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SWMManywhere software

Project description

SWMManywhere: Synthesise Urban Drainage Network Models Anywhere in the World

Test and build

SWMManywhere is a tool to synthesise urban drainage network models (UDMs) using publicly available data such as street network, DEM, and building footprints, across the globe. It also provides tools for generating SWMM input files and performing simulations for the synthesised UDMs.

Features

  • Automatic data retrieval and preprocessing: all of our data requirements are met with global datasets, so all you need is a bounding box!
  • Customisable network synthesis: change a range of parameters to create different networks, power users can easily extend existing functionality.
  • Streamlined evaluation to compare with real networks: we include a variety of performance metrics and automatic running/comparing if you have your own SWMM model.
  • Command line interface: All of this and more can be accessed by passing a configuration file to a CLI.

Installation

Install SWMManywhere:

pip install swmmanywhere

Documentation and Quickstart

Once installed, you can simply run SWMManywhere from the command line giving a configuration file in YAML format as input. As SWMManywhere can download data automatically from well known sources, this settings file can often be minimal and restricted to indicating the geographical area to be processed:

python -m swmmanywhere --config_path=\path\to\config.yml

The result of the calculation will be a model of the sewage system for that area, like the following, which can then be further processed or analysed with SWMM, for example:

SWMM Model

Follow the Quickstart for a more detailed initial example and ReadTheDocs for full information of SWMManywhere capabilities.

Use and contributing

This project is licensed under the BSD-3-Clause licence, see LICENSE.

There are many things we would like to do! If you are interested to contribute please see CONTRIBUTING and CODE OF CONDUCT.

Project details


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Source Distribution

swmmanywhere-0.1.2.tar.gz (301.0 kB view hashes)

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