Merge branch 'documentation_changes' into dev

SabineHaas · SabineHaas · commit 97b1e12588f4 · 2019-01-15T15:03:51.000+01:00
diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
@@ -1 +1,7 @@
-Contributor Agreement
+Fixes # .
+
+Changes proposed in this pull request:
+-
+-
+-
+
diff --git a/doc/getting_started.rst b/doc/getting_started.rst
@@ -44,7 +44,7 @@ Matplotlib can be installed using pip3 though some Linux users reported that it
 Examples and basic usage
 =========================
 
-The basic usage of the windpowerlib is shown in the :ref:`modelchain_example <modelchain_example_notebook.ipynb>`. The presented example is available as jupyter notebook and python script. You can download them along with example weather data:
+The basic usage of the windpowerlib is shown in the ModelChain example. The presented example is available as jupyter notebook and python script. You can download them along with example weather data:
 
  * :download:`ModelChain example (Python script) <../example/modelchain_example.py>`
  * :download:`ModelChain example (Jupyter notebook) <../example/modelchain_example.ipynb>`
diff --git a/doc/model_description.rst b/doc/model_description.rst
@@ -22,8 +22,8 @@ correction of weather data.
 
 Functions for the height correction of wind speed to the hub height of a wind turbine are described in the
 :ref:`windspeedmodule-label` module. Respectively a function for the height correction of temperature data is provided in the
-:ref:`temperature_module_label`. Functions for density calculations can be found in the
-:ref:`density_module_label`
+:ref:`temperature_module_label` module. Functions for density calculations can be found in the
+:ref:`density_module_label` module.
 
 If weather data is available for at least two different heights the respective figure at hub height
 can be determined by using linear or logarithmic inter-/extrapolation functions of the :ref:`tools_module_label` module.
@@ -55,7 +55,7 @@ mean wind efficiency curve.
    :align: center
 
 The second option of considering wake losses is applying them to power curves by reducing the power values
-by a constant or a wind speed depending wind farm efficiency (see :py:func:`~.wake_losses_to_power_curve`).
+by a constant or on a wind speed depending wind farm efficiency (see :py:func:`~.wake_losses_to_power_curve`).
 Applying the wind farm efficiency (curve) to power curves instead of to feed-in time series has the advantage that the
 power curves can further be aggregated to achieve turbine cluster power curves (see :py:class:`~.wind_turbine_cluster.WindTurbineCluster`).
 
@@ -75,4 +75,4 @@ of the windpowerlib can be selected. For parameters not being specified default
 The :ref:`modelchain_module_label` is a model
 to determine the output of a wind turbine while the :ref:`tc_modelchain_module_label` is a model to determine
 the output of a wind farm or wind turbine cluster.
-The usage of both modelchains is shown in the :ref:`example_section_label` section.
+The usage of both modelchains is shown in the :ref:`examples_section_label` section.
diff --git a/doc/modules.rst b/doc/modules.rst
@@ -169,7 +169,7 @@ Methods of the ModelChain object.
    modelchain.ModelChain.temperature_hub
    modelchain.ModelChain.density_hub
    modelchain.ModelChain.wind_speed_hub
-   modelchain.ModelChain.turbine_power_output
+   modelchain.ModelChain.calculate_power_output
 
 .. _tc_modelchain_module_label:
 
@@ -199,7 +199,7 @@ Methods of the TurbineClusterModelChain object.
    turbine_cluster_modelchain.TurbineClusterModelChain.temperature_hub
    turbine_cluster_modelchain.TurbineClusterModelChain.density_hub
    turbine_cluster_modelchain.TurbineClusterModelChain.wind_speed_hub
-   turbine_cluster_modelchain.TurbineClusterModelChain.turbine_power_output
+   turbine_cluster_modelchain.TurbineClusterModelChain.calculate_power_output
 
 
 .. _tools_module_label:
diff --git a/doc/whatsnew/v0-1-0.txt b/doc/whatsnew/v0-1-0.txt
@@ -1,4 +1,4 @@
-v0.1.0 (expected January 16, 2019)
+v0.1.0 (January 16, 2019)
 ++++++++++++++++++++++++++++++++++
 
 New classes
diff --git a/example/modelchain_example.py b/example/modelchain_example.py
@@ -261,7 +261,7 @@ def plot_or_print(my_turbine, e126, dummy_turbine):
 
 def run_example():
     r"""
-    Run the basic example.
+    Runs the basic example.
 
     """
     weather = get_weather_data('weather.csv')
diff --git a/example/turbine_cluster_modelchain_example.py b/example/turbine_cluster_modelchain_example.py
@@ -208,7 +208,7 @@ def plot_or_print(example_farm, example_cluster):
 
 def run_example():
     r"""
-    Run the example.
+    Runs the example.
 
     """
     weather = mc_e.get_weather_data('weather.csv')
diff --git a/windpowerlib/power_curves.py b/windpowerlib/power_curves.py
@@ -73,8 +73,8 @@ def smooth_power_curve(power_curve_wind_speeds, power_curve_values,
 
         :math:`P_{smoothed}` is the smoothed power curve value,
         :math:`v_{std}` is the standard wind speed in the power curve,
-        :math: `\Delta v_i` is the interval length between
-        :math: `v_\text{i}` and :math: `v_\text{i+1}`
+        :math:`\Delta v_i` is the interval length between
+        :math:`v_\text{i}` and :math:`v_\text{i+1}`
 
     Power curve smoothing is applied to take account for the spatial
     distribution of wind speed. This way of smoothing power curves is also used
diff --git a/windpowerlib/power_output.py b/windpowerlib/power_output.py
@@ -182,6 +182,7 @@ def power_curve_density_correction(wind_speed, power_curve_wind_speeds,
                       \text{ m/s}<v_{std}<12.5\text{ m/s}\\
                       \frac{2}{3} & \geq 12.5 \text{ m/s}
                     \end{cases},
+
         v: wind speed [m/s], :math:`\rho`: density [kg/m³]
 
     :math:`v_{std}` is the standard wind speed in the power curve
diff --git a/windpowerlib/tools.py b/windpowerlib/tools.py
@@ -158,7 +158,7 @@ def gauss_distribution(function_variable, standard_deviation, mean=0):
                      \left[-\frac{(x-\mu)^2}{2 \sigma^2}\right]
 
     with:
-        :math:`\sigma`: standard deviation, :math: `\mu`: mean
+        :math:`\sigma`: standard deviation, :math:`\mu`: mean
 
     References
     ----------
diff --git a/windpowerlib/wake_losses.py b/windpowerlib/wake_losses.py
@@ -98,14 +98,15 @@ def get_wind_efficiency_curve(curve_name='all'):
 
     Examples
     --------
-    # Example to plot all curves
-    fig, ax = plt.subplots()
-    df = get_wind_efficiency_curve(curve_name='all')
-    for t in df.columns.get_level_values(0).unique():
-        p = df[t].set_index('wind_speed')['efficiency']
-        p.name = t
-        ax = p.plot(ax=ax, legend=True)
-    plt.show()
+    .. parsed-literal::
+        # Example to plot all curves
+        fig, ax = plt.subplots() /n
+        df = get_wind_efficiency_curve(curve_name='all')
+        for t in df.columns.get_level_values(0).unique():
+            p = df[t].set_index('wind_speed')['efficiency']
+            p.name = t
+            ax = p.plot(ax=ax, legend=True)
+        plt.show()
 
     """
     possible_curve_names = ['dena_mean', 'knorr_mean', 'dena_extreme1',
diff --git a/windpowerlib/wind_farm.py b/windpowerlib/wind_farm.py
@@ -112,6 +112,7 @@ def mean_hub_height(self):
         Notes
         -----
         The following equation is used [1]_:
+
         .. math:: h_{WF} = e^{\sum\limits_{k}{ln(h_{WT,k})}
                            \frac{P_{N,k}}{\sum\limits_{k}{P_{N,k}}}}
 
diff --git a/windpowerlib/wind_turbine_cluster.py b/windpowerlib/wind_turbine_cluster.py
@@ -17,6 +17,7 @@
 
 class WindTurbineCluster(object):
     r"""
+    Defines a standard set of wind turbine cluster attributes.
 
     Parameters
     ----------
@@ -74,6 +75,7 @@ def mean_hub_height(self):
         Notes
         -----
         The following equation is used [1]_:
+
         .. math:: h_{WTC} = e^{\sum\limits_{k}{ln(h_{WF,k})}
                            \frac{P_{N,k}}{\sum\limits_{k}{P_{N,k}}}}
 

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-v0.1.0 (expected January 16, 2019)`
	`1`	`+v0.1.0 (January 16, 2019)`
`2`	`2`	`++++++++++++++++++++++++++++++++++`
`3`	`3`
`4`	`4`	`New classes`