class_docstr: Create plots for `InteractTargetPlot` or `InteractPredictPlot`
  
  Methods
  -------
  plot_matplotlib : plot using matplotlib
  plot_plotly : plot using plotly
class_docstr_tok: ["Create","plots","for","`","InteractTargetPlot","`","or","`","InteractPredictPlot","`","Methods","--","--","--","-","plot_matplotlib",":","plot","using","matplotlib","plot_plotly",":","plot","using","plotly"]
code: def _draw_legend_sizes(self, axes, cmap):
      size_style = self.plot_style.legend["circles"]
      dark_color = plt.get_cmap(cmap)(1.0)
      xs, ys = [0.75, 2], [1] * 2
  
      axes.plot(xs, ys, color=dark_color, zorder=1, ls="--", lw=1)
      axes.scatter(
          xs,
          ys,
          s=[200, 500],
          edgecolors=dark_color,
          color="white",
          zorder=2,
      )
      axes.set_xlim(0.0, 3)
  
      text_params = {
          "fontdict": {
              "color": dark_color,
              "fontsize": size_style["fontsize"],
              "fontfamily": size_style["fontfamily"],
          },
          "ha": "center",
          "va": "center",
      }
  
      for x, count in zip(xs, [self.count_min, self.count_max]):
          count_text = axes.text(x, 1, count, **text_params)
          count_text.set_path_effects(
              [PathEffects.withStroke(linewidth=3, foreground="w")]
          )
  
      _modify_legend_axes(axes, size_style["fontfamily"])
  
imports: from .styles import _prepare_plot_style, _axes_modify, _display_percentile, _modify_legend_axes, _get_axes_label
  import numpy
  from itertools import cycle
  import plotly.express
  import matplotlib
  import matplotlib.pyplot
  from matplotlib.gridspec import GridSpecFromSubplotSpec
  from mpl_toolkits.axes_grid1.inset_locator import inset_axes
  import matplotlib.patheffects
  import plotly.graph_objects
label_desc: Use image node_id 10 for calling the InteractInfoPlotEngine obj's underlying member method code with example usage: obj._draw_legend_sizes(axes, cmap) without return types