Explanation

Understanding-oriented material: the why and how it works behind OasisLMF.

These pages are co-located with the code they describe so that a change in behaviour and its explanation travel together in the same pull request. This is the core of the documentation strategy — see How the documentation is organised.

Financial Module

The conceptual model and the Python/NumPy implementation of the Financial Module (oasislmf/pytools/fm):

Financial Module

• Financial Module
• Financial Module — architecture

Ground-up loss modelling

How ground-up losses are simulated by the Monte-Carlo engine (oasislmf/pytools/gulmc): the modelling methodology, sampling, correlation, disaggregation, and coverage dependency.

Ground-up loss

• Modelling methodology
• Sampling Methodology
• Correlation
• Disaggregation

Adjustments & methodology

Adjustments applied around the core loss calculation — vulnerability and damage adjustments, post-loss amplification, pre-analysis exposure adjustments, and currency conversion:

Adjustments & methodology

• Vulnerability Adjustments
• Absolute Damage
• Post Loss Amplification
• Pre Analysis Adjustments
• Currency Conversion

Models

What an Oasis model is made of — its components and structure:

Models

• Oasis Models

Keys & lookup

How exposure is matched to model data (areaperil and vulnerability IDs) via the keys / lookup service (oasislmf/lookup):

Keys & lookup

• Keys Service
• Geocoding

The corresponding API reference for these subsystems is generated directly from the source in Reference, so explanation and reference sit side by side.

How the docs work

Guidance for people writing these pages — ownership, the content model, tooling and the authoring traps worth knowing:

• How the documentation is organised