Adaptions for documentation

Author: SabineHaas

windpowerlib/power_curves.py

@@ -40,7 +40,7 @@ def smooth_power_curve(power_curve_wind_speeds, power_curve_values,
         Default: 'turbulence_intensity'.
     mean_gauss : float
         Mean of the Gaus distribution in
-        :py:func:`~.tools.gauss_distribution`:. Default: 0.
+        :py:func:`~.tools.gauss_distribution`. Default: 0.
 
     Other Parameters
     ----------------

windpowerlib/tools.py

@@ -134,7 +134,7 @@ def gauss_distribution(function_variable, standard_deviation, mean=0):
     Gauss distribution.
 
     The Gauss distribution is used in the function
-    :py:func:`~.power_curves.smooth_power_curve`: for power curve smoothing.
+    :py:func:`~.power_curves.smooth_power_curve` for power curve smoothing.
 
     Parameters
     ----------
@@ -188,7 +188,7 @@ def estimate_turbulence_intensity(height, roughness_length):
     -----
     The following equation is used [1]_:
 
-    .. math:: TI = \frac{1}{\ln\left(\frac{h}{z_\text{0}}\right)}
+    .. math:: TI = \frac{1}{\ln\left( \frac{h}{z_0} \right)}
 
     with:
         TI: turbulence intensity, h: height, :math:`z_{0}`: roughness length

windpowerlib/turbine_cluster_modelchain.py

@@ -26,15 +26,15 @@ class TurbineClusterModelChain(ModelChain):
         consideration. Options: None, 'power_efficiency_curve' or
         'constant_efficiency' or the name of a wind efficiency curve like
         'dena_mean'. Default: 'dena_mean'.
-        Use :py:func:`~.wake_losses.display_wind_efficiency_curves`: to see a
+        Use :py:func:`~.wake_losses.display_wind_efficiency_curves` to see a
         list of all provided wind efficiency curves.
     smoothing : boolean
         If True the power curves will be smoothed before or after the
         aggregation of power curves depending on `smoothing_order`.
         Default: False.
     block_width : float
         Width between the wind speeds in the sum of the equation in
-        :py:func:`~.power_curves.smooth_power_curve`:. Default: 0.5.
+        :py:func:`~.power_curves.smooth_power_curve`. Default: 0.5.
     standard_deviation_method : string
         Method for calculating the standard deviation for the Gauss
         distribution. Options: 'turbulence_intensity', 'Staffell_Pfenninger'.
@@ -84,15 +84,15 @@ class TurbineClusterModelChain(ModelChain):
         consideration. Options: None, 'power_efficiency_curve' or
         'constant_efficiency' or the name of a wind efficiency curve like
         'dena_mean'. Default: 'dena_mean'.
-        Use :py:func:`~.wake_losses.display_wind_efficiency_curves`: to see a
+        Use :py:func:`~.wake_losses.display_wind_efficiency_curves` to see a
         list of all provided wind efficiency curves.
     smoothing : boolean
         If True the power curves will be smoothed before or after the
         aggregation of power curves depending on `smoothing_order`.
         Default: False.
     block_width : float
         Width between the wind speeds in the sum of the equation in
-        :py:func:`~.power_curves.smooth_power_curve`:. Default: 0.5.
+        :py:func:`~.power_curves.smooth_power_curve`. Default: 0.5.
     standard_deviation_method : string
         Method for calculating the standard deviation for the Gauss
         distribution. Options: 'turbulence_intensity', 'Staffell_Pfenninger'.

windpowerlib/wind_farm.py

@@ -122,7 +122,7 @@ def get_installed_power(self):
         The installed power of wind farms is necessary when a
         :class:`~.wind_turbine_cluster.WindTurbineCluster` object is used and
         is power weighed mean hub height is calcuated with
-        :py:func:`~.wind_turbine_cluster.WindTurbineCluster.mean_hub_height`:.
+        :py:func:`~.wind_turbine_cluster.WindTurbineCluster.mean_hub_height`.
 
         Returns
         -------
@@ -162,7 +162,7 @@ def assign_power_curve(self, wake_losses_model='power_efficiency_curve',
             Default: False.
         block_width : float
             Width between the wind speeds in the sum of the equation in
-            :py:func:`~.power_curves.smooth_power_curve`:. Default: 0.5.
+            :py:func:`~.power_curves.smooth_power_curve`. Default: 0.5.
         standard_deviation_method : string
             Method for calculating the standard deviation for the Gauss
             distribution. Options: 'turbulence_intensity',

windpowerlib/wind_turbine_cluster.py

@@ -135,7 +135,7 @@ def assign_power_curve(self, wake_losses_model='power_efficiency_curve',
             Default: False.
         block_width : float
             Width between the wind speeds in the sum of the equation in
-            :py:func:`~.power_curves.smooth_power_curve`:. Default: 0.5.
+            :py:func:`~.power_curves.smooth_power_curve`. Default: 0.5.
         standard_deviation_method : string
             Method for calculating the standard deviation for the Gauss
             distribution. Options: 'turbulence_intensity',