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Selectively invert plot axis via normal vector in CutPlane #384

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Mar 9, 2022
Merged

Selectively invert plot axis via normal vector in CutPlane #384

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3 changes: 2 additions & 1 deletion floris/tools/cut_plane.py
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Original file line number Diff line number Diff line change
Expand Up @@ -105,7 +105,7 @@ class CutPlane:
FLORIS simulation, or other such as SOWFA result.
"""

def __init__(self, df, x1_resolution, x2_resolution):
def __init__(self, df, x1_resolution, x2_resolution, normal_vector):
"""
Initialize CutPlane object, storing the DataFrame and resolution.

Expand All @@ -114,6 +114,7 @@ def __init__(self, df, x1_resolution, x2_resolution):
columns x1, x2, u, v, w.
"""
self.df = df
self.normal_vector = normal_vector
self.resolution = (x1_resolution, x2_resolution)


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6 changes: 3 additions & 3 deletions floris/tools/floris_interface.py
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Expand Up @@ -329,7 +329,7 @@ def calculate_horizontal_plane(
)

# Compute the cutplane
horizontal_plane = CutPlane(df, self.floris.grid.grid_resolution[0], self.floris.grid.grid_resolution[1])
horizontal_plane = CutPlane(df, self.floris.grid.grid_resolution[0], self.floris.grid.grid_resolution[1], "z")

# Reset the fi object back to the turbine grid configuration
self.floris = Floris.from_dict(floris_dict)
Expand Down Expand Up @@ -409,7 +409,7 @@ def calculate_cross_plane(
)

# Compute the cutplane
cross_plane = CutPlane(df, y_resolution, z_resolution)
cross_plane = CutPlane(df, y_resolution, z_resolution, "x")

# Reset the fi object back to the turbine grid configuration
self.floris = Floris.from_dict(floris_dict)
Expand Down Expand Up @@ -488,7 +488,7 @@ def calculate_y_plane(
)

# Compute the cutplane
y_plane = CutPlane(df, x_resolution, z_resolution)
y_plane = CutPlane(df, x_resolution, z_resolution, "y")

# Reset the fi object back to the turbine grid configuration
self.floris = Floris.from_dict(floris_dict)
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6 changes: 5 additions & 1 deletion floris/tools/visualization.py
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Expand Up @@ -169,6 +169,9 @@ def visualize_cut_plane(
# Add line contour
line_contour_cut_plane(cut_plane, ax=ax, levels=levels, colors="w", linewidths=0.8, alpha=0.3)

if cut_plane.normal_vector == "x":
ax.invert_xaxis()

if color_bar:
cbar = plt.colorbar(im, ax=ax)
cbar.set_label('m/s')
Expand Down Expand Up @@ -249,7 +252,7 @@ def plot_rotor_values(
return_fig_objects: bool = False,
save_path: Union[str, None] = None,
show: bool = False
) -> Union[None, tuple[plt.figure, plt.axes]]:
) -> Union[None, tuple[plt.figure, plt.axes, plt.axis, plt.colorbar]]:
"""Plots the gridded turbine rotor values. This is intended to be used for
understanding the differences between two sets of values, so each subplot can be
used for inspection of what values are differing, and under what conditions.
Expand Down Expand Up @@ -294,6 +297,7 @@ def plot_rotor_values(
norm = mplcolors.Normalize(vmin, vmax)

ax.imshow(values[wd_index, ws_index, i].T, cmap=cmap, norm=norm, origin="lower")
ax.invert_xaxis()

ax.set_xticks([])
ax.set_yticks([])
Expand Down