firebench.stats

firebench.stats.internal.fuel_models.anderson_2015_stats(output_filename: str | None = None, unit_wind: str = 'm/s', unit_ros: str = 'm/s', dpi: int = 150)[source]

Plot statistics from the Anderson 2015 dataset.

This function processes the Anderson (2015) dataset and visualizes:

  • Histogram of observed rate of spread (ROS)

  • Scatter plot of wind speed vs dead fuel moisture

  • Histogram of closest Scott and Burgan 40 (SB40) fuel model matches

Parameters:

  • output_filename (str, optional) – If provided, the resulting figure will be saved to this file path. If None, the figure is displayed interactively. Default None.

  • unit_wind (str, optional) – Unit to which wind speed observations are converted (e.g., “km/h”). Default “m/s”.

  • unit_ros (str, optional) – Unit to which rate of spread observations are converted (e.g., “ft/min”). Default “m/s”.

  • dpi (int, optional) – The resolution in dots per inch. Default 150.

Notes

For more details about the dataset structure and variables, refer to the documentation page for the Anderson (2015) validation dataset.

firebench.stats.utils.hist.auto_bins(data, max_bins=40, base=10)[source]

Automatically generate histogram bin edges for plotting, based on data range.

The function estimates a “nice” bin width using a logarithmic base scaling and selects a width that produces up to max_bins bins while preserving human-readable spacing. It handles NaNs and constant data gracefully.

Parameters:

  • data (array_like) – Input array of values to be histogrammed.

  • max_bins (int, optional) – Maximum number of bins to aim for (default is 40).

  • base (float, optional) – Logarithmic base used to scale bin widths (default is 10).

Returns:

bins – Array of bin edges suitable for use with np.histogram or plt.hist.

Return type:

np.ndarray

Examples

>>> auto_bins([0.1, 0.2, 0.3, 0.4])
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5])