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Python reader for data generated by FDS.

Project description

FDSReader

Fast and easy-to-use Python reader for FDS data

PyPI version

Installation

The package is available on PyPI and can be installed using pip:

pip install fdsreader

FDS Version 6.7.5 and above are fully supported. Versions below 6.7.5 might work, but are not guaranteed to work.

Usage example

import fdsreader as fds

# Creates an instance of a simulation master-class which manages all data for a given simulation
sim = fds.Simulation("./sample_data")

# Examples of data that can be easily accessed
print(sim.meshes, sim.surfaces, sim.slices, sim.data_3d, sim.smoke_3d, sim.isosurfaces, sim.particles, sim.obstructions)

More advanced examples can be found in the respective data type directories inside of the examples directory.

Configuration

The package provides a few configuration options that can be set using the settings module.

fds.settings.KEY = VALUE

# Example
fds.settings.DEBUG = True
KEY VALUE Default Description
LAZY_LOAD boolean True Load all data when initially loading the simulation (False) or only when specific data is needed (True).
ENABLE_CACHING boolean True Cache the loaded simulation to reduce startup times when loading the same simulation again.
DEBUG boolean False Crash on non-critical errors with an exception (True) or output non-critical errors as warnings (False).
IGNORE_ERRORS boolean False Ignore any non-critical errors completely.

Data structure

Data structure

Beware that not all attributes and methods are covered in this diagram. For a complete
documentation of all classes check the API Documentation below.

API Documentation

https://firedynamics.github.io/fdsreader/

Deployment

As the fdsreader has come a long way and the free capabilities of Travis CI have been used up, we now moved to manual CI/CD using a local docker container.
First, the Dockerfile has to be modified to make authentication to GitHub and PyPI possible from within the container. To do so generate these two tokens:
PyPI: https://pypi.org/manage/account/token/
GitHub: https://github.com/settings/tokens/new (set the repo_deployment and public_repo scopes)
Now add these Tokens in the Dockerfile. To now deploy the fdsreader to PyPI and update the Github Pages (Documentation), run the following commands after pushing your changes to the FDSReader to GitHub (apart from the Dockerfile).

cd $REPO_ROOT_DIR
docker build . -t fdsreader-ci  # Only needed the very first time
docker run --rm fdsreader-ci

Manual deployment

It is also possible to deploy to PyPI and Github pages manually using the following steps:

  1. python setup.py sdist bdist_wheel
  2. twine upload dist/*
  3. sphinx-build -b html docs docs/build
  4. cd .. && mkdir gh-pages && cd gh-pages
  5. git init && git remote add origin git@github.com:FireDynamics/fdsreader.git
  6. git fetch --all
  7. git checkout gh-pages
  8. cp -r ../fdsreader/docs/build/* .
  9. git add . && git commit -m "..." && git push origin HEAD:gh-pages

Meta

Distributed under the LGPLv3 (GNU Lesser General Public License v3) license. See LICENSE for more information.

https://github.com/FireDynamics/fdsreader

Contributing

  1. Fork it (https://github.com/FireDynamics/fdsreader/fork)
  2. Create your feature branch (git checkout -b feature/fooBar)
  3. Commit your changes (git commit -am 'Add some fooBar')
  4. Push to the branch (git push origin feature/fooBar)
  5. Create a new Pull Request

Project details


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