code: def radar_chart(
      ground_truth,
      predictions,
      algorithms=None,
      log_scale=False,
      title=None,
      filename=None,
      callbacks=None,
  ):
      sns.set_style("whitegrid")
  
      if title is not None:
          plt.title(title)
  
      ground_truth = ground_truth[0:10]
      predictions = [pred[0:10] for pred in predictions]
  
      gt_argsort = np.argsort(-ground_truth)  # sort deacreasing
      logger.info(gt_argsort)
      ground_truth = ground_truth[gt_argsort]
      predictions = [pred[gt_argsort] for pred in predictions]
  
      maximum = max(max(ground_truth), max(max(p) for p in predictions))
  
      ax = plt.subplot(111, polar=True)
      ax.set_theta_zero_location("N")
      ax.set_theta_direction(-1)
      ax.set_rmax(maximum)
      ax.set_rlabel_position(305)
      ax.set_ylabel("Probability")
      # ax.set_rscale('log')
      ax.grid(True)
  
      colors = plt.get_cmap("tab10").colors
  
      num_classes = len(ground_truth)
  
      # Set ticks to the number of properties (in radians)
      t = np.arange(0, 2 * np.pi, 2 * np.pi / num_classes)
      if _matplotlib_34:
          ax.set_xticks(t)
      else:
          ax.set_xticks(t, [])
      ax.set_xticklabels(np.arange(0, num_classes))
  
      # Set yticks from 0 to 10
      # ax.set_yticks(np.linspace(0, 10, 11))
      # Set axes limits
      # ax.set_rlim(0, 1)
      # ax.set_rscale('log')
  
      def draw_polygon(values, label, color="grey"):
          points = [(x, y) for x, y in zip(t, values)]
          points.append(points[0])
          points = np.array(points)
  
          codes = (
              [path.Path.MOVETO]
              + [path.Path.LINETO] * (len(values) - 1)
              + [path.Path.CLOSEPOLY]
          )
          _path = path.Path(points, codes)
          _patch = patches.PathPatch(
              _path, fill=True, color=color, linewidth=0, alpha=0.2
          )
          ax.add_patch(_patch)
          _patch = patches.PathPatch(
              _path, fill=False, color=color, linewidth=3
          )
          ax.add_patch(_patch)
  
          # Draw circles at value points
          # line = ax.scatter(points[:, 0], points[:, 1], linewidth=3,
          #            s=50, color='white', edgecolor=color, zorder=10)
          ax.plot(
              points[:, 0],
              points[:, 1],
              linewidth=3,
              marker="o",
              fillstyle="full",
              markerfacecolor="white",
              markeredgecolor=color,
              markeredgewidth=2,
              color=color,
              zorder=10,
              label=label,
          )
  
      draw_polygon(ground_truth, "Ground Truth")
  
      # Draw polygon representing values
      for i, alg_predictions in enumerate(predictions):
          draw_polygon(alg_predictions, algorithms[i], colors[i])
  
      ax.legend(frameon=True, loc="upper left")
      plt.tight_layout()
      visualize_callbacks(callbacks, plt.gcf())
      if filename:
          plt.savefig(filename)
      else:
          plt.show()
  
imports: import copy
  import logging
  from collections import Counter
  from sys import platform
  from typing import Dict, List
  import numpy
  import pandas
  import ptitprince
  from packaging import version
  from ludwig.constants import SPACE, TRAINING, VALIDATION
label_desc: Use image node_id 6 for calling a global function with example usage: radar_chart(ground_truth, predictions, algorithms, log_scale, title, filename, callbacks) without return types