Merge branch 'features/tests' into dev

Author: SabineHaas

example/basic_example.ipynb

@@ -361,5 +361,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 0
 }

tests/test_modelchain.py

@@ -124,6 +124,11 @@ def test_wind_speed_hub(self):
         test_mc_3 = mc.ModelChain(
             wt.WindTurbine(**self.test_turbine),
             wind_speed_model='interpolation_extrapolation')
+        # Test modelchain with
+        # wind_speed_model='log_interpolation_extrapolation'
+        test_mc_4 = mc.ModelChain(
+            wt.WindTurbine(**self.test_turbine),
+            wind_speed_model='log_interpolation_extrapolation')
 
         # Parameters for tests
         wind_speed_8m = np.array([[4.0], [5.0]])
@@ -145,6 +150,8 @@ def test_wind_speed_hub(self):
         assert_series_equal(test_mc_2.wind_speed_hub(weather_df), v_wind_exp)
         v_wind_exp = pd.Series(data=[50.0, 74.0])
         assert_series_equal(test_mc_3.wind_speed_hub(weather_df), v_wind_exp)
+        v_wind_exp = pd.Series(data=[15.3188511585, 21.9782767378])
+        assert_series_equal(test_mc_4.wind_speed_hub(weather_df), v_wind_exp)
 
         # wind_speed is given at hub height
         weather_df.columns = [np.array(['wind_speed', 'wind_speed',

tests/test_tools.py

@@ -1,7 +1,8 @@
 import pandas as pd
 from pandas.util.testing import assert_series_equal
 
-from windpowerlib.tools import linear_interpolation_extrapolation
+from windpowerlib.tools import (linear_interpolation_extrapolation,
+                                logarithmic_interpolation_extrapolation)
 
 
 class TestTools:
@@ -39,3 +40,38 @@ def test_linear_interpolation_extrapolation(self):
         assert_series_equal(linear_interpolation_extrapolation(
             df, **parameters), exp_output)
 
+    def test_logarithmic_interpolation_extrapolation(self):
+        parameters = {'target_height': 80}
+        df = pd.DataFrame(data={10: [2.0, 2.0, 3.0],
+                                80: [4.0, 5.0, 6.0],
+                                200: [5.0, 8.0, 10.0]},
+                          index=[0, 1, 2])
+        # target_height is equal to height given in a column of the DataFrame
+        exp_output = pd.Series(data=[4.0, 5.0, 6.0])
+        assert_series_equal(logarithmic_interpolation_extrapolation(
+            df, **parameters), exp_output)
+        # target_height is between heights given in the columns of the
+        # DataFrame
+        exp_output = pd.Series(
+            data=[4.61074042165, 6.83222126494, 8.44296168659])
+        parameters['target_height'] = 140
+        assert_series_equal(logarithmic_interpolation_extrapolation(
+            df, **parameters), exp_output)
+        exp_output = pd.Series(
+            data=[4.11328333429, 5.16992500144, 6.16992500144])
+        parameters['target_height'] = 90
+        assert_series_equal(logarithmic_interpolation_extrapolation(
+            df, **parameters), exp_output)
+        # target_height is greater than the heights given in the columns of the
+        # DataFrame
+        exp_output = pd.Series(
+            data=[5.19897784672, 8.59693354015, 10.7959113869])
+        parameters['target_height'] = 240
+        assert_series_equal(logarithmic_interpolation_extrapolation(
+            df, **parameters), exp_output)
+        # target_height is smaller than the heights given in the columns of the
+        # DataFrame
+        exp_output = pd.Series(data=[1.33333333333, 1.0, 2.0])
+        parameters['target_height'] = 5
+        assert_series_equal(logarithmic_interpolation_extrapolation(
+            df, **parameters), exp_output)