mu-star

Mauritius - Systemic Tool for the Analysis of (infrastructure) Risk

This repository contains project-specific codes and configuration to run climate-related risk and resilience analysis of infrastructure networks in Mauritius.

Setup and installation

Clone or download this repository from GitHub:

git clone [email protected]:nismod/mu-star.git

Next, install required dependencies. We recommend using micromamba to install these into a conda environment.

Create a conda environment once (per machine/user):

micromamba create --file environment.yaml

Usage

The principal goal of this repository is to produce analysis results, (damages, losses and adaptation options) that can be visualised in an online viewer akin to infra-risk-vis.

The analysis is comprised of Python scripts wrapped in snakemake rules. Snakemake is a workflow management system that can be used to break up complex modelling chains and improve the reproducibility of analyses. To invoke a rule, call snakemake followed by the file you want to produce.

Some functionality is contained within a helper Python module, located in src/mu_star.

Environment

To make snakemake, the helper Python module and other software dependencies available, activate the environment we previously created.

micromamba activate mu-star

Configuration

Analysis options can be configured using the config/config.yaml file. See it for inline documentation.

Invocation

We use snakemake to drive any analysis. It's best explained with an example. To invoke the rule (and all necessary predecessor rules) to compute direct damage (rehabiliation) costs to the road network due to fluvial flooding, we'd run the following:

snakemake --dry-run --cores 1 data/out/damage/layer-road/rp/peril-flood/subperil-fluvial/ensemble-0/damage.zarr

Parts of the requested file path are parameterisable, e.g. layer-road, peril-flood, subperil-fluvial. By varying these 'wildcards' different outputs can be produced.

Note that the --dry-run flag asks snakemake to report on what work (if any) is necessary. As jobs can be long running, this is useful to check beforehand. To actually run the rules, remove the dry run flag.

The --cores flag indicates how many processors snakemake will use to execute the rules. If rules do not depend on one another and enough processors are available, they may execute simultaneously.

Available rules

See .smk files in workflow/ for available rules and their required input and output files.

While this workflow is in development, some of the rules are placeholders.

Testing

Test the helper library by activating the environment and running the following from this directory:

pytest src/mu_star

Acknowledgements

Funded by the Foreign and Commonwealth Development Office (FCDO) of the United Kingdom.