Use FLORIS tools for layout visualizations

examples_artificial_data/00_setup_floris_model/00_visualize_layout.py

@@ -1,13 +1,8 @@
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import (
-    plot_floris_layout,
-    plot_layout_only,
-    plot_layout_with_waking_directions,
-    shade_region,
-)
 
 # Example demonstrates some methods for visualizing the layout of the farm
 # represented within the FLORIS interface
@@ -21,42 +16,59 @@
     # Defines alternative names for each turbine with 1-index
     turbine_names = ["Turbine-%d" % (t + 1) for t in range(len(fm.layout_x))]
 
-    # Plot using default 0-indexed labels (includes power/thrust curve)
-    plot_floris_layout(fm, plot_terrain=False)
+    # Plot the basic farm layout
+    ax = layoutviz.plot_turbine_points(fm, plotting_dict={"color": "g"})
+    layoutviz.plot_turbine_labels(fm, ax=ax, turbine_names=turbine_names)
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
 
-    # Plot using default given 1-indexed labels (includes power/thrust curve)
-    plot_floris_layout(fm, plot_terrain=False, turbine_names=turbine_names)
-
-    # Plot only the layout with default options
-    plot_layout_only(fm)
-
-    # Plot only the layout with custom options
-    plot_layout_only(fm, {"turbine_names": turbine_names, "color": "g"})
-
-    # Plot layout with wake directions and inter-turbine distances labeled
-    plot_layout_with_waking_directions(fm)
-
-    # Plot layout with wake directions and inter-turbine distances labeled
-    # (using custom options)
-    plot_layout_with_waking_directions(
+    # Plot using the default names and show the wake directions
+    turbines_to_plot = range(2, len(fm.layout_x))
+    ax = layoutviz.plot_turbine_points(fm, turbine_indices=turbines_to_plot)
+    layoutviz.plot_turbine_labels(
+        fm, ax=ax, turbine_indices=turbines_to_plot, turbine_names=turbine_names
+    )
+    layoutviz.plot_waking_directions(
         fm,
-        limit_num=3,  # limit to 3 lines per turbine
-        layout_plotting_dict={
-            "turbine_names": turbine_names,
-            "turbine_indices": range(2, len(fm.layout_x)),
-        },
+        ax=ax,
+        limit_num=3,
         wake_plotting_dict={"color": "r"},
+        turbine_indices=turbines_to_plot,
     )
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
 
     # Demonstrate shading of an arbitrary region
     points_for_demo = np.array([[600, 0], [1400, 0], [1200, 1000]])
-    ax = plot_layout_only(fm)
-    shade_region(
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax, turbine_names=turbine_names)
+    layoutviz.shade_region(
         points_for_demo,
         show_points=True,
         plotting_dict_region={"color": "blue", "label": "Example region"},
         plotting_dict_points={"color": "blue", "marker": "+", "s": 50},
         ax=ax,
     )
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
+
+    # Turbine data
+    fig, ax = plt.subplots(2, 1)
+    ax[0].plot(
+        fm.core.farm.turbine_map[0].power_thrust_table["wind_speed"],
+        fm.core.farm.turbine_map[0].power_thrust_table["power"],
+    )
+    ax[1].plot(
+        fm.core.farm.turbine_map[0].power_thrust_table["wind_speed"],
+        fm.core.farm.turbine_map[0].power_thrust_table["thrust_coefficient"],
+    )
+    ax[1].set_xlabel("Wind Speed [m/s]")
+    ax[1].set_ylabel("Thrust coefficient [-]")
+    ax[0].set_ylabel("Power [kW]")
+    ax[0].grid()
+    ax[1].grid()
 
     plt.show()

examples_artificial_data/00_setup_floris_model/01_visualize_flowfield.py

@@ -1,9 +1,9 @@
 # Copyright 2022 NREL & Shell
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 from floris.flow_visualization import visualize_cut_plane
 
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import plot_floris_layout
 
 if __name__ == "__main__":
     # User settings
@@ -26,7 +26,11 @@
         wind_speeds=[wind_speed],
         turbulence_intensities=[turbulence_intensity],
     )
-    plot_floris_layout(fm, plot_terrain=False)
+    ax = layoutviz.plot_turbine_points(fm)
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
+    ax.set_title("Turbine layout")
 
     # Generate baseline flowfield
     print("Calculating flowfield...")

examples_artificial_data/00_setup_floris_model/03_compute_turbine_dependencies.py

@@ -1,7 +1,7 @@
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 
-from flasc import visualization as fsaviz
 from flasc.utilities import floris_tools as fsatools
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
 
@@ -19,7 +19,11 @@
 fm, _ = load_floris()
 
 # Plot the layout of the farm for reference
-fsaviz.plot_layout_only(fm)
+ax = layoutviz.plot_turbine_points(fm)
+layoutviz.plot_turbine_labels(fm, ax=ax)
+ax.grid()
+ax.set_xlabel("x coordinate [m]")
+ax.set_ylabel("y coordinate [m]")
 
 # Get the dependencies of turbine 2
 check_directions = np.arange(0, 360.0, 2.0)

examples_artificial_data/02_wake_steering_design/00_analyze_single_ws_vs_range.py

@@ -1,10 +1,10 @@
+import floris.layout_visualization as layoutviz
 import numpy as np
 from _local_helper_functions import evaluate_optimal_yaw_angles, optimize_yaw_angles
 from matplotlib import pyplot as plt
 
 from flasc.utilities.lookup_table_tools import get_yaw_angles_interpolant
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import plot_floris_layout, plot_layout_with_waking_directions
 from flasc.yaw_optimizer_visualization import (
     plot_offsets_wd,
     plot_offsets_wswd_heatmap,
@@ -14,8 +14,9 @@
 if __name__ == "__main__":
     # Load FLORIS model and plot layout (and additional information)
     fm, _ = load_floris()
-    plot_floris_layout(fm)
-    plot_layout_with_waking_directions(fm, limit_dist_D=5, limit_num=3)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    layoutviz.plot_waking_directions(fm, ax=ax, limit_dist_D=5, limit_num=3)
 
     # Compare optimizing over all wind speeds vs. optimizing over a single wind speed
     AEP_baseline_array = []

examples_artificial_data/03_energy_ratio/04_energy_ratio_in_turbine_array.py

@@ -1,5 +1,6 @@
 import os
 
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
@@ -10,7 +11,6 @@
 from flasc.analysis.energy_ratio_input import EnergyRatioInput
 from flasc.data_processing import dataframe_manipulations as dfm
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import plot_floris_layout
 
 
 def load_data():
@@ -169,7 +169,11 @@ def plot_energy_ratios(turbine_array, results_energy_ratio, ax=None, label=None)
     ax = plot_energy_ratios(turbine_array, results_energy_ratio)
 
     # Also plot wake situation according to FLORIS
-    plot_floris_layout(fm, plot_terrain=False)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
 
     fig, ax = plt.subplots()
     fm.set(wind_directions=[wd], wind_speeds=[10.0])

examples_artificial_data/03_energy_ratio/05_estimate_heterogeneity_from_energy_ratios.py

@@ -7,8 +7,6 @@
 from flasc.analysis.energy_ratio_heterogeneity_mapper import heterogeneity_mapper
 from flasc.data_processing import dataframe_manipulations as dfm
 from flasc.utilities import floris_tools as ftools
-
-# from flasc.visualization import plot_floris_layout
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
 
 

examples_artificial_data/03_energy_ratio/06_wake_steering_example.py

@@ -1,3 +1,4 @@
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
@@ -6,7 +7,7 @@
 from flasc.analysis import energy_ratio as er
 from flasc.analysis.energy_ratio_input import EnergyRatioInput
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import plot_binned_mean_and_ci, plot_layout_with_waking_directions
+from flasc.visualization import plot_binned_mean_and_ci
 
 if __name__ == "__main__":
     # Construct a simple 3-turbine wind farm with a
@@ -19,7 +20,12 @@
     fm.set(layout_x=[0, 0, 5 * 126], layout_y=[5 * 126, 0, 0])
 
     # Show the wind farm
-    plot_layout_with_waking_directions(fm)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    layoutviz.plot_waking_directions(fm, ax=ax)
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
 
     # Create a time history of points where the wind speed and wind
     # direction step different combinations

examples_artificial_data/03_energy_ratio/07_wake_steering_total_uplift.py

@@ -1,11 +1,12 @@
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 
 from flasc.analysis import total_uplift as tup
 from flasc.analysis.energy_ratio_input import EnergyRatioInput
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
-from flasc.visualization import plot_binned_mean_and_ci, plot_layout_with_waking_directions
+from flasc.visualization import plot_binned_mean_and_ci
 
 if __name__ == "__main__":
     # Generate the data as in example 05_wake_steering_example.py
@@ -20,7 +21,12 @@
     fm.set(layout_x=[0, 0, 5 * 126], layout_y=[5 * 126, 0, 0])
 
     # Show the wind farm
-    plot_layout_with_waking_directions(fm)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    layoutviz.plot_waking_directions(fm, ax=ax)
+    ax.grid()
+    ax.set_xlabel("x coordinate [m]")
+    ax.set_ylabel("y coordinate [m]")
 
     # Create a time history of points where the wind speed and wind
     # direction step different combinations

examples_artificial_data/_legacy/sensitivity_analysis/sensitivity_analysis_suite.py

@@ -7,9 +7,7 @@
 import numpy as np
 import pandas as pd
 
-from flasc.model_estimation.floris_sensitivity_analysis import (
-    floris_sobol_analysis,
-)
+from flasc.model_estimation.floris_sensitivity_analysis import floris_sobol_analysis
 
 
 def _save_pickle(dict_in, fn):

examples_artificial_data/_legacy/table_analysis/energy_table_for_two_df.py

@@ -5,9 +5,7 @@
 from floris.utilities import wrap_360
 
 from flasc.analysis import energy_ratio_suite
-from flasc.data_processing import (
-    dataframe_manipulations as dfm,
-)
+from flasc.data_processing import dataframe_manipulations as dfm
 from flasc.utilities import floris_tools as fsatools
 from flasc.utilities.utilities_examples import load_floris_artificial as load_floris
 

flasc/utilities/utilities_examples.py

@@ -2,12 +2,11 @@
 from pathlib import Path
 from time import perf_counter as timerpc
 
+import floris.layout_visualization as layoutviz
 import matplotlib.pyplot as plt
 import numpy as np
 from floris import FlorisModel, UncertainFlorisModel
 
-from flasc.visualization import plot_floris_layout
-
 
 def load_floris_smarteole(wake_model="gch", wd_std=0.0):
     """Load a FlorisModel object for the wind farm at hand.
@@ -114,14 +113,18 @@ def load_floris_artificial(wake_model="gch", wd_std=0.0, cosine_exponent=None):
 if __name__ == "__main__":
     # Load and time the artificial FLORIS model
     t0 = timerpc()
-    fi, turbine_weights = load_floris_artificial()
+    fm, turbine_weights = load_floris_artificial()
     print("Time spent to load the FLORIS model (artificial): {:.2f} s.".format(timerpc() - t0))
-    plot_floris_layout(fi, plot_terrain=False)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    ax.grid()
 
     # Load and time the Smarteole FLORIS model
     t0 = timerpc()
-    fi, turbine_weights = load_floris_smarteole()
+    fm, turbine_weights = load_floris_smarteole()
     print("Time spent to load the FLORIS model (smarteole): {:.2f} s.".format(timerpc() - t0))
-    plot_floris_layout(fi, plot_terrain=False)
+    ax = layoutviz.plot_turbine_points(fm)
+    layoutviz.plot_turbine_labels(fm, ax=ax)
+    ax.grid()
 
     plt.show()