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Move polar plot to Python_Toolkit #315

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7fdaae6
moved polar plotting to python_toolkit.
Tom-Kingstone Jul 1, 2025
b37596d
make call to polar more future proof
Tom-Kingstone Jul 1, 2025
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121 changes: 23 additions & 98 deletions LadybugTools_Engine/Python/src/ladybugtools_toolkit/wind.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,8 +41,10 @@
analysis_period_to_datetimes,
describe_analysis_period,
)
from .bhom.logging import CONSOLE_LOGGER
from python_toolkit.plot.timeseries import timeseries
from .plot.utilities import contrasting_color, format_polar_plot
from python_toolkit.plot.polar import polar
from .plot.utilities import contrasting_color

# pylint: enable=E0401

Expand Down Expand Up @@ -1837,13 +1839,13 @@ def plot_windrose(
self,
ax: plt.Axes = None,
directions: int = 36,
other_data: list[float] = None,
other_bins: list[float] = None,
colors: list[str | tuple[float] | Colormap] = None,
value_bins: list[float] = BEAUFORT_CATEGORIES.bins,
colors: list[str | tuple[float] | Colormap] = BEAUFORT_CATEGORIES.cmap,
title: str = None,
legend: bool = True,
ylim: tuple[float] = None,
label: bool = False,
**kwargs,
) -> plt.Axes:
"""Create a wind rose showing wind speed and direction frequency.

Expand All @@ -1852,12 +1854,9 @@ def plot_windrose(
The axes to plot this chart on. Defaults to None.
directions (int, optional):
The number of directions to use. Defaults to 36.
other_data (list[float], optional):
A list of other data to bin by direction.
If None, then wind speed will be used.
other_bins (list[float]):
The other data bins to use for the histogram. These bins are right inclusive.
If other data is None, then the default Beaufort bins will be used,
value_bins (list[float], optional):
The bins to use for the wind speed values. These bins are right inclusive.
If unset, then the default BEAUFORT_CATEGORIES bins will be used.
otherwise 11 evenly spaced bins will be used.
colors: (str | tuple[float] | Colormap, optional):
A list of colors to use for the other bins. May also be a colormap.
Expand All @@ -1875,103 +1874,29 @@ def plot_windrose(
plt.Axes: The axes object.
"""

#deprecation warnings
if kwargs.pop("other_data", None) is not None:
CONSOLE_LOGGER.warning("'other_data' can no longer be used as an argument to plot custom polar plots with the Wind class. Please use the python_toolkit.plot.polar polar() method instead for this functionality.")

if kwargs.pop("other_bins", None) is not None:
CONSOLE_LOGGER.warning("'other_bins' has been renamed. Please use 'value_bins' in future instead.")
value_bins = kwargs["other_bins"]

if ax is None:
_, ax = plt.subplots(subplot_kw={"projection": "polar"})

# create grouped data for plotting
binned = self.histogram(
directions=directions,
other_data=other_data,
other_bins=other_bins,
density=True,
remove_calm=True,
)
df = pd.concat([self.ws, self.wd], axis=1)

df = df[self.ws >= 1e-10] #remove times where the wind speed is calm, as direction doesn't make sense in this context

# set colors
if colors is None:
if other_data is None:
colors = [
to_hex(BEAUFORT_CATEGORIES.cmap(i))
for i in np.linspace(0, 1, len(binned.columns))
]
else:
colors = [
to_hex(plt.get_cmap("viridis")(i))
for i in np.linspace(0, 1, len(binned.columns))
]
if isinstance(colors, str):
colors = plt.get_cmap(colors)
if isinstance(colors, Colormap):
colors = [to_hex(colors(i)) for i in np.linspace(0, 1, len(binned.columns))]
if isinstance(colors, list | tuple):
if len(colors) != len(binned.columns):
raise ValueError(
f"colors must be a list of length {len(binned.columns)}, or a colormap."
)

# HACK to ensure that bar ends are curved when using a polar plot.
fig = plt.figure()
rect = [0.1, 0.1, 0.8, 0.8]
hist_ax = plt.Axes(fig, rect)
hist_ax.bar(np.array([1]), np.array([1]))
colors = BEAUFORT_CATEGORIES.cmap

if title is None or title == "":
ax.set_title(textwrap.fill(f"{self.source}", 75))
else:
ax.set_title(title)

theta_width = np.deg2rad(360 / directions)
patches = []
color_list = []
x = theta_width / 2
for _, data_values in binned.iterrows():
y = 0
for n, val in enumerate(data_values.values):
patches.append(
Rectangle(
xy=(x, y),
width=theta_width,
height=val,
alpha=1,
)
)
color_list.append(colors[n])
y += val
if label:
ax.text(x, y, f"{y:0.1%}", ha="center", va="center", fontsize="x-small")
x += theta_width
local_cmap = ListedColormap(np.array(color_list).flatten())
pc = PatchCollection(patches, cmap=local_cmap)
pc.set_array(np.arange(len(color_list)))
ax.add_collection(pc)

# construct legend
if legend:
handles = [
mpatches.Patch(color=colors[n], label=f"{i} to {j}")
for n, (i, j) in enumerate(binned.columns.values)
]
_ = ax.legend(
handles=handles,
bbox_to_anchor=(1.1, 0.5),
loc="center left",
ncol=1,
borderaxespad=0,
frameon=False,
fontsize="small",
title=binned.columns.name,
title_fontsize="small",
)

# set y-axis limits
if ylim is None:
ylim = (0, max(binned.sum(axis=1)))
if len(ylim) != 2:
raise ValueError("ylim must be a tuple of length 2.")
ax.set_ylim(ylim)
ax.yaxis.set_major_formatter(mticker.PercentFormatter(xmax=1))
title = textwrap.fill(f"{self.source}", 75)

format_polar_plot(ax, yticklabels=True)
ax = polar(data=df, value_column=df.columns[0], direction_column=df.columns[1], ax=ax, directions=directions, value_bins=value_bins, colours=colors, title=title, legend=legend, ylim=ylim, label=label)

return ax

Expand Down