code: def get_color(self, value):
      # Find the appropriate color & intensity for a node
      if self.colors["bounds"] is None:
          # Classification tree
          color = list(self.colors["rgb"][np.argmax(value)])
          sorted_values = sorted(value, reverse=True)
          if len(sorted_values) == 1:
              alpha = 0.0
          else:
              alpha = (sorted_values[0] - sorted_values[1]) / (
                  1 - sorted_values[1]
              )
      else:
          # Regression tree or multi-output
          color = list(self.colors["rgb"][0])
          alpha = (value - self.colors["bounds"][0]) / (
              self.colors["bounds"][1] - self.colors["bounds"][0]
          )
      # compute the color as alpha against white
      color = [
          int(round(alpha * c + (1 - alpha) * 255, 0)) for c in color
      ]
      # Return html color code in #RRGGBB format
      return "#%2x%2x%2x" % tuple(color)
  
imports: from collections.abc import Iterable
  from io import StringIO
  from numbers import Integral
  import numpy
  from ..base import is_classifier
  from ..utils._param_validation import HasMethods, Interval, StrOptions, validate_params
  from ..utils.validation import check_array, check_is_fitted
  from .None import DecisionTreeClassifier, DecisionTreeRegressor, _criterion, _tree
  from ._reingold_tilford import Tree, buchheim
label_desc: Use image node_id 2 for calling the _BaseTreeExporter obj's underlying member method code with example usage: obj.get_color(value) and returns: unknown