import numpy as np
from foxes.core import TurbineModel
import foxes.variables as FV
import foxes.constants as FC
[docs]
class kTI(TurbineModel):
"""
Calculates the wake model parameter `k`
as a linear function of `TI`.
Attributes
----------
ti_var: str
The `TI` variable name
k_var: str
The variable name for k
:group: models.turbine_models
"""
[docs]
def __init__(self, kTI=None, kb=None, ti_var=FV.TI, ti_val=None, k_var=FV.K):
"""
Constructor.
Parameters
----------
kTI: float, optional
Uniform value for `kTI`. If not given it
will be searched in farm data
kb: float, optional
Uniform value for `kb`. If not given it
will be searched in farm data, and zero by default
ti_var: str
The `TI` variable name
ti_val: float, optional
The uniform value of `TI`. If not given it
will be searched in farm data
k_var: str
The variable name for k
"""
super().__init__()
self.ti_var = ti_var
self.k_var = k_var
setattr(self, ti_var, ti_val)
setattr(self, FV.KTI, kTI)
setattr(self, FV.KB, 0 if kb is None else kb)
[docs]
def __repr__(self):
kti = getattr(self, FV.KTI)
kb = getattr(self, FV.KB)
ti = getattr(self, self.ti_var)
tiv = f", ti_val={ti}" if ti is not None else ""
a = f"kTI={kti}, kb={kb}, ti_var={self.ti_var}{tiv}, k_var={self.k_var}"
return f"{type(self).__name__}({a})"
[docs]
def output_farm_vars(self, algo):
"""
The variables which are being modified by the model.
Parameters
----------
algo: foxes.core.Algorithm
The calculation algorithm
Returns
-------
output_vars: list of str
The output variable names
"""
return [self.k_var]
[docs]
def calculate(self, algo, mdata, fdata, st_sel):
"""
The main model calculation.
This function is executed on a single chunk of data,
all computations should be based on numpy arrays.
Parameters
----------
algo: foxes.core.Algorithm
The calculation algorithm
mdata: foxes.core.MData
The model data
fdata: foxes.core.FData
The farm data
st_sel: slice or numpy.ndarray of bool
The state-turbine selection,
for shape: (n_states, n_turbines)
Returns
-------
results: dict
The resulting data, keys: output variable str.
Values: numpy.ndarray with shape (n_states, n_turbines)
"""
kti = self.get_data(
FV.KTI, FC.STATE_TURBINE, lookup="sf", fdata=fdata, upcast=True
)[st_sel]
kb = self.get_data(
FV.KB, FC.STATE_TURBINE, lookup="sf", fdata=fdata, upcast=True
)[st_sel]
ti = self.get_data(
self.ti_var, FC.STATE_TURBINE, lookup="sf", fdata=fdata, upcast=True
)[st_sel]
k = fdata.get(
self.k_var, np.zeros((fdata.n_states, fdata.n_turbines), dtype=FC.DTYPE)
)
k[st_sel] = kti * ti + kb
return {self.k_var: k}