code: def describe_all_rules(self):
      self._check_is_fitted()
      coverage = self._predict_overlap_support(self.X).mean()
      return_str = "SUMMARY:\n"
      return_str = f"Rules cover {coverage:.1%} of all samples\n"
      if not self._support_only:
          return_str += (
              f"Overall, {self.raw_overlap_set.mean():.1%} of samples meet the criteria for inclusion in the overlap set, \n"
              "defined as (a) being covered by support rules and having propensity\n"
              f"score in ({self.overlap_eps:.2f}, {1 - self.overlap_eps:.2f})\n"
          )
          true_positive = self.overlap_indicator * self.raw_overlap_set
          overlap_coverage = (
              true_positive.sum() / self.raw_overlap_set.sum()
          )
          return_str += f"Rules capture {overlap_coverage:.1%} of samples which meet these criteria\n"
      # NOTE: The original paper implements both DNF and CNF rules, but for simplicity, this code only implements DNF rules
      return_str += "\nHow to read rules: The following rules are given in Disjuntive Normal Form, \n"
      return_str += "a series of AND clauses (e.g., X and Y and Z) joined by ORs. Hence, if a sample \n "
      return_str += "satifies any of the clauses for the support rules, it is included in the support, \n"
      return_str += "and likewise for the overlap rules.\n"
      return_str += "\nDETAILED RULES:\n"
      return_str += self.describe_support_rules()
      return_str += self.describe_overlap_rules()
      return return_str
  
imports: from dataclasses import asdict, dataclass
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  from sklearn.base import BaseEstimator
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import GridSearchCV, cross_val_predict
  from dowhy.causal_refuters.overrule.ruleset import BCSRulesetEstimator
  from dowhy.causal_refuters.overrule.utils import fatom
label_desc: Use image node_id 7 for calling the OverruleAnalyzer obj's underlying member method code with example usage: obj.describe_all_rules() and returns: return_str