Merge pull request #85 from NREL/develop

Merge develop into main

.codecov.yml

@@ -1,9 +1,12 @@
 # Codecov configuration file
 
+comment: false
+
 coverage:
     range: 0..100  # sets the range for the color bar in the dashboard
     round: down
     precision: 2
 
 ignore:
-    - "setup.py"
+    - "setup.py"
+    - "tests/"

.github/workflows/continuous-integration-workflow.yaml

@@ -6,10 +6,12 @@ name: Python package
 on:
   push:
     paths-ignore:
+      - 'AUTHORS.rst'
       - 'LICENSE.txt'
+      - 'NOTICE.txt'
       - 'README.rst'
       - 'docs/**'
-      - 'examples/**'
+      - 'examples*/**'
   pull_request:
     types: [opened, synchronize, edited, reopened]
 
@@ -20,8 +22,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9"]
-        os: [ubuntu-latest, macos-latest]
+        python-version: ["3.9", "3.10"]
+        os: [ubuntu-latest]
 
     steps:
     - uses: actions/checkout@v2
@@ -33,14 +35,14 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements.txt
-    - name: Test with pytest
-      run: |
-        pytest
     - name: Run tests and collect coverage
       run: |
         pip install pytest-cov
         pytest --cov=./ --cov-report=xml
     - name: Upload coverage to Codecov  
-      uses: codecov/codecov-action@v2
+      uses: codecov/codecov-action@v3
       with:
-        fail_ci_if_error: true
+        token: ${{ secrets.CODECOV_TOKEN }}
+        files: ./coverage.xml
+        fail_ci_if_error: true
+

.gitignore

@@ -24,4 +24,7 @@ _build
 *.png
 
 # Documentation build files
-docs/build
+docs/build
+SMARTEOLE_WakeSteering_ReadMe.xlsx
+SMARTEOLE_WakeSteering_Map.pdf
+SMARTEOLE-WFC-open-dataset.zip

docs/source/data_analysis.rst

@@ -156,7 +156,7 @@ allows the user to compare, for example, FLORIS model predictions to SCADA
 data. Different instantiations of the FLORIS model can be analyzed by creating
 multiple dataframes and all inserting them into the suite object using the
 function ``add_df()``. An example of this usage is shown in
-``a_08_plot_energy_ratios.py`` in the ``examples/raw_data_processing/``
+``a_08_plot_energy_ratios.py`` in the ``examples_artificial_data/raw_data_processing/``
 folder.
 
 
@@ -171,7 +171,7 @@ showcasing the energy ratios under various inflow conditions and in different
 bins. Continuing on the example of the previous section, a user can generate
 such an Excel file using the ``fsc.export_detailed_energy_info_to_xlsx()``
 function. Usage of this function is exemplified in
-``energy_table_for_two_df.py``, in the folder ``examples/table_analysis/``.
+``energy_table_for_two_df.py``, in the folder ``examples_artificial_data/table_analysis/``.
 The function produces an Excel sheet which looks as follows:
 
 .. image:: images/example_table_analysis.png

docs/source/data_processing.rst

@@ -99,7 +99,7 @@ Data filtering
 
 With the SCADA data now in a wide-formatted Pandas DataFrame, the flasc
 data filtering tools can readily be applied. The files in 
-``examples/raw_data_processing`` demonstrate how the SCADA data files are
+``examples_artifical_data/raw_data_processing`` demonstrate how the SCADA data files are
 processed.
 
 ++++++++++++++++++++++++

docs/source/getting_started.rst

@@ -11,7 +11,7 @@ Install the repository following the instructions `here <installation.html>`_.
 Generating an artificial dataset
 ================================
 You can generate a demo dataset using the script at
-``examples/demo_dataset/``. The script ``generate_demo_dataset.py`` downloads
+``examples_artificial_data/demo_dataset/``. The script ``generate_demo_dataset.py`` downloads
 historical data from a meteorological measurement tower at the U.S. National
 Wind Technology Center (NWTC), part of the National Renewable Energy
 Laboratory (NREL). This data is made readily available to the public on its

examples/demo_dataset/generate_demo_dataset.py → examples_artificial_data/demo_dataset/generate_demo_dataset.py

@@ -104,8 +104,9 @@ def get_wind_data_from_nwtc():
         df_approx = ftls.calc_floris_approx_table(
             fi=fi,
             wd_array=np.arange(0.0, 360.0, 3.0),
-            ws_array=np.arange(0.0, 27.0, 1.0),
+            ws_array=np.arange(0.001, 27.0, 1.0),
             ti_array=np.arange(0.03, 0.30, 0.03),
+            save_turbine_inflow_conditions_to_df=True
         )
         df_approx.to_feather(fn_approx)
 

examples/energy_ratio/energy_ratio_in_turbine_array.py → examples_artificial_data/energy_ratio/energy_ratio_in_turbine_array.py

@@ -32,7 +32,7 @@ def load_data():
         root_dir, '..', 'demo_dataset', 'demo_dataset_scada_60s.ftr'
     )
     if not os.path.exists(ftr_path):
-        raise FileNotFoundError('Please run ./examples/demo_dataset/' +
+        raise FileNotFoundError('Please run ./examples_artifical/demo_dataset/' +
                                 'generate_demo_dataset.py before try' +
                                 'ing any of the other examples.')
     df = pd.read_feather(ftr_path)

examples/energy_ratio/energy_ratio_vs_wd_for_multiple_dfs.py → examples_artificial_data/energy_ratio/energy_ratio_vs_wd_for_multiple_dfs.py

@@ -30,7 +30,7 @@ def load_data():
     ftr_path = os.path.join(root_dir, '..', 'demo_dataset',
                             'demo_dataset_scada_60s.ftr')
     if not os.path.exists(ftr_path):
-        raise FileNotFoundError('Please run ./examples/demo_dataset/' +
+        raise FileNotFoundError('Please run ./examples_artificial_data/demo_dataset/' +
                                 'generate_demo_dataset.py before try' +
                                 'ing any of the other examples.')
     df = pd.read_feather(ftr_path)
@@ -122,4 +122,5 @@ def load_floris():
         percentiles=[5., 95.],
         verbose=False)
     fsc.plot_energy_ratios(superimpose=True)
+    fsc.plot_energy_ratios(superimpose=True, polar_plot=True)  # Also show in a polar plot
     plt.show()

examples/energy_ratio/energy_ratio_vs_wd_for_single_df.py → examples_artificial_data/energy_ratio/energy_ratio_vs_wd_for_single_df.py

@@ -28,7 +28,7 @@ def load_data():
     ftr_path = os.path.join(root_dir, '..', 'demo_dataset',
                             'demo_dataset_scada_60s.ftr')
     if not os.path.exists(ftr_path):
-        raise FileNotFoundError('Please run ./examples/demo_dataset/' +
+        raise FileNotFoundError('Please run ./examples_artificial_data/demo_dataset/' +
                                 'generate_demo_dataset.py before try' +
                                 'ing any of the other examples.')
     df = pd.read_feather(ftr_path)
@@ -89,25 +89,45 @@ def load_floris():
         test_turbines=[1],
         wd_step=2.0,
         ws_step=1.0,
-        wd_bin_width=3.0,
+        wd_bin_width=2.0,
     )
     fig, ax = era.plot_energy_ratio()
     ax[0].set_title("Energy ratios for turbine 001 without UQ")
     plt.tight_layout()
 
+    fig, ax = era.plot_energy_ratio(polar_plot=True)  # Plot in polar format too
+    ax[0].set_title("Energy ratios for turbine 001 without UQ")
+    plt.tight_layout()
+
     # Get energy ratio with uncertainty quantification
     # using N=50 bootstrap samples and 5-95 percent conf. bounds.
     era.get_energy_ratio(
         test_turbines=[1],
         wd_step=2.0,
         ws_step=1.0,
-        wd_bin_width=3.0,
-        N=50,
+        wd_bin_width=2.0,
+        N=20,
         percentiles=[5.0, 95.0]
     )
     fig, ax = era.plot_energy_ratio()
     ax[0].set_title("Energy ratios for turbine 001 with UQ "
-                    + "(N=50, 90% confidence interval)")
+                    + "(N=20, 90% confidence interval)")
+    plt.tight_layout()
+
+    # Get energy ratio with uncertainty quantification
+    # using N=10 bootstrap samples and block bootstrapping
+    era.get_energy_ratio(
+        test_turbines=[1],
+        wd_step=2.0,
+        ws_step=1.0,
+        wd_bin_width=2.0,
+        N=20,
+        percentiles=[5.0, 95.0],
+        num_blocks=20 # Resample over 20 blocks
+    )
+    fig, ax = era.plot_energy_ratio()
+    ax[0].set_title("Energy ratios for turbine 001 with UQ "
+                    + "(N=20, Block Bootstrapping)")
     plt.tight_layout()
 
     plt.show()

examples/energy_ratio/estimate_heterogeneity_from_energy_ratios.py → examples_artificial_data/energy_ratio/estimate_heterogeneity_from_energy_ratios.py

@@ -18,7 +18,7 @@ def load_data():
         root_dir, '..', 'demo_dataset', 'demo_dataset_scada_60s.ftr'
     )
     if not os.path.exists(ftr_path):
-        raise FileNotFoundError('Please run ./examples/demo_dataset/' +
+        raise FileNotFoundError('Please run ./examples_artificial_data/demo_dataset/' +
                                 'generate_demo_dataset.py before try' +
                                 'ing any of the other examples.')
     df = pd.read_feather(ftr_path)