123e+00, 1.02248614e+00, 4.06025218e+00, 7.10129626e+00, 1.01459367e+01, 1.31946312e+01, 1.62475702e+01, 1.93044511e+01, 2.23644788e+01, 2.54265185e+01, 2.84892997e+01, 3.15515954e+01, 3.46123426e+01 ], [ -2.33971472e+01, -2.04144525e+01, -1.74245193e+01, -1.44256870e+01, -1.14169177e+01, -8.39830615e+00, -5.37141115e+00, -2.33902937e+00, 6.95823925e-01, 3.73133431e+00, 6.76769593e+00, 9.80663091e+00, 1.28500821e+01, 1.58991008e+01, 1.89534737e+01, 2.20119662e+01, 2.50728111e+01, 2.81341606e+01, 3.11943854e+01, 3.42522163e+01 ], [ -2.36965870e+01, -2.07206976e+01, -1.77370901e+01, -1.47426715e+01, -1.17347885e+01, -8.71247709e+00, -5.67801094e+00, -2.63761285e+00, 4.00625914e-01, 3.43182302e+00, 6.45782532e+00, 9.48491128e+00, 1.25187545e+01, 1.55616657e+01, 1.86127822e+01, 2.16694756e+01, 2.47286680e+01, 2.77876297e+01, 3.08443066e+01, 3.38973527e+01 ], [ -2.39698399e+01, -2.10022612e+01, -1.80281475e+01, -1.50423801e+01, -1.20388157e+01, -9.01204040e+00, -5.96160398e+00, -2.89867328e+00, 1.52194374e-01, 3.17268218e+00, 6.17334725e+00, 9.17699572e+00, 1.21964990e+01, 1.52330975e+01, 1.82821226e+01, 2.13375815e+01, 2.43943933e+01, 2.74490375e+01, 3.04994435e+01, 3.35446330e+01 ], [ -2.42070742e+01, -2.12471979e+01, -1.82855675e+01, -1.53163304e+01, -1.23296744e+01, -9.31127857e+00, -6.24535210e+00, -3.12882361e+00, -2.24460581e-02, 2.95354485e+00, 5.89215412e+00, 8.86387424e+00, 1.18748249e+01, 1.49128245e+01, 1.79640055e+01, 2.10182501e+01, 2.40696313e+01, 2.71153177e+01, 3.01543919e+01, 3.31869788e+01 ], [ -2.43971375e+01, -2.14368866e+01, -1.84826148e+01, -1.55321207e+01, -1.25786621e+01, -9.60654678e+00, -6.58612151e+00, -3.48118311e+00, 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-1.37101816e+01, -1.09927140e+01, -8.26378719e+00, -5.51007519e+00, -2.71836365e+00, 1.22111758e-01, 3.01754598e+00, 5.96851903e+00, 8.97043180e+00, 1.20150997e+01, 1.50927299e+01, 1.81935916e+01, 2.13090724e+01, 2.44321477e+01 ], [ -3.08377073e+01, -2.80281994e+01, -2.52335334e+01, -2.24524366e+01, -1.96825082e+01, -1.69199811e+01, -1.41595768e+01, -1.13945492e+01, -8.61701306e+00, -5.81861191e+00, -2.99148017e+00, -1.29317230e-01, 2.77170749e+00, 5.71249079e+00, 8.69110042e+00, 1.17033684e+01, 1.47437429e+01, 1.78061436e+01, 2.08846464e+01, 2.39739290e+01 ] ]) np.testing.assert_allclose(targetT, dists['T'], atol=0.01)