code: def _generate_confounder_from_residuals(c1, c2, d_y, d_t, X):
      """
      This function takes the residuals from the treatment and outcome model and their coefficients and simulates the intermediate random variable U by taking
      the row wise normal distribution corresponding to each residual value and then debiasing the intermediate variable to get the final variable.
  
      :param c1: coefficient to the residual from the outcome model
      :type float
      :param c2: coefficient to the residual from the treatment model
      :type float
      :param d_y: residuals from the outcome model
      :type list
      :param d_t: residuals from the treatment model
      :type list
  
      :returns: The simulated values of the unobserved confounder based on the data
      :type pandas.core.series.Series
  
      """
      U = []
  
      for j in range(len(d_t)):
          simulated_variable_mean = c1 * d_y[j] + c2 * d_t[j]
          simulated_variable_stddev = 1
          U.append(
              np.random.normal(
                  simulated_variable_mean, simulated_variable_stddev, 1
              )
          )
  
      U = np.array(U)
      model = sm.OLS(U, X)
      results = model.fit()
      U = U.reshape(
          -1,
      )
      final_U = U - results.fittedvalues.values
      final_U = pd.Series(U)
  
      return final_U
  
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 6 for calling a global function with example usage: _generate_confounder_from_residuals(c1, c2, d_y, d_t, X) and returns: final_U