moved polar plotting to python_toolkit.

Author: Tom-Kingstone

LadybugTools_Engine/Python/src/ladybugtools_toolkit/wind.py

@@ -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
 
@@ -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.
 
@@ -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.
@@ -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(df, "Wind Speed (m/s)", "Wind Direction (degrees)", ax, directions, value_bins, colors, title, legend, ylim, label)
 
         return ax