Bug fixes and test fixes

Author: birgits

tests/test_modelchain.py

@@ -178,9 +178,9 @@ def test_run_model(self):
         test_turbine = {'hub_height': 100,
                         'rotor_diameter': 80,
                         'turbine_name': 'ENERCON E 126 7500',
-                        'fetch_curve': 'p'}
+                        'fetch_curve': 'power_curve'}
 
-        # Test with default parameters of modelchain (p curve)
+        # Test with default parameters of modelchain (power curve)
         power_output_exp = pd.Series(data=[1731887.39768, 3820152.27489],
                                      name='feedin_wind_turbine')
         test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine))
@@ -201,7 +201,7 @@ def test_run_model(self):
         # Test with power coefficient curve and hellman
         power_output_exp = pd.Series(data=[559060.36156, 1251143.98621],
                                      name='feedin_wind_turbine')
-        test_turbine['fetch_curve'] = 'cp'
+        test_turbine['fetch_curve'] = 'power_coefficient_curve'
         test_modelchain = {'wind_speed_model': 'hellman',
                            'power_output_model': 'power_coefficient_curve',
                            'density_correction': False}
@@ -229,17 +229,17 @@ def test_run_model(self):
                                     **test_modelchain)
             test_mc.run_model(weather_df)
         with pytest.raises(ValueError):
-            test_modelchain['wind_speed_model'] = 'wrong_spelling'
+            test_modelchain['density_model'] = 'wrong_spelling'
             test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),
                                     **test_modelchain)
             test_mc.run_model(weather_df)
         with pytest.raises(ValueError):
-            test_modelchain['density_model'] = 'wrong_spelling'
+            test_modelchain['temperature_model'] = 'wrong_spelling'
             test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),
                                     **test_modelchain)
             test_mc.run_model(weather_df)
         with pytest.raises(ValueError):
-            test_modelchain['temperature_model'] = 'wrong_spelling'
+            test_modelchain['wind_speed_model'] = 'wrong_spelling'
             test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),
                                     **test_modelchain)
             test_mc.run_model(weather_df)
@@ -263,7 +263,7 @@ def test_run_model(self):
             test_turbine = {'hub_height': 100,
                             'rotor_diameter': 80,
                             'turbine_name': 'ENERCON E 126 7500',
-                            'fetch_curve': 'p'}
+                            'fetch_curve': 'power_curve'}
             test_modelchain = {'power_output_model': 'power_coefficient_curve',
                                'density_correction': True}
             test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),
@@ -273,7 +273,7 @@ def test_run_model(self):
             test_turbine = {'hub_height': 100,
                             'rotor_diameter': 80,
                             'turbine_name': 'ENERCON E 126 7500',
-                            'fetch_curve': 'cp'}
+                            'fetch_curve': 'power_coefficient_curve'}
             test_modelchain = {'power_output_model': 'power_curve',
                                'density_corr': True}
             test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),

tests/test_tools.py

@@ -39,3 +39,4 @@ def test_linear_interpolation_extrapolation(self):
         parameters['target_height'] = 5
         assert_series_equal(linear_interpolation_extrapolation(
             df, **parameters), exp_output)
+

windpowerlib/modelchain.py

@@ -236,7 +236,7 @@ def density_hub(self, weather_df):
                 weather_df['density'], self.wind_turbine.hub_height)
         else:
             raise ValueError("'{0}' is an invalid value. ".format(
-                             self.density_model) + "`rho_model` " +
+                             self.density_model) + "`density_model` " +
                              "must be 'barometric', 'ideal_gas' or " +
                              "'interpolation_extrapolation'.")
         return density_hub
@@ -348,8 +348,8 @@ def turbine_power_output(self, wind_speed_hub, density_hub):
                           'curve.')
             return (power_output.power_coefficient_curve(
                         wind_speed_hub,
-                        self.wind_turbine.power_curve['wind_speed'],
-                        self.wind_turbine.power_curve['values'],
+                        self.wind_turbine.power_coefficient_curve['wind_speed'],
+                        self.wind_turbine.power_coefficient_curve['values'],
                         self.wind_turbine.rotor_diameter, density_hub,
                         self.density_correction))
         else:

windpowerlib/wind_turbine.py

@@ -170,17 +170,19 @@ def restructure_data():
                         data = np.vstack((data, np.array(
                             [float(col), float(wpp_df[col])])))
             data = np.delete(data, 0, 0)
-            df = pd.DataFrame(data, columns=['v_wind', self.fetch_curve])
-            series = pd.Series(df[self.fetch_curve], index=df['v_wind'])
-            nominal_power = wpp_df['p_nom'].iloc[0] * 1000.0  # kW to W
-            return series, nominal_power
-        if self.fetch_curve == 'p':
-            filename = 'p_curves.csv'
-            p_values, p_nom = restructure_data()
-            self.p_values = p_values * 1000.0  # kW to W
+            df = pd.DataFrame(data, columns=['wind_speed', 'values'])
+            nominal_power = wpp_df['p_nom'].iloc[0]
+            return df, nominal_power
+        if self.fetch_curve == 'power_curve':
+            filename = 'power_curves.csv'
+            self.power_curve, p_nom = restructure_data()
+        elif self.fetch_curve == 'power_coefficient_curve':
+            filename = 'power_coefficient_curves.csv'
+            self.power_coefficient_curve, p_nom = restructure_data()
         else:
-            filename = 'cp_curves.csv'
-            self.cp_values, p_nom = restructure_data()
+            raise ValueError("'{0}' is an invalid value. ".format(
+                             self.fetch_curve) + "`fetch_curve` must be " +
+                             "'power_curve' or 'power_coefficient_curve'.")
         if self.nominal_power is None:
             self.nominal_power = p_nom
         return self
@@ -198,9 +200,8 @@ def read_turbine_data(**kwargs):
     datapath : string, optional
         Path where the data file is stored. Default: './data'
     filename : string, optional
-        Name of data file. Provided data files are 'p_curves.csv' containing
-        power curves and 'cp_curves.csv' containing power coefficient curves.
-        Default: 'p_curves.csv'
+        Name of data file. Provided data files are 'power_curves.csv' and
+        'power_coefficient_curves.csv'. Default: 'power_curves.csv'.
 
     Returns
     -------