Correct imports

Author: birgits

example/basic_example.py

@@ -8,15 +8,14 @@
 
 import os
 import pandas as pd
-import numpy as np
 
 try:
     from matplotlib import pyplot as plt
 except ImportError:
     plt = None
 
-from windpowerlib import modelchain
-from windpowerlib import wind_turbine as wt
+from windpowerlib.modelchain import ModelChain
+from windpowerlib.wind_turbine import WindTurbine
 
 # You can use the logging package to get logging messages from the windpowerlib
 # Change the logging level if you want more or less messages
@@ -108,7 +107,7 @@ def initialise_wind_turbines():
                   'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]})  # in m/s
     }
     # initialise WindTurbine object
-    my_turbine = wt.WindTurbine(**myTurbine)
+    my_turbine = WindTurbine(**myTurbine)
 
     # specification of wind turbine where power curve is provided
     # if you want to use the power coefficient curve add
@@ -119,7 +118,7 @@ def initialise_wind_turbines():
         'rotor_diameter': 127  # in m
     }
     # initialise WindTurbine object
-    e126 = wt.WindTurbine(**enerconE126)
+    e126 = WindTurbine(**enerconE126)
 
     return my_turbine, e126
 
@@ -149,28 +148,28 @@ def calculate_power_output(weather, my_turbine, e126):
     # power output calculation for my_turbine
     # initialise ModelChain with default parameters and use run_model method
     # to calculate power output
-    mc_my_turbine = modelchain.ModelChain(my_turbine).run_model(weather)
+    mc_my_turbine = ModelChain(my_turbine).run_model(weather)
     # write power output timeseries to WindTurbine object
     my_turbine.power_output = mc_my_turbine.power_output
 
     # power output calculation for e126
     # own specifications for ModelChain setup
     modelchain_data = {
-        'obstacle_height': 0,  # default: 0
         'wind_speed_model': 'logarithmic',  # 'logarithmic' (default),
                                             # 'hellman' or
                                             # 'interpolation_extrapolation'
         'density_model': 'ideal_gas',  # 'barometric' (default), 'ideal_gas' or
                                        # 'interpolation_extrapolation'
-        'temperature_model': 'linear_gradient', # 'linear_gradient' (def.) or
-                                                # 'interpolation_extrapolation'
+        'temperature_model': 'linear_gradient',  # 'linear_gradient' (def.) or
+                                                 # 'interpolation_extrapolation'
         'power_output_model': 'power_curve',  # 'power_curve' (default) or
                                               # 'power_coefficient_curve'
         'density_correction': True,  # False (default) or True
+        'obstacle_height': 0,  # default: 0
         'hellman_exp': None}  # None (default) or None
     # initialise ModelChain with own specifications and use run_model method
     # to calculate power output
-    mc_e126 = modelchain.ModelChain(e126, **modelchain_data).run_model(weather)
+    mc_e126 = ModelChain(e126, **modelchain_data).run_model(weather)
     # write power output timeseries to WindTurbine object
     e126.power_output = mc_e126.power_output
 

windpowerlib/modelchain.py

@@ -9,8 +9,7 @@
 __license__ = "GPLv3"
 
 import logging
-from windpowerlib import wind_speed, density, temperature, power_output, tools
-import pandas as pd
+from . import wind_speed, density, temperature, power_output, tools
 
 
 class ModelChain(object):