From b423313ad0a851a4b42e7f4946d283ae01edf53f Mon Sep 17 00:00:00 2001
From: "Mads M. Pedersen" <mmpe@dtu.dk>
Date: Fri, 3 Dec 2021 12:28:22 +0000
Subject: [PATCH] automatic detect args4deficit if not set + add all extra
surrogate variable to TensorflowSurrogate
---
py_wake/deficit_models/deficit_model.py | 5 +++++
py_wake/deficit_models/gaussian.py | 2 +-
py_wake/utils/tensorflow_surrogate_utils.py | 13 ++++---------
3 files changed, 10 insertions(+), 10 deletions(-)
diff --git a/py_wake/deficit_models/deficit_model.py b/py_wake/deficit_models/deficit_model.py
index f1e93acbf..3594d89fb 100644
--- a/py_wake/deficit_models/deficit_model.py
+++ b/py_wake/deficit_models/deficit_model.py
@@ -1,11 +1,16 @@
from abc import ABC, abstractmethod
import numpy as np
from numpy import newaxis as na
+import inspect
class DeficitModel(ABC):
deficit_initalized = False
+ def __init__(self):
+ if not hasattr(self, 'args4deficit'):
+ self.args4deficit = set(inspect.getfullargspec(self.calc_deficit).args) - {'self'}
+
def _calc_layout_terms(self, **_):
"""Calculate layout dependent terms, which is not updated during simulation"""
diff --git a/py_wake/deficit_models/gaussian.py b/py_wake/deficit_models/gaussian.py
index c35d5fbc6..0e8bf9bb4 100644
--- a/py_wake/deficit_models/gaussian.py
+++ b/py_wake/deficit_models/gaussian.py
@@ -14,11 +14,11 @@ class BastankhahGaussianDeficit(ConvectionDeficitModel):
A new analytical model for wind-turbine wakes.
J. Renew. Energy. 2014;70:116-23.
"""
- args4deficit = ['WS_ilk', 'WS_eff_ilk', 'dw_ijlk', 'cw_ijlk', 'D_src_il', 'ct_ilk']
def __init__(self, k=0.0324555, use_effective_ws=False):
self._k = k
self.use_effective_ws = use_effective_ws
+ ConvectionDeficitModel.__init__(self)
def k_ilk(self, **_):
return np.reshape(self._k, (1, 1, 1))
diff --git a/py_wake/utils/tensorflow_surrogate_utils.py b/py_wake/utils/tensorflow_surrogate_utils.py
index 8efba343e..306b04278 100644
--- a/py_wake/utils/tensorflow_surrogate_utils.py
+++ b/py_wake/utils/tensorflow_surrogate_utils.py
@@ -41,13 +41,8 @@ class TensorflowSurrogate():
path = Path(path)
with open(path / 'extra_data.json') as fid:
extra_data = json.load(fid)
-
- self.input_channel_names = extra_data['input_channel_names']
- self.output_channel_name = extra_data['output_channel_name']
- self.wind_speed_cut_in = extra_data['wind_speed_cut_in']
- self.wind_speed_cut_out = extra_data['wind_speed_cut_out']
- if 'wohler_exponent' in extra_data:
- self.wohler_exponent = extra_data['wohler_exponent']
+ for k, v in extra_data.items():
+ setattr(self, k, v)
# Create the MinMaxScaler scaler objects.
def json2scaler(d):
@@ -56,8 +51,8 @@ class TensorflowSurrogate():
setattr(scaler, k, v)
return scaler
- self.input_scaler = json2scaler(extra_data['input_scalers'][set_name])
- self.output_scaler = json2scaler(extra_data['output_scalers'][set_name])
+ self.input_scaler = json2scaler(self.input_scalers[set_name])
+ self.output_scaler = json2scaler(self.output_scalers[set_name])
self.model = tf.keras.models.load_model(path / f'model_set_{set_name}.h5')
--
GitLab