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 plot_matplotlib(self):
      fig, inner_grids, title_axes = self.plot_style.make_subplots()
      axes = {
          "title_axes": title_axes,
          "value_axes": [],
          "legend_axes": [],
      }
  
      for i, class_idx in enumerate(self.which_classes):
          target, cmap = self.prepare_data(class_idx)
          value_axes, legend_axes = self.prepare_axes(inner_grids[i])
          value_min, value_max = self._draw_interact(
              target, value_axes, cmap
          )
  
          self._draw_legend_colorbar(
              value_min, value_max, legend_axes[0], cmap
          )
          self._draw_legend_sizes(legend_axes[1], cmap)
          self.set_subplot_title(target, value_axes)
          axes["value_axes"].append(value_axes)
          axes["legend_axes"].append(legend_axes)
  
      return fig, axes
  
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 15 for calling the InteractInfoPlotEngine obj's underlying member method code with example usage: obj.plot_matplotlib() and returns: fig,  axes