SWMManywhere sensitivity analysis

This repository is to reproduce the experiments and plots from this paper:

Dobson, Barnaby, et al. "SWMManywhere: A Global-scale Workflow for Generation and Sensitivity Analysis of Synthetic Urban Drainage Models." (2024). doi: 10.31223/X5GT5X

Installation

Clone the repository:

git clone https://github.com/barneydobson/swmmanywhere_paper.git

Navigate to the repository and install:

pip install -e .
pip install -r dev-requirements.txt

Running the experiments

The intended use is via config file. We extend its behaviour with two new options:

• parameters_to_sample: provides a list of parameters to be sampled. For example,

parameters_to_sample:
- min_v
- max_v

• sample_magnitude: provides the amount of sampling effort to perform. The total number of samples to be evaluated is equal to:

2**(sample_magnitude + 1) * (n_parameters_to_sample + 1)

This new config file should be passed to the experimenter. For example,

python experimenter.py --config_path=/path/to/config.yml

You are likely to need to run such an experiment on HPC. The experimenter is set up to parallelise as a PBS jobarray - with an example submit file in submit_icl_example.

Recreating plots

The results of the experiments used in the paper are contained in tests/test_data in this repository. Only those required to create the plots are retained to avoid overwhelming the storage on this repository. All figures can be reproduced in the tests/test_data/plots directory by running tests/test_figs.py locally:

pytest tests/test_figs.py