Feature: Add external library functionality

.pre-commit-config.yaml

@@ -1,13 +1,13 @@
 repos:
 -   repo: https://github.com/timothycrosley/isort
-    rev: 5.10.1
+    rev: 5.12.0
     hooks:
         - id: isort
           name: isort
           stages: [commit]
 
 -   repo: https://github.com/psf/black
-    rev: 22.6.0
+    rev: 23.1.0
     hooks:
         - id: black
           name: black
@@ -23,7 +23,7 @@ repos:
 #           args: [--no-strict-optional, --ignore-missing-imports]
 
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
+    rev: v4.4.0
     hooks:
     -   id: trailing-whitespace
     -   id: end-of-file-fixer
@@ -37,7 +37,7 @@ repos:
         args: [--autofix]
 
 -   repo: https://github.com/pycqa/flake8
-    rev: '4.0.1'
+    rev: '6.0.0'
     hooks:
     -   id: flake8
         args: [--max-line-length=120]

docs/dev_guide.md

@@ -58,31 +58,6 @@ to fit a specific use case or purpose. If significant development has
 happened locally, then [merge conflicts](https://www.atlassian.com/git/tutorials/using-branches/merge-conflicts)
 are likely and should be resolved as early as possible.
 
-
-## Code quality tools
-
-FLORIS is configured to use tools to automatically check and enforce
-aspects of code quality. In general, these should be adopted by all
-developers and incorporated into the development workflow. Most
-tools are configured in [pyproject.toml](https://github.com/NREL/floris/blob/main/pyproject.toml),
-but some may have a dedicated configuration file.
-
-### isort
-
-Import lines can easily get out of hand and cause unnecessary distraction
-in source code files. [isort](https://pycqa.github.io/isort/index.html)
-it used to automatically manage imports in the source code. It can be run
-directly with the following command:
-
-```bash
-isort <path to file>
-isort dir/*
-```
-
-This tool was initially configured in [#535](https://github.com/NREL/floris/pull/535),
-and additional information on specific decisions can be found there.
-
-
 ## Testing
 
 In order to maintain a level of confidence in the software, FLORIS is expected

docs/examples.md

@@ -86,10 +86,6 @@ impact on wind turbine wakes.
 Load an input file that describes a wind farm with two turbines
 of different types and plot the wake profiles.
 
-### 23_visualize_layout.py
-Use the visualize_layout function to provide diagram visualization
-of a turbine layout within FLORIS
-
 
 ## Optimization
 
@@ -112,12 +108,6 @@ Construct wind farm yaw settings for a full wind rose based on the
 optimized yaw settings at a single wind speed. Then, compare
 results to the baseline no-yaw configuration.
 
-### 12_optimize_yaw_in_parallel.py
-Comparable to the above but perform all the computations using
-parallel processing. In the current example, use 16 cores
-simultaneously to calculate the AEP and perform a wake steering
-yaw angle optimization for multiple wind speeds.
-
 ### 13_optimize_yaw_with_neighboring_farm.py
 Same as above but considering the effects of a nearby wind farm.
 

examples/01_opening_floris_computing_power.py

@@ -13,11 +13,11 @@
 # See https://floris.readthedocs.io for documentation
 
 
+import matplotlib.pyplot as plt
 import numpy as np
 
 from floris.tools import FlorisInterface
 
-
 """
 This example creates a FLORIS instance
 1) Makes a two-turbine layout

examples/02_visualizations.py

@@ -15,9 +15,9 @@
 
 import matplotlib.pyplot as plt
 
-import floris.tools.visualization as wakeviz
 from floris.tools import FlorisInterface
-
+from floris.tools.visualization import visualize_cut_plane
+from floris.tools.visualization import plot_rotor_values
 
 """
 This example initializes the FLORIS software, and then uses internal
@@ -52,9 +52,9 @@
 # Create the plots
 fig, ax_list = plt.subplots(3, 1, figsize=(10, 8))
 ax_list = ax_list.flatten()
-wakeviz.visualize_cut_plane(horizontal_plane, ax=ax_list[0], title="Horizontal")
-wakeviz.visualize_cut_plane(y_plane, ax=ax_list[1], title="Streamwise profile")
-wakeviz.visualize_cut_plane(cross_plane, ax=ax_list[2], title="Spanwise profile")
+visualize_cut_plane(horizontal_plane, ax=ax_list[0], title="Horizontal")
+visualize_cut_plane(y_plane, ax=ax_list[1], title="Streamwise profile")
+visualize_cut_plane(cross_plane, ax=ax_list[2], title="Spanwise profile")
 
 # FLORIS further includes visualization methods for visualing the rotor plane of each
 # Turbine in the simulation
@@ -64,7 +64,7 @@
 fi.calculate_wake()
 
 # Plot the values at each rotor
-fig, axes, _ , _ = wakeviz.plot_rotor_values(fi.floris.flow_field.u, wd_index=0, ws_index=0, n_rows=1, n_cols=3, return_fig_objects=True)
+fig, axes, _ , _ = plot_rotor_values(fi.floris.flow_field.u, wd_index=0, ws_index=0, n_rows=1, n_cols=3, return_fig_objects=True)
 fig.suptitle("Rotor Plane Visualization, Original Resolution")
 
 # FLORIS supports multiple types of grids for capturing wind speed
@@ -86,7 +86,7 @@
 fi.calculate_wake()
 
 # Plot the values at each rotor
-fig, axes, _ , _ = wakeviz.plot_rotor_values(fi.floris.flow_field.u, wd_index=0, ws_index=0, n_rows=1, n_cols=3, return_fig_objects=True)
+fig, axes, _ , _ = plot_rotor_values(fi.floris.flow_field.u, wd_index=0, ws_index=0, n_rows=1, n_cols=3, return_fig_objects=True)
 fig.suptitle("Rotor Plane Visualization, 10x10 Resolution")
 
-wakeviz.show_plots()
+plt.show()

examples/03_making_adjustments.py

@@ -16,9 +16,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-import floris.tools.visualization as wakeviz
 from floris.tools import FlorisInterface
-
+from floris.tools import visualize_cut_plane #, plot_turbines_with_fi
 
 """
 This example makes changes to the given input file through the script.
@@ -39,53 +38,53 @@
 
 # Plot a horizatonal slice of the initial configuration
 horizontal_plane = fi.calculate_horizontal_plane(height=90.0)
-wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[0], title="Initial setup", min_speed=MIN_WS, max_speed=MAX_WS)
+visualize_cut_plane(horizontal_plane, ax=axarr[0], title="Initial setup", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+
 
 # Change the wind speed
 horizontal_plane = fi.calculate_horizontal_plane(ws=[7.0], height=90.0)
-wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[1], title="Wind speed at 7 m/s", min_speed=MIN_WS, max_speed=MAX_WS)
+visualize_cut_plane(horizontal_plane, ax=axarr[1], title="Wind speed at 7 m/s", minSpeed=MIN_WS, maxSpeed=MAX_WS)
 
 
 # Change the wind shear, reset the wind speed, and plot a vertical slice
 fi.reinitialize( wind_shear=0.2, wind_speeds=[8.0] )
 y_plane = fi.calculate_y_plane(crossstream_dist=0.0)
-wakeviz.visualize_cut_plane(y_plane, ax=axarr[2], title="Wind shear at 0.2", min_speed=MIN_WS, max_speed=MAX_WS)
+visualize_cut_plane(y_plane, ax=axarr[2], title="Wind shear at 0.2", minSpeed=MIN_WS, maxSpeed=MAX_WS)
 
 
-# # Change the farm layout
+# Change the farm layout
 N = 3  # Number of turbines per row and per column
 X, Y = np.meshgrid(
     5.0 * fi.floris.farm.rotor_diameters[0][0][0] * np.arange(0, N, 1),
     5.0 * fi.floris.farm.rotor_diameters[0][0][0] * np.arange(0, N, 1),
 )
-fi.reinitialize(layout_x=X.flatten(), layout_y=Y.flatten(), wind_directions=[360.0])
+fi.reinitialize(layout_x=X.flatten(), layout_y=Y.flatten())
 horizontal_plane = fi.calculate_horizontal_plane(height=90.0)
-wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[3], title="3x3 Farm", min_speed=MIN_WS, max_speed=MAX_WS)
-wakeviz.add_turbine_id_labels(fi, axarr[3], color="w", backgroundcolor="k")
-wakeviz.plot_turbines_with_fi(fi, axarr[3])
+visualize_cut_plane(horizontal_plane, ax=axarr[3], title="3x3 Farm", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+
 
 # Change the yaw angles and configure the plot differently
 yaw_angles = np.zeros((1, 1, N * N))
 
 ## First row
 yaw_angles[:,:,0] = 30.0
-yaw_angles[:,:,3] = -30.0
-yaw_angles[:,:,6] = 30.0
+yaw_angles[:,:,1] = -30.0
+yaw_angles[:,:,2] = 30.0
 
 ## Second row
-yaw_angles[:,:,1] = -30.0
+yaw_angles[:,:,3] = -30.0
 yaw_angles[:,:,4] = 30.0
-yaw_angles[:,:,7] = -30.0
+yaw_angles[:,:,5] = -30.0
 
 horizontal_plane = fi.calculate_horizontal_plane(yaw_angles=yaw_angles, height=90.0)
-wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[4], title="Yawesome art", cmap="PuOr", min_speed=MIN_WS, max_speed=MAX_WS)
-wakeviz.plot_turbines_with_fi(fi, axarr[4], yaw_angles=yaw_angles, color="c")
+visualize_cut_plane(horizontal_plane, ax=axarr[4], title="Yawesome art", cmap="PuOr", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+# plot_turbines_with_fi(axarr[8], fi)
 
 
 # Plot the cross-plane of the 3x3 configuration
 cross_plane = fi.calculate_cross_plane(yaw_angles=yaw_angles, downstream_dist=610.0)
-wakeviz.visualize_cut_plane(cross_plane, ax=axarr[5], title="Cross section at 610 m", min_speed=MIN_WS, max_speed=MAX_WS)
+visualize_cut_plane(cross_plane, ax=axarr[5], title="Cross section at 610 m", minSpeed=MIN_WS, maxSpeed=MAX_WS)
 axarr[5].invert_xaxis()
 
 
-wakeviz.show_plots()
+plt.show()

examples/04_sweep_wind_directions.py

@@ -17,6 +17,7 @@
 import numpy as np
 
 from floris.tools import FlorisInterface
+from floris.tools.visualization import visualize_cut_plane
 
 
 """
@@ -71,5 +72,4 @@
 ax.legend()
 ax.set_xlabel('Wind Direction (deg)')
 ax.set_ylabel('Power (kW)')
-
 plt.show()

examples/05_sweep_wind_speeds.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from floris.tools import FlorisInterface
-
+from floris.tools.visualization import visualize_cut_plane
 
 """
 05_sweep_wind_speeds

examples/06_sweep_wind_conditions.py

@@ -13,12 +13,12 @@
 # See https://floris.readthedocs.io for documentation
 
 
+import enum
 import matplotlib.pyplot as plt
 import numpy as np
 
 from floris.tools import FlorisInterface
 
-
 """
 06_sweep_wind_conditions
 

examples/07_calc_aep_from_rose.py

@@ -16,10 +16,8 @@
 import numpy as np
 import pandas as pd
 from scipy.interpolate import NearestNDInterpolator
-
 from floris.tools import FlorisInterface
 
-
 """
 This example demonstrates how to calculate the Annual Energy Production (AEP)
 of a wind farm using wind rose information stored in a .csv file.

examples/08_calc_aep_from_rose_use_class.py

@@ -12,15 +12,12 @@
 
 # See https://floris.readthedocs.io for documentation
 
-import numpy as np
-
-import floris.tools.visualization as wakeviz
-from floris.tools import (
-    FlorisInterface,
-    wind_rose,
-    WindRose
-)
 
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from scipy.interpolate import NearestNDInterpolator
+from floris.tools import FlorisInterface, WindRose, wind_rose
 
 """
 This example demonstrates how to calculate the Annual Energy Production (AEP)
@@ -47,8 +44,7 @@
 # floris object and assign the layout, wind speed and wind direction arrays.
 D = 126.0 # Rotor diameter for the NREL 5 MW
 fi.reinitialize(
-    layout_x=[0.0, 5* D, 10 * D],
-    layout_y=[0.0, 0.0, 0.0],
+    layout=[[0.0, 5* D, 10 * D], [0.0, 0.0, 0.0]]
 )
 
 # Compute the AEP using the default settings
@@ -68,19 +64,11 @@
 )
 print("Farm AEP (with cut_in/out specified): {:.3f} GWh".format(aep / 1.0e9))
 
-# Compute the AEP a final time, this time marking one of the turbines as 
-# belonging to another farm by setting its weight to 0
-turbine_weights = np.array([1.0, 1.0, 0.0])
-aep = fi.get_farm_AEP_wind_rose_class(
-    wind_rose=wind_rose,
-    turbine_weights= turbine_weights
-)
-print("Farm AEP (one turbine removed from power calculation): {:.3f} GWh".format(aep / 1.0e9))
-
 # Finally, we can also compute the AEP while ignoring all wake calculations.
 # This can be useful to quantity the annual wake losses in the farm. Such
 # calculations can be facilitated by enabling the 'no_wake' handle.
 aep_no_wake = fi.get_farm_AEP_wind_rose_class(wind_rose=wind_rose, no_wake=True)
 print("Farm AEP (no_wake=True): {:.3f} GWh".format(aep_no_wake / 1.0e9))
 
-wakeviz.show_plots()
+
+plt.show()

examples/09_compare_farm_power_with_neighbor.py

@@ -13,11 +13,10 @@
 # See https://floris.readthedocs.io for documentation
 
 
-import matplotlib.pyplot as plt
 import numpy as np
-
+import pandas as pd
 from floris.tools import FlorisInterface
-
+import matplotlib.pyplot as plt
 
 """
 This example demonstrates how to use turbine_wieghts to define a set of turbines belonging to a neighboring farm which

examples/10_opt_yaw_single_ws.py

@@ -12,12 +12,12 @@
 
 # See https://floris.readthedocs.io for documentation
 
-import matplotlib.pyplot as plt
 import numpy as np
-
+import matplotlib.pyplot as plt
 from floris.tools import FlorisInterface
-from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import YawOptimizationSR
-
+from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import (
+    YawOptimizationSR,
+)
 
 """
 This example demonstrates how to perform a yaw optimization for multiple wind directions and 1 wind speed.

examples/11_opt_yaw_multiple_ws.py

@@ -12,12 +12,12 @@
 
 # See https://floris.readthedocs.io for documentation
 
-import matplotlib.pyplot as plt
 import numpy as np
-
+import matplotlib.pyplot as plt
 from floris.tools import FlorisInterface
-from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import YawOptimizationSR
-
+from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import (
+    YawOptimizationSR,
+)
 
 """
 This example demonstrates how to perform a yaw optimization for multiple wind directions and multiple wind speeds.

examples/12_optimize_yaw.py

@@ -14,14 +14,13 @@
 
 
 from time import perf_counter as timerpc
-
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-
 from floris.tools import FlorisInterface
-from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import YawOptimizationSR
-
+from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import (
+    YawOptimizationSR,
+)
 
 """
 This example demonstrates how to perform a yaw optimization and evaluate the performance over a full wind rose.