Load cp_ct data on turbine construction rather than in operation model calls. Revert type_dec changes.

Author: misi9170

floris/core/turbine/tum_operation_model.py

@@ -1,8 +1,6 @@
 from __future__ import annotations
 
 import copy
-import os
-from pathlib import Path
 
 import numpy as np
 from attrs import define
@@ -191,13 +189,10 @@ def power(
         # ratio of yawed to unyawed thrust coefficients
         ratio = p / p0
 
-        # Load Cp surface data and construct interpolator
-        pkgroot = Path(os.path.dirname(os.path.abspath(__file__))).resolve().parents[1]
-        lut_file = pkgroot / "turbine_library" / power_thrust_table["cp_ct_data_file"]
-        LUT = np.load(lut_file)
-        cp_i = LUT["cp_lut"]
-        pitch_i = LUT["pitch_lut"]
-        tsr_i = LUT["tsr_lut"]
+        # Extract data from lookup table and construct interpolator
+        cp_i = power_thrust_table["cp_ct_data"]["cp_lut"]
+        pitch_i = power_thrust_table["cp_ct_data"]["pitch_lut"]
+        tsr_i = power_thrust_table["cp_ct_data"]["tsr_lut"]
         interp_lut = RegularGridInterpolator(
             (tsr_i, pitch_i), cp_i, bounds_error=False, fill_value=None
         )
@@ -343,13 +338,10 @@ def thrust_coefficient(
         # Compute ratio of yawed to unyawed thrust coefficients
         ratio = thrust_coefficient1 / thrust_coefficient0 # See above eq. (29)
 
-        # Load Ct surface data and construct interpolator
-        pkgroot = Path(os.path.dirname(os.path.abspath(__file__))).resolve().parents[1]
-        lut_file = pkgroot / "turbine_library" / power_thrust_table["cp_ct_data_file"]
-        LUT = np.load(lut_file)
-        ct_i = LUT["ct_lut"]
-        pitch_i = LUT["pitch_lut"]
-        tsr_i = LUT["tsr_lut"]
+        # Extract data from lookup table and construct interpolator
+        ct_i = power_thrust_table["cp_ct_data"]["ct_lut"]
+        pitch_i = power_thrust_table["cp_ct_data"]["pitch_lut"]
+        tsr_i = power_thrust_table["cp_ct_data"]["tsr_lut"]
         interp_lut = RegularGridInterpolator(
             (tsr_i, pitch_i), ct_i, bounds_error=False, fill_value=None
         )  # *0.9722085500886761)
@@ -702,13 +694,10 @@ def get_pitch(x, *data):
             y = aero_pow - electric_pow
             return y
 
-        # Load Cp/Ct data
-        pkgroot = Path(os.path.dirname(os.path.abspath(__file__))).resolve().parents[1]
-        lut_file = pkgroot / "turbine_library" / power_thrust_table["cp_ct_data_file"]
-        LUT = np.load(lut_file)
-        cp_i = LUT["cp_lut"]
-        pitch_i = LUT["pitch_lut"]
-        tsr_i = LUT["tsr_lut"]
+        # Extract data from lookup table
+        cp_i = power_thrust_table["cp_ct_data"]["cp_lut"]
+        pitch_i = power_thrust_table["cp_ct_data"]["pitch_lut"]
+        tsr_i = power_thrust_table["cp_ct_data"]["tsr_lut"]
         idx = np.squeeze(np.where(cp_i == np.max(cp_i)))
 
         tsr_opt = tsr_i[idx[0]]

floris/core/turbine/turbine.py

@@ -2,6 +2,7 @@
 from __future__ import annotations
 
 import copy
+import os
 from collections.abc import Callable, Iterable
 from pathlib import Path
 
@@ -476,10 +477,6 @@ class Turbine(BaseClass):
     correct_cp_ct_for_tilt: bool = field(default=False)
     floating_tilt_table: dict[str, NDArrayFloat] | None = field(default=None)
 
-    # Even though this Turbine class does not support the multidimensional features as they
-    # are implemented in TurbineMultiDim, providing the following two attributes here allows
-    # the turbine data inputs to keep the multidimensional Cp and Ct curve but switch them off
-    # with multi_dimensional_cp_ct = False
     multi_dimensional_cp_ct: bool = field(default=False)
 
     # Initialized in the post_init function
@@ -507,13 +504,21 @@ def __attrs_post_init__(self) -> None:
 
     def __post_init__(self) -> None:
         self._initialize_tilt_interpolation()
+
+        bypass_numeric_converter = False
         if self.multi_dimensional_cp_ct:
             self._initialize_multidim_power_thrust_table()
-        else:
-            self.power_thrust_table = floris_numeric_dict_converter(
-                self.power_thrust_table,
-                allow_strings=True
-            )
+            bypass_numeric_converter = True
+
+        # Check for whether a cp_ct_data_file is specified, and load it if so.
+        if "cp_ct_data_file" in self.power_thrust_table:
+            floris_root = Path(__file__).resolve().parents[2]
+            file_path = floris_root / "turbine_library" / self.power_thrust_table["cp_ct_data_file"]
+            self.power_thrust_table["cp_ct_data"] = np.load(file_path)
+            bypass_numeric_converter = True
+
+        if not bypass_numeric_converter:
+            self.power_thrust_table = floris_numeric_dict_converter(self.power_thrust_table)
 
     def _initialize_power_thrust_functions(self) -> None:
         turbine_function_model = TURBINE_MODEL_MAP["operation_model"][self.operation_model]

floris/type_dec.py

@@ -59,7 +59,7 @@ def floris_array_converter(data: Iterable) -> np.ndarray:
         raise TypeError(e.args[0] + f". Data given: {data}")
     return a
 
-def floris_numeric_dict_converter(data: dict, allow_strings=False) -> dict:
+def floris_numeric_dict_converter(data: dict) -> dict:
     """
     For the given dictionary, convert all the values to a numeric type. If a value is a scalar, it
     will be converted to a float. If a value is an iterable, it will be converted to a Numpy
@@ -79,11 +79,9 @@ def floris_numeric_dict_converter(data: dict, allow_strings=False) -> dict:
         except TypeError:
             # Not iterable so try to cast to float
             converted_dict[k] = float(v)
-        else: # Iterable so convert to Numpy array
-            if allow_strings and isinstance(v, str):
-                converted_dict[k] = v
-            else:
-                converted_dict[k] = floris_array_converter(v)
+        else:
+            # Iterable so convert to Numpy array
+            converted_dict[k] = floris_array_converter(v)
     return converted_dict
 
 # def array_field(**kwargs) -> Callable:

tests/tum_operation_model_unit_test.py

@@ -1,3 +1,6 @@
+import os
+from pathlib import Path
+
 import numpy as np
 import pytest
 
@@ -22,6 +25,10 @@ def test_TUMLossTurbine():
     wind_speed = 10.0
     turbine_data = SampleInputs().turbine
     turbine_data["power_thrust_table"] = SampleInputs().tum_loss_turbine_power_thrust_table
+    data_file_path = Path(__file__).resolve().parents[1] / "floris" / "turbine_library"
+    turbine_data["power_thrust_table"]["cp_ct_data"] = np.load(
+        data_file_path / turbine_data["power_thrust_table"]["cp_ct_data_file"]
+    )
 
     yaw_angles_nom = 0 * np.ones((1, n_turbines))
     tilt_angles_nom = turbine_data["power_thrust_table"]["ref_tilt"] * np.ones((1, n_turbines))
@@ -138,6 +145,10 @@ def test_TUMLossTurbine_regression():
     wind_speed = 10.0
     turbine_data = SampleInputs().turbine
     turbine_data["power_thrust_table"] = SampleInputs().tum_loss_turbine_power_thrust_table
+    data_file_path = Path(__file__).resolve().parents[1] / "floris" / "turbine_library"
+    turbine_data["power_thrust_table"]["cp_ct_data"] = np.load(
+        data_file_path / turbine_data["power_thrust_table"]["cp_ct_data_file"]
+    )
 
     N_test = 20
     tilt_angles_nom = turbine_data["power_thrust_table"]["ref_tilt"] * np.ones((N_test, n_turbines))
@@ -262,6 +273,10 @@ def test_TUMLossTurbine_integration():
     n_turbines = 1
     turbine_data = SampleInputs().turbine
     turbine_data["power_thrust_table"] = SampleInputs().tum_loss_turbine_power_thrust_table
+    data_file_path = Path(__file__).resolve().parents[1] / "floris" / "turbine_library"
+    turbine_data["power_thrust_table"]["cp_ct_data"] = np.load(
+        data_file_path / turbine_data["power_thrust_table"]["cp_ct_data_file"]
+    )
 
     N_test = 20
     tilt_angles_nom = turbine_data["power_thrust_table"]["ref_tilt"] * np.ones((N_test, n_turbines))