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sjbrandenberg edited this page Dec 5, 2024 · 17 revisions

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The supported modeling team developed a Python code that contains the following functions.

function description
cpt_inverse_filter(qt, depth, **kwargs) Apply Boulanger and DeJong (2018) inverse filter to correct for thin layer effects
cpt_layering(qc1Ncs, Ic, depth, **kwargs) Apply Hudson et al. (2024) clustering algorithm to identify layers in CPT profile
get_pfs(Ic) Computes probability factor for liquefaction susceptibility
get_pfts(csrm_hat, crr_hat) Computes probability factor for liquefaction triggering conditional on susceptibility
get_pfmt(ztop, Ic) Computes probability factor for manifestation of a layer conditional on triggering of the layer
get_pmp(pfmt, pfts, pfs, Ksat, t) Computes probability of manifestation at surface of profile

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