FireGenerator: Generate random sequence of fire events#

class FireGenerator(*args, **kwds)[source]#

Bases: Component

Generate a random fire event or time series.

Parameters:

  • mean_fire_recurrence (float) – Average time between fires for a given location

  • shape_parameter (float) – Describes the skew of the Weibull distribution. If shape < 3.5, data skews left. If shape == 3.5, data is normal. If shape > 3.5, data skews right. To approximate a normal bell curve, use a value of 3.5

  • scale_parameter (float, optional) – Describes the peak of the Weibull distribution, located at the 63.5% value of the cumulative distribution function. If unknown, it can be found using mean fire recurrence value and the get_scale_parameter() method described later.

Generate a random fire event in time.

Parameters:

  • grid (landlab model grid) –

  • mean_fire_recurrence (float) – Average time between fires for a given location

  • shape_parameter (float) – Describes the skew of the Weibull distribution. If shape < 3.5, data skews left. If shape == 3.5, data is normal. If shape > 3.5, data skews right.

  • scale_parameter (float, optional) – Describes the peak of the Weibull distribution, located at the 63.5% value of the cumulative distribution function. If unknown, it can be found using mean fire recurrence value and the get_scale_parameter().

__init__(grid, mean_fire_recurrence=1.0, shape_parameter=3.5, scale_parameter=None)[source]#

Generate a random fire event in time.

Parameters:

  • grid (landlab model grid) –

  • mean_fire_recurrence (float) – Average time between fires for a given location

  • shape_parameter (float) – Describes the skew of the Weibull distribution. If shape < 3.5, data skews left. If shape == 3.5, data is normal. If shape > 3.5, data skews right.

  • scale_parameter (float, optional) – Describes the peak of the Weibull distribution, located at the 63.5% value of the cumulative distribution function. If unknown, it can be found using mean fire recurrence value and the get_scale_parameter().

generate_fire_recurrence()[source]#

Get time to next fire.

Finds the time to next fire (fire recurrence) based on the scale parameter (63.5% of fire Weibull distribution) and the shape parameter (describes the skew of the histogram, shape = 3.5 represents a normal distribution).

Rounds the time to next fire to 4 significant figures, for neatness.

Returns:

Updated value for the time to next fire.

Return type:

float

get_scale_parameter()[source]#

Get the scale parameter.

::
mean_fire_recurrence = (scale_parameter * (

special.gamma(1 + (1 / shape))))

sets the scale parameter.

property scale_parameter#

Scale parameter for the random distribution.