Code overview

The diagram below shows the main internal workflow of ler: how the public classes connect to the source-population samplers, lens-population samplers, image solver, detectability calculation, rate estimators, and JSON outputs.

Flowchart of the internal workflow of ler

Main entry points

GWRATES handles unlensed compact-binary population sampling and detection rates. LeR extends that workflow to strongly lensed events by adding lens galaxy sampling, optical-depth weighting, image-property calculations, and image-level detectability.

The same source-population machinery is used in both paths. The lensed path adds lens parameters and transforms each lensed image into effective GW parameters before applying the same detection-probability and rate machinery.