class_docstr: Manager for generating causal analyses from a dataset.
class_docstr_tok: ["Manager","for","generating","causal","analyses","from","a","dataset","."]
docstr: Load the CausalManager from the given path.
  
  :param path: The directory path to load the CausalManager from.
  :type path: str
  :param rai_insights: The loaded parent RAIInsights.
  :type rai_insights: RAIInsights
  :return: The CausalManager manager after loading.
  :rtype: CausalManager
docstr_tok: ["Load","the","CausalManager","from","the","given","path",".",":","param","path",":","The","directory","path","to","load","the","CausalManager","from",".",":","type","path",":","str",":","param","rai_insights",":","The","loaded","parent","RAIInsights",".",":","type","rai_insights",":","RAIInsights",":","return",":","The","CausalManager","manager","after","loading",".",":","rtype",":","CausalManager"]
code: def _load(path, rai_insights):
      """Load the CausalManager from the given path.
  
      :param path: The directory path to load the CausalManager from.
      :type path: str
      :param rai_insights: The loaded parent RAIInsights.
      :type rai_insights: RAIInsights
      :return: The CausalManager manager after loading.
      :rtype: CausalManager
      """
      inst = CausalManager.__new__(CausalManager)
  
      # Rehydrate results
      all_causal_dirs = DirectoryManager.list_sub_directories(path)
      inst.__dict__["_results"] = []
      for causal_dir in all_causal_dirs:
          dm = DirectoryManager(
              parent_directory_path=path, sub_directory_name=causal_dir
          )
          causal_result = CausalResult.load(dm.get_data_directory())
          inst.__dict__["_results"].append(causal_result)
  
      # Rehydrate model analysis data
      inst.__dict__["_train"] = rai_insights.train
      inst.__dict__["_test"] = rai_insights.test
      inst.__dict__["_target_column"] = rai_insights.target_column
      inst.__dict__["_task_type"] = rai_insights.task_type
      inst.__dict__[
          "_categorical_features"
      ] = rai_insights.categorical_features
      inst.__dict__[
          "_feature_metadata"
      ] = rai_insights._feature_metadata
  
      return inst
  
imports: from pathlib import Path
  from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from econml.solutions.causal_analysis import CausalAnalysis
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai._data_validations import validate_train_test_categories
  from responsibleai._internal.constants import CausalManagerKeys, ListProperties, ManagerNames
  from responsibleai._tools.causal.causal_config import CausalConfig
  from responsibleai._tools.causal.causal_constants import DefaultParams, ModelTypes
  from responsibleai._tools.causal.causal_result import CausalResult
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai.utils import _find_features_having_missing_values, _measure_time
label_desc: Use image node_id 15 for calling the CausalManager obj's underlying member method code with example usage: obj._load(path, rai_insights) and returns: inst