class_docstr: Visualizations specific to Method of Morris.
docstr: Initializes class.
  
  Args:
      explanation_type:  Type of explanation.
      internal_obj: A jsonable object that backs the explanation.
      feature_names: List of feature names.
      feature_types: List of feature types.
      name: User-defined name of explanation.
      selector: A dataframe whose indices correspond to explanation entries.
docstr_tok: ["Initializes","class",".","Args",":","explanation_type",":","Type","of","explanation",".","internal_obj",":","A","jsonable","object","that","backs","the","explanation",".","feature_names",":","List","of","feature","names",".","feature_types",":","List","of","feature","types",".","name",":","User-defined","name","of","explanation",".","selector",":","A","dataframe","whose","indices","correspond","to","explanation","entries","."]
code: def __init__(
      self,
      explanation_type,
      internal_obj,
      feature_names=None,
      feature_types=None,
      name=None,
      selector=None,
  ):
      """Initializes class.
  
      Args:
          explanation_type:  Type of explanation.
          internal_obj: A jsonable object that backs the explanation.
          feature_names: List of feature names.
          feature_types: List of feature types.
          name: User-defined name of explanation.
          selector: A dataframe whose indices correspond to explanation entries.
      """
  
      super(MorrisExplanation, self).__init__(
          explanation_type,
          internal_obj,
          feature_names=feature_names,
          feature_types=feature_types,
          name=name,
          selector=selector,
      )
  
imports: from ..api.base import ExplainerMixin
  from ..api.templates import FeatureValueExplanation
  from ..utils._explanation import gen_name_from_class, gen_global_selector
  from abc import ABC, abstractmethod
  import numpy
  from ..utils._clean_x import preclean_X
  from ..utils._unify_predict import determine_classes, unify_predict_fn
  from ..utils._unify_data import unify_data
label_desc: Use image node_id 1 to create a new MorrisExplanation object from inherited base classes: FeatureValueExplanation with example: obj = MorrisExplanation(explanation_type, internal_obj, feature_names, feature_types, name, selector)