code: def _compute_min_max_coeff(
      min_coeff: float,
      max_coeff: float,
      effect_strength_fraction: np.ndarray,
  ):
      max_coeff = effect_strength_fraction * max_coeff
      min_coeff = effect_strength_fraction * min_coeff
      return min_coeff, max_coeff
  
imports: import copy
  import logging
  import math
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  import scipy.stats
  import statsmodels.api
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import StandardScaler
  from tqdm.auto import tqdm
  from dowhy.causal_estimator import CausalEstimate
  from dowhy.causal_estimators.econml import Econml
  from dowhy.causal_estimators.linear_regression_estimator import LinearRegressionEstimator
  from dowhy.causal_estimators.regression_estimator import RegressionEstimator
  from dowhy.causal_identifier.identified_estimand import IdentifiedEstimand
  from dowhy.causal_refuter import CausalRefutation, CausalRefuter, choose_variables
  from dowhy.causal_refuters.evalue_sensitivity_analyzer import EValueSensitivityAnalyzer
  from dowhy.causal_refuters.linear_sensitivity_analyzer import LinearSensitivityAnalyzer
label_desc: Use image node_id 2 for calling a global function with example usage: _compute_min_max_coeff(min_coeff, max_coeff, effect_strength_fraction) and returns: min_coeff,  max_coeff