4.5. Proficiency — Incremental Dynamic Analysis

imselection.compute_proficiency_ida(ida_dict, ds_index=0)[source]

Proficiency measure βIM|DCR=1 from an Incremental Dynamic Analysis result.

Proficiency is estimated as 0.5 · ln(im84 / im16) where im16 and im84 are the 16th and 84th percentile IDA curves evaluated at the damage threshold for the specified damage state.

Parameters:

ida_dict (dict) – Output of postprocessor.process_ida_results.
ds_index (int, optional) – Damage-state index. Default 0.

Returns:

dict with keys
* 'beta_IM_given_DCRLS1' — proficiency (NaN if p16 ≥ p84)
* 'im16' — IM at 16th percentile for this DS
* 'im84' — IM at 84th percentile for this DS
* 'method' — 'IDA'

Example

from openquake.vmtk.imselection import imselection

ims = imselection()
result = ims.compute_proficiency_ida(ida_dict)
print(f"Proficiency (zeta) = {result['proficiency']:.4f}")