pygmm.pezeshk_zandieh_tavakoli_2011.PezeshkZandiehTavakoli2011¶

class pygmm.pezeshk_zandieh_tavakoli_2011.PezeshkZandiehTavakoli2011(scenario)[source]¶

Pezeshk, Zandieh, and Tavakoli (2011, [Pezeshk et al., 2011]) model.

Developed for the Eastern North America with a reference velocity of 2000 m/s.

Parameters:: scenario (pygmm.model.Scenario) – earthquake scenario

NAME = 'Pezeshk et al. (2011)'¶: Long name of the model

ABBREV = 'Pea11'¶: Short name of the model

V_REF = 2000.0¶

COEFF = rec.array([( 0. , 1.5828, 0.2298, -0.03847, -3.8325, 0.3535, 0.3321 , -0.09165, -2.5517, 0.1831 , -4.224e-04, 6.6521, -0.02105 , 0.3778, 0.2791, 0.021), ( 0.01 , 2.0434, 0.1987, -0.03837, -4.0521, 0.3688, 0.1995 , -0.08918, -2.5948, 0.1847 , -3.965e-04, 7.0645, -0.01974 , 0.3688, 0.2792, 0.022), ( 0.02 , 2.305 , 0.1877, -0.03697, -4.0443, 0.3616, -0.1222 , -0.09157, -2.9998, 0.1941 , -1.707e-04, 7.3314, -0.01974 , 0.3691, 0.2796, 0.023), ( 0.03 , 1.9848, 0.2203, -0.03616, -3.8032, 0.3384, 0.07814, -0.1126 , -3.3125, 0.2017 , -5.322e-05, 7.1183, -0.02094 , 0.3817, 0.2838, 0.022), ( 0.04 , 1.6854, 0.2404, -0.03578, -3.6129, 0.3247, 0.2956 , -0.118 , -3.332 , 0.1977 , -1.113e-04, 6.8113, -0.0218 , 0.3914, 0.2874, 0.024), ( 0.05 , 1.4517, 0.2414, -0.03468, -3.4683, 0.3177, 0.5224 , -0.1296 , -3.2109, 0.1956 , -2.669e-04, 6.3705, -0.02244 , 0.399 , 0.2905, 0.025), ( 0.075, 1.0698, 0.2989, -0.03897, -3.377 , 0.318 , 0.7422 , -0.1215 , -2.6889, 0.1723 , -6.659e-04, 6.0817, -0.02312 , 0.4108, 0.2976, 0.025), ( 0.1 , 0.9314, 0.3088, -0.03844, -3.2926, 0.3063, 0.7064 , -0.09521, -2.209 , 0.1472 , -9.254e-04, 6.1621, -0.02259 , 0.4102, 0.3007, 0.022), ( 0.15 , 0.3964, 0.4317, -0.04578, -3.2112, 0.2937, 0.6084 , -0.06727, -1.6121, 0.1072 , -1.077e-03, 6.2667, -0.02185 , 0.4066, 0.3023, 0.016), ( 0.2 , -0.4883, 0.6278, -0.05654, -3.0304, 0.2673, 0.5422 , -0.05347, -1.3516, 0.08784, -1.045e-03, 6.1905, -0.02046 , 0.3979, 0.3033, 0.014), ( 0.25 , -1.0098, 0.7401, -0.06309, -2.9959, 0.2623, 0.4421 , -0.03625, -1.2309, 0.07733, -9.648e-04, 6.0635, -0.01933 , 0.3908, 0.3041, 0.015), ( 0.3 , -1.68 , 0.886 , -0.07162, -2.8894, 0.2481, 0.4869 , -0.04324, -1.149 , 0.07056, -9.049e-04, 5.9891, -0.01837 , 0.3867, 0.3068, 0.015), ( 0.4 , -2.3106, 1.022 , -0.07965, -2.9265, 0.2515, 0.4716 , -0.04039, -1.0923, 0.06554, -7.853e-04, 6.0263, -0.01683 , 0.3774, 0.3082, 0.017), ( 0.5 , -3.1365, 1.201 , -0.09037, -2.8823, 0.2456, 0.3333 , -0.02105, -1.0022, 0.05519, -7.069e-04, 5.9117, -0.01556 , 0.3722, 0.3119, 0.017), ( 0.75 , -4.5494, 1.508 , -0.1087 , -2.8614, 0.2424, 0.4023 , -0.03092, -0.975 , 0.05536, -5.685e-04, 5.9835, -0.01339 , 0.3654, 0.3203, 0.021), ( 1. , -5.4113, 1.69 , -0.1196 , -2.8998, 0.2465, 0.3766 , -0.02928, -0.947 , 0.05249, -4.563e-04, 6.1234, -0.0118 , 0.3588, 0.3249, 0.022), ( 1.5 , -6.4806, 1.867 , -0.1282 , -2.9338, 0.2525, 0.2633 , -0.01442, -0.9007, 0.04974, -3.540e-04, 5.9875, -0.0104 , 0.3569, 0.3327, 0.019), ( 2. , -6.934 , 1.907 , -0.1287 , -3.0128, 0.2639, 0.3172 , -0.0215 , -0.8749, 0.04774, -3.025e-04, 6.1355, -0.009443, 0.3561, 0.3387, 0.021), ( 3. , -7.4264, 1.881 , -0.1205 , -2.9742, 0.2576, 0.2585 , -0.0152 , -0.8821, 0.05376, -2.641e-04, 6.0598, -0.008509, 0.354 , 0.3431, 0.024), ( 4. , -7.8064, 1.895 , -0.1183 , -3.005 , 0.2588, 0.3069 , -0.02545, -0.8808, 0.05703, -2.423e-04, 6.2536, -0.007859, 0.3527, 0.3463, 0.03 ), ( 5. , -8.2704, 1.938 , -0.118 , -2.9501, 0.2503, 0.3296 , -0.03023, -1.0125, 0.07332, -2.002e-04, 6.3423, -0.0069 , 0.3577, 0.358 , 0.032), ( 7.5 , -8.3376, 1.806 , -0.1042 , -2.9839, 0.2542, 0.2879 , -0.02252, -1.1817, 0.09598, -1.624e-04, 6.5181, -0.00724 , 0.373 , 0.371 , 0.03 ), (10. , -9.1046, 1.899 , -0.1076 , -2.8611, 0.2395, 0.2868 , -0.0229 , -1.3786, 0.1222 , -1.268e-04, 6.5384, -0.007485, 0.3848, 0.381 , 0.024)], dtype=[('period', '<f8'), ('c_1', '<f8'), ('c_2', '<f8'), ('c_3', '<f8'), ('c_4', '<f8'), ('c_5', '<f8'), ('c_6', '<f8'), ('c_7', '<f8'), ('c_8', '<f8'), ('c_9', '<f8'), ('c_10', '<f8'), ('c_11', '<f8'), ('c_12', '<f8'), ('c_13', '<f8'), ('c_14', '<f8'), ('sigma_reg', '<f8')])¶

PERIODS = array([ 0. , 0.01 , 0.02 , 0.03 , 0.04 , 0.05 , 0.075, 0.1 , 0.15 , 0.2 , 0.25 , 0.3 , 0.4 , 0.5 , 0.75 , 1. , 1.5 , 2. , 3. , 4. , 5. , 7.5 , 10. ])¶: Indices of the periods

INDEX_PGA = 0¶: Index of the peak ground acceleration

INDICES_PSA = array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22])¶: Indices for the spectral accelerations

PARAMS = [<pygmm.model.NumericParameter object>, <pygmm.model.NumericParameter object>]¶: Model parameters

__init__(scenario)[source]¶

Initialize the model.

Parameters:: scenario (Scenario)

INDEX_PGD = None¶: Index of the peak ground displacement

INDEX_PGV = None¶: Index of the peak ground velocity

LIMITS = {}¶: Limits of model applicability

PGD_SCALE = 1.0¶: Scale factor to apply to get PGD in cm

PGV_SCALE = 1.0¶: Scale factor to apply to get PGV in cm/sec

interp_ln_spec_accels(periods, kind='linear')¶

Interpolate the spectral acceleration.

Interpolation of the spectral acceleration is done in natural log space.

Parameters:

periods (array_like) – spectral periods to interpolate the response.
kind (str, optional) – see scipy.interpolate.interp1d() for description of kind. Options include: ‘linear’ (default), ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, and ‘cubic’

Returns:

ln_spec_accels – interpolated spectral accelerations

Return type:

np.ndarray

interp_ln_stds(periods, kind='linear')¶

Interpolate the logarithmic standard deviation.

Interpolate the logarithmic standard deviation (\(\sigma_{\ln}\)) of spectral acceleration at the provided damping at specified periods.

Parameters:

periods (array_like) – spectral periods to interpolate the response.
kind (str, optional) – see scipy.interpolate.interp1d() for description of kind. Options include: ‘linear’ (default), ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, and ‘cubic’

Returns:

ln_stds – interpolated logarithmic standard deviations

Return type:

np.ndarray

interp_spec_accels(periods, kind='linear')¶

Interpolate the spectral acceleration.

Interpolation of the spectral acceleration is done in natural log space.

Parameters:

periods (array_like) – spectral periods to interpolate the response.
kind (str, optional) – see scipy.interpolate.interp1d() for description of kind. Options include: ‘linear’ (default), ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, and ‘cubic’

Returns:

spec_accels – interpolated spectral accelerations

Return type:

np.ndarray

property ln_std_pga: float¶: Peak ground accelaration log-standard deviation.

property ln_std_pgd: float¶: Peak ground displacement log-standard deviation.

property ln_std_pgv: float¶: Peak ground velocity log-standard deviation.

property ln_stds: ndarray¶: Pseudo-spectral accelerations log-standard deviation.

property periods: ndarray¶: Periods specified by the model.

property pga: float¶: Peak ground acceleration (PGA) computed by the model (g).

property pgd: float¶: Peak ground displacement (PGD) computed by the model (cm).

property pgv: float¶: Peak ground velocity (PGV) computed by the model (cm/sec).

property scenario¶

property spec_accels: ndarray¶: Pseudo-spectral accelerations computed by the model (g).