length | Truncated Normal | length_sigma | sample_trunc_norm_dist(self.length, self.length_sigma) def truncated_normal(mean, std_dev, std_dev_limit=2): return float( truncnorm(-std_dev_limit, std_dev_limit, loc=mean, scale=std_dev).rvs() ) |
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Recur_int_median | - | mw→moment, slip_rate, nhm_moment | moment = mag_scaling.mag2mom_nm(mw) moment_base = mag_scaling.mag2mom_nm(self.mw) moment_rate_base = moment_base * 1 / self.recur_int_median
# if the slip rate is 0, then the moment rate does not need scaling if self.slip_rate > 0: slip_factor = slip_rate / self.slip_rate else: slip_factor = 1
moment_rate = moment_rate_base * slip_factor recur_int_median = moment / moment_rate |
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