pyPhenology.models.M1

class pyPhenology.models.M1(parameters={})

The Thermal Time Model with a daylength correction.

Event happens on \(DOY\) when the following is met:

\[\sum_{t=t_{1}}^{DOY}R_{f}(T_{i}) \geq (L_{i}/24)^kF^*\]

where:

\[R_{f}(T_{i}) = max(T_{i}-threshold, 0)\]

This model requires a daylength column in the predictors in addition to daily mean temperature.

Parameters:

t1 : int

\(t_{1}\) - The DOY which forcing accumulating beings

default : (-67,298)

T : int

\(T\) - The threshold above which forcing accumulates

default : (-25,25)

F : int, > 0

\(F^{*}\) - The total forcing units required

default : (0,1000)

k : int, > 0

\(k^{*}\) - Daylength coefficient

default : (0,50)

Notes:

Blümel, K., & Chmielewski, F. M. (2012). Shortcomings of classical phenological forcing models and a way to overcome them. Agricultural and Forest Meteorology, 164, 10–19. http://doi.org/10.1016/j.agrformet.2012.05.001

__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