class_docstr: Create plots for `PDPIsolate`
  
  Methods
  -------
  plot : generate the plot
  plot_matplotlib : plot using matplotlib
  plot_plotly : plot using plotly
class_docstr_tok: ["Create","plots","for","`","PDPIsolate","`","Methods","--","--","--","-","plot",":","generate","the","plot","plot_matplotlib",":","plot","using","matplotlib","plot_plotly",":","plot","using","plotly"]
code: def _ice_line_plot(self, x, lines, cmap, axes):
      total = len(lines)
      linewidth, linealpha = max(1.0 / np.log10(total), 0.3), min(
          max(1.0 / np.log10(total), 0.3), 0.8
      )
      colors = plt.get_cmap(cmap)(np.linspace(0, 1, 20))[5:15]
  
      if self.plot_style.engine == "matplotlib":
          for i, line in enumerate(lines.values):
              axes.plot(
                  x,
                  line,
                  linewidth=linewidth,
                  c=colors[i % 10],
                  alpha=linealpha,
              )
      else:
          colors = [_to_rgba(v, linealpha) for v in colors]
          return [
              go.Scatter(
                  x=x,
                  y=line,
                  mode="lines",
                  line=dict(color=colors[i % 10], width=linewidth),
                  hoverinfo="none",
              )
              for i, line in enumerate(lines.values)
          ]
  
imports: from .utils import _get_string, _to_rgba
  from .styles import _prepare_plot_style, _axes_modify, _display_percentile, _modify_legend_axes, _get_axes_label
  import pandas
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from matplotlib.gridspec import GridSpecFromSubplotSpec
  import copy
  from mpl_toolkits.axes_grid1.inset_locator import inset_axes
  import plotly.graph_objects
  from sklearn.cluster import MiniBatchKMeans, KMeans
  from itertools import cycle
label_desc: Use image node_id 6 for calling the PDPIsolatePlotEngine obj's underlying member method code with example usage: obj._ice_line_plot(x, lines, cmap, axes) and returns: unknown