Merge branch 'API_Changes' into features/weather_df_multiindex

Conflicts:
	windpowerlib/modelchain.py

Author: Birgit Schachler

pytest.ini

@@ -0,0 +1,2 @@
+[pytest]
+addopts = --doctest-modules

tests/test_density.py

@@ -1,29 +1,13 @@
-from windpowerlib.density import (temperature_gradient,
-                                  rho_barometric, rho_ideal_gas)
+from windpowerlib.density import barometric, ideal_gas
 import pandas as pd
 from pandas.util.testing import assert_series_equal
-from numpy.testing import assert_array_equal, assert_allclose
+from numpy.testing import assert_allclose
 import numpy as np
 
 
-class TestDensityTemperature:
+class TestDensity:
 
-    def test_temperature_gradient(self):
-        parameters = {'temperature': pd.Series(data=[267, 268]),
-                      'temperature_height': 2,
-                      'hub_height': 100}
-
-        # Test temperature as pd.Series
-        temp_hub_exp = pd.Series(data=[266.363, 267.36300])
-        assert_series_equal(temperature_gradient(**parameters), temp_hub_exp)
-
-        # Test temperature as np.array
-        temp_hub_exp = np.array([266.363, 267.36300])
-        parameters['temperature'] = np.array(parameters['temperature'])
-        assert_array_equal(temperature_gradient(**parameters), temp_hub_exp)
-        assert isinstance(temperature_gradient(**parameters), np.ndarray)
-
-    def test_rho_barometric(self):
+    def test_barometric(self):
         parameters = {'pressure': pd.Series(data=[101125, 101000]),
                       'pressure_height': 0,
                       'hub_height': 100,
@@ -32,25 +16,25 @@ def test_rho_barometric(self):
         # Test pressure as pd.Series and temperature_hub_height as pd.Series
         # and np.array
         rho_exp = pd.Series(data=[1.30305336, 1.29656645])
-        assert_series_equal(rho_barometric(**parameters), rho_exp)
+        assert_series_equal(barometric(**parameters), rho_exp)
         parameters['temperature_hub_height'] = np.array(
             parameters['temperature_hub_height'])
-        assert_series_equal(rho_barometric(**parameters), rho_exp)
+        assert_series_equal(barometric(**parameters), rho_exp)
 
         # Test pressure as np.array and temperature_hub_height as pd.Series
         parameters['pressure'] = np.array(parameters['pressure'])
         parameters['temperature_hub_height'] = pd.Series(
             data=parameters['temperature_hub_height'])
-        assert_series_equal(rho_barometric(**parameters), rho_exp)
+        assert_series_equal(barometric(**parameters), rho_exp)
 
         # Test pressure as np.array and temperature_hub_height as np.array
         rho_exp = np.array([1.30305336, 1.29656645])
         parameters['temperature_hub_height'] = np.array(
             parameters['temperature_hub_height'])
-        assert_allclose(rho_barometric(**parameters), rho_exp)
-        assert isinstance(rho_barometric(**parameters), np.ndarray)
+        assert_allclose(barometric(**parameters), rho_exp)
+        assert isinstance(barometric(**parameters), np.ndarray)
 
-    def test_rho_ideal_gas(self):
+    def test_ideal_gas(self):
         parameters = {'pressure': pd.Series(data=[101125, 101000]),
                       'pressure_height': 0,
                       'hub_height': 100,
@@ -59,20 +43,20 @@ def test_rho_ideal_gas(self):
         # Test pressure as pd.Series and temperature_hub_height as pd.Series
         # and np.array
         rho_exp = pd.Series(data=[1.30309439, 1.29660728])
-        assert_series_equal(rho_ideal_gas(**parameters), rho_exp)
+        assert_series_equal(ideal_gas(**parameters), rho_exp)
         parameters['temperature_hub_height'] = np.array(
             parameters['temperature_hub_height'])
-        assert_series_equal(rho_ideal_gas(**parameters), rho_exp)
+        assert_series_equal(ideal_gas(**parameters), rho_exp)
 
         # Test pressure as np.array and temperature_hub_height as pd.Series
         parameters['pressure'] = np.array(parameters['pressure'])
         parameters['temperature_hub_height'] = pd.Series(
             data=parameters['temperature_hub_height'])
-        assert_allclose(rho_ideal_gas(**parameters), rho_exp)
+        assert_allclose(ideal_gas(**parameters), rho_exp)
 
         # Test pressure as np.array and temperature_hub_height as np.array
         rho_exp = np.array([1.30309439, 1.29660728])
         parameters['temperature_hub_height'] = np.array(
             parameters['temperature_hub_height'])
-        assert_allclose(rho_ideal_gas(**parameters), rho_exp)
-        assert isinstance(rho_ideal_gas(**parameters), np.ndarray)
+        assert_allclose(ideal_gas(**parameters), rho_exp)
+        assert isinstance(ideal_gas(**parameters), np.ndarray)

tests/test_power_output.py

@@ -1,101 +1,126 @@
 from pandas.util.testing import assert_series_equal
-from windpowerlib.power_output import (cp_curve, cp_curve_density_corr,
-                                       p_curve, p_curve_density_corr)
+from windpowerlib.power_output import (power_coefficient_curve,
+                                       power_curve, _p_curve_density_corr)
 import pandas as pd
 import numpy as np
 from numpy.testing import assert_allclose
+import pytest
 
 
 class TestPowerOutput:
 
-    def test_cp_curve(self):
+    def test_power_coefficient_curve(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.DataFrame(data={'cp': [0.3, 0.4, 0.5]},
-                                                index=[4.0, 5.0, 6.0])}
+                      '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')
-        assert_series_equal(cp_curve(**parameters), power_output_exp)
+        assert_series_equal(power_coefficient_curve(**parameters),
+                            power_output_exp)
         parameters['density'] = np.array(parameters['density'])
-        assert_series_equal(cp_curve(**parameters), power_output_exp)
-
+        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'])
-        assert_allclose(cp_curve(**parameters), power_output_exp)
-        assert isinstance(cp_curve(**parameters), np.ndarray)
+        assert_allclose(power_coefficient_curve(**parameters),
+                        power_output_exp)
+        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
         parameters['density'] = pd.Series(data=parameters['density'])
-        assert_allclose(cp_curve(**parameters), power_output_exp)
-        assert isinstance(cp_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.DataFrame(data={'cp': [0.3, 0.4, 0.5]},
-                                                index=[4.0, 5.0, 6.0])}
+        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 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_p_curve(self):
+    def test_power_curve(self):
         parameters = {'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
-                      'p_values': pd.DataFrame(data={'p': [300, 400, 500]},
-                                               index=[4.0, 5.0, 6.0])}
+                      'p_values': pd.Series([300, 400, 500],
+                                            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(p_curve(**parameters), power_output_exp)
-
+        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(p_curve(**parameters), power_output_exp)
-        assert isinstance(p_curve(**parameters), np.ndarray)
+        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.DataFrame(data={'p': [300, 400, 500]},
-                                               index=[4.0, 5.0, 6.0])}
+                      '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)

tests/test_temperature.py

@@ -0,0 +1,23 @@
+from windpowerlib.temperature import linear_gradient
+import pandas as pd
+from pandas.util.testing import assert_series_equal
+from numpy.testing import assert_array_equal
+import numpy as np
+
+
+class TestTemperature:
+
+    def test_linear_gradient(self):
+        parameters = {'temperature': pd.Series(data=[267, 268]),
+                      'temperature_height': 2,
+                      'hub_height': 100}
+
+        # Test temperature as pd.Series
+        temp_hub_exp = pd.Series(data=[266.363, 267.36300])
+        assert_series_equal(linear_gradient(**parameters), temp_hub_exp)
+
+        # Test temperature as np.array
+        temp_hub_exp = np.array([266.363, 267.36300])
+        parameters['temperature'] = np.array(parameters['temperature'])
+        assert_array_equal(linear_gradient(**parameters), temp_hub_exp)
+        assert isinstance(linear_gradient(**parameters), np.ndarray)