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FireBench is a Python library designed for the systematic benchmarking and inter-comparison of fire models.

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# FireBench

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**FireBench** is a Python library designed for the systematic benchmarking and inter-comparison of fire models.
Recent advancements in fire modeling have introduced complex and varied models, but there is a lack of systematic evaluation regarding their accuracy, efficiency, sensitivity, validity domain, and inter-compatibility.
FireBench aims to address this gap by providing a framework to assess fire models on the following criteria:

- **Accuracy**: Precision in predicting fire front positions and plume dynamics.
- **Efficiency**: Computational resources required for specific computation.
- **Sensitivity**: Model outputs' responsiveness to input variations, crucial for calibration and data assimilation.
- **Validity Domain**: Operational input ranges for which models are applicable.
- **Inter-Compatibility**: Integration capabilities with other models.

FireBench offers a dual approach for evaluation: intercomparison without extensive observational data and benchmarking against a validation dataset. This framework aims to enhance fire modeling for both scientific research and operational applications, with results archived in a dedicated database.

## Installation

### Prerequisites

To install the FireBench library, follow these steps:

### 1. Clone the Repository

You can clone the repository using either HTTPS or SSH. Choose one of the following methods:

#### Using HTTPS:
```bash
git clone https://github.com/wirc-sjsu/firebench.git
```

#### Using SSH:
```bash
git clone git@github.com:wirc-sjsu/firebench.git
```

### 2. Install FireBench and its Dependencies

Navigate to the cloned repository and install the FireBench library along with its dependencies using `pip`:

```bash
cd firebench
pip install .
```

### 3. Set up local paths

FireBench uses `~/.firebench/local_db` as the default local database directory for files managed locally by workflows.
Functions that write workflow records also accept an explicit `local_db_path` argument.

FireBench contains package data such as fuel models in the repository `data` directory.
Data helpers use that directory by default, and `get_firebench_data_directory(data_path=...)` can be used when a custom data location is needed.

## Community Discussions

We encourage you to use the [GitHub Discussions](https://github.com/wirc-sjsu/firebench/discussions) tab for questions, help requests, and general discussions about the project. This helps keep our issue tracker focused on bugs and feature requests.

### How to Use Discussions

- **Q&A**: If you have a question about using FireBench, please check the Q&A category.
- **Ideas**: Share your ideas for new features or improvements in the Ideas category.
- **Show and Tell**: Showcase your projects and workflows using FireBench.
- **General**: For any other discussions related to FireBench.

Feel free to start a new discussion or join existing ones to engage with the community!

## Contributing

We welcome contributions to FireBench! For more information on how to contribute, please see our [contribution guidelines](CONTRIBUTE.md).

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