Merge branch 'dev' into make_windpowerlib_work_offline

Author: SabineHaas

doc/whats_new.rst

@@ -8,6 +8,7 @@ These are new features and improvements of note in each release
     :local:
     :backlinks: top
 
+.. include::  whatsnew/v0-1-2.txt
 .. include::  whatsnew/v0-1-1.txt
 .. include::  whatsnew/v0-1-0.txt
 .. include::  whatsnew/v006.txt

windpowerlib/wake_losses.py

@@ -121,7 +121,7 @@ def get_wind_efficiency_curve(curve_name='all'):
         curve_names = curve_name
 
     efficiency_curve = pd.DataFrame(columns=pd.MultiIndex(levels=[[], []],
-                                                          labels=[[], []]))
+                                                          codes=[[], []]))
 
     for curve_name in curve_names:
         if curve_name.split('_')[0] not in ['dena', 'knorr']:

windpowerlib/wind_farm.py

@@ -264,13 +264,14 @@ def assign_power_curve(self, wake_losses_model='power_efficiency_curve',
                     power_curve = pd.concat(
                         [pd.DataFrame(data={
                             'value': [0.0], 'wind_speed': [0.0]}),
-                         power_curve])
+                         power_curve], sort=True)
                 if power_curve.iloc[-1]['value'] != 0.0:
                     power_curve = pd.concat(
                         [power_curve, pd.DataFrame(data={
                             'value': [0.0], 'wind_speed': [
                                 power_curve['wind_speed'].loc[
-                                    power_curve.index[-1]] + 0.5]})])
+                                    power_curve.index[-1]] + 0.5]})],
+                        sort=True)
             # Add power curves of all turbine types to data frame
             # (multiplied by turbine amount)
             df = pd.concat(

windpowerlib/wind_turbine.py

@@ -238,7 +238,7 @@ def isfloat(x):
         try:
             float(x)
             return x
-        except:
+        except ValueError:
             return False
 
     try:
@@ -337,8 +337,8 @@ def load_turbine_data_from_oedb():
         oep_url + '/api/v0/schema/{}/tables/{}/rows/?'.format(
             schema, table), )
     if not result.status_code == 200:
-        raise ConnectionError("Database connection not successful. " +
-                              "Error: ".format(result.status_code))
+        raise ConnectionError("Database connection not successful. "
+                              "Error: {}".format(result.status_code))
     # extract data
     turbine_data = pd.DataFrame(result.json())
     return turbine_data
@@ -387,9 +387,9 @@ def get_turbine_types(print_out=True):
     """
 
     df = load_turbine_data_from_oedb()
-    cp_curves_df = df.iloc[df.loc[df['has_cp_curve'] == True].index][
+    cp_curves_df = df.iloc[df.loc[df['has_cp_curve']].index][
         ['manufacturer', 'turbine_type', 'has_cp_curve']]
-    p_curves_df = df.iloc[df.loc[df['has_power_curve'] == True].index][
+    p_curves_df = df.iloc[df.loc[df['has_power_curve']].index][
         ['manufacturer', 'turbine_type', 'has_power_curve']]
     curves_df = pd.merge(p_curves_df, cp_curves_df, how='outer',
                          sort=True).fillna(False)