docstr: Composite of decision tree related components:
  
  - index selector
  - individual decision trees barchart
  - decision path table
  - deciion path graph
  
  Args:
      explainer (Explainer): explainer object constructed with either
                  RandomForestClassifierExplainer() or RandomForestRegressionExplainer()
      title (str, optional): Title of tab or page. Defaults to
                  "Decision Trees".
      name (str, optional): unique name to add to Component elements.
                  If None then random uuid is generated to make sure
                  it's unique. Defaults to None.
      hide_treeindexselector (bool, optional): hide ClassifierRandomIndexComponent
          or RegressionRandomIndexComponent
      hide_treesgraph (bool, optional): hide DecisionTreesComponent
      hide_treepathtable (bool, optional): hide DecisionPathTableComponent
      hide_treepathgraph (bool, optional): DecisionPathGraphComponent
      hide_selector (bool, optional): hide all pos label selectors. Defaults to True.
      index_check (bool, optional): only pass valid indexes from random index
          selector to feature input. Defaults to True.
code: def __init__(
      self,
      explainer,
      title="Decision Trees",
      name=None,
      hide_treeindexselector=False,
      hide_treesgraph=False,
      hide_treepathtable=False,
      hide_treepathgraph=False,
      hide_selector=True,
      index_check=True,
      **kwargs,
  ):
      """Composite of decision tree related components:
  
      - index selector
      - individual decision trees barchart
      - decision path table
      - deciion path graph
  
      Args:
          explainer (Explainer): explainer object constructed with either
                      RandomForestClassifierExplainer() or RandomForestRegressionExplainer()
          title (str, optional): Title of tab or page. Defaults to
                      "Decision Trees".
          name (str, optional): unique name to add to Component elements.
                      If None then random uuid is generated to make sure
                      it's unique. Defaults to None.
          hide_treeindexselector (bool, optional): hide ClassifierRandomIndexComponent
              or RegressionRandomIndexComponent
          hide_treesgraph (bool, optional): hide DecisionTreesComponent
          hide_treepathtable (bool, optional): hide DecisionPathTableComponent
          hide_treepathgraph (bool, optional): DecisionPathGraphComponent
          hide_selector (bool, optional): hide all pos label selectors. Defaults to True.
          index_check (bool, optional): only pass valid indexes from random index
              selector to feature input. Defaults to True.
      """
      super().__init__(explainer, title, name)
  
      self.trees = DecisionTreesComponent(
          explainer, hide_selector=hide_selector, **kwargs
      )
      self.decisionpath_table = DecisionPathTableComponent(
          explainer, hide_selector=hide_selector, **kwargs
      )
  
      if explainer.is_classifier:
          self.index = ClassifierRandomIndexComponent(
              explainer, hide_selector=hide_selector, **kwargs
          )
      elif explainer.is_regression:
          self.index = RegressionRandomIndexComponent(
              explainer, **kwargs
          )
  
      self.decisionpath_graph = DecisionPathGraphComponent(
          explainer, hide_selector=hide_selector, **kwargs
      )
  
      self.index_connector = IndexConnector(
          self.index,
          [
              self.trees,
              self.decisionpath_table,
              self.decisionpath_graph,
          ],
          explainer=explainer if index_check else None,
      )
      self.highlight_connector = HighlightConnector(
          self.trees, [self.decisionpath_table, self.decisionpath_graph]
      )
  
imports: import dash_bootstrap_components
  from dash import html
  from ..explainers import RandomForestExplainer, XGBExplainer
  from ..dashboard_methods import *
  from .classifier_components import *
  from .regression_components import *
  from .overview_components import *
  from .connectors import *
  from .shap_components import *
  from .decisiontree_components import *
  from ..None import to_html
label_desc: Use image node_id 1 to create a new DecisionTreesComposite object from inherited base classes: ExplainerComponent with example: obj = DecisionTreesComposite(explainer, title, name, hide_treeindexselector, hide_treesgraph, hide_treepathtable, hide_treepathgraph, hide_selector, index_check)