import os
import numpy as np
import matplotlib.axes
import matplotlib.pyplot as plt
import openmdao
import optiwindnet.plotting
# get plot limits based on the farm boundaries
[docs]
def get_limits(
windIOdict: dict,
lim_buffer: float = 0.05,
):
"""
generate plot limits based on the expected values found in the windIO file
Parameters
----------
windIOplant : dict
a full, presumed validated, windIO plant specification file
lim_buffer : float, optional
a percent buffer for plot edges, by default 0.05 (5%)
Returns
-------
x_lim : np.ndarray
the two-valued limits for the x-axis based on the windIO
y_lim : np.ndarray
the two-valued limits for the y-axis based on the windIO
"""
x_lim = [
np.min(windIOdict["site"]["boundaries"]["polygons"][0]["x"])
- lim_buffer * np.ptp(windIOdict["site"]["boundaries"]["polygons"][0]["x"]),
np.max(windIOdict["site"]["boundaries"]["polygons"][0]["x"])
+ lim_buffer * np.ptp(windIOdict["site"]["boundaries"]["polygons"][0]["x"]),
]
y_lim = [
np.min(windIOdict["site"]["boundaries"]["polygons"][0]["y"])
- lim_buffer * np.ptp(windIOdict["site"]["boundaries"]["polygons"][0]["y"]),
np.max(windIOdict["site"]["boundaries"]["polygons"][0]["y"])
+ lim_buffer * np.ptp(windIOdict["site"]["boundaries"]["polygons"][0]["y"]),
]
return x_lim, y_lim
[docs]
def plot_layout(
ard_prob: openmdao.api.Problem,
input_dict: dict,
ax: matplotlib.axes.Axes = None,
show_image: bool = False,
save_path: os.PathLike = None,
save_kwargs: dict = {},
include_cable_routing: bool = False,
include_mooring_system: bool = False,
):
"""
plot the layout of a farm
Parameters
----------
ard_prob : openmdao.api.Problem
the active Ard/OpenMDAO problem
input_dict : dict
the active Ard input dictionary
ax : matplotlib.axes.Axes, optional
an already-active pyplot Axes, by default None
show_image : bool, optional
to show the image, rather than just saving, by default False
save_path : os.PathLike, optional
location where the image be saved, by default None
save_kwargs : dict, optional
optional keyword arguments for plt.savefig, by default {}
include_cable_routing : bool, optional
should the collection system routing be plotted also, by default False
Returns
-------
matplotlib.axes.Axes
the matplotlib Axes that have been generated (or modified)
"""
# get the turbine locations to plot
x_turbines = ard_prob.get_val("x_turbines", units="m")
y_turbines = ard_prob.get_val("y_turbines", units="m")
# make axis object
if ax is None:
fig, ax = plt.subplots()
# plot wind plant boundaries
windIO_dict = input_dict["modeling_options"]["windIO_plant"]
ax.fill(
windIO_dict["site"]["boundaries"]["polygons"][0]["x"],
windIO_dict["site"]["boundaries"]["polygons"][0]["y"],
linestyle="--",
alpha=0.5,
fill=False,
c="k",
# linecolor="k",
)
# plot turbines
ax.plot(x_turbines, y_turbines, "ok")
# adjust plot limits
x_lim, y_lim = get_limits(windIO_dict)
ax.set_xlim(x_lim)
ax.set_ylim(y_lim)
if include_cable_routing:
optiwindnet.plotting.gplot(
ard_prob.model.collection.graph,
ax=ax,
dark=False,
legend=False,
hide_ST=True,
infobox=False,
landscape=False,
)
if include_mooring_system:
# get the coordinates of the anchors
x_anchors = ard_prob.get_val("x_anchors", units="m")
y_anchors = ard_prob.get_val("y_anchors", units="m")
# loop over the anchors and plot from their originating turbine to each
for idx_turbine in range(
input_dict["modeling_options"]["layout"]["N_turbines"]
):
for idx_anchor in range(
input_dict["modeling_options"]["platform"]["N_anchors"]
):
ax.plot(
[x_turbines[idx_turbine], x_anchors[idx_turbine, idx_anchor]],
[y_turbines[idx_turbine], y_anchors[idx_turbine, idx_anchor]],
"-r",
alpha=0.25,
)
# plot the anchors as red circles
ax.plot(
x_anchors[idx_turbine, :],
y_anchors[idx_turbine, :],
"or",
alpha=0.25,
)
ax.axis("equal")
# show, save, or return
if save_path is not None:
plt.savefig(save_path, **save_kwargs)
if show_image:
plt.show()
return ax
