code: def filter_to_used_features(df, tree):
      """Filters the DataFrame to only include features used in the tree.
  
      :param df: The DataFrame to filter.
      :type df: pandas.DataFrame
      :param tree: The tree to get the features from.
      :type tree: dict
      :return: The filtered DataFrame.
      :rtype: pandas.DataFrame
      """
      features = tree[CACHED_SUBTREE_FEATURES]
      features = features.union({PRED_Y, TRUE_Y, DIFF})
      return df[list(features)]
  
imports: import logging
  import numbers
  from enum import Enum
  import numpy
  import pandas
  from lightgbm import Booster, LGBMClassifier, LGBMRegressor
  from sklearn.metrics import mean_absolute_error, mean_squared_error, median_absolute_error, r2_score
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import DIFF, LEAF_INDEX, METHOD, PRED_Y, ROW_INDEX, SPLIT_FEATURE, SPLIT_INDEX, TRUE_Y, CohortFilterMethods, Metrics, ModelTask, TreeNode, error_metrics, f1_metrics, metric_to_display_name, precision_metrics, recall_metrics, regression_metrics
  from erroranalysis._internal.metrics import get_ordered_classes, metric_to_func
  from erroranalysis._internal.process_categoricals import process_categoricals
  from erroranalysis._internal.utils import is_spark
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 11 for calling a global function with example usage: filter_to_used_features(df, tree) and returns: df