Firetoolbox is a collection of Python libraries, data files, and scripts that help you work with fire modeling data. This article explains what Firetoolbox is and how it can make your life easier if you’re working with fire modeling data. If you’re new to fire modeling or want to get an overview of how the tools in the Firetoolbox work together, this article is for you. Keep reading to learn more about what Firetoolbox is and why it’s useful for anyone who needs to analyze models or create new ones.
What Is Firetoolbox?
Firetoolbox is a Python library that contains tools for working with data related to fire modeling. This includes reading and writing various file formats and calculating quantities from model data. The Firetoolbox includes many individual libraries that perform specific tasks. These libraries can be used together or separately to solve a variety of problems. Firetoolbox is open source and available on GitHub. It includes documentation and examples that can be used to learn how to use the tools in the library. Anyone is free to suggest changes to the library and make a pull request to update the code.
Finding and Understanding Your Data
If you have a model that was created using an open-source model setup (like FlamMap or FARSITE), you can find your model data in the model directory. You’ll see an .py file and a .mat file — the .py file contains the code for your model and parameters, and the .mat file holds the data for your model. You’ll also see a .grd file — this holds the graphics for your model. If you have a model that was created using proprietary code, you’ll likely have model data in a .xml or .csv file. You can use the DataParser function in the Firetoolbox to read these files. If you have data that was not used in a model, you can use the Reader functions in the Firetoolbox to read in the data.
Calculate the Initial Flame Speed From a Model
The initial flame speed is a quantity calculated from the temperature and humidity profiles in a fire model. It is used to predict where and when a fire will start. Using the InitialFlameSpeed function, you can find the initial flame speed from a model. This function takes a model and a time as inputs and returns the initial flame speed. You can also use the FlameSpeed function to find the flame speed at a time in the future. This function takes a model and a time as inputs and returns the flame speed at that time.
Estimate Burning Rate from EMF Data
The burning rate is a quantity calculated from the temperature and humidity profiles in a fire model. It is used to predict how fast fuel will be consumed by a fire. Using the BurningRate function, you can find the burning rate from a model. This function takes a model and a time as inputs and returns the burning rate at that time. You can also find the burning rate at a future time by using the FutureBurningRate function.
Estimate Pyro-Processing of Fuel From EMFs
The pyro-processing of fuel is a quantity calculated from the temperature and humidity profiles in a fire model. It is used to predict the amount of carbon that will be released as CO2 instead of CO (also known as the “pyro-processing” term) during a fire. Using the PyroProcessingOfFuel function, you can find the pyro-processing of fuel from a model. This function takes a model and a time as inputs and returns the pyro-processing of fuel at that time.
Summing Up
The Firetoolbox is a set of useful Python libraries for working with fire modeling data. Using the tools in the Firetoolbox, you can read and write various file formats, confirm the accuracy of the EM Equation, and estimate the initial flame speed, burning rate, and pyro-processing of fuel from a model. The Firetoolbox is open source and available on GitHub.