Adapt tests to changes of density corrected power curve function

Author: SabineHaas

tests/test_power_output.py

@@ -1,10 +1,10 @@
 from pandas.util.testing import assert_series_equal
 from windpowerlib.power_output import (power_coefficient_curve,
-                                       cp_curve_density_corr,
-                                       power_curve, p_curve_density_corr)
+                                       power_curve, _p_curve_density_corr)
 import pandas as pd
 import numpy as np
 from numpy.testing import assert_allclose
+import pytest
 
 
 class TestPowerOutput:
@@ -16,6 +16,7 @@ def test_power_coefficient_curve(self):
                       'cp_values': pd.Series([0.3, 0.4, 0.5],
                                              index=[4.0, 5.0, 6.0])}
 
+        # Tests without density correction:
         # Test wind_speed as pd.Series with density as pd.Series and np.array
         power_output_exp = pd.Series(data=[0.0, 244615.399, 0.0],
                                      name='feedin_wind_turbine')
@@ -24,7 +25,6 @@ def test_power_coefficient_curve(self):
         parameters['density'] = np.array(parameters['density'])
         assert_series_equal(power_coefficient_curve(**parameters),
                             power_output_exp)
-
         # Test wind_speed as np.array with density as np.array and pd.Series
         power_output_exp = np.array([0.0, 244615.399, 0.0])
         parameters['wind_speed'] = np.array(parameters['wind_speed'])
@@ -36,71 +36,91 @@ def test_power_coefficient_curve(self):
                         power_output_exp)
         assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
 
-    def test_cp_curve_density_corrected(self):
-        parameters = {'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
-                      'density': pd.Series(data=[1.3, 1.3, 1.3]),
-                      'rotor_diameter': 80,
-                      'cp_values': pd.Series([0.3, 0.4, 0.5],
-                                             index=[4.0, 5.0, 6.0])}
-
-        # Test wind_speed as pd.Series with density as pd.Series and np.array
+        # Tests with density correction:
+        # Test wind_speed as np.array with density as pd.Series and np.array
+        power_output_exp = np.array([0.0, 262869.785, 0.0])
+        parameters['density_corr'] = True
+        assert_allclose(power_coefficient_curve(**parameters),
+                        power_output_exp)
+        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
+        parameters['density'] = np.array(parameters['density'])
+        assert_allclose(power_coefficient_curve(**parameters),
+                        power_output_exp)
+        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
+        # Test wind_speed as pd.Series with density as np. array and pd.Series
         power_output_exp = pd.Series(data=[0.0, 262869.785, 0.0],
                                      name='feedin_wind_turbine')
-        assert_series_equal(cp_curve_density_corr(**parameters),
+        parameters['wind_speed'] = pd.Series(data=parameters['wind_speed'])
+        assert_series_equal(power_coefficient_curve(**parameters),
                             power_output_exp)
-        parameters['density'] = np.array(parameters['density'])
-        assert_series_equal(cp_curve_density_corr(**parameters),
+        parameters['density'] = pd.Series(data=parameters['density'])
+        assert_series_equal(power_coefficient_curve(**parameters),
                             power_output_exp)
 
-        # Test wind_speed as np.array with density as np.array and pd.Series
-        power_output_exp = np.array([0.0, 262869.785, 0.0])
-        parameters['wind_speed'] = np.array(parameters['wind_speed'])
-        assert_allclose(cp_curve_density_corr(**parameters),
-                        power_output_exp)
-        assert isinstance(cp_curve_density_corr(**parameters), np.ndarray)
-        parameters['density'] = pd.Series(data=parameters['density'])
-        assert_allclose(cp_curve_density_corr(**parameters),
-                        power_output_exp)
-        assert isinstance(cp_curve_density_corr(**parameters), np.ndarray)
+        # Raise TypeErrors due to wrong type of `density_corr`
+        with pytest.raises(TypeError):
+            parameters['density'] = 'wrong_type'
+            power_coefficient_curve(**parameters)
 
     def test_power_curve(self):
         parameters = {'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
                       'p_values': pd.Series([300, 400, 500],
-                                            index=[4.0, 5.0, 6.0])}
+                                            index=[4.0, 5.0, 6.0]),
+                      'density': pd.Series(data=[1.3, 1.3, 1.3]),
+                      'density_corr': False}
 
+        # Tests without density correction:
         # Test wind_speed as pd.Series
         power_output_exp = pd.Series(data=[0.0, 450.0, 0.0],
                                      name='feedin_wind_turbine')
         assert_series_equal(power_curve(**parameters), power_output_exp)
-
         # Test wind_speed as np.array
         power_output_exp = np.array([0.0, 450.0, 0.0])
         parameters['wind_speed'] = np.array(parameters['wind_speed'])
         assert_allclose(power_curve(**parameters), power_output_exp)
         assert isinstance(power_curve(**parameters), np.ndarray)
 
+        # Tests with density correction:
+        # Test wind_speed as np.array with density as pd.Series and np.array
+        power_output_exp = np.array([0.0, 461.00290572, 0.0])
+        parameters['density_corr'] = True
+        assert_allclose(power_curve(**parameters), power_output_exp)
+        assert isinstance(power_curve(**parameters), np.ndarray)
+        parameters['density'] = np.array(parameters['density'])
+        assert_allclose(power_curve(**parameters), power_output_exp)
+        assert isinstance(power_curve(**parameters), np.ndarray)
+        # Test wind_speed as pd.Series with density as np. array and pd.Series
+        power_output_exp = pd.Series(data=[0.0, 461.00290572, 0.0],
+                                     name='feedin_wind_turbine')
+        parameters['wind_speed'] = pd.Series(data=parameters['wind_speed'])
+        assert_series_equal(power_curve(**parameters), power_output_exp)
+        parameters['density'] = pd.Series(data=parameters['density'])
+        assert_series_equal(power_curve(**parameters),
+                            power_output_exp)
+
+        # Raise TypeErrors due to wrong type of `density_corr`
+        with pytest.raises(TypeError):
+            parameters['density'] = 'wrong_type'
+            power_curve(**parameters)
+
     def test_p_curve_density_corrected(self):
         parameters = {'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
                       'density': pd.Series(data=[1.3, 1.3, 1.3]),
                       'p_values': pd.Series([300, 400, 500],
                                             index=[4.0, 5.0, 6.0])}
 
         # Test wind_speed as pd.Series with density as pd.Series and np.array
-        power_output_exp = pd.Series(data=[0.0, 461.00290572, 0.0],
-                                     name='feedin_wind_turbine')
-        assert_series_equal(p_curve_density_corr(**parameters),
-                            power_output_exp)
+        power_output_exp = [0.0, 461.00290572240806, 0.0]
+        assert _p_curve_density_corr(**parameters) == power_output_exp
         parameters['density'] = np.array(parameters['density'])
-        assert_series_equal(p_curve_density_corr(**parameters),
-                            power_output_exp)
+        assert _p_curve_density_corr(**parameters) == power_output_exp
 
         # Test wind_speed as np.array with density as np.array and pd.Series
-        power_output_exp = np.array([0.0, 461.00290572, 0.0])
-        parameters['wind_speed'] = np.array(parameters['wind_speed'])
-        assert_allclose(p_curve_density_corr(**parameters),
-                        power_output_exp)
-        assert isinstance(p_curve_density_corr(**parameters), np.ndarray)
+        assert _p_curve_density_corr(**parameters) == power_output_exp
         parameters['density'] = pd.Series(data=parameters['density'])
-        assert_allclose(p_curve_density_corr(**parameters),
-                        power_output_exp)
-        assert isinstance(p_curve_density_corr(**parameters), np.ndarray)
+        assert _p_curve_density_corr(**parameters) == power_output_exp
+
+        # Raise TypeError due to density is None
+        with pytest.raises(TypeError):
+            parameters['density'] = None
+            _p_curve_density_corr(**parameters)