https://github.com/koverholt/bayes-fire

A collection of examples for performing Bayesian Inference using PyMC for fire engineering scenarios
https://github.com/koverholt/bayes-fire

Last synced: 9 days ago
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A collection of examples for performing Bayesian Inference using PyMC for fire engineering scenarios

• Host: GitHub
• URL: https://github.com/koverholt/bayes-fire
• Owner: koverholt
• License: other
• Created: 2015-03-12T17:12:12.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2016-02-08T04:55:09.000Z (almost 9 years ago)
• Last Synced: 2024-12-24T04:44:23.396Z (17 days ago)
• Language: Python
• Homepage:
• Size: 92.1 MB
• Stars: 5
• Watchers: 3
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
About

=====

This is a collection of example scripts that makes use of the Python package

PyMC, which is an implementation of Bayesian inference in Python. The scripts

here were adapted from a tutorial given at SciPy 2011 held in Austin, TX, by

Christopher Fonnesbeck (founder of PyMC) and Abie Flaxman. The slides for the

tutorial are located in the Tutorial_Slides folder.

Requirements

============

These scripts require Python and the PyMC and NetworkX packages to be installed. For a

convenient installation of Python, you can download the

[Anaconda Python Distribution](https://store.continuum.io/cshop/anaconda/)

from Continuum Analytics. Anaconda includes the `pymc` and `networkx` packages.

Files

=====

```

./

 ├── CFAST_Model            -  Contains the CFAST model executable and holds

 |                                 the temporary CFAST case files when running

 |                                 the CFAST examples.

 |

 ├──├ Example Cases         -  Examples using PyMC in fire scenarios.

 |  |

 |  ├── */Experimental_Data -  Experimental data to be read in by the scripts.

 |  |

 |  ├── */Figures           -  Output figures and plots will be written to

 |  |                              this folder.

 |  |

 |  ├── */PyMC_Output_Files -  Output from PyMC cases that require longer

 |  |                              runtimes (FDS and CFAST).

 |  |

 |  └── */Scripts           -  Contains the example PyMC scripts.

 |

 ├── FDS_Model              -  Contains the FDS model executable and holds the

 |                                 temporary FDS case files when running the

 |                                 FDS examples.

 |

 ├── Scripts_Other          -  Contains Python scripts that demonstrate

 |                                 additional functionality.

 |

 └── Tutorial_Slides        -  Slides from the SciPy 2011 tutorial.

```

Usage

=====

Run the Run_Case.py Python files in the Scripts directory for each example

case, and check the output in the Figures directory.

The scripts data_*.py, graphics.py, and models.py are called by the example

scripts.

Happy Bayesianing!