pyPhenology.models.Sequential

class pyPhenology.models.Sequential(parameters={})

The sequential model

This uses a triangular response for chilling, and growing degree days for forcing.

Parameters:

t0 : int

The doy which chilling accumulation beings

c_t_min: int | float

Triangular response parameter. The minimum temperature where chilling accumulates.

c_t_opt: int | float

Triangular response parameter. The optimum temperature where chilling accumulates.

c_t_max: int | float

Triangular response parameter. The maximum temperature where chilling accumulates.

C : int | float

Total chilling units required.

f_t : int | float

The threshold above which warming forcing accumulates

F : int, > 0

The total forcing units required

__init__(parameters={})

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([parameters])	Initialize self.
fit(observations, predictors[, …])	Estimate the parameters of a model
get_params()	Get the fitted parameters
predict([to_predict, predictors])	Make predictions
save_params(filename[, overwrite])	Save the parameters for a model
score([metric, doy_observed, to_predict, …])	Evaluate a prediction given observed doy values