Merge dev to solve merge conflicts

Author: uvchik

.stickler.yml

@@ -0,0 +1,12 @@
+linters:
+    flake8:
+      python: 3
+      max-line-length: 79
+      select: C,E,F,W,B,B950
+      ignore: E203, E501, W503
+    black:
+      config: ./pyproject.toml
+      fixer: true
+
+fixers:
+    enable: true

.travis.yml

@@ -5,8 +5,7 @@ matrix:
     - python: 3.5
     - python: 3.6
     - python: 3.7
-      dist: xenial
-      sudo: true
+    - python: 3.8
 
 # command to install dependencies
 #before_install:

README.rst

@@ -4,6 +4,8 @@
     :target: https://coveralls.io/github/wind-python/windpowerlib?branch=dev
 .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.824267.svg
    :target: https://doi.org/10.5281/zenodo.824267
+.. image:: https://mybinder.org/badge_logo.svg
+ :target: https://mybinder.org/v2/gh/wind-python/windpowerlib/dev?filepath=example
 
 Introduction
 =============
@@ -50,26 +52,28 @@ Matplotlib can be installed using pip:
 Examples and basic usage
 =========================
 
+The simplest way to run the example notebooks without installing windpowerlib is to click `here <https://mybinder.org/v2/gh/wind-python/windpowerlib/dev?filepath=example>`_ and open them with Binder.
+
 The basic usage of the windpowerlib is shown in the `ModelChain example <http://windpowerlib.readthedocs.io/en/stable/modelchain_example_notebook.html>`_ that is available as jupyter notebook and python script:
 
- * `ModelChain example (Python script) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/modelchain_example.py>`_
- * `ModelChain example (Jupyter notebook) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/modelchain_example.ipynb>`_
+* `ModelChain example (Python script) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/modelchain_example.py>`_
+* `ModelChain example (Jupyter notebook) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/modelchain_example.ipynb>`_
 
 To run the example you need the example weather and turbine data used:
 
- * `Example weather data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/weather.csv>`_
- * `Example power curve data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_power_curves.csv>`_
- * `Example power coefficient curve data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_power_coefficient_curves.csv>`_
- * `Example nominal power data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_turbine_data.csv>`_
+* `Example weather data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/weather.csv>`_
+* `Example power curve data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_power_curves.csv>`_
+* `Example power coefficient curve data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_power_coefficient_curves.csv>`_
+* `Example nominal power data file <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/data/example_turbine_data.csv>`_
 
-Furthermore, you have to install the windpowerlib. To run the notebook you also need to install `notebook` using pip3. To launch jupyter notebook type ``jupyter notebook`` in the terminal.
+To run the examples locally you have to install windpowerlib. To run the notebook you also need to install `notebook` using pip3. To launch jupyter notebook type ``jupyter notebook`` in the terminal.
 This will open a browser window. Navigate to the directory containing the notebook to open it. See the jupyter notebook quick start guide for more information on `how to install <http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/install.html>`_ and
-`how to run <http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html>`_ jupyter notebooks.
+`how to run <http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html>`_ jupyter notebooks. In order to reproduce the figures in a notebook you need to install `matplotlib`.
 
 Further functionalities, like the modelling of wind farms and wind turbine clusters, are shown in the `TurbineClusterModelChain example <http://windpowerlib.readthedocs.io/en/stable/turbine_cluster_modelchain_example_notebook.html>`_. As the ModelChain example it is available as jupyter notebook and as python script. The weather and turbine datadata used in this example is the same as in the example above.
 
- * `TurbineClusterModelChain example (Python script) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/turbine_cluster_modelchain_example.py>`_
- * `TurbineClusterModelChain example (Jupyter notebook) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/turbine_cluster_modelchain_example.ipynb>`_
+* `TurbineClusterModelChain example (Python script) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/turbine_cluster_modelchain_example.py>`_
+* `TurbineClusterModelChain example (Jupyter notebook) <https://raw.githubusercontent.com/wind-python/windpowerlib/master/example/turbine_cluster_modelchain_example.ipynb>`_
 
 You can also look at the examples in the `Examples section <http://windpowerlib.readthedocs.io/en/stable/examples.html>`_.
 
@@ -153,4 +157,4 @@ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+SOFTWARE.

example/modelchain_example.ipynb

@@ -139,11 +139,6 @@
     "    weather_df.index = pd.to_datetime(weather_df.index).tz_convert(\n",
     "        'Europe/Berlin')\n",
     "    \n",
-    "    # change type of height from str to int by resetting columns\n",
-    "    l0 = [_[0] for _ in weather_df.columns]\n",
-    "    l1 = [int(_[1]) for _ in weather_df.columns]\n",
-    "    weather_df.columns = [l0, l1]\n",
-    "    \n",
     "    return weather_df\n",
     "\n",
     "\n",

example/modelchain_example.py

@@ -64,24 +64,24 @@ def get_weather_data(filename='weather.csv', **kwargs):
 
     """
 
-    if 'datapath' not in kwargs:
-        kwargs['datapath'] = os.path.join(os.path.split(
-            os.path.dirname(__file__))[0], 'example')
-    file = os.path.join(kwargs['datapath'], filename)
+    if "datapath" not in kwargs:
+        kwargs["datapath"] = os.path.join(
+            os.path.split(os.path.dirname(__file__))[0], "example"
+        )
+    file = os.path.join(kwargs["datapath"], filename)
 
     # read csv file
     weather_df = pd.read_csv(
-        file, index_col=0, header=[0, 1],
-        date_parser=lambda idx: pd.to_datetime(idx, utc=True))
+        file,
+        index_col=0,
+        header=[0, 1],
+        date_parser=lambda idx: pd.to_datetime(idx, utc=True),
+    )
 
     # change type of index to datetime and set time zone
     weather_df.index = pd.to_datetime(weather_df.index).tz_convert(
-        'Europe/Berlin')
-
-    # change type of height from str to int by resetting columns
-    l0 = [_[0] for _ in weather_df.columns]
-    l1 = [int(_[1]) for _ in weather_df.columns]
-    weather_df.columns = [l0, l1]
+        "Europe/Berlin"
+    )
 
     return weather_df
 
@@ -112,33 +112,38 @@ def initialize_wind_turbines():
     # specification of wind turbine where data is provided in the oedb
     # turbine library
     enercon_e126 = {
-        'turbine_type': 'E-126/4200',  # turbine type as in register
-        'hub_height': 135  # in m
+        "turbine_type": "E-126/4200",  # turbine type as in register
+        "hub_height": 135,  # in m
     }
     # initialize WindTurbine object
     e126 = WindTurbine(**enercon_e126)
 
     # specification of own wind turbine (Note: power values and nominal power
     # have to be in Watt)
     my_turbine = {
-        'nominal_power': 3e6,  # in W
-        'hub_height': 105,  # in m
-        'power_curve': pd.DataFrame(
-            data={'value': [p * 1000 for p in [
-                      0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]],  # in W
-                  'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]})  # in m/s
+        "nominal_power": 3e6,  # in W
+        "hub_height": 105,  # in m
+        "power_curve": pd.DataFrame(
+            data={
+                "value": [
+                    p * 1000
+                    for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]
+                ],  # in W
+                "wind_speed": [0.0, 3.0, 5.0, 10.0, 15.0, 25.0],
+            }
+        ),  # in m/s
     }
     # initialize WindTurbine object
     my_turbine = WindTurbine(**my_turbine)
 
     # specification of wind turbine where power coefficient curve and nominal
     # power is provided in an own csv file
-    csv_path = os.path.join(os.path.dirname(__file__), 'data')
+    csv_path = os.path.join(os.path.dirname(__file__), "data")
     dummy_turbine = {
-        'turbine_type': "DUMMY 1",
-        'hub_height': 100,  # in m
-        'rotor_diameter': 70,  # in m
-        'path': csv_path
+        "turbine_type": "DUMMY 1",
+        "hub_height": 100,  # in m
+        "rotor_diameter": 70,  # in m
+        "path": csv_path,
     }
     # initialize WindTurbine object
     dummy_turbine = WindTurbine(**dummy_turbine)
@@ -182,18 +187,19 @@ def calculate_power_output(weather, my_turbine, e126, dummy_turbine):
     # power output calculation for e126
     # own specifications for ModelChain setup
     modelchain_data = {
-        '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'
-        '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
+        "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'
+        "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
     # initialize ModelChain with own specifications and use run_model method
     # to calculate power output
     mc_e126 = ModelChain(e126, **modelchain_data).run_model(weather)
@@ -203,8 +209,8 @@ def calculate_power_output(weather, my_turbine, e126, dummy_turbine):
     # power output calculation for example_turbine
     # own specification for 'power_output_model'
     mc_example_turbine = ModelChain(
-        dummy_turbine,
-        power_output_model='power_coefficient_curve').run_model(weather)
+        dummy_turbine, power_output_model="power_coefficient_curve"
+    ).run_model(weather)
     dummy_turbine.power_output = mc_example_turbine.power_output
 
     return
@@ -272,7 +278,7 @@ def run_example():
     Runs the basic example.
 
     """
-    weather = get_weather_data('weather.csv')
+    weather = get_weather_data("weather.csv")
     my_turbine, e126, dummy_turbine = initialize_wind_turbines()
     calculate_power_output(weather, my_turbine, e126, dummy_turbine)
     plot_or_print(my_turbine, e126, dummy_turbine)

example/test_examples.py

@@ -15,31 +15,45 @@
 
 
 class TestExamples:
-
     def test_modelchain_example_flh(self):
         # tests full load hours
-        weather = mc_e.get_weather_data('weather.csv')
+        weather = mc_e.get_weather_data("weather.csv")
         my_turbine, e126, dummy_turbine = mc_e.initialize_wind_turbines()
         mc_e.calculate_power_output(weather, my_turbine, e126, dummy_turbine)
 
-        assert_allclose(2764.194772, (e126.power_output.sum() /
-                                      e126.nominal_power), 0.01)
-        assert_allclose(1882.7567, (my_turbine.power_output.sum() /
-                                    my_turbine.nominal_power), 0.01)
+        assert_allclose(
+            2764.194772, (e126.power_output.sum() / e126.nominal_power), 0.01
+        )
+        assert_allclose(
+            1882.7567,
+            (my_turbine.power_output.sum() / my_turbine.nominal_power),
+            0.01,
+        )
 
     def test_turbine_cluster_modelchain_example_flh(self):
         # tests full load hours
-        weather = mc_e.get_weather_data('weather.csv')
+        weather = mc_e.get_weather_data("weather.csv")
         my_turbine, e126, dummy_turbine = mc_e.initialize_wind_turbines()
         example_farm, example_farm_2 = tc_mc_e.initialize_wind_farms(
-            my_turbine, e126)
+            my_turbine, e126
+        )
         example_cluster = tc_mc_e.initialize_wind_turbine_cluster(
-            example_farm, example_farm_2)
+            example_farm, example_farm_2
+        )
         tc_mc_e.calculate_power_output(weather, example_farm, example_cluster)
-        assert_allclose(1956.164053, (example_farm.power_output.sum() /
-                                      example_farm.nominal_power), 0.01)
-        assert_allclose(2156.794154, (example_cluster.power_output.sum() /
-                                      example_cluster.nominal_power), 0.01)
+        assert_allclose(
+            1956.164053,
+            (example_farm.power_output.sum() / example_farm.nominal_power),
+            0.01,
+        )
+        assert_allclose(
+            2156.794154,
+            (
+                example_cluster.power_output.sum()
+                / example_cluster.nominal_power
+            ),
+            0.01,
+        )
 
     def _notebook_run(self, path):
         """
@@ -49,30 +63,44 @@ def _notebook_run(self, path):
         dirname, __ = os.path.split(path)
         os.chdir(dirname)
         with tempfile.NamedTemporaryFile(suffix=".ipynb") as fout:
-            args = ["jupyter", "nbconvert", "--to", "notebook", "--execute",
-                    "--ExecutePreprocessor.timeout=60",
-                    "--output", fout.name, path]
+            args = [
+                "jupyter",
+                "nbconvert",
+                "--to",
+                "notebook",
+                "--execute",
+                "--ExecutePreprocessor.timeout=60",
+                "--output",
+                fout.name,
+                path,
+            ]
             subprocess.check_call(args)
 
             fout.seek(0)
             nb = nbformat.read(fout, nbformat.current_nbformat)
 
-        errors = [output for cell in nb.cells if "outputs" in cell
-                  for output in cell["outputs"]
-                  if output.output_type == "error"]
+        errors = [
+            output
+            for cell in nb.cells
+            if "outputs" in cell
+            for output in cell["outputs"]
+            if output.output_type == "error"
+        ]
 
         return nb, errors
 
     @pytest.mark.skipif(sys.version_info < (3, 6), reason="requires python3.6")
     def test_modelchain_example_ipynb(self):
         dir_path = os.path.dirname(os.path.realpath(__file__))
         nb, errors = self._notebook_run(
-            os.path.join(dir_path, 'modelchain_example.ipynb'))
+            os.path.join(dir_path, "modelchain_example.ipynb")
+        )
         assert errors == []
 
     @pytest.mark.skipif(sys.version_info < (3, 6), reason="requires python3.6")
     def test_turbine_cluster_modelchain_example_ipynb(self):
         dir_path = os.path.dirname(os.path.realpath(__file__))
         nb, errors = self._notebook_run(
-            os.path.join(dir_path, 'turbine_cluster_modelchain_example.ipynb'))
+            os.path.join(dir_path, "turbine_cluster_modelchain_example.ipynb")
+        )
         assert errors == []