Merge pull request #512 from rafmudaf/api

FLORIS Tools API improvements

examples/01_opening_floris_computing_power.py

@@ -13,7 +13,6 @@
 # See https://floris.readthedocs.io for documentation
 
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 from floris.tools import FlorisInterface

examples/02_visualizations.py

@@ -16,8 +16,7 @@
 import matplotlib.pyplot as plt
 
 from floris.tools import FlorisInterface
-from floris.tools.visualization import visualize_cut_plane
-from floris.tools.visualization import plot_rotor_values
+import floris.tools.visualization as wakeviz
 
 """
 This example initializes the FLORIS software, and then uses internal
@@ -52,9 +51,9 @@
 # Create the plots
 fig, ax_list = plt.subplots(3, 1, figsize=(10, 8))
 ax_list = ax_list.flatten()
-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")
+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")
 
 # FLORIS further includes visualization methods for visualing the rotor plane of each
 # Turbine in the simulation
@@ -64,7 +63,7 @@
 fi.calculate_wake()
 
 # Plot the values at each rotor
-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, 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.suptitle("Rotor Plane Visualization, Original Resolution")
 
 # FLORIS supports multiple types of grids for capturing wind speed
@@ -86,7 +85,7 @@
 fi.calculate_wake()
 
 # Plot the values at each rotor
-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, 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.suptitle("Rotor Plane Visualization, 10x10 Resolution")
 
-plt.show()
+wakeviz.show_plots()

examples/03_making_adjustments.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from floris.tools import FlorisInterface
-from floris.tools import visualize_cut_plane #, plot_turbines_with_fi
+import floris.tools.visualization as wakeviz
 
 """
 This example makes changes to the given input file through the script.
@@ -38,53 +38,53 @@
 
 # Plot a horizatonal slice of the initial configuration
 horizontal_plane = fi.calculate_horizontal_plane(height=90.0)
-visualize_cut_plane(horizontal_plane, ax=axarr[0], title="Initial setup", minSpeed=MIN_WS, maxSpeed=MAX_WS)
-
+wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[0], title="Initial setup", min_speed=MIN_WS, max_speed=MAX_WS)
 
 # Change the wind speed
 horizontal_plane = fi.calculate_horizontal_plane(ws=[7.0], height=90.0)
-visualize_cut_plane(horizontal_plane, ax=axarr[1], title="Wind speed at 7 m/s", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+wakeviz.visualize_cut_plane(horizontal_plane, ax=axarr[1], title="Wind speed at 7 m/s", min_speed=MIN_WS, max_speed=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)
-visualize_cut_plane(y_plane, ax=axarr[2], title="Wind shear at 0.2", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+wakeviz.visualize_cut_plane(y_plane, ax=axarr[2], title="Wind shear at 0.2", min_speed=MIN_WS, max_speed=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())
+fi.reinitialize(layout_x=X.flatten(), layout_y=Y.flatten(), wind_directions=[360.0])
 horizontal_plane = fi.calculate_horizontal_plane(height=90.0)
-visualize_cut_plane(horizontal_plane, ax=axarr[3], title="3x3 Farm", minSpeed=MIN_WS, maxSpeed=MAX_WS)
-
+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])
 
 # 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[:,:,1] = -30.0
-yaw_angles[:,:,2] = 30.0
+yaw_angles[:,:,3] = -30.0
+yaw_angles[:,:,6] = 30.0
 
 ## Second row
-yaw_angles[:,:,3] = -30.0
+yaw_angles[:,:,1] = -30.0
 yaw_angles[:,:,4] = 30.0
-yaw_angles[:,:,5] = -30.0
+yaw_angles[:,:,7] = -30.0
 
 horizontal_plane = fi.calculate_horizontal_plane(yaw_angles=yaw_angles, height=90.0)
-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)
+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")
 
 
 # Plot the cross-plane of the 3x3 configuration
 cross_plane = fi.calculate_cross_plane(yaw_angles=yaw_angles, downstream_dist=610.0)
-visualize_cut_plane(cross_plane, ax=axarr[5], title="Cross section at 610 m", minSpeed=MIN_WS, maxSpeed=MAX_WS)
+wakeviz.visualize_cut_plane(cross_plane, ax=axarr[5], title="Cross section at 610 m", min_speed=MIN_WS, max_speed=MAX_WS)
 axarr[5].invert_xaxis()
 
 
-plt.show()
+wakeviz.show_plots()

examples/04_sweep_wind_directions.py

@@ -17,8 +17,6 @@
 import numpy as np
 
 from floris.tools import FlorisInterface
-from floris.tools.visualization import visualize_cut_plane
-
 
 """
 04_sweep_wind_directions
@@ -72,4 +70,5 @@
 ax.legend()
 ax.set_xlabel('Wind Direction (deg)')
 ax.set_ylabel('Power (kW)')
+
 plt.show()

examples/05_sweep_wind_speeds.py

@@ -17,7 +17,6 @@
 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

@@ -13,7 +13,6 @@
 # See https://floris.readthedocs.io for documentation
 
 
-import enum
 import matplotlib.pyplot as plt
 import numpy as np
 

examples/08_calc_aep_from_rose_use_class.py

@@ -13,11 +13,8 @@
 # See https://floris.readthedocs.io for documentation
 
 
-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
+import floris.tools.visualization as wakeviz
 
 """
 This example demonstrates how to calculate the Annual Energy Production (AEP)
@@ -70,5 +67,4 @@
 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))
 
-
-plt.show()
+wakeviz.show_plots()

examples/09_compare_farm_power_with_neighbor.py

@@ -14,7 +14,6 @@
 
 
 import numpy as np
-import pandas as pd
 from floris.tools import FlorisInterface
 import matplotlib.pyplot as plt
 

examples/17_multiple_turbine_types.py

@@ -14,10 +14,9 @@
 
 
 import matplotlib.pyplot as plt
-import numpy as np
 
 from floris.tools import FlorisInterface
-from floris.tools.visualization import visualize_cut_plane
+import floris.tools.visualization as wakeviz
 
 """
 This example uses an input file where multiple turbine types are defined.
@@ -38,8 +37,8 @@
 # Create the plots
 fig, ax_list = plt.subplots(3, 1, figsize=(10, 8))
 ax_list = ax_list.flatten()
-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")
+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")
 
-plt.show()
+wakeviz.show_plots()

examples/18_check_turbine.py

@@ -18,7 +18,6 @@
 import os
 
 from floris.tools import FlorisInterface
-from floris.tools import visualize_cut_plane #, plot_turbines_with_fi
 
 """
 For each turbine in the turbine library, make a small figure showing that its power curve and power loss to yaw are reasonable and 
@@ -109,8 +108,4 @@
     # Give a suptitle
     fig.suptitle(t)
 
-
-
 plt.show()
-
-

examples/19_streamlit_demo.py

@@ -16,7 +16,6 @@
 import matplotlib.pyplot as plt
 import streamlit as st
 import numpy as np
-import pandas as pd
 # import seaborn as sns
 
 from floris.tools import FlorisInterface

examples/22_get_wind_speed_at_turbines.py

@@ -13,7 +13,6 @@
 # See https://floris.readthedocs.io for documentation
 
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 from floris.tools import FlorisInterface
@@ -35,13 +34,10 @@
 print('U points is 1 wd x 1 ws x 4 turbines x 3 x 3 points (turbine_grid_points=3)')
 print(u_points.shape)
 
-# Collect the average wind speeds from each turbine
-avg_vel = fi.get_turbine_average_velocities()
-
-print('Avg vel is 1 wd x 1 ws x 4 turbines')
-print(avg_vel.shape)
+print('turbine_average_velocities is 1 wd x 1 ws x 4 turbines')
+print(fi.turbine_average_velocities)
 
 # Show that one is equivalent to the other following averaging
-print('Avg Vel is determined by taking the cube root of mean of the cubed value across the points')
-print('Average velocity: ', avg_vel)
+print('turbine_average_velocities is determined by taking the cube root of mean of the cubed value across the points')
+print('turbine_average_velocities: ', fi.turbine_average_velocities)
 print('Recomputed:       ', np.cbrt(np.mean(u_points**3, axis=(3,4))))

floris/tools/cut_plane.py

@@ -113,9 +113,33 @@ def __init__(self, df, x1_resolution, x2_resolution, normal_vector):
             df (pandas.DataFrame): Pandas DataFrame of data with
                 columns x1, x2, u, v, w.
         """
-        self.df = df
-        self.normal_vector = normal_vector
+        self.df: pd.DataFrame = df
+        self.normal_vector: str = normal_vector
         self.resolution = (x1_resolution, x2_resolution)
+        self.df.set_index(["x1", "x2"])
+
+    def __sub__(self, other):
+
+        if self.normal_vector != other.normal_vector:
+            raise ValueError("Operands must have consistent normal vectors.")
+
+        # if self.normal_vector.df.
+        # DF must be of the same size
+        # resolution must be of the same size
+
+        df: pd.DataFrame = self.df.copy()
+        other_df: pd.DataFrame = other.df.copy()
+
+        df['u'] = self.df['u'] - other_df['u']
+        df['v'] = self.df['v'] - other_df['v']
+        df['w'] = self.df['w'] - other_df['w']
+
+        return CutPlane(
+            df,
+            self.resolution[0],
+            self.resolution[1],
+            self.normal_vector
+        )
 
 
 # Modification functions
@@ -323,37 +347,6 @@ def project_onto(cut_plane_a, cut_plane_b):
     )
 
 
-def subtract(cut_plane_a_in, cut_plane_b_in):
-    """
-    Subtract u,v,w terms of cut_plane_b from cut_plane_a
-
-    Args:
-        cut_plane_a_in (:py:class:`~.tools.cut_plane.CutPlane`):
-            Plane of data to subtract from.
-        cut_plane_b_in (:py:class:`~.tools.cut_plane.CutPlane`):
-            Plane of data to subtract b.
-
-    Returns:
-        cut_plane (:py:class:`~.tools.cut_plane.CutPlane`):
-            Difference of cut_plane_a_in minus cut_plane_b_in.
-    """
-
-    # First make copies of original
-    cut_plane_a = copy.deepcopy(cut_plane_a_in)
-    cut_plane_b = copy.deepcopy(cut_plane_b_in)
-
-    # Sort x1 and x2 and make the index
-    cut_plane_a.df = cut_plane_a.df.set_index(["x1", "x2"])
-    cut_plane_b.df = cut_plane_b.df.set_index(["x1", "x2"])
-
-    # Do subtraction
-    cut_plane_a.df = cut_plane_a.df.subtract(
-        cut_plane_b.df
-    ).reset_index()  # .sort_values(['x2','x1'])# .dropna()
-    # cut_plane_a.df = cut_plane_a.df.sort_values(['x1','x2'])
-    return cut_plane_a
-
-
 def calculate_wind_speed(cross_plane, x1_loc, x2_loc, R):
     """
     Calculate effective wind speed within specified range of a point.

floris/tools/floris_interface.py

@@ -117,15 +117,16 @@ def calculate_wake(
             track_n_upstream_wakes (bool, optional): When *True*, will keep track of the
                 number of upstream wakes a turbine is experiencing. Defaults to *False*.
         """
-        # self.floris.flow_field.calculate_wake(
-        #     no_wake=no_wake,
-        #     points=points,
-        #     track_n_upstream_wakes=track_n_upstream_wakes,
-        # )
 
-        # TODO decide where to handle this sign issue
-        if (yaw_angles is not None) and not (np.all(yaw_angles==0.)):
-            self.floris.farm.yaw_angles = yaw_angles
+        if yaw_angles is None:
+            yaw_angles = np.zeros(
+                (
+                    self.floris.flow_field.n_wind_directions,
+                    self.floris.flow_field.n_wind_speeds,
+                    self.floris.farm.n_turbines
+                )
+            )
+        self.floris.farm.yaw_angles = yaw_angles
 
         # Initialize solution space
         self.floris.initialize_domain()
@@ -601,11 +602,9 @@ def get_turbine_ais(self) -> NDArrayFloat:
         )
         return turbine_ais
 
-    def get_turbine_average_velocities(self) -> NDArrayFloat:
-        turbine_avg_vels = average_velocity(
-            velocities=self.floris.flow_field.u,
-        )
-        return turbine_avg_vels
+    @property
+    def turbine_average_velocities(self) -> NDArrayFloat:
+        return average_velocity(velocities=self.floris.flow_field.u)
 
     def get_turbine_TIs(self) -> NDArrayFloat:
         return self.floris.flow_field.turbulence_intensity_field